Environmental impacts of domestic
and imported commodities in U.S. economy
By
Sangwon Suh — Gjalt Huppes — Helias Udo de Haes
Centre of Environmental Science (CML), Leiden University,
P.O. Box 9518, 2300 RA-NL, Leiden, The Netherlands
To be presented at
the 14 International Conference on Input-Output Techniques
th
at the Université du Québec à Montréal, Canada
October 10 - 15, 2002
Corresponding author: Sangwon Suh
Centre of Environmental Science (CML), Leiden University,
P.O. Box 9518, 2300 RA-NL, Leiden, The Netherlands
suh@cml.leidenuniv.nl
Abstract
Environmental impacts of domestic and imported commodities in US economy are analysed
using 1996 US input-output table and various environmental statistics. The objective of this
study is 1) to characterise the environmental impacts of intermediate and consumer products in
U.S. and 2) to identify the relationship between environmental impacts and reliance on foreign
commodities using Life Cycle Impact Assessment (LCIA) methods. A total of 1170 different
pollutants to air, water and soil environment were compiled and analysed with a total of 92
different impact assessment methods for more than 15 environmental impact categories
including global warming, eutrophication, ozone layer depletion, photochemical oxidant
creation and various eco- and human toxicological impacts. 1996 U.S. input-output table was
used to calculate direct and indirect environmental impacts of each commodity as well as the
amount of foreign production.
The result clearly shows that different impact assessment methods result in rather consistent
trends for larger samples of environmental intervention, like current study, even though the
underlying models and number of pollutants covered by each method differs. For most of the
impact categories, coal, metallic ores, iron and steel products are found to be highly
environmental impacts-intensive per unit monetary value. As a total direct polluter, wholesale
trade, electric utilities, iron and steel and industrial other chemicals were found to be the most
important commodities. Considering the indirect impacts, constructions, food and kindred
products, health services and motor vehicles are environmentally the most important
commodities in U.S. Furthermore, it is shown that inequalities in environmental impacts of
products are rather large, so that a small number of products are responsible for majority of the
total impact of each impact category.
The relationship between relative reliance on foreign production and their relative share total
environmental impact is analysed using environmental trade balance (ETB), pollution terms of
trade index (PTTI) and regression study. ETB and PTTI result shows that, for major toxic
impact categories, except for human toxic impacts, U.S. was a net problem exporter. Important
vehicles of environmental problem imports and exports in U.S. are identified as well. The
regression study shows that environmental impact is not the main reason for an industry
relocated in foreign countries.
Keywords: environmental impacts, IOA, LCIA, trade
3
1. Introduction
In setting environmental policy direction, characterisation of environmental impacts associated
with economic activities is often of great importance. Such a characterisation involves
characterising both production system and environmental mechanisms, which include complex
interactions within and between various socio-economic and environmental agents such as
technology, price, trade, consumption, regulation, fate and exposure, background concentration
of pollutants, environmental carrying capacity, etc. Thus a proper characterisation of
environmental impact of an economic activity requires knowledge on both social science and
natural science for economic side and environmental side, respectively. A good balance is,
however, not always the case. Economics literatures tend to focus more on economics side by
limiting environmental factors within a few pollutants or energy requirements only, which may
overlook possible problem shifting towards other persistent pollutants and environmental
problems. Whilst literatures in natural science and engineering provide comprehensive
treatments on environmental side, they, on the other hand, often tend to be remained within
rather confined process analysis limiting their application for macro level environmental policy
making.
This story seems to be equally applicable to the current debate on trade and environment.
Analyses from the economics side, due also to the problem of data lack in many cases, often
assume that environmental impacts can be represented by a few pollutants, such as SO2 and
NOX, leaving thousands of other pollutants untouched (see eg. Dasgupta et al., 2002; Cole,
2000; Suri and Chapman, 1998; Grossman and Krueger, 1995). 1 Even those exceptionally
comprehensive studies on environmental variables like Wheeler (2001), Mani and Wheeler
(1997) and Hettige et al. (1992) stop at the total weight of pollutants although the differences in
environmental impact of pollutants with the same mass can easily reach factor 106. One of the
tools in environmental systems analysis that seem promising for the questions on environment
and trade, Life Cycle Assessment (LCA) does not provide the whole picture based on a
complete economic system boundary either (see eg. Lave et al, 1995 and Hendrickson et al.,
1998 for critiques). Therefore, a harmonised framework as well as an operational database
where rich findings from both economics and environmental science can meet would be
beneficial to properly address the problem of trade and environment.
1
Another problem is that SO2 and NOX emissions are relatively more technology-dependant, leaving the
possibility that the role of technology be over estimated.
4
The objective of current study is, first, to provide a bird’s-eye-view on environmental impacts of
commodities in U.S. economy and, second, to identify the relationship between imports and
both direct and indirect environmental impacts of commodities that are consumed in U.S. We
employed environmental input-output model and Life Cycle Impact Assessment (LCIA)
methods to describe the economic and environmental side, respectively. A database with
comprehensive environmental data, which is linked to U.S. input-output table is developed as
well.
