Quantifying data quality of continuous emissions monitoring systems in China
报 告 人:: 常象宇
报告地点:: 数学与统计学院 4楼报告厅
报告时间:: 2018年11月05日星期一10:00-11:30

We evaluate the data quality of Continuous Emissions Monitoring Systems (CEMS) in China by proposing a new data quality assessment framework. First, we show the quality of waste-gas and waste-water monitoring data are both getting better from January 1, 2016 to June 30, 2017. Second, our result indicates that state-controlled factories, large-scale factories and factories with foreign investment or with funds from Hong Kong, Macao and Taiwan get better data quality scores. However, private enterprises perform poorly and call for more attention from authorities. Third, we find that the quality of CEMS data in underdeveloped regions of China where suffer from serious air pollution is worse. And this situation may hamper further improvement of environment. To achieve continued CEMS data quality improvement, our results suggest a need to differentiated regional CEMS-related policy. Fourth, we compare the factories with poor CEMS data quality with the list of factories received serious administrative penalty in 2016-2017 and find a striking overlap. To detect factories with suspicious pollution activities, clustering analysis and logistic regression model are used. Furthermore, we show the two approaches provide a potential application for a new quantitative monitoring strategy of pollutant factory.

发 布 人:吴双 发布时间: 2018-11-04