Bureau of Soils and Water Management
Copyright ©2013
ISBN# 978-971-0583-15-7
APPLICATION OF STABLE
ISOTOPES TO THE ASSESSMENT
OF POLLUTION LOADING FROM
VARIOUS SOURCES IN THE
PAMPANGA RIVER SYSTEM INTO
THE MANILA BAY, PHILIPPINES
December 2013
Funded by the Environmental Management Bureau, Department of
Environment and Natural Resources
Office of the Director
Environmental
Management Bureau
Visayas Avenue, Diliman
Quezon City, Philippines
MESSAGE
Water is a basic source without substitute. The Environmental Management Bureau (EMB)
of the Department of the Environment and Natural Resources (DENR), as the lead steward
in water quality management welcomes the opportunity to support the development and
generation of a science-based study that is valuable for area-based planning and
management.
In the light of the continuing mandamus to clean up, rehabilitate and restore the Manila
Bay, we at the DENR family truly appreciate the cooperation and support of various
institutions and fellow mandamus agencies. We are delighted by the partnership with the
Bureau of Soils and Water Management of the Department of Agriculture and Philippine
Nuclear Research Institute of the Department of Science and Technology for pursuing a
science-based approach towards identification of various sources of pollution and
determination of the contribution to receiving bodies of water.
Together, let us continue and intensify our efforts towards the common goal of improving
the state of Manila Bay.
Mabuhay!
ATTY. JUAN MIGUEL T. CUNA, CESO IV
Director
i
Office of the Director
Manila Bay Coordinating
Office
Visayas Avenue, Diliman
Quezon City, Philippines
MESSAGE
I would like to extend my sincerest congratulations to the officers and employees of the
Department of Environment and Natural Resources (DENR), Bureau of Soils and Water
Management (DA-BSWM) and the Philippine Nuclear Research Institute (PNRI) for
spearheading the timely conduct of study titled, “Application of Stable Isotopes to the
Assessment of Pollution Loading from Various Sources in the Pampanga River System into
the Manila Bay, Philippines”.
Such endeavour is a demonstration of a successful collaboration amongst various agencies
driven by a unified goal of restoring the Manila Bay and the abutting river systems. The
application of stable isotope techniques is considered as one of our forefront innovations, as
the technology is capable of tracing the precise sources of pollutants on the receiving body
of water. This will be an effective proposal for us to effectively manage, enforce and
monitor the prime sources of pollution.
The results generated from this course of action have been an effective medium for more
collaborative efforts to take place for the rehabilitation of the Pampanga River System. This
achievement has also exemplified an ideal model where hard science form part as a vital
component for policy-decision making. I am glad that the DA-BSWM, headed by Dr. Silvino
Q. Tejada has played an enabling role for this partnership to take place. Atty. Juan Miguel T.
Cuna of the DENR-EMB and Dr. Alumanda M. Dela Rosa of the DOST-PNRI should also be
acknowledged for the necessary inputs which guaranteed the success of this project.
Lastly, I would like to commend the staff and partners of the research team, headed by Dr.
Edna D. Samar of the DA-BSWM for their untiring commitment. By all means, all these
success would not be possible without the paramount support of Hon. Ramon P. Paje
(DENR), Hon. Proceso J. Alcala (DA) and Hon. Mario G. Montejo (DOST). It is with great hope
that these partnerships would be sustained through the coming years. Indeed, there is still
hope with the tides.
Isang luntiang pagbati po sa ating lahat!
NOEL ANTONIO V. GAERLAN
Executive Director
ii
Office of the Director
Philippine Nuclear
Research Institute
Commonwealth Avenue, Diliman
Quezon City, Philippines
MESSAGE
The advantage of the application of nuclear techniques in scientific investigations in the
Philippines, particularly in the areas of agriculture, environment and water resources, has
steadily gained recognition in recent years through the unwavering efforts of the Philippine
Nuclear Research Institute and the Department of Science and Technology.
We welcome the opportunity to again demonstrate the utility of this technology in
addressing the environmental issues confronting the Manila Bay through this collaborative
project “Application of Stable Isotopes to the Assessment of Pollution Loading from
Various Sources within the Pampanga River Basin into the Manila Bay”, with the Bureau of
Soils and Water Management, Department of Agriculture (BSWM-DA).
Indeed the marine ecosystem is one of the country’s greatest natural resource but the
impact of human activity has led to the degradation of its environmental conditions. In
effect, a wide range of waste and discharge emerging from agricultural, industrial and
domestic activities contribute to the distribution of contaminants. To curb this, it is
imperative to apply environmental regulations which can only be effective if contaminant
distributions are clearly linked to known processes or sources. It is in this regard that
nuclear techniques can be most useful for providing a unique source of information for
identifying the source of contaminants and tracing their pathways in the environment.
We would like to express our appreciation to the BSWM-DA and the Manila Bay
Coordinating Office (MBCO) for choosing the PNRI as a partner in this endeavor. We hope
that the information generated from this study will be useful in framing cost effective
mitigation decisions and eventually lead to the restoration of the Manila Bay.
Mabuhay!
ALUMANDA M. DELA ROSA, Ph. D
Director
iii
Office of the Director
Bureau of Soils and Water
Management
Elliptical Road, Diliman 1100
Quezon City, Philippines
MESSAGE
Greetings!
My congratulations to the Bureau of Soils and Water Management and the Philippine
Nuclear Research Institute for this research report on “The Application of Stable Isotopes to
the Assessment of Pollution Loading from Various Sources in the Pampanga River System
into the Manila Bay, Philippines”. I would like to extend my sincere gratitude to the
Department of Environment and Natural Resources through the Environmental
Management Bureau for the financial assistance and technical support. Likewise, I am
deeply appreciative of the valuable contribution of the Manila Bay Coordinating Office in the
development and facilitation of this project.
In support to the “writ of continuing mandamus” issued by the Supreme Court, this research
is indeed timely and relevant to provide baseline information for the development of action
programs towards meeting the prescribed water quality standards of the Manila bay.
Again, I commend the men and women behind this research project as well as our partner
institutions. Together, we can make a difference.
SILVINO Q. TEJADA, CESO III
Director
iv
ACKNOWLEDGEMENT
The Bureau of Soils and Water Management (BSWM), is greatly indebted to Dr. Lee
Kheng Heng of the International Atomic Energy Agency (IAEA) and Mr. Rolland V. Rallos
during the early conceptualization of the proposal.
The untiring support from the Manila Bay Coordinating Office of Executive Director
Noel Antonio V. Gaerlan is well appreciated along with the help extended by Mesdames
Nilda Baling, Araceli Oradina and Floradema Colado during the project development. As
partners, the BSWM hopes to incessantly work with DENR-MBCO in harmony to optimize
efforts in providing the best management practices necessary for the rehabilitation and
sustainability of the Manila Bay System.
Moreover, the Bureau extends its sincerest gratitude to the Environmental
Management Office - Department of Environment and Natural Resources (DENR) under the
leadership of Atty. Juan Miguel T. Cuna for the full cooperation and funding assistance in the
conduct of this study and the provision of valuable information prerequisite to its
completion. Appreciation is extended to Engr. Nicanor Mendoza and Mr. Bobby Bataller, Jr.
for the technical support in the generation of sediment samples offshore of Manila Bay.
The valuable laboratory support from the following agencies are likewise recognized
in this study: IAEA, Vienna; GNS Laboratory, New Zealand; Philippine Coconut Authority
(PCA), Research and Analytical Services-Natural Sciences Research Institute of University of
the Philippines (UP-NSRI), National Institute of Geological Services of the University of the
Philippines (UP-NIGS) and Intertek Testing Service.
More importantly, the BSWM appreciates the partnership of the Philippine Nuclear
Research Institute (PNRI) of the Department of Science and Technology. Under the
leadership of Director Alumanda M. dela Rosa and Dr. Soledad S. Castaneda. They
generously shared their expertise and facilitated the completion of project outputs.
Lastly, the BSWM recognized the valuable support of Secretary Ramon P. Paje
(DENR), Secretary Proceso J. Alcala (DA) and Secretary Mario G. Montejo (DOST) and the
inputs from different agencies that were involved in the consultations, particularly the UPMarine Science Institute (MSI), Partnership in Environmental Management for Seas in East
Asia (PEMSEA) and the DA Regional Field Offices, attached Agencies and Bureaus.
v
Table of Contents
Page
Messages
i
Acknowledgement
v
List of Figures
vii
List of Map
viii
List of Tables
viii
Executive Summary
ix
I. Introduction
1
II. Objectives
1
III. Framework
1
IV. Methodology
2
V. Results and Discussions
4
VI. Summary and Recommendations
15
BSWM Technical Working Committee
17
PNRI Project Implementation Team
18
Attachment 1 – Watershed Approach to Surface Water Sampling and
Analysis
 Edna D. Samar, Mario B. Collado, Alan H. Anida and Perla P.
Estabillo
1-1
Attachment 2 – Sampling and Sample Preparation for Isotopic
Analyses
 Soledad S. Castañeda, Jennyvi D. Ramirez and Efren J. Sta.
Maria
2-1
Attachment 3 – Watersheds of the Pampanga River Basin,
Philippines: Water Quality and Pollution Loading
 Edna D. Samar, Mario B. Collado, Alan H. Anida, Andrew B.
Flores and Teodorico M. Fajardo
3-1
vi
Page
Attachment 4 – Nutrients and Heavy Metals Assessment in the
Pampanga River Basin, Philippines
 Edna D. Samar, Perla P. Estabillo, Mario B. Collado, Alan H.
Anida and Andrew B. Flores
4-1
Attachment 5 – Total and Fecal Coliform Bacteria Assessment in the
Pampanga River Basin, Philippines
 Marcelina J. Palis, Amy O. Yambot, Jacqueline S. Rojales,
Alma J.Gonzales, Digna R. Allag, Alan H. Anida, Mario B.
Collado and Edna D. Samar
5-1
Attachment 6 – Nitrogen and Oxygen Isotopes in Source Identification
of Nitrates in Water
 Soledad S. Castañeda, Jennyvi D. Ramirez, Efren J. Sta.
Maria and Edna D. Samar
6-1
Attachment 7 – Estimation of Pollutant Source Contribution to the
Pampanga River Basin Using Carbon and Nitrogen
Isotopes
 Soledad S. Castañeda, Jennyvi D. Ramirez and Efren J. Sta.
Maria, Mario B. Collado and Edna D.Samar
7-1
Attachment 8 – Assessment of Terrestrial and Marine Contribution to
the Nutrient Loading in Manila Bay Using Carbon and
Nitrogen Isotopes
 Soledad S. Castañeda, Jennyvi D. Ramirez, Efren J. Sta.
Maria and Edna D. Samar
8-1
List of Figures
1
2
3
4
Framework for the assessment of water quality and identification of
sources using stable isotopes
3
Daily nitrate loading within and nearby the Pampanga River Basin,
2012-2013
8
Annual nitrate loading within and nearby the Pampanga River Basin,
2012-2013
8
Annual loading of total phosphorous within and nearby the Pampanga
River Basin, 2012-2013
9
vii
List of Map
Page
1
Sub-watersheds of Pampanga River Basin, Philippines
3
List of Tables
1
Surface water quality in forestry areas and the origin of contamination
13
2
Surface water quality in croplands and the origin of contamination
13
3
Surface water quality in fishery and the origin of contamination
14
4
Surface water quality in livestock and poultry areas/ slaughter areas
and the origin of contamination
14
5
Surface water quality in domestic areas and the origin of
contamination
15
viii
EXECUTIVE SUMMARY
EXECUTIVE SUMMARY
I. Introduction
The Pampanga River Basin is critical to Philippine economy, providing
irrigation, water and power to Luzon especially Metro Manila. It contributes the most
to Manila Bay based on net water influx of 49 percent into the Bay (Jacinto, et al.,
1998). The National Water Quality Status Report (2005) has identified the
Pampanga River as one of the rivers with poor water quality. Bay-wide monitoring
undertaken by PEMSEA (2006) revealed nitrate & orthophosphate concentrations
above the ASEAN marine water quality criteria of 0.06 and 0.015mg/L, respectively.
The pollution of the Bay is associated to loadings from agriculture, industry
and services sectors but there are no conclusive and direct evidences to identify the
origins and contributions. In 2008 and 2011, the Supreme Court ordered mandamus
agencies to plan and implement clean up, rehabilitation and restoration of the Bay
into class SB. Recent efforts of the DENR and other mandamus agencies are
focused on the water quality monitoring offshore and neighboring the Bay. Water
quality upstream of the Bay is wanting. Moreover, the origins of pollution have to be
identified for area-based resource management actions.
Nuclear analytical techniques are tools that could identify through spectral
signature, the sources of nutrient loading. Thus, Miller, et al. (2011) used stable
isotopes to identify sources of pollution in Manila Bay. The study reported that the
nitrogen stable isotopes were less clear due to the multiple sources of N from
different river systems with varying nutrient inputs. With this limitation, the use of
multiple stable isotopes is deemed vital and thus applied in this study.
II. Objectives
The study focuses on the Pampanga River Basin as prototype for the other
watersheds of Manila Bay. Specifically, the study intends to:
a) Identify and trace source(s) of nutrients in the Manila Bay using nuclear
techniques;
b) Quantify nutrients loaded from source(s) into the Manila Bay; and
c) Provide recommendations for various related purposes.
III. Framework
The framework, shown in Figure 1, guided the assessment of surface water
quality considering different parameters and criteria, and the identification of sources
of pollution and their contribution based on references values.
1
SUB-WATERSHED:
Pampanga River Basin
Sampling and Bio-physico-chemical analyses
Water
Sediment
Isotopic Analyses
Water
Solid (sediment,
biota)
Biota
INPUTS
INPUTS
Criteria
O
U
T
P
U
T
S
Water quality, sources of
pollution & contribution
•Isotopic signature / reference
values (C, N, O, H)
•Nutrients
•Heavy metals
•Coliform
Figure 1. Framework for the assessment of surface water quality and
identification of sources using stable isotopes
IV. Methodology
The study area is subdivided into three major sub-basins, namely: 1) Main
Pampanga River (north and central section), 2) Angat River (eastern Sierra Madre
Mountain), and 3) the western section consisting of Pasig-Gumain, Pasig-Potrero
River network. The Main Pampanga River Basin was further sub-divided into 11 subwatersheds presented in Map 1. Attachment 3 provides the details of the different
sub-watersheds.
This study utilized the watershed approach for strategic sampling and analysis
of different parameters. A total of 38 sampling sites were identified within and around
the watershed to represent non-point and point sources of pollutants. All samples are
geo-referenced and documented. Attachment 1 provides the protocol for the
watershed delineation, sampling and analysis.
The multiple isotope analyses is useful to identify and trace through spectral
signature the origin of nutrient loading (provide the scientific basis for identifying the
origin of nutrient loading from multiple sources and determine their specific
contribution). Hence, δ15N, δ13C, δ2H and δ18O in water, plants and sediments were
used to indicate their sources (e.g. manure or fertilizers). The protocol for collecting
samples for isotopic analysis is provided in Attachment 2.
A total of 14 parameters were evaluated to assess the surface water quality of
the Pampanga River Basin considering the DENR DAO 90-34, ASEAN marine water
2
quality criteria and Bloom’s (n. d.) prescribed level for phosphorous. Attachment 3
presents the physico-chemical parameters, namely: temperature, pH, electrical
conductivity, turbidity, total dissolved solids, oxidation reduction potential, dissolved
oxygen, salinity. Attachment 4 discusses the seven toxic heavy metals in water
particularly lead, chromium, cadmium, arsenic, mercury, cobalt and nickel including
the nutrients (nitrate, phosphorous) loaded into the Bay. Moreover, Attachment 5
presents two biological parameters (total and fecal colliforms).
Map 1. Sub-watersheds of Pampanga River Basin, Philippines
3
V. Results
A. State of surface water quality within the Pampanga River Basin
The surface water investigated traverses 249.2 km from the head water at
Banga, Caranglan, Nueva Ecija down to Sapang Makawayan, Masantol-Macabebe,
Pampanga which is about 0.8 km from the river mouth, passing directly through ten
sampling points along the Pampanga River.
Surface water quality was assessed in terms of the physico-chemical and
biological parameters and these are discussed below.
1. Physico-chemical parameters
Eight physico-chemical parameters were gathered using multi-parameter
water checker, namely: temperature, pH, electrical conductivity, turbidity, total
dissolved solids, oxidation reduction potential, dissolved oxygen, and salinity. The
pH, dissolved oxygen and total suspended solids were assessed considering the
criteria from the DAO 90-34.
The pH of the water collected from all the sites ranged from 3.64 to 7.77.
Twelve of them had pH values below that prescribed by the DAO 90-34 for class B
water (6.5 -8.5) and that of class SB water (6.0 – 8.5). The lowest pH of 3.64 was
observed in San Ildefonso, Bulacan where effluents from slaughter house flow to the
creek where water was sampled. Acidic pH value was also observed at Barangay
San Vicente, Gapan, San Leonardo, Nueva Ecija. The highest pH value was
observed at Coronel River between Palayan City and Bongabon,Nueva Ecija.
The DAO 90-34 required 5 mg/L as minimum dissolved oxygen (DO). Along
the Pampanga River, all sampled sites have met this minimum requirement. The
highest DO value of 50 mg/L was recorded in two sites - San Antonio, Nueva Ecija
and Barangay Garay, Angat, Bulacan. Notably, a fishpond (site D) located at
Barangay Santo Tomas, Sasmuan, Pampanga had a DO of 4.24 mg/L which is not
favorable for aquatic and other organism needing oxygen.
Total suspended solids (TSS) in all sites during the wet and dry seasons are
less than 1 mg/L which is below the DAO 90-34 criterion for class A (50mg/L).
2. Heavy metals in water
The concentrations of heavy metals in water particularly lead, arsenic,
chromium, cadmium, mercury, cobalt and nickel are compared with the DAO 90-34
maximum limits for these metals in Class C and Class SB waters. Results showed
that 22 sites passed the allowable limit for lead (0.05 mg/L), arsenic (0.05 mg/L),
chromium (0.10 mg/L) and cadmium (0.01 mg/L). Seven sites, mostly upstream of
the watersheds exceeded the said criteria in one season. These sites are located
within Nueva Ecija, particularly:
4





Site 1 - Barangay Bunga, Carranglan, Nueva Ecija (249.2 km from river
mouth)
Site 2 - Baluarte Bridge,Barangay R. Padilla, Carranglan, Nueva Ecija
(238.6 km)
Site 3 - Pantabangan Dam outlet, Barangay Sampaloc, Pantabangan,
Nueva
Ecija (208.6 km)
Site 4 - Gen Luna Bridge, Barangay Mayapyap, Cabanatuan City (139.9
km)
Site 9 - Animal Stockfarm, Barangay Nazareth, Gen Tinio, Nueva Ecija
(158.7 km)
Considering the concentrations of heavy metals in water upstream of
Pampanga River, lead is about eight times the acceptable criterion of 0.05 mg/L,
arsenic is about seven times the acceptable criterion of 0.05 mg/L, cadmium is about
36 times the acceptable criterion of 0.01 mg/L, chromium is almost four times the
acceptable criterion of 0.10 mg/L. The high concentration of these heavy metals is
attributed to small mining operations in Nueva Ecija. Site 19 at Barangay Catmon,
Santa Maria, Bulacan also showed concentrations above the allowable criteria for
these four heavy metals during the wet season. In the dry season, all observed
values for these heavy metals were within the allowable criteria.
3. Nutrients in water
The water samples taken from the different sampling sites revealed nitrate
and phosphorous loading from Pampanga River into Manila Bay. The laboratory
analysis showed the presence of nitrate as NO3-1 in water throughout the 249.2 km
stretch of Pampanga River. Nitrate traverses 12 sampling points before reaching the
downstream passing through tributaries of the Coronel River, Peñaranda River, Rio
Chico River, San Miguel River and Maasin River.
Nitrate ranged from 0.05 to 1.94 mg/L during the wet season and 0.02 to 1.69
mg/L during the dry season. All nitrate concentrations are within the allowable limit of
10mg/L for Class C (DENR, DAO 90-34). However, in almost all sites, nitrate
concentrations exceed the Asian water quality criterion of 0.06 mg/L. With
concentration of 0.42 mg/L near the river mouth, this shows that Pampanga River
contributes to nitrate pollution beyond the allowable limits of 0.06 mg/L during the
wet season. Nitrate discharge during the dry season is within the allowable limit for
the ASEAN marine water quality.
The Pampanga River contributed directly to the phosphorous loading into the
Bay considering concentrations near the river mouth at 0.67 and 0.09 ppm during the
wet and dry seasons, respectively. As Bloom (n. d.) pointed out, concentration of
more than 0.02 ppm accelerate algal growth. The ASEAN marine water quality
criterion is 0.015 mg/L for organophosphate.
From Arayat down to San Luis and Apalit up to Masantol-Macabebe,
Pampanga, total phosphorous showed increasing concentration from 0.30 to 0.67
ppm during the wet season and from 0.5 to 0.9 ppm during the dry season, indicating
5
that these areas towards the river mouth contribute greatly to discharge of
phosphorous into the Bay. Along the Pampanga River, only site 3 which is located at
Pantabangan Dam outlet, Barangay Sampaloc, Pantabangan, Nueva Ecija showed
TP below 0.02 ppm in both wet and dry seasons.
4. Colliforms bacteria
Two parameters - total and fecal colliforms were the basis of the biological
assessment. The density of the total and fecal coliform bacteria varied widely by
location and time of sampling.
For the wet season, four sites exceeded the allowable limit of 1,000 MPN/100
ml for total colliform based on the DENR, DAO 90-34. In the same period, three sites
exceeded the allowable limit of 200 MPN/100 ml for fecal colliform. The water
discharge near the river mouth of Pampanga River showed discharge to Manila Bay
of total and fecal colliform within the allowable criteria even if some sites exceeded
the prescribed limits for SB category. Critical sites are Masantol proper, (Masantol,
Pampanga - site 24) and
Pampanga River, Barangay Sagrada (Masantol,
Pampanga - site 26), which are just 15 km and 8.9 km from the river mouth with total
colliform of 16,000 and 1,950 MPN/100 ml, respectively. No fecal colliform were
observed in these sites, indicating that sources of colliform are not directly from
human/ animal feces. These two sites are associated to fisheries being the
dominant contaminant and domestic as the associated contaminant. Also, the former
result is comparable to that of site C (San Ildefonso, Bulacan) which is point source
for piggery farm.
For the dry season, only eight out of 25 sites passed the allowable criterion for
total colliform and 11 passed the limit for fecal colliform. So far, three sites located
upstream have total fecal colliform within the acceptable level. Notably, high levels of
total and fecal colliform were observed near the river mouth particularly Masantol,
Pampanga. Almost all point sources exhibited high levels of total and fecal colliform
during the dry season.
5. Surface water quality rating
A water body must meet all the criteria of each applicable parameter 100
percent of the time to maintain its designated classification. About 0.8 km from the
river mouth, water draining into the Bay passes the criteria for pH, DO and TSS.
However, water influx from Pampanga River contained nitrates and phosphorous
beyond the allowable levels (DAO 90-34 and ASEAN marine water quality criteria).
Moreover, values of fecal colliforms exceeded the safe level of 200 MPN/100 ml
during the dry season. For two seasons, concentrations of heavy metals near the
Bay were within the criteria (DAO 90-34) even if high concentrations were noted
upstream of the Pampanga River Basin.
Overall, the Pampanga River obtained a “failed” rating with values for some
chemical and biological parameters exceeding the criteria. It remains in poor state
based on discharged water into the Manila Bay containing nitrates, phosphorous,
heavy metals and colliforms. This results confirmed earlier study undertaken in 2005.
6
B. Nutrient Loading
Daily and annual loading of nitrate in water at the different sampling sites are
presented in Figures 1 and 2. At the nearest sampling point, which is about 8.9 km
from the Bay (site 26 – Barangay Sagrada, Masantol, Pampanga), annual nitrate
load is estimated at 2,849 metric tons. This amount exceeded the allowable loading
for class SB based on the ASEAN water quality criterion. The top five major
contributors to nitrate loading are identified in the following locations:
a)
b)
c)
d)
e)
Site 16 – Apalit, Pampanga
Site 10 – Arayat, Pampanga
Site 6 – Jaen, Nueva Ecija
Site 7 – San Isidro, Nueva Ecija
Site 4 – Mayapyap, Cabanatuan City.
Total phosphorous loading into the Bay is estimated at 358 metric tons with
leading contributors, as follows:
a) Site 16 – Apalit, Pampanga
b) Site 12 - San Luis, Pampanga
c) Site 25 – San Pedro, Sasmuan, Pampanga
7
Nitrate in water (mt/yr)
Dumpsite, Cabanatuan City
Wet season
Dry season
Sagrada, Masantol, Pampanga
San Pedro, Sasmuan, Pampanga
Masantol, Pampanga
Barangay Catmon, Santa Maria, Bulacan
Poblacion, Guiguinto, Bulacan
Apalit, Pampanga
Garay, Angat, Bulacan
Bahay Pari, Candaba, Pampanga
San Luis, Pampanga
NIA Dam, San Miguel, Bulacan
Arayat, Pampanga
Gapan-San Leonardo, Nueva Ecija
San Isidro, Nueva Ecija
Jaen, Nueva Ecija
Barangay Mayapyap, Cabanatuan City
,Barangay Sampaloc , Pantabangan, Nueva Ecija
Barangay R. Padilla, Carranglan, Nueva Ecija
Barangay Bunga, Carranglan, Nueva Ecija
Piggery-chicken farm, San Jose Del Monte City
Slaugther house, San Ildefonso, Bulacan
Piggery Farm, San Ildefonso, Bulacan
Nitrate (kg/day)
20,000
15,000
10,000
5,000
0
sampling sites
Asian criterion of 0.06 mg/L
Figure 2. Daily nitrate loading within and nearby the Pampanga River Basin, 2012-2013
4,000
3,000
2,000
1,000
-
sampling sites
Figure 3. Annual nitrate loading within and nearby the Pampanga River Basin, 2012-2013
8
400
350
TP (mt/yr)
300
250
200
150
100
50
Sagrada, Masantol, Pampanga
Masantol, Pampanga
San Pedro, Sasmuan, Pampanga
Barangay Catmon, Santa Maria, Bulacan
Apalit, Pampanga
Poblacion, Guiguinto, Bulacan
Garay, Angat, Bulacan
San Luis, Pampanga
Bahay Pari, Candaba, Pampanga
Arayat, Pampanga
NIA Dam, San Miguel, Bulacan
Gapan-San Leonardo, Nueva Ecija
Jaen, Nueva Ecija
San Isidro, Nueva Ecija
Barangay Mayapyap, Cabanatuan City
Barangay R. Padilla, Carranglan, Nueva Ecija
,Barangay Sampaloc , Pantabangan, Nueva Ecija
Barangay Bunga, Carranglan, Nueva Ecija
Slaugther house, San Ildefonso, Bulacan
Piggery-chicken farm, San Jose Del Monte City
Dumpsite, Cabanatuan City
Piggery Farm, San Ildefonso, Bulacan
0
sampling sites
Figure 4. Annual loading of total phosphorous within and nearby the Pampanga River Basin, 2012-2013
C. Source Identification of Nitrates in Water
The basic problem in controlling nutrient loads into the Manila Bay is the
difficulty to distinguish among contributions from natural sources and various point
and non-point N sources, such as fertilizers, animal waste, and sewage. Identifying
the source of N in downstream reaches of surface water, using chemical properties
alone, is complicated because, generally, N compounds are not conservative, thus
are not ideal for use as tracers. This study made use of the unique diagnostic
capability of stable isotope techniques to trace the various anthropogenic inputs of
nitrogenous compounds in the Pampanga River Basin. The multi-isotope approach
was used because nitrogen isotopes alone have been shown to be inadequate in
providing definite signatures due to overlapping signals and changes in the isotopic
signal with denitrification in aquatic environments. Thus, the isotopes of N and O in
dissolve nitrate, O and H in water, and C and N in particulate organic matter (POM),
plant tissues, and top soil, were determined.
The development of sufficiently sensitive and accurate mass spectrometers
has made possible the detection of differences in chemical as well as physical
behavior of so-called isotopic molecules or isotopic compounds, i.e., of molecules
that contain different isotopes of the same element. The differences in physical and
chemical properties of isotopic compounds are brought about by mass differences of
the atomic nuclei. This results in the fractionation of the heavy and light isotope (eg.,
9
14
N and 15N in nitrogen and 16O, 17O, and 18O in oxygen, 12C and 13C in carbon)
which occurs as a change in isotopic composition by the transition of a compound
from one state to another or into another compound. Isotope ratio analysis involves
precise measurement, usually by mass spectrometry of the less abundant heavy
isotope to the more abundant light isotope, (e.g., 15N/14N, 18O/16O). This ratio (R) is
reported relative to the isotopic ratio of a reference standard. In the case of nitrogen,
the reference standard is atmospheric gas nitrogen (N2) for oxygen, the Vienna
Standard Mean Ocean Water (VSMOW). The isotopic composition is expressed in
terms of the isotopic ratio delta value, δ, defined as
δ={ [Rsample/ Rreference] – 1} x 1000
where δ is reported in ‰ (per mil). For the nitrogen isotopes, (15N/14N), δ 15N is used;
for 18O/16O, the notation is δ 18O, and for carbon isotopes, δ 13C.
The extent of isotope fractionation during synthesis and transformation
of organic compounds leaves isotopic fingerprint that can provide clues for the
identification of sources, transformation reactions, and sinks of organic compounds
in the environment.
Fractionation mechanisms for nitrogen isotopes in nitrogenous compounds
include volatilization of NH3(g) after ammonification, conversion of ammonium to
nitrate during nitrification, and conversion of nitrate to N 2(g) during denitrification.
The coupled δ 15N - δ 18O approach was applied in the isotopic determination of
nitrates in streams, effluent and leachates from point and non-point sources from
several land use areas, namely domestic, croplands, livestock, fishery, and forestry.
In most of these land use areas, the nitrate concentrations in the fluids collected are
lower than 2 mg/L. Nitrate is highest in the domestic dominant land use areas with
concentrations reaching as high as 60 mg/L in the wet season and 500 mg/L during
the dry season. Sewage input and other anthropogenic activities are the two main
factors impacting these domestic dominant areas. The lower concentration of nitrate
in the wet season is attributed to dilution by precipitation which is relatively low in
nitrate and to lower rate of nitrification.
The 15N composition of nitrate in point sources varied among the different land
use areas and also between seasons. The variation between seasons is attributed to
the difference in the degree of microbial degradation and to the rate of evaporation.
The isotopic signatures obtained indicate the potential for identifying the different
sources, although some overlap between the signature of cropland and domestic
land use exist.
The 15N composition of non –point sources in the wet season
showed a large variability in the values for cropland affected areas which indicates
mixing of the different N sources.
The 18O in nitrate provided additional information that is useful in the
resolution of signatures of the different sources. The signatures of the sources in the
wet season were effectively resolved with minimum overlap between the values for
cropland and domestic sources. In the dry season, the overlap between domestic
and cropland sources are adequately resolved.
10
The analysis obtained from dual isotope approach yielded the following
signatures for the different sources: livestock and fishery -> inorganic fertilizer;
croplands -> soil N; domestic -> soil N and sewage/septic. The isotopic composition
of non-point sources generally indicated the mixing of cropland and domestic
sources of N. The signature coming from livestock activity which consistently
exhibited that of synthetic nitrate fertilizer indicates a direct input from such sources
in the river system, and not from nitrification which is that exhibited by croplands.