2. Method and data
2.1. Characterising environmental impact of commodities
How can we better characterise the environmental impacts of commodities? Or, what might be a
definition of ‘dirty’ product? When some environmental activists paint ‘stop CO2’ on a stack of
a power station or iron and steel manufacturing plant, the definition may be ‘a product of which
production facility generates large share of the total environmental impact of a society’. If a
production process of certain kind of commodity generates 30% of the total greenhouse gas
impact, for instance, the commodities from that facility should be, indeed, named as a ‘dirty
product’. However, considering the fact that the electricity and steel products are used, for
instance, for maintaining cold chain of food and kindred products and automobile
manufacturing, the blame should go much further towards final consumer goods that use those
dirty products. Then another possible definition of dirty product will be ‘a product of which the
total supply-chain generates large share of the total environmental impact of a society’. Then,
can we reduce environmental impact by spending money to products other than the dirty
products defined above? The answer may be ‘depends’. Since the above definitions are based on
the effects not only of technology and composition but also scale, if the total amount of money
spent on alternative product become larger, it will result in increase of scale of the alternative
product, of which the environmental impacts per dollar can be higher. In such a case,
environmental impact intensity, rather than the gross direct or direct and indirect environmental
impact of product is more important.
Thus, this paper used four different ways of definition in characterising environmental impact of
commodities in U.S.: 1) direct environmental impacts per unit monetary value of each
commodity (direct environmental impact intensity - MDT), 2) direct and indirect environmental
value of unit monetary value of each commodity, (direct and indirect environmental impact
5
intensity - MDIT) 3) total direct environmental impacts generated by production of each
commodity (total direct environmental impact - MDM) and 4) total direct and indirect
environmental impacts by each commodity consumed in U.S. (total direct and indirect
environmental impact - MDIM).
We used static input-output table of U.S. and various LCIA methods to calculate environmental
impact of commodities. Commodity-by-commodity input-output table and corresponding
environmental intervention matrix was derived by using both industry-by-technology
assumption and commodity-by-technology assumption with scrap correction. The difference
between the two assumptions in final result was also analysed.
Let e = 1, … , E index environmental impact categories such as global warming, ozone layer
depletion, etc., let c = 1, … , C index commodities, let p = 1, … , P index pollutants. The direct
domestic environmental impact intensity of domestically produced commodities are calculated
by
P
B pc
p 1
qc
M ecDT   ( Fep 
),
(1)
where Fep is characterisation factor of pollutant p for impact category e, B pc is direct emission
of pollutant p to produce commodity c, and q c is the total domestic production of commodity c.
In matrix formula (1) can be noted as
M DT  FB qˆ 1 .
(2)
Equations (1) and (2) indicate how much environmental impacts are created on-site to produce a
unit monetary value of each commodity. Let d = 1, … , D index production of commodities.2
Then direct and indirect environmental impact intensity by domestic and foreign production
process is calculated by
C
P
M edDIT   ( Fep 
c 1 p 1
B pc
qc
)Ccd ,
(3)
In input-output literatures, the term ‘commodity production’ here is often referred to simply
‘commodity’.
2
6
where Ccd is total direct and indirect requirements of domestically produced or imported
commodity c to produce a unit monetary value of commodity by d. In matrix form (3) become
M DIT  FB qˆ 1 (I  A) 1 ,
(4)
where A is a commodity-by-commodity technology matrix where imports requirements are
endogenised and normalised by domestically produced total output of each commodity. 3 By
using (2), equation (4) become
M DIT  M DT (I  A) 1 .
(5)
Equations (3) to (5) indicate how much environmental impacts are created not only on-site but
also off-site through supply-chain to produce a unit monetary value of a product.
Total direct environmental impact by domestic production of commodity is calculated by
P
M ecDT   ( Fep  B pc )
(6)
p 1
or
M DM  FB .
(7)
Equations (6) and (7) show how much environmental impacts are created on-site to meet the
total production volume of each product in U.S. economy.
The total direct and indirect environmental impact through domestically produced and imported
commodities is calculated by
C
P
M edDIM   ( Fep 
c 1 p 1
B pc
qc
)Ccd ( y ddom  y dimp )
(8)
or simply by
3
The A matrix in equation (4) is derived by U=UD+UM and V, where UD, UM and V describes use of
domestic commodities by domestic industries, use of imported commodities by domestic industries and
7
M DIM  FB qˆ 1 (I  A) 1 (y dom  y imp ) ,
(9)
where y ddom and y dimp denotes total final demand by U.S. household on domestically produced
commodity, d and imported commodity, d, respectively. Using (2) and (5), equation (9) becomes
M DIM  M DIT (y dom  y imp ) .
(10)
Equation (8) to (10) shows how much environmental impacts are created not only on-site but
also off-site through supply-chain to meet the total final demand of each product.
For each approach, both industry-by-technology assumption and commodity-by-technology
assumption were used and compared.
2.2. Trade and environment
The relationship between trade and environmental impacts in U.S. is studied focussing on 1) the
relationship between environmental impacts and reliance on foreign production, 2) Pollution
Terms of Trade Index (PTTI) for each impact category and 3) total trade balance of U.S. in
terms of environmental impacts.
Pollution Terms of Trade Index (PTTI) utilise the idea of factor content of trade and was
initially calculated by Antweiler (1996) using a few substances including SOx, NOx and CO.
