Leaching of atrazine, metolachlor and diuron in the field in relation to their injection depth into a silt loam soil

A field experiment was conducted on a Calcaric Cambisol soil to study the consequences of the penetration depth and properties of pesticides on the risk of subsequent leaching. Three pesticides with different mobility characteristics and bromide were injected at 30 cm (where soil organic matter (OM) was 2%) and 80 cm (soil OM 0.5%) on irrigated plots without a crop. The migration of injected solutes was assessed for two years by sampling the soil solution using six porous cups installed at 50 and 150 cm depth and by relating solute contents to drainage water flux estimated by the STICS model (Simulateur mulTIdisciplinaire pour les Cultures Standard). Pesticides injected at 30 cm were strongly retained so that no metolachlor or diuron was detected at 50 and 150 cm. The ratio of atrazine peak concentration in the soil solution to concentration in the injected solution (C/C₀) was 1 × 10⁻³ and 0.2 × 10⁻³, respectively, at 50 and 150 cm. When injected at 80 cm, (C/C₀) of atrazine, metolachlor and diuron were 10 × 10⁻³, 1 × 10⁻³ and 0.3 × 10⁻³ at 150 cm, respectively; 1/(C/C₀) was correlated with K_oc values reported from databases. The ratio of drainage volume to the amount of water at field capacity in the soil layer between the injection point at 30 cm and the water sampling level (V/V₀) at 50 and 150 cm was 0.6 and 0.9, respectively, for bromide and 1.6 and 1.0 for atrazine. V/V₀ of the injected solutes at 80 cm was for bromide, atrazine, metolachlor and diuron 0.6, 0.9, 1.2 and 1.7, respectively; pesticide V/V₀ was correlated with K_oc. The retardation factor was a good indicator of migration risk, but tended to overestimate retardation of molecules with high K_oc. Atrazine desorption represented an additional leaching risk as a source of prolonged low contamination. The large variability in soil solution of bromide and pesticide concentrations in the horizontal plane was attributed to flow paths and clods in the tilled soil layer. This heterogeneity was assumed to channel water fluxes into restricted areas and thereby increase the risk of groundwater contamination. The methodology used in the field proves to provide consistent results.     

Variation of MCPA, metribuzine, methyltriazine-amine and glyphosate degradation, sorption, mineralization and leaching in different soil horizons

Pesticide mineralization and sorption were determined in 75 soil samples from 15 individually drilled holes through the vadose zone along a 28 km long transect of the Danish outwash plain. Mineralization of the phenoxyacetic acid herbicide MCPA was high both in topsoils and in most subsoils, while metribuzine and methyltriazine-amine was always low. Organic matter and soil pH was shown to be responsible for sorption of MCPA and metribuzine in the topsoils. The sorption of methyltriazine-amine in topsoil was positively correlated with clay and negatively correlated with the pH of the soil. Sorption of glyphosate was tested also high in the subsoils. One-dimensional MACRO modeling of the concentration of MCPA, metribuzine and methyltriazine-amine at 2 m depth calculated that the average concentration of MCPA and methyltriazine-amine in the groundwater was below the administrative limit of 0.1 μg/l in all tested profiles while metribuzine always exceeded the 0.1 μg/l threshold value.     

Field monitoring of volatile organic compounds using passive air samplers in an industrial city in Japan

Highly portable, sensitive, and selective passive air samplers were used to investigate ambient volatile organic compound (VOC) levels at multiple sampling sites in an industrial city, Fuji, Japan. We determined the spatial distributions of 27 species of VOCs in three campaigns: Mar (cold season), May (warm season), and Nov (mild season) of 2004. In all campaigns, toluene (geometric mean concentration, 14.0microg/m3) was the most abundant VOC, followed by acetaldehyde (4.76microg/m3), and formaldehyde (2.58microg/m3). The spatial distributions for certain VOCs showed characteristic patterns: high concentrations of benzene and formaldehyde were typically found along major roads, whereas high concentrations of toluene and tetrachloroethylene (PCE) were usually found near factories. The spatial distribution of PCE observed was extremely consistent with the diffusion pattern calculated from Pollutant Release and Transfer Register data and meteorological data, indicated that passive air samplers are useful for determining the sources and distributions of ambient VOCs.     

