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A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification
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作者 Tienan Ju Mei Lei +4 位作者 Guanghui Guo Jinglun Xi Yang Zhang Yuan Xu Qijia Lou 《Frontiers of Environmental Science & Engineering》 SCIE EI CSCD 2023年第1期87-97,共11页
Industrial emissions are the main source of atmospheric pollutants in China.Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmosph... Industrial emissions are the main source of atmospheric pollutants in China.Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely.Based on China’s coking enterprises in 2020,we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards(QRPES)into the construction of support vector regression(SVR)and random forest regression(RFR)prediction methods for SO_(2) emission of coking enterprises in China.The results show that,affected by the types of coke ovens and regions,China’s current coking enterprises have implemented a total of 21 emission standards,with marked differences.After adding QRPES,it was found that the root mean squared error(RMSE)of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a,and the R2 increased from 0.890 and 0.881 to 0.926 and 0.945,respectively.This shows that the QRPES can greatly improve the prediction accuracy,and the SO_(2) emissions of each enterprise are highly correlated with the strictness of standards.The predicted result shows that 45%of SO_(2) emissions from Chinese coking enterprises are concentrated in Shanxi,Shaanxi and Hebei provinces in central China.The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants. 展开更多
关键词 Industrial atmospheric pollutants pollutant emission standards Quantitative method Machine learning Single enterprise
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Design and demonstration of a next-generation air quality attainment assessment system for PM_(2.5)and O_3 被引量:13
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作者 Hua Wang Yun Zhu +9 位作者 Carey Jang Che-Jen Lin Shuxiao Wang Joshua S.Fu Jian Gao Shuang Deng Junping Xie Dian Ding Xuezhen Qiu Shicheng Long 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2015年第3期178-188,共11页
Due to the increasingly stringent standards, it is important to assess whether the proposed emission reduction will result in ambient concentrations that meet the standards. The Software for Model Attainment Test-Comm... Due to the increasingly stringent standards, it is important to assess whether the proposed emission reduction will result in ambient concentrations that meet the standards. The Software for Model Attainment Test-Community Edition (SMAT-CE) is developed for demonstrating attainment of air quality standards of O3 and PM2.5. SMAT-CE improves computational efficiency and provides a number of advanced visualization and analytical functionalities on an integrated GIS platform. SMAT-CE incorporates historical measurements of air quality parameters and simulated air pollutant concentrations under a number of emission inventory scenarios to project the level of compliance to air quality standards in a targeted future year. An application case study of the software based on the U.S. National Ambient Air Quality Standards (NAAQS) shows that SMAT-CE is capable of demonstrating the air quality attainment of annual PM2.5 and 8-hour O3 for a proposed emission control policy. 展开更多
关键词 Air quality standards Attainment test Air pollution GIS Emission control
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