Current study maintains the general structure of PTTI by Antweiler (1996) and extends with
more comprehensive set of environmental emissions and LCIA methods. The environmental
impact
content
of
PeM  d 1 M edDIT xdimp
D
import

D
d 1
per
unit
monetary
value
of
imported
is
given
by
xdimp , which is, in matrix form, P M  M DIT x imp / i x imp , where
ximp denotes total import of commodities by U.S. Similarly, the environmental impact content of
export per unit monetary value exported is calculated by PeX 

D
d 1
M edDIT xdexp

D
d 1
xdexp , or
P X  M DIT x exp / i x exp , where xexp denotes total export of commodities by U.S. Then the PTTI
per each impact categories are calculated by
make of commodities by domestic industries, respectively.
8
PTTI e  PeX / PeM .
(14)
PTTI shows whether a country tends to export pollution intensive commodity or not. Antweiler
(1996) concluded that five of G-7 countries tends to export more pollution intensive
commodities than import.
The net pollution trade balance is calculated by
TBe  d 1 M edDIT ( xdexp  xdimp ) ,
D
(15)
which will tell us whether U.S. gains or loss pollutants through trade.
2.3. Life Cycle Impact Assessment
According to the ISO standard, LCIA comprises one step of mandatory element and three steps
of optional elements (ISO, 2000). The mandatory element, characterisation is a step to convert
pollutants emission and resources use into indicator result for each impact category such as
global warming or human toxicological impact. These conversion procedure aggregates
different environmental interventions into a common unit, category indicator to which each
pollutant emitted and resource used are related in terms of relative magnitude of impact on
category endpoints through environmental mechanism. A well-known indicator that are
frequently used in LCIA is Global Warming Potential (GWP), which aggregates different global
warming gases into kg CO2-equivalent unit.
Developing category indicators in LCIA involves use of complex models that simulate the
behaviour of each pollutant in our environment and their effects on various category end points.
The relevance of LCIA factors for meso- or macro-level study is that they are based on some
general conditions with which geographical and temporal specifics are eliminated.4 For instance,
in the process of photochemical oxidants creation, not only Volatile Organic Compound (VOC)
but also background NOx level and strength of UV radiation are important factors, which may
vary seasonally and also geographically. Then LCIA factors on POC is derived assuming some
generic conditions like annual average UV radiation and high or low background concentration
of NOx.
4
However, it is notable that site-specific LCIA is currently under development as well.
9
Generally there are three LCIA approaches that are commonly used. They are mid-point
approach, end-point approach and index methods. Mid-point approach uses indicators that are
located at the middle of the environmental mechanism such as GWP, while end-point approach
tries to find out the relationship between emission and environmental impacts at the end of the
environmental mechanism such as Damage Adjusted Life Year (DALY) due to ozone depleting
substances. Index methods are using less complicated model and directly convert the amount of
emissions into relevant indicators such as willingness to pay for certain remedy action.
Each method has advantages and disadvantages over others. Furthermore, all of them has
inherently high uncertainty level. Therefore, we used all of the three approaches, which includes
99 different sets of characterisation factors and see if they generate consistent results. Table 1
shows the characterisation methods that are used in this study. The selection out of 99 was
made due either to the similarity between methods or limited emission data.
Table 2. Selected characterisation method used in this study
Methods
Problem
Oriented
approach
(Mid-point
approach)
EcoIndicator
99
(End-point
approach)
Index
methods
Name
GW
OD
HT
FAET
MAET
FSET
MSET
TET
POC
AD
EU
EI-HCG
EI-HRO
EI-HRI
EI-HCC
EI-HOD
EI-EET
EI-EAE
Extern E
EPS
Ecopoint
Description
Global warming
Ozone layer depletion
Human toxicity
Freshwater aquatic ecotoxicity
Marine aquatic ecotoxicity
Freshwater sediment ecotoxicity
Marine sediment ecotoxicity
Terrestrial ecotoxicity
Photochemical oxidant creation
Acidification
Eutrophication
Carcinogenic effects on humans
Respiratory effects on humans by organic substances
Respiratory effects on humans by inorganics
Damages to human health by climate change
Human health effects by ozone layer depletion
Damage to ecosystem by ecotoxic emissions
Damage to ecosystem by acidification and
eutrophication
External cost
Willingness to pay on environmental damage
Environmental damage points
Unit
kg CO2 eq.
kg CFC-11 eq.
kg 1,4-dichlorobenzene eq.
kg 1,4-dichlorobenzene eq.
kg 1,4-dichlorobenzene eq.
kg 1,4-dichlorobenzene eq.
kg 1,4-dichlorobenzene eq.
kg 1,4-dichlorobenzene eq.
kg ethylene eq.
kg SO2 eq.
kg NOx eq.
DALY
DALY
DALY
DALY
DALY
PDF*m2*yr
PDF*m2*yr
ecu
elu
Ecopoints
2.4. Data preparation
Environmental intervention matrix used in this study is compiled using various information
sources including Toxic Releases Inventory (TRI) 98, Aerometric Information Retrieval System
(AIRS) Data of US. Environmental Protection Agency (EPA), Energy Information
Administration (EIA) data of US. Department of Energy (DOE), Bureau of Economic Analysis
10
(BEA) data of US. Department of Commerce (DOC), National Center for Food and
Agricultural Policy (NCFAP) and World Resources Institute (WRI) data. These sources are
the up-to-date ones and some of the data sources have been significantly improved very recently.
