Using the expert model PERPEST to translate measured and predicted pesticide exposure data into ecological risks

An important topic in the registration of pesticides and the interpretation of monitoring data is the estimation of the consequences of a certain concentration of a pesticide for the ecology of aquatic ecosystems. Solving these problems requires predictions of the expected response of the ecosystem to chemical stress. Up until now, a dominant approach to come up with such a prediction is the use of simulation models or safety factors. The disadvantage of the use of safety factors is a crude method that does not provide any insight into the concentration–response relationships at the ecosystem level. On the other hand, simulation models also have serious drawbacks like that they are often very complex, lack transparency, their implementation is expensive and there may be a compilation of errors, due to uncertainties in parameters and processes. In this paper, we present the expert model prediction of the ecological risks of pesticides (PERPEST) that overcomes these problems. It predicts the effects of a given concentration of a pesticide based on the outcome of already performed experiments using experimental ecosystems. This has the great advantage that the outcome is more realistic. The paper especially discusses how this model can be used to translate measured and predicted concentrations of pesticides into ecological risks, by taking data on measured and predicted concentrations of atrazine as an example. It is argued that this model can be of great use to evaluate the outcome of chemical monitoring programmes (e.g. performed in the light of the Water Framework Directive) and can even be used to evaluate the effects of mixtures.     

Parameterizing,evaluating and comparing metapopulation models with data from individual-based simulations

Due to the lack of sufficient data and appropriate ecological information parameterizing predictive population dynamical models usually is a difficult task. The approach proposed in this study is meant to overcome this problem by using detailed individual-based simulations to generate artificial data. With short-term data samples, the models to be investigated can be parameterized and their predictions be compared. The flexibility of individual-based simulations as experimental tools also facilitates the evaluation and comparison of different (aggregated) model types. The presented approach is a step towards unifying models of different complexity. As an example we applied it to two metapopulation models of insect species in a highly fragmented landscape: the well-known incidence function model with a patch-based representation of space and a grid-based analogue. The models are tested with respect to their data requirement and recommendations for a better data sampling are derived.     

Optimal Selection of Priority Development Areas Considering Tradeoffs Between Hydrology and Development Configuration

Mixed-integer linear programs are proposed for siting development and conservation areas in watersheds, addressing economic objectives (development perimeter and proximity) and ecological objectives. Links between watershed hydrology and ecology need not be well defined. Parameters for the linear programs are obtained from linearization of the SWAT hydrologic model.     

线性修正趋势分析技术在环境质量预警预测中的应用

线性修正趋势分析法根据历年数据建立线性模型并进行修正,预测年度、季环境要素污染物变化情况,可应用于空气质量、水环境质量、噪声环境质量、污染源污染物排放等预警预测数据统计分析评价,为环境决策提供技术支持。本文通过实例论述了该方法在实际工作中的应用。     

曝气沉砂池除砂机理分析

针对曝气沉砂池小试装置模型,通过配砂实验对沉砂池除砂率进行统计分析,研究曝气强度与HRT对沉砂池除砂率的影响。实验结果表明,不同曝气强度下,随着HRT变化,除砂率逐渐上升,并最终趋于平衡状态;不同HRT下,曝气强度与除砂率近似呈现一定的线性关系,且随着曝气强度的增大,除砂率降低;在HRT小于1min时,砂粒的运行路径和沉降时间缩短,不利于砂粒的去除;在HRT大于1min时,其中1、3和4min,随着气水比的增加除砂率降低幅度相对较小,曝气所引起的横向环流在一定程度上有利于砂粒的沉降,而HRT为2min时,除砂率降幅却很大,这与砂粒在曝气沉砂池池体断面分布有关,即断面处旋转流速和水平流速的大小变化将影响砂粒的运动;相比曝气强度,HRT对除砂率的影响较大。     

Effects of input uncertainty and variability on the modelled environmental fate of organic pollutants under global climate change scenarios

Global climate change (GCC) is expected to influence the fate, exposure and risks of organic pollutants to wildlife and humans. Multimedia chemical fate models have been previously applied to estimate how GCC affects pollutant concentrations in the environment and biota, but previous studies have not addressed how uncertainty and variability of model inputs affect model predictions. Here, we assess the influence of climate variability and chemical property uncertainty on future projections of environmental fate of six polychlorinated biphenyl congeners under different GCC scenarios using a spreadsheet version of the ChemCAN model and the Crystal Ball® software. Regardless of emission mode, results demonstrate: (i) uncertainty in degradation half-lives dominates the variance of modelled absolute levels of PCB congeners under GCC scenarios; (ii) when the ratios of predictions under GCC to predictions under present day climate are modelled, climate variability dominates the variance of modelled ratios; and (iii) the ratios also indicate a maximum of about a factor of 2 change in the long-term average environmental concentrations due to GCC that is forecasted between present conditions and the period between 2080 and 2099. We conclude that chemical property uncertainty does not preclude assessing relative changes in a GCC scenario compared to a present-day scenario if variance in model outputs due to chemical properties and degradation half-lives can be assumed to cancel out in the two scenarios.     