D. Pollutant source contribution
Isotopic analyses of the N-source materials such as particulate organic matter
(POM), plant tissues, and top soil were conducted to identify the sources of the
nutrient loads and estimate the percentage contributions of these anthropogenic
sources by using stable isotopes of δ13C and δ15N. Isotopic mass balance and
fractionation were used to estimate nutrient load contributed by multiple sources.
Similar to that found in nitrates, the δ15N values in organic matter indicated the
potential to distinguish different N-sources, although the isotopic composition of
cropland and domestic sources may cause some overlap. The use of carbon isotope
was useful in resolving this overlap.
For carbon, the most important factor affecting its isotopic composition in
natural compounds in the biosphere is the effect of absorption and photosynthetic
fixation of CO2 by plants. Thus, the isotopic composition of upland trees is distinct
from that of tropical grasses and corn. In animals, diet is the primary determinant for
the carbon isotopic composition. These characteristics of carbon isotopes allow the
differentiation between terrestrial and marine sources of pollution.
The combination of C and N isotopic determination in organic matter resulted
in a significant resolution between the signatures of human waste (sewage) and
animal waste (represented by livestock) and between cropland and fisheries.
Correlation analysis showed that most of the samples reflect the contribution of
mixture of domestic waste and cropland, and to a lesser degree, of livestock. The
δ13C and δ15N values of the point and non-point sources in surface sediments
distinguished the signatures from livestock (animal manure), cropland and fishery.
Likewise, forest soil signature was distinct from that of cropland soil. In plant tissues,
the delineation of the isotopic signatures of the different sources was distinct.
In general, isotopic characterization of the different sources leads to the
conclusion that, indeed, the major land use areas within the Pampanga River basin,
such as cropland areas, domestic activities, and livestock, contribute in some ways
to the pollutant loading of the Pampanga River and eventually of the Manila Bay. The
relative contribution of these activities to the total nutrient load from the basin was
estimated using a three source – two-tracer isotope mixing model. The model
revealed that cropland sources generally contributed the most to pollutant loading
during the wet season, from 22% to 98%, while domestic waste contributed higher in
the dry season, from 55% to 65%
11
E. Terrestrial and marine contribution to pollution loading of Manila Bay
Carbon stable isotope ratios in surface sediments served as proxy of land use
change in the Pampanga River Basin and, in combination with C/N concentrations,
provided an insight on how these terrestrial anthropogenic sources affect and
contribute to the nutrient loading in Manila Bay. A two source – one isotope mixing
model, using δ13C values was used to determine the extent of terrestrial input in the
offshore marine environment where there are two known end members, the
terrestrial signature and the marine signature. Carbon stable isotope ratios from off
shore surface sediment samples collected by the Environmental Management
Bureau (EMB-DENR) were used together with the carbon stable isotope ratios in
surface sediments collected in this study. Assessment of the evolution of δ13C in
surface sediments from “ridge to reef” along the Pampanga River Basin showed that
even up to around 20 km to the coast, terrestrial influence was still significant.
Using the mixing model, terrestrial contribution from the different sources is as
follows: cropland, 27-100%, forestry, 12%, livestock, 37-93%, and fishery, 55-79%.
The relative contribution of this terrestrial input into the Manila Bay was estimated
from the isotopic composition of the off shore surface sediments. The mixing model
showed that 17- 30 % of the organic matter deposited in the Bay comes from
terrestrial activities from the Pampanga River basin, mostly from agriculture.
The nutrient loading from the Pampanga river basin mainly come from C 3
terrestrial vegetation although this signature is masked by that of algal growth,
probably promoted by the nutrient loading. However, the contribution is seen in the
signature of C3 soil and riverine materials.
F. Implications of Surface Water Quality to Intended/ Current Uses
To better understand the implication of surface water quality to intended/
current uses, wet season data were summarized for specific locations. Tables 1 to 5
provide a summary of the conditions of surface water for various purposes. The
tables show which parameters “failed” (red shade) and needs periodic monitoring,
and the parameters which “passed” (green shade) the criteria adopted in this study
(DAO 90-34 for heavy metals, ASEAN marine quality criterion for nitrate, Bloom
(n.d.) for phosphorous). Likewise, the origin of pollution is identified for each location
based on signatures from water, plant tissues and from particulate organic matter.
Manures (M) in the form of human (HW) and animal wastes (AW) are among the
specific origin of pollution aside from inorganic fertilizers and soil N. The final codes
represented in numbers are non-point sources of pollutants while those in letters are
point sources of pollutants.
Overall, surface waters for different purposes – forestry, croplands, fishery,
livestock and poultry and domestic uses do not meet the criteria as prescribed.
Concerned government agencies should ensure fitness of surface water to current
purposes. Considering danger to human health, periodic monitoring should be strictly
undertaken and appropriate measures be implemented. Proper solid and liquid
waste disposal should be enforced by the local government units.
12
Table 1. Surface water quality in forestry areas and the origin of contamination
Wet season sampling
Final Code
Site Location
Fecal Coliform, MPN/100 ml
Total Coliform, MPN/100 ml
11/26/2012
12/6/2012
1
15
Barangay Bunga, Carranglan, Nueva
Ecija
0
0
Upstream Bustos Dam, Barangay Garay, Angat,
Bulacan
0
1186
1.25
0
0.402
0.368
0.360
0.379
<LLD
Fail
0.49
0.02
0.015
<LLD
<LLD
<LLD
<LLD
Fail
Soil N
M(AW/HW)
M(AW/HW)
M(AW/HW)
Soil N
M(AW/HW)
Nitrate (NO3-1) in water, mg/L
TOTAL P in water, ppm
Lead (Pb) in water, mg/kg
Arsenic (As) in water, mg/kg
Cadmium (Cd) in water, mg/kg
Chromium (Cr) in water, mg/kg
Mercury (Hg) in water, mg/kg
Overall rating: Water Quality
Isotopic analysis:
Dissolved Nitrates
Particulate Organic Matter
Plant tissues
Surface Sediments
M(AW/HW)
Table 2. Surface water quality in croplands and the origin of contamination
Wet season sampling
Final Code
Site Location
Fecal Coliform, MPN/100 ml
Total Coliform, MPN/100 ml
Nitrate (NO 3-1 ) in water, mg/L
TOTAL P in water, ppm
Lead (Pb) in water, mg/kg
Arsenic (As) in water, mg/kg
Cadmium (Cd) in water, mg/kg
Chromium (Cr) in water, mg/kg
Mercury (Hg) in water, mg/kg
Overall rating: Water Quality
Isotopic analysis:
Dissolved Nitrates
Particulate Organic Matter
Plant tissues
Surface Sediments
11/27/2012
3
12/6/2012
11
Pantabangan Dam
outlet,Barangay
Sampaloc ,
Diversion Dam, Barangay
Pantabangan, Nueva Sabangan, San Miguel,
Bulacan
Ecija
310
130
800
76
11/14/2012
14
12/6/2012
15
Diversion Dam,
Upstream Bustos
Barangay Sabangan, Dam, Barangay
Bustos Bulacan
Garay, Angat, Bulacan
653
0
9000
1186
0.38
0.004
0.432
0.385
0.307
0.41
<LLD
0.73
0.03
<LLD
<LLD
<LLD
<LLD
<LLD
0.05
0.09
<LLD
<LLD
<LLD
<LLD
<LLD
0.49
0.02
0.015
<LLD
<LLD
<LLD
<LLD
Fail
Fail
Fail
Fail
Soil N
M (AW/HW)
M (AW/HW)
M (AW/HW)
Soil N
M (AW/HW)
Soil N
M (AW/HW)
Soil N
M (AW/HW)
M (AW/HW)
M (AW/HW)
13
Table 3. Surface water quality in fishery areas and the origin of contamination
Wet season sampling
Final Code
12/6/2012
G
Site Location
12/6/2012
H
12/6/2012
I
12/10/2012
D
Fishpond, Barangay
Santo
Tomas, Sasmuan, Pam
panga
Site 1, Navotas Site 2, Navotas Site 3, Navotas
Fish Port
Fish Port
Fish Port
172
233
186
Fecal Coliform, MPN/100 ml
0
Total Coliform, MPN/100 ml
2,600
7,833
16,000
230
Nitrate (NO 3-1) in water, mg/L
TOTAL P in water, ppm
Lead (Pb) in water, mg/kg
Arsenic (As) in water, mg/kg
Cadmium (Cd) in water, mg/kg
Chromium (Cr) in water, mg/kg
Mercury (Hg) in water, mg/kg
Overall rating: Water Quality
6.30
0.06
<LLD
<LLD
<LLD
<LLD
<LLD
10.00
0.04
<LLD
<LLD
<LLD
<LLD
<LLD
5.80
0.02
0.008
<LLD
<LLD
<LLD
<LLD
0.08
0.34
<LLD
<LLD
<LLD
<LLD
<LLD
Fail
Fail
Fail
Fail
M (AW/HW)
M (AW/HW)
Inorganic fert
M (AW/HW)
Inorganic fert
Inorganic fert
Isotopic analysis:
Dissolved Nitrates
Particulate Organic Matter
Plant tissues
boundary between
inorganic fert & M
(AW/HW)
Surface Sediments
Table 4. Surface water quality in livestock and poultry areas/ slaughter areas
and the origin of contamination
Wet season sampling
Final Code
Site Location
Fecal Coliform, MPN/100 ml
Total Coliform, MPN/100 ml
Nitrate (NO 3-1) in water, mg/L
TOTAL P in water, ppm
Lead (Pb) in water, mg/kg
Arsenic (As) in water, mg/kg
Cadmium (Cd) in water, mg/kg
Chromium (Cr) in water, mg/kg
Mercury (Hg) in water, mg/kg
Overall rating: Water Quality
Isotopic analysis:
Dissolved Nitrates
Particulate Organic Matter
Plant tissues
Surface Sediments
12/4/2012
C
Piggery Farm,
San Ildefonso,
Bulacan
12/4/2012
B
Slaugther house,
San Ildefonso,
Bulacan
12/3/2012
E
Piggery farm,
Barangay
Gayagaya, San
Jose Del Monte
City
11/27/2012
9
12/3/2012
19
Animal
Stockfarm,
Barangay
Barangay Catmon,
Nazareth, Gen Santa Maria,
Tinio, Nueva Ecija Bulacan
3316
16,000
66
3,136
1,570
8,333
76
76
0
1,693
0.52
1.20
<LLD
<LLD
<LLD
<LLD
<LLD
Fail
0.17
0.48
<LLD
<LLD
<LLD
<LLD
<LLD
Fail
1.05
1.25
0.069
<LLD
<LLD
<LLD
<LLD
Fail
0.17
0.27
0.421
0.375
0.374
0.356
<LLD
Fail
0.36
1.03
0.493
0.397
0.397
0.41
<LLD
Fail
Inorganic fert
M (AW/HW)
M (AW/HW)
Inorganic fert
M (AW/HW)
M (AW/HW)
M (AW/HW)
M (AW/HW)
Inorganic fert
M (AW/HW)
M (AW/HW)
boundary
between
inorganic fert &
M (AW/HW)
M (AW/HW)
14
Table 5. Surface water quality in domestic areas and the origin of contamination
Wet season sampling
Final Code
Site Location
Fecal Coliform, MPN/100 ml
Total Coliform, MPN/100 ml
Nitrate (NO 3-1) in water, mg/L
TOTAL P in water, ppm
Lead (Pb) in water, mg/kg
Arsenic (As) in water, mg/kg
Cadmium (Cd) in water, mg/kg
Chromium (Cr) in water, mg/kg
Mercury (Hg) in water, mg/kg
Overall rating: Water Quality
Isotopic analysis:
Dissolved Nitrates
Particulate Organic Matter
Plant tissues
Surface Sediments
11/27/12
A
12/10/2012
F
Dumpsite,
Barangay Valle Domestic site,
Cruz,
Diliman,
Cabanatuan
Quezon City
City
106
1753
12/11/2012
24
Masantol
proper,
Masantol,
Pampanga
26
0
0.63
0.30
0.410
0.365
0.366
0.399
<LLD
Fail
59.70
0.17
<LLD
<LLD
<LLD
<LLD
<LLD
Fail
0.51
0.22
<LLD
<LLD
<LLD
<LLD
<LLD
Fail
Soil N
Soil N
boundary
between
inorganic fert &
M (AW/HW)
Soil N
M (AW/HW)
M (AW/HW)
12/10/2012
25
12/11/2012
26
12/11/2012
27
near Manila Bay,
San Pedro
Pampanga
Sapang
River, Barangay River, Barangay
Makawayan,
San Pedro,
Sagrada,
MasantolSasmuan,
Masantol,
Macabebe,
Pampanga
Pampanga
Pampanga
0
156
0
23
1213
8620
16000
106
0.05
0.73
0.42
0.23
0.10
0.67
<LLD
<LLD
<LLD
<LLD
<LLD
<LLD
<LLD
<LLD
<LLD
0.021
<LLD
<LLD
<LLD
<LLD
<LLD
Fail
Fail
Fail
Soil N
Soil N
M (AW/HW)
Inorganic fert Inorganic fert
M (AW/HW)
M (AW/HW)
Inorganic fert
M (AW/HW)
VI. Summary and Recommendation
The study proved the usefulness of the watershed approach for strategic
sampling and analysis in order to identify critical areas contributing to pollution
loading into the Manila Bay. It identified five critical locations for nitrate and three for
phosphorous where major contributions to loading occur and where area-based
strategic action plans can be pursued.
Estimated annual nitrate and phosphorous loadings into the Bay (8.9 km from
Manila Bay - Site 26- Barangay Sagrada, Masantol, Pampanga) are 2,849 and 358
metric tons, respectively. Nitrate loading exceeded the allowable loading for class SB
based on the ASEAN marine water quality criterion while phosphorous loading is
above threshold for limited algal growth.
In general, the surface water quality of Pampanga River remains poor
considering laboratory analyses from two seasons covering 14 parameters physical, biological, nutrients and heavy metals.
In the light of the above findings on pollution loadings and water quality, a
review of the DAO 90-34 may be necessary to harmonize with international criteria
and to update classification of water bodies considering not only intended uses but
impact to receiving body of water. Also, periodic monitoring would be essential and
area-based action plans be developed, with strong LGU participation and support
from sectoral groups.
15
The use of multiple isotopes is useful to identify various sources of pollution.
The model revealed that domestic and cropland sources contribute dominantly to the
nutrient inputs in Pampanga River. These observations have significant implications
for the management of increasing nutrient input in Pampanga River Basin and in MB.
The differences in the distribution of nutrients and terrestrial input suggest that
main the main sources depend on the land use pattern of the catchments (Chang, et
al. 2009). Based on the estimated NO3 and TP loading to the Pampanga River
Basin, management efforts towards substantial reduction in the loading is vital to
meet local and international criteria.
For future studies, off-shore water sampling for isotopic analyses would be
vital complementary to sediment and biotic samples.
The non-conservative nature of the isotopic compositions of nitrogen as it
undergoes different transformations in the terrestrial and aquatic environment poses
a challenge in attributing its sources. Conducting more elaborate sampling and
thorough characterization of known nitrate sources in the watershed has the
potential of more quantitative estimation of nutrient load. Commercial fertilizers and
feeds used locally should be characterized isotopically for better source
identification.
16
BSWM PROJECT IMPLEMENTATION TEAM
Core Advisory Team:
Dir. Silvino Q. Tejada
Asst. Dir. Wilfredo E. Cabezon
Project Leader:
Dr. Edna D. Samar
Asst. Project Leader:
Engr. Mario B. Collado
Field Assessment and Sample Collection
Team:
Engr. Mario B. Collado
Mr. Alan H. Anida
Mr. Juancho F. Roque
Mr. Renato S. Gonzales
Sample Preparation (water, soil sediment and
biota) and Laboratory Analysis Team:
Ms. Perla P. Estabilo
Ms. Elvira B. Bayalas
Ms. Bernardina I. Daguio
Ms. Marcelina J. Palis
Ms. Jacqueline S. Rojales
Ms. Amy O. Yambot
Ms. Alma J.Gonzales
Database Development and Documentation
Team:
Mr. Andrew B. Flores
Mr. Teodorico M. Fajardo
Ms. Frances C.Villa Juan
Ms.Josefina L. Creencia
SWAC Region 3 Coordinators:
Mr. Crisostomo V. Mamorbor
Ms. Clarita D. Bacatio
Administrative Support Team:
Ms. Ester S.Santos
Mr. Rodrigo I. Ablaza
Ms. Narcisa D. Ramis
Mr. Edgar P. Santos
Ms. Nancy C. De Sagun
17
PNRI PROJECT IMPLEMENTATION TEAM
Adviser:
Dir. Alumanda M. Dela Rosa
Project Leader:
Dr. Soledad S. Castañeda
Asst. Project Leader:
Mr. Efren J. Sta. Maria
Members:
Mr. Roland V. Rallos
Mr. Norman DS. Mendoza
Ms. Jennyvi D. Ramirez
Mr. Charles Darwin T. Racadio
18
ATTACHMENT 1
Table of Contents
Page
I.
II.
Introduction
Methodology
A. Watershed approach
B. Participatory approach to site selection
C. Identification of dominant and associated contaminants
D. On-site investigation
E. Sampling and sample preparation
References
1-1
1-1
1-1
1-3
1-4
1-4
1-5
1-8
List of Figures
1-1
Multi-parameter water checker used for on-site physico- chemical river
characterization
1-5
1-2
Flow meter measuring velocity across river
1-5
1-3
Method of collecting water samples using bailer
1-5
1-4
Method of collecting water sample using submersible pump
1-6
1-5
Sediment sampling using shovel
1-6
1-6
Sediment sampling using suction auger
1-6
List of Table
1-1
Container, quantity of samples and holding time for water samples per
type of analysis
1-7
1-i
ATTACHMENT 1
WATERSHED APPROACH TO SURFACE WATER SAMPLING
AND ANALYSIS
1
Samar, E.D., 2Collado, M.B., 3Anida, A.H.,and 4Estabillo, P.E.
l. Introduction
The concept of river basin or watershed approach is not new in the
Philippines. Since the 70s, the government is engaged into river basin projects. River
basin is formally recognized in Executive Order 510 (s. 2006) with the creation of the
River Basin Control Office that rationalizes river basin projects particularly for flood
control, reforestation and integrated river basin management and development with
water quality protection and monitoring as one of the supplemental frameworks. The
watershed approach is indispensable towards water quality protection and
monitoring.
This protocol details the activities for the delineation of the watershed into
sub-watersheds and for the identification of representative sampling sites to trace the
origin and sources of pollution from the different river tributaries draining to the
receiving body of water. Through this approach, the water quality within the
watershed can be assessed and specific area-based actions can be formulated.
II. Methodology
A. Watershed Approach
A watershed is defined as “all land area which drains into a stream system,
upstream from its mouth and is surrounded with a divide” (Paragas, et al., undated).
It is an area that drains to a common outlet. It is recognized as the basic building
block for land and water planning (Darghouth, 2008). In the Philippines, river basin is
defined as watershed with land area greater than 1,000 square kilometer.
Management includes the land and the coastal reach of the basin. The term river
basin is used synonymous with watershed in American usage and catchment in
other countries.
The use of watershed approach to the surface water quality assessment is
valuable to identify convergence areas from various dominant and associated landusing activities, and identify the specific points along waterways whereby identified
parameters taken from water samples, need control and further monitoring.
Delineating a watershed into small units of sub-watershed would provide the basis to
1
Edna D. Samar, Project Leader and Agricultural Center Chief IV, Bureau of Soils and Water Management
Mario B. Collado, Engineer IV, Bureau of Soils and Water Management
3
Alan H. Anida, Agriculturist II, Bureau of Soils and Water Management
4
Perla P. Estabillo, Senior Agriculturist, Bureau of Soils and Water Management
2
1-1
area-specific action planning and implementation for environmental resources
management.
1. Watershed and sub-watershed delineation
Topographic map serves as the base map to locate the major and minor river
systems. Topographic sheets of the Pampanga River Basin are available from the
National Mapping and Resource Information Authority (NAMRIA). These are used to
delineate the sub-watershed based on the drainage system.
Based on electronic copy of topographic maps (1:50,000 scale), the subwatersheds of Pampanga Basin is delineated using a GIS program.
2. Area estimation by sub-watershed
The area for each sub-watershed is determined using the GIS program.
Depending on the size of the sub-watershed, further delineation may be necessary
subject to micro-watershed planning and monitoring requirement.
3. Identification of representative sites for sampling
Within the sub-watershed, representative sampling sites are identified. In
general, sampling sites represent the upstream, midstream and downstream
environment. Micro-watershed sampling is considered for detailed study especially
for small area. The following criteria serve as technical guide in the selection of
representative sampling sites:
a) Sites before the inflow of the river or stream into a lake.
b) Sites near to a bridge to be able to utilize the staff gauge already installed by
DPWH for discharge measurement during the sampling activity.
c) Sites along the tributaries or drainage channel immediately before the
confluence with the main or a major river.
d) Sites along the river immediately after a confluence of tributaries with
considerable size of agricultural areas.
e) Sites along the main river with immediate agricultural areas which could affect
the water quality of the channel.
f) Sites immediately before the inflow of river or stream into a marine or water
body.
g) Sites immediately tributaries representing immediate non-point source.
There are several considerations in sampling surface water, namely:
a) Representativeness: Samples must be representative of the water quality at
the place and time of sampling.
b) Flow measurement: Ideally, samples for water quality analysis should be
taken at the same point as the gauging station. If this is not possible,
sampling station should be located upstream or downstream where no
significant change may have occurred.
1-2
c) Accessibility:
Sampling locations must be easily reached for vehicular
transport or boat to save on time and effect in sampling.
i.
Bridges: These are excellent places to establish sampling stations
(provided that it is located at a sampling site on the river) owing to its
accessibility, exact identification of location, ease of control of sampling
equipment and for safety considerations. The exact location of the station
can be determined by the description of the station from the position of
landmarks.
ii.
Boats:
If samples are taken from a boat, a buoy placed at the desired
location may mark the sampling station. Such sampling station may also
be identified by the intersection of lines between landmarks on the shore.
The use of protective personnel equipment (PPE) like life vest and/or
lifeline is recommended.
iii.
Wading: When rivers are sufficiently shallow, it is possible to sample by
wading to the middle of the river. However, bottom of river may be
disturbed and care must be exercised to exclude this. Use of PPE is
highly recommended.
iv.
River bank: This form of sampling must be done when there is no
alternative possible. Sampling is taken where water is turbulent or where
the water is fast and deep. The use of PPE is highly recommended.
v.
Cable ways: Cable ways used for current velocity measurements can be
adopted for sampling in smaller rivers.
Distances between sampling points are determined by using GIS program. A
schematic diagram of the sampling sites and their distances is prepared to visualize
and trace water flow from the upstream to downstream of the watershed.
In each sampling point, coordinates (latitude and longitude) are taken using
the global positioning system (GPS) intended for mapping purposes. Georeferencing is important to ensure that samples are taken in the same site
particularly samples collected from boat. With coordinates, sampling sites are
located in the map and observed values for various parameters can be presented in
map form.
Likewise, photo documentation of the sampling and observed economic and
domestic activities is done in support to physical, chemical and biological analyses of
water, sediment and biotic samples. The photos are linked to the geo-referenced
sampling sites.
B. Participatory Approach to Site Selection
Site selection is based on technical and socio-economic considerations. A
series of technical consultations is necessary to review existing sampling sites within
and around the watersheds and even offshore of receiving body of water. Based on
1-3
local knowledge, potential sources of water pollution must be identified by concerned
stakeholders.
In the case of the Pampanga River Basin, the sampling sites of the
Environmental Management Bureau (EMB), Bureau of Fisheries and Aquatic
Resources (BFAR), National Irrigation Administration (NIA) and BSWM are important
consideration to avoid duplication and to harmonize water sampling of the
mandamus agencies. Consultative meetings of stakeholders particularly government
agencies such as the Manila Bay Coordinating Office (MBCO), EMB, BFAR, NIA,
Fertilizer and Pesticides Authority (FPA), Bureau of Animal Industry (BAI), Philippine
Coconut Authority (PCA), Sugar Regulatory Administration (SRA), National Water
Resources Board (NWRB), Philippine Fisheries Development Authority (PFDA) and
Bureau of Plant Industry (BPI), including Partnership for Environmental Management
of Seas in East Asia (PEMSEA) and academe (UP-Marine Science Institute must be
done to present preliminary sampling sites and to solicit inputs. The assistance of
BFAR regional field unit is necessary for the identification of sampling site
representative of fishery. Similarly, consultation with NIA is vital relative to water
sampling for irrigation purposes.
C. Identification of Dominant and Associated Contaminants
Representative sampling sites are identified for the sub-watershed depending
on its size, dominant landuses and economic activities. A recent landuse and
vegetation survey with map scale of 1:50,000 from the BSWM provide the basis for
the dominant and associated uses particularly the agricultural uses. The economic
activities within the Basin must be obtained from available sources to provide
additional information on contaminants likely to affect water quality. In particular, the
municipal/ city profile on the socio-economic activities provides the basis for potential
sources of pollution; hence point sources can be identified for sampling in order to
generate references values. Also, the participatory approach to site selection
provides option to include diverse concerns particularly on identifying sampling sites
for reference values.
The sampling sites from within the sub-watershed represent non-point source
of pollution. Additionally, point sources of pollution within the watershed and nearby
the watershed are identified to serve as reference for specific dominant land use/
economic use.
In the case of Manila Bay, the 2011 land use and vegetation survey of the
watersheds of Manila Bay (Arellano, et al., 2012) provides the bases for the
dominant and associated land uses. The identified dominant contaminants are
forestry, croplands, fishery, livestock and domestic uses.
D. On-site Investigation
On-site investigation of physico-chemical condition is carried out using multiparameters water checker (Figure 3-1). Parameters include temperature, pH, EC,
TDS, DO, salinity and oxidation reduction potential (ORP).
1-4
Also, the flow rate is an important data to establish a link between water
quality and pollutant loads. If the flow rate is high which normally occurs during wet
season, concentration of pollutants is diluted and hence relatively lower and vice
versa. The concentration in the dry season maybe critical for water quality, however,
during dry season, there is no runoff from croplands and therefore the contributors of
pollutant load may not be from agricultural inputs and activities. In the absence of
river discharge data, on the spot river velocity and river cross sections are measured
to determine the cubic meters per second (cms) discharge of the river. River flow
velocity is measured along the surface cross section by using digital flow meter
(Figure 3-2).
E. Sampling and Sample Preparation
Sampling and sample preparation for isotopic analyses is discussed
thoroughly in Attachment 2. This section presents the general sampling procedure
for water collection intended for nutrients, heavy metals and bacteriological analyses.
Two methods are adopted in getting water samples. For surface water, bailer
or plastic container is used to get the samples and transferred to required bottles for
laboratory analysis (Figure 3-3). On the other hand, a small submersible pump run
powered by car battery is used to get sample at required river depth (Figure 3-4).
Overall, water samples are taken for seven types of analyses as enumerated in the
subsequent section.
Water sampling using bailer
Figure 1-1. Multi-parameter water
checker used for on-site physicochemical river characterization
Figure 1-3. Method of collecting water samples using bailer
Figure 13-2. Flow meter measuring velocity across river
1-5
Figure 1-4. Method of collecting water sample using submersible pump
During the sampling activities, the container is rinsed with the river water and
threw the rinsed water downstream of the sampling location. For shallow and
accessible rivers, sampling bottles are dipped directly into the river facing upstream
at about 10 cm below the surface after rinsing and sealed with its cap before lifting
and placing a container for labelling. After the samples were labelled, the sampling
bottles are placed into the ice chest with sufficient amount of ice to lower and
maintain the temperature until it reached the appropriate laboratory.
Sediments are collected by using small shovel for surface collection (Figure 35) and suction auger for soft sediment collection at the river beds (Figure 3-6).
Figure 1-5. Sediment sampling using shovel
Figure 1-6. Sediment sampling using suction
auger
Biotic samples like plants are collected near the water sampling point.
Sampling materials vary depending on the analysis to be undertaken for the
samples. Table 1-1 summarizes the container used and quantity of samples
including the holding time for the samples.
1-6
Table 1-1. Container, quantity of samples and holding time for water samples per
type of analysis
Type of analysis
a) Nitrate*
Sampling
Bottles/container
Plastic/ Nalgene
bottle
Quantity of
Samples
1L
b) Particulate
Organic Matter**
Plastic/ Nalgene
bottle
1L
c) N, O isotopic
analysis in
nitrate**
d) H & O isotopic
analysis**
Plastic/ Nalgene
bottle
150-200 ml
Plastic/ Nalgene
bottle
50 ml
e) Heavy Metals***
Glass (amber);
colored plastic
1L
f) Biological***
Sterile plastic or
glass; autoclave
Plastic or glass
125 ml
g) Nutrients &
others***
(phosphorous,
TSS)
250 ml
Holding Time
48 hrs
Filtered
immediately &
over-dry 1-2 days
Stabilize samples
with acid using
10% HCl
Acidify with
concentrated nitric
acid, good for 6
months
6 hrs for fecal and
total colliform
2 to 7 days
* Samples are submitted to ISO certified local service laboratory.
** Samples are submitted to foreign service laboratory in Vienna and New Zealand including
the prepared sediments and biotic samples.
*** Samples are submitted to government laboratory or DENR accredited laboratory.
Clean the bottles and glass containers with soap and water. Final rinse should
preferably be done with distilled water. Before filling with water, rinse the container
five times with water being collected.
The time of sampling started from about 6am in the morning till 4:00pm,
considering the required holding time of water samples and transport to local service
laboratory. The time of sampling also consider the occurrence of rainfall i.e. after a
rainfall event. The two samplings events –wet and dry represent periods of high and
low flows.
1-7
References
Darghouth, Salah, Christopher Ward, Gretel Gambarelli, Erika Styger, and Julienne
Roux. 2008. Watershed Management Approaches, Policies, and Operations:
Lessons for Scaling Up. The World Bank. Water Sector Board Discussion
Paper Series. Paper No. 11, May 2008.
Department of Environment and Natural Resources. DENR Administrative Order No.
34 – Revised Water Usage and Classification Criteria of 1990. Visayas
Avenue, Diliman, Quezon City.
Department of Environment and Natural Resources. DENR Administrative Order No.
35 – Revised Effluent Regulations of 1990. Visayas Avenue, Diliman, Quezon
City.
Environmental Management Bureau - Department of Environment and Natural
Resources. 2008. Ambient Water Quality Monitoring Manual
Paragas, Vicente S., Juanito A. Manzano, Jr. and Danilo C. Cacanindin. n. d. Land
Use Planning Strategies on Watershed Management and Disaster Reduction
in
the
Philippines.
Retrieved
January
28,
2014
from
ces.iisc.ernet.in/energy/.../LM/.../255.PDF
River Basin Control Office. Plans and Programs of River Basin Control Office relative
to Water resources Management and River Basin Management. Retrieved
January
28,
2014
from
http://www.wepadb.net/pdf/0710philippines/8_RBCO.pdf
1-8
ATTACHMENT 2
Table of Contents
Page
I.
Introduction
2-1
II.