Firstly, annual total environmental interventions generated by each industry are compiled.
Greenhouse gas emissions by industry is compiled mainly using EIA and BEA data. EIA (DOE,
1999) provides CO2 emission data by most of the manufacturing industries due to energy use.
Missing data in (DOE, 1999) are estimated using fuel use data and emission factors (DOE,
1998; DOE, 2000; EPA, 2000a; BEA, 1998). CO2 emission by non-fuel use including cement
manufacturing, lime manufacturing and steel making are added to corresponding industries
referring to (DOE, 1999). CO2 emission by Flue Gas Disulfurisation (FGD) facilities are
distributed and added to each industries’ annual emission inventory based on energy use by
industries according to (DOE, 2000a). CO2 emission by industries other than manufacturing is
calculated based on fuel use data supplied by BEA (BEA, 1998), which contains end use fuel
consumption data on 9 major fuels in monetary term. Fuel consumption data is converted into
physical units by applying price data for different fuel and consumer types referring to (DOE,
1998) and CO2 emission by industry is derived by multiplying emission factors by EIA (DOE,
1999). Other greenhouse gases including nitrous oxides and methane are compiled using EIA
and EPA data (DOE, 2000; EPA, 2000a). Toxic pollutants emission by industry is calculated
using TRI 98 database (EPA, 2000b; EPA, 2000c). Stationery and mobile emission of
conventional pollutants including carbon monoxide, nitrogen dioxide, lead, sulphur dioxide,
volatile organic compounds (VOC) and particulate matter (PM10) are compiled using
Aerometric Information Retrieval System (AIRS) Data (EPA, 2000d). Pesticide use data is
based on NCFAP data (NCFAP, 1995), which contains pesticide use for crop production
excluding forestry and other use of pesticides. For resources use, only fossil fuel resources
extraction is considered in this study and WRI data is used (WRI, 1998).
Resulting annual environmental intervention matrix is classified based on Standard Industry
Classification (SIC) which differs from the industry classification used in national account.
Therefore, SIC based annual environmental intervention is assigned to each industry IO code
based on the standard comparison table provided by BEA.
Obtained environmental intervention matrix contains 1170 kinds of different environmental
intervention from 1,1,1,2-Tetrachloro-2-fluoroethane to Ziram including air, water, soil and
agricultural soil emission and fossil resources extraction.
11
3. Result and discussion
3.1. Sensitivity of method and data selection
We tested whether the result is generally invariable to the assumptions and methods that we
used. First, the difference in the final result derived using industry-by-technology assumption
and commodity-by-technology assumption is analysed with MDIM. The environmental impacts
of each commodity are related to the total annual impact of corresponding impact category,
which results in a share of each product in the total environmental impact of each impact
category. Then the difference in each of corresponding element between the two methods is
calculated. Ie. the difference in the share of the environmental impact, e of commodity, c
between industry-technology assumption (MDIM,
(M
IxT
) and commodity-technology assumption
DIM, CxT
d ec 1 
) is calculated by.
C
M ecDIM,CxT
M
M ecDIM,IxT
 M ecDIM,IxT
c 1
C
DIM,CxT
ec
(16)
c 1
Figure 2 shows that the two methods generate considerable difference for some parameters in
MDIM, although majority of parameters results in relatively similar value. 82% of total 2002
parameters showed less than 10% of differences. This difference produced several variations in
ranking of commodities between the two methods. However, 97% of total parameters resulted
from the two methods are graded around two upper or lower neighbouring ranks in all impact
assessment methods except for EPS. The EPS method shows large differences between the two
methods. The difference between the two methods was large enough to require a sensitivity
analysis for a detailed study, however, either of the two methods was considered useful for a
‘bird’s eye view’ like current study. Results that are presented in the rest of the part of this paper
are based on industry-technology assumption.
12
Figure 2. Frequency distribution of difference
between two allocation methods
Second, the differences in results derived by each impact assessment methods are analysed.
Since each methods had its own category indicator, it is not meaningful to compare the absolute
value of the results, we compared the ranking profiles and relative share by each commodity in
the total of each impact.
Figure 3 shows correlation matrix calculated using MDIM, as an example. The high hill on
diagonal shows all one, which refers to the correlation between the same method. Four island on
the diagonal are clearly visible which show more than 0.8 of correlation coefficient between
each other. Those four strongly correlated groups are listed in table 2.
