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Zhao N, Zhang H, Wang G. Revealing the nonlinear responses of PM 2.5 and O 3 to VOC and NO x emissions from various sources in Shandong, China. JOURNAL OF HAZARDOUS MATERIALS 2025; 489:137655. [PMID: 39983648 DOI: 10.1016/j.jhazmat.2025.137655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2024] [Revised: 02/08/2025] [Accepted: 02/16/2025] [Indexed: 02/23/2025]
Abstract
Fine particulate matter (PM2.5) and ozone (O3) are the primary air pollutants that degrade air quality in China. Reducing precursor emissions reasonably, volatile organic compound (VOC) and nitrogen oxides (NOx), are the keys to achieving effective improvement of air quality. To better tackle this challenge, we revealed the nonlinear response of PM2.5 and O3 concentrations to precursor reduction from various sources in Shandong, China using the Weather Research and Forecasting-Comprehensive Air Quality Model Extensions (WRF-CAMx) models and Empirical Kinetics Modeling Approach (EKMA). VOC reductions from all sources presented a positive effect in reducing PM2.5 and O3 concentrations in four seasons, while both levels showed a trend of first increasing and then decreasing as the proportion of NOx reduction increased, except in summer. Focusing on VOC emissions reduction first is critical for reducing PM2.5 concentrations and the long-term improvement in PM2.5 requires strengthening the deep emission reduction of NOx. The reduction ratios of VOC and NOx emissions from all sources with 3:1 in spring and autumn, and 1:2 in summer were more conducive to reducing O3 concentrations. The reasonable emission reduction ratios of VOCs and NOx from industry, power, transportation, and residential sources were also evaluated. For example, the reduction ratios of VOC and NOx emissions with 2:1 from industry and residential, and 1:2 from power and transportation are beneficial for decreasing PM2.5 concentrations. This study offers valuable insights for formulating rational and effective PM2.5 and O3 control strategies.
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Affiliation(s)
- Na Zhao
- Environment Research Institute, Shandong University, Qingdao 266237, China
| | - Hanyu Zhang
- Department of Environmental Science and Engineering, Beijing Technology and Business University, Beijing 100048, China.
| | - Gang Wang
- Department of Environmental and Safety Engineering, College of Chemistry and Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, China.
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Ding Z, Li Y, Fu Q, Tian M, Wang F, Wang Y, Huang K. Volatile organic compounds in a typical petrochemical production area in Shanghai, China: Source profiles, human health and environmental impacts. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2025; 372:126074. [PMID: 40107491 DOI: 10.1016/j.envpol.2025.126074] [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: 10/09/2024] [Revised: 03/13/2025] [Accepted: 03/15/2025] [Indexed: 03/22/2025]
Abstract
Volatile organic compounds (VOCs) emitted from industrial facilities include significant precursors to the formation of aerosols and ozone in urban areas, often affecting atmospheric environments and public health. By investigating the VOC emission profiles across nine petrochemical production units, the predominant component in VOC emission profiles was alkanes, followed by oxygenated VOCs, aromatics, halocarbons, and alkenes. Aldehydes were identified as major contributors to odorous pollution. Chloroform, benzene, and 1,2-dibromoethane from petrochemical industry emissions exceeded health thresholds and will require targeted reduction measures. Additionally, three years of ambient VOC measurements (2020-2022) at two typical sites were analyzed to clarify VOC pollution characteristics and environmental impacts. The VOCs measured at both the Jiangwan residential (JW) and petrochemical industrial (PI) sites exhibited similar diurnal variations but different seasonal patterns. Source apportionment of VOCs using a positive matrix factorization model revealed five sources at PI and six sources at JW. Specific VOCs (e.g., dichloromethane) identified at JW were related to the petrochemical industry and solvent usage processes. Quantification of VOC photochemical reactivity indicated that the aromatic industry and solvent usage from the petrochemical industry significantly contributed more to both ozone and secondary organic aerosol formation potential than other sources, which underscores the need for stringent control measures by policymakers, particularly focusing on aromatic hydrocarbon production processes and the adoption of green solvents. The findings provide valuable insights for developing targeted VOC control strategies to mitigate their adverse effects on human health and environmental quality in regions heavily influenced by petrochemical activities.
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Affiliation(s)
- Zhijian Ding
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433, China
| | - Yuewu Li
- Shanghai Environmental Monitoring Center, Shanghai, 200030, China
| | - Qingyan Fu
- Shanghai Academy of Environmental Sciences, Shanghai, 200233, China
| | - Mengke Tian
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433, China
| | - Fanglin Wang
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong
| | - Yunkai Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433, China
| | - Kan Huang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433, China; Institute of Eco-Chongming, No.20 Cuiniao Road, Chen Jiazhen, Shanghai, 202162, China; IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, 200433, China.