Sampling and sample preparation
A. 18O/16O and 2H/1H of water
B. 15N/14N and 18O/16O of nitrate dissolved in water
C. 13C/12C and 15N/14N, C and N concentrations in soils and
sediments
D. 13C/12C and 15N/14N, C and N concentrations in particulate
organic matter (POM)
E. 13C/12C and 15N/14N, C and N concentrations in vegetation
2-1
2-1
2-2
2-2
Isotopic measurements
A. 18O/16O and 2H/1H of water
B. 15N/14N and 18O/16O of nitrate dissolved in water
C. 13C/12C and 15N/14N, C and N concentrations in soils,
sediments, POM, and plant tissue
References
2-6
2-6
2-6
2-6
III.
2-3
2-4
2-7
2-i
ATTACHMENT 2
SAMPLING AND SAMPLE PREPARATION FOR ISOTOPIC ANALYSES
1
Castañeda, S.S., 2Ramirez, J.D. and 3Sta. Maria, E.J.
I. Introduction
Proper sampling and field measurements of both physicochemical and
isotopic parameters are critical to ensure high quality analysis, reliable interpretation
of data and consistency for the establishment of databases.
Different types of samples (i.e. soils/sediments, vegetation, water, fauna,
shellfish) require different storage and collection methods to ensure maximum
sample integrity and reliability. Sample containers must be clean and non-reactive. In
general, it is required for samples to be stored in a temperature below 4 °C
temperature prior to analysis. In all cases, a homogenous sample is required to
achieve reliable results.
Before embarking on a sampling campaign, ensure that all materials and
equipment needed for field work have been properly checked and packed.
Equipment should have been properly calibrated.
II. Sampling and Sample Preparation
A.
18
O/16O and 2H/1H of water
Sampling for Hydrogen and Oxygen isotopes is simple. No sample filtration or
preservation is required.
1. Materials
 50 mL double capped glass or polypropylene bottle
 at least 2 Li pail or can
 labeling tape
 waterproof marking pen
2. Sample collection and preservation
Surface water samples are obtained by submerging the sampling bottles into
the water at areas where there is an active, but not turbulent flow. Completely fill a
50 mL, double capped, glass or polyethylene bottle directly from the source or from a
1
Soledad S. Castañeda, Chief, Atomic Research Division, Philippine Nuclear Research Institute
Jennyvi D. Ramirez, Science Research Analyst, Philippine Nuclear Research Institute
3
Efren J. Sta. Maria, Senior Science Research Specialist, Philippine Nuclear Research Institute
2
2-1
secondary container (a pail). There should be no headspace (indicated by the
presence of bubbles when turned upside down). If a bubble occurs, repeat sampling
until this is eliminated. Make sure the bottles are tightly capped. Clearly label the
sample with all details.
During sampling, storage and transportation to the laboratory, take care to
avoid evaporation of the sample.
B.
15
N/14N and 18O/16O of nitrate dissolved in water
A reliable concentration of nitrate measurement is required to process the
sample in a Stable Isotope Laboratory. It is necessary to plan to send the samples
out for nitrate concentration analysis promptly.
1. Materials
 100 mL double capped glass or polypropylene bottle
 at least 2 Li pail or can
 10% good technical grade HCl
 Pipet
 pH strips
 labeling tape
 waterproof marking pen
2. Sample collection and preservation
Surface water samples are obtained by submerging the sampling bottles into
the water at areas where there is an active, but not turbulent flow. Completely fill a
100 mL, double capped, glass or polyethylene bottle directly from the source or from
a secondary container (a pail). Stabilize samples with acid for NO3 isotopic analysis
after collection using good technical grade acid. Use a pipette to add 1 ml of 10%
HCl per 100 ml sample. This will cause the sample to have pH-3, stopping all
nitrification. Thus, samples do not need to be filtered. They will be stable at room
temperature for indefinite periods.
C.
13
C/12C and 15N/14N, C and N concentrations in soils and sediments
1. Materials
 Clean plastic bags (i.e. Ziplocks)
 Trowel
 Watch glass/clean tray
 Beaker
 Centrifuge tubes
 Mortar and pestle
 1M HCl
 Distilled water
 Oven/freeze dryer
 Centrifuge
 pH meter
2-2
2. Sampling
a) Surface sediments and soils are collected from the uppermost layer (top 2-3
cm).
b) Store in clean plastic bags (Ziplocks) and place in fridge or freezer (below
4oC) to prevent biodegradation prior to sample preparation and analysis.
3. Preparation
Drying
1. Wet sediment/soil samples are spread out on a watch glass or
clean tray and air dried.
2. Oven drying at 35-40oC or freeze drying can also be done.
For
organic
carbon
analysis
Inorganic contribution (shells and calcareous sediments) is removed
using 1M HCl at room temperature.
1. About 20-50g of sample is usually reacted in a beaker with
100mL of 1M HCl.
2. Allow overnight to ensure complete dissolution of the inorganic
carbon.
3. Rinse the residue with distilled water.
4. Separate the residue from the liquid several times using a
centrifuge and decantation until the rinsing water has a pH of
between 5-7.
Grinding Homogenous sample is required.
1. Grind samples to a fine powder (100-200 um) using ring mill or
mortar and pestle
Storage
D. 13C/12C and
(POM)
Store in a dessicator.
15
N/14N, C and N concentrations in particulate organic matter
1. Materials
 GF/F glass filters
 Aluminum foil
 Centrifuge tubes
 Watch glass
 Filtration set-up (filter
holder, receiver, vacuum
hand pump)
 1L plastic bottles
 Teflon coated forceps
 1M HCl in wash bottle
 Distilled water
 Furnace
 Oven
2-3
2. Sampling
a) Pre-combustion of GF/F glass filter: Use Teflon coated forceps in handling
glass filters.
1. Pre-combust the glass filters at 450oC for 4 hours.
2. Wrap the pre-combusted glass filters in aluminum foil.
Avoid
contamination and touching the glass filters since it may alter the
carbon and nitrogen isotopic signal.
b) Collection
1. Put the pre-combusted glass filter into the filtration set-up using Teflon
coated forceps.
2. Filter 1-2 L of water. Take note of the volume of water being filtered
(especially when filter become brownish in color).
3. Rinse with a small amount of dilute HCl to remove any inorganic
contribution.
4. Final rinse with distilled water to remove residual acid.
5. Carefully remove the glass filter (Teflon coated forceps) from the
filtration set-up and store in a clean centrifuge tube. Close tightly.
6. Place in a cool place (below 4oC).
3. Preparation
Drying
1.
2.
3.
4.
Storage
Store in a dessicator
Use Teflon coated forceps in handling glass filters
Place the glass filters on watch glass.
Oven dry at 30-40oC for 1 to 2 days.
Pace the dried glass filters into clean containers (centrifuge
tubes)
E. 13C/12C and 15N/14N, C and N concentrations in vegetation
1. Materials







Clean plastic bags (i.e. Ziplocks)
Watch glass/clean tray
Scissors
Mortar and pestle
Distilled water
Liquid nitrogen
Oven/freeze dryer
2-4
2. Sampling
 Collect young leaves and place in clean
plastic bags.
3. Preparation
Drying
Grinding
Storage
1. Check samples to ensure that there is no adhering material.
2. Rinse with distilled water.
3. Cut the leaves into small pieces using clean scissors for faster
drying.
4. Oven dry at 35-40oC.
5. In case of slow drying vegetation, use freeze drying method to
prevent occurrence of moulds.
1. Place dried samples in mortar and pestle
2. Put small amount of liquid nitrogen.
3. Grind to produce a homogenous powder.
Store in a dessicator.
2-5
III. Isotopic measurements
A.
18
O/16O and 2H/1H of water
Isotopic ratios of hydrogen and oxygen isotopes in water were performed at
the Isotope Hydrology Laboratory, International Atomic Energy Agency, Vienna
Austria, by laser spectroscopic analysis. The equipment measures absorption
around an optimum wavelength. Isotopic compositions are given as delta scale (δ)
values, the relative deviations with respect to the standard is used to calculate
molecular concentrations of 2HHO, HH18O, and HHO. Molecular concentrations are
converted into atomic ratios 2H/1H and 18O/16O and a post processing procedure is
used to calculate the delta scale (δ) values with respect to the Vienna Standard
Mean Ocean Water (VSMOW 2).
B.
15
N/14N and 18O/16O of nitrate dissolved in water
Isotopic ratios of hydrogen and oxygen isotopes nitrates dissolved in water
were performed at the Stable Isotope Laboratory particularly the GNS Science, New
Zealand.
Nitrates samples (NO3-) were converted to nitrite (NO2-) using cadmium, then
to nitrous oxide (N2O) using sodium azide in an acetic acid buffer. The nitrous oxide
is then purged from the water sample, goes through a series of chemical traps to
remove H2O and CO2, the N2O is then cryogenically trapped under liquid nitrogen.
After being cryofocused in a second trap, the N2O goes through a GC column and
into an Isoprime IRMS to determine its isotopic signature of nitrogen and oxygen.
The method is modified from McIlvin and Altabet (2005) following personal
communication with Mark Altabet.
All results are reported with respect to AIR for δ15N and VSMOW for δ18O,
normalized to the international standards; USGS 34 (-1.8‰ for δ15N and -27.9‰ for
δ18O), IAEA-NO3 (4.7‰ for δ15N and 25.6‰ for δ18O) and to the internal standard;
KNO3b (10.7‰ for δ15N and 11.7‰ for δ18O).
The analytical precision for these measurements is 0.3‰ for δ 15N and for
δ18O, except for samples below 100 g/m3 NO3-N which may have lower precisions.
C.
13
C/12C and 15N/14N, C and N concentrations in soil, sediments, POM, and
plant tissue
Samples are analysed by combustion on a Eurovector elemental analyser
coupled to an Isoprime mass spectrometer.
All results are reported with respect to VPDB and N-Air, normalized to the
internal standard; Leucine (-23.0‰ for δ13C, 2.0‰ for δ15N.
The analytical precision for these measurements is 0.3‰ for δ 15N and 0.2‰
for δ C.
13
2-6
References
Analytical Chemistry, 2005, 77 (17), pp 5589–5595
International Atomic Energy Agency. Sampling Procedures for Isotope Hydrology
Brochure. IAEA. Water Resources Programme, ihs@iaea.org,
www.iaea.org/water
Matthew R. McIlvin and Mark A. Altabet - Chemical Conversion of Nitrate and Nitrite
to Nitrous Oxide for Nitrogen and Oxygen Isotopic Analysis in Freshwater and
Seawater.
Rogers, K.M. 2005. Application of Stable Isotopes in Ecological Research: It’s All
Elemental. QT Workshop 2005.
2-7
ATTACHMENT 3
Table of Contents
Page
I.
II.
III.
IV.
Abstract
Introduction
Methodology
A. Sampling and analysis
B. Assessment of surface water quality
C. Estimation of pollutant loading
Results and Discussion
A. Watersheds of the Pampanga River Basin
B. Surface Water Quality
C. Pollutant loading
Summary and Recommendation
References
3-1
3-2
3-2
3-2
3-3
3-4
3-4
3-8
3-14
3-18
3-19
List of Figure
3-1
Diagram of the location of sampling sites and their distances
3-9
List of Tables
3-1
Surface water quality rating based on nutrients, heavy metals and
colliform loading from Pampanga River Basin into Manila Bay
3-3
3-2
General land uses, Pampanga River Basin, 2011
3-8
3-3
On-site physico-chemical results from multi-parameter water
checker, March to April 2013
3-11
3-4
Annual nitrate and total phosphorus loading into Manila Bay, 20122013
3-17
3-i
List of Maps
Page
3-1
3-2
3-3
3-4
3-5
3-6
3-7
Location of the Pampanga River Basin, Philippines
Sub-watersheds of Pampanga River Basin
Dominant contaminant in the Pampanga River Basin
Location of sampling sites for non-point sources of contaminants,
Pampanga River Basin
Location of sampling sites for point sources of contaminants,
Pampanga River Basin
Surface water quality within and nearby the Pampanga River Basin,
wet season, 2012
3-5
3-5
3-9
3-10
Surface water quality within and nearby the Pampanga River Basin,
dry season, 2013
3-16
3-10
3-16
3-ii
ATTACHMENT 3
STATE OF THE PAMPANGA RIVER BASIN, PHILIPPINES
1
Samar, E.D., 2Collado, M.B., 3Anida, A.H. 4Flores, A. B. and 5Fajardo, T.M.
Abstract
The Pampanga River Basin provides precious water vital not only to its residents but also to
the general public and economy in Luzon. The surface water quality of Pampanga River remains poor
considering results from two seasons covering 14 parameters - physical, biological, nutrients and
heavy metals.
The Pampanga River contributed an annual nitrate load beyond the allowable loading for class
SB based on the ASEAN marine water quality criterion. Additionally, the Pampanga River contributed
a total phosphorous loading that exceeded the threshold for limited algal growth.
The study proved the usefulness of the watershed approach for strategic sampling and
analysis in order to identify critical areas contributing to pollution loading into the Manila Bay. It
identified critical locations where major contributions to nitrate and phosphorous loading occur and
where area-based strategic action plans can be pursued.
A review of the DAO 90-34 may be necessary to harmonize with international criteria and to
update classification of water bodies considering not only intended uses but impact to receiving body
of water. Strong LGU participation in periodic monitoring and enforcement of existing legislation would
be essential with support from sectoral groups.
Keywords: Water quality, pollution loading Pampanga River Basin
l. Introduction
The Pampanga River Basin is one of the identified 20 major river basins
considered as the lifeblood and driver of Philippine Economy (RBCO, n.d.). It drains
directly to Manila Bay, a highly valuable receiving body of water considering its
historical, cultural, economic and social significance in the life of Filipinos.
The Pampanga River contributes the most (approximately 49 percent) to the
net fresh water influx into the Bay (Jacinto, et al., 1998). Thus, the state of water
draining into the Bay potentially influences its pollution. The Environmental
Management Bureau (2005) through its Philippine Water Quality Status Report
(2001-2005) has prescribed that the Philippine surface water quality be assessed
based on the set beneficial use as defined in the DENR Administrative Order (DAO)
90-34. Under this DAO, there are 32 parameters that define the desired water quality
per water body classification. Accordingly, a water body must meet all the criteria of
each applicable parameter 100 percent of the time to maintain its designated
classification.
1
2
3
4
5
Edna D. Samar, Project Leader and Agricultural Center Chief IV, Bureau of Soils and Water Management
Mario B. Collado, Engineer IV, Bureau of Soils and Water Management
Alan H. Anida, Agriculturist II, Bureau of Soils and Water Management
Andrew B. Flores , Computer Programmer II, Bureau of Soils and Water Management
Teodorico M. Fajardo Cartographer II, Bureau of Soils and Water Management
3-1
In the absence of a water quality index, an interim methodology based on
compliance to DAO 90-34 water quality criteria is used for all surface waters. The
parameters for monitoring include:
a) inland surface waters - dissolved oxygen (DO), biochemical oxygen demand
(BOD), total suspended solids (TSS), total dissolved solids (TDS), and heavy
metals;
b) groundwater - fecal coliform, nitrates, and salinity (chloride content) as defined
in the Philippine National Standards for Drinking Water (PNSDW);
c) coastal and marine waters - DO, coliform, and heavy metals.
In 2005, the National Water Quality Status Report cited the Pampanga River
as one of the rivers with poor water quality. To provide bases for area-specific plan of
actions to address pollution, this study evaluates the surface water quality from
upstream to downstream of the Pampanga River to identify specific locations where
pollution occurs. The physical and socio-economic attributes that influence surface
water quality is likewise presented. Moreover, this report provides a summary of the
surface water quality of the Pampanga River Basin and its contribution to pollution
loading of Manila Bay. The origin of pollution is identified using multiple stable
isotopes as discussed in Attachments 6 and 7.
II. Methodology
The watershed approach is adopted for strategic sampling and assessment of
surface water quality considering the physical, biological and chemical parameters
particularly the nutrients and heavy metals in water.
A. Sampling and analysis
Attachment 1 presents the watershed approach to surface water sampling and
analysis. The entire watershed of Pampanga River Basin was divided into 11
sub-units. Representative sampling sites for non-point sources of pollution within the
entire Pampanga River Basin were identified considering the sub-watersheds and
surface water flows from upstream to downstream of the Main Pampanga River. The
non-point sources are confluence of runoff from dominant land use.
Additionally, point sources for specific uses were identified to provide
reference values. Specifically, the point source pollutant is the discharge of effluent to
surface water from discrete conveyance, such as pipes or man-made ditches.
Non-point source pollutant is from any other source, such as precipitation and excess
water that runs over land or through the ground accumulating and carrying pollutants
to the nearby body of water.
B. Assessment of surface water quality
Surface water quality was assessed considering 14 parameters enumerated in
Table 3-1. Measured value for each sampling site was compared to the prescribed
criterion and a rating of pass or fail for the parameter is given. Following the DAO
3-2
90-34, all the criteria must be met for each applicable parameter 100 percent of the
time to pass the water quality. When one or more parameter is not met, the body of
water fail in the overall water quality rating.
Using the multi-parameter water checker, eight parameters were observed but
during the dry season only because of the unavailability of the equipment. Only two
parameters (pH, DO) form part of the assessment considering the prescribed criteria
in the DAO 90-34. Additionally, the laboratory result of the TSP was included in the
assessment considering available criterion.
Two nutrients in water, specifically nitrate and total phosphorous were
assessed considering ASEAN marine water quality criteria for class SB and the DAO
90-34 for class C. Also, the criterion relative to growth of algae based from Bloom
(n.d.) was considered in the assessment. Additionally, seven heavy metals were
evaluated relative to the DAO 90-34 criteria. For both nutrients and heavy metals,
Attachment 4 provides the details on their assessments.
On the other hand, the assessment of colliform bacteria in water samples
based on DAO 90-34 is discussed lengthily in Attachment 5.
Table 3-1 Surface water quality rating based on physical, nutrients, heavy metals and
colliform parameters
Parameters
Within the
criteria
Beyond the
criteria
pH
Pass
Fail
Dissolved oxygen (DO)
Pass
Fail
Total suspended solid (TSS)
Pass
Fail
Nutrients in water (NO3-1,
TP):
Pass
Fail
Colliforms (Total, fecal)
Pass
Fail
Heavy metals in water:
(Pb, Ar, Cd, Cr, Hg, Co, Ni)
Pass
Fail
All parameters:
Overall rating
Pass
Fail
Overall rating
Fail (one or more
parameters)
C. Estimation of pollutant loading
Nutrient loading is determined by measuring the a) river discharge and b) the
concentration of nutrient. Nutrient load varies spatially with time. River flow or stream
discharge is not fixed; it varies with the watershed physical condition including
climatic parameters. River flow was measured using current flow meter, details of
which are discussed in Attachment 1.
3-3
The nutrient load is estimated using the formula:
Nutrient load = River discharge x concentration of nutrients
Given the river discharge, the allowable loadings are estimated based on
specific criteria, particularly a) the ASEAN marine water quality criteria, b)
DENR-DAO 90-34, and c) criterion set by Bloom (n. d.) for total phosphorous.
III. Results and Discussions
The study area – the Pampanga River Basin is located in Central Luzon (Map
3-1). It is border to the south by Manila Bay, to the east by Sierra Madre Mountains, to
the north by Caraballo Mountains, and to western section by Zambales Mountain
Range, where Mount Pinatubo is located. The western Zambales Mountain Range is
characterized by the volcanic pyroclastics flow during 1991 eruption. In contrast, the
eastern Sierra Madre Mountain comprises of more dissected and faulted terrain. All
river systems within the Basin drains into Manila Bay together with the sediments
loaded of pollutants. In general, it covers the provinces of Nueva Ecija, Tarlac,
Bulacan and Pampanga.
A. Watersheds of the Pampanga River Basin
1. Sub-watersheds of the Pampanga River Basin
The study area is subdivided into three major sub-basins, namely: 1) Main
Pampanga River (north and central section), 2) Angat River (eastern Sierra Madre
Mountain), and 3) the western section consisting of Pasig-Gumain, Pasig-Potrero
River network. Map 3-2 shows the extent and distribution of the delineated
sub-watershed.
Main Pampanga River Basin
The Main Pampanga River Basin is the largest sub-watershed consisting of
461,360 hectares and has the longest river length. The Main Pampanga River Basin
was further sub-divided into 11 sub-watersheds with corresponding areas (ha) as
follows:
a) SW01-A – Digdig River
- 30,041.88
b) SW01-B – Rio Chico River
- 118,096.38
c) SW01-C – Rio Chico – Pampanga River - 284,615.08
d) SW01-D – San Miguel River
- 28,607.22
3-4
Map 3-1. Location of the Pampanga River Basin, Philippines
Map 3-2. Sub-watersheds of Pampanga River Basin and the
sampling sites
3-5
e)
f)
g)
h)
i)
j)
k)
SW02-A – Caranglan River
SW02-B – Pampanga Coronel River
SW02-C – Coronel River
SW02-D – Nazareth Creek
SW03 – Peñaranda River
SW04 – Pampanga- Peñaranda River
SW07 – Pampanga-Maasim River
- 85,171.70
- 133,283.68
- 58,176.31
- 3,039.76
- 55,089.91
- 5,198.53
- 13,380.02
The river originates in Caraballo Mountains to the north at Carranglan,
and flows into Pantabangan storage reservoir. After passing the dam, the river
further flows downstream southward converging with several tributaries and
finally drains into Manila Bay at Masantol-Macabebe Pampanga. Major
tributaries of Pampanga main stream are Coronel River, Peñaranda River and
Rio Chico River. Coronel River is located at middle-upstream area draining from
the eastern Sierra Madre to Gabaldon and Palayan City. Adjacent watershed is
Peñaranda River, it drains from Gen. Tinio to Peñaranda and meet with the Main
Pampanga River at Jaen-San Isidro. Opposite these two rivers, the Rio Chico
River flows from the western side of the study area. It covers the area from
Lupao, San Jose City, Munoz, Guimba, Santo Domingo and La Paz, Tarlac. It
has the largest watershed area of 284,615 ha and joins the main river at Arayat
and Candaba which has bigger flooding area during rainy seasons.
Pasig-Potrero, Porac-Gumian River Basin (SW 05)
The network of river basins to the western section of the study area
represents the rivers draining to the eastern flanks of Mount Pinatubo. This
includes Abacan River, Pasig-Potrero and Porac-Gumain River Basin. Total area
of the watershed is approximately 140,164 ha. At the downstream, the rivers
are connected to Main Pampanga River by cut-off channel Bebe-San Esteban.
River morphologies of the basin are much affected by the Pinatubo Eruption in
1991.
Angat River Basin (SW 06)
Angat River Basin initiates from Sierra Madre Mountain and pours into
Angat storage dam through a narrow valley. Downstream of dam, the river flows
westward and finally empties into Manila Bay at Calumpit-Hagonoy area through
Labangan Floodway. There is a small connecting channel with Pampanga River,
which is called as Bagbag River. The main channel passes Angat Dam and Ipo
Dam Reservoir. It is joint by Bayabas River about 10 km upstream of Bustos
rubber dam. Total Angat Watershed area is about 117,211 hectares.
2.
Climatic Condition
There are three PAGASA climatic classifications identified in the study
area. The large western and central sections of the basin is classified as climatic
Type I; the eastern mountainous region belongs to Type III; and portion of this
3-6
mountainous area is classified as Type II. PAGASA climatic classification Type I
have two distinct seasons; dry from November to April and wet during the rest of
the year. Type II category has no dry season with very pronounce rainfall from
November to January and Type III category at the small section of the watershed
is characterized by not very pronounced seasons, relatively dry from November
to April and wet during the rest of the year. Based from PAGASA Weather
Station at CLSU Munoz, the maximum rainfall depth recorded is usually between
June to September and the long term average annual rainfall is estimated at
2,160 mm/year about 84 percent of the annual rainfall concentration in rainy
season between May and October.
Rainfall pattern in the study areas affects the sampling activity as well as
the spatial difference of chemical concentration on the river water samples
brought to laboratory.
3.
Multiple Uses and Pressures of the Pampanga River Basin
The Pampanga River Basin is home to 8.17million residents (NSO, 2010)
in four provinces (Nueva Ecija, Tarlac, Bulacan and Pampanga). It is habitat to
2.11 million livestock and 25.3 million poultry (BAS, Jan 2013) with hog and
poultry as leading sources of production for the country. The Pampanga River
Basin is valuable not only to the residents of the four provinces but also to the
residents of entire Region 3, Metro Manila and Luzon as it supplies the
hydro-electric power of the Luzon grid. It is the source of industrial, commercial,
and domestic water supply for Region 3 and Metro Manila.
It provides the irrigation coming from the Pantabangan Dam, Angat
Reservoir and Ipo Reservoir serving extensive agricultural areas devoted mainly
to rice, sugarcane and vegetables (Table 3-2). With irrigation as the intended
use for croplands, most rivers are classified as Class C. Surface water draining
into the Manila Bay comes mainly from the agricultural areas representing 42
percent of the entire watersheds (Arellano, et al., 2012).
The watershed abounds with copper ores and these have attracted small
scale mining within the forested areas. Mining in the forest areas is associated to
heavy metal contamination in water.
Human intervention for the maintenance of the agricultural lands to
sustain production for growing population requires chemical inputs like
application of fertilizers, pesticides and other agricultural amendments. In 2010,
Samar, et al. (2012) estimated a total of 42,261metric tons of nitrogen fertilizer
that was applied in 480,895 hectares of rice fields in the Pampanga River Basin.
Such applications add chemical pollution to surface water that drain into creeks,
rivers and finally to Manila Bay. The same source cited that only 21,468 metric
tons was taken by the rice plants and the remaining amount (20,792 mt) was
loaded to the environment with estimated nitrogen losses in surface runoff at 423
to 5,494 metric tons. In the same period, BAS recorded usage of 192.4 metric
tons of solid pesticide and 337,858 liters of liquid pesticides in 203,794 hectares
3-7
of rice lands. The pesticides consist of insecticides, herbicides, fungicide,
molluscide, rodenticide and nematocide.
Table 3-2. General land uses and vegetation, Pampanga River Basin, 2011
Description
Agricultural Lands
Paddy rice irrigated
Paddy rice non-irrigated
Corn
Vegetables
Rootcrops
Sugarcane
Citrus
Mixed fruit trees
Poultry/Piggery
Grass/Pasture/Shrubland
Grass/Pasture
Shrubs
Area (ha)
562,774
466,557
14,338
6,304
3,846
5,745
21,956
1,026
39,453
3,547
232,854
104,716
128,138
Description
Forest/Woodland
Forest
Wetlands
Fishpond
Marsh
Miscellaneous Areas
Built-up
Major river/Lakes
River wash
River Islet/Sand Bar
Volcanic ash/lahar
Area (ha)
163,340
163,340
44,060
33,107
10,953
189,431
130,507
8,664
46,664
97
3,499
*Adopted from Arellano, et al. (2012)
Dominant and associated contaminants in each of the sampling sites
were identified considering the dominant landuses and these were reflected in
the map (Map 3-3). The contaminants were identified as follows: forestry,
croplands, livestock/ poultry, fishery and domestic uses. These contaminants
were correlated to the isotopic values discussed in Attachment 6.
Furthermore, the growing built-up areas along the main stream of
Pampanga River have increased domestic wastes along the channel.
Observations during the collection of samples revealed uncontrolled dumping of
solid and liquid wastes into bodies of water within the watershed. Photo
documentation is presented in Attachments 4 (Figures 4-3 and 4-5) and 5
(Figures 5-1 to 5-6) showing dumping from piggery, poultry, slaughterhouse and
households. The uncontrolled dumping of waste poses threat on the bodies of
water. There are 32 open dumpsites and three controlled dumpsites that require
local monitoring.
B. Surface water quality
A total of 38 sampling sites within and around the Pampanga River Basin
were identified and geo-referenced (Maps 3-4 and 3-5). Water travelled 249.2
km from the farthest sampling point to the mouth of the Pampanga River. The
nearest sampling point is 0.8 km away from the Bay. The schematic location of
the various sites and their distances are presented in Figure 3-2.
Surface water quality was assessed in terms of the physical, chemical
and biological parameters. The recorded values for eight physico-chemical
parameters during the dry season are shown in Table 3-3.
3-8
Figure 3-1 Diagram of the location of sampling sites and their distances
Map 3-3.
Dominant contaminants in the Pampanga River Basin
3-9
Map 3-4. Location of sampling sites for non-point sources of
contaminants, Pampanga River Basin
Map 3-5. Location of sampling sites for point sources of
contaminants, Pampanga River Basin
3-10
Table 3-3. On-site physico-chemical results from multi-parameter water checker, March to April 2013
Final
code
1a
1b
3
4
5
6
7
8
9b
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Location
Non-point sources
Barangay Bunga, Carranglan, Nueva Ecija
Barangay R. Padilla, Carranglan, Nueva
Ecija
Barangay Sampaloc, Pantabangan, Nueva
Ecija
Barangay Mayapyap, Cabanatuan
San Antonio, Nueva Ecija
Barangay San Anton, Jaen, Nueva Ecija
San Isidro, Nueva Ecija
Barangay San Vicente, Gapan–San
Leonardo.
Purok Sagingan, Nazareth Gen, Tinio,
Nueva Ecija
Arayat Pampanga
NIA dam, Barangay Sabangan, San Miguel
San Luis Pampanga
Barangay BahayPari, Candaba, Pampanga
NIA Diversion Dam, Barangay Tibagan,
Bustos, Bulacan
Barangay Garay, Angat, Bulacan
Apalit, Pampanga
Labangan Bridge, Calumpit, Bulacan
Poblacion, Guiguinto, Bulacan
Barangay Catmon, Santa Maria, Bulacan
Barangay Curva, Guimba Nueva Ecija
Sibul Spring, San Miguel, Bulacan
Bongabon-Palayan, Coronel River
Barangay San Roque, La Paz, Tarlac
Temp
(°C)
pH
Electrical
Conductivity
(mS/cm)
Turbidity
(NTU)
Total
Dissolved
Solids (g/L)
Oxidation
Reduction
Potential
(mV)
Dissolved
Oxygen
(DO)
(mg/L)
Salinity
(ppt)
22.28
24.94
6.76
5.22
0.232
0.064
12.8
97.7
0.151
0.038
151
301
12.32
10.02
0.1
0.0
23.05
4.97
0.139
12.9
0.091
233
15.79
0.1
21.88
29.58
29.68
22.11
30.64
6.67
4.66
4.62
6.78
3.91
0.239
0.255
0.282
0.234
0.405
21.5
32.2
35.1
23.6
17.6
0.155
0.165
0.183
0.152
0.263
174
352
654
157
299
8.63
50.00
No data
12.23
No data
0.1
0.0
0.0
0.1
0.0
29.21
6.96
0.644
17.1
0.412
83
11.93
0.3
21.95
29.39
26.52
27.48
30.00
6.73
3.92
4.33
5.46
6.88
0.243
0.31
0.274
0.184
0.332
32.9
21.5
43.0
43.6
24.0
0.158
0.201
0.178
0.120
0.216
33
317
286
255
85
8.99
9.13
12.28
14.31
15.86
0.1
0.1
0.1
0.1
0.2
22.39
28.24
28.57
30.08
29.00
30.02
29.43
26.09
32.36
7.70
5.48
5.72
6.67
7.30
4.63
7.09
7.77
8.06
0.134
0.662
1.600
0.697
98.700
0.295
1.77
0.725
0.853
19.3
52.0
29.1
30.0
230.0
40.4
26.1
15.9
114.0
0.087
0.424
1.020
0.446
0.800
0.195
1.130
0.464
0.546
56
179
146
100
119
434
81
31
89
50.00
7.05
6.65
5.08
12.50
10.64
9.52
8.62
5.66
0.1
0.3
0.8
0.3
0.1
0.1
0.9
0.4
0.4
3-11
Final
code
24
25
26
27
A
B
C
D
E
F
G
H
I
Location
Masantol Proper, Masantol Pampanga
Barangay San Pedro Sasmuan, Pampanga
Barangay Sagrada, Masantol, Pampanga
Sapang Makawayan, Masantol Macabebe Pampanga
Point sources:
Dumpsite, Barangay Valle Cruz,
Cabanatuan City
Slaughter House, San Ildefonso Bulacan
Piggery Farm, San Ildefonso Bulacan
Fishpond Barangay Santo Tomas,
Sasmuan, Pampanga
Piggery-chiken farm, Barangay Gaya-gaya,
San Jose del Monte
Domestic site, Diliman Quezon City
Fish port site 1, Navotas
Fish port site 2, Navotas
Fish port site 3, Navotas
Criteria for B (DENR- DAO 90-34)
Criteria for SB (DENR- DAO 90-34)
Temp
(°C)
pH
29.79
29.32
30.22
28.64
7.00
5.67
6.69
6.08
15.100
26.000
24.200
55.400
50.0
59.6
32.0
31.0
9.360
16.100
15.000
33.300
Oxidation
Reduction
Potential
(mV)
85
94
89
72
31.38
6.87
No data
249.0
No data
52
8.92
0.0
28.28
30.68
28.87
3.64
4.45
6.47
No data
5.940
7.590
199.0
1000.0
105.0
0.900
3.740
4.780
312
128
111
12.08
9.28
4.24
0.0
3.2
4.2
28.05
6.68
1.950
62.1
1.250
49
6.45
1.0
27.71
27.46
26.70
27.40
4.51
5.66
6.43
7.06
0.549
27.200
9.830
1.600
26.0
26.1
446.0
40.0
0.351
16.800
6.190
1.030
542
-309
-234
6
13.11
3.22
4.59
10.53
0.0
16.7
5.5
0.8
6.5-8.5
6.0-8.5
Electrical
Conductivity
(mS/cm)
Turbidity
(NTU)
Total
Dissolved
Solids (g/L)
-
Dissolved
Oxygen
(DO)
(mg/L)
8.53
5.31
7.19
5.42
Salinity
(ppt)
9.3
15.9
14.7
36.8
Min. 5
Min. 5
3-12
Water temperature is recorded highest (32.36 °C) in Rio-chico River and
lowest (21.88 °C) in Barangay Mayapyap, Cabanatuan City. Water temperature
varies and directly affects several chemical element concentrations and
dissolved oxygen is one of them.
