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Gao Z, Mei EJ, He X, Ebelt S, Rich DQ, Russell AG. Accountability Assessment of Source-Specific Impacts of Regulations on Emissions and Air Quality Using Positive Matrix Factorization. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2025; 59:8651-8661. [PMID: 40272206 PMCID: PMC12060267 DOI: 10.1021/acs.est.4c12511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2024] [Revised: 04/14/2025] [Accepted: 04/15/2025] [Indexed: 04/25/2025]
Abstract
Emission controls targeting electric generating units (EGUs) and mobile sources have been implemented for decades to mitigate PM2.5 concentrations. Impacts of emission controls on source-apportioned PM2.5 concentrations (diesel/gasoline vehicles, biomass burning, secondary nitrate, secondary sulfate, soil/road dust, and residual oil estimated via positive matrix factorization) across three U.S. highly urbanized regions─Atlanta, New York City, and the South Coast Air Basin (SoCAB)─from 2005 to 2019 were evaluated. We considered major controls on EGUs, mobile sources, ports, and heating fuel. Daily counterfactual source-apportioned PM2.5 concentrations without emission controls were estimated based on meteorological indicators and counterfactual emissions using the generalized additive model. Results indicate that emission controls reduced the PM2.5 concentrations by 65-85% across all regions. Secondary sulfate concentrations without EGU controls would be 4.8 times higher, and diesel-vehicle-related PM2.5 would increase 6.8 times without mobile controls in Atlanta. Secondary inorganic aerosols in New York City would increase 5-fold from 1.92 to 10.5 μg/m3, shifting the dominant PM2.5 contributors. Seasonal trends in the counterfactual PM2.5 concentrations were similar to the actual trends, but the peaks in the counterfactual scenario were clearer than those with emission controls.
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Affiliation(s)
- Ziqi Gao
- School of
Civil and Environmental Engineering, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
| | - Eric J. Mei
- School of
Civil and Environmental Engineering, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
| | - Xin He
- School of
Civil and Environmental Engineering, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
| | - Stefanie Ebelt
- Gangarosa
Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, United States
| | - David Q. Rich
- Department
of Public Health Sciences, University of
Rochester School of Medicine and Dentistry, Rochester, New York 14642, United States
| | - Armistead G. Russell
- School of
Civil and Environmental Engineering, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
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2
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Wang Z, Chen X, Wu C, Ju H, Fu Z, Xiong X, Qiu T, Lu Y, He J, Liu Y, Wu H, Cheng C, Li M. Identification and Characterization of Atmospheric Nickel-Containing Particles in Guangzhou After the Implementation of the Clean Fuel Policy. TOXICS 2025; 13:345. [PMID: 40423424 DOI: 10.3390/toxics13050345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2025] [Revised: 04/16/2025] [Accepted: 04/24/2025] [Indexed: 05/28/2025]
Abstract
Nickel, as a toxic trace element in fine particulate matter (PM2.5), has detrimental effects on both air quality and human health. Based on measurements from 2020 to 2021 using a single-particle aerosol mass spectrometer (SPAMS), this study investigates the properties of nickel-containing particles (NCPs) in Guangzhou. The composition, sources, and temporal trends of NCPs were evaluated and the impact of the clean ship fuel policy introduced in 2020 was also examined. The key findings include: (1) Nickel particles account for 0.08% number fraction of PM2.5, which is consistent with previously reported mass fraction in PM2.5. (2) Three distinct types of NCPs were identified, including Ni-fresh, Ni-aged, and Ni-ash. Each type exhibits unique characteristics in size distribution, wind direction dependence, sources, and temporal variations. Ni-fresh particles originate from shipping emissions in the Huangpu Port area 2 km away and are the major contributors to fine nickel particles in the region. (3) Ni-aged and Ni-ash particles, which carry secondary components, tend to be larger (>500 nm) and are representative of regional or background nickel particles. (4) The implementation of the clean ship fuel policy has effectively reduced the number concentrations of NCPs and is beneficial to regional and local air quality.
