Soil Arsenic Concentrations Research Articles

Comparison of Bioavailability and Biological Transfer Factor of Arsenic in Agricultural Soils with Different Crops

Heavy metal pollution in agricultural field near at the abandoned metal mines has been a critical issue in Korea. In particular, bioaccumulation in plants can have detrimental effect on human health. Main objective of this research was to examine arsenic (As) concentration in soil with varied extraction methods and to determine bioaccumulation and biological transfer factor in different crops. Results showed that bioaccumulation ratio of As for total contents in soil was ordered leafy and stem vegetables (1.19%) > fruit bearing vegetables (0.79%) > pulses (0.40%) > root vegetables (0.36%) with different crop species. Among 6 different extraction methods, all of extraction methods showed high correlation (R² = 0.87 - 0.97) except DTPA (R² = 0.25) when comparing As concentration in soil extracted with different extractants and As concentration in each crops. Calculated biological transfer factor was ranged 0.002-0.018 depending on crop species. Overall, concentration of As in crops can be varied and best management practice for minimizing bioaccumulation of As should be considered depending on crop species.

Comparison of Total Content of Zinc and Arsenic in Soils of Średzka Upland and Wrocław Ice-Marginal Valley

Abstract The aim of this study was to demonstrate that alluvial sediments of Wrocław ice-marginal Valley are characterized by higher con-centrations of metallic elements in relation to the adjacent areas of different soil cover genesis. Studies of zinc and arsenic content in soils were carried out in six municipalities of Średzki district. A total of 117 soil samples from arable land was collected: 80 from Średzka Upland and 37 from Wrocław ice-marginal Valley The process of accumulation of heavy metals in alluvial sediments in the Wocław ice-marginal Valley is so effective that, despite the heavier grain size composition of the soil cover immediately adjacent to Średzka Upland, zinc and arsenic concentrations are higher in the alluvial soils.

Geogenic arsenic anomalies in soils and stream waters of Neogene Emet basin (Kütahya-Western Turkey)

Arsenic is one of the most deleterious trace elements due essentially to its carcinogenicity resulting in the development of internal malignancies and skin cancer. In this study, arsenic concentrations of soils and stream waters in an area where the world class borate deposits of Turkey occur are presented. Soil and stream water samples were collected from the Emet basin of Neogene age, where intense borate mining activities have been practiced for about 60 years. Inductively coupled plasma–mass spectrometry (ICP-MS) was employed to analyze arsenic concentrations in soils and Gutzeit Method for water samples. As concentration levels in soils and waters ranged from 0.4 up to 2488.4 mg kg−1 (mean 111.8 ± 200.1 SD) and from 8 to 243 µg/L (mean 96.63 ± 66.83 SD), respectively. While soil pH measurements varied between 5.97 and 7.75 (avg. 7.06 ± 0.56), water pH values ranged from 6.44 to 8.32 (avg. 7.734 ± 0.59). As contents of both soils and surface waters were significantly (few tens to thousands times) high exceeding the maximum contaminant levels of current US-EPA’s maximum contaminant level of 0.01 mg As/L. Western Anatolian young (down to about 1 my) volcanic activities and shallow intrusive emplacements resulted in the formation of considerable number of geothermal and hydrothermal systems and kept them active for long enough that gave rise not only to the formation of numerous epithermal mineralizations rich in As–Sb–Hg-bearing sulfide minerals, but also to the formation of As-enriched sedimentary and magmatic rocks. Their dissolution and redistribution within the rocks and resultant soils consequently made them geogenically As-rich.

Hyperspectral Visible–Near Infrared Determination of Arsenic Concentration in Soil

The development of rapid techniques, such as hyperspectral spectrophotometry, for investigating arsenic (As) soil contamination could be of great value with respect to conventional methods. This study was conducted to detect As concentrations in artificially polluted soils (from 25 to 1045 mg kg−1) through hyperspectral visible–near infrared spectrophotometry and to compare two multivariate statistical regression analyses: partial least squares and support vector machines. The correlation coefficient r is greater in the partial least squares in both model (0.93%) and test (0.87%) with respect to support vector machines (0.88% for the model and 0.82% for the test). The most important model variables extracted from the variable importance in projection scores resulted the absorption peaks at 580, 660, 715, and 780 nm. Bands in the visible spectra are not directly associated to As, but the metalloid can interact with the main spectrally active components of soil permitting to multivariate statistical models to screen As concentrations.