A pH of 6.5 – 8.5 is prescribed by DAO 90-34 for Class B waters and
6.0-8.5 for Class SB waters. The highest pH value (7.77) is recorded at
Coronel River between Palayan City and Bongabon,Nueva Ecija and the acidic
value of 3.91 was observed at Barangay San Vicente, Gapan, San Leonardo,
Nueva Ecija. Lowest pH value at 3.64 is noted at San Ildefonso where slaughter
house contributes to loading at the creek.
Measured turbidity which refers to cloudiness or haziness of the water
caused by presence of suspended solids is high at piggery-poultry farm located
in San Ildefonso, Bulacan with reading of more than 1000 NTU. The clearer
water sampling sites are at upstream area of Barangay Bunga, Carranglan and
Barangay Sampaloc, Pantabangan (12.8 and 12.9 NTU, respectively). Oxidation
reduction potential (ORP) is another parameter measured by water checker to
determine the tendency of the sample either to gain or lose electrons when it is
subject to change by a new species. Sampling sites at Navotas fish port has
lower reduction potential which has tendency to lose electrons to new species
while Barangay San Anton, Jaen, Nueva Ecija has a gaining electron potential
from new species because it has higher ORP values.
Dissolve oxygen (DO) is important for on-field monitoring for aquatic and
other organism needing oxygen. Generally higher DO level indicates better
water quality. Sampling sites at San Antonio, Nueva Ecija and Barangay Garay
have DO of 50 mg/L. The DAO 90-34 required only a minimum DO of 5 mg/L.
More oxygen can be dissolve at lower temperature during rainy season where
oxygen concentration tends to interacts with oxygen in the air as it falls.
Total dissolved solids (TDS) measures the water content of all inorganic
and organic substances in a molecular and iodized form which is related to
salinity. TDS and salinity results are parallel to sampling site along the coastal
area. Municipalities of Sasmuan and Masantol-Macabebe have higher
measured TDS and salinity. Along the main Pampanga River only Masantol and
Macabebe have distinct saline reading while Apalit has minimal reading.
Total suspended solids (TSS) in all sites during the wet and dry seasons
are less than 1 mg/L which is below the DAO 90-34 criterion for Class A
(50mg/L). The concentrations obtained for nitrate, total phosphorous and heavy
metals are presented and discussed lengthily in Attachment 4 while the values
from colliforms are provided in Attachment 5.
Considering colliform results from two seasons, only four sites passed the
safe criterion of DENR. Among them, three sites are located upstream of
Pampanga River from Barangay Bunga to Barangay R. Padilla in Carrangalan
down to Pantabangan dam outlet in Barangay Sampaloc, Pantabangan, Nueva
3-13
Ecija. However, these same sites failed in heavy metals assessments. On the
other hand, water samples taken at Arayat Bridge (Pampanga) also passed the
safe level for colliform but nitrate loading is considerably high although still within
the threshold for class C.
Considering Class C category, all sampling sites within the Pampanga
River Basin are discharging nitrate and total phosphorous within the allowable
level. Considering a strict criteria for Class SB, all sites failed in the overall
water quality rating during the wet season. During the dry season, another site
(site 15- Batangay Garay, Angat, Bulacan) passed the water quality while the
rest failed in one or more parameters.
A summary of the water quality in terms of the biological and chemical
analyses of nitrate, total phosphorous and heavy metals particularly lead,
arsenic, chromium, cadmium, mercury, cobalt and nickel is presented in Maps
3-6 and 3-7. In as much as a water body must meet all the criteria of each
applicable parameter 100 percent of the time to maintain its designated
classification, results from this study confirms the poor water quality from
Pampanga River as reported in 2005.
This suggests that surface water from the Pampanga River draining into
Manila Bay must be periodically monitored and specific mitigating actions be
undertaken at targeted sites to minimize nutrients, colliforms and heavy metals
loading into the Bay.
C. Pollutant Loading
Nutrient loading in terms of nitrate and total phosphorous is presented in
Table 3-4. The seasonal and locational variability for both nutrients are
presented lengthily in Attachment 4. Based on the river discharges and the
average concentrations at the different sampling sites, the top five major
contributors to nitrate loading are identified in the following locations:
1) Site 16 - Apalit, Pampanga
2) Site 10 - Arayat, Pampanga
3) Site 6 – Jaen, Nueva Ecija
4) Site 7 – San isidro, Nueva Ecija
5) Site 4 – Mayapyap, Cabanatuan City
Although they are the leading contributors, nitrate loadings are within the
threshold for river class C as provided by DAO 90-34. These results are
consistent with earlier findings from measured values in six major rivers of
Pampanga River Basin as reported in Sandoval, et al. (2002). From this study,
nutrient loading contribution from croplands to the Manila Bay System was
regarded to be minimal and below the threshold for River Class C.
About 8.9 km from Manila Bay (Site 26- Barangay Sagrada, Masantol,
Pampanga) annual nitrate load is estimated at 2,849.41 mt. At this point, the
3-14
nitrate loading is beyond the allowable loading for class SB based on the Asian
water quality criterion.
On sources of pollution, earlier study by Samar, et al. (2012) associated
nitrate loading to chemical fertilizer use, with the Pampanga River Basin having
the greatest nitrate loading (from intensive rice cultivation and from sugarcane
farms) compared to the Pasig-Marikina River Basin, Bataan and Cavite
Watersheds. This study is limited, providing only an indirect estimate of nitrate
loading. A direct method to identify the origin of nitrate loading to the Bay is
through the use of multiple stable isotopes which is provided in Attachments 6, 7
and 8.
At site 26, total phosphorous loading into the Bay is estimated at 358.25
metric tons. Leading contributors are as follows:
1) Site 16 - Apalit, Pampanga
2) Site 12 - San Luis, Pampanga
3) Site 25 - San Pedro, Sasmuan, Pampanga.
3-15
Map 3-6. Surface water quality within and nearby the Pampanga River
Basin, wet season, 2012
Map 3-7. Surface water quality within and nearby the Pampanga River
Basin, dry season, 2013
3-16
Table 3-4.
Annual nitrate and total phosphorus loading from Pampanga River Basin into Manila Bay, 2012-2013
Final
code
1a
1b
3
4
6
7
8
10
11
12
13
15
16
18
19
24
25
26
A
C
B
E
Location
Non-point sources:
Barangay Bunga, Carranglan, Nueva Ecija
Barangay R. Padilla, Carranglan, Nueva Ecija
Barangay Sampaloc, Pantabangan, Nueva Ecija
Barangay Mayapyap, Cabanatuan City
Jaen, Nueva Ecija
San Isidro, Nueva Ecija
Gapan-San Leonardo, Nueva Ecija
Arayat, Pampanga
NIA Dam, San Miguel, Bulacan
San Luis, Pampanga
BahayPari, Candaba, Pampanga
Garay, Angat, Bulacan
Apalit, Pampanga
Poblacion, Guiguinto, Bulacan
Barangay Catmon, Santa Maria, Bulacan
Masantol, Pampanga
San Pedro, Sasmuan, Pampanga
Sagrada, Masantol, Pampanga
Point sources:
Dumpsite, Cabanatuan City
Piggery Farm, San Ildefonso, Bulacan
Slaughter house, San Ildefonso, Bulacan
Piggery-chicken farm, San Jose Del Monte City
Discharge
(cms)
Annual nitrate load
(mt)
Annual total
phosphorous load
(mt)
0.0105
0.7153
0.0671
53.7075
49.9444
38.5550
14.6353
58.9556
12.1917
55.2933
20.0100
14.2744
154.9625
2.7001
0.4808
1.3238
12.4551
215.6889
0.47
8.91
0.46
1,486.76
2,073.89
1,606.88
463.66
3,173.41
140.62
884.38
291.74
114.16
3,527.13
33.64
3.03
20.56
57.47
2,849.41
0.00
0.10
0.01
10.99
10.75
50.99
36.69
32.64
7.31
130.11
28.00
4.19
166.82
6.44
9.27
4.54
52.68
358.25
0.0229
0.0525
2.2500
0.0011
173.64
0.81
10.87
0.02
0.16
1.16
24.88
0.02
3-17
IV.
Summary and Recommendations
In general, the surface water quality of Pampanga River remains poor
considering laboratory analyses from two seasons covering 14 parameters physical, biological, nutrients and heavy metals.
The study proved the usefulness of the watershed approach for strategic
sampling and analysis in order to identify critical areas contributing to pollution
loading into the Manila Bay. It identified five critical locations where major
contributions to nitrate loading occur and where area-based strategic action
plans can be pursued, namely:
1)
2)
3)
4)
5)
Site 16 - Apalit, Pampanga
Site 10 - Arayat, Pampanga
Site 6 – Jaen, Nueva Ecija
Site 7 – San isidro, Nueva Ecija
Site 4 – Mayapyap, Cabanatuan City
At 8.9 km from Manila Bay (Site 26- Barangay Sagrada, Masantol,
Pampanga). Pampanga River contributed an annual nitrate load of 2,849.41
metric tons which surpassed the allowable loading for class SB based on the
ASEAN marine water quality criterion. Additionally, Pampanga River (Site 26)
contributed a total phosphorous loading of 358 metric tons a year which
exceeded the threshold for limited algal growth. Critical contributors of
phosphorous loading are:
1) Site 16 - Apalit, Pampanga
2) Site 12 - San Luis, Pampanga
3) Site 25 - San Pedro, Sasmuan, Pampanga.
In the light of the above findings on pollution loadings and water quality, a
review of the DAO 90-34 may be necessary to harmonize with international
criteria and to update classification of water bodies considering not only intended
uses but impact to receiving body of water. Also, periodic monitoring would be
essential and area-based action plans be developed, with strong LGU
participation and support from sectoral groups.
3-18
References
Arellano, B.P., Flores, A.B. and Fajardo, T. M. Present land Use and Vegetation.
IN: Bureau of Soils and Water Management-Department of Agriculture.
2012. Assessment of Non-Point Source Pollution from Croplands of
Manila Bay System.
Department of Environment and Natural Resources. 1990. Administrative Order
No. 34. Revised Water Usage and Classification/ Water Quality Criteria.
Jacinto, G. S., San Diego-McGlone, M. L., Velasquez I. B., and Smith, S. V. 1998.
N and P Budget of Manila Bay, Philippines.
River Basin Control Office. Plans and Programs of River Basin Control Office
relative to Water resources Management and River Basin Management.
Retrieved
January
28,
2014
from
http://www.wepa-db.net/pdf/0710philippines/8_RBCO.pdf
Samar, E.D., Arellano, B.P., Flores, A.B. and Talavera, I.M. 2012. Assessment
of Anthropogenic Sources of Pollution from Croplands of Manila Bay
System. IN: Bureau of Soils and Water Management-Department of
Agriculture. 2012. Assessment of Non-Point Source Pollution from
Croplands of Manila Bay System.
Sandoval, T.S., Reños, E.B., Anida, A.H., Estabillo, P.P., Raquepo, C.M. and De
Mata, L.D., 2012. Water Quality Assessment on Nutrients/ Pollution
Loading into Manila Bay System.IN: Bureau of Soils and Water
Management-Department of Agriculture. 2012. Assessment of Non-Point
Source Pollution from Croplands of Manila Bay System.
3-19
ATTACHMENT 4
Table of Contents
Page
I.
II.
III.
IV.
Abstract
Introduction
Methodology
A. Sampling and Analysis
1. Nitrate in Water
2. Heavy metals in Water
3. Nutrients in water
B. Comparison of Measured Concentrations relative to the Prescribed
Criteria
Results and Discussion
A. Nitrate-Nitrogen
B. Total Phosphorus
C. Heavy Metals
D. Other Nutrients in Water
E. Surface Water Quality
Summary and Conclusion
References
4-1
4-3
4-3
4-3
4-4
4-4
4-4
4-5
4-5
4-9
4-11
4-17
4-18
4-18
4-19
List of Figures
4-1
Nitrate-Nitrogen in water, Pampanga River Basin, 2012-2013
4-5
4-2
Nitrate and total phosphorous in water upstream and
downstream of Pampanga River for the wet and dry season, 2012-2013
4-7
4-3
Dumping of wastes under Apalit bridge, Pampanga
4-7
4-4
Total phosphorous in water, Pampanga River Basin, 2012-2013
4-9
4-5
Dumping of solid and liquid wastes from piggery, urban dwellers into
bodies of water
4-10
4-6
Concentrations of heavy metals in water at Nueva Ecija sites, 20122013
4-13
4-7
Concentrations of calcium, magnesium, sodium and potassium in
water at upstream and downstream, Pampanga River Basin, 2012-2013
4-17
4-8
Concentrations of zinc, copper, iron, and manganese in water at
upstream and downstream, Pampanga River Basin, 2012-2013
4-18
4-i
List of Tables
Page
4-1
Water quality criteria for nutrients and heavy metal pollutants for
different classifications
4-4
4-2
Comparative concentration of nutrients and heavy metals in water at
upstream and downstream of Pampanga River Basin, 2012-2013
4-6
4-3
Heavy metal concentration in water and sediment, Manila Bay
4-13
4-4
Ranges of concentrations of calcium, magnesium, sodium, potassium,
zinc, copper, iron and manganese at watersheds of Pampanga River
Basin, 2012-2013
4-17
List of Maps
4-1
Nitrate concentration from water samples within the sub-watersheds of
Pampanga River Basin, wet season, 2012
4-8
4-2
Nitrate concentration from water samples within the sub-watersheds of
Pampanga River Basin, dry season, 2013
4-8
4-3
Total phosphorus concentration from water samples within the subwatershed of Pampanga River Basin, wet season, 2012
4-12
4-4
Total phosphorus concentration from water samples within the subwatershed of Pampanga River Basin, dry season, 2013
4-12
4-5
Lead in water samples from non-point sources within the subwatersheds of Pampanga River Basin, 2012-2013
4-15
4-6
Arsenic in water samples from non-point sources within the subwatersheds of Pampanga River Basin, 2012-2013
4-15
4-7
Cadmium in water samples from non-point sources within the subwatersheds of Pampanga River Basin, 2012-2013
4-15
4-8
Chromium in water samples from non-point sources within the subwatersheds of Pampanga River Basin, 2012-2013
4-15
4-ii
4-9
List of Maps
Page
Mercury in water samples from non-point sources within the subwatersheds of Pampanga River Basin, wet season, 2012
4-16
4-10 Cobalt in water samples from non-point sources within the subwatersheds of Pampanga River Basin, dry season, 2013
4-16
4-11 Nickel in water samples from non-point sources within the subwatersheds of Pampanga River Basin, dry season, 2013
4-16
List of Appendix Table
4-1
Concentrations of nitrate and total phosphorus in water samples
collected from non-point and point sources within the watersheds of
Pampanga River Basin, 2012-2013
4-21
4-iii
ATTACHMENT 4
NUTRIENTS AND HEAVY METALS ASSESSMENT IN THE
PAMPANGA RIVER BASIN, PHILIPPINES
1
Samar, E.D., 2Estabillo, P.P., 3Collado, M.B., 4Anida, A.H., and 5Flores, A.B.
Abstract
This study aims to assess the surface water quality within the Pampanga River Basin and the
pollution in terms of siting and the concentrations of nutrients and heavy metals that drain finally into
the Manila Bay. Surface water samples from non-point sources along the Pampanga River were
collected for two seasons. Additionally, water samples were collected from point sources from within
and nearby the watershed to serve as reference values representing forestry, croplands, fisheries,
livestock and domestic uses.
Nitrates value in water were determined using Ion chromatography method and heavy metals
such as lead, cadmium, chromium, arsenic, mercury and nickel were determined using Inductively
Coupled Plasma Atomic Emission Spectrometer method. Using the Atomic Absorption Spectroscopy,
the following nutrients were analyzed, namely: total phosphorous, calcium, magnesium, sodium,
potassium, zinc, copper, iron and manganese.
-1
On surface water quality, laboratory analysis showed the presence of nitrate as NO 3 in water
throughout the 249.2 km stretch of Pampanga River. Nitrate loading was evident from the forestry
areas down to the extensive agricultural areas although all concentrations for the two seasons are
below the allowable limit of 10mg/L for Class C (DAO 90-34). Almost all sampling sites failed to meet
the ASEAN marine water quality criterion of 0.06 mg/L for nitrate. The Pampanga River contributed
directly to the phosphorous loading into the Bay considering concentrations near the river mouth at
0.67 and 0.09 ppm during the wet and dry seasons, respectively.
Small-scale mining has contributed to high concentrations of lead, arsenic, chromium and
cadmium in the upstream of Pampanga River. Among point sources, dumpsite contributes the most to
pollution considering high content of nitrate, total phosphorous, lead, arsenic, chromium and cadmium
from its effluent.
Waste management particularly near the river mouth is critical to reduce further levels of
nitrate, total phosphorous and heavy metals. Periodic monitoring of local government units would be
vital as well as shifting from open dumpsite to controlled dumpsite to reduce further pollution at the
Bay.
Keywords: Pollution, heavy metals, nitrate, total phosphorous, Pampanga River Basin
I. Introduction
The quality of Philippine waters is prescribed by the Department of
Environment and Natural Resources’ Administrative Order 90-34. Water shall be
1
Edna D. Samar, Project Leader and Agricultural Center Chief IV, Bureau of Soils and Water Management
Perla P. Estabillo, Senior Agriculturist, Bureau of Soils and Water Management
3
Mario B. Collado, Engineer IV, Bureau of Soils and Water Management
4
Alan H. Anida, Agriculturist II, Bureau of Soils and Water Management
5
Andrew B. Flores, Computer Programmer II, Bureau of Soils and Water Management
2
4-1
maintained in a safe and satisfactory condition according to the best usage.
Classifications are arranged in the order of protection required with Classes AA and
SA having generally the most stringent water quality for fresh surface waters and
marine/coastal waters, respectively; and Classes D and SD waters have the least
stringent water quality. In the light of the Writ of Continuing Mandamus (Velasco,
2010), it is essential to evaluate surface water quality from the perspective of Class
SB which is required by Supreme Court from government agencies to restore water
quality of Manila Bay into Recreational Water Class 1 - areas regularly used by the
public for bathing, swimming and skin diving. Also, Class SB as Fishery Water Class
1 is intended as spawning areas for milkfish and similar species.
Among substances that may cause risks to human health are nitrogen
compounds at different oxidation states (ammonia nitrogen, nitrite and nitrate
nitrogen). Water contamination by N compounds is increasing and becomes a global
problem due to its large and diverse origin which is associated particularly through
drinking water. Nitrates in water can cause severe illness in infants and domestic
animals. Common sources of excess nitrate identified as reaching lakes and streams
include septic systems, animal feed lots, agricultural fertilizers, manure, industrial
waste waters, sanitary landfills, and garbage dumps (Minnesota Pollution Control
Agency, 2008).
The level of phosphorous in body of water has become a growing concern
too. Total phosphorus (TP) is the measure of all the forms of phosphorus, dissolved
or particulate that is found in a sample. Under natural conditions, phosphorous is
typically scarce in water. Increased loading of phosphorous into many freshwater
systems is attributed to human activities. This can cause water pollution by
promoting excessive algae growth particularly in lakes. Water quality can be further
impaired when bacteria consumed dead algae and use up dissolved oxygen
suffocating fish and other aquatic life. Point sources of phosphorous in water include
municipal waste treatment plants, industrial discharge and large confined livestock
operations. Non-point sources, on the other hand, includes soil erosion and water
runoff from cropland, lawns and gardens, home waste treatment system, livestock
pastures and even forest. Urban areas may produce significant non-point source
phosphorous runoff due to over application of fertilizer to lawns and gardens
Heavy metals dissolved in water have also become critical issues of concern.
Heavy metals are highly reactive, bio-accumulative and extremely toxic elements
above maximum limits. Their ill effects are reported in various literatures. Lead (Pb)
may cause multiple endoctrine effects as those associated with renal dysfunctions
and male infertility (Piato, et al., 2011). Arsenic exposure is linked to skin cancer as
well as liver, lung, kidney and bladder cancer (Smith, et al., 1997). Chromium (Cr) as
hexavalent chromium can be toxic and many years of exposures to it could result to
allergic dermatitis (US EPA). Cadmium (Cd) has cumulative effect and highly toxic in
all chemical forms. It accumulates in plant cells (Canadian Council of Ministers of the
Environment). Mercury (Hg) is reported as total mercury in water and plant tissues.
Mercury compounds are highly toxic and have long retention in animal cell. It bioaccumulates in kidney and liver and can cause permanent brain damage. Cobalt can
accumulate to toxic levels in the liver, kidney, pancreas, and heart, as well as the
skeleton and skeletal muscle. Cobalt has been found to produce tumors in animals
and is likely a human carcinogen as well. High exposure to nickel can result to skin
4-2
irritation and hypersensitivity (WHO, 2007). Nickel is a dietary requirement for many
organisms but this may be toxic in larger doses. Phosphate fertilizers contain traces
of nickel. Nickel restrains the growth of algae at concentrations between 0.5 to
10ppm. Fishes are less susceptible depending on the species.
At Manila Bay, PEMSEA (2006) identified the pollutants to consist of nitrate,
organophosphate and heavy metals but their origin are not known. Identifying where
these pollutants came considering surface runoff from the upstream to downstream
and the sources of pollution (i.e. croplands, livestock, etc.) is a big challenge.
Considering the transect of the Main Pampanga River, this study identifies the sites
where pollution were observed to provide the baseline for area-based action
planning in order to address pollution at points of origin and thus minimize further
pollution of the Bay.
In terms of concentrations, the Bay-wide monitoring undertaken by PEMSEA
(2006) reported nitrate & orthophosphate as pollutants of Manila Bay with observed
values above 0.06 and 0.015mg/L, respectively based on ASEAN marine water
quality criteria.
This study aims to assess the surface water quality within the Pampanga
River Basin and the pollution in terms of the siting and the concentrations of nutrients
and heavy metals that drain finally into the Manila Bay.
II. Methodology
A. Sampling and analysis
The selection of sampling sites is provided in Attachment 1. Water samples
were collected from November 26 to December 12, 2012 for the wet season and
from March 5 to May 7, 2013 for the dry season. A total of 31 and 38 water samples
were collected for the wet and dry seasons, respectively. Within the watersheds of
Pampanga River Basin, 23 sites were collected with water samples during the wet
season and 29 sites during the dry season. Of which, two are point sources of
pollution representing fishpond and dumpsite. Seven additional sites nearby the
watershed were collected with water samples as reference for livestock and
domestic sources of pollution
All water samples were collected according to the Standard Operating
Procedure set by the DENR for water quality determination (EMB, DENR, 2008).
Water samples were analyzed as follows:
1. Nitrate in water by Ion Chromatography
Nitrate in water by Ion Chromatography was performed and analyzed by the
Research and Analytical Services-Natural Sciences Research Institute of University
of the Philippines, which is ISO certified. Dionex Ion Chromatograph System 1000
equipped with a conductivity detector was used.
4-3
2. Heavy metals in water by Inductively-Coupled Plasma (ICP) Atomic Emission
Spectrometer (AES)
Heavy metals in water particularly lead, arsenic, chromium, cadmium,
Mercury, cobalt and nickel were analyzed. Mercury was analyzed during the wet
season only while cobalt and nickel were analyzed during the dry season only
because of limitations in the laboratory services.
Samples collected in the wet season were analyzed by ICP-AES at the Plant
and Soil Division - Plant Tissue Analysis Laboratory of the Philippine Coconut
Authority. Samples collected during the dry season were analyzed at Inductively
Coupled Plasma Mass Spectrometry Laboratory of the National Institute of
Geological Services of the University of the Philippines (UP-NIGS) because of the
equipment breakdown at the PCA. When the UP-NIGS equipment also broke down,
the remaining re-sampling were submitted to Intertek Testing Service, a DENR
accredited laboratory.
3. Nutrients in water using the Atomic Absorption Spectroscopy (AAS)
The following nutrients were analyzed at BSWM using the AAS, namely: total
phosphorous, calcium, magnesium, sodium, potassium, zinc, copper, iron and
manganese.
B. Comparison of measured concentrations relative to the prescribed criteria
To determine whether the sampling site failed or passed the criterion,
measured values were compared to the prescribed criterion from national and
international sources. The DENR-DAO 90-34 provides the water quality criteria for
nitrate, phosphate and heavy metals pollutants for specific classifications – Classes
B, C and D for fresh surface water and Class SB for coastal and marine waters
(Table 4-1). Class B is intended for primary contact recreation, Class C for fishery
water and Class D for irrigation.
Table 4-1. Water quality criteria for nutrients and heavy metal pollutants for different
classifications
Parameter
Fresh Surface Water
Unit
Class B
Class C
Class D
10
--
mg/L
Not
required
0.2
0.4
--
mg/L
mg/L
mg/L
mg/L
mg/L
0.05
0.01
0.05
0.05
0.002
0.05
0.01
0.05
0.05
0.002
0.10
0.05
0.10
0.50
0.002
Coastal/
Marine Water
Class SB
Nutrients:


Nitrate as
Nitrogen
Phosphate as
Phosphorous
mg/L
Heavy metals:





Arsenic
Cadmium
Chromium
Lead
Mercury (Hg)
0.05
0.01
0.10
0.05
0.002
Source: DENR DAO 34, s. 1990
4-4
The ASEAN marine water quality criteria of 0.06mg/L for nitrate and of
0.015mg/L for organophosphate were also considered in the assessment of sites.
Similarly, the relationship between total phosphorous (Total P) and growth of algae
was considered (Bloom, n.d.)
< 0.02 ppm Total P - Little algal growth
> 0.02 ppm Total P - Accelerated algal growth
In the case of the World Health Organization, it provides the following
standards for drinking water:
o Zinc
– 5 mg/L
o Copper
– 1 mg/L
o Magnesium – 50 mg/ L
o Calcium
– 75 mg/L
o Iron
– 0.1 mg/L
III. Results and Discussions
A. Nitrate-Nitrogen
Maps 4-1 and 4-2 present the concentration of nitrate for two seasons from
the upstream to downstream of the Pampanga River Basin. Laboratory analysis
showed the presence of nitrate as NO3-1 in water throughout the 249.2 km stretch of
Pampanga River (Appendix Table 4-1). The maps reflect nitrate loading from the
forestry areas down to the extensive agricultural areas (croplands including
livestock/poultry and fishery) although all concentrations for the two seasons are
below the allowable limit of 10mg/L for Class C (DENR, DAO 90-34). From the 27
sampling sites, nitrate ranged from 0.05 to 1.94 mg/L during the wet season and
0.02 to 1.69 mg/L during the dry season (Figure 4-1).
ASEAN
marine
water
quality
criterion
of 0.06
mg/L.
Figure 4-1 - Nitrate-Nitrogen in water, Pampanga River Basin, 2012-2013
While all of the 23 sites during the wet season had NO3-1 concentrations
within the allowable limit prescribed in the DENR DAO 90-34 for fresh surface water,
only two sites passed the ASEAN marine quality criterion of 0.06mg/L, namely:
4-5
•
•
Site 14 - Diversion Dam, Barangay Tibagan, Bustos Bulacan, which is about
42 km from the river mouth.
Site 25 - San Pedro River, Barangay San Pedro, Sasmuan, Pampanga, which
is 16.5 km from the river mouth.
During the dry season, all of the 27 sites (non-point) showed NO3-1 values
within the DENR criteria of 10mg/L for Class C. Six of these passed the ASEAN
criterion of 0.06mg/L (Map 4-2). However, sites 14 and 25 are not among them.
Table 4-2 compares the observed values at upstream and downstream during
the wet and dry seasons. Upstream at Barangay Bunga, Caranglan, Nueva Ecija
(site 1), nitrate in water showed lower concentration during the wet season than the
dry season. The heavy downpour dilutes the nitrate from the watershed into the
Bay. On the contrary, downstream at Sapang Makawayan, Masantol-Macabebe (site
27) which is about 0.8 km from the river mouth, nitrate was higher during the wet
season than the dry season. Nitrate traverses 12 sampling points before reaching
the downstream passing through tributaries of the Coronel River, Peñaranda River,
Rio Chico River, San Miguel River and Maasin River. With concentration of 0.42
mg/L near the river mouth, this shows that Pampanga River contributes to nitrate
pollution beyond the allowable limits of 0.06 mg/L during the wet season. Nitrate
discharge during the dry season is within the allowable limit for the ASEAN marine
water quality.
