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Guo Z, Chen X, Wu D, Huo Y, Cheng A, Liu Y, Li Q, Chen J. Higher Toxicity of Gaseous Organics Relative to Particulate Matters Emitted from Typical Cooking Processes. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:17022-17031. [PMID: 37874853 DOI: 10.1021/acs.est.3c05425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Cooking emission is known to be a significant anthropogenic source of air pollution in urban areas, but its toxicities are still unclear. This study addressed the toxicities of fine particulate matter (PM2.5) and gaseous organics by combining chemical fingerprinting analysis with cellular assessments. The cytotoxicity and reactive oxygen species activity of gaseous organics were ∼1.9 and ∼8.3 times higher than those of PM2.5, respectively. Moreover, these values of per unit mass PM2.5 were ∼7.1 and ∼15.7 times higher than those collected from ambient air in Shanghai. The total oleic acid equivalent quantities for carcinogenic and toxic respiratory effects of gaseous organics, as estimated using predictive models based on quantitative structure-property relationships, were 1686 ± 803 and 430 ± 176 μg/mg PM2.5, respectively. Both predicted toxicities were higher than those of particulate organics, consistent with cellular assessment. These health risks are primarily attributed to the high relative content and toxic equivalency factor of the organic compounds present in the gas phase, including 7,9-di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione, 2-ethylhexanoic acid, and 2-phenoxyethoxybenzene. Furthermore, these compounds and fatty acids were identified as prominent chemical markers of cooking-related emissions. The obtained results highlight the importance of control measures for cooking-emitted gaseous organics to reduce the personal exposure risks.
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Affiliation(s)
- Zihua Guo
- Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Fudan University, Shanghai 200433, China
| | - Xiu Chen
- Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Fudan University, Shanghai 200433, China
| | - Di Wu
- Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Fudan University, Shanghai 200433, China
| | - Yaoqiang Huo
- Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Fudan University, Shanghai 200433, China
- Key Laboratory of Environmental Pollution Control and Remediation at Universities of Inner Mongolia Autonomous Region, College of Resources and Environmental engineering, Inner Mongolia University of Technology, Hohhot 010051, China
| | - Anyuan Cheng
- Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Fudan University, Shanghai 200433, China
| | - Yuzhe Liu
- Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Fudan University, Shanghai 200433, China
| | - Qing Li
- Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Fudan University, Shanghai 200433, China
- Shanghai Institute of Eco-Chongming (SIEC), 20 Cuiniao Road, Chenjia Town, Chongming District, Shanghai 202162, China
| | - Jianmin Chen
- Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Fudan University, Shanghai 200433, China
- Shanghai Institute of Eco-Chongming (SIEC), 20 Cuiniao Road, Chenjia Town, Chongming District, Shanghai 202162, China
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Wang Y, Wang F, Min R, Song G, Song H, Zhai S, Xia H, Zhang H, Ru X. Contribution of local and surrounding anthropogenic emissions to a particulate matter pollution episode in Zhengzhou, Henan, China. Sci Rep 2023; 13:8771. [PMID: 37253757 DOI: 10.1038/s41598-023-35399-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 05/17/2023] [Indexed: 06/01/2023] Open
Abstract
In this study, we simulated the spatial and temporal processes of a particulate matter (PM) pollution episode from December 10-29, 2019, in Zhengzhou, the provincial capital of Henan, China, which has a large population and severe PM pollution. As winter is the high incidence period of particulate pollution, winter statistical data were selected from the pollutant observation stations in the study area. During this period, the highest concentrations of PM2.5 (atmospheric PM with a diameter of less than 2.5 µm) and PM10 (atmospheric PM with a diameter of less than 10 µm) peaked at 283 μg m-3 and 316 μg m-3, respectively. The contribution rates of local and surrounding regional emissions within Henan (emissions from the regions to the south, northwest, and northeast of Zhengzhou) to PM concentrations in Zhengzhou were quantitatively analyzed based on the regional Weather Research and Forecasting model coupled with Chemistry (WRF/Chem). Model evaluation showed that the WRF/Chem can accurately simulate the spatial and temporal variations in the PM concentrations in Zhengzhou. We found that the anthropogenic emissions south of Zhengzhou were the main causes of high PM concentrations during the studied episode, with contribution rates of 14.39% and 16.34% to PM2.5 and PM10, respectively. The contributions of anthropogenic emissions from Zhengzhou to the PM2.5 and PM10 concentrations in Zhengzhou were 7.94% and 7.29%, respectively. The contributions of anthropogenic emissions from the area northeast of Zhengzhou to the PM2.5 and PM10 concentrations in Zhengzhou were 7.42% and 7.18%, respectively. These two areas had similar contributions to PM pollution in Zhengzhou. The area northeast of Zhengzhou had the lowest contributions to the PM2.5 and PM10 concentrations in Zhengzhou (5.96% and 5.40%, respectively).