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Affiliation(s)
- Zaihua Wang
- School of Energy Conservation and Safety, Guangdong Polytechnic of Environmental Protection Engineering, Guangzhou 510655, China
| | - Xuanxiao Chen
- School of Energy Conservation and Safety, Guangdong Polytechnic of Environmental Protection Engineering, Guangzhou 510655, China
| | - Cheng Wu
- College of Environment and Climate, Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for Online Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Hong Ju
- Guangzhou Sub-Branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510006, China
| | - Zhong Fu
- Key Laboratory of Organic Compound Pollution Control Engineering, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Xin Xiong
- Hubei Academy of Eco-Environmental Sciences, Wuhan 430072, China
| | - Ting Qiu
- School of Energy Conservation and Safety, Guangdong Polytechnic of Environmental Protection Engineering, Guangzhou 510655, China
| | - Yuchen Lu
- School of Energy Conservation and Safety, Guangdong Polytechnic of Environmental Protection Engineering, Guangzhou 510655, China
| | - Junjie He
- Guangzhou Sub-Branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510006, China
| | - Yaxi Liu
- Department of Resource and Environment, Moutai Institute, Renhuai 564507, China
- Chishui River Middle Basin, Watershed Ecosystem, Observation and Research Station of Guizhou Province, Renhuai 564501, China
| | - Haining Wu
- Guangzhou Sub-Branch of Guangdong Maritime Safety Administration of the People's Republic of China, Guangzhou 510260, China
| | - Chunlei Cheng
- College of Environment and Climate, Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for Online Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Mei Li
- College of Environment and Climate, Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for Online Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
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Lyu T, Meng X, Tang Y, Zhang Y, Gao Y, Zhang W, Zhou X, Zhang R, Sun Y, Liu S, Guo T, Zhou J, Cao H. Assessment of the gridded burden of disease caused by PM 2.5-bound heavy metals in Beijing based on machine learning algorithm and DALYs. THE SCIENCE OF THE TOTAL ENVIRONMENT 2025; 968:178788. [PMID: 39987820 DOI: 10.1016/j.scitotenv.2025.178788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2024] [Revised: 01/14/2025] [Accepted: 02/06/2025] [Indexed: 02/25/2025]
Affiliation(s)
- Tong Lyu
- Engineering Research Center of Natural Medicine, Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Xin Meng
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Yilin Tang
- Engineering Research Center of Natural Medicine, Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Yidan Zhang
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Yue Gao
- Engineering Research Center of Natural Medicine, Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Wei Zhang
- Engineering Research Center of Natural Medicine, Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Xu Zhou
- Engineering Research Center of Natural Medicine, Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Ruidi Zhang
- Engineering Research Center of Natural Medicine, Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Yue Sun
- Engineering Research Center of Natural Medicine, Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Siqi Liu
- Engineering Research Center of Natural Medicine, Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Tianqing Guo
- Engineering Research Center of Natural Medicine, Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Jianan Zhou
- Institute of Environmental Information, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Hongbin Cao
- Engineering Research Center of Natural Medicine, Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
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Chao CY, Li W, Hopke PK, Guo F, Wang Y, Griffin RJ. Increases in PM 2.5 levels in Houston are associated with a highly recirculating sea breeze. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2025; 366:125381. [PMID: 39581370 DOI: 10.1016/j.envpol.2024.125381] [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: 09/08/2024] [Revised: 11/12/2024] [Accepted: 11/21/2024] [Indexed: 11/26/2024]
Abstract
Local land-sea breezes play an important role in coastal air quality because they circulate air between coastal/urban and marine areas, potentially causing the accumulation of pollutants. This has been observed for the secondary photochemical pollutant ozone. However, particulate matter (PM) also warrants investigation. To understand the complicated interactions between coastal urban air quality and a local land-sea breeze, we analyzed historical monitoring data from Houston, Texas, which is the fourth most populous city in the United States. Using k-means clustering algorithms to analyze wind data from Houston, we successfully identified a sea breeze recirculation cluster. Additionally, we performed positive matrix factorization on PM2.5 (2.5 μm in diameter or smaller) composition data for 2010-2018 from Houston Deer Park #2 monitoring site, 5 km south of the industrialized Houston Ship Channel. The resulting eight factors indicated a variety of anthropogenic, natural, primary and secondary sources. Emphasizing the PM2.5 sources in each of the wind clusters for June, July, and August, we discovered that on southernly wind and sea breeze recirculation days, the PM2.5 concentrations are ∼30% higher than those under other wind patterns. Under southerly wind, 53% of PM2.5 was attributed to long-range transport of soil and 15% to aged and fresh sea salt. In contrast, on days identified as being impacted by a sea breeze, 60% of PM2.5 was attributed to anthropogenic emissions and only 15% to soil sources. Secondary organic aerosol from multiple sources also appeared to be important on sea breeze days.