Table 4-2. Comparative concentration of nutrients and heavy metals in water at
upstream and downstream of Pampanga River Basin, 2012-2013
Parameters
Criteria
Wet Season
Dry Season
Upstream
Downstream
Upstream
Downstream
1.25
0.42
1.69
0.02
0
0.67
0.04
0.09
Nutrients in water:
Nitrate (mg/L)
0.06*
TP (ppm)
0.02**
Heavy metals in water (mg/L):
Lead
0.05***
0.402
<LLD (0.002)
0.0002
0.0003
Arsenic
0.05***
0.368
<LLD (0.0001)
<MDL (0.0001)
0.0242
Cadmium
0.01***
0.36
<LLD (0.0001)
<MDL (0.0001)
0.0002
Chromium
0.10***
0.379
<LLD (0.0006)
0.0005
0.0008
Mercury
0.002***
<LLD (0.0001)
<LLD (0.0001)
<MDL (0.0001)
0.0012
0.0009
0.0051
Cobalt
Nickel
Other nutrients in water (ppm):
Calcium
13.42
16.99
31.94
152.74
2.9
6.38
12.31
37.31
5
15.1
6.82
47.03
0.2
13.46
0.65
66.39
Zinc
0.021
0.028
0.0138
0.05
Copper
0.013
0.026
T (0.006)
0.043
Iron
0.017
0.875
T (0.006)
0.144
Magnesium
Sodium
Potasium
Manganese
T – Trace;
0.006
0.417
0.013
* ASEAN marine water quality criterion; ** Bloom (undated); *** DENR DAO 90-34
0.054
4-6
At the Apalit Bridge which is about 25 km from the river mouth, nitrate
concentration is also 0.20 mg/L during the dry season. Two critical sites are
Masantol proper (site 24) and Barangay Sagrada, also in Masantol (site 26) which
discharges nitrate at concentrations of 0.50 and 0.129 mg/L, respectively. These
nitrate concentrations in 2012-2013 are higher compared to the 0.107 mg/L report by
PEMSEA in the 2006 initial monitoring of the Manila Bay.
Concentration in water
1.8
1.6
Criteria
1.4
Wet _upstream
Wet_downstream
1.2
Dry_upstream
1
Dry_downstream
0.8
0.6
0.4
0.2
NO3 ASEAN marine water
quality criterion of 0.06 mg/L.
0
Nitrate (mg/L)
TP (ppm)
TP criterion of 0.02 mg/L
(Bloom, n.d.)
Figure 4-2. Nitrate and Total Phosphorous in water upstream and
downstream of Pampanga River for the wet and dry season, 2012-2013
For point source of pollution, extremely high value of 492 mg/L was noted in
the dumpsite (site - 5) located in Nueva Ecija, which is 13 times more than the
concentrations in other domestic site nearby the watershed in the same period. If
wastes and leachate are not controlled, this result reflects that dumpsites are critical
sources of nitrate pollution into the Manila Bay. Considering the number of
dumpsites throughout the entire watershed which put pressure on nitrate pollution of
Manila Bay, periodic monitoring of water quality would be essential. Shifting from
open dumpsite to controlled dumpsite is an option. Also, local monitoring of waste
disposal would help reduce pollution at the Bay (as shown in the photo).
Figure 4-3. Dumping of wastes under Apalit bridge, Pampanga.
4-7
Map 4-1. Nitrate concentration from water samples within the
sub-watersheds of Pampanga River Basin, wet season, 2012
Map 4-2. Nitrate concentration from water samples within the
sub-watersheds of Pampanga River Basin, dry season, 2013
4-8
Within the watershed, there are 32 open dumpsites and 3 controlled
dumpsites that need monitoring:

Open dumpsite (Bulacan, Nueva Ecija, Pampanga – 24

Open dumpsite with authority to close (ATC) (Nueva Ecija, Pampanga) – 8

Controlled dumpsites with ATC (Bulacan, Nueva Ecija) – 3
Hence, proper management of the dumpsites within the Pampanga River Basin is
vital to minimize its contribution to the nitrate pollution in Manila Bay.
B. Total Phosphorous
Total phosphorous in water ranged from 0.0003 to 1.03 ppm during the wet
season and 0.001 to 2.25 ppm during the dry season (Figure 4-4). DENR, DAO 9034 prescribed 0.4mg/L in terms of phosphate as phosphorous for Class C. So far,
only two sites (sites 19 and 27) during the wet season and four sites (sites 7, 19, 21,
25) during the dry seasons have observed values more than 0.4mg/L. The ASEAN
marine water quality criterion is 0.015mg/L for organophosphate. To avoid
accelerated algal bloom, TP of not more than 0.02 ppm is desirable (Bloom, n.d.).
Maps 4-3 and 4-4 present the TP during the wet and dry seasons from the
upstream to the downstream. During the wet season, seven sites have TP of less
than 0.02 ppm, located in the upstream to midstream of the Main Pampanga River.
These sites include sites 1, 2, 3, 4 and 6, all within Nueva Ecija. Site 7 at San IsidroJaen Bridge, San Isidro, Nueva Ecija has TP of 0.02 ppm. During the dry season,
only three sites have observed TP of 0.02 ppm and below which is ideal for limited
algal growth. These are site 3 (Pantabangan Dam outlet,Barangay Sampaloc,
Pantabangan, Nueva Ecija); site 9b (Purok Sagingan Nazareth , Gen Tinio, Nueva
Ecija) and site 15 (Upstream Bustos Dam, Barangay Garay, Angat, Bulacan).
TP
criterion
of 0.02
ppm
(Bloom,
undated)
Figure 4-4. Total Phosphorous in water, Pampanga River Basin, 2012-2013
4-9
The Pampanga River contributed directly to the phosphorous loading into the
Bay considering concentrations near the river mouth at 0.67 and 0.09 ppm during the
wet and dry seasons, respectively (Figure 4-2). From Arayat down to San Luis and
Apalit up to Masantol-Macabebe, Pampanga, TP showed increasing concentration
from 0.30 to 0.67 ppm during the wet season and from 0.5 to 0.9 ppm during the dry
season, indicating that these areas towards the river mouth contribute greatly to
discharge of phosphorous into the Bay. Along the Pampanga River, only site 3 which
is located at Pantabangan Dam outlet, Barangay Sampaloc, Pantabangan, Nueva
Ecija showed TP below 0.02 ppm in both wet and dry seasons.
Compared to the initial TP monitoring in 2006 (PEMSEA) at 0.281 mg/L (1
meter depth) at the Bay particularly near the Pampanga River, there is an increased
discharge in 2012-2013 during the wet season but not during the dry season.
Aside from being a significant source of nitrate pollution, dumpsite is also a
considerable point source of TP loading, contributing as much as 70 times than the
0.02 ppm criteria ideal for limited algal growth. As point sources, piggery, chicken
and slaughter house generate TP which is about 120 times than the said loading for
limited algal growth. Similarly, domestic sources from urban wastes also generate
TP comparable to livestock and poultry wastes (Appendix Table 4-1). Uncontrolled
dumping of animal and urban wastes was observed during the sampling events as
shown in Figure 4-5.
Figure 4-5. Dumping of solid and liquid wastes from piggery, urban dwellers into bodies of water.
4-10
C. Heavy metals
Maps 4-5 to 4-8 present the concentrations in the wet and dry seasons for the
following heavy metals in water: lead, arsenic, chromium and cadmium. Results
showed that 22 sites passed the allowable limit for lead (0.05 mg/L), arsenic (0.05
mg/L), chromium (0.10 mg/L) and cadmium (0.01 mg/L) for Classes B, C and SB.
while seven sites mostly upstream of the watersheds exceeded the said criteria in
one season. Considering the limit set for Class D which is 0.4mg/L, all seven sites
have observed values more than 0.4 mg/L but not more than 0.5mg/L.
Among all sites sampled in the wet season, five of them, located mainly in the
upstream of the Main Pampanga River have measured values above the allowable
limit for lead, arsenic, chromium and cadmium. These sites are located within Nueva
Ecija, particularly:





Site 1 - Barangay Bunga, Carranglan, Nueva Ecija (249.2 km from river mouth)
Site 2 - Baluarte Bridge,Barangay R. Padilla, Carranglan, Nueva Ecija (238.6 km)
Site 3 - Pantabangan Dam outlet, Barangay Sampaloc, Pantabangan, Nueva
Ecija (208.6 km)
Site 4 - Gen Luna Bridge, Barangay Mayapyap, Cabanatuan City (139.9 km)
Site 9 - Animal Stockfarm, Barangay Nazareth, Gen Tinio, Nueva Ecija
(158.7 km)
Considering the concentrations of heavy metals upstream of Pampanga River
as shown in Figure 4-6, lead in water is about eight times the acceptable criterion of
0.05 mg/L. Arsenic in water is about seven times the acceptable criterion of 0.05
mg/L. Cadmium is about 36 times the acceptable criterion of 0.01 mg/L. On the other
hand, chromium in water is almost four times the acceptable criterion of 0.10 mg/L.
The high concentration of these heavy metals is attributed to small mining
operations in Nueva Ecija. NSCB (undated) reported that for Region 3, the
operations of small-scale mines are concentrated in the Province of Nueva Ecija.
The report cited estimate of 4,410,000 million metric tons of ore reserves deposited
in and around Palayan City and are distributed in barangays Dona Josefa, Palae and
Kabalugan. Small-scale mining covered large claims in Nueva Ecija (Israel and
Asirot, 2006). This is affirmed by the fact that House Bill 2816 intends to declare
Nueva Ecija a mining-free zone. Proponent of this bill claimed that stories that the
hills and mountains of Carranglan and Palayan City produce gold, have lured many
unscrupulous and irresponsible miners in the province with their operations. Rich
mineral deposits like copper and manganese are also found in Nueva Ecija,
especially in General Tinio, Carranglan and Pantabangan municipalities and the
upper reaches of Carranglan and Palayan City are said to contain gold.
Additionally, site 19 at Barangay Catmon, Santa Maria, Bulacan showed
concentrations above the allowable criteria for these four heavy metals during the
wet season. For the dry season, all measured values for these heavy metals are
within the allowable criteria.
4-11
Map 4-3. Total phosphorus concentration from water samples within
the sub-watersheds of Pampanga River Basin, wet season, 2012
Map 4-4. Total phosphorus concentration from water samples within
the sub-watersheds of Pampanga River Basin, dry season, 2013
4-12
Criteria - DENR DAO 90-34
Figure 4-6. Concentrations of heavy metals in water at Nueva Ecija sites, 2012-2013
As shown in Table 4-2, heavy metals in water discharged from Pampanga
River into the Bay are all within the allowable criteria considering results near the
river mouth, indicating that these heavy metals in water that traverse from upstream
are diluted along the way reaching the downstream at acceptable limit especially
during the wet season. In 2004-2005, chromium and copper at sediment (site 1) in
the Bay exceeded already the allowable criteria. Thus, an in-depth historical
sediment study using tracer isotope would be useful to validate pollution from the
entire watershed of Manila Bay.
Table 4-3. Heavy metal concentration in water and sediment, Manila Bay
Concentration in water (mg/L)
Elements
Allowable
Criteria*
0.8 km from river mouth of
Pampanga River
(2012-2013)
Wet
<LLD (0.002)
Dry
0.0003
<LLD (0.0001)
<LLD (0.0006)
<LLD (0.0001)
-
0.0242
0.0008
0.0002
0.0051
Lead
0.05
Arsenic
Chromium
Cadmium
Nickel
Copper
Zinc
0.05
0.10
0.01
* DENR DAO 90-34;
** PEMSEA (2007)
Concentration in sediment
(mg/kg)
Site 1 -Manila
Allowable
Bay (Dec.
Criteria**
2004-Jan.
2005)
75
13
80
139
40
65
200
16
65.9
124
4-13
Considering point sources of pollution during the wet season, dumpsite
contributes to high content in water of lead (0.410 mg/L), arsenic (0.365 mg/L),
cadmium (0.366 mg/L) and chromium (0.399 mg/L). These concentrations at point
sources are 8 times, 7 times, 36 times and about 4 times the allowable criteria,
respectively.
Mercury pollution emanates from small-scale mining activities. Surprisingly,
the presence of mercury in the five sites within Nueva Ecija was below the maximum
limit of detection (Map 4-9). In fact, results showed that mercury content of water
from upstream to downstream during the wet season is below the lower limit of
detection, thus safe. The DENR DAO 90-34 prescribed a maximum limit of 0.002m/L
for public health. Even at point sources – dumpsite, domestic, fishery, piggery,
slaughter house, concentration of mercury in water is below the lower limit of
detection. No analysis was done during the dry season because of changes in the
service laboratory.
In the case of cobalt (Map 4-10), most of the sampling sites showed
concentrations below the maximum limit of detection. Nine sites including the
downstream have measured values less than 0.01 mg/L. Likewise, an increasing
concentration of cobalt was noted from upstream to downstream. Cobalt in water
was below the maximum limit of detection at the upstream. Near the river mouth, a
cobalt concentration of 0.0012 mg/L was observed. Notably, point sources of
pollution – dumpsite, fishery, domestic, piggery and slaughter house are not major
contributors of cobalt in water based on level of concentrations at sources. Cobalt
comes primarily from the following:



Site 9b - Purok Sagingan Nazareth, Gen Tinio, Nueva Ecija (143.2 km from river
mouth) - 0.0010 mg/L
Site 21 - Sibul Spring , San Miguel, Bulacan (84.3 km from river mouth) - 0.0011
mg/L
Site 23 - Rio Chico Dela Pampanga River, Brgy San Roque, Lapas, Tarlac (108.7
km from the river mouth) - 0.0014 mg/L
Concentration of nickel in water is presented in Map 4-11. Results showed
that nickel content of water from all sites during dry season exhibited measured
values below the maximum limit of WHO which is 2 mg/L. Nonetheless, it is
interesting to note that nickel from upstream to downstream show increasing
concentration from 0.009 (Bunga, Caranglan, Nueva Ecija) to 0.0051 mg/L (near
river mouth - Sapang Makawayan, Masantol-Macabebe, Pampanga) during the dry
season. Increased nickel content near the river mouth comes from nearby pollutant
(within about 9 km from river mouth). Nickel content at point source in Barangay
Valle Cruz, Cabanatuan City is 0.1990 mg/L. This reflects nickel pollution by 39
times from effluent of dumpsite. Thus, dumping of garbage near the river mouth can
substantially increased nickel content in water. Also, nickel was not originally
considered during the wet season because of limitation from the service laboratory.
4-14
Map 4-5. Lead in water samples from non-point
sources within the sub-watersheds of
Pampanga River Basin, 2012-2013
Map 4-6. Arsenic in water samples from non-point
sources within the sub-watersheds of
Pampanga River Basin, 2012-2013
Map 4-7. Cadmium in water samples from non-point
sources within the sub-watersheds of
Pampanga River Basin, 2012-2013
Map 4-8. Chromium in water samples from non-point
sources within the sub-watersheds of
Pampanga River Basin, 2012-2013
4-15
Map 4-9. Mercury in water samples from non-point
sources within the sub-watersheds of
Pampanga River Basin, Wet Season, 2012
Map 4-10. Cobalt in water samples from non-point
sources within the sub-watersheds of
Pampanga River Basin, Dry Season, 2013
Map 4-11. Nickel in water samples from non-point
sources within the sub-watersheds of
Pampanga River Basin, Dry Season, 2013
4-16
D. Other Nutrients in Water
Table 4-4 presents the range of values for the other nutrients. From Table 4-2
and Figure 4-7, calcium, magnesium, sodium and potassium showed higher
concentrations near the river mouth compared to upstream particularly during the dry
season. A similar trend was observed for zinc, copper, iron and manganese (Figure
4-8).
Table 4-4. Ranges of concentrations of calcium, magnesium, sodium, potassium,
zinc, copper, iron and manganese at watersheds of Pampanga River
Basin, 2012-2013
Nutrients
Calcium
Magnesium
Sodium
Potassium
Zinc
Copper
Iron
Manganese
Wet season
Range (ppm)
1.150
27.260
0.130
15.320
0.520
57.560
0.020
42.000
0.000
0.051
0.000
0.056
0.018
1.170
0.005
0.417
Dry season
Range (ppm)
26.280
152.740
4.770
37.310
3.830
8.970
0.320
75.840
0.015
0.189
0.000
0.043
T (0.006)
0.296
0.005
1.140
Figure 4-7. Concentrations of calcium, magnesium, sodium and potassium in
water at upstream and downstream, Pampanga River Basin, 2012-2013
4-17
Figure 4-8. Concentrations of zinc, copper, iron, and manganese in water at
upstream and downstream, Pampanga River Basin, 2012-2013
E. Surface Water Quality
Considering the above discussions on nitrate, total phosphorous and heavy
metals, and the criteria enumerated in Table 4-2, only one site passed the water
quality during the wet season and another site passed the water quality during the
dry season. All the other sites failed in one or more parameters. This suggests that
surface water from the Pampanga River draining into Manila Bay must be
periodically monitored and specific mitigating actions be undertaken to minimize
nutrients and heavy metals loading into the Bay.
IV. Summary and Conclusion
Surface water traverses 249.2 km from the head water at Banga, Caranglan,
Nueva Ecija down to Sapang Makawayan, Masantol-Macabebe, Pampanga which is
about 0.8 km from the river mouth passing directly through 12 sampling points along
the Pampanga River. Chemical analyses of water samples taken during the wet and
dry seasons showed varying concentrations of nutrients (nitrate and total
phosphorous) and of heavy metals particularly lead, arsenic, chromium, cadmium,
mercury, cobalt and zinc.
Nitrate loading was evident from the forestry areas down to the extensive
agricultural areas although all concentrations for the two seasons are below the
allowable limit of 10mg/L for Class C (DENR, DAO 90-34). Almost all sampling sites
failed to meet the ASEAN marine water quality criterion of 0.06 mg/L for nitrate
considering results for two seasons. The Pampanga River contributed directly to the
phosphorous loading into the Bay considering concentrations near the river mouth at
0.67 and 0.09 ppm during the wet and dry seasons, respectively.
The upstream of Pampanga River showed high levels of heavy metals in
water – lead, arsenic, chromium and cadmium due to small-scale mining operations
in Nueva Ecija. Near the river mouth, their concentrations are within acceptable
4-18
levels. Concentrations of mercury, cobalt and nickel are below the allowable limits
especially near the river mouth.
Overall, the surface water draining from the upstream to near river mouth
failed to meet the criteria for nitrate, phosphorous and/or heavy metals based on the
ASEAN marine water quality and the DENR DAO 90-34. The use of isotopic
technique is valuable to identify the specific origin of pollution.
For point sources, dumpsite contributes the most to pollution considering high
content of nitrate, total phosphorous, lead, arsenic, chromium and cadmium from its
effluent. Solid waste and leachate must be controlled to minimize pollution at
different points along the Pampanga River. Considering the number of dumpsites
and the irresponsible dumping to rivers and creeks and other water bodies, periodic
monitoring of water quality would be essential. Shifting from open dumpsite to
controlled dumpsite is an option. Also, local monitoring of waste disposal would help
reduce pollution at the Bay.
References
American Public Health Association, 2005. Standard Methods for the Examination of
Water and Wastewater, 21st ed. ALHA Washington, DC 20005 USA.
APHA,1992. Standard Method for the Examination of Waste and Wastewater. 18 th
Ed. American Public Health Association, Washington, DC.
Black, J.A.1997. Water Pollution Technology. Reston Publishing Co., Reston, VA
Bloom, Paul R. n. d. Particulate Soil Phosphorus and Eutrophication in Lakes and
Streams. www.pca.state.mn.us/index.php/view-document.html
Carlson, R. E. and J. Simpson, 1996. A Coordinator’s Guide to Volunteer Lake
Monitoring Methods. North American Lake Management Society.
Dates, G., 1994. Monitoring for Phosphorous on How Come They Don’t Tell You
This Stuff in the Manual. Volunteer Monitor, Spring 1994.
Department of Environment and Natural Resources. 1990. Administrative Order No.
34. Revised Water Usage and Classification/ Water Quality Criteria.
Dionex. 2005. ICS-1000 Instruction Manual.
031879_02%20ICS-1000%20manual.
www.dionex.com/en-us/.../4559-
Environmental Management Bureau, Department of Environment and Natural
Resources, 2008. Ambient Water Quality Monitoring Manual.
Israel, Danilo C. and Jasminda P. Asirot. 2006. Managing Mercury Pollution from
Philippine Small-Scale Gold Mining Activities: An Economic Analysis. IN
Socio-Economic Impacts of Artisanal and Small-Scale Mining in the
Philippines. Gavin M. Hilson (Ed.)
4-19
Jacinto, G. S., San Diego-McGlone, M. L., Velasquez I. B., and Smith, S. V. 1998. N
and P Budget of Manila Bay, Philippines.
Loganathan P.2011. Nitrate Pollution and Fecal Coliform Contamination in Domestic
Wells in the Vavuniya District Sri Lanka with Special Reference to Hospital
Area, Department of Biological Science, Faculty of Applied Sciences,
Vavuniya Campus of the University of Jafina, Sri Lanka.
Minnesota Pollution Control Agency, 2008. Nutrients: Phosphorus, Nitrogen
Sources, Impact on Water Quality - A General Overview. Water
Quality/Impaired Waters #3.22 • May 2008. www.pca.state.mn.us.
Murphy, S., 2007. General Information on Phosphorous, City of Boulder/USGS
Water Quality
Monitoring.http://bcn.boulder.co.us/basin/data/COBWQ/info/TP.html.
National Statistical Coordination Board. n.d. Estimation of the Geologic Mineral
Reserve of the small-scale Gold Mines in the Philippines.
http://www.nscb.gov.ph/peenra/results/mineral/SSMineral.pdf
Pinto, A., Fernandez, A., Fernandez, R. Indic Mendez, I, Perira, S., Herdeiro, T.,
Santos, E., Machado, M., 2011. Determination of Heavy Metals and Other
Indicators in Water, Soils and Medicinal Plants from Ave Valley in Portugal
and its Correlation to Urban and Industrial Pollution. IN Mendez-Vilas, A.
(ed.), Science Against Microbial Pathogens: Communicating Current Reseach
and technological Advances.
Smith, A H Smith, C Hopenhayn-Rich, M N Bates, H M Goeden, I Hertz-Picciotto, H
M Duggan, R Wood, M J Kosnett, and M T Smith, 1997. Cancer risks from
arsenic in drinking water. Environ Health Perspective 1992
Smolen, M.D., Oklahoma Cooperative Extension Service, Division of Agricultural
Sciences and Natural Resources, Oklahoma State University
United States Environmental Protection Agency, 1983. Methods for Chemical
Analysis on Water and Wastewater, 2nd ed. U.S. Environmental Protection
Agency, Washington, DC.
United States Environmental Protection Agency. Basic Information about Chromium
in Drinking
Water.http://water.epa.gov/drink/contaminants/basicinformation/chromium.cfm
#three.
Velasco, Presbitero. 2010. The Manila Bay Case - The Writ of Continuing
Mandamus. www.scribd.com/...The-Manila-Bay-Case-The-Writ-of-ContinuingMandamus. Available in http://www.adb.org/documents/events/2010/asianjudges-symposium/default.asp.
World Health Organization, 2013.Water Quality and Health Strategy, 20132020.http://www.who.int/water_sanitation_health/publications/2013/water_qua
lity_strategy/en/
World Health Organization, 2007. Nickel in Drinking Water.
4-20
Appendix Table 4-1. Concentrations of nitrate and total phosphorus in water samples collected from non-point and point sources within the
watersheds of Pampanga River Basin, 2012-2013
Final Code
Location
NO3 (mg/L)
Wet
Dry
Total P (ppm)
Wet
Dry
Non-point sources
1a
Barangay Bunga, Carranglan, Nueva Ecija
1b
Barangay Bunga, Carranglan, Nueva Ecija
Baluarte Bridge,Barangay R. Padilla, Carranglan, Nueva Ecija
2
3
4
Pantabangan Dam outlet,Barangay Sampaloc ,
Pantabangan, Nueva Ecija
Gen Luna Bridge, Barangay Mayapyap, Cabanatuan City
1.25
0
1.690
0.04
0.67
0.140
0.01
0.03
0.38
0.070
0.004
0.01
0.13
1.670
0.0003
0.13
5
San Antonio-Cabiao Bdry, Rio Chico river, San Antonio,
Nueva Ecija
6
Jaen-San Anton Bridge, Jaen, Nueva Ecija
1.29
1.410
0.01
0.05
7
San Isidro-Jaen Bridge, San Isidro, Nueva Ecija
1.45
1.260
0.02
0.67
8
Dona Josefa Bridge, Gapan-San Leonardo, Nueva Ecija
Animal Stockfarm, Barangay Nazareth, Gen Tinio, Nueva
Ecija
1.68
0.380
0.16
0.03
9a
0.920
0.17
0.05
0.27
9b
Purok Sagingan Nazareth , Gen Tinio, Nueva Ecija
0.213
0.01
10
Arayat bridge, Arayat, Pampanga
1.94
1.560
0.03
0.05
11
Diversion Dam, Barangay Sabangan, San Miguel, Bulacan
0.73
0.020
0.03
0.11
12
Pampanga River, San Luis, Pampanga
0.68
0.360
0.15
0.06
13
Maasim river, Barangay Bahay Pari, Candaba, Pampanga
0.47
0.478
0.07
0.17
14
Diversion Dam, Barangay Tibagan, Bustos Bulacan
0.05
0.198
0.09
0.06
15
Upstream Bustos Dam, Barangay Garay, Angat, Bulacan
0.49
0.030
0.02
0.001
16
Apalit Bridge , Apalit, Pampanga
1.46
0.020
0.058
0.12
17
Labangan Bridge, Calumpit, Bulacan
18
Barangay Poblacion, Guiguinto, Bulacan
0.470
0.79
0.020
0.11
0.126
0.29
4-21
Final Code
Location
NO3 (mg/L)
Wet
Dry
Total P (ppm)
Wet
Dry
Non-point sources
17
Labangan Bridge, Calumpit, Bulacan
18
Barangay Poblacion, Guiguinto, Bulacan
0.79
0.020
0.126
0.29
19
Barangay Catmon, Santa Maria, Bulacan
0.36
0.050
1.03
2.25
20
Barangay Curva, Guimba, Guimba, Nueva Ecija
0.940
0.07
21
Sibul Spring , San Miguel, Bulacan
Boundary Bongabon-Palayan City, Coronel -Pampanga
river, Nueva Ecija
Rio Chico Dela Pampanga River, Brgy San Roque, Lapas,
Tarlac
0.840
0.75
1.420
0.05
0.450
0.05
22
23
0.470
0.11
24
Masantol proper, Masantol, Pampanga
0.51
0.500
0.22
0.07
25
San Pedro River, Barangay San Pedro, Sasmuan, Pampanga
0.05
0.250
0.23
0.44
26
Pampanga River, Barangay Sagrada, Masantol, Pampanga
near Manila Bay, Sapang Makawayan, Masantol-Macabebe,
Pampanga
0.73
0.129
0.10
0.09
0.42
0.020
0.67
0.09
A
Dumpsite, Barangay Valle Cruz, Cabanatuan City
0.63
492.000
0.30
1.42
C
Piggery Farm, San Ildefonso, Bulacan
0.52
0.478
1.20
2.42
B
Slaughter house, San Ildefonso, Bulacan
0.17
0.144
0.48
2.44
1.05
0.130
1.25
2.39
0.08
0.020
0.34
1.76
27
Point sources
D
Piggery-chicken farm, Barangay Gayagaya, San Jose Del
Monte City
Fishpond, Barangay Santo Tomas, Sasmuan, Pampanga
F
Domestic site, Diliman, Quezon City
59.70
37.500
0.17
1.45
G
Site 1, Navotas Fish Port
6.30
0.020
0.06
2.52
H
Site 2, Navotas Fish Port
10.00
0.020
0.04
2.46
I
Site 3, Navotas Fish Port
5.80
2.340
0.02
0.60
E
4-22
ATTACHMENT 5
Table of Contents
Page
I.
II.
III.
IV.
IV.
Abstract
Introduction
Review of Related Literature
Methodology
Results and Discussion
Summary
References
5-1
5-3
5-3
5-4
5-12
5-13
List of Figures
5-1
Farm waste from piggery-chicken farm
5-6
5-2
Samples taken directly at the discharge area
5-6
5-3
Water sampling at Catmon river
5-6
5-4
Piggery and poultry farm at San Ildefonso, Bulacan discharging farm
waste into the creek
5-6
5-5
Slaughter house discharging wastes into creek
5-6
5-6
Slaughter house at San Ildefonso, Bulacan
5-6
5-7
Levels of total coliform bacteria in the sampling sites as influenced
by the identified contaminants
5-10
5-8
Levels of fecal coliform bacteria in the sampling sites as influenced
by the identified contaminants
5-10
5-9
Pictures showing gas formation in Durham tubes for water samples
5-11
5-10
Relationship of the number of human population in the sampling
area with the concentration of total coliform bacteria for wet and dry
seasons, 2012-2013
5-11
5-11
Relationship of the number of human population in the sampling
area with the concentration of fecal coliform bacteria for wet and dry
seasons, 2012-2013
5-11
5-i
List of Table
Page
5-1
Correlation coefficient between the concentrations of total and fecal
coliform bacteria and the level of human population in the sampling sites.
5-12
List of Maps
5-1
Total coliform concentration from water samples within the subwatersheds of Pampanga River Basin, wet season, 2012
5-7
5-2
Total coliform concentration from water samples within the subwatersheds of Pampanga River Basin, dry season, 2013
5-7
5-3
Fecal coliform concentration from water samples within the subwatersheds of Pampanga River Basin, wet season, 2012
5-8
5-4
Fecal coliform concentration from water samples within the subwatersheds of Pampanga River Basin, dry season, 2013
5-8
5-ii
ATTACHMENT 5
TOTAL AND FECAL COLIFORM BACTERIA ASSESSMENT IN THE PAMPANGA
RIVER BASIN, PHILIPPINES
1
Palis, M.J., 2Yambot, A.O., 3Rojales, J.S., 4Gonzales, A.J., 5Allag, D.R., 6Anida,
A.H., 7Collado, M.B., and 8Samar, E.D.
Abstract
The study assesses the degree of coliform bacteria contamination in rivers and tributary
streams within the watersheds of the Pampanga River Basin during the wet and dry seasons of 20122013. Water samples were also collected from known point-sources of pollution such as livestock
farms and dumpsites within the watershed.
Results indicated that the levels of total and fecal coliform bacteria were highly variable
among sites. The colliform assessment near the river mouth shows that Pampanga River contributes
to total and fecal colliform at levels acceptable during the wet season but not during the dry season.
Only four sites passed the safe criterion of DENR.
Elevated concentrations were mostly obtained in sites characterized as point-sources of
pollution and in sites considered as croplands, but with domestic as the associated contaminant.
Concentrations of coliform bacteria were higher during the dry-season sampling and more
sites showed substantial bacterial contamination during this period when compared to the wet-season
sampling, due probably by the dilution effect of water and precipitation during the wet-season.
Keywords: colliforms, Pampanga River Basin
I. Introduction
The Pampanga River Basin is the fourth largest basin in the country. It is the
habitat to 8.17 million inhabitants (NSO, 2010) of Nueva Ecija, Bulacan, Tarlac and
Pampanga. Livestock and poultry is extensive in these four provinces. The
Pampanga River Basin is the habitat of 0.78 million backyard and 1.33 million
commercial livestock and home to 25.3 million poultry (BAS, Jan 1, 2013).
Livestock and poultry raising is a highly significant economic activity
considering that Central Luzon is among the top producers in the Philippines. In
2012, Bulacan ranked first with hog production of 223,763 representing 11.3 percent
of the total. In terms of chicken production, Bulacan, Pampanga and Nueva Ecija
1
Marcelina J. Palis, Supervising Agriculturist, Bureau of Soils and Water Management
Amy O. Yambot, Senior Science Research Specialist, Bureau of Soils and Water Management
3
Jacqueline S. Rojales, Senior Agriculturist, Bureau of Soils and Water Management
4
Alma J. Gonzales, Senior Agriculturist, Bureau of Soils and Water Management
5
Digna R. Allag, Agriculturist II, Bureau of Soils and Water Management
6
Alan H. Anida, Agriculturist II, Bureau of Soils and Water Management
7
Mario B. Collado, Engineer IV, Bureau of Soils and Water Management
8
Edna D. Samar, Project Leader and Agricultural Center Chief IV, Bureau of Soils and Water Management
2
5-1
ranked first, second and third with production of 128,406 (8.7%) 122, 644 (8.3%) and
100,798 (6.8%), In the case of duck production, Bulacan is the leading producer
followed by Nueva Ecija and Pampanga. In 2012, livestock slaughtered in abattoir
reached 1.3 million while birds dressed in plants reached 94.5 million. Due to human
activities which cause widespread pollution, the Pampanga River has shown signs of
ecological imbalance.