Volatilization of arsenic from polluted soil by Pseudomonas putida engineered for expression of the arsM Arsenic(III) S-adenosine methyltransferase gene.

Even though arsenic is one of the most widespread environmental carcinogens, methods of remediation are still limited. In this report we demonstrate that a strain of Pseudomonas putida KT2440 endowed with chromosomal expression of the arsM gene encoding the As(III) S-adenosylmethionine (SAM) methyltransfase from Rhodopseudomonas palustris to remove arsenic from contaminated soil. We genetically engineered the P. putida KT2440 with stable expression of an arsM-gfp fusion gene (GE P. putida), which was inserted into the bacterial chromosome. GE P. putida showed high arsenic methylation and volatilization activity. When exposed to 25 μM arsenite or arsenate overnight, most inorganic arsenic was methylated to the less toxic methylated arsenicals methylarsenate (MAs(V)), dimethylarsenate (DMAs(V)) and trimethylarsine oxide (TMAs(V)O). Of total added arsenic, the species were about 62 ± 2.2% DMAs(V), 25 ± 1.4% MAs(V) and 10 ± 1.2% TMAs(V)O. Volatilized arsenicals were trapped, and the predominant species were dimethylarsine (Me2AsH) (21 ± 1.0%) and trimethylarsine (TMAs(III)) (10 ± 1.2%). At later times, more DMAs(V) and volatile species were produced. Volatilization of Me2AsH and TMAs(III) from contaminated soil is thus possible with this genetically engineered bacterium and could be instrumental as an agent for reducing the inorganic arsenic content of soil and agricultural products.

Optimization arsenic immobilization in a sandy loam soil using iron-based amendments by response surface methodology

The survey of reports regarding high concentrations of arsenic in soils and groundwater around the world, which refers to increase of arsenic exposure to the living organisms, has been increased. In this research work arsenic immobilization process using three iron amendments (soluble Fe(II), zero-valent iron (ZVI), and Fe (II)-modified zeolite (Fe-Z)) was modeled and optimized in a spiked soil by response surface methodology (RSM). Three factors including initial concentration of As(III) (20 to 580mgkg−1 of soil), amount of added Fe (0.5 to 2.5wt.% of soil for both Fe(II) and ZVI, 0.05 to 0.2wt.% of soil for loaded Fe on zeolite) and shaking time (15 to 960min) were selected as the independent factors on arsenic immobilization efficiency. The five-level central composite design (CCD) was used for experiment design and optimization model parameters. Variance analysis showed that CCD models were statistically significant for all amendments (p<0.01) with high accuracy (R2=0.98 for Fe(II), R2=0.89 for ZVI and R2=0.92 for Fe-Z) in predicting As(III) immobilization. Optimization results showed that at 200mgAskg−1 soil and 600minute shaking time, the immobilization of As(III) with Fe(II), ZVI and Fe-Z was 90.6%, 92% and 81.4%, respectively. However ZVI was most effective amendment, but with negligible difference in immobilization As(III), Fe(II) is more economical. In conclusion Fe(II) was more efficient and cost-effective than ZVI and Fe-Z in long-term immobilization.

Arsenic Content and the Bioavailability in Farmland Soils Affected by Mining Activities of a Realgar Ore, South China

Investigation on arsenic (As) accumulation in soil and agricultural products collected from the areas influenced by mine tailings and spoils around Shimen realgar mine, Hunan province, China, was carried out in this study. Water solubility, fractionation and bioavailability of As were determined as well to understand the environmental risk of arsenic releasing from farmland to water system this region. The results indicated that total soil arsenic concentrations varied from 18.9 to 932mg kg-1 and the highest arsenic concentration exceeding 500mg kg-1 in soils occurred only within 500m from these arsenic sources, and relatively low content (&lt;40 mg="" kg="" sup=""&gt;-1) appeared in the areas far away (&gt;3000m) from the pollution source. Arsenic content in dryland soils decreased with the distance from the mining arsenic ore, tailings and heaps increased. Through sequential extraction procedure (SEP), it was verified that the least arsenic amount occurred for exchangeable fraction with the percentage of 1.1%, then the organically bound fraction (1.6%), and much of the arsenic in the soils was associated with relatively immobile solid phases as residual fraction ranging from 87.5% to 93.3%. The fraction of mobile species, which potentially is harmful to the environment, was found to be higher in the soils with more AsT (total arsenic) content. Through statistical analysis, it was found out that arsenic content in plants was significantly correlated (R2=0.202; P&lt;0.01) with exchangeable As among these five As fractions in soils. Comparing extracted arsenic content in soils using distilled water (H2O-As), muriatic acid (HCl-As) and ammonium chloride (NH4Cl-As), better positive relationship occurred significantly (R2=0.226; P&lt;0.01) between NH4Cl-As and arsenic in plant, indicating the bioavailability was most closely related to NH4Cl-As rather than total As and other chemical solvents for extracting arsenic from soil.