Figure 3. Correlation matrix of normalised impact by
total final consumption and export of each commodity
13
Table. 2. List of correlated LCIA methods and important environmental intervention
Average correlation
Groups
LCIA method
coefficient
Fossil fuel combustion
GW, POC, AD, EU, EI-HRI, EI-HCC,
0.96
related group
EI-EAE, Extern E, EPS, Ecopoints
Toxic emission related group
HT, MAET, MSET, TET, EI-HCG, EIEET
0.86
Freshwater toxicity related
group
FAET, FSET
0.98
Ozone layer depleting
substance related group
OD, EI-HOD
0.99
No correlation with other
methods
EI-HRO
-
The strong correlation between impact assessment methods implies that, first, for those
indicators that describe the same problem, such as GW and EI-HCC or OD and EI-HOD,
despite the differences in detailed methodology, either of the methods can provide a general
picture of environmental impacts, and second, generation of some pollutants are highly
correlated. For instance the amount of CO2 emission and SO2 of NOx emission by an industry,
which are the major pollutants in global warming and acidification, respectively, are highly
correlated, since both are caused mainly by fossil fuel combustion. Especially, when the sample
size on environmental intervention is large enough, omission of an indicator by a methodology
can be covered by other remaining indicators of the methodology, resulting in a rather consistent
trend. However, two toxic emission related groups including freshwater toxicity related group
and others and a ozone layer depletion related group is not correlated with fossil fuel
combustion related impacts. Thus, looking only at energy requirements or a few fossil fuel
related emission was considered to be overlook possible problem shifting towards other impact
groups, such as toxic impacts. Since the set of problem oriented approaches well span over
different groups, the rest of the paper only shows results based on problem oriented approaches
(see table 1).
3.2. General environmental characteristics of commodities in U.S.
Table 3 to 6 shows 10 most polluting commodities using four different characterisation
approaches explained in the prior section.
The direct environmental impact intensity per unit monetary values shown in table 3 (MDT).
Table 3 shows that production of which commodity has high potential external cost shares due
14
to its environmental risks, although those risks may not yet visualised as internal environmental
expenditures. In overall, electric utilities (68A), water sanitary services (68C) and iron and steel
(37), business and professional services (73C) and metallic ores (05+06) were the most
frequently appeared products in the table 3. A service item, business and professional services
(73C) is found to be one of the most environmental impact-intensive product per unit monetary
value of its service. It is due to its chemical and chemical products releases mainly through
‘repair shops’, ‘photofinishing labs and commercial photography’, and ‘research, development
and testing services’. Non-fossil-fuel-combustion based emissions from coal mining (07), water
and sanitary services (68C) and live stock and live stock products (01) were identified as global
warming impact-intensive products due mainly to their methane emissions.
Table 4 shows the direct and indirect environmental impact intensity per unit monetary values of
each products (MDIT). Table 4 can be used to decide avoiding consumption of which product is
environmentally more friendly if an alternative choice is possible, and the total money spent is
the same. The over all ranking order of the table 4 is rather similar to the table 3, suggesting that
the direct environmental impact shares large portion in the total direct and indirect
environmental impacts. Most of the commodities shown in table 4 are located to the beginning
of the supply-chain close to the raw materials extraction and primary materials processing, such
as primary iron and steel manufacturing (37), metallic ores mining (05+06) and Industrial and
other chemicals (27A), but not many of final consumer items can be found. Considering the fact
that those primary materials are to be used to produce final consumer items, this implies that
industrial processes after the raw materials extraction and primary materials processing gains
relatively more value added than they pollute on-site. As a consumer item, foods and energy
products such as electricity (68A), livestock and livestock products (01), other agricultural prod
ucts (02), petroleum refining and related products (31) have high environmental impacts per uni
t monetary value as are frequently found in table 4.
By combining scale effects to the direct environmental impact intensity (table 3), direct
environmental impacts by each commodity is calculated (MDM). Table 5 shows on-site pollutant
generation of which production facilities shares larger portion in the total environmental impacts
in U.S. As the most frequently appeared item, a service, whole sales trade (69A) is found to be a
larger direct polluter in U.S. in most of the impact categories. The whole sales trade (69A)
includes whole sales of chemicals and allied products, not elsewhere classified (SIC 5169) and
petroleum bulk stations and terminals (SIC 5171), which has been included in the U.S. TRI only
recently, and these two subcategories generates significant amount of pollutants to all
environmental media. This shows the role of better management in handling chemicals and
15
chemical products over the role of cleaner production technology in manufacturing industries.
Besides, electricity (68A), industrial and other chemicals (27A) and primary iron and steel
manufacturing (37) are the most frequently appeared items in the table 5. Especially pesticide
use in agricultural products (02), heavy metal releases from metallic ores mining and business
services (05+06, 73C) and fossil fuel combustion gas emissions (37, 68A) dominate total direct
toxic impacts in U.S.
The most important consumer items in U.S. are shown in table 6 (MDIM). Table 6 shows the
consumer items of which direct and indirect environmental impact share large portion in the
total environmental impacts in U.S. New constructions (11), food and kindred products (14),
health services (77A) and motor vehicles (59A) are the most frequently found items in the table
6. Clearly, some basic necessities for households such as food and kindred products (14),
construction (11), electric utilities (68A), motor vehicles (59A) and health care services (77A)
are found to be environmentally important consumer items in most of the impact categories,
which may limit the possible environmental impact reduction by simply reducing the volume of
consumption in U.S.