Contamination of Manila Bay by coliform bacteria is a concern because of
potential public-health risk (PEMSEA, 2006). The coliform group of bacteria
constitutes the principal indicator of the degree of contamination and the quality of
water bodies. This group of bacteria is composed of the total and fecal coliforms.
Total coliform bacteria are widespread in nature. All members of the total coliform
group can occur in human feces, but some can also be present in animal manure,
soil, and submerged wood and in other places outside the human body. Fecal
coliforms, a subset of total coliform bacteria, are more fecal-specific in origin.
Because the origins of fecal coliforms are more specific than the origins of the more
general total coliform group of bacteria, fecal coliforms are considered a more
accurate indication of animal or human waste than the total coliforms
(water.epa.gov/type/rsl/.../vms511.cfmNaka-cache - Katulad ). Fecal coliforms reside
in the intestinal tract, and are excreted in large numbers in feces, averaging about 50
million coliforms per gram. In fresh feces, it may attain concentrations of 109
(www.who.int/water_sanitation.../2edvol3d).
High levels of indicator bacteria can indicate the possible presence of
pathogens that cause such waterborne diseases such as gastroenteritis, bacillary
dysentery, typhoid fever, and cholera (Myers and Sylvester, 1997). The origin of
bacterial contamination can be from point or non-point sources. The primary point
source of bacterial contamination is sewage-treatment-plant outfalls. Non-point
sources are diffuse in nature and include:




Agricultural: animal waste, application of manure and biosolids to fields, crop
irrigation from contaminated storage ponds
Urban/residential: failed septic systems, pet waste, landfill leakage;
Recreational: direct discharge of water-craft sewage;
Wildlife waste (Wilhelm and Maluk, 1998).
In 2008, “concerned residents of Manila Bay” have established that the fecal
coliform content of the beaches surrounding Manila Bay ranged from 5,000
MPN/100ml to 8,000 MPN/100 ml, which far exceeds the prescribed 200 MPN/100
ml safe level for bathing and other forms of contact recreational activities
(Oposa,www.boalt.org/elq/documents/elq37_2_27_decastro_2010_0630.pdf).
This study provides baseline water quality data especially on the coliform
bacteria load of rivers and tributaries in the Pampanga watershed area that
eventually discharge water into the Manila Bay.
5-2
II. Review of Related Literature
Coliform bacteria can enter a stream through runoff that contacts fecal
material from wildlife, domesticated animals, and humans in the watershed (Steven
W. O’Neal and David N. Hollrah). It can also enter streams from illegal or leaky
sanitary sewer connections, poorly functioning septic systems, and poorly
functioning wastewater treatment plant (WWTPs) effluent. High amounts of sediment
are often related to higher levels of bacteria which can occur during high runoff
events. Bacteria are much more abundant on soils than in water (Murphy, 2007).
Storm water runoff is a significant contributor of fecal coliform pollution. During
rain events, fecal matter from domestic animals and wildlife are readily transported to
surface waters via the storm water drainage systems and/or overland flow
(www.mass.gov/.../water/.../nep...).
Mallin, et al. (2000) found that in five watersheds, fecal-indicator bacteria
concentrations were significantly correlated with watershed population, percentage
of developed land, and impervious area. Embrey (2001) also observed that fecalindicator bacteria concentrations closely corresponded to the level of human
population density in urban/ suburban watersheds.
Young and Thackston (1999) likewise found that fecal bacteria counts in
urban tributaries were much higher in sewered basins than in non-sewered basins
and in general were related to housing density, population, development, percent
impervious area, and domestic animal density.
Fecal coliform concentrations generally show positive correlations with
discharge because surface runoff from pastures, feedlots, and urban areas can
contribute sediment and associated fecal coliform to streams (Smith, 1993, Wilhelm
and Maluk, 1998). Increased discharge can also resuspend fine bottom sediments.
In a study conducted by the MB-RRA (2004), the fecal coliform
measurements in all 14 stations at the eastern part of Manila Bay exceeded the
criteria for swimming by almost 900 times. The total coliform measurements in the
same stations exceeded the criteria for non-contact recreation by almost 150 times.
The high total coliform and fecal coliform levels in rivers and coastal waters of Manila
Bay can be attributed to the voluminous sewage and domestic wastes being
discharged directly to the environment from households, hospital and other
institutions, commercial facilities and industrial establishments (PEMSEA, 2006).
III. Methodology
Water samples from non-point sources of pollution within the watershed areas
of the Pampanga River Basin were collected during the wet and dry seasons
commencing in November, 2012 and continued through May, 2013. Likewise,
samples from identified point sources of pollution were collected to provide the
reference values for specific contaminants. All sampling sites are geo-referenced.
5-3
For every sampling location and sampling event, three water samples were
obtained and submitted to the laboratory for the analysis of total and fecal coliform
bacteria. Water samples were stored in coolers with ice packs after collection and
transported to the laboratory for analysis. The required 6-hour holding time for
coliform bacteria analysis had been observed.
Laboratory analysis for the coliform bacteria was performed using Standard
Protocols (MPN Technique). A five-tube MPN determination was performed for each
of the three replicate samples collected at each site (American Public Health
Association, Standard Protocols for the Examination of Water and Wastewater, 20 th
ed.).
A series of fermentation tubes that contain Lauryl Tryptose Broth were
inoculated with the water samples and incubated for 24 hours at 35°C/ 44.5 oC. The
fermentation tubes contain inverted tubes (Durham tubes) to trap gases that are
being produced by the coliform bacteria. The temperatures of incubation are the
following:


Total coliforms - 35°C
Fecal coliforms - 44.5oC
After 24 hours, the fermentation tubes were examined for gas production.
Statistical tables for MPN were utilized to determine the density of bacteria
present with a 95% confidence interval based on the number of positive culture
tubes.
Results were correlated with the identified dominant and associated
contaminants per location. The identified contaminants are forestry, croplands,
livestock/piggery and domestic.
IV. Results and Discussion
Levels of total and fecal coliform bacteria in the sampling sites for both wet
and dry seasons are presented in Maps 5-1 to 5-4. The density of the total and fecal
coliform bacteria varied widely by location and time of sampling.
For the wet season, four sites exceeded the allowable limit of 1,000 MPN/100
ml for total colliform based on the DENR, DAO 34, s. 1990 (Map 4-1). In the same
period, three sites exceeded the allowable limit of 200 MPN/100 ml for fecal colliform
(Map 4-2). The water discharge near the river mouth of Pampanga River showed
discharge to Manila Bay of total and fecal colliform within the allowable criteria even
if some sites exceeded the prescribed limits for SB category. Critical sites are
Masantol proper, (Masantol, Pampanga - site 24) and Pampanga River, Barangay
Sagrada (Masantol, Pampanga - site 26), which are just 15 km and 8.9 km from the
river mouth with total colliform of 16,000 and 1,950 MPN/100 ml, respectively. No
fecal colliform were observed in these sites, indicating that sources of colliform are
not directly from human/ animal feces. These two sites are associated to fisheries
being the dominant contaminant and domestic as the associated contaminant. Also,
5-4
the former result is comparable to that of site C (San Ildefonso, Bulacan) which is
point source for piggery farm.
Other critical sites include Maasim river, Barangay Bahay Pari (Candaba,
Pampanga –site 13 which is 57.4 km from the river mouth) and Diversion Dam,
Barangay Sabangan (Bustos Bulacan –site 14 which is, 42 km from river mouth)
having total colliform of 2,200 and 1,595 MPN/100ml. These sites are influenced
primarily by croplands and associated to domestic use. Also, Barangay Catmon
(Santa Maria, Bulacan – site 19 which is 22 km from river mouth) is a critical site
considering livestock and domestic as dominant and associated contaminants.
Observations during water sampling showed discharges of wastes from livestock
and poultry into the creek and river (Figures 5-1 to 5-6).
For the dry season, only eight out of 25 sites passed the allowable criterion for
total colliform (Map 4-3) and 11 passed the limit for fecal colliform (Map 4-4). So far,
three sites located upstream have total fecal colliform within the acceptable level.
Notably, high levels of total and fecal colliform were observed near the river mouth
particularly Masantol, Pampanga. Almost all point sources exhibited high levels of
total and fecal colliform during the dry season.
Values obtained showed that differences in the concentrations of the coliform
bacteria are affected by season. Lower levels of the total and fecal coliform bacteria
were observed during the wet-season sampling probably because of the dilution
effect of water during the rainy season. In the same vein, higher concentrations of
the bacteria were observed during the dry-season sampling. According to a study by
the Minnesota State University, higher bacterial concentrations during the warm
summer months maybe associated with the greater nutrient and algae
concentrations during that time of the year. Nutrient and algae may support bacterial
growth (www.co.sibley.mn.us/high_island_creek_watershed/docs/FC_TMDL.pdf).
5-5
Figure 5-1. Farm waste from piggerychicken farm
Figure 5-3. Water sampling at Catmon river
Figure 5-5. Slaughter house discharging wastes
into creek
Figure 5-2. Samples taken directly at the
discharge area
Figure 5-4. Piggery and poultry farm at San Ildefonso,
Bulacan discharging farm waste into the creek
Figure 5-6. Slaughter house at San Ildefonso, Bulacan
5-6
Map 5-1. Total coliform concentration from water samples within the subwatersheds of Pampanga River Basin, Wet Season, 2012
Map 5-2. Total coliform concentration from water samples within the sub-watersheds of
Pampanga River Basin, Dry Season, 2013
5-7
Map 5-3 Fecal coliform concentration from water samples within the
sub-watersheds of Pampanga River Basin, Wet Season, 2012
Map 5-4. Fecal coliform concentration from water samples within the
sub-watersheds of Pampanga River Basin, Dry Season, 2013
5-8
Considering results from two seasons, only four sites passed the safe criterion
of DENR. Among them, three sites are located upstream of Pampanga River
traversing 40.6 km from Barangay Bunga to Barangay R. Padilla in Carrangalan
down to Pantabangan dam outlet in Barangay Sampaloc, Pantabangan, Nueva
Ecija. About 67 km from the river mouth, water samples taken at Arayat Bridge
(Pampanga) also passed the safe level for colliform.
All other sites failed in terms of total and/or fecal colliform based on
prescribed limit. Thus, LGU monitoring would be important especially for the
following sites whereby water is utilized as irrigation to extensive crop areas.
Site 11 - Diversion Dam, Barangay Sabangan, San Miguel, Bulacan
Site 14 - Diversion Dam, Barangay Tanauan, Bustos Bulacan
Site 15 - Upstream Bustos Dam, Barangay Garay, Angat, Bulacan
The densities of the total coliform bacteria and the fecal coliform bacteria as
affected by the primary and associated contaminants in the sampling sites are
likewise presented in Figures 5-7 and 5-8, respectively.
Elevated levels of the total coliform bacteria were mostly observed in areas
with point sources of pollution (letter-coded) and in croplands with domestic as the
associated contaminant. The densities of the bacteria exceeded the criterion value of
1,000 MPN/100 ml for class B fresh surface waters (DENR-DAO 34, series of 1990).
The DENR-DAO water-quality criterion for class B fresh surface water for
fecal coliform bacteria is 200 MPN/100 ml, as a mean value. Based from the results
of the analysis, water samples collected from eight sites exceeded the criterion
during the wet-season sampling, with two (2) sites (Piggery Farm- San Ildefonso,
Bulacan and Piggery-chicken Farm, San Jose del Monte) exceeding the criterion by
16x and 8x, respectively. This is not surprising, since both of these sites are
considered point sources of pollution where fecal discharges from the animals are
the primary pollutants. During the dry-season sampling, 50 percent of the sites
sampled exceeded the required safe level of fecal coliform concentrations. Among
the sites, 10 sites (Sites A, E, G, H, I, 16, 18. 19, 21 and 24) exhibited very high
concentrations of fecal coliform bacteria (16,000 MPN/100 ml), which is 80x the
required safe level for fecal coliform bacteria in class B fresh surface waters. One
site (Site 17) surpassed the water quality criterion by 69 times.
5-9
18,000.00
16,000.00
14,000.00
wet
season
MPN/100 ml
12,000.00
10,000.00
dry
season
8,000.00
6,000.00
Criterion
4,000.00
2,000.00
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
domestic
domestic
fishery
fishery
fishery
fishery
fishery
fishery
fishery
fishery
forestry
forestry
forestry
livestock
livestock
livestock
livestock
livestock
livestock
0.00
2 3 4 5 5a 6 7 8 10 11 12 13 14 16 17 18 20 21 22 23 A F D G H I 24 25 26 27 1 1a 15 C B E 9 9a 19
Site/ Dominant contaminant
Figure 5-7. Levels of total coliform bacteria in the sampling sites as infuenced by the identified contaminants
18,000.00
16,000.00
14,000.00
MPN/100 ml
12,000.00
10,000.00
wet season
8,000.00
dry season
6,000.00
4,000.00
2,000.00
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
croplands
domestic
domestic
fishery
fishery
fishery
fishery
fishery
fishery
fishery
fishery
forestry
forestry
forestry
livestock
livestock
livestock
livestock
livestock
livestock
0.00
2 3 4 5 5a 6 7 8 10 11 12 13 14 16 17 18 20 21 22 23 A F D G H I 24 25 26 27 1 1a 15 C B E 9 9a 19
Site/Dominant contaminant
Figure 5-8. Levels of fecal coliform bacteria in the sampling sites as influenced by the identified contaminants
5-10
Figures 5-9. Pictures showing gas formation in Durham tubes for water samples
18000
16000
MPN/100 ml
14000
12000
10000
8000
wet season
6000
dry season
4000
2000
0
0
20000
40000
60000
80000
number of human population, CY 2010
Figure 5-10. Relationship of the number of human population in the sampling area with the concentration
of total coliform bacteria for wet and dry seasons, 2012-2013
18000
16000
14000
MPN/100 ml
12000
10000
wet season
8000
dry season
6000
4000
2000
0
0
20000
40000
60000
80000
Number of human population, CY 2010
Figure 5-11. Relationship of the number of human population in the sampling area with the concentration
of fecal coliform bacteria for wet and dry seasons, 2012-2013
5-11
Previous studies (Mallin, et al., 2000; Young and Thackston, 1999) showed
that the concentrations of coliform bacteria are positively correlated to the density of
human population in urban/ suburban watersheds. In this study, the total number of
human population of all the barangays that drains water into the sampling area and
the concentrations of total and fecal coliform bacteria in that particular sampling site
were subjected to simple linear correlation analysis to determine whether there is an
association between the two variables. Results of the correlation analysis of the two
data sets indicated a not so strong degree of association between the level of
human population in the sampling area and the concentrations of total and fecal
coliforms based on the the computed correlation coefficients (r-value) as seen in
Table 5.2. Figures 5-10 and 5-11 show the graphical relationship of the total number
of of human population of the barangays in the sampling area and the concentrations
of total and fecal coliform bacteria. For both total and fecal coliforms, only four sites
(sites G, H, I and 16) showed close positive relationship between the two variables.
This was obtained during the dry season sampling.
Table 5.1. Correlation coefficient (r value) between the concentrations of total and
fecal coliform bacteria and the level of human population in the sampling sites.
Total coliforms
Fecal coliforms
Wet season
r= 0.421
r= 0.424
Dry season
r= 0.305
r= 0.418
V. Summary
Levels of total and fecal coliform bacteria were highly variable among sites.
The colliform assessment near the river mouth shows that Pampanga River
contributes to total and fecal colliform at levels acceptable during the wet season but
not during the dry season. Considering results from two seasons, only four sites
passed the safe criterion of DENR, three of which are located upstream. All other
sites failed to meet the prescribed limit. Thus, LGU monitoring would be important
especially for surface water utilized as irrigation to extensive crop areas and utilized
for fishery.
Elevated concentrations were mostly obtained in sites characterized as pointsources of pollution and in sites considered as croplands, but with domestic as the
associated contaminant.
Concentrations of coliform bacteria were higher during the dry-season
sampling and more sites showed substantial bacterial contamination during this
period when compared to the wet-season sampling, due probably by the dilution
effect of water and precipitation during the wet-season.
Simple linear correlation analysis between the levels of human population in
the sampling area and the concentrations of total and fecal coliform bacteria showed
a not so strong degree of association of the two variables.
5-12
References
American Public Health Association, American Water Works Association and Water
Environment Federation, 1998. Standard Methods for the Examination of
Water and Wastewater. 20th ed.
Brian Gregory and Elizabeth Frick, U.S. Geological Survey. 1994. Fecal-coliform
bacteria concentrations in streams of the Chattahoochee River
National
Recreation Area, Metropolitan Atlanta, Georgia, May–October 1994.
pubs.usgs.gov/wri/wri004139/pdf/wrir00-4139.pdf
Department of Environment and Natural Resources. Revised Water Usage and
Classification.
DENR-DAO
No.
34,
Series
of
1990.
www.emb.gov.ph/laws/water%20quality%20management/dao90-34.pdf
Environmental
Management
Bureau.
An
Overview
emb.gov.ph/mbemp/dloads/mbcs%2002mvw.pdf
of
Manila
Bay.
Interaksyon. Not Yet Sunset - Super toxic Manila Bay can be saved.
www.interaksyon.com/
Mallin, M.A., K.E. Williams, E.G. Esham, and R.P. Low, 2000. Effect of Human
Development on Bacteriological Water Qualityin Coastal Watersheds.
Ecological Applications 10(4):1047-1056. In.
Murphy,
Shiela,
2007.
General
information
cn.boulder.co.us/basin/data/NEW/info/FColi.html.
on
Fecal
National Statistics Office, 2012. Census of Population
census.gov.ph/statistics/census/population-and-housing
and
Coliform.
Housing.
Oposa, Jr. Antonio. Cleaning Up Manila Bay: Mandamus as a Tool for Environmental
Protection.
www.boalt.org/elq/documents/elq37_2_27_decastro_2010_0630.pdf
Pampanga River Basin Flood Forecasting and Warning Center. The Pampanga
River Basin System. prffwc.webs.com/thebasinsystem.htm.
Velasco, Presbitero. The Manila Bay Case - The Writ of Continuing Mandamus.
www.scribd.com/...The-Manila-Bay-Case-The-Writ-of-Continuing-Mandamus.
Water Resources Center, Minnesota State University, 2006. Fecal Coliform TMDL
Assessment for High Island Creek
and Rush River, August. 2006.
www.co.sibley.mn.us/high_island_creek_watershed/docs/FC_TMDL.pdf
Wilhelm, L.J., and Maluk, T.L., 1998, Fecal-indicator bacteria in surface waters of
the Santee River Basin and coastal drainages, North and South Carolina,
1995-98: U.S. Geological Survey Fact Sheet. FS-085-98, 6 p.
Young, K.D. and E.L. Thackston, 1999. Housing Density and Bacterial Loading in
Urban Streams, Journal of Environmental Engineering 125(12):1177-1180.
5-13
ATTACHMENT 6
Table of Contents
Page
I.
II.
III.
IV.
Abstract
Introduction
Methodology
A. Theoretical Framework
B. Study Site
C. Analytical Parameters and Methods
Results and Discussion
A. Nitrate Concentrations
B. Assessment of N Inputs
1. 15N composition of nitrate
2. 18O composition of nitrate
3. Isotopic composition of water
C. Characterization and Identification of Nitrate Sources
1. Assessment of point sources
2. Identification of dominant contaminant in non-point sources
Conclusion
References
6-1
6-2
6-2
6-5
6-5
6-5
6-5
6-6
6-6
6-7
6-8
6-11
6-11
6-13
6-14
6-15
List of Figures
6-1
Simplified diagram of the nitrogen cycle
6-4
6-2
The Kendall 15N vs. 18 O Plot for typical δ-NO3- and δ18O-NO3-
6-5
6-3
Concentration profile of nitrate in point and non –point sources
during wet and dry seasons
6-6
6-4
δ15N in nitrate of point and non-point sources during wet and dry
seasons
6-7
6-5
δ18O in nitrate of point and non-point sources during wet and dry
seasons
6-8
6-6
The δ2H and δ18O in water in relation to the LMWL during wet
season
6-9
6-7
The δ2H and δ18O in water in relation to the LMWL during dry
season
6-9
6-8
The relationship between δ18O-NO3- and δ18O-H2O for point and
non-point sources during wet season
6-10
6-i
List of Figures
Page
6-9
Relationship between δ18O-NO3- and δ18O-H2O for point and nonpoint sources during dry season
6-10
6-10
The Kendall 15N vs. 18 O plots for point sources in the wet season
6-12
6-11
The Kendall 15N vs. 18 O plots for point sources during dry season
6-12
6-12
The Kendall 15N vs. 18 O plots for non-point sources during wet
season
6-14
6-13
The Kendall 15N vs. 18 O plot for non- point sources during dry
season
6-14
6-ii
ATTACHMENT 6
NITROGEN AND OXYGEN ISOTOPES IN SOURCE IDENTIFICATION OF
NITRATES IN WATER
1
Castañeda, S.S., 2Collado, M.B., 3Estabillo, P.P., and 4Samar, E.D.
Abstract
This study assessed and identified the sources of nitrate in the Pampanga River Basin using
15
18
nitrogen and oxygen isotopes in dissolved nitrate. The δ N and δ O values were determined in
nitrate of streams, effluent, and leachate from point and non-point sources from several land uses,
namely: domestic, croplands, livestock, fishery, and forestry. Investigations were conducted in the wet
15
and dry seasons in 2012 to 2013. The range of δ N values of N sources such as croplands,
18
domestic, and livestock overlapped but the δ O values provided an additional dimension which
distinguished among animal manure, human waste (septic and sewage), and synthetic fertilizer.
Croplands did not reflect the signature of synthetic fertilizer but that of the nitrification of NH 4 fertilizer.
18
Information provided by the δ O values in meteoric water indicated that nitrification was the main
pathway for nitrate production in the study area. Characterization of the non-point N-sources based
on the isotopic fingerprints obtained from the point sources revealed that domestic, cropland,
livestock, and fishery, influenced the isotopic composition of the materials but domestic and croplands
provided the most significant influence. Livestock also contributed to a lesser extent.
Keywords: Dual O and N isotopes in nitrate Manila Bay pollution, pollutant source contribution
I. Introduction
Nutrients are needed for the growth and survival of animals, plants and other
organisms. They can be introduced to surface and groundwater by natural processes
such as atmospheric deposition, biological fixation, soil leaching, and subsequent
transport mechanisms. Industrial, agricultural, and urban development have resulted
to the excess use of fertilizers and the increase release of human and animal wastes
and have elevated the fluxes of nutrients such as nitrogen and phosphorus
containing substances into the aquatic environment. Consequently, this has caused
water quality degradation and eutrophication. The management of river systems is
an important part of water resources management, still, effective nutrient
assessment remains to be a challenge for environmental managers and policy
makers.
The basic problem in controlling nutrient loads is the difficulty to distinguish
among contributions from natural sources and various point and non-point N
sources, including fertilizers, animal waste and sewage. Identifying the source of N in
downstream reaches of surface water is complicated because, generally, N
compounds are not conservative, thus are not ideal for use as tracers.
1
Soledad S. Castañeda, Chief, Atomic Research Division, Philippine Nuclear Research Institute
Mario B. Collado, Engineer IV, Bureau of Soils and Water Management
3
Perla P. Estabillo, Senior Agriculturist, Bureau of Soils and Water Management
4
Edna D. Samar, Project Leader and Agricultural Center Chief IV, Bureau of Soils and Water Management
2
6-1
To circumvent these limitations, stable isotopes have been increasingly used
to trace various anthropogenic inputs of nitrogenous compounds in ecosystems
(Kendall et al., 2007). The use of nitrogen isotopes alone has limitations due to
overlapping signals and changes in the isotopic signal with denitrification within an
aquifer. Analysis of the oxygen isotopes and nitrogen isotopes of dissolved NO3 had
been shown to help factor out the effects of denitrification and clarify the
identification of the primary nitrate sources (Kendall and Aravena, 2000). With the
combination of O and N isotopes in nitrates, characteristic fingerprints of δ value will
be generated and therefore delineate the major sources (Kendall and Aravena,
2000).
This study involves the determination of the two nitrate isotopes to better
understand the isotopic behavior of nitrate from different sources typically found in
the Pampanga River Basin. This information could be applied to other river basins
contributing to the pollution in Manila Bay where the source of nitrate is uncertain or
needs to be verified. The results of this study will allow for more effective land use
practices designed to reduce the amount of nitrate contamination to the Manila Bay.
Moreover, the results of this study are valuable for area-based action planning and
development intended to protect human health and minimize further environmental
degradation.
II. Methodology
A. Theoretical Framework
1. Principles of Isotopic Measurements
The nitrate molecule contains nitrogen, with stable isotopes 14N and 15N, and
oxygen, with stable isotopes 16O, 17O, and 18O. Isotope ratio analysis involves
precise measurement, usually by mass spectrometry of the less abundant heavy
isotope to the more abundant light isotope, (e.g., 15N/14N, 18O/16O). This ratio (R) is
reported relative to the isotopic ratio of a reference standard. In the case of nitrogen,
the reference standard is atmospheric gas nitrogen (N2), for oxygen, the Vienna
Standard Mean Ocean Water (VSMOW). The isotopic composition is expressed in
terms of the isotopic ratio delta value, δ, defined as (Mook, 2000):
δ={ [Rsample/ Rreference] – 1} x 1000
(1)
where δ is reported in ‰ (per mil)
For the nitrogen isotopes, (15N/14N), δ 15N is used; for 18O/16O, the notation is δ 18O.
2. Isotope Fractionation
The development of sufficiently sensitive and accurate mass spectrometers
has made possible the detection of differences in chemical as well as physical
behavior of so-called isotopic molecules or isotopic compounds, i.e., of molecules
that contain different isotopes of the same element, such as HD16O and H218O.
This phenomenon is called isotope fractionation. It can occur as a change in isotopic
6-2
composition by the transition of a compound from one state to another (liquid water
to water vapor) or into another compound (carbon dioxide into plant organic carbon),
or it can manifest itself as a difference in isotopic composition between two
compounds in chemical equilibrium (dissolved bicarbonate and carbon dioxide) or in
physical equilibrium (liquid water and water vapor). The extent of isotope
fractionation during synthesis of organic compounds leaves isotopic fingerprint that
can provide clues for the identification of sources, transformation reactions, and
sinks of organic compounds in the environment (Mook, 2000).
The differences in physical and chemical properties of isotopic compounds
are brought about by mass differences of the atomic nuclei. The consequences of
these mass differences are two-fold (IAEA-IHP, 2000):
1) The heavier isotopic molecules have a lower mobility, thus have a lower
diffusion velocity and smaller collision frequency. This is one of the reasons
why, as a rule, lighter molecules react faster.
2) The heavier molecules generally have higher binding energies, consequently,
have higher heat of evaporation.
Biological processes are generally unidirectional and are good examples of
kinetic isotope reactions. Organisms preferentially use the lighter isotopic species
because of the lower energy required for breaking the bonds in these molecules,
resulting in significant fractionations between the substrate, with the heavier isotope,
and the biologically mediated product, with the lighter isotope. Kinetic isotopic
fractionations of biologically-mediated processes vary in magnitude, depending on
reaction rates, concentrations of products and reactants, environmental conditions,
and -- in the case of metabolic transformations -- species of the organism (MaymoGatel, et al., 1997).
3. Nitrogen and Oxygen Isotope Fractionation Processes Associated with Nitrate
Nitrogen occurs in several forms in natural waters, including the aqueous
species nitrate (NO3-), nitrite (NO2-), and ammonium (NH4+) and the dissolved gases,
nitrogen (N2) and ammonia (NH3). Nitrogen also occurs in organic molecules (Org-N)
that can be in dissolved or solid form. Figure 6-1 is a simplified illustration of the
nitrogen cycle showing the typical nitrogen transformations (Roadcap, et al., 2002).
The main processes that control N dynamics in ecosystems are volatilization,
fixation, assimilation, mineralization, nitrification and denitrification. These processes
commonly result in increases of δ15N in the substrate and decreases in the δ15N of
the product, unless the reactions go to completion (Kendall et al., 2007).
Fractionation mechanisms for nitrogen isotopes include volatilization of NH 3(g)
after ammonification, conversion of ammonium to nitrate during nitrification, and
conversion of nitrate to N2(g) during denitrification. The greatest amount of
fractionation in the 15N/14N ratio, up to +45‰ (AIR), is found at animal feed lots
where there is a significant amount of NH3(g) evaporation from wastes on the land
surface. There can be significant fractionation of the nitrogen isotopes during
nitrification due to the selectivity of the lighter isotopes by the microbes involved.
6-3
Figure 6–1. Simplified diagram of the nitrogen cycle
However, due to a number of factors, such as nearly complete consumption of
NH4+ to NO3 -, decreases in nitrification rates with the progression of the reaction,
and increased values of NH4+ due to volatilization, the overall δ15N of NO3- in the soil
usually ends up similar or slightly greater than that of the original NH4+ (Feigen et al.,
1974; Heaton, 1986; Kendall, 1998). Both the oxygen and nitrogen isotopes in nitrate
are fractionated during denitrification. This is a microbial reaction and the lighter
isotopes are selectively enriched in the products.
4. The coupled δ 15N - δ 18O approach
An initial step in understanding nitrate contamination in aqueous systems is
through the dual isotope approach (δ15N - δ18O) to trace the origin and nitrification
process. Nitrate is the dominant nitrogen species in aqueous systems and this may
be derived from soil organic nitrogen, synthetic fertilizer, livestock waste, sewage
effluent, and atmospheric precipitation. The use of N isotope alone does not
sufficiently distinguish between sources and transformation of nitrate due to the nonconservative behavior of nitrate during the transformation (Cravotta, 1987). By
analyzing 18O in nitrate, another dimension is obtained which provides better
information on the source of nitrate.
The isotopic compositions of the major anthropogenic sources of nitrates are
captured in the Kendall 15N vs. 18 O plot in Figure 6-2. The δ15N- NO3- ranges (x-axis)
are plotted against the δ18O ranges (y-axis) of the different nitrate sources. From this
plot, general δ15N- NO3- ranges can be assigned to the different contaminant sources
such as inorganic fertilizer, nitrogenous materials in soil, manure and septic waste.
Values obtained in this study will be similarly plotted to determine the source of
nitrate contamination in samples collected.
6-4
15
Figure 6–2. The Kendall N vs.
18
-
18
-
O Plot for typical δ-NO3 and δ O-NO3
B. Study Site
Surface water samples were collected from representative sites within the
sub-watersheds of the Pampanga River Basin. They represent the non-point sources
– that transect from the upstream to downstream of the Main Pampanga River
draining into the Manila Bay. All sampling points are geo-referenced. In each of the
sampling sites, the dominant and associated contaminants such as croplands,
livestock and poultry, forestry, fishery, and domestic were identified. This was based
on the field investigation and the land use and vegetation study of the BSWM in
2012. Additionally, water samples from point sources were collected to provide the
reference isotopic value for each type of contaminant. Attachment 3 provides the
details about the study sites.