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Affiliation(s)
- Chun-Ying Chao
- Department of Civil and Environmental Engineering, Rice University, Houston, TX, 77005, USA
| | - Wei Li
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77204, USA; Cooperative Institute for Satellite Earth System Studies, George Mason University, Fairfax, VA, 22030, USA
| | - Philip K Hopke
- Departments of Public Health Sciences and Environmental Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY, 14642, USA
| | - Fangzhou Guo
- Aerodyne Research, Inc., Billerica, MA, 01821, USA
| | - Yuxuan Wang
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77204, USA
| | - Robert J Griffin
- Department of Civil and Environmental Engineering, Rice University, Houston, TX, 77005, USA; School of Engineering, Computing and Construction Management, Roger Williams University, Bristol, RI, 02809, USA.
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5
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Savadkoohi M, Sofowote UM, Querol X, Alastuey A, Pandolfi M, Hopke PK. Source-dependent absorption Ångström exponent in the Los Angeles Basin: Multi-time resolution factor analyses of ambient PM 2.5 and aerosol optical absorption. THE SCIENCE OF THE TOTAL ENVIRONMENT 2025; 958:178095. [PMID: 39708755 DOI: 10.1016/j.scitotenv.2024.178095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2024] [Revised: 11/27/2024] [Accepted: 12/10/2024] [Indexed: 12/23/2024]
Abstract
Advanced receptor models can leverage the information derived from optical and chemical variables as input by a variety of instruments at different time resolutions to extract the source specific absorption Ångström exponent (AAE) from aerosol absorption. The multilinear engine (ME-2), a Positive Matrix Factorization (PMF) solver, serves as a proficient tool for performing such analyses, thereby overcoming the constraints imposed by the assumptions in current optical source apportionment methods such as the Aethalometer approach since the use of a-priori AAE values introduces additional uncertainty into the results of optical methods. Comprehensive PM2.5 chemical speciation datasets, and aerosol absorption coefficients (babs, λ) at seven wavelengths measured by an Aethalometer (AE33), were used in multi-time source apportionment (MT-PMF). The study focused on two locations in the Los Angeles (LA) Basin: Central LA (CELA, Main St.), an urban area surrounded by major freeways, and Rubidoux (RIVR), a residential area surrounded by local roads. Factor profiles and temporal variations of their contributions were obtained. Additionally, factor displacements (DISP) and profile constraints were applied. Five-factor solutions were obtained at both sites. At CELA, the resolved factors included traffic + crustal matter (traffic+ Cr_M), secondary sulfate + nitrate (SSN), biomass burning (BB), diesel emissions (DIE) and aged sea salt (ASS). Moreover, source-dependent AAE values at CELA were obtained without a-priori assumption, with values of 1.46 for traffic+ Cr_M, 1.45 for DIE and 2.37 for BB. At RIVR, the resolved factors were traffic+ Cr_M (AAE = 1.24), particulate sulfate, particulate nitrate, BB (AAE = 3.00) and aged sea salt. PM2.5 composition differed at both locations. SSN accounted for the largest fraction of the ambient PM2.5 mass concentration, their sum at the CELA site averaged 40 % of the PM2.5 mass while the same species represented 77 % at RIVR.
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Affiliation(s)
- Marjan Savadkoohi
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08023, Spain; Department of Mining, Industrial and ICT Engineering (EMIT), Manresa School of Engineering (EPSEM), Universitat Politècnica de Catalunya (UPC), 08242 Manresa, Spain.
| | - Uwayemi M Sofowote
- Environmental Monitoring and Reporting Branch, Ontario Ministry of the Environment, Conservation and Parks, Toronto, Canada.
