1
|
Yao PT, Peng X, Cao LM, Zeng LW, Feng N, He LY, Huang XF. Evaluation of a new real-time source apportionment system of PM 2.5 and its implication on rapid aging of vehicle exhaust. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 937:173449. [PMID: 38797425 DOI: 10.1016/j.scitotenv.2024.173449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Revised: 05/07/2024] [Accepted: 05/20/2024] [Indexed: 05/29/2024]
Abstract
Accurate identification and rapid analysis of PM2.5 sources and formation mechanisms are essential to mitigate PM2.5 pollution. However, studies were limited in developing a method to apportion sources to the total PM2.5 mass in real-time. In this study, we developed a real-time source apportionment method based on chemical mass balance (CMB) modeling and a mass-closure PM2.5 composition online monitoring system in Shenzhen, China. Results showed that secondary sulfate, secondary organic aerosol (SOA), vehicle emissions and secondary nitrate were the four major PM2.5 sources during autumn 2019 in Shenzhen, together contributed 76 % of PM2.5 mass. The novel method was verified by comparing with other source apportionment methods, including offline filter analysis, aerosol mass spectrometry, and carbon isotopic analysis. The comparison of these methods showed that the new real-time method obtained results generally consistent with the others, and the differences were interpretable and implicative. SOA and vehicle emissions were the major PM2.5 and OA contributors by all methods. Further investigation on the OA sources indicated that vehicle emissions were not only the main source of primary organic aerosol (POA), but also the main contributor to SOA by rapid aging of the exhaust in the atmosphere. Our results demonstrated the great potential of the new real-time source apportionment method for aerosol pollution control and deep understandings on emission sources.
Collapse
Affiliation(s)
- Pei-Ting Yao
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Xing Peng
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China.
| | - Li-Ming Cao
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Li-Wu Zeng
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Ning Feng
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Ling-Yan He
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Xiao-Feng Huang
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China.
| |
Collapse
|
2
|
Huo Y, Yao D, Guo H. Differences in aerosol chemistry at a regional background site in Hong Kong before and during the COVID-19 pandemic. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:171990. [PMID: 38537818 DOI: 10.1016/j.scitotenv.2024.171990] [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: 01/15/2024] [Revised: 03/23/2024] [Accepted: 03/24/2024] [Indexed: 04/04/2024]
Abstract
Restrictions on human-related activities implemented in Hong Kong to curb the spread of the coronavirus disease 2019 (COVID-19) pandemic provided an opportunity to investigate the anthropogenic impact on organic aerosols (OA) composition. In this study, we conducted a comparative analysis of online measurements of non-refractory submicron particulate matters (NR-PM1) at a regional background site in Hong Kong, covering the periods before the COVID-19 control (November 2018) and during the COVID-19 control (October to November 2020), to investigate changes in OA sources and formation mechanisms. Among the measured NR-PM1 components, organics were the most dominant species with an average percentage of 51.0 ± 0.5 %, exceeding pre-control levels of 44.0 ± 0.7 %. Moreover, 88 % of the organics were attributed to oxygenated OA (OOA). Diurnal variations of all bulk components in NR-PM1 consistently showed afternoon peaks, indicating photochemical processes during COVID-19 control. Similar to the pre-restriction period, the positive matrix factorization (PMF) model showed that OOA was composed of three factors, including two less-oxidized oxygenated factors (LO-OOA1 and LO-OOA2) and one more-oxidized oxygenated factor (MO-OOA). The contribution of the LO-OOA2 factor remained small and stable during both sampling campaigns, which might imply background levels of OOA at this site. The formation of the two predominant components of organics (e.g., LO-OOA1 and MO-OOA) was further discussed. Compared with before control, observational evidence showed that the levels of MO-OOA exceeded LO-OOA1 during the control period, and the average concentration of odd oxygen (Ox = ozone + nitrogen dioxide) increased by 53 % during the COVID-19 control. Besides, the results showed that both LO-OOA1 and MO-OOA exhibited similar diurnal variations to Ox, and their concentrations generally enhanced with increasing Ox levels. This suggested that the formation of OOA was closely related to the photochemical oxidation processes when anthropogenic emissions were reduced. By correlating LO-OOA1 and MO-OOA with speciated OA markers, we found that the formation of LO-OOA1 remained associated with anthropogenic sources, while biogenic emissions contributed to the formation of MO-OOA during the COVID-19 control. Our findings highlight the interplay between emissions, atmospheric conditions, and aerosol composition, providing valuable insights to guide strategic decisions for future air quality improvement.