Associations between land cover categories, soil concentrations of arsenic, lead and barium, and population race/ethnicity and socioeconomic status

The potential of using land cover/use categories as a proxy for soil metal concentrations was examined by measuring associations between Anderson land cover category percentages and soil concentrations of As, Pb, and Ba in ten sampling areas. Land cover category and metal associations with ethnicity and socioeconomic status at the United States Census 2000 block and block group levels also were investigated. Arsenic and Pb were highest in urban locations; Ba was a function of geology. Consistent associations were observed between urban/built up land cover, and Pb and poverty. Land cover can be used as proxy for metal concentrations, although associations are metal-dependent.

Bayesian importance parameter modeling of misaligned predictors: soil metal measures related to residential history and intellectual disability in children.

In this paper, we propose a novel spatial importance parameter hierarchical logistic regression modeling approach that includes measurement error from misalignment. We apply this model to study the relationship between the estimated concentration of soil metals at the residence of mothers and the development of intellectual disability (ID) in their children. The data consist of monthly computerized claims data about the prenatal experience of pregnant women living in nine areas within South Carolina and insured by Medicaid during January 1, 1996 and December 31, 2001 and the outcome of ID in their children during early childhood. We excluded mother-child pairs if the mother moved to an unknown location during pregnancy. We identified an association of the ID outcome with arsenic (As) and mercury (Hg) concentration in soil during pregnancy, controlling for infant sex, maternal race, mother's age, and gestational weeks at delivery. There is some indication that Hg has a slightly higher importance in the third and fourth months of pregnancy, while As has a more uniform effect over all the months with a suggestion of a slight increase in risk in later months.

Estimation of Arsenic Contamination in Reclaimed Agricultural Soils Using Reflectance Spectroscopy and ANFIS Model

Heavy metal contamination from anthropogenic sources is a threat to human health. To assess the feasibility of predicting surface soil arsenic (As) concentration from hyperspectral reflectance measurement, three different regression algorithms are compared in this paper, i.e., multiple linear regression (MLR), partial least squares regression (PLSR), and adaptive neural fuzzy inference system (ANFIS) modeling. Soil samples were taken from three study sites in mining/agricultural areas after reclamation. As concentration was determined by hydride generation atomic fluorescence spectrometry (HG-AFS) analysis, and the reflectance was measured with an analytical spectral devices (ASD) field spectrometer covering the spectral region of 350–2500 nm. First, after preprocessing of the original reflectance spectroscopy, the correlation coefficients between the As concentration and spectral reflectance measurement were derived. Characteristic bands were then chosen for the quantitative retrieval model. Finally, all of the 30 samples were divided into a calibration set and a validation set of 18 and 12 samples, respectively. When compared with the MLR and PLSR algorithms, the ANFIS model was the best retrieval model, with a coefficient of determination ( <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">${\bf R}^{\bf 2}$</tex> </formula> ) of 0.94 and a root-mean-square error (RMSE) of 0.88. ANFIS model and reflectance spectroscopy therefore have the potential to map the spatial distribution of As abundance, with the aim of improving public health.