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Affiliation(s)
- Yaobin Wang
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004, Henan, China
- Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, Henan, China
| | - Feng Wang
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004, Henan, China
- Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, Henan, China
| | - Ruiqi Min
- Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, Henan, China
| | - Genxin Song
- Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, Henan, China.
| | - Hongquan Song
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004, Henan, China.
- Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security, Henan University, Kaifeng, 475004, Henan, China.
| | - Shiyan Zhai
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004, Henan, China
- Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, Henan, China
| | - Haoming Xia
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004, Henan, China
| | - Haopeng Zhang
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004, Henan, China
- Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, Henan, China
| | - Xutong Ru
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, 475004, Henan, China
- Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, Henan, China
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Lin P, Gao J, Xu Y, Schauer JJ, Wang J, He W, Nie L. Enhanced commercial cooking inventories from the city scale through normalized emission factor dataset and big data. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 315:120320. [PMID: 36191795 DOI: 10.1016/j.envpol.2022.120320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 09/12/2022] [Accepted: 09/27/2022] [Indexed: 06/16/2023]
Abstract
Cooking emission inventories always have poor spatial resolutions when applying with traditional methods, making their impacts on ambient air and human health remain obscure. In this study, we created a systematic dataset of cooking emission factors (CEFs) and applied it with a new data source, cooking-related point of interest (POI) data, to build up highly spatial resolved cooking emission inventories from the city scale. Averaged CEFs of six particulate and gaseous species (PM, OC, EC, NMHC, OVOCs, VOCs) were 5.92 ± 6.28, 4.10 ± 5.50, 0.05 ± 0.05, 22.54 ± 20.48, 1.56 ± 1.44, and 7.94 ± 6.27 g/h normalized in every cook stove, respectively. A three-field CEF index containing activity and emission factor species was created to identify and further build a connection with cooking-related POI data. A total of 95,034 cooking point sources were extracted from Beijing, as a study city. In downtown areas, four POI types were overlapped in the central part of the city and radiated into eight distinct directions from south to north. Estimated PM/VOC emissions caused by cooking activities in Beijing were 4.81/9.85 t per day. A 3D emission map showed an extremely unbalanced emission density in the Beijing region. Emission hotspots were seen in Central Business District (CBD), Sanlitun, and Wangjing in Chaoyang District and Willow and Zhongguancun in Haidian District. PM/VOC emissions could be as high as 16.6/42.0 kg/d in the searching radius of 2 km. For PM, the total emissions were 417.4, 389.0, 466.9, and 443.0 t between Q1 and Q4 2019 in Beijing, respectively. The proposed methodology is transferrable to other Chinese cities for deriving enhanced commercial cooking inventories and potentially highlighting the further importance of cooking emissions on air quality and human health.
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Affiliation(s)
- Pengchuan Lin
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Jian Gao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Yisheng Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - James J Schauer
- Environmental Chemistry and Technology Program, University of Wisconsin-Madison, Madison, WI, 53706, USA; Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, 53718, USA
| | - Jiaqi Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Wanqing He
- Beijing Key Laboratory of Urban Atmospheric Volatile Organic Compounds Pollution Control and Application, Beijing Municipal Research Institute of Eco-Environmental Protection, Beijing, 100037, China
| | - Lei Nie
- Beijing Key Laboratory of Urban Atmospheric Volatile Organic Compounds Pollution Control and Application, Beijing Municipal Research Institute of Eco-Environmental Protection, Beijing, 100037, China
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