Concentrations and trends of benzene in ambient air over New York State during 1990–2003

Since 1990s, a systematic program to measure air toxics has been active in New York State with monitors located both in urban and rural areas. In this study we examined the spatial and temporal characteristics of benzene, a known human carcinogen that is emitted by many source categories. The analysis indicates that ambient concentration levels of benzene have decreased by as much as 60% over this period not only in the ozone non-attainment area of New York City that had the reformulated gas (RFG) requirements, but also over the rest of the state as well. Although the rate of decrease appears to have flattened out in recent years, the annual average concentration levels are found to be above the health risk threshold even at the remote location, Whiteface Mountain, suggesting the need for further reductions in benzene emissions.     

Spectral estimation of global levels of atmospheric pollutants

Underlying levels of atmospheric pollutants, assumed to be governed by smoothing mechanisms due to atmospheric dispersion, can be estimated from global emissions source databases on greenhouse gases and ozone-depleting compounds. However, spatial data may be contaminated with noise or even missing or zero-valued at many locations. Therefore, a problem that arises is how to extract the underlying smooth levels. This paper sets out a structural spatial model that assumes data evolve across a global grid constrained by second-order smoothing restrictions. The frequency-domain approach is particularly suitable for global datasets, reduces the computational burden associated with two-dimensional models and avoids cumbersome zero-inflated skewed distributions. Confidence intervals of the underlying levels are also obtained. An application to the estimation of global levels of atmospheric pollutants from anthropogenic emissions illustrates the technique which may also be useful in the analysis of other environmental datasets of similar characteristics.     

Development and Parameterization of a Rain- and Fire-driven Model for Exploring Elephant Effects in African Savannas

We describe the development and parameterization of a grid-based model of African savanna vegetation processes. The model was developed with the objective of exploring elephant effects on the diversity of savanna species and structure, and in this formulation concentrates on the relative cover of grass and woody plants, the vertical structure of the woody plant community, and the distribution of these over space. Grid cells are linked by seed dispersal and fire, and environmental variability is included in the form of stochastic rainfall and fire events. The model was parameterized from an extensive review of the African savanna literature; when available, parameter values varied widely. The most plausible set of parameters produced long-term coexistence between woody plants and grass, with the tree–grass balance being more sensitive to changes in parameters influencing demographic processes and drought incidence and response, while less sensitive to fire regime. There was considerable diversity in the woody structure of savanna systems within the range of uncertainty in tree growth rate parameters. Thus, given the paucity of height growth data regarding woody plant species in southern African savannas, managers of natural areas should be cognizant of different tree species growth and damage response attributes when considering whether to act on perceived elephant threats to vegetation.     

Evaluating Nonpoint Pollution Policy Using a Tightly Coupled Spatial Decision Support System

Policy makers often must rely on the cumulative impact of independent actions taken by local landowners to achieve environmental goals. The connection between policy, regulation, and local action, however, is often not well understood and, thus, the impact of proposed policies may be difficult to predict. In this study we evaluate the effectiveness of alternative policy scenarios for agricultural set aside programs (e.g., the conservation reserve program administered by the United States Department of Agriculture) in reducing nonpoint pollution. Two alternative policy scenarios are developed and analyzed; one based on the erodibility index (detachment), the other sediment yield (transport). An estimate of the cumulative impact of associated land use change on nonpoint pollution is made using the AGNPS distributed parameter watershed model. This work is completed within the Cypress Creek watershed in southern Illinois. An analysis of the resulting data suggests that the most efficacious regulatory strategy for achieving nonpoint water pollution goals depends, in part, on place-specific land use patterns. This conclusion provides a solid argument for place-based regulatory strategies.     

Probability of intellectual disability is associated with soil concentrations of arsenic and lead

Background

The association between metals in water and soil and adverse child neurologic outcomes has focused on the singular effect of lead (Pb), mercury (Hg), and arsenic (As). This study describes the complex association between soil concentrations of As combined with Pb and the probability of intellectual disability (ID) in children.

