Abstract:
A modeling framework was created for the development of spatially explicit aquatic exposure models for any region or country of interest for chemicals disposed of down the drain. The framework relies on globally available data sets for river flow and population, and locally available data sets for wastewater treatment infrastructure and domestic water use, and leverages the iSTREEM® chemical routing algorithm. The framework was applied to China and Japan as case study countries. Spatially explicit population data were obtained from WorldPop. River flows covering the spatial extent of the two countries were derived from a high-resolution surface runoff gridded data set that was based on the Curve Number approach and combined with the hydrology network for catchments and rivers from HydroBASINS and HydroSHEDS data sets. Publicly available data from government sources were used for estimating per capita water use and wastewater treatment infrastructure. To demonstrate the framework, the China model was used to predict the levels of the antifungal agent climbazole in rivers across the country, and the Japan model was used to predict river concentrations of linear alkylbenzene sulfonate. For both chemicals, the comparison of measured to modeled values showed good agreement, using linear regression analysis (R2 ≥ 0.96). The framework presented in this study provides a systematic and robust approach to develop spatially resolved exposure models that can be extrapolated to any country or region, allowing more accurate risk assessment of chemicals disposed down the drain by leveraging concentration distributions generated by the model. Integr Environ Assess Manag 2021;00:1-12. © 2021 SETAC.
摘要:
创建了一个建模框架,用于为任何感兴趣的区域或国家开发空间上明确的水生暴露模型,以处理在下水道中的化学物质。该框架依赖于全球可用的河流流量和人口数据集,以及当地可获得的废水处理基础设施和生活用水数据集,并利用iSTREEM®化学路由算法。该框架应用于中国和日本作为案例研究国家。从WorldPop获得了空间上明确的种群数据。涵盖两个国家空间范围的河流流量来自高分辨率的地表径流网格化数据集,该数据集基于曲线数方法,并与来自HydroBASINS和HydroSHEDS数据集的流域和河流的水文网络相结合。政府来源的公开数据用于估计人均用水量和废水处理基础设施。为了演示框架,中国模型被用来预测全国河流中抗真菌药物的水平,并利用日本模型预测了河流中直链烷基苯磺酸盐的浓度。对于这两种化学品,测量值与建模值的比较显示出良好的一致性,采用线性回归分析(R2≥0.96)。本研究提出的框架提供了一种系统和强大的方法来开发空间分辨暴露模型,可以外推到任何国家或地区,通过利用模型产生的浓度分布,允许对排放的化学品进行更准确的风险评估。Integr环境评估管理2021;00:1-12。©2021SETAC。