Contaminant mobility and biogeochemical processing in peri-urban soils
(Study 5 in the EPA Acid Rain Impacts study)
Breck Bowden
There is a considerable body of literature on the effects of atmospheric deposition on ecosystem structure
and function, primarily in non-urban systems. A smaller portion of this literature focuses on the effects of
atmospheric deposition on biogeochemical dynamics in urban and peri-urban ecosystems. The bulk of
this literature describes the composition of atmospheric deposition in urban environments (e.g. Gatz 1991,
Treloar 1993, Bricker and Rice 1993, Lee 1993, Sansui et al. 1996, He at al. 2002, Kulshrestha et al.
2003) and the direct impacts of this deposition on receiving water quality (e.g.; Groffman and Jaworski
1991) and on urban infrastructures (e.g.; May and Klessig 199)0). A separate and growing body of
literature suggests that urban development alters both the nature and composition of urban soils (Pouyat et
al. 1995, Freedman et al. 1996, Carreiro et al. 1999, Weathers et al. 2001, Baxter et al. 2002, Brack 2002,
Pouyat et al. 2002). This is clearly the case in contaminated sites. But even in developed areas that
would not normally be thought of as contaminated, pollutants accumulate. Interactions between
atmospheric deposition and soil processes in peri-urban environments that are characteristic of ‘urban
sprawl’ in the northeast are not well known. We hypothesize that atmospheric deposition on peri- urban
soils mobilizes important contaminants, such as heavy metals and that, in turn, these contaminants and
the atmospheric deposition itself interfere with key soil biogeochemical processes; in particular,
respiration, mineralization, and nitrification. If true, this hypothesis has important implications for the
extension of results from studies proposed elsewhere in this workplan which focus on deposition-induced
stress in forests, including urban forests.
Proposed research: To address this hypothesis, we propose three linked sub-studies
Study 5a. Soil characteristics as a function of development intensity: Previous research suggests that
substantial differences in soil properties occur along undeveloped to urbanized gradients (Pouyat et al.
1995, Freidman et al. 1996, Carreiro et al. 1999, Weathers et al. 2001, Baxter et al. 2002, Brack 2002,
Pouyat et al. 2002). Urban sprawl in the Burlington-Chittenden County area in Vermont is widely
recognized as a pressing problem and the development patterns that have evolved here are representative
of those seen elsewhere in the formerly undeveloped, but urbanizing fringes of the northeast. For this
reason, we propose to use the greater Burlington-Chittenden County as our study area. The purpose of
this sub-study is to establish that identifiable differences do exist among sites that differ as a function of
development intensity.
We propose to identify a series of replicated sites that are representative of four development classes:
undeveloped, low-density residential, high-density residential, and urban/business. The undeveloped
class will have no built structures or impervious area and will have a natural vegetation cover. This class
will serve as the reference. We do not propose to include active agricultural activities as a part of this
project and so the undeveloped sites we choose will be ones that have little or no history of agricultural
use. We recognize that most of the northeast has experienced some form of agriculture activity at some
time and that agricultural activities can have long legacies. We will include these considerations in our
site selection process. Numerous alternatives are available as candidate sites for the other three
development classes. The low-density residential class will have <30% impervious area with single
family housing densities of <2/acre. The high-density residential class will have >30% impervious area
with single family housing at >2/acre. The urban class will have >30% impervious area with a mix of
multi-family residential, business and light industry. To the extent possible, we will select sites on a
single common soil type, to reduce variation that would be inherent among different soil types. It is
important to recognize, however, that usage legacies, soil disturbance and soil differences (e.g.; ‘made’
soils) are common characteristics of developed areas. Indeed, they are one of the consequences of
development and as such are potentially part of the ‘development’ treatment effect.
Within each class we will identify sites that are dominated by tall vegetation (mixed hardwood-conifer) or
by grasses/forbs. The reason for this distinction is that we expect that the contaminant input processes
may differ between these two land cover categories; e.g., in tall vegetation, atmospheric scavenging may
be more important while in grass/forb systems, direct anthropogenic inputs may be more important. In
summary, there will be 4 development classes with 2 land cover categories for a total of 8 treatment types.
For each treatment type we will select 3 replicate sampling sites which will be selected on the basis of
similarity in development intensity (impervious area, building type and density), soil type, and vegetation
cover type and density. At each site we will collect composite samples of the upper 0-15 cm of soil and
from mineral sub-soils (nominally 30-45 cm). The composite samples are intended to reduce local, subsite variability and will be derived from 5 randomly located sub-site samples. The composite samples (8
sampling sites x 3 composite replicates x 2 soil horizons = 48 total samples) will be sieved to pass a 2 mm
mesh.
