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| Volatile organic compound emissions and odor characteristics of typical automotive coating industry |
| JI Yu-jing1, CHEN Yu-qing1, XIE Long-fei1, WANG Shi-yi1, SUN Xiao-jing1, LU Li-wen1, HUANG Hao-min1,2, YE Dai-qi1,2 |
1. School of Environment and Energy, South China University of Technology, Guangzhou 510006, China;
2. National Engineering Laboratory for VOCs Pollution Control Technology and Equipment, Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control (SCUT), Guangdong Provincial Engineering and Technology Research Centre for Environmental Risk Prevention and Emergency Disposal, South China University of Technology, Guangzhou 510006, China |
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Abstract This study conducted sampling and testing on the waste gases generated from different processes in typical automobile manufacturing plant coating workshops located in northern and southern China. It meticulously analyzed the emission characteristics of volatile organic compounds (VOCs) and odor characteristics, and extensively explored odor characteristic prediction methods from multiple dimensions. The results revealed that OVOCs, alkanes, and aromatic hydrocarbons are the predominant components in the exhaust gases, with OVOCs constituting 73.80% to 99.03% of the odor activity value (OAV), thereby classifying them the most significant odor-contributing substance category. Acetaldehyde, n-butyl acetate, isobutyl acetate, and n-butyraldehyde all significantly contributed to the odor at both the inlet and outlet of the treatment equipment. Furthermore, electronic noses were used to classify waste gas samples, achieving 100% and 98.1% accuracy rates for inlet and outlet, respectively. Quantification of odour was achieved through regression analysis, which revealed a strong linear correlation between OVOCs substance concentration and OAVmax and OAVsum. The electronic nose technology combined with BP neural networks was found to be an effective predictor of OAVmax and OAVsum. Additionally, a logarithmic relationship was observed between OVOCs substance concentration, OAVmax, OAVsum, and odor concentration.
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Received: 15 October 2024
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Corresponding Authors:
黄皓旻,责任作者,高级工程师,huanghm@scut.edu.cn
E-mail: huanghm@scut.edu.cn
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