Mid-infrared spectroscopy and partial least-squares regression to estimate soil arsenic at a highly variable arsenic-contaminated site

The potential of mid-infrared spectroscopy in combination with partial least-squares regression was investigated to estimate total and phosphate-extractable arsenic contents in soil samples collected from a highly variable arsenic-contaminated disused cattle-dip site. Principal component analysis was performed prior to mid-infrared partial least-squares analysis to identify spectral outliers in the absorbance spectra of soil samples. The mid-infrared partial least-squares calibration model (n = 149) excluding spectral outliers showed an acceptable reliability (coefficient of determination, $$R_{\text{c}}^{2}$$ = 0.75 (P < 0.01); ratio of performance to interquartile distance, RPIQc = 2.20) to estimate total soil arsenic. For total soil arsenic, the validation of final calibration model using 149 unknown samples also resulted in a good acceptability with $$R_{\text{v}}^{2}$$ = 0.67 (P < 0.05) and RPIQv = 2.01. However, the mid-infrared partial least-squares calibration model based on phosphate-extractable arsenic was not acceptable to estimate the extractable (bioavailable) arsenic content in soil ( $$R_{\text{c}}^{2}$$ = 0.13 (P > 0.05); RPIQc = 1.37; n = 149). The results show that the mid-infrared partial least-squares prediction model based on total arsenic can provide a rapid estimate of soil arsenic content by taking into account the integrated effects of adsorbed arsenic, arsenic-bearing minerals and arsenic associated with organic components in the soils. This approach can be useful to estimate total soil arsenic in situations, where analysis of a large number of samples is required for a single soil type and/or to monitor changes in soil arsenic content following (phyto)remediation at a particular site.

Association between risk of birth defects occurring level and arsenic concentrations in soils of Lvliang, Shanxi province of China

The risk of birth defects is generally accredited with genetic factors, environmental causes, but the contribution of environmental factors to birth defects is still inconclusive. With the hypothesis of associations of geochemical features distribution and birth defects risk, we collected birth records and measured the chemical components in soil samples from a high prevalence area of birth defects in Shanxi province, China. The relative risk levels among villages were estimated with conditional spatial autoregressive model and the relationships between the risk levels of the villages and the 15 types of chemical elements concentration in the cropland and woodland soils were explored. The results revealed that the arsenic levels in cropland soil showed a significant association with birth defects occurring risk in this area, which is consistent with existing evidences of arsenic as a teratogen and warrants further investigation on arsenic exposure routine to birth defect occurring risk.

Probability distributions of arsenic in soil from brownfield sites in Beijing (China): statistical characterization of the background populations and implications for site assessment studies

A probabilistic analysis was performed on soil arsenic concentration data from 4 brownfield sites at Beijing (Chaoyang and Haidian Districts), involved in environmental assessment studies. The available data sets were processed to provide a statistical characterization of the background populations and differentiate “anomalous data” from the natural range of variation of arsenic concentrations in soil. The site-specific background distributions and the existing wide-scale background values defined for the Beijing area were compared, discussing related implications for the definition of metal contamination soil screening levels (SSLs) in site assessment studies. The statistical analysis of As data sets discriminated site-specific background populations, encompassing 88% to 94% of the sample data, from outliers values, associated with either subsoil natural enrichments or possible anthropogenic releases. Upper Baseline Concentration (UBC) limits (+ 2σ level), including most of the site-specific metal background variability, were derived based on the statistical characterization of the background populations. Sites in the Chaoyang South District area had UBC values in the range 10.4–12.6 mg·kg−1. These ranges provide meaningful SSL values to be adopted for As in local site assessment studies. Using the wide-scale background value for the Beijing area would have erroneously classified most of the areas in the subject sites as potentially contaminated.

Using Asclite to Reduce Arsenic Concentration in Vegetables Grown on Arsenic Contaminated Soil

Three pot experiments were conducted to assess the capacity of asclite in reducing arsenic (As) contents in vegetable plants from arsenic contaminated soil. Asclite is an artificially made granular amorphous iron (Fe)-hydroxide material having high ability in adsorbing As(III) as well as As(V). In the first experiment, Japanese mustard spinach (JMS) (Brassica rapa var. perviridis) was grown in a 242 mg As kg soil with 10 and 20% of asclite application. The second and third experiments were conducted in Japan and Bangladesh, respectively, with JMS and Bangladesh spinach (BS) (Spinacia oleracea) grown in a 50 mg As kg soil where 1 and 2% asclite were applied. Application of asclite to arsenic contaminated soil significantly reduced the arsenic concentration in the edible part of the plants as compared to the control plants. The arsenic concentration in JMS reduced by 43 and 60% at 10 and 20% asclite application when grown in a 242 mg As kg 1 soil. The arsenic concentration was reduced by 29 and 37% in JMS, whereas it was 52 and 74% in BS, at 1 and 2% asclite application, respectively, when grown in a 50 mg As kg soil. There was no significant change in the growth and the nutrient elements concentration in Original Research Article IJPSS, Article no. IJPSS.2014.008 206 the plants. Our findings suggested that asclite could be used to reduce arsenic concentration in vegetables grown on arsenic contaminated soil. Considering the soil type, soil pH, soil arsenic concentration and plant species, further study is required to examine the desirable conditions for reducing the arsenic concentration in vegetable plants with asclite application.