A general observation throughout the different definitions of 'dirty products', was that the
inequality in environmental impacts between products are significant. Figure 4 is an example of
human toxic impact using MDIM. Horizontal axis shows the share in the total number of
pollutants and vertical axis shows the relative share in cumulative human toxic impact. Note
that the order of commodities are sorted in ascending order. If the line between (0,0) and (1,1) is
straight, it means that the human toxic impacts are equally distributed over commodities (skew
= 0). Figure 4 shows that human toxic impact distribution is highly distorted, so that 12% of
commodities are responsible for half of the total direct and indirect human toxic impact.
16
Draft
Version : 2002-07-21
Table 3. Ten most pollution-intensive commodities in U.S. based on direct impacts per M$ (MDT).
Rank
GW
OD
HT
FET
MET
FSET
MSET
TET
1
07
41
05+06
05+06
05+06
05+06
05+06
05+06
2
68C
32
37
02
37
02
37
02
3
68A
39
38
03
68A
03
68A
68C
4
01
38
39
04
68C
37
68C
73C
5
65D
64
41
37
73C
04
73C
09+10
6
31
13
02
76
41
68C
02
07
7
68B
27A
31
68C
02
73C
38
37
8
36
56
42
73C
38
68A
39
03
9
37
57
13
68A
39
09+10
41
68A
10
02
28
68A
09+10
36
07
68B
27A
POC
68C
65B
07
01
37
68B
27A
25
30
28
AD
68A
68B
37
35
36
31
68C
65B
25
24
EUT
68A
65B
68B
68C
35
36
05+06
08
25
27A
AD
68A
68B
37
05+06
35
31
36
25
24
27A
EUT
68A
68B
65B
05+06
36
35
68C
31
25
27A
* Abbreviations of environmental impact category and commodity code are shown in the appendix of this paper.
Table 4. Ten most pollution-intensive commodities in U.S. based on total (direct and indirect) impacts per M$ (MDIT).
Rank
GW
OD
HT
FET
MET
FSET
MSET
TET
POC
1
07
41
05+06
05+06
05+06
05+06
05+06
05+06
68C
2
68A
39
37
02
37
02
37
38
65B
3
68C
38
39
01
38
38
38
37
07
4
01
32
41
14
39
01
39
39
01
5
37
64
40
38
41
37
41
02
37
6
68B
54
43
16
68A
39
40
59B
25
7
31
56
42
04
40
14
59B
27A
27B
8
36
58
46
37
59B
16
42
40
68B
9
27A
57
59B
39
42
04
27A
41
27A
10
65D
28
44+45
15
43
27A
68A
42
28
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Table 5. Ten most polluting commodities in U.S. based on their direct impacts and total gross production (MDM).
Rank
GW
OD
HT
FET
MET
FSET
MSET
TET
POC
1
68A
32
37
02
05+06
02
05+06
05+06
65B
2
68C
69A
05+06
05+06
68A
05+06
68A
02
68C
3
31
41
31
73C
37
73C
37
73C
01
4
01
38
02
76
73C
68A
73C
69A
37
5
07
27A
68A
37
69A
37
02
68A
68B
6
65D
57
38
14
02
69A
69A
68C
69A
7
02
62
69A
68A
68B
76
38
27A
27A
8
68B
64
27A
69A
68C
14
68C
37
07
9
69A
56
73C
04
38
68C
68B
76
24
10
27A
29A
41
03
27A
04
27A
07
08
AD
68A
68B
65B
31
37
24
69A
27A
36
08
EUT
68A
65B
68B
31
69A
27A
08
24
68C
36
Table 6. Ten most polluting commodities in U.S. based on total (direct and indirect) impacts and total final demand (MDIM).
Rank
GW
OD
HT
FET
MET
FSET
MSET
TET
POC
1
68A
59A
59A
14
68A
14
59A
59A
65B
2
14
11
11
02
59A
02
11
11
14
3
11
69A
14
74
11
74
68A
14
68C
4
69B
64
44+45
11
14
59A
14
05+06
11
5
68C
56
31
59A
77A
11
77A
02
59A
6
77A
14
77A
18
69B
77A
05+06
77A
77A
7
74
77A
75
77A
05+06
18
69B
74
74
8
31
62
61
15
74
05+06
75
75
69B
AD
68A
69B
11
77A
14
59A
74
31
EUT
68A
11
14
77A
69B
68B
59A
65B
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9
10
59A
69A
51
29A
22+23
47
05+06
77B
44+45
75
15
75
19
74
44+45
56
59B
69A
31
68B
69A
31
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Similar pattern has been found for other impact categories. The highly skewed line in figure 4
shows that there are a few dominant products in each impact categories and, therefore, a special
attention to these products can effectively reduce the total environmental problems.
Share in total HT impact by commodities
1
0.5
0
0
0.5
0.88
Share in total number of commodities
1
Figure 4. Skewness of distribution in human toxic
impact by commodities (skewness=1.46)
3.2. Relationship between imports and exports and environmental impacts
The amount of direct imports by U.S. in 1996 was 6.97% of the total commodity used and in
U.S. Considering the foreign production required to produce the direct imports, the amount of
total foreign production become 14.95% of the total domestic and foreign production required
to meet the final demand in U.S.5 How this will look like in terms of environmental impacts?
Generally reliance on foreign environmental impacts are calculated higher than the reliance on
foreign production in monetary terms. In other words U.S. tends to import more polluting
products than they use on average, which may support pollution heaven hypothesis. However, it
5
Here we assume that the technology and structure of the foreign industries is the same as those of U.S.
and re-import by U.S. though its import is negligible.