Collapse
Affiliation(s)
- Yunxi Huo
- Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Dawen Yao
- School of Intelligent Systems Engineering, Sun Yat-Sen University, Shenzhen 518107, China
| | - Hai Guo
- Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
| |
Collapse
|
3
|
Bhattu D, Tripathi SN, Bhowmik HS, Moschos V, Lee CP, Rauber M, Salazar G, Abbaszade G, Cui T, Slowik JG, Vats P, Mishra S, Lalchandani V, Satish R, Rai P, Casotto R, Tobler A, Kumar V, Hao Y, Qi L, Khare P, Manousakas MI, Wang Q, Han Y, Tian J, Darfeuil S, Minguillon MC, Hueglin C, Conil S, Rastogi N, Srivastava AK, Ganguly D, Bjelic S, Canonaco F, Schnelle-Kreis J, Dominutti PA, Jaffrezo JL, Szidat S, Chen Y, Cao J, Baltensperger U, Uzu G, Daellenbach KR, El Haddad I, Prévôt ASH. Local incomplete combustion emissions define the PM 2.5 oxidative potential in Northern India. Nat Commun 2024; 15:3517. [PMID: 38664406 PMCID: PMC11045729 DOI: 10.1038/s41467-024-47785-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Accepted: 04/10/2024] [Indexed: 04/28/2024] Open
Abstract
The oxidative potential (OP) of particulate matter (PM) is a major driver of PM-associated health effects. In India, the emission sources defining PM-OP, and their local/regional nature, are yet to be established. Here, to address this gap we determine the geographical origin, sources of PM, and its OP at five Indo-Gangetic Plain sites inside and outside Delhi. Our findings reveal that although uniformly high PM concentrations are recorded across the entire region, local emission sources and formation processes dominate PM pollution. Specifically, ammonium chloride, and organic aerosols (OA) from traffic exhaust, residential heating, and oxidation of unsaturated vapors from fossil fuels are the dominant PM sources inside Delhi. Ammonium sulfate and nitrate, and secondary OA from biomass burning vapors, are produced outside Delhi. Nevertheless, PM-OP is overwhelmingly driven by OA from incomplete combustion of biomass and fossil fuels, including traffic. These findings suggest that addressing local inefficient combustion processes can effectively mitigate PM health exposure in northern India.
Collapse
Affiliation(s)
- Deepika Bhattu
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland.
- Department of Civil and Infrastructure Engineering, Indian Institute of Technology Jodhpur, Rajasthan, India.
| | - Sachchida Nand Tripathi
- Department of Civil Engineering & Department of Sustainable Energy Engineering, Indian Institute of Technology Kanpur, Uttar Pradesh, India.
- Department of Sustainable Energy Engineering, Indian Institute of Technology Kanpur, Uttar Pradesh, India.