Calibration and Evaluation of an X-Ray Fluorescence Method for the Determination of Lead and Arsenic in Soils

A portable X-ray fluorescence method is described for the measurement of lead and arsenic in soils based on calibration with standard reference materials. Both elements exhibited good linear calibration curves. The method was used to analyze dried and ground soil samples obtained from the metropolitan New York City area. Results were compared to measurements obtained by graphite furnace atomic absorption spectrometry with microwave assisted acid leaching. No significant difference was found for lead measurements between the two methods however, arsenic values were significantly different with XRF exhibiting higher values. It is hypothesized that incomplete leaching and spectral interference are the predominant causes of this discrepancy. The XRF method provides a simple, quick, and nondestructive method for the determination of total lead and arsenic content in soils.

Impacts of Gold Mining on Rice Production in the Anum Valley of Ghana

This study assessed the concentrations of arsenic and iron in paddy soil and rice grain samples collected from the Nobewam and Odumase paddy field sites in the Anum Valley of Ghana, as a means of determining the impacts of gold mining activities in the area on rice production. The arsenic content of rice grains from the Anum Valley paddy fields was compared to that in rice grains of the same variety harvested from three non-impacted paddy fields (control sites) in other parts of Ghana. The study findings indicated that soils in the Odumase paddy fields, which are located closer to the gold mining site, were significantly more impacted by mining pollution than soils in the Nobewam paddy fields. Arsenic concentration in the Nobewam paddy soils ranged from 0.6 to 76.1 mg/kg with a mean of 8.3 mg/kg, while that in the Odumase paddy soils ranged from 5.3 to 106.2 mg/kg with a mean of 41.1 mg/kg. Despite the significant difference in mean soil arsenic content, there was no significant difference in the arsenic content of rice grains harvested from the two Anum Valley paddy sites (i.e. Nobewam and Odumase). There was also no significant difference between the two Anum Valley paddy sites with respect to soil iron concentration. The regression equation for a graph of soil arsenic against soil iron (As = 70.0 Fe – 37.7) was, however, highly significant (P

Geochemical characterization and biomonitoring of reclaimed soils in the Po River Delta (Northern Italy): implications for the agricultural activities

This geochemical study is focused on the easternmost part of the Po River alluvial plain in Northern Italy, which is interested by widespread agricultural activities, investigating a reclaimed sector of the Province of Ferrara, known as "Valle del Mezzano" (Mezzano Low Land, hereafter reported as MLL) characterized by peat-rich soils. The chemical-mineralogical characterization of these reclaimed soils is important to compare the local geochemical backgrounds with those recorded in other sectors of the River Po plain and to monitor if the observed concentration exceeds critical thresholds. The reported analyses include (a) measurement of the soil salinity, (b) nutrient evaluation, (c) major and trace element concentrations carried out on bulk soils, (d) tests of metal extraction with both aqua regia and EDTA to highlight the distinct elemental mobility and (e) phyto-toxicological measurement of heavy metal concentrations in plants (Lactuca sativa acephala) grown on the studied soils. The results indicate (1) high soil salinity, often with drastic increase of sodium and chloride along the soil profiles, (2) high nitrogen content (in part related to anthropogenic activities) on superficial horizons and nitrate decrease along the soil profiles and (3) comparative enrichments in heavy metals with respect to other soils of the province, which indicate that peat deposits are effective in trapping metals from anthropogenic sources. This, in turn, implies potential geochemical risks for the agricultural activities. In this regard, specific concerns are related to the high nickel and arsenic content of MLL soils due to the mobility of these elements and their attitude to be taken up by plants.