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is also true that U.S. exports more polluting products than they use on average. The total
domestic and foreign production required for export was 10.86% of the total domestic and
foreign production, but the environmental impacts due to production of export are generally
more than that in most of the impact categories (Table 7). In table 7, RF shows the portion of
environmental impact occurred outside of U.S. to fulfil the domestic final demand in U.S. RX
shows how much is the environmental impact caused by the export in the total domestic and
foreign environmental impacts required for the domestic final demand and export by U.S. For
instance one might say that 39% of human toxic impact of an average product in U.S. occurs
outside of U.S., although the product relies on foreign production only in 14.95% .
In terms of overall environmental trade balance, U.S. is problem net exporter for major toxic
problems including freshwater ecotoxicity, marine water ecotoxicity, freshwater sediment
ecotoxicity, marine sediment ecotoxicity and terrestrial ecotoxicity. Among others, trade
imbalances in two freshwater related impacts are, apparently, caused by the massive export of
agricultural products other than livestock (02) by U.S. Other three impacts that lead U.S. a net
environmental problem exporter are dominated by the metallic ores mining (05+06). U.S. was
an problem net importer in other impact categories including global warming, ozone layer
depletion, human toxicity, photochemical oxidant creation, acidification and eutrophication.
Important vehicles of problem imports includes crude petroleum and natural gas (08), motor
vehicles (passenger cars and trucks) (59A) and primary iron and steel manufacturing (37) (table
8 and 9).
However, since U.S. has been a net importer in monetary sense in 1996, the overall trade
balance prone to be negative. In contrast, PTTI shows whether U.S. tends to import more
polluting products than it exports or vise versa if the amount of trade is the same. PTTI less than
1 shows U.S. tends to export problems and PTTI more than 1 does the other way around. PTTI
results in table 7 generally confirms the environmental trade balance results. U.S. tends to sell
more toxic products than they buy, except for the human toxic problem, and buy more polluting
products than they sell for other impact categories.
Then the next question is whether there is a meaningful relationships between environmental
impacts and reliance on foreign production. In general there are no or very week relationship
between the direct environmental impacts (MDT) and reliance on foreign production shown by a
regression study. Fig. 5 and 6 shows the case of global warming impact and human toxic impact,
respectively. This results support Jaffe et al. (1995) who showed that the compliance cost in
developing countries are almost negligible compare to overall expenses. Although the
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environmental impacts may influence the decision for a firm to be relocated in a country with
less-environmental awareness, other cost factors such as labour costs and subsidy are large
enough to cover the influence.
3
3
2
1
log(RF(i)/mRF)
log(RF(i)/mRF)
y = 0.1333x - 3E-17
y = 0.0547x + 2E-17
R2 = 0.0066
2
0
-3
-2
-1
0
1
2
3
-1
-2
2
R = 0.154
1
0
-3
-1
1
3
-1
-2
-3
-3
DT
log( M DT
HT (i)/m M HT )
DT
DT )
log( M GW
(i)/m M GW
Figure 5. Global warming vs.
reliance on foreign production
Figure 6. Human toxic impact vs.
reliance on foreign production
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Table 7. Trade and environment
Index*
GW
OD
RF
RX
ETB**
PTTI
0.14
0.11
-1.23E+11
0.93
0.34
0.19
-2.60E+05
0.76
HT
FET
MET
FSET
MSET
TET
POC
AD
EUT
0.39
0.20
-8.50E+10
0.70
0.19
0.22
3.29E+10
1.58
0.24
0.20
6.49E+11
1.15
0.20
0.24
4.88E+10
1.65
0.23
0.22
1.81E+12
1.34
0.22
0.27
1.93E+10
1.83
0.17
0.14
-1.92E+07
1.00
0.13
0.09
-1.16E+09
0.77
0.16
0.11
-6.78E+07
0.81
* RF: Reliance on foreign environmental impacts in the total domestic and foreign environmental impacts due to the final consumption by U.S.
RX: Ratio of environmental impact due to exports in the total domestic and foreign environmental impacts due to final consumption and export by US.
ETB: Environmental Trade Balance
PTTI: Pollution terms of trade index
** The values are represented by the equivalency of an indicator substance (category indicator), which are GW: kg CO2 eq.; OD: kg CFC-11 eq.; HT, FET, MET,
FSET, MSET and TET: kg 1,4-dichlorobenzene eq.; POC: kg formed ozone; AD: kg SO2; EUT: eq. kg PO4--- eq.
Table 8. Five most important vehicles for environmental problem imports in U.S.
Rank
GW
OD
HT
FET
MET
FSET
1
08
59A
37
02
37
02
2
59A
64
59A
14
38
38
3
37
57
59B
38
59A
37
4
27A
51
38
18
59B
14
5
14
56
42
37
51
59A
MSET
37
38
59A
59B
27A
TET
38
37
59A
59B
27A
POC
08
59A
37
27A
14
AD
08
59A
37
18
51
EUT
08
59A
27A
18
31
Table 9. Five most important vehicles for environmental problem exports in U.S.