| | - Himadri Sekhar Bhowmik
- Department of Civil Engineering & Department of Sustainable Energy Engineering, Indian Institute of Technology Kanpur, Uttar Pradesh, India
| | - Vaios Moschos
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Chuan Ping Lee
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Martin Rauber
- Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern, Switzerland
- Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
| | - Gary Salazar
- Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern, Switzerland
- Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
| | - Gülcin Abbaszade
- Comprehensive Molecular Analytics (CMA), Department Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany
| | - Tianqu Cui
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Jay G Slowik
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Pawan Vats
- Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India
| | - Suneeti Mishra
- Department of Civil Engineering & Department of Sustainable Energy Engineering, Indian Institute of Technology Kanpur, Uttar Pradesh, India
| | - Vipul Lalchandani
- Department of Civil Engineering & Department of Sustainable Energy Engineering, Indian Institute of Technology Kanpur, Uttar Pradesh, India
| | - Rangu Satish
- Geosciences Division, Physical Research Laboratory, Ahmedabad, India
- College of Engineering, Science, Technology and Agriculture, Central State University, Wilberforce, Ohio, USA
| | - Pragati Rai
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Roberto Casotto
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Anna Tobler
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
- Datalystica Ltd., Park innovAARE, Villigen, Switzerland
| | - Varun Kumar
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
- Department of Environmental science, Aarhus University, Roskilde, Denmark
| | - Yufang Hao
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Lu Qi
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Peeyush Khare
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
| | | | - Qiyuan Wang
- Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
| | - Yuemei Han
- Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
| | - Jie Tian
- Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
| | - Sophie Darfeuil
- University Grenoble Alpes, IRD, CNRS, INRAE, Grenoble INP*, IGE (Institute of Environmental Geosciences), Grenoble, France
| | - Mari Cruz Minguillon
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Christoph Hueglin
- Laboratory for Air Pollution and Environmental Technology, Swiss Federal Laboratories for Materials Science and Technology (Empa), Duebendorf, Switzerland
| | - Sébastien Conil
- ANDRA DRD/GES Observatoire Pérenne de l'Environnement, Bure, France
| | - Neeraj Rastogi
- Geosciences Division, Physical Research Laboratory, Ahmedabad, India
| | - Atul Kumar Srivastava
- Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, New Delhi, India
| | - Dilip Ganguly
- Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India
| | - Sasa Bjelic
- Biogenergy and Catalysis Laboratory, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Francesco Canonaco
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
- Datalystica Ltd., Park innovAARE, Villigen, Switzerland
| | - Jürgen Schnelle-Kreis
- Comprehensive Molecular Analytics (CMA), Department Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany
| | - Pamela A Dominutti
- University Grenoble Alpes, IRD, CNRS, INRAE, Grenoble INP*, IGE (Institute of Environmental Geosciences), Grenoble, France
| | - Jean-Luc Jaffrezo
- University Grenoble Alpes, IRD, CNRS, INRAE, Grenoble INP*, IGE (Institute of Environmental Geosciences), Grenoble, France
| | - Sönke Szidat
- Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern, Switzerland
- Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
| | - Yang Chen
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, 400714, Chongqing, China
| | - Junji Cao
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Urs Baltensperger
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Gaëlle Uzu
- University Grenoble Alpes, IRD, CNRS, INRAE, Grenoble INP*, IGE (Institute of Environmental Geosciences), Grenoble, France
| | - Kaspar R Daellenbach
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Imad El Haddad
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland.
| | - André S H Prévôt
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen PSI, Switzerland.
| |
Collapse
|
4
|
Qu Q, Wang S, Zhao B, Hu R, Liang C, Zhang H, Li S, Feng B, Hou X, Yin D, Du J, Chu Y, Zhang Y, Wu Q, Wen Y, Wu X, Hu J, Zhang S, Hao J. Response of organic aerosol in Beijing to emission reductions during the XXIV Olympic Winter Games. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 914:170033. [PMID: 38220000 DOI: 10.1016/j.scitotenv.2024.170033] [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: 01/05/2024] [Accepted: 01/07/2024] [Indexed: 01/16/2024]
Abstract
Organic aerosol (OA) serves as a crucial component of fine particulate matter. However, the response of OA to changes in anthropogenic emissions remains unclear due to its complexity. The XXIV Olympic Winter Games (OWG) provided real atmospheric experimental conditions on studying the response of OA to substantial emission reductions in winter. Here, we explored the sources and variations of OA based on the observation of aerosol mass spectrometer (AMS) combined with positive matrix factorization (PMF) analysis in urban Beijing during the 2022 Olympic Winter Games. The influences of meteorological conditions on OA concentrations were corrected by CO and verified by deweathered model. The CO-normalized primary OA (POA) concentrations from traffic, cooking, coal and biomass burning during the OWG decreased by 39.8 %, 23.2 % and 65.0 %, respectively. Measures controlling coal and biomass burning were most effective in reducing POA during the OWG. For the CO-normalized concentration of secondary OA (SOA), aqueous-phase related oxygenated OA decreased by 51.8 % due to the lower relative humidity and emission reduction in precursors, while the less oxidized‑oxygenated OA even slightly increased as the enhanced atmospheric oxidation processes may partially offset the efficacy of emission control. Therefore, more targeted reduction of organic precursors shall be enhanced to lower atmospheric oxidation capacity and mitigate SOA pollution.