For each of the 48 samples, we will directly measure total nitrogen, total carbon, cation exchange
capacity, and total base cations and selected extractable metals (Cu, Cd, Pb, Ni, Zn, and Hg) using ICPAES. We will follow standard methods as described in the Quality Management Plan (June 2000),
Methods of Soil Analysis (Sparks et al. 1996), Standard Methods for the Examination of Water and
Wastewater 19th ed., and EPA SW846. Ancillary information about these soils (including particle size
distribution and bulk density) will be extracted from NRCS soil surveys. The measured data will be
analyzed in a simple, three-way, ANOVA model with development intensity (4 classes), vegetation type
(2 classes), and soil horizon (2 classes) as the independent model variables.
Study 5b. Soil leachate characteristics as a function of development intensity: The same soil samples
from study 5a will be used for studies 5b and 5c. Soil sub-samples will be packed into funnel lysimeters
at a bulk density approximating the native condition of these soils. A total of 3 funnel lysimeters will be
assembled for each of the 48 soils samples derived from study 5a (total = 144). One each of these 3
funnel lysimeters will be assigned to a leaching treatment at one of 3 pH levels (6, 5 or 4). Note that the
48 soil samples from study 5a include composite replicates, so the pH treatments are automatically
replicated. Each week over a period of 15 weeks, synthetic rain water acidified to the 3 indicated pH
levels with a combination of H2SO4 and HNO3 reflecting the proportions of SO4 and NO3 found in local
rainfall, will be leached through the soil samples in the funnel lysimeters. The leachate from each
lysimeter will be stored for future analysis. Based on prior experience, we have found that it is better to
analyze these samples in a ‘batch’ mode at the end of the study rather than to analyze samples ‘on the fly’
as the study progresses. The samples collected a weeks 0, 5, 10, and 15 will be analyzed for selected
leachable metals (Cd, Ni, Pb, Cu, Zn, and Hg) by ICP-AES (EPA method SW-846). All samples will be
saved for study 5c.
We recognize that soil disturbance is likely to alter soil characteristics and process (see in particular, Ross
and Hales 2003). Sampling intact cores reduces some of these artifacts. However, extraction of intact
cores is labor-intensive and typically greatly increases the sampling variability. Furthermore, the
objective of this study is not focused on measurement of in situ rates. Rather, we wish to develop simple
and reliable comparative indicators of the influences of development intensity on key soil characteristics
and processes. For this reason, we think the sample disturbance proposed here is justified.
Study 5c. Soil biogeochemical processes as a function of development intensity: Leachate samples from
week 0 and every other (even numbered) week after that will be analyzed for ammonium and nitrate using
standard methods as outlined in the Quality Management Plan (QMP) of June 2000. These data will be
used to assess how the soil and treatment effects influence nitrogen mineralization and nitrification (as per
the QMP, Sparks et al. 1996, and Hallet et al. 1999). Samples from odd-numbered weeks will be
archived as back-up samples, in the event that we need to explore these nitrogen dynamics at finer
temporal resolutions or in the event that we lose or need to rerun samples from even numbered weeks.
On odd-numbered weeks we will measure soil respiration from the funnel lysimeters, following methods
described in Methods of Soils Analysis (Sparks et al. 1996) as modified by Ashby et al. (1998). The
essential analytical method is consistent with EPA Emission Measurement Center promulgated Method
3C for CO2, CH4, N2, O2 - TCD (1996). Briefly, measurements will be made one day after the weekly
leaching treatment, to mimic conditions in the soils that approximate field capacity of soil moisture.
Funnel lysimeters will be placed in air-tight enclosures without further disturbing the soil and the build-up
of CO2 over time (typically no more than 2 h) will be monitored as a metric for respiration. Samples of
CO2 will be measured on a gas-chromatograph equipped with a thermal conductivity detector. Samples
will be analyzed against certified standard gas mixtures. A mid-range standard will be analyzed every
10th sample. If these check standards vary by more than 5% a complete standard series will be run before
additional samples are analyzed.
For each of the 48 original soil samples, subsamples will be analyzed for potential mineralization and
nitrification as described in Methods of Soil Analysis (Sparks et al. 1996) and Hallet et al. (1999). These
analyses will be used to normalize the mineralization and nitrification rates measured in the leaching
experiments; i.e. the ratio of cumulative mineralization and nitrification from leachate samples at 15
weeks to total potential mineralization and nitrification.
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