Rank
GW
OD
HT
FET
MET
FSET
1
65D
57
37
02
05+06
02
MSET
05+06
TET
05+06
POC
65B
AD
27A
EUT
65B
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2
3
4
5
27A
02
14
69A
51
59A
27A
62
59B
59A
44+45
43
14
05+06
38
27A
38
59B
37
27A
05+06
14
38
59B
24
38
59B
27A
37
38
02
59B
27A
27A
14
69A
28
69A
59B
24
31
27A
69A
28
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4. Conclusion
Environmental impacts of domestically produced and imported commodities in U.S. economy is
analysed using standard U.S. input-output table and various life-cycle impact assessment
methods. Environmentally important commodities in U.S. are identified per each impact
category based on direct environmental impact intensity, direct and indirect environmental
intensity, total direct environmental impact and total direct and indirect environmental impact.
Robustness of the result was checked by analysing the difference in the result when varying
basic assumptions and methods. First, employing either of the industry-technology assumption
or commodity-technology assumption generates considerable difference for some results,
although majority of parameters results in relatively similar value. 82% of the total
environmental direct and indirect impact per each commodity result (MDIM) showed less than
10% of differences. In terms of the ranking, 97% of total parameters resulted from the two
methods are graded around two upper or lower neighbouring ranks in all impact assessment
methods except for EPS. Second, weather different life-cycle impact assessment methods can
still show the general trends of environmental impacts of a commodities are tested using the
relative share by each commodity in the total environmental impacts in U.S. The result shows
that either mid-point or endpoint approach produces a similar result for current result that has
compiled large number of environmental interventions.
Commodities located in the early stage of the supply-chain, such as iron and steel (37), metallic
ores (05+06), industrial and other chemicals (27A) and live stock and live stock products (01)
are found to be generally environmental impact-intensive per unit monetary value of commodity
in terms of direct impacts as well as total direct and indirect impacts. As a direct polluter,
wholesales trade (69A), electricity (68A), industrial and other chemicals (27A) and primary iron
and steel (37) shares large parts of the total impacts. As a total direct and indirect polluters, new
constructions (11), food and kindred products (14), health services (77A) and motor vehicles
(59A) are found to be the most important items in many impact categories.
First, the results show that some services such as business and professional services (73C) and
whole sales trade (63A) are highly polluting in terms of its environmental impact intensity or its
directs and indirect environmental impacts, elucidating the importance of materials handling
besides the role of cleaner production technology. Second, some basic necessities for
households such as food and kindred products (14), construction (11), electric utilities (68A),
motor vehicles (59A) and health care services (77A) are found to be environmentally important
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consumer items in most of the impact categories, which may limit the possible environmental
impact reduction by simply reducing the volume of consumption in U.S. Third, the share of
environmental impacts in the total impacts significantly differ between commodities, so that a
few commodities are responsible major part of the total impacts. This suggest that focussing on
a few important contributor identified by a systematic bird's eye view can effectively reduce the
total environmental impacts either though cleaner technology or better management of materials
handling.
The results on trade and environmental impacts shows that both imports and exports by U.S.
tends to be more pollution intensive than domestically used on average. In general U.S.
exported toxic impacts, except for the human toxic impact, and imported other environmental
impacts including human toxic impact, global warming, ozone layer depletion, photochemical
oxidant creation, acidification and eutrophication. Pollution Terms of Trade Index (PTTI)
generally confirms the environmental trade balance results. Important vehicles of environmental
impact trading in U.S. are identified for both problem imports and exports. Important vehicles
of problem imports includes crude petroleum and natural gas (08), motor vehicles (passenger
cars and trucks) (59A) and primary iron and steel manufacturing (37).
Finally the relationship between direct environmental impacts and reliance on foreign
production was analysed. The results show that there are no or very weak relationship between
them, which does not support the pollution heaven hypnotises. This results show that
environmental factor is not a dominant factor in deciding relocation of a firm. For instance,
although agricultural products other than live stocks (02) is a pollution intensive product and
also takes large share in the total toxic impacts, farms are not relocated in the developing
countries under the extensive subsidy program of U.S.
5. Limitations and Future outlook
We used available economic and environmental statistics that has been published in U.S., and,
thus, limitations of these statistics are equally applicable for the current study. Especially,
although it is one of the most comprehensive datasets on the toxic releases in the world, the TRI
does not includes the service, except for some whole sales industry, and agricultural sectors, and
even in manufacturing sectors, establishments that have less than 10 full-time or equivalent
employs and processes less than 25,000 pounds or use less than 10,000 pounds of any listed
chemical are not included. This limitation may lead underestimation for sectors like ‘plating and
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polishing’ where small and medium sized enterprises are considerable. Furthermore, some of the
environmental interventions such as noise and odour, radio active substances, land disturbances
are not considered in this study due mainly to the data lacks. The result of the assessment,
therefore, can not represent the consequences of these missed environmental interventions.
For the results on trade and environment the assumptions used by the current study, especially
one that foreign industry has the same technology and industrial structure as U.S. implies an
inherent limitation of the result. Provably, the assumption used here may lead some
underestimation of the environmental impacts of imported products. Current study can be
further extended using a multi-national input-output table with bilateral trade statistics and
environmental data. Such a database is currently under development.
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