Collapse
Affiliation(s)
- Qipeng Qu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China.
| | - Bin Zhao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Ruolan Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Chengrui Liang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Haowen Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shengyue Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Boyang Feng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Xuan Hou
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Dejia Yin
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jinhong Du
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yangxi Chu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yanning Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Qingru Wu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Yifan Wen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Xiaomeng Wu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jingnan Hu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Shaojun Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jiming Hao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| |
Collapse
|
5
|
Stavroulas I, Bougiatioti A, Grivas G, Liakakou E, Petrinoli K, Kourtidis K, Gerasopoulos E, Mihalopoulos N. Cooking as an organic aerosol source leading to urban air quality degradation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:168031. [PMID: 37890627 DOI: 10.1016/j.scitotenv.2023.168031] [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: 05/31/2023] [Revised: 09/20/2023] [Accepted: 10/20/2023] [Indexed: 10/29/2023]
Abstract
Air quality degradation events in the urban environment are often attributed to anthropogenic aerosol sources related to combustion of liquid or solid fuels in various activities. The effects of massive cooking emissions during Greek nationwide traditional festivities were investigated by a combined characterization of particulate matter (PM) levels and organic aerosol (OA) sources. Focus was centered on periods around two major festivities, namely "Fat Thursday" and Easter Sunday along six different years. OA sources were apportioned through Positive Matrix Factorization (PMF) on Aerosol Chemical Speciation Monitor (ACSM) mass spectra, while the spatial characteristics of the episodes were assessed through a low-cost, sensor-based PM2.5 monitoring network operating in Athens and other Greek cities. Contrasts were examined by considering a 15-day period around each event, while the effect of the 2020-2021 mobility restrictions, related to COVID-19, was also assessed. An episode-specific cooking organic aerosol (COA) spectral profile was delineated, and can be considered as a reference for ambient COA from meat grilling. Severe pollution episodes that affected the entire Athens basin were recorded, with PM2.5 concentrations exceeding 300 μg m-3 on occasions. COA contributions dominated primary organic aerosol (POA) and made up almost half of OA concentrations. During "Fat Thursday" COA concentrations and contributions peaked during night-time (23.2 μg m-3 and 46 %, respectively) while for Easter Sunday COA maxima were recorded in the early afternoon (27.4 μg m-3 and 39 %). Analyzing a full-year OA source dataset, revealed a pronounced recreational cooking pattern in central Athens, with COA concentrations rising towards the weekend, reflecting the impact of the food service sector. In view of the upcoming review of the EU air quality directive, foreseeing stricter annual PM2.5 limits as well as 24-h limit values and related alerts, the mitigation of cooking emissions appears as a potent instrument for achieving tangible air quality benefits.
