Validation of regression models for nitrate concentrations in the upper groundwater in sandy soils

For Dutch sandy regions, linear regression models have been developed that predict nitrate concentrations in the upper groundwater on the basis of residual nitrate contents in the soil in autumn. The objective of our study was to validate these regression models for one particular sandy region dominated by dairy farming. No data from this area were used for calibrating the regression models. The model was validated by additional probability sampling. This sample was used to estimate errors in 1) the predicted areal fractions where the EU standard of 50 mg l⁻¹ is exceeded for farms with low N surpluses (ALT) and farms with higher N surpluses (REF); 2) predicted cumulative frequency distributions of nitrate concentration for both groups of farms.Both the errors in the predicted areal fractions as well as the errors in the predicted cumulative frequency distributions indicate that the regression models are invalid for the sandy soils of this study area.     

Assessment of the emission of PCDD/Fs and dioxin-like PCBs from an industrial area over a nearby town using a selective wind direction sampling device

The development of new sampling devices or strategies to assess the concentration of persistent organic pollutants (POPs) in the environment has increased in the last two decades. In this study, a selective sampling device was used to evaluate the impact of potential local sources of polychlorinated dibenzo-p-dioxin and dibenzofuran (PCDD/Fs) and dioxin-like polychlorinated biphenyl (dl-PCBs) emissions on the ambient air levels of such compounds in a town near an important industrial estate. Average concentrations of target compounds of up to 2.5 times for PCDD/Fs and 2 times for dl-PCBs were found to come from the industrial state confirming this area as the main responsible for the majority of such compounds reaching the town.This finding was supported by a PCDD/F and dl-PCB sample profile analysis and a principal component analysis (PCA), which established a direct link between the dioxin-like compounds found in the samples collected in the town and their source.     

Partitioning of organochlorine pesticides from water to polyethylene passive samplers

The mass transfer rates and equilibrium partitioning behaviour of 14 diverse organochlorine pesticides (OCP) between water and polyethylene (PE) passive samplers, cut from custom made PE sheets and commercial polyethylene plastic bags, were quantified. Overall mass transfer coefficients, k_O, estimated PE membrane diffusion coefficients, D_PE, and PE-water partitioning coefficients, K_PE-water, are reported. In addition, the partitioning of three polycyclic aromatic hydrocarbons (PAHs) from water to PE is quantified and compared with literature values. K_PE-water values agreed mostly within a factor of two for both passive samplers and also with literature values for the reference PAHs. As PE is expected to exhibit similar sorption behaviour to long-chain alkanes, PE-water partitioning coefficients were compared to hexadecane-water partitioning coefficients estimated with the SPARC online calculator, COSMOtherm and a polyparameter linear free energy relationship based on the Abraham approach. The best correlation for all compounds tested was with COSMOtherm estimated hexadecane-water partitioning coefficients.     

Estimating risk at a Superfund site using passive sampling devices as biological surrogates in human health risk models

Passive sampling devices (PSDs) sequester the freely dissolved fraction of lipophilic contaminants, mimicking passive chemical uptake and accumulation by biomembranes and lipid tissues. Public Health Assessments that inform the public about health risks from exposure to contaminants through consumption of resident fish are generally based on tissue data, which can be difficult to obtain and requires destructive sampling. The purpose of this study is to apply PSD data in a Public Health Assessment to demonstrate that PSDs can be used as a biological surrogate to evaluate potential human health risks and elucidate spatio-temporal variations in risk. PSDs were used to measure polycyclic aromatic hydrocarbons (PAHs) in the Willamette River; upriver, downriver and within the Portland Harbor Superfund megasite for 3 years during wet and dry seasons. Based on an existing Public Health Assessment for this area, concentrations of PAHs in PSDs were substituted for fish tissue concentrations. PSD measured PAH concentrations captured the magnitude, range and variability of PAH concentrations reported for fish/shellfish from Portland Harbor. Using PSD results in place of fish data revealed an unacceptable risk level for cancer in all seasons but no unacceptable risk for non-cancer endpoints. Estimated cancer risk varied by several orders of magnitude based on season and location. Sites near coal tar contamination demonstrated the highest risk, particularly during the dry season and remediation activities. Incorporating PSD data into Public Health Assessments provides specific spatial and temporal contaminant exposure information that can assist public health professionals in evaluating human health risks.     

Space-time statistics for environmental and agricultural related phenomena

This paper presents an overview of space-time statistical procedures to analyse agricultural and environmental related phenomena. It starts with an application on root-rot development in cotton. Dependence modelling in space and time is done with the space-time variogram. Various kriging interpolators are presented for making predictions in space and time. Simulated annealing is used to design an optimal monitoring network for estimation of space-time variograms. In the application no clear indication was found for anisotropy, although strong evidence exists that the disease not only proceeds within rows but also jumps between rows. The optimal sampling scheme showed a spatial clustering of observations at the first and the last monitoring day and less observations at intermediate times.     

Line transect sampling of Karner blue butterflies ( Lycaeides melissa samuelis)

Line transect sampling is an effective survey method for estimating butterfly densities because it provides unbiased estimates of site-density (provided key assumptions are met), and estimates are comparable among sites. For monitoring Karner blue butterflies in Wisconsin, USA, comparable estimates are required because each year a different selection of sites will be monitored. Annual state-wide indices of species abundance can be derived from the site-surveys and compared to previous year's indices to monitor trends. We advocate that line transect sampling is preferable to Pollard-Yates transects as a survey technique for monitoring Karner blue butter- flies. The Pollard-Yates surveys do not adjust for diferences in site detectability. As a consequence, estimates of among-site from Pollard-Yates surveys can be biased. © Rapid Science 1998     

Estimating the number of active and successful bald eagle nests:an application of the dual frame method

Monitoring the number of animals in a wildlife population is an important task. In this paper, we estimate the number of active and successful bald eagle nests in a specific region using dual frame sampling techniques. The dual frame method combines independent samples from an incomplete list frame and an area frame that is assumed to be complete. Hartley's screening estimator is used to combine sample information from both frames. This methodology will be useful for monitoring any wildlife population where the breeding individuals have highly visible nesting territories which tend to be stable over many years.     

天津市大气主要污染物总量控制允许排放量实施方案

本文采用环境质量总量控制技术路线。在天津市建立了１８个总量控制区,利用箱扩散模型（Ａ值法）测算了各总控区二氧化硫的允许排放量。利用Ｐ值法将区域允排量分配到源。本文还将化学质量受体平衡（ＣＭＢ）模型纳入Ａ－Ｐ值模型,形成ＡＰ－ＣＭＢ模型,用以测算烟尘和工业粉尘的区域允排量将将分配到源。由此构成天津市大气主要污染物总量控制允排量实施方案。     

Predicting the variation in detection function in line transect sampling through random parameter model

A method for calibrating (localizing) detection function models in line transect sampling is proposed. The method is based on a random parameter model which supplies localized predictions of detection function parameters utilizing a few sample data points from the concerned location(s). The method has the clear advantage of being able to provide density estimates based on very few observations from a location which would be impossible through traditional methods. The method is successfully illustrated using census data on sambar (Cervus unicolor) from a set of wildlife sanctuaries in Kerala, India. The need for further research in this direction is indicated.     

公路隧道机动车流量调查及其构成特点

报道了谭峪沟隧道和梧桐山隧道实验中机动车流量及其变化的调查和分析结果,得出了机动车流量的日变化趋势及车辆构成特点,并对其可能造成的环境影响进行了探讨.