2,4-D Mineralization in soil profiles of a cultivated hummocky landscape in Manitoba,Canada

The objective of this study was to quantify 2,4-D (2,4-dichlorophenoxyacetic acid) mineralization in soil profiles characteristic of hummocky, calcareous-soil landscapes in western Canada. Twenty-five soil cores (8 cm inner diameter, 50 to 125 cm length) were collected along a 360 m transect running west to east in an agricultural field and then segmented by soil-landscape position (upper slopes, mid slopes, lower slopes and depressions) and soil horizon (A, B, and C horizons). In the A horizon, 2,4-D mineralization commenced instantaneously and the mineralization rate followed first-order kinetics. In both the B and C horizons, 2,4-D mineralization only commenced after a lag period of typically 5 to 7 days and the mineralization rate was biphasic. In the A horizon, 2,4-D mineralization parameters including the first-order mineralization rate constant (k ₁), the growth-linked mineralization rate constant (k ₂) and total 2,4-D mineralization at the end of the experiment at 56 days, were most strongly correlated to parameters describing 2,4-D sorption by soil, but were also adequately correlated to soil organic carbon content, soil pH, and carbonate content. In both B and C horizons, there was no significant correlation between 2,4-D mineralization and 2,4-D sorption parameters, and the correlation between soil properties and 2,4-D mineralization parameters was very poor. The k ₁ significantly decreased in sequence of A horizon (0.113% day^?1) > B horizon (0.024% day^?1) = C horizon (0.026% day^?1) and in each soil horizon was greater than k ₂. Total 2,4-D mineralization at 56 days also significantly decreased in sequence of A horizon (42%) > B horizon (31%) = C horizon (27%). In the A horizon, slope position had little influence on k ₁ or k ₂, except that k ₁ was significantly greater in upper slopes (0.170% day^?1) than in lower slopes (0.080% day^?1). Neither k ₁ nor k ₂ was significantly influenced by slope position in the B or C horizons. Total 2,4-D mineralization at 56 days was not influenced by slope positions in any horizon. Our results suggest that, when predicting 2,4-D transport at the field scale, pesticide fate models should consider the strong differences in 2,4-D mineralization between surface and subsurface horizons. This suggests that 2,4-D mineralization is best predicted using a model that has the ability to describe a range of non-linear mineralization curves. We also conclude that the horizontal variations in 2,4-D mineralization at the field scale will be difficult to consider in predictions of 2,4-D transport at the field scale because, within each horizon, 2,4-D mineralization was highly variable across the twenty-five soil cores, and this variability was poorly correlated to soil properties or soil-landscape position.     

Assessing Spatial, Temporal, and Analytical Variation of Groundwater Chemistry in a Large Nuclear Complex, USA

Statistical analyses were applied at the Hanford Site, USA, to assess groundwater contamination problems that included (1) determining local backgrounds to ascertain whether a facility is affecting the groundwater quality and (2) determining a ‘pre-Hanford' groundwater background to allow formulation of background-based cleanup standards. The primary purpose of this paper is to extend the random effects models for (1) assessing the spatial, temporal, and analytical variability of groundwater background measurements; (2) demonstrating that the usual variance estimate s ², which ignores the variance components, is a biased estimator; (3) providing formulas for calculating the amount of bias; and (4) recommending monitoring strategies to reduce the uncertainty in estimating the average background concentrations. A case study is provided. Results indicate that (1) without considering spatial and temporal variability, there is a high probability of false positives, resulting in unnecessary remediation and/or monitoring expenses; (2) the most effective way to reduce the uncertainty in estimating the average background, and enhance the power of the statistical tests in general, is to increase the number of background wells; and (3) background for a specific constituent should be considered as a statistical distribution, not as a single value or threshold. The methods and the related analysis of variance tables discussed in this paper can be used as diagnostic tools in documenting the extent of inherent spatial and/or temporal variation and to help select an appropriate statistical method for testing purposes.     

Application of processed organic municipal solid waste on agricultural land – a scenario analysis

Source separation, composting and anaerobic digestion, with associated land application, are increasingly being considered as alternative waste management strategies to landfilling and incineration of municipal solid waste (MSW). Environmental life cycle assessments are a useful tool in political decision-making about waste management strategies. However, due to the diversity of processed organic MSW and the situations in which it can be applied, the environmental impacts of land application are very hard to determine by experimental means. In the current study, we used the agroecosystem model Daisy to simulate a range of different scenarios representing different geographical areas, farm and soil types under Danish conditions and legislation. Generally, the application of processed organic MSW resulted in increased emissions compared with the corresponding standard scenarios, but with large differences between scenarios. Emission coefficients for nitrogen leaching to the groundwater ranged from 0.03 to 0.87, while those for nitrogen lost to surface waters through tile drains ranged from 0 to 0.30. Emission coefficients for N₂O formation ranged from 0.013 to 0.022 and for ammonia volatilization from 0.016 to 0.11. These estimates are within reasonable range of observed values under similar conditions. Furthermore, a sensitivity analysis showed that the estimates were not very sensitive to the mineralization dynamics of the processed organic MSW. The results show that agroecosystem models can be powerful tools to estimate the environmental impacts of land application of processed MSW under different conditions. Despite this, agroecosystem models have only been used to a very limited degree for this purpose.     

Modeling of non-point source pollution in a Mediterranean drainage basin

SWAT ver. 2000 was used to predict hydrographs, and sediment, nitrate and total phosphorus loadings from a 1349 km² mountainous/agricultural watershed in Northern Greece. The model was calibrated and verified using continuous meteorological data from eight stations within the drainage area, and runoff, sediment and nutrient concentrations measured at nine stations located within the main tributaries of the watershed, for the time period from May 1st, 1998 to January 31st, 2000. Model validation methodology and resulting input parameters appropriate for Mediterranean drainage basins are presented. Predicted by the model hydrographs, sedimentographs and pollutographs are plotted against observed values and show good agreement. Model performance is evaluated using the root mean square error computation and scattergrams of predicted versus observed data. The validated model is also used to test the effectiveness of three alternative cropping scenarios in reducing nutrient loadings from the agricultural part of the watershed. The study showed that this model, if properly validated, can be used effectively in testing management scenarios in Mediterranean drainage basins.