Collapse
Affiliation(s)
- I Stavroulas
- Institute for Environmental Research and Sustainable Development, National Observatory of Athens, 15236 Palea Penteli, Greece; Climate and Atmosphere Research Center, The Cyprus Institute, 2121 Nicosia, Cyprus; Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, 71003 Heraklion, Greece.
| | - A Bougiatioti
- Institute for Environmental Research and Sustainable Development, National Observatory of Athens, 15236 Palea Penteli, Greece.
| | - G Grivas
- Institute for Environmental Research and Sustainable Development, National Observatory of Athens, 15236 Palea Penteli, Greece
| | - E Liakakou
- Institute for Environmental Research and Sustainable Development, National Observatory of Athens, 15236 Palea Penteli, Greece
| | - K Petrinoli
- Institute for Environmental Research and Sustainable Development, National Observatory of Athens, 15236 Palea Penteli, Greece
| | - K Kourtidis
- Department of Environmental Engineering, Democritus University of Thrace, 67100 Xanthi, Greece
| | - E Gerasopoulos
- Institute for Environmental Research and Sustainable Development, National Observatory of Athens, 15236 Palea Penteli, Greece
| | - N Mihalopoulos
- Institute for Environmental Research and Sustainable Development, National Observatory of Athens, 15236 Palea Penteli, Greece; Climate and Atmosphere Research Center, The Cyprus Institute, 2121 Nicosia, Cyprus; Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, 71003 Heraklion, Greece
| |
Collapse
|
6
|
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.
Collapse
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
| |
Collapse
|
7
|
Zheng H, Chang X, Wang S, Li S, Zhao B, Dong Z, Ding D, Jiang Y, Huang G, Huang C, An J, Zhou M, Qiao L, Xing J. Sources of Organic Aerosol in China from 2005 to 2019: A Modeling Analysis. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:5957-5966. [PMID: 36994990 DOI: 10.1021/acs.est.2c08315] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Organic aerosol (OA) is a key component of fine particulate matter (PM2.5) and affects the human health and leads to climate change. With strict control measures for air pollutants during the last decade, the OA concentration in China declined slowly, while its sources remain unclear. In this study, we simulate the primary OA (POA) and secondary OA (SOA) concentrations from 2005 to 2019 with a state-of-the-art air quality model, Community Multiscale Air Quality (CMAQ, version 5.3.2) coupled with a Two-Dimensional Volatility Basis Set (2D-VBS) module, and a long-term emission inventory of full-volatility organic compounds in China and conduct source apportionment and sensitivity analysis. The simulation results show that, from 2005 to 2019, the OA concentration in China decreased from 24.0 to 12.8 μg/m3 with most of the reduction from POA. The OA pollution from residential biomass burning declined 75% from 2005 to 2019, while it is still the major OA source in China. OA pollution from VCP increased by more than 2-fold and became the largest SOA source in China. From 2014 to 2019, the NOx control in China slightly offset the decrease of SOA concentration due to elevated oxidation capacity.
Collapse
Affiliation(s)
- Haotian Zheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of the Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Xing Chang
- Transport Planning and Research Institute, Ministry of Transport, Laboratory of Transport Pollution Control and Monitoring Technology, Beijing 100028, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shengyue Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Bin Zhao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Zhaoxin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Dian Ding
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Yueqi Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Guanghan Huang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of the Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Jingyu An
- State Environmental Protection Key Laboratory of the Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Min Zhou
- State Environmental Protection Key Laboratory of the Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Liping Qiao
- State Environmental Protection Key Laboratory of the Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| |
Collapse
|
8
|
Liang C, Wang S, Hu R, Huang G, Xie J, Zhao B, Li Y, Zhu W, Guo S, Jiang J, Hao J. Molecular tracers, mass spectral tracers and oxidation of organic aerosols emitted from cooking and fossil fuel burning sources. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 868:161635. [PMID: 36657674 DOI: 10.1016/j.scitotenv.2023.161635] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 01/11/2023] [Accepted: 01/12/2023] [Indexed: 06/17/2023]
Abstract
Secondary organic aerosol (SOA) composes a substantial fraction of atmospheric particles, yet the formation and aging mechanism of SOA remains unclear. Here we investigate the initial oxidation of primary organic aerosol (POA) and further aging of SOA in winter Beijing by using aerosol mass spectrometer (AMS) measurements along with offline molecular tracer analysis. Multilinear engine (ME-2) source apportionment was conducted to capture the characteristic of source-related SOA, and connect them with specific POA. Our results show that urban cooking and fossil fuel burning sources contribute significantly (17 % and 20 %) to total organic aerosol (OA) in winter Beijing. Molecular tracer analysis by two-dimensional gas chromatography-time-of-flight mass spectrometer (GC × GC-ToF-MS) reveals that cooking SOA (CSOA) is produced through both photooxidation and aqueous-phase processing, while less oxidized SOA (LO-SOA) is the photooxidation product of fossil fuel burning OA (FFOA) and may experience aqueous-phase aging to form more-oxidized oxygenated OA (MO-OOA). Furthermore, CHOm/z 69 and CHOm/z 85 are mass spectral tracers indicating the initial photooxidation, while CHO2+ and C2H2O2+ imply further aqueous-phase aging of OA. Tracer analysis indicates that the formation of diketones is involved in the initial photooxidation of POA, while the formation of glyoxal and diacids is involved in the further aqueous-phase aging of SOA.
