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模拟水体中有机微量污染物的光降解动力学:以黄河口为例。

Modeling photodegradation kinetics of organic micropollutants in water bodies: A case of the Yellow River estuary.

机构信息

Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Linggong Road 2, Dalian 116024, China.

Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Linggong Road 2, Dalian 116024, China.

出版信息

J Hazard Mater. 2018 May 5;349:60-67. doi: 10.1016/j.jhazmat.2018.01.051. Epub 2018 Jan 31.

Abstract

Predicting photodegradation rate constants (k) of pollutants in water bodies is important for assessing their persistence and fate. This prediction used to be based on the k values determined under laboratory conditions that seldom consider underwater downward sunlight attenuation in the field. We studied a procedure to predict k taking the Yellow River estuary and two model chemicals (sulfamethoxazole and acyclovir) as a case. Models were developed for predicting underwater sunlight intensities from optically-active substances. Based on the predicted underwater sunlight intensities, hourly variation of k for the model compounds was predicted as a function of water depth, for a fresh water, an estuarine water and a seawater body in the estuary. Results show that photodegradation half-lives (t) of the two compounds will be underestimated by dozens of times if underwater downward sunlight attenuation and intensity variation are not considered. Outdoor validation experiments show the maximum deviation between the predicted and measured k values is a factor of 2. The developed models can be employed to predict k of environmental chemicals in coastal water bodies once they are locally calibrated.

摘要

预测水体中污染物的光降解速率常数 (k) 对于评估它们的持久性和归宿非常重要。过去,这种预测是基于在实验室条件下确定的 k 值,而这些条件很少考虑到野外水下向下的阳光衰减。我们研究了一种考虑黄河河口和两种模型化学品(磺胺甲恶唑和阿昔洛韦)的预测 k 值的方法。开发了用于从光活性物质预测水下阳光强度的模型。基于预测的水下阳光强度,预测了模型化合物在河口淡水、河口咸水和海水体中随水深变化的 k 值的每小时变化。结果表明,如果不考虑水下向下的阳光衰减和强度变化,两种化合物的光降解半衰期 (t) 将被低估几十倍。户外验证实验表明,预测和测量 k 值之间的最大偏差是 2 倍。一旦在当地进行校准,所开发的模型就可以用于预测沿海水体中环境化学品的 k 值。

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