C. Analytical Parameters and Methods
Water samples were collected and analyzed for nitrate by ion chromatography
and isotopic composition by isotope ratio mass spectrometry. Isotopic analyses
primarily included the oxygen and nitrogen isotopes of the dissolved nitrate and the
hydrogen and oxygen isotopes of water. Details of sample collection and analyses
are reported in Attachment 2.
III. Results and Discussion
A. Nitrate Concentrations
Dissolved nitrate concentrations for point and non-point sources in the wet
and dry seasons are shown in Figure 6-3. In most of the land use areas identified,
such as cropland, livestock, fishery, and forestry, the nitrate concentrations in the
water samples collected are lower than 2 mg/L. This could indicate low
mineralization of the nitrogenous compounds during the time of collection. Nitrate is
highest in the domestic dominant land use areas with concentrations reaching as
6-5
high as 60 mg/L in the wet season and almost 500 mg/L during the dry season.
Sewage input and other anthropogenic activities are the two main factors impacting
these domestic dominant areas. It should be noted that two point sources were
sampled to represent domestic waste. One was an open dumpsite for all sort of
municipal waste and another was wastewater released from a sewage treatment
plant. In the wet season, the dumpsite had a low [NO 3-] of less than 1 mg/L while
treated sewage water had a high content of [NO3-] of 60 mg/L. In the dry season,
[NO3-] in the leachate from the dumpsite increased to a high 500 mg/L. Water
released from the waste treatment plant had a [NO3-] of 35 mg/L. During the dry
season, precipitation is reduced, there was little supplemental water (or material)
from upstream and nitrification is fast due to increased temperatures. These resulted
in the increase in concentration of nitrate in the leachate from the dumpsite. The
lower concentration of nitrate in the wet season is attributed to dilution by
precipitation which is relatively low in nitrate and to lower rate of nitrification.
Figure 6-3. Concentration profile of nitrate in point and non –point
sources during wet and dry seasons
B. Assessment of N inputs
Nitrates in the Pampanga river system could be derived from various sources,
including atmospheric deposition, chemical and organic fertilizers, human waste, and
animal manure. The N isotopes of these sources have specific ranges of values due
to the processes occurring during the transformation to nitrate
1.
15
N composition of nitrate
Figure 6-4 presents the ranges of δ15N values for the point and non-point
sources collected in the wet and dry seasons. The characteristic δ 15N values for the
point sources in the wet season are as follows: cropland, 6.8‰; domestic, 7.1‰–
7.6‰; fishery, 1.3‰; slaughterhouse, 5.7‰; and forestry, 3.9‰. There was no
available δ15N value for livestock point source. Except for the domestic sources for
which it was possible to collect from two locations, the values indicated are results
from only one measurement for each source. These values indicate the potential for
identifying the different sources, although there may be an overlap between the
signature of cropland and domestic land use. The profile of 15N composition of non –
6-6
point sources in the wet season shows a large variability in the values for cropland
affected areas which indicates mixing of the different N sources. The signatures of
the point sources of domestic waste and fishery were significantly enriched in the dry
season. This is attributed to higher nitrification and volatilization rate brought about
by increased temperature. It is noteworthy from the data that the signature of animal
waste (livestock) with δ15N values of -30.9‰ to 3.0‰, is effectively distinct from that
of domestic waste, 12.9‰ to 33.3‰, although the value of -30.9‰ may be
anomalous and needs further verification. The δ15N values exhibited by the non-point
sources in the dry season make it impossible to distinguish among the different
sources.
15
Figure 6-4. δ N in nitrate of point and non-point sources
during wet and dry seasons
2.
18
O composition of nitrate
The 18O in nitrate provides additional information that is useful in the
resolution of signatures of the different sources. In Figure 6-5, the profile of
δ 18O
values of the point and non-point sources in the wet and dry seasons is shown. The
signatures of the sources in the wet season are effectively resolved with minimum
overlap between the values for cropland and domestic sources. In the wet season
where runoff is sufficient, there is a possibility of nutrient from domestic waste mixing
with cropland water. The δ18O values, with increasing enrichment, are as follows:
forestry, -1.2‰; cropland, 0.1‰, domestic, -0.1‰ to 5.0‰; animal waste
(slaughterhouse) 17.4‰ and fishery, and 22‰. However, in the dry season,
resolution is satisfactory with the δ18O values, as follows: forestry, -1.6‰; cropland,
2.7‰, domestic, 7.7‰ to 8.7‰; animal waste (livestock + slaughter house), 14.3‰
to 25.2‰; and fishery, 24.2 ‰. The δ18O values for fishery and livestock related
samples are significantly higher than that of cropland and domestic related samples,
already within the range of synthetic fertilizers. This indicates that the feeds supplied
to the animals are synthetic or have been produced using synthetic fertilizers.
Synthetic nitrogenous compounds are usually manufactured by industrial processes
using atmospheric nitrogen (δ 15N = 0‰) and atmospheric oxygen (δ 18O = 23.5 ‰),
and have δ18O values ranging from 17‰ to 25‰ (Amberger and Schimdt, 1987). In
contrast, nitrate derived from ammonium fertilizers has a lower δ 18O range, (-5 ‰ to
6-7
15‰). This range of values is what is normally observed for nitrates produced from
microbial nitrification in well oxygenated soils. The aerobic nitrification pathway from
NH4+ to NO3- results in 1/3 of the oxygen in NO3- being derived from air and 2/3
from water (Anderson and Hooper, 1983). Thus, the variation in the oxygen isotope
values for aerobic nitrification is in most cases attributed to the 18O of local meteoric
water in the area and has a relatively narrow range of variability (IAEA, 2013).
Examining the non-point sources, the values obtained for these are in good
agreement with the signature of the attributed dominant contaminant, except for the
samples attributed to fisheries which exhibit the signature of domestic waste, the
secondary contaminant identified in these areas.
18
Figure 6-5. δ O in nitrate of point and non-point sources
during wet and dry seasons
3. Isotopic composition of water
It was indicated in the preceding section that the oxygen isotopic composition
of local meteoric water influenced the δ18O value of the resulting nitrate during
microbial nitrification. The isotopic composition of water in the streams, leachate and
effluents were determined and are plotted in relation to the Local Meteoric Water
Line (LMWL) in Figures 6-6 and 6-7 in the wet and dry seasons, respectively. The
LMWL shows the correlation between the isotopic composition of hydrogen and
oxygen in local precipitation. Deviation from the line indicates mixing or isotopic
exchange with other sources such as mixing with evaporated water or mixing with
seawater as indicated in the graphs. The graphs show that some river water lie along
the LMWL, reflecting that of meteoric water, while some are slightly evaporated
(lying along the evaporation line). Samples from the aqua farm and fish port show
the effect of mixing with seawater.
Considering the samples with isotopic composition along the LMWL, i.e.,
those that have not undergone fractionation, the range of δ 18O values for meteoric
water in the area is from -3.78‰ to -8.45‰. As discussed in the preceding section, if
during nitrification, the O from these sources is incorporated without isotope
fractionation, and considering the δ18O–O2 = 23.5‰, the theoretical δ18O-NO3value for nitrification would range from +2.2 ‰ to +5.3‰.
6-8
2
18
2
18
Figure 6-6. The δ H and δ O in water in relation to the LMWL during wet season
Figure 6-7. The δ H and δ O in water in relation to the LMWL during dry season
In Figure 6-8, samples representing croplands, domestic waste and forestry
had δ O-NO3- values around these theoretical values. However, representatives of
fisheries and livestock deviated significantly from the expected trend. This indicates
that the nitrate from livestock and fisheries area is not a product of nitrification of
ammonium but mineralized directly from nitrate fertilizers which could have been
used in the production of the feeds consumed by these animals. In many cases, the
δ18O-NO3- = δ18O-H2O. This could be attributed to variability in the diffusion of O2
into the soil, and some biological processes. A similar plot is shown for the dry
season in Figure 6-9. A similar trend is noted except that enrichment in the δ 18ONO3- in some samples is observed. This is attributed to the evaporation effect on
water. Further, some samples included here are representative of aqua farm which is
reflecting the signature of marine nitrate.
18
6-9
18
-
18
-
18
Figure 6-8. The relationship between δ O-NO3 and δ O-H2O for point and non-point sources during wet season
18
Figure 6-9. Relationship between δ O-NO3 and δ O-H2O for point and non-point sources during dry season
6-10
C. Characterization and identification of nitrate sources
The δ15N-NO3- and δ18O-NO3- of the point and non-point sources were plotted
on the Kendall plot and assessed whether the values obtained in this study agree
with the general classifications by Kendall, et al. The expected N-source from the
land use areas are identified based on the values obtained for the point sources; e.g.
from livestock, the expected signature is that of animal manure; from domestic
waste, the signature for human waste; from fishery that of synthetic N; and
cropland and forest will reflect the signature from nitrification.
1. Assessment of point sources
Dissolved nitrates from streams directly affected by croplands, fishery,
forestry, livestock, and leachate from waste disposal facilities and water treatment
plant, served as point sources for the assessment of signature isotopic composition
of major contaminants in the basin. Figures 6-10 and 6-11 show the relationship
between the δ15N and δ18O values of these sources in the wet season and dry
season, respectively.
Isotopic composition of effluent water influenced by the fishpond falls on the
signature of inorganic fertilizer at a δ15N = +1.3 ‰ and δ18O = +22 ‰. It has been
proposed earlier that such signature may be coming from the feeds. Nitrogen in
fertilizer, commonly in the ammonium nitrate or anhydrous ammonia form and urea,
is derived from the industrial fixation of atmospheric nitrogen by a quantitative
process that, depending on variations in the manufacturing processes, yields
fertilizers with a δ15N- NO3- value between -4‰ and +4‰.
The signatures exhibited by the cropland and forest influenced streams fall
within the expected values for soil N. In the soil, the nitrogen bound in organic
material can mineralize, and then undergo ammonification followed by nitrification. If
ammonium was created at a sufficiently slow rate with a short residence time, there
will be minimal volatilization and the nitrification reaction will go to completion. Under
such conditions, the net fractionation is low and the resulting δ15N- NO3- value is
generally similar to that of the soil organic matter, which is typically in the range of
+4‰ to +9‰ (Heaton, 1986, Mariotti et al., 1988). Although application of inorganic
fertilizer is known of croplands and thus, cropland affected water is expected to
reflect its isotopic signature, the fertilizer nitrogen can lose its isotopic signature due
to exchange with the large mass of organic nitrogen in the soil (Heaton, 1986).
Dealy (1995) suggests a range of +3.5‰ to +7‰ as being the range of δ15N- NO3for contamination with a combined fertilizer and an organic soil nitrogen source.
Further, it has been observed (Mengis, 1999) that nitrate in surface water or even
groundwater rarely reflected the signature of synthetic fertilizers. It was explained
that nitrate from synthetic fertilizer does not behave conservatively but rather,
undergoes immobilization-mineralization cycles in the soil. During immobilization the
three original oxygen atoms, which carried the signature of synthetic fertilizer, are
removed. Subsequently, upon mineralization three new oxygen atoms are acquired,
now carrying the signature of soil N. This is not observed in the case of fishery and
livestock because the samples obtained from these sources were direct effluents
and have not been incorporated in the soil, retaining the signature of synthetic
fertilizer.
6-11
The signature obtained for the forested headwater is within the expected
values, usually low δ15N- NO3- , usually < 5‰.
15
Figure 6-10 . The Kendall N vs.
15
Figure 6-11. The Kendall N vs.
18
18
O plots for point sources in the wet season
O plots for point sources during dry season
The isotopic characteristic of point sources for livestock, including that of
slaughterhouse, representing manure, reflects δ15N- NO3- values(+2.5‰ to +6‰)
intermediate between soil organic N and animal manure. The δ 18O- NO3- is still
within the range for the upper limit of nitrification, however, as seen in the earlier
section, the values fall outside the trend expected for nitrification. The observed
isotopic N signatures are less than that typically reported in the literature for animal
6-12
waste, typically δ15N- NO3- values greater than +10‰. The range of observed values
may be again due to exchange with organic N in the soil.
The point sources for domestic waste (sewage effluent and dumpsite)
indicated δ15N- NO3 of about + 7‰.and δ18O- NO3 of 0‰ to 5‰ in the wet season. In
the dry season, enrichment in the δ15N- NO3 is observed, owing to higher rate of
volatilization. The enrichment is caused by volatilization of ammonia gas as the
organic nitrogen in the waste, mostly urea, is converted to ammonium. The degree of
δ15N- NO3- enrichment is highly dependent on the physical conditions affecting
volatilization, such as the length of time the waste is exposed directly to the
atmosphere. The isotopic enrichment from human waste tends to be less than
animal waste. Mariotti (1988) found δ15N- NO3- values between +10‰ and +13.5‰
in sewer and septic tank discharges. This study, however, obtained more enriched
values for domestic waste than that of animal waste. It is possible to identity
between the two since animal waste has a higher range of δ18O- NO3 values than
that of septic waste.
2. Identification of dominant contaminant in non-point sources
The Kendall plots for the non-point sources are presented in Figures 6-12 and
6-13 for the wet and dry seasons respectively. The samples from land use areas
identified to be affected dominantly by cropland exhibit a large variability in the δ 15NNO3 values, encompassing the ranges for ammonium fertilizer to sewage, which is
an indication of mixing of nitrate from agricultural and domestic activities. Livestock
related sources reflect the signature of nitrate fertilizer, while that of domestic related
sources match that of septic waste.
In the dry season, only a few samples were collected because some of the
streams have dried up. It is noteworthy that the areas identified as fisheries related
did not reflect the signature of the point source for fisheries. Their δ15N- NO3 values
fit within the range for ammonium nitrification and domestic waste. The livestock
samples consistently, carry the signature for inorganic fertilizer. The cropland
identified areas now exhibit variation not only in 15N composition but also in 18O. This
has been attributed earlier to strong fractionation effects of water evaporation in the
dry season as well as the different microbial processes that occur with the changes
in the riparian environment. Nonetheless, most of the non-point sources cluster
within the boundaries delineated for nitrification processes which encompasses that
of ammonium fertilizers, soil organics and domestic waste.
6-13
15
Figure 6-12. The Kendall N vs.
15
18
Figure 6-13. The Kendall N vs.
O plots for non-point sources during wet season
18
O plot for non- point sources during dry season
IV. Conclusion
The determination of the isotopic composition of nitrogen and oxygen in
nitrates has provided unique information about the sources and processes that affect
the dynamics and fluxes of nitrate in the Pampanga River Basin and into the Manila
Bay. The results corroborate the findings that the Pampanga River system is
impacted by fertilizers from croplands, effluents from sewage and open dumpsites,
and to a lesser extent, by animal waste. The signature coming from livestock activity
which consistently exhibited that synthetic nitrate fertilizer indicates a direct input
from these sources in the river system, and not from nitrification. This information
may be useful in estimating nitrate loading into the river system and consequently
into the Manila Bay.
6-14
The non-conservative nature of the isotopic composition of nitrogen as it
undergoes the different transformation in the terrestrial and aquatic environment
poses a challenge in interpreting analytical results. Conducting more elaborate
sampling and thorough characterization of known nitrate sources in a watershed has
the potential of more quantitative results in the future. Commercial fertilizers and
feeds being used by local farmers should be characterized for provenancing. The
inclusion of ammonium in the parameters measured is also recommended.
References
Amberger, A., Schmidt, H., L., 1987. Naturliche isotopengehaltevon nitrat als
indikatoren fur dessen herkunft, Geochim. Cosmochim. .Acta, 51, 2699-2705.
In: IAEA TECDOC 1695, 2013. Application of Isotope techniques for
assessing nutrient dynamics in river basins. pp.39.
Anderson, K.K., Hooper, A.B., 1983. O2 and H2O are each the source of one O in
NO2- produced from NH3 by Nitrosomonas: 15N-NMR evidence. FEBS Lett.
164, 236–240. In: Yue Fu-Jun, et al., 2013. Using dual isotopes to evaluate
sources and transformation of nitrogen in the Liao River, northeast China,
Applied Geochemistry 36, pp 1–9.
Cravotta, C. A. 1987. Use of stable isotopes of carbon, nitrogen, and sulfur to identify
sources of nitrogen in surface waters in the Lower Sesquahanna River Basin,
Pennsylvania. US Geological Survey, Branch of Information Services, Box
25286, Denver, CO. ISBN 0-607-87207-1Dealy, M.T., 1995. Investigation of
Nitrate-Nitrogen Concentrations in the Aqueous Beds Aquifer,Southeast Reno
County, Kansas. U.S. Geological Survey, Water Quality Invest. 95-01, 56 pp
In: Cravotta, C.A. 1987. Use of stable isotopes of carbon, nitrogen, and sulfur
to identify sources of nitrogen in surface waters in the Lower Susquehanna
River Basin, Pennsylvania. US Geological Survey, Branch of Information
Services, Box 25286, Denver, CO. ISBN 0-607-87207-1
Feigin, A., G. Shearer, D. H. Kohl and B. Commoner, 1974, the amount and nirogen15 content of nitrate in soil profiles from two centroal Illinois fields in a cornsoybean rotation. Soil Sci. Coc. Amer. Proc., 38, pp. 465-471.
Heaton, T.H.E., 1986. Isotopic Studies of Nitrogen Pollution in the Hydrosphere and
Atmosphere: A Review. Chemical Geology, vol. 59, pp. 87-102.
IHP/IAEA TECDOC, 2000 Vol. 1
Kendall, C. 1998. Tracing nitrogen sources and cycling in catchments. In: Kendall,
C., and J.J. McDonnell (Eds.), Isotope Tracers in Catchment Hydrology.
Elsevier Science B.V., Amsterdam, pp. 517-576, Chap. 16.
6-15
Kendall, C., Elliot, E.M., Wankel, S.D., 2007. Tracing anthropogenic inputs of
Nitrogen to ecosystems. In: Mitchener, R., Lajtha, K. (Eds.), Stable Isotopes in
ecology and environmental science, pp. 375–449.
Kendall, C., Aravena, R., 2000. Nitrate isotopes in groundwater Systems. In: Minet,
et al. 2012. Evaluating the utility of 15N and 18O isotope abundance analyses
to identify nitrate sources: A soil zone study. Water Research 46, pp. 3723 3736
Kohl, D.H., G.B. Shearer, and B. Commoner, 1971. Fertilizer Nitrogen: Contribution
to nitrate in Surface Waters in a Corn Belt Watershed. Science, vol. 174, pp.
1331-1334.
Mariotti, A., 1984. Utilisation des Variations Naturelles d'Abondance Isotopique en
15N pour tracer l'Origine des pollutions des Aquifers par les Nitrates. In:
Isotope Hydrology 1983, I.A. E.A., Vienna, pp. 605-633.
Maymo-Gatell, X., Chien, Y.T., Gosset, J.M., Zinder, S.H. Isolation of a bacterium
that reductively dichlorinates tetrachloroethene to ethene. Science 1997, 276
(5318), 1568– 1571.
Mazor, E. Applied Chemical and Isotopic Groundwater Hydrology. 1991
Meints, V.W., L.V. Boone, and L.T. Kurtz, 1975. Natural 15N Abundance in Soil,
Leaves, and Grain as Influenced by Long Term Additions of Fertilizer N at
Several Rates. J. Environmental Quality, vol. 4, pp. 486-490.
Mengis, M. et al., 1999. Multiple geochemical and isotopic approaches for assessing
groundwater nitrate elimination in riparian zones. Ground Water, 37,448-457.
In: IAEA TECDOC 1695, 2013. Application of Isotope techniques for
assessing nutrient dynamics in river basins. pp.19.
Mook, W. G. 2000. Environmental Isotopes in the Hydrological Cycle- Principles and
Application, IHP Technical Documents in Hydrology,
Vol. 1. UNESCO,
Paris
Roadcap, G. S, Hackley, K. C., Hwang, H. H. 2002. Application of Nitrogen and
Oxygen Isotopes to Identify Sources of Nitrate Report to the Illinois
Groundwater Consortium Southern Illinois University,
6-16
ATTACHMENT 7
Table of Contents
Page
I.
II.
III.
IV.
Abstract
Introduction
Methodology
A. Qualitative Assessment of Nutrient Sources
B. Isotopic Mass Balance
C. Three-Source – Two-Tracer Isotope Modeling
Results and Discussion
A. Assessment of Pollution Sources
1. Assessment of N Sources
2. Assessment of Carbon Sources
3. Characterization of POM, Sediment, and Plant from Different
Land Use Areas
B. Three – Source Two-Tracer Isotope Modeling
Conclusion
References
7-1
7-2
7-2
7-3
7-3
7-4
7-4
7-4
7-6
7-10
7-14
7-16
7-17
List of Figures
7-1
δ15N in particulate organic matter from point and non-point sources
collected in the wet and dry seasons
7-5
7-2
δ15N in surface sediment from point and non-point sources collected
in the wet season
7-6
7-3
δ15N in plant tissues from point and non-point sources collected in
the wet season
7-7
7-4
δ13C in particulate organic matter from point and non-point sources
collected in the wet and dry seasons
7-8
7-5
δ13C in sediment from point and non-point sources collected in the
wet and dry seasons
7-9
7-6
δ13C in plant tissue from point and non-point sources collected in the
wet and dry seasons
7-9
7-7
The relationship between the δ13C and δ15N values of the point
and non-point sources in POM
7-11
7-i
List of Figures
Page
7-8
The relationship between the δ13C and δ15N values of the point and
non-point sources in surface sediments
7-12
7-9
The relationship between the δ13C and δ15N values of the point and
non-point sources in plant tissues
7-12
7-10
Characterization of pollutant sources in the Pampanga River Basin
from isotopic signatures of C and N in particulate organic matter
7-13
7-11
Characterization of pollutant sources in the Pampanga River Basin
from isotopic signatures of C and N in surface sediments
7-13
7-12
Characterization of pollutant sources in the Pampanga River Basin
from isotopic signatures of C and N in plant tissues
7-14
7-13
Three-source mixing model for POM along Pampanga River during
wet and dry seasons
7-15
List of Table
7-1
Percentage contribution of the three sources of nutrients during wet
and dry seasons
7-16
7-ii
ATTACHMENT 7
ESTIMATION OF POLLUTANT SOURCE CONTRIBUTION TO THE PAMPANGA
RIVER BASIN USING CARBON AND NITROGEN ISOTOPES
1
Castañeda, S.S, 2Ramirez, J.D., 3Sta. Maria, E.J.,4Collado, M.B., and 5Samar, E.D.
Abstract
This study assessed and estimated the percentage contribution of potential pollution sources
13
in Pampanga River Basin using carbon and nitrogen isotopes as environmental tracers. The δ C and
15
δ N values were determined in particulate organic matter, surface sediment, and plant tissue
samples from point and non-point sources from several land use areas, namely domestic, croplands,
livestock, fishery, and forestry. Investigations were conducted in the wet and dry seasons (2012 and
15
2013). Some N sources do not have unique δ N and there is overlapping among different N-sources
13
type. δ C data for the N-sources provided an additional dimension which distinguished animal
manure, human waste (septic and sewage), leaf litter, and synthetic fertilizer. Characterization of the
non-point N-sources based on the isotopic fingerprints obtained from the point sources revealed that
domestic, cropland, livestock, and fishery, influenced the isotopic composition of the materials but
domestic and cropland land use provided the most significant influence. Livestock also contributed to
a lesser extent. Isotope mixing model revealed that cropland sources generally contributed the most
to pollutant loading during the wet season, from 22% to 98%, while domestic waste contributed higher
in the dry season, from 55% to 65%.
Keywords: C and N isotopes, nutrient loading, Manila Bay pollution, pollutant source contribution
I. Introduction
Nutrient loadings from various anthropogenic sources such as domestic,
livestock, and croplands, are associated to pollution of the Manila Bay (EMBDENR/UNEP, 1991; Jacinto, et al., 1998; Jacinto, et al., 2006; PEMSEA, 2007;
Samar, et al., 2011). However, there is still no concrete evidence to attribute the
loadings to these sources and to quantify their contribution to the nutrient enrichment
in the Manila Bay. While Miller, et al., (2011) initiated the conduct of the application
of stable isotope to identify sources of pollution for Manila Bay, results revealed that
information obtained from the nitrogen stable isotopes were not conclusive due to
the multiple sources of N from different river systems with varying nutrient inputs.
The said study focuses on areas nearby and offshore of Manila Bay. To address the
said limitation, this study uses multiple isotopes (C, N, O, H) for the identification of
the various sources of pollution and quantification of their contribution to pollution.
1
Soledad S. Castañeda, Chief, Atomic Research Division, Philippine Nuclear Research Institute
Jennyvi D. Ramirez, Science Research Analyst, Philippine Nuclear Research Institute
3
Efren J. Sta. Maria, Senior Science Research Specialist, Philippine Nuclear Research Institute
4
Mario B. Collado, Engineer IV, Bureau of Soils and Water Management
5
Edna D. Samar, Project Leader and Agricultural Center Chief IV, Bureau of Soils and Water Management
2
7-1
Likewise, this study focuses on the watershed approach to identify sources of
pollution from upstream to downstream of the receiving body of water.
Specifically, this report presents the results of the isotopic analyses of the Nsource materials such as particulate organic matter (POM), plant tissues, and top
soil. It aims to identify the sources of the nutrient loads and estimate the percentage
contributions of these anthropogenic sources by using stable isotopes of δ13C and
δ15N as tracers. Isotopic mass balance and fractionation are used to estimate
nutrient load contributed by multiple sources.
A mixing model is used to simulate the mixing processes and indicate which
sources dominate the mixtures (Fry, 2006). Isotope mixing models have various
applications which include trophic web studies, water sources for soils, plants, and
water bodies, geochemistry and pollution source identification. Isotopes act as
natural dyes or color that tract the circulation of elements. This application uses
mass balance equations and the distinct isotopic signatures of various sources to
determine their percentage contributions to the signature of the mixture product.
II. Methodology
A. Qualitative Assessment of Nutrient Sources
Qualitative assessment of the nutrient sources was based on isotopic
compositions of known sources reported in the literature and of the point sources
investigated in this study.
The two main sources of organic input in aquatic systems are in-situ (aquatic
derived such as algae and phytoplankton) and human derived organic matter.
However, both types of contributions can be further affected by fractionation process
and biodegradation of organic matter thus changing their isotopic signatures and
compositions (Angradi, 1993; Meyers, 1994 and Caraco et al., 1998 in Rogers,
2010). In this study, it is assumed that the isotopic composition of samples from
identified point sources which represent different land use areas and dominant
contaminants reflects the changes in the composition of transported N-bearing
materials near the N source.
It has been reported from investigations on organic materials and sediments
that in general, synthetic nitrogen (e.g. from inorganic fertilizer) can be differentiated
from human/animal waste using the δ15N values. Synthetic fertilizers have δ15N
values in the range of -2 to +2‰, while human/animal wastes have higher δ15N
values, from +3 to 20+‰ (Rogers, 2010b). As discussed in Attachment 6, the δ15N,
coupled with δ18O values from dissolved nitrates, further delineate between N from
decay of organic materials in soil and N from sewage and manure.
For carbon, the most important factor affecting its isotopic composition in
natural compounds in the biosphere is the effect of absorption and photosynthetic
fixation of CO2 by plants (Cravotta, 1997). Photosynthesis by upland trees involves a
7-2
net fractionation of about 19‰ while that of tropical grasses, including corn involves
a lower fractionation of 6‰ (Cravotta, 1997). The δ13C values of forest vegetation are
expected to be smaller than that of corn and maize due to the difference in
fractionation during photosynthesis.
Diet is the primary determinant for the carbon isotopic composition of animals
(Cravotta, 1997).
B. Isotopic Mass Balance
Isotopic compositions, expressed as δ values are additive so that the isotopic
composition of the reactant is equal to that of the product when summed in
stoichiometric proportions:
QR = QA + QB
and
δR • QR = δA •QA + δB •QB
(1)
(2)
where Q = mass and δ is the isotopic composition.
Equation 2 will apply to simple mixing of two N-containing source having
different isotopic compositions. The mixture will have an intermediate composition,
QR, depending on the relative contributions of added materials. Combining equations
1 and 2 will yield
QB = QR [(δR – δA)/( δB – δA)]
(3)
Equation 3 can be used to estimate the N load contribution of source, QB to
the measured N load at a downstream point, QR.
C. Three-Source – Two-Tracer Isotope Modeling
The number of sources that can be partitioned by isotope mixing models is
limited by the number of isotopic signatures analyzed, where with n isotope
signatures, contributions for n+1 sources can be determined. If the number of
sources exceeds n+1, then the model is mathematically underdetermined, with more
unknowns than equations and no unique solution (Phillips and Gregg, 2003)
Carbon and nitrogen stable isotope ratios were used as environmental tracers
to estimate percentage contributions of three possible anthropogenic sources of
water pollution in Manila Bay thru a three source-two tracer isotope mixing model:
(4)
7-3
(5)
(6)
where the δ’s (
and
) are the isotopic composition of the POM samples and
possible sources, while f1, f2, and f3 are the percentage contributions of domestic,
livestock, and cropland sources, respectively. These sources were considered to be
the three major contributors to the nutrient loading based on the results of the
assessment of the isotopic compositions of C and N in POMs and on the isotopic
composition of N and O in nitrates. There was some data gap in the isotopic
composition of plant tissues and surface sediments, thus, these were not used for
the modeling.
Using the isotopic composition of point sources, the following end-member
values were used for the attributed contaminant:
1) Domestic (Site A):
2) Livestock (Site E):
3) Cropland (Site 2):
and
and
and
III. Results and Discussion
A. Assessment of Pollution Sources
The pollution sources were classified into: croplands, livestock & poultry,
forestry, fishery and domestic based on the field investigation and the land use and
vegetation study of the BSWM in 2012. These pollution sources are classified as
dominant or associated contaminant. The sampling points which are all georeferenced, together with the identified dominant contaminant are indicated in Map 33 in Attachment 3. Water samples from non-point sources represent transect from
the upstream to downstream of the Main Pampanga River draining into the Manila
Bay. Additionally, water samples from point sources were collected as reference
values for specific land uses which are considered contaminants.
The profile of δ15N values measured in POM, surface sediments, and plant
tissues is shown in the box and whisker plots in Figures 7-1, 7-2, and 7-3. δ15N
data are available for the wet and dry season (2012-2013) for POM while data are
available only for the wet season for surface sediment and plant tissue.
1. Assessment of N sources
In Figure 7-1, the δ15N values in POM from the point sources are as follows:
cropland, 2.2 ‰; domestic, 2.9 ‰– 5.1‰; fishery, 1.9 ‰; livestock, 13.5 ‰ -18.3 ‰;
forestry, 3.5 ‰, and slaughterhouse, 8.2 ‰. Except for the domestic and livestock
sources for which it was possible to collect from two locations, the values indicated
are results from only one measurement for each source. This range of isotopic
7-4
values indicates a potential to distinguish different N-sources. Most noteworthy
would be that between livestock and cropland sources as well as between livestock
and domestic sources. The small difference between the isotopic composition of
cropland and domestic sources may cause some overlap.
Relating the δ15N values of the non-point sources obtained in the wet season
to that of the point sources, the influence from domestic activities to the isotopic
signature of the non-point sources is evident, particularly for cropland and fishery
related sources. These are characterized by δ15N values ranging from 0.9 ‰ to 7.6
‰ and from 1.3 ‰ to 4.4 ‰, respectively. Also noteworthy is that the signature of
livestock exhibited by the point source, with δ15N values ranging from 13.5 to 18‰ is
not reflected in the non-point sources. The isotopic signatures of the N-material in
livestock non-point source are significantly lower than 13.5‰, showing the influence
of domestic waste and slaughterhouse.