Collapse
Affiliation(s)
- Chengrui Liang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China.
| | - Ruolan Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Guanghan Huang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jinzi Xie
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Bin Zhao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Yuyang Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Wenfei Zhu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Song Guo
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Jingkun Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jiming Hao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| |
Collapse
|
9
|
Zhang Z, Zhu W, Hu M, Wang H, Tang L, Hu S, Shen R, Yu Y, Song K, Tan R, Chen Z, Chen S, Canonaco F, Prévôt ASH, Guo S. Secondary organic aerosol formation in China from urban-lifestyle sources: Vehicle exhaust and cooking emission. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159340. [PMID: 36228803 DOI: 10.1016/j.scitotenv.2022.159340] [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: 08/22/2022] [Revised: 10/05/2022] [Accepted: 10/06/2022] [Indexed: 06/16/2023]
Abstract
An increasing number of people tend to live in cities, where they suffer from serious air pollution from anthropogenic sources. Vehicle exhaust and cooking emission are closely related to daily life of urban residents, and could be defined as "urban-lifestyle sources". The primary emissions of urban-lifestyle sources tend to form abundant secondary organic aerosols (SOA) through complicated atmospheric chemistry processes. The newly formed SOA is a kind of complex mixture and causes considerable health effects with high uncertainty. Most studies focus on formation pathway, mass growth potential and chemical feature of urban-lifestyle SOA under simple laboratory conditions. Few studies have measured the urban-lifestyle SOA in ambient air, let alone verified laboratory findings under complicated atmospheric conditions. In this work, we established a new method that combined laboratory simulation and field observation, which quantified the urban-lifestyle SOA with high time resolution under the real atmospheric condition. The complex SOA was measured and resolved by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). The multilinear engine model (ME-2) and multilinear correction methods were used to apply laboratory results into ambient SOA apportionment. It was found that the vehicle source dominated the SOA formation during the diurnal photochemical process, and the SOA:POA ratio of vehicle source was about 1.4 times larger than that of cooking source. The vehicle emission may undergo an alcohol/peroxide & carboxylic acid oxidation pathway and form higher oxidized SOA, while the cooking emission may undergo an alcohol/peroxide oxidation pathway and form relatively lower oxidized SOA. The vehicle SOA and cooking SOA contributed 45.6 % and 24.8 % of OA during a local episode in 2021 winter of downtown Beijing. Our findings could not only provide a new way to quantify urban SOA but also demonstrate some laboratory hypotheses, conducing to understand its ambient contributions, chemical features, and environmental effects.