Fluoride and arsenic exposure through water and grain crops in Nagarparkar, Pakistan

The aim of present study was to simultaneously estimate the arsenic (As) and fluoride (F−) concentrations in irrigated surface water, soil and grain crops of Nagarparkar, Pakistan during 2010–2012. The As and F− were analyzed by hydride generation atomic absorption spectrometer and ion selective electrode, respectively. Total arsenic (AsT) and F− in irrigated surface water samples were found in the range of 360–683μgL−1 and 18.5–35.4mgL−1, respectively. While AsT and F− concentrations in agriculture soil samples were observed in the range of 110–266 and 125–566mgkg−1, respectively. The water extractable As and F− were found 3–4% of total concentration of these in soils.The AsT concentration was higher in kidney been (KB) as compared to pearl millet (PM) and green gram (GG), whereas GG had higher F− levels as compared to other two grain crops (p<0.05). The KB samples grown in nine sites shows BCF of As in the range of 0.018–0.038. The GG has higher BCF of F− as compared to KB and PM (p<0.05) grown in all sites. The exposure dose and risk factor of As and F− were obtained by estimated daily intake (EDI) and hazardous index (HI). It was found that all understudy age groups were at the severe risk of arsenicosis and fluorosis, but the severity is higher in younger age group (7–15years) as compared to elder groups (p<0.05).

Spatial modeling of ecological areas by fitting the limiting factors for As in the vicinity of mine, Serbia

Elevated arsenic (As) concentrations in soil are often found in the vicinity of certain mineral deposits that have been, or are currently, under exploitation, regardless of the target resource. Detailed study of such areas for safe agriculture requires considerable financial costs and long periods of time. Application of an appropriate spatial model that describes the behavior of arsenic in soil and plants can significantly ease the whole investigation process. This paper presents a model of ecological security of an area that, in the past, was an antimony mine and has a naturally high content of arsenic. For simulation and modeling the geographic information science (GIS) technology with the inserted predictors influencing the accessibility of As and its content in plants was used. The results obtained were the following: (1) a categorization of contaminated soils according to soil properties was developed; (2) the proposed methodology allows focusing on particular suspect area saving an energy and human resource input; and (3) new safe areas for growing crops in contaminated area were modeled. The application of the proposed model of As solubility to various crops grown around a former antimony mine near the village of Lisa, southwest Serbia showed that significant expansion of the areas suitable for growing potato, raspberry, and pasture was possible.

Relationship of Arsenic Concentration in Residential Yard Soil, Home Location, and Topography in a Community near a Superfund Site

Background: The Iron King Mine and Humboldt Smelter Superfund Site is located in northern Arizona adjacent to the town of Dewey-Humboldt, AZ. Community exposure to metals in residential yard soil deposited via windblown dust from the Site is a concern. Aims: The objective of this study was to examine the arsenic value of yard soil for homes within 3 miles of the Site in relation to homes' distance from the Site, elevation, slope, and underlying soil type. Methods: Approximately 140 grams of soil was collected from 18 homes around the yard perimeter. Each sample was sieved to the &lt;63 µm size fraction and analyzed for a variety of metals using ICP-MS after microwave-assisted nitric acid digestion. Geographic information systems maps and Wilcoxon-Mann-Whitney tests were used to assess relationships between distance from the Site, elevation, slope, and underlying soil type. Results: The overall mean arsenic concentration in soil was 53.1 mg/kg. The 11 homes &lt;1 mile from the Site had a mean arsenic concentration of 24.4 mg/kg with values ranging from 11.8 to 51.5 mg/kg; the 7 homes 1-3 miles from the Site had a mean arsenic concentration of 98.3 mg/kg with values ranging from 8.53 to 432 mg/kg. Homes &lt;1 mile had a mean elevation of 1,386 meters and a slope of 3.23%; homes 1-3 miles had a mean elevation of 1,415 meters and a slope of 4.7%. Only elevation was statistically significant (p=0.0043) between homes &lt;1 mile versus 1-3 miles away. There was no relationship between distance from the Site and underlying soil types. Conclusions: Homes at higher elevations in areas further from the Site may receive more windblown dust from the Site containing elevated levels of arsenic. These findings compliment wind event modeling that simulates dust blowing from the Site, through homes &lt;1 mile away at lower elevations, then being deposited in areas with higher elevation. Soil sampling beyond 3 miles may illuminate the complex relationship between meteorological conditions, the area's topography, and soil arsenic values in relation to the Site.