In the dry season, it was not possible to collect samples from the same
locations sampled in the wet season because of the changes in the physical
environment. Some streams have dried up and dumpsites have sprouted in some
areas. Thus, in Figure 7-1, only three point sources were sampled. The isotopic
composition of the N-material have changed to more enriched values, which could
be attributed to the contamination of these point sources from domestic wastes
which naturally exhibit higher δ15N values. Denitrification due to higher degree of
microbial activity could also lead to enrichment in the isotopic ratio of nitrogen.
15
Figure 7-1. δ N in particulate organic matter from point and non-point sources collected in the
wet and dry seasons
In surface sediments collected in the wet season (Figure 7-2), significantly
lower δ15N values in the livestock sources, 4.1 ‰ to 7.2 ‰, are obtained compared
7-5
to those found in POM. The point sources for cropland and fishery reflect values
similar to those found in POM. The non-point cropland sources tend toward more
enriched values compared to that of the point source, indicating mixing with other
contaminant source such as domestic waste.
Figure 7-2. δ15N in surface sediment from point and non-point sources collected in the wet season
The δ15N values of the different sources in plant tissue are shown in Figure 73. There are distinct differences in the isotopic composition of the point sources
sampled. In order of increasing enrichment, these are: slaughterhouse, 7.7‰;
livestock, 9.9 ‰; sewage, 13.2 ‰, forestry, 16.8 ‰, and cropland, 19.0 ‰. These
are considerably different from the isotopic compositions of the same sources in
POM and surface sediment. This indicates that plant tissues do not necessarily
reflect the isotopic composition of the N-contaminant source. The only non-point
source that had a data available were for croplands, which had a δ15N values
ranging from 12.5 ‰ to 15.8 ‰.
2. Assessment of Carbon sources
The δ13C values of the point and non-point sources in POM, sediments, and
plant tissue are shown in Figures 7-4 to 7-6. In Figure 7-4, the δ13C values in POM
from the point sources during the wet season, in order of increasing enrichment
are as follows: ‰; livestock (including the slaughterhouse), -29.6 ‰ to -27.7 ‰;
forestry, -28.4 ‰; cropland, --27.4 ‰; domestic (sewage and dumpsite), -28.8‰ to 24.7‰; and fishery, -24.7‰. Significant separation between the isotopic values of
human waste (sewage) and animal waste (represented by livestock) and between
cropland and fisheries is evident.
7-6
In the dry season, the δ13C value for domestic sources covers a wider span.
Enrichment (shifting of δ13C value to more positive value) is also observed in the
livestock source. This may be attributed to different process of microbial degradation
during the dry season where there is less dissolved oxygen for aerobic activity as
well as on the type of wastes being dumped in the dumpsite.
The isotopic values exhibited by non-point sources covers a wide span
reflecting the influence of mixing of various sources, most probably between the
identified point source and of domestic waste.
Figure 7-3. δ15N in plant tissues from point and non-point sources collected in the wet season
7-7
Figure 7-4. δ13C in particulate organic matter from point and non-point sources collected in
the wet and dry seasons
The profile of δ13C values of point and non-point sources in the wet and dry
seasons in surface sediment is shown in Figure 7-5. The 13C concentration in the
sediments are generally higher than that in the POM although similar trends in the
relative isotopic composition is evident.. In order of increasing enrichment the δ13C
values are as follows: livestock (including the slaughterhouse), -20.6 ‰ to -23.0 ‰;
cropland, -24.9 ‰; and fishery, -22.1‰. In the dry season, the isotopic values are
further enriched. The δ13C values are: livestock (including the slaughterhouse), -21.0 ‰; cropland, -21.9 ‰; and fishery, -20.2‰. The non-point sources appear to
bear the signatures of the N-sources they are attributed to.
7-8
Figure 7-5. δ13C in sediment from point and non-point sources collected in the wet and dry seasons
13
Figure 7-6. δ C in plant tissue from point and non-point sources collected in the wet and dry seasons
In Figure 7-6, the profile of δ13C values of point and non-point sources in the
wet and dry seasons in plant tissue shows depletion (more negative) in the 13C
concentration relative to that observed in POM and in sediments. In the wet season,
the δ13C values are: slaughterhouse, --30.6‰; domestic, -30.3‰; cropland, -29.8‰;
forestry, -28.0‰, and livestock, -26.9‰. The plants from the piggery farm (livestock)
and the slaughterhouse are distinctly different in signature in this case. Forest plants
also show a distinct signature from agricultural crops due to the difference in
fractionation during photosynthesis. The higher 13C concentration in forest plant than
7-9
in agricultural crops is however, not consistent with what is found in the literature
which indicates the opposite trend. A verification of the identity of plants collected is
needed to explain the observation. The δ13C value of non-point sources from
croplands reflect a combination of domestic and cropland land use.
In the dry season, samples were collected only from cropland and forestry
sources. The results show that the forestry non-point source is not reflecting the
signature of forestry land use probably because the type of plants collected were of
different type of photosynthetic pathway (C4 plants vs C3 plants)
3. Characterization of POM, sediment, and plant from different land use areas
The δ13C and δ15N values of the samples in the matrices studied from
different land use areas, in general, are different within a land use category. Further,
there is some overlapping in the isotopic signatures of the different sources; hence,
assessment using a single isotope is not very useful. The combination of multiisotopes will be more useful in characterizing the receptor materials and in attributing
the sources of pollutants.
In Figures 7-7, 7-8 and 7-9, the relationship between the δ13C and δ15N values
in POM, sediment, and plant tissues collected in the wet season, respectively, are
shown. The expected N-source from the land use areas are identified based on the
values obtained for the point sources; e.g. from livestock, the signature of animal
manure; for domestic waste, the signature for human waste; for fishery, that of
synthetic N; while cropland and forest will show organic N or soil N from fertilizers
and forest litters.
The profile of C and N isotopic compositions in particulate organic matter in
Figure 7-7 shows that it is possible to differentiate between human waste and animal
waste. The clustering of points in the two dimensional plot indicates that most of the
samples reflect the contribution of mixture of domestic waste and cropland, and to a
lesser degree, of livestock.
7-10
Figure 7-7. The relationship between the δ13C and δ15N values of the point and non-point sources in POM
In Figure 7-8, the relationship between the δ13C and δ15N values of the point
and non-point sources in surface sediments is shown. Only data for the point
sources of livestock, cropland, and fishery land use areas were available. The graph
shows that livestock signature (animal manure) is distinct from organic material in
cropland and from the signature of fishery land use area. Forest soil signature is
distinct from that of cropland soil as well. The isotopic values of samples obtained
from cropland areas vary over a wide range. One group exhibits a signature that is a
mixture of cropland and domestic waste, one of that is forest sediment, and still
another one is cropland sediment.
In Figure 7-9, point sources for cropland, livestock, domestic, and forest land
use are represented. The delineation of the isotopic signatures of these sources is
distinct. Three non-point sources from cropland areas give stronger signals from
domestic land use than from cropland use.
Based on the interpretations on the nature of the contaminants in the
representative samples in the wet season, the dominant contaminant source are
reflected on a line diagram of the Pampanga River watershed and its vicinity in
Figures 7-10, 7-11, and 7-12.
In general, it can be deduced from this
characterization that, indeed, the impact of major land use areas within the
Pampanga River Basin, such as cropland areas, domestic activities, and livestock,
could be traced along the river system. The relative contribution of these activities to
the total nutrient load from the basin will be discussed in the following section.
7-11
13
15
Figure 7-8. The relationship between the δ C and δ N values of the point and
non-point sources in surface sediments
13
15
Figure 7-9. The relationship between the δ C and δ N values of the point and
non-point sources in plant tissues
7-12
Figure 7-10. Characterization of pollutant sources in the Pampanga River Basin from isotopic
signatures of C and N in particulate organic matter
Figure 7-11. Characterization of pollutant sources in the Pampanga River Basin from isotopic signatures of
C and N in surface sediments
7-13
Figure 7-12. Characterization of pollutant sources in the Pampanga River Basin from isotopic signatures of C
and N in plant tissues.
B. Three-Source – Two-Tracer Isotope Modeling
Isotope mixing models are now widely used in studying the effects and
percentage contributions of anthropogenic sources of pollution in water bodies with
two source or three source formulation using one and two tracers, respectively
(Vargas, et al., 2011, Dittmar, et al., 2001, Zhou, et al., 2011).
The composition of particulate organic matter along Pampanga River and its
tributaries were measured using δ13C and δ15N which were used as tracers to
estimate the anthropogenic contributions from the identified sources, particularly
domestic, livestock, and croplands (Figure 7-13). In the models, the points within the
triangle were considered for quantification. Those outside the triangle, although seen
to be clustering in the vicinity of cropland and domestic use signature, could not be
quantified.
Table 7-1 shows the estimates of percentage contributions of domestic,
livestock, and cropland sources in POMs along the river and its tributaries during wet
and dry seasons for the valid points.
The results from the model are consistent with the characterization made
earlier. Sites 2 and 3 are cropland areas located upstream, still free from the
influence of domestic waste, while Site 15 is a forested land upstream. The δ15N
values of POM in these locations range from 2.2‰ to 4.3‰, indicating that nitrogen
7-14
sources from these areas are coming from fertilizers (Rogers, 2010). This is further
supported by the result of isotope mixing model wherein Site 2 has the highest
cropland contribution with 98%, followed by Site 3 and 15 with 76% and 60%
cropland contribution, respectively. On the other hand, Sites 4 and 19 with δ15N
values from 7.6‰ to 9.1‰, are indicated to be mainly affected by domestic sources
or human/animal waste. The mixing model quantifies the domestic contribution in
Sites 4 and 19 to be 46% and 52%, respectively. The δ13C values may indicate that
the POM is a mixture from two sources, terrestrial and marine or from C 3 and C4
plants. In this case, δ13C values in all sites ranging from 22.5 to 27.5‰ indicate more
of C3 terrestrial plants.
During the dry season, only two sites fell within the three source triangle of the
mixing model. The reflected contributions from domestic sources in these areas are
higher (56% to 65%) than that from agricultural activities (28% to 36%). Livestock
contributed the least at 7% to 9%.
Figure 7-13. Three-source mixing model for POM along Pampanga River during (a) wet and (b) dry season:
Domestic and cropland sources being the dominant contributors to the nutrient loading
7-15
Table 7.1. Percentage contribution of the three sources of nutrients during wet and
dry seasons
Wet Season
Site No.
Dry Season
domestic
Livestock
croplands
Domestic
livestock
croplands
2
1
0
98
-
-
-
3
7
17
76
-
-
-
4
46
7
47
-
-
-
12
-
-
-
55
9
36
15
40
0
60
-
-
-
16
41
37
22
-
-
-
17
-
-
-
65
7
28
19
52
47
1
-
-
-
IV. Conclusion
The combination of the isotopic concentrations of carbon and nitrogen in
nutrient related media was useful in elucidating the sources of nutrients in non-point
sources in the Pampanga River Basin. The isotopic data for the N-sources indicate
that animal manure, human waste (septic and sewage), leaf litter, and synthetic
fertilizer can be distinguished from each other using C and N isotopes. Some N
sources do not have unique δ15N and overlap among different N-sources type
necessitating the use of multi - isotope technique.
The study confirmed the finding from earlier studies that nutrient loadings from
anthropogenic sources such as, domestic, livestock and croplands, constitute the
major contributors. Improvement of the estimation of the contribution of these
sources can be achieved by conducting more measurements of isotopic composition
of point sources to enhance reliability of the estimations.
A more definite attribution of the sources of pollutant loading in the river basin
and quantitative assessment of the contribution of these sources will pave the way
for a more effective management and mitigation of the pollution of the Pampanga
River Basin and eventually, of the Manila Bay.
7-16
REFERENCES
Angradi, T. R. 1993. Stable carbon and nitrogen isotope analysis of seston in a
regulated rocky mountain river, USA. Regulated Rivers: Research and
Management 8: 251-270.
Caraco, N. F., G. Lampman, J. J. Cole, K. E. Limburg, M. L. Pace, and D. Fischer.
1998. Microbial assimilation of DIN in a nitrogen rich estuary: implications for
food quality and isotope studies. Marine Ecology Progress Series 167: 59-71.
Cravotta, C.A. 1987. Use of stable isotopes of carbon, nitrogen, and sulfur to identify
sources of nitrogen in surface waters in the Lower Sesquahanna River Basin,
Pensylvannia. US Geological Survey, Branch of Information Services, Box
25286, Denver, CO. ISBN 0-607-87207-1
Dittmar, T., Lara, R., and Kattner, G. 2001. River or mangrove? Tracing major
organic matter sources in tropical Brazilian coastal waters. Marine Chemistry ,
73, 253–271.
Fry, B. 2006. Stable Isotope Ecology (3rd ed.). United States of America: Springer
Science+Business Media.
Fry, B. 2003. Steady state models of stable isotopic distributions. Isot Environ Health
Stud , 39, 219–232.
Jacinto, G. S., San Diego-McGlone, M. L., Velasquez I. B., and Smith, S. V. 1998. N
and P Budget of Manila Bay, Philippines.
Jacinto, G. S., Velasquez, I. B., San Diego-McGlone, M.L., Villanoy, C. L., Siringan,
F. B., 2006. Biophysical environment of Manila Bay – Then and Now. Chapter
18. In Wolanski, W. (ed.) The Environment in Asia Pacific Harbours. 293307. Springer.
Laguna Lake Development Authority, 2005. National Water Quality Status Report.
Executive Summary.
Meyers, P. A. 1994. Preservation of elemental and isotopic source identification of
sedimentary organic matter. Chemical Geology 114: 289-302.
Miller, Todd W., Gil Jacinto, Malou Mcglone, Atsuhiko Isobe, Jun-ya Shibata, Hideki
Hamaoka and Koji Omor. 2011. Tracing Dynamics of Organic Material Flow in
Coastal Marine Ecosystems: Results from Manila Bay (Philippines) and
Kyucho Intrusion (Japan)
7-17
Partnership on Environmental Management for Seas of East Asia (PEMSEA) and
MBEMP-MBIN. 2007. Manila Bay Area: Environmental Atlas. PEMSEA
Technical Report 20.
Phillips, D., and Gregg, J. 2003. Source partitioning using stable isotopes: coping
with too many sources. Ecosystems Ecology , 136, 261–269.
Phillips, D., Newsome, S., and Gregg, J. 2005. Combining sources in stable isotope
mixing models: alternative methods. Stable Isotopes Issue , 144, 520–527.
Rogers, K. 2010. Using stable isotopes to detect land use change and nitrogen
sources in aquatic systems. IAEA Techdoc, 1-29.
Rogers, K. 2010. Detecting land-use change in near shore aquatic environments
using a stable isotopes approach. Lecture presentation (IAEA Expert Mission
for RAS/7/019: Harmonizing Nuclear and Isotopic Techniques for Marine
Pollution) at PNRI, Quezon City, November 2010.
Samar, E.D., Arellano, B.P., Flores, A.B. and Talavera, I.M. 2011. Assessment of
Anthropogenic Sources of Pollution from Croplands of Manila Bay System. IN:
Bureau of Soils and Water Management-Department of Agriculture. 2011.
Assessment of Non-Point Source Pollution from Croplands of Manila Bay
System.
Vargas, C., Martinez, R. S., Aguayo, M., Silva, N., & Torres, R. 2011. Allochthonous
subsidies of organic matter across a lake–river–fjord. Continental Shelf
Research , 31, 187–201.Zhou, Q., Xie, P., Xu, J., Liang, X., Qin, J., Cao, T.,
2011. Seasonal Trophic Shift of Littoral Consumers in Eutrophic Lake Taihu
(China) Revealed by a Two-Source Mixing Model. The Scientific World Jornal
, 11, 1442–1454.
7-18
ATTACHMENT 8
Table of Contents
Page
I.
II.
III.
IV.
Abstract
Introduction
Methodology
A. Theoretical Framework
B. Two-Source – One-Tracer Isotope Modeling
C. Field Investigations
Results and Discussion
A. δ13C of Surface Sediments as Proxy of Land Use Change
along the Pampanga River Basin
B. Contribution of Terrestrial Sources to the Nutrient Loading of
Manila Bay as Indicated in the Surface Sediments Offshore
8-1
8-2
8-2
8-2
8-3
8-4
8-4
8-5
8-7
8-8
Conclusion
References
List of Figures
8-1
Offshore sampling sites in Manila Bay
8-3
8-2
Spatial profile of δ13C from “ridge to reef” along the Pampanga
River Basin in the wet season
8-4
8-3
Spatial profile of δ13C from “ridge to reef” along the Pampanga River
Basin in the dry season
8-5
8-4
Plots of δ13C vs. C:N ratio in offshore surface sediments during wet
and dry seasons
8-6
8-5
Percentage contributions of terrestrial sources into Manila Bay
8-7
8-i
ATTACHMENT 8
ASSESSMENT OF TERRESTRIAL AND MARINE CONTRIBUTION
TO THE NUTRIENT LOADING IN MANILA BAY USING
CARBON AND NITROGEN ISOTOPES
1
Castañeda, S.S., 2Ramirez, J.D., 3Sta. Maria, E.J., and 4Samar, E.D.
Abstract
Carbon and nitrogen isotopes in surface sediments in the Pampanga River Basin and
offshore of Manila Bay were used to determine the relative contribution of terrestrial and marine
sources in the nutrient loading of Manila Bay. A linear mixing model, utilizing two sources, the marine
and terrestrial, and one isotope, C, was applied to quantify the contributions of these sources. It
shows that as much as 30 % of the organic matter deposited in the Bay comes from terrestrial
activities from the Pampanga River Basin, mostly from agriculture. The nutrient loading from the
Pampanga River Basin within the sampling period, appears to come from both C3 and C4 terrestrial
vegetation, although those signatures are masked by that of algal growth. However, the contribution
is seen in the signatures of C3 and C4 soil and riverine materials. On the Cavite side of the Manila
Bay, terrestrial contribution from the basin is evidence by the signature of C4 plants, C4 soil and
riverine materials. This may indicate poor sediment management especially in agricultural areas. The
differences in the distribution of nutrients and terrestrial input are captured in the isotopic signatures in
the sediment.
Keywords: marine and terrestrial sources of pollution, sediments as proxy, carbon isotopes
I. Introduction
Multi- isotopic analysis of materials collected from the Pampanga River Basin
including dissolved nitrates, water, surface sediments, particulate organic matter and
plant tissues provided basis for identification of the potential major source of nutrient
loading to the Manila Bay coming from the basin. This report presents the application
of the carbon and nitrogen stable isotope ratios (δ13C and δ15N ) in surface
sediments to serve as a proxy of land use change in the Pampanga River Basin and
to provide a better understanding of how these terrestrial anthropogenic sources
affect and contribute to the nutrient loading in Manila Bay.
Sediments often serve as a sinks of pollutants / nutrients that regularly
recharge overlying waters and with other favorable environmental conditions could
trigger algal blooms with negative effects. Pollutants / nutrients maybe associated
with fine sediments which then maybe assimilated or transported to various
catchments and repositories. Stable carbon isotopes are useful in estimating relative
contributions of land-derived (terrestrial) carbon and in-situ sources of carbon from
aquatic particulate organic matter, particularly in marine environments (Rogers,
1
Soledad S. Castañeda, Chief, Atomic Research Division, Philippine Nuclear Research Institute
Jennyvi D. Ramirez, Science Research Analyst, Philippine Nuclear Research Institute
3
Efren J. Sta. Maria, Senior Science Research Specialist, Philippine Nuclear Research Institute
4
Edna D. Samar, Project Leader and Agricultural Center Chief IV, Bureau of Soils and Water Management
2
8-1
2010). The stable isotope technique takes into account the differences among
natural abundances of carbon and nitrogen stable isotopes and C/N elemental ratios
in organic matter from terrigenous and marine origin (Liu et al., 2006 in Sampiao et
al., 2010).
This study applied isotope mixing model, using δ13C values, to determine the
extent of terrestrial input in a near shore marine environment where there are two
known end members, the terrestrial signature and the marine signature (Rogers,
2010).
II. Methodology
A. Theoretical Framework
Stable carbon isotope ratios have been used as an index of the relative
importance of [C3] and [C4] plants in the diet. [C3] plants include trees, most shrubs,
and grasses found in temperate areas. Such plants have low 13C/12C ratios, as a
result of discrimination against the heavier 13C isotope during Calvin, or [C3]
photosynthesis. Plants which employ the Hatch-Slack or [C4] photosynthetic pathway
are mainly tropical grasses, with higher 13C/12C ratios. Wheat, barley, oats, rice, and
most 'vegetables' are [C3] plants, whereas maize, millets and sorghum are [C4]. The
isotopic composition of body tissues derived from foods eaten in life, with bone
'collagen' isotope values representing mainly the protein component of diet
(Ambrose & Norr, 1993). Stable carbon isotope ratios in the sea are, on the whole,
enriched in 13C when compared with [C3] terrestrial ecosystems.
The aquatic or terrestrial nature of the contributing material could be reflected
on the variations of the C/N (atomic) ratios (where C/N= (%C/%N)/ (14/12)). Higher
C/N ratios (>+15) could be observed on terrestrial plants due to the many carbon
ring structures (e.g. cellulose, resins, lignin) that gives rigidity and strength to plants.
Relatively, terrestrial plants have lower nitrogen content. In comparison, aquatic
plants (e.g. algae, phytoplankton) generally have lower C/N ratio than terrestrial
plants. They have fewer carbon rings and have more of longer chain molecules of
lipids and chlorophyll, and water give these delicate plants their support (Rogers,
2010).
B. Two-Source – One-Tracer Isotope Modeling
Carbon stable isotope ratios was used as environmental tracer to estimate
proportional contributions of terrestrial and marine sources of nutrient loadings in
Manila Bay through a two source-one tracer isotope mixing model:
where the δ’s (
) are the isotopic composition of the surface sediment
samples from offshore sites (Figure 8-1), while f1 and f2 are the proportional
contributions terrestrial and marine sources, respectively. The marine end member
8-2
δ13C value was assumed from S8 in Figure 8-1 because it was the point farthest from
land among the sampling sites. The δ13C value assumed was the average of the
values obtained in the wet and dry season, δ13C = -17.4‰. This value is consistent
with that reported in literature (Silva, et al., 2011). On the other hand, the terrestrial
end member δ13C value was assumed from the most negative values obtained for
the surface sediment from the point source for
cropland area. The δ13C value
assumed was the average of the values obtained in the wet and dry season, δ 13C = 28‰, which is close to the value reported in literature (Silva, et al., 2011; Vargas, et
al., 2011; Rogers, 2010).
Proportional contributions, f1 and f2, are quantified using average values
obtained in the wet and dry seasons.
C. Field Investigations
Surface sediments from nine offshore sites (Figure 8-1) along the Manila Bay
were collected by the Environmental Management Bureau quarterly in 2012 and
2013. The sediments were analyzed for C an N concentration and isotope ratio at
the GNS Isotope Laboratory, New Zealand.
Figure 8-1. Offshore sampling sites in Manila Bay
8-3
III. Results and Discussion
A. δ13C of Surface Sediments as Proxy of Land Use Change along the
Pampanga River Basin
The evolution δ13C in surface sediments from “ridge to reef” along the
Pampanga River Basin in the wet and dry seasons is shown in Figures 8-2 and 8-3,
respectively.
From these graphs, the contribution of terrestrial sources on
approaching the coastline of Manila Bay can be estimated by a two –source one
isotope mixing model. In the wet season (Figure 8-2), the marine signature was
taken to be that of the offshore sample, S8, with δ13C = -17.4‰, while the most
negative δ13C value was taken as the terrestrial fingerprint, C = -25.9‰. It is evident
from the graph that even at around 20 km to the coast, terrestrial influence is still
significant. Using the mixing model, terrestrial contribution from the different sources
is as follows: cropland, 27-100%, forestry, 12%, livestock, 37-93%, and fishery, 5579%.
The point source for fishery is reflecting a δ13C value that is characteristic of
C4 plants, outside the marine and C3 terrestrial mixing range.
13
Figure 8-2. Spatial profile of δ C from “ridge to reef” along the Pampanga River
Basin in the wet season
In the dry season (Figure 8-3), the marine signature was taken to be still that
of the offshore sample, S8, with δ13C = -17.4‰, while the most negative δ13C value
was taken as the terrestrial fingerprint, δ13C = -30.1‰. Using the mixing model,
terrestrial contribution from the different sources is as follows: cropland, 36-100%,
forestry, 66%, livestock, 28-50%, and fishery, 22-77%.
8-4
As in the wet season, the point source for livestock is reflecting a δ13C value
that is characteristic of C4 plants, outside the marine and C3 terrestrial mixing range.
One cropland site also is within the range of δ13C value for C4 plants. Next to rice,
sugarcane, a C4 plant is one of the major crops in the Pampanga River Basin
(Arellano, et al., 2012). It is noted that terrestrial contribution during the dry season is
less than in the wet season. This could be attributed to reduced runoff during the dry
season which, consequently, brings less sediment transport downstream.
13
Figure 8-3. Spatial profile of δ C from “ridge to reef” along the Pampanga River
Basin in the dry season
B. Contribution of Terrestrial Sources to the Nutrient Loading of Manila Bay as
Indicated in the Surface Sediments Offshore
The δ13C values of surface sediments collected offshore of Manila Bay are
plotted against the C/N ratio in Figure 8-4. The plot shows that S6 and S7 are of a
different group from the other sites. S6 and S7 are more proximate to the Cavite
watershed. They exhibit higher C:N ratios and more enriched δ13C value than that of
marine origin. The range of values fall within the characteristic values for C4 plants,
C4 soil and riverine materials. These results indicate increasing land use change in
the catchment area since most of the surface sediments are coming from C 4 sources
which consist of corn, sugarcane and any warm-season crops that are now replacing
the natural plantation in the area.
8-5
Figure 8-4. Plots of δ13C vs. C:N ratio in offshore surface sediments during wet and dry seasons
The other group of offshore sediments potentially affected by the Pampanga
River Basin, based on locations, are S1, S2, S3, S4, and S9. The range of δ13C
values exhibited by these samples fall within the characteristics values for algae and
submerged plants but also bordering along that of C3 soil and riverine materials. In
the dry season, algal bloom in S2 and S5 must have significantly increased the
nitrogen load in these areas so that the C:N ratio have shifted to much lower values.
The percent contributions of terrestrial and marine sources in offshore sites
S1, S2, S3, S4, and S9 were estimated using the two-source and 1-tracer isotope
mixing model. S5, S6, and S7 were not included since they belong to a different
distribution, more likely affected by Cavite and Bataan watersheds. Terrestrial
contribution ranges from 17% to 30% where S3 has the highest terrestrial
contribution and S4 with the lowest. S1, S2, and S9 receive approximately the same
terrestrial input at 21%, 24%, and 23%, respectively. S8, its δ 13C value taken as the
8-6
reference value for marine end member, naturally has 100 % marine component.
The terrestrial contributions are shown in Figure 8-5.
Figure 8-5. Percentage contributions of terrestrial sources into Manila Bay
IV. Conclusion
This study has been useful in estimating the terrestrial input into the Manila
Bay. It shows that as much as 30 % of the organic matter deposited in the Bay
comes from terrestrial activities from the Pampanga River Basin, mostly from
agriculture. The nutrient loading from the Pampanga River Basin mainly come from
C3 terrestrial vegetation although this signature is masked by that of algal growth,
probably promoted by the nutrient loading. However, the contribution is seen in the
signature of C3 soil and riverine materials. On the Cavite side of the Manila Bay,
terrestrial contribution from the watershed is evidence by the signature of C4 plants,
C4 soil and riverine materials. This may indicate poor sediment management
especially in agricultural areas. The differences in the distribution of nutrients and
terrestrial input are captured in the isotopic signatures in the sediment.
8-7
References
Arellano, B.P., Flores, A.B. and Fajardo, T.M. 2012. Present Landuse and
Vegetation. In: Bureau of Soils and Water Management. Assessment of Nonpoint Source Pollution from Croplands of Manila Bay System.
Boon, P. I., and S. E. Bunn. 1994. Variations in the stable isotope composition of
aquatic plants and their implications for food web analysis. Aquatic Botany 48:
99-108.
Chang, K., Amano, A., Miller, T., Isobe, T., Maneja, R., Siringan, F., et al. 2009.
Pollution Study in Manila Bay: Eutrophication and Its Impact on Plankton
Community. Interdisciplinary Studies on Environmental Chemistry , 261–267.
Dittmar, T., Lara, R., & Kattner, G. 2001. River or mangrove? Tracing major organic
matter sources in tropical Brazilian coastal waters. Marine Chemistry , 73,
253–271.
Environmental Management Bureau. n.d. Manila Bay Coastal Strategy. Retrieved
November 19, 2013, from
http://www.emb.gov.ph/mbemp/dloads/mbcs%2002mvw.pdf
Fry, B. 2006. Stable Isotope Ecology (3rd ed.). United States of America: Springer
Science+Business Media.
Laguna Lake Development Authority. 2005. National Water Quality Status Report.
Executive Summary.
Kendall, C., S. R. Silva, and V. J. Kelly. 2001. Carbon and nitrogen isotopic
compositions of particulates organic matter in four large river systems across
the United States. Hydrological Processes 15: 1301-1346.
PEMSEA. 2006. Sustainable Development and Management of Manila Bay: A Focus
on Water Quality. Policy Brief , 2 (2).
Rogers, K. 2010. Using stable isotopes to detect land use change and nitrogen
sources in aquatic systems. IAEA Techdoc 1-29.
Rosenfeld, J. S., and J. C. Roff. 1992. Examination of the carbon base in southern
Ontario streams using stable isotopes. Journal of the North American
Benthological Society. 11: 1-10.
Rounick, J. S., M. J. Winterbourn, and G. L. Lyon. 1982. Differential utilization of
allochthonous and autochthonous inputs by aquatic invertebrates in some
New Zealand streams: a stable carbon isotope study. Oikos 39: 191-198.
8-8
Sampiao, L., Freitas, R., Maguas, C., Rodrigues, A., Quintino, V. 2010. Coastal
sediments under the influence of multiple organic enrichment sources: An
evaluation using carbon and nitrogen stable isotopes. Mar. Poll. Bull. 60
(2010) 272-282.
Silva, N., Vargas, C., & Prego, R. 2011. Land–ocean distribution of allochthonous
organic matter in surface sediments of the Chiloe ´ and Ayse ´n interior seas
(Chilean Northern Patagonia). Continental Shelf Research , 31, 330–339.
Vargas, C., Martinez, R. S., Aguayo, M., Silva, N., & Torres, R. 2011. Allochthonous
subsidies of organic matter across a lake–river–fjord. Continental Shelf
Research , 31, 187–201.
Winterbourn, M. J., J. S. Rounick, and A. G. Hildrew. 1986. Patterns of carbon
resource utilization by benthic invertebrates in two British river systems: a
stable carbon isotope study. Archives of Hydrobiology 107: 349-361.
Zhou, Q., Xie, P., Xu, J., Liang, X., Qin, J., Cao, T., et al. 2011. Seasonal Trophic
Shift of Littoral Consumers in Eutrophic Lake Taihu (China) Revealed by a
Two-Source Mixing Model. The Scientific World Jornal , 11, 1442–1454.
8-9