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在欧洲范围内,对 PCB-153 浓度在空气中、沉积物、土壤和水生生物群中的时空变化进行建模和监测。

Modeled and monitored variation in space and time of PCB-153 concentrations in air, sediment, soil and aquatic biota on a European scale.

机构信息

Department of Environmental Sciences, Institute for Water and Wetland Research, Radboud University Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands.

出版信息

Sci Total Environ. 2010 Aug 15;408(18):3831-9. doi: 10.1016/j.scitotenv.2009.11.037. Epub 2009 Dec 24.

Abstract

We evaluated various modeling options for estimating concentrations of PCB-153 in the environment and in biota across Europe, using a nested multimedia fate model coupled with a bioaccumulation model. The most detailed model set up estimates concentrations in air, soil, fresh water sediment and fresh water biota with spatially explicit environmental characteristics and spatially explicit emissions to air and water in the period 1930-2005. Model performance was evaluated with the root mean square error (RMSE(log)), based on the difference between estimated and measured concentrations. The RMSE(log) was 5.4 for air, 5.6-6.3 for sediment and biota, and 5.5 for soil in the most detailed model scenario. Generally, model estimations tended to underestimate observed values for all compartments, except air. The decline in observed concentrations was also slightly underestimated by the model for the period where measurements were available (1989-2002). Applying a generic model setup with averaged emissions and averaged environmental characteristics, the RMSE(log) increased to 21 for air and 49 for sediment. For soil the RMSE(log) decreased to 3.5. We found that including spatial variation in emissions was most relevant for all compartments, except soil, while including spatial variation in environmental characteristics was less influential. For improving predictions of concentrations in sediment and aquatic biota, including emissions to water was found to be relevant as well.

摘要

我们使用嵌套的多媒体命运模型与生物积累模型相结合,评估了各种用于估算欧洲环境和生物群中 PCB-153 浓度的建模选项。最详细的模型设置使用具有空间显式环境特征的空气、土壤、淡水沉积物和淡水生物群中浓度的空间显式排放物来估算 1930 年至 2005 年期间的浓度。使用均方根误差 (RMSE(log)) 评估模型性能,该值基于估计浓度与实测浓度之间的差异。在最详细的模型方案中,空气的 RMSE(log)为 5.4,沉积物和生物群为 5.6-6.3,土壤为 5.5。总体而言,除了空气之外,所有部分的模型估算值都倾向于低估观察值。对于有测量值的时间段(1989-2002 年),模型也低估了观察到的浓度下降。应用具有平均排放和平均环境特征的通用模型设置,空气的 RMSE(log)增加到 21,沉积物的 RMSE(log)增加到 49。对于土壤,RMSE(log)降低至 3.5。我们发现,除了土壤之外,排放的空间变化对所有部分都最相关,而环境特征的空间变化影响较小。对于提高沉积物和水生生物群中浓度的预测,发现包括对水的排放也很重要。

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