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Predicting Risks from Down-the-Drain Chemicals in a Developing Country: Mexico and Linear Alkylbenzene Sulfonate as a Case Study

机译:预测发展中国家排水化学品的风险:墨西哥和线性烷基苯磺酸盐为例

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It is recognized that the amount of natural dilution available can make a significant difference in the exposure and risk assessment of chemicals that emanate from wastewater treatment plants (WWTPs). However, data availability is a common limiting factor in exposure assessments for emerging markets. In the present study, we used a novel approach to derive dilution factors for the receiving waters within 5km of wastewater discharge points in Mexico by combining locally measured river volumes, ecoregion categorization, data on WWTP capacity, and global river network models. Distributions of wastewater effluent into receiving stream dilution factors were developed for the entire country and organized by ecoregion type to explore spatial differences. The distribution of dilution factors in Mexico ranged from 1000 in tropical and temperate ecoregions to 1 in desert ecoregions. To demonstrate its utility, dilution factors were used to develop a probabilistic model to explore the potential ecological risks of the high-volume surfactant linear alkylbenzene sulfonate (LAS), commonly used in down-the-drain cleaning products. The predicted LAS river exposure values were below the predicted no-effect concentration in all regions. The methodology developed for Mexico can be used to derive refined exposure assessments in other countries with emerging markets throughout the world, resulting in more realistic risk assessments. Environ Toxicol Chem 2018;37:2475-2486. (c) 2018 SETAC
机译:公认的是,可用的自然稀释量可以对废水处理厂(WWTP)排放的化学物质的暴露和风险评估产生重大影响。但是,数据可用性是新兴市场风险评估中常见的限制因素。在本研究中,我们通过结合当地测量的河流流量,生态区分类,污水处理厂容量数据和全球河流网络模型,采用一种新颖的方法来得出墨西哥废水排放点5公里以内的接收水的稀释因子。为整个国家开发了废水入接收流稀释因子的分布,并按生态区域类型进行了组织,以探讨空间差异。墨西哥的稀释因子分布范围从热带和温带生态区的> 1000到沙漠生态区的1。为了证明其实用性,使用稀释因子开发了一个概率模型,以研究通常用于排水清洁产品的高容量表面活性剂线性烷基苯磺酸盐(LAS)的潜在生态风险。预测的LAS河暴露值低于所有区域的预测无效应浓度。为墨西哥开发的方法可用于在具有全球新兴市场的其他国家/地区中进行精确的暴露评估,从而得出更现实的风险评估。 Environ Toxicol Chem 2018; 37:2475-2486。 (c)2018年SETAC

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