Methods

We used a retrospective cohort design with 3988 mother child pairs who were insured by Medicaid and lived during pregnancy and early childhood in South Carolina between 1/1/97 and 12/31/02. The children were followed until 6/1/08, using computerized service files, to identify the diagnosis of ID in medical records and verified by either school placement or disability service records. The soil was sampled using a uniform grid and analyzed for eight metals. The metal concentrations were interpolated using Bayesian Kriging to estimate concentration at individual residences.

Results

The probability of ID increased for increasing concentrations of As and Pb in the soil. The Odds Ratio for ID, for one unit change in As was 1.130 (95% confidence interval 1.048-1.218) for Pb was 1.002 (95% confidence interval 1.000-1.004). We identified effect modification for the infants based on their birth weight for gestational age status and only infants who were normal size for their gestational age had increased probability of ID based on the As and Pb soil concentrations (OR for As at normal weight for gestational age = 1.151 (95% CI: 1.061-1.249) and OR for Pb at normal for gestational age = 1.002 (95% CI: 1.002-1.004)). For normal weight for gestational age children when As = 22 mg kg⁻¹ and Pb = 200 mg kg⁻¹ the risk for ID was 11% and when As = 22 mg kg⁻¹and Pb = 400 mg kg⁻¹ the probability of ID was 65%.

Conclusion

The probability of ID is significantly associated with the interaction between Pb and As for normal weight for gestational age infants.     

Forest Health Assessment and Monitoring – Issues for Consideration

Part of this paper has been prepared for the lecture Forest Health Assessment-Criteria,Methods and Problems given by the author at the UIMPuniversity course Sanidad Forestal en el Bosques Mediterraneos yTemplados. Implicacion de la Contaminacion Atmosferica y del Cambio Global, held in Valencia, Spain, October, 1995. Assessment and monitoring of forest health representsa key point for environmental policy and for the management ofenvironmental resources. With the renewed interest in assessment andmonitoring of forest health generated by the suspected occurrence ofa widespread forest decline in Europe and North America, manyactivities have been undertaken: however, some questions should beconsidered and clarified when attempting to estimate forest health.Particularly, the objective(s) of the assessment and monitoringprogram should be carefully identified. Identification of a program‘stask has a number of implications and consequences: it implies adefinition of what concept of forest health (forest ecosystem health,forest health or forest trees health?) is assumed, what will be thetarget entity to be monitored, and therefore the identification of therelevant assessment questions and assessment endpoints.Consequences concern the definition of the spatial scale (frominternational to landscape and plot scale monitoring) and ecologicalcoverage (from single species population to population ofecosystems) of the program, which can have a considerable influenceon the choice of the proper sampling strategy and tactic, as well ason the most suitable methods, indicators and indices to be used.Although much of the work in the field of forest health and airpollution has concentrated on surveys on crown transparency anddiscoloration, there is an entire range of methods, indicators andindices developed to assess the health status of forests. The decisionas to which ones should be used will depend on the aim of theprogram and on economic and practical considerations. A furtherconsideration concerns the time span of the program, but anydecision in this field is subject to many limitations due to difficultiesin predicting future monitoring needs. All these points should becarefully considered and implemented according to a rigorousQuality Assurance procedure since any decision will influence futurework for many years.     

Geographic Analysis of Forest Health Indicators Using Spatial Scan Statistics

Geographically explicit analysis tools are needed to assess forest health indicators that are measured over large regions. Spatial scan statistics can be used to detect spatial or spatiotemporal clusters of forests representing hotspots of extreme indicator values. This paper demonstrates the approach through analyses of forest fragmentation indicators in the southeastern United States and insect and pathogen indicators in the Pacific Northwest United States. The scan statistic detected four spatial clusters of fragmented forest including a hotspot in the Piedmont and Coastal Plain region. Three recurring clusters of insect and pathogen occurrence were found in the Pacific Northwest. Spatial scan statistics are a powerful new tool that can be used to identify potential forest health problems.