Collapse
Affiliation(s)
- Zirui Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Wenfei Zhu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Min Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
| | - Hui Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Lizi Tang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Shuya Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Ruizhe Shen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Ying Yu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Kai Song
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Rui Tan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Zheng Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Shiyi Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Francesco Canonaco
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), Villigen 5232, Switzerland; Datalystica Ltd., Park innovAARE, 5234 Villigen, Switzerland
| | - Andre S H Prévôt
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), Villigen 5232, Switzerland
| | - Song Guo
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| |
Collapse
|
10
|
Zeng L, Huang DD, Zhu S, Li F, Zhou M, Qiao L, Wang Q, Wang Q, Ma Y, Lou S, Shi H, In Hoi K, Mok KM, Ge X, Wang H, Yu JZ, Huang C, Li YJ. The interplays among meteorology, source, and chemistry in high particulate matter pollution episodes in urban Shanghai, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 853:158347. [PMID: 36041601 DOI: 10.1016/j.scitotenv.2022.158347] [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: 06/15/2022] [Revised: 08/09/2022] [Accepted: 08/24/2022] [Indexed: 06/15/2023]
Abstract
High particulate matter (PM) pollution episodes still occur occasionally in urban China, despite of improvements in recent years. Investigating the influencing factors of high-PM episodes is beneficial in the formulation of effective control measures. We herein present the effects of weather condition, emission source, and chemical conversion on the occurrence of high-PM episodes in urban Shanghai using multiple online measurements. Three high-PM episodes, i.e., locally-accumulated, regionally-transported, and dust-affected ones, as well as a clean period were selected. Stagnant air with temperature inversion was found in both locally-accumulated and regionally-transported high-PM episodes, but differences in PM evolution were observed. In the more complicated dust-affected episode, the weather condition interacted with the emission/transport sources and chemical conversion, resulting in consecutive stages with different PM characteristics. Specifically, there were (1) stronger local accumulation in the pre-dust period, (2) dust-laden air with aged organic aerosol (OA) upon dust arrival, (3) pollutants being swept into the ocean, and (4) back to the city with aged OA. Our results suggest that (a) local emissions could be rapidly oxidized in some episodes but not all, (b) aged OA from long-range transport (aged in space) had a similar degree of oxygenation compared to the prolonged local oxidation (aged in time), and (c) OA aged over land and over the ocean were similar in chemical characteristics. The findings help better understand the causes and evolution of high-PM episodes, which are manifested by the interplays among meteorology, source, and chemistry, providing a scientific basis for control measures.
Collapse
Affiliation(s)
- Lulu Zeng
- Department of Civil and Environmental Engineering, Centre for Regional Oceans, Faculty of Science and Technology, University of Macau, Taipa, Macau 999078, China; State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Dan Dan Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China.
| | - Shuhui Zhu
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China; Division of Environment and Sustainability, Hong Kong University of Science and Technology, Hong Kong, China
| | - Fangbing Li
- Department of Civil and Environmental Engineering, Centre for Regional Oceans, Faculty of Science and Technology, University of Macau, Taipa, Macau 999078, China
| | - Min Zhou
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Liping Qiao
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Qian Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Qiongqiong Wang
- Department of Chemistry, Hong Kong University of Science and Technology, Hong Kong, China
| | - Yingge Ma
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Shengrong Lou
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Huabin Shi
- Department of Civil and Environmental Engineering, Centre for Regional Oceans, Faculty of Science and Technology, University of Macau, Taipa, Macau 999078, China; The State Key Laboratory of Internet of Things for Smart City, University of Macau, Taipa, Macau, China
| | - Ka In Hoi
- Department of Civil and Environmental Engineering, Centre for Regional Oceans, Faculty of Science and Technology, University of Macau, Taipa, Macau 999078, China
| | - Kai Meng Mok
- Department of Civil and Environmental Engineering, Centre for Regional Oceans, Faculty of Science and Technology, University of Macau, Taipa, Macau 999078, China
| | - Xinlei Ge
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Jian Zhen Yu
- Division of Environment and Sustainability, Hong Kong University of Science and Technology, Hong Kong, China; Department of Chemistry, Hong Kong University of Science and Technology, Hong Kong, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Yong Jie Li
- Department of Civil and Environmental Engineering, Centre for Regional Oceans, Faculty of Science and Technology, University of Macau, Taipa, Macau 999078, China.
| |
Collapse
|
11
|
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.
Collapse
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
| |
Collapse
|