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Wei Y, Jing X, Chen Y, Sun W, Zhang Y, Zhu R. Spatial-Temporal Characteristics, Source Apportionment, and Health Risks of Atmospheric Volatile Organic Compounds in China: A Comprehensive Review. TOXICS 2024; 12:787. [PMID: 39590967 PMCID: PMC11598060 DOI: 10.3390/toxics12110787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2024] [Revised: 10/19/2024] [Accepted: 10/25/2024] [Indexed: 11/28/2024]
Abstract
Volatile organic compounds (VOCs) are ubiquitous in the atmosphere, posing significant adverse impacts on air quality and human health. However, current research on atmospheric VOCs mainly focuses on specific regions or industries, without comprehensive national-level analysis. In this study, a total of 99 articles on atmospheric VOCs in China published from 2015 to 2024 were screened, and data on their concentrations, source apportionment, and health risks were extracted and summarized. The results revealed that the annual average concentrations of TVOCs and their groups in China generally increased and then decreased between 2011 and 2022, peaking in 2018-2019. A distinct seasonal pattern was observed, with the highest concentrations occurring in winter, followed by autumn, spring, and summer. TVOC emissions were highly concentrated in northern and eastern China, mainly contributed by alkanes and alkenes. Source apportionment of VOCs indicated that vehicle sources (32.9% ± 14.3%), industrial emissions (18.0% ± 12.8%), and other combustion sources (13.0% ± 13.0%) were the primary sources of VOCs in China. There was a significant positive correlation (p < 0.05) between the annual mean VOC concentration and population size, and a notable negative correlation (p < 0.05) with GDP per capita. Atmospheric VOCs had no non-carcinogenic risk (HI = 0.5) but exhibited a probable carcinogenic risk (7.5 × 10-5), with relatively high values for 1,2-dibromoethane, 1,2-dichloroethane, and naphthalene. The health risk was predominantly driven by halocarbons. These findings are essential for a better understanding of atmospheric VOCs and for developing more targeted VOC control measures.
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Affiliation(s)
- Yangbing Wei
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China;
- Institute of Atmospheric Environment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
- School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China; (X.J.); (Y.C.); (W.S.)
| | - Xuexue Jing
- School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China; (X.J.); (Y.C.); (W.S.)
| | - Yaping Chen
- School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China; (X.J.); (Y.C.); (W.S.)
| | - Wenxin Sun
- School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China; (X.J.); (Y.C.); (W.S.)
| | - Yuzhe Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China;
- Institute of Atmospheric Environment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Rencheng Zhu
- School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China; (X.J.); (Y.C.); (W.S.)
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Ren H, Xia Z, Yao L, Qin G, Zhang Y, Xu H, Wang Z, Cheng J. Investigation on ozone formation mechanism and control strategy of VOCs in petrochemical region: Insights from chemical reactivity and photochemical loss. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 914:169891. [PMID: 38190918 DOI: 10.1016/j.scitotenv.2024.169891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 12/11/2023] [Accepted: 01/01/2024] [Indexed: 01/10/2024]
Abstract
To investigate disparities in VOCs pollution characteristics, O3 generation activity, and source apportionment outcomes resulting from photooxidation, online monitoring of 106 VOCs was conducted in Jinshan District, Shanghai from April to October 2020. The observed VOCs concentrations (VOCs-obs) were 47.1 ppbv and 59.2 ppbv for clear days (CD) and O3-polluted days (OPD), respectively. The increase in daytime concentrations of alkenes is a significant factor contributing to the enhanced atmospheric photochemical activity during the OPD period, corroborated by VOCs-loss, ozone formation potential (OFP), propy-equiv concentration, and LOH. The sensitivity analysis of O3-NOx-VOCs indicated that O3 formation was in a transitional regime towards NOx-limited conditions. The results of positive matrix factorization (PMF) demonstrated that refining and petrochemicals (20.8-25.0 %), along with oil and gas evaporation (15.6-16.7 %) were the main sources of VOCs concentrations. Notably, source apportionment based on VOCs-obs underestimated the contributions from sources of reactive components. It is worth highlighting that the sunlight impact & background source was identified as the major contributor to LOH (21.6 %) and OFP (25.3 %), signifying its significant role in O3 formation. This study reiterates the importance of controlling reactive VOC components to mitigate O3 pollution and provides a scientific foundation for air quality management, with emphasis on priority species and controlling sources.
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Affiliation(s)
- Huarui Ren
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zhongyan Xia
- Fengxian District Environmental Monitoring Station, Shanghai 201400, China
| | - Lingbo Yao
- Fengxian District Environmental Monitoring Station, Shanghai 201400, China
| | - Guimei Qin
- Sinopec Shanghai Petrochemical Co., Ltd., Shanghai 200540, China
| | - Yu Zhang
- Tianjin Product Quality Inspection Technology Research Institute, Tianjin 300384, China
| | - Hui Xu
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zhuo Wang
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jinping Cheng
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
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