A novel approach for VOC source apportionment combining characteristic factor and pattern recognition technology in a Chinese industrial area

被引:15
作者
Jing, Deji [1 ]
Cheng, Nana [1 ]
Zhang, Cheng [1 ]
Chen, Ziwei [1 ]
Cai, Xingnong [1 ]
Li, Sujing [1 ]
Zhao, Jingkai [2 ]
Wang, Qiaoli [2 ]
Li, Wei [1 ]
机构
[1] Zhejiang Univ, Coll Chem & Biol Engn, Key Lab Biomass Chem Engn, Minist Educ,Inst Ind Ecol & Environm, Yuquan Campus, Hangzhou 310027, Peoples R China
[2] Zhejiang Univ Technol, Coll Environm, Hangzhou 310032, Peoples R China
来源
JOURNAL OF ENVIRONMENTAL SCIENCES | 2022年 / 121卷
关键词
VOC; Source apportionment; Characteristic factors; Pattern recognition; Industrial areas; VOLATILE ORGANIC-COMPOUNDS; HEALTH-RISK ASSESSMENT; RIVER DELTA REGION; OZONE FORMATION; EMISSION CHARACTERISTICS; SPATIAL-DISTRIBUTION; HANGZHOU; EXPOSURE; SITE;
D O I
10.1016/j.jes.2021.08.056
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Volatile organic compound (VOC) emission control and source apportionment in small-scale industrial areas have become key topics of air pollution control in China. This study proposed a novel characteristic factor and pattern recognition (CF-PR) model for VOC source apportionment based on the similarity of characteristic factors between sources and receptors. A simulation was carried out in a typical industrial area with the CF-PR model involving simulated receptor samples. Refined and accurate source profiles were constructed through in situ sampling and analysis, covering rubber, chemicals, coating, electronics, plastics, printing, incubation and medical treatment industries. Characteristic factors of n-undecane, styrene, o-xylene and propane were identified. The source apportionment simulation results indicated that the predicted contribution rate was basically consistent with the real contribution rate. Compared to traditional receptor models, this method achieves notable advantages in terms of refinement and timeliness at similar accuracy, which is more suitable for VOC source identification and apportionment in small-scale industrial areas. ?? 2022 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.
引用
收藏
页码:25 / 37
页数:13
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