| | - Xavier Querol
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08023, Spain
| | - Andrés Alastuey
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08023, Spain
| | - Marco Pandolfi
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08023, Spain
| | - Philip K Hopke
- Department of Public Health Sciences, University of Rochester, School of Medicine and Dentistry, Rochester, NY, USA; Institute for a Sustainable Environment, Clarkson University, Potsdam, NY, USA
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Stanimirova I, Rich DQ, Russell AG, Hopke PK. Spatial variability of pollution source contributions during two (2012-2013 and 2018-2019) sampling campaigns at ten sites in Los Angeles basin. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 354:124244. [PMID: 38810681 DOI: 10.1016/j.envpol.2024.124244] [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: 03/19/2024] [Revised: 05/23/2024] [Accepted: 05/26/2024] [Indexed: 05/31/2024]
Abstract
This study assessed the spatial variability of PM2.5 source contributions across ten sites located in the South Coast Air Basin, California. Eight pollution sources and their contributions were obtained using positive matrix factorization (PMF) from the PM2.5 compositional data collected during the two sampling campaigns (2012/13 and 2018/19) of the Multiple Air Toxics Exposure Study (MATES). The identified sources were "gasoline vehicles", "aged sea salt", "biomass burning", "secondary nitrate", "secondary sulfate", "diesel vehicles", "soil/road dust" and "OP-rich". Among them, "gasoline vehicle" was the largest contributor to the PM2.5 mass. The spatial distributions of source contributions to PM2.5 at the sites were characterized by the Pearson correlation coefficients as well as coefficients of determination and divergence. The highest spatial variability was found for the contributions from the "OP-rich" source in both MATES campaigns suggesting varying influences of the wildfires in the Los Angeles Basin. Alternatively, the smallest spatial variabilities were observed for the contributions of the "secondary sulfate" and "aged sea salt" sources resolved for the MATES campaign in 2012/13. The "soil/road dust" contributions of the sites from the 2018/19 campaign were also highly correlated. Compared to the other sites, the source contribution patterns observed for Inland Valley and Rubidoux were the most diverse from the others likely due to their remote locations from the other sites, the major urban area, and the Pacific Ocean.
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Affiliation(s)
- Ivana Stanimirova
- Institute of Chemistry, University of Silesia in Katowice, Katowice, 40-006, Poland; Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA.
| | - David Q Rich
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA
| | - Armistead G Russell
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Philip K Hopke
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA; Institute for Sustainable Environment, Clarkson University, Potsdam, NY, 13699, USA
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Ducruet C, Polo Martin B, Sene MA, Lo Prete M, Sun L, Itoh H, Pigné Y. Ports and their influence on local air pollution and public health: A global analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 915:170099. [PMID: 38224889 DOI: 10.1016/j.scitotenv.2024.170099] [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: 09/19/2023] [Revised: 01/04/2024] [Accepted: 01/09/2024] [Indexed: 01/17/2024]
Abstract
Despite the skyrocketing growth in recent decades of environmental studies on ports and shipping, their local health impacts remain largely under-researched. This article tackles this gap in research by statistically analyzing data on global shipping flows across nearly 5000 ports in 35 OECD countries between 2001 and 2018. The different traffic types, from containers to bulk and passengers, are analyzed jointly with data on natural conditions, air pollution, socio-economic indicators, and public health. The principal results show that port regions pollute more than non-port regions on average, while health impacts vary according to the size and specialization of the port region. Three types of port regions are clearly differentiated: industrial, intermediate, and metropolitan port regions.
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Affiliation(s)
- César Ducruet
- French National Centre for Scientific Research, UMR 7235 EconomiX, University of Paris-Nanterre, France.
| | - Bárbara Polo Martin
- French National Centre for Scientific Research, UMR 7235 EconomiX, University of Paris-Nanterre, France
| | - Mame Astou Sene
- French National Centre for Scientific Research, UMR 7235 EconomiX, University of Paris-Nanterre, France
| | - Mariantonia Lo Prete
- Laboratory Territoires, Villes, Environnement et Société (TVES ULR 4477), Université du Littoral Côte d'Opale (ULCO), France
| | - Ling Sun
- Fudan University & Shanghai Maritime University, China
| | | | - Yoann Pigné
- LITIS, University of Le Havre Normandie, France
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Alfeus A, Molnar P, Boman J, Hopke PK, Wichmann J. PM2.5 in Cape Town, South Africa: Chemical characterization and source apportionment using dispersion-normalised positive matrix factorization. ATMOSPHERIC POLLUTION RESEARCH 2024; 15:102025. [DOI: 10.1016/j.apr.2023.102025] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2025]
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Stanimirova I, Rich DQ, Russell AG, Hopke PK. Common and distinct pollution sources identified from ambient PM 2.5 concentrations in two sites of Los Angeles Basin from 2005 to 2019. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 340:122817. [PMID: 37913979 DOI: 10.1016/j.envpol.2023.122817] [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: 10/01/2023] [Revised: 10/23/2023] [Accepted: 10/26/2023] [Indexed: 11/03/2023]
Abstract
The effects of air quality control policies implemented in California from 2005 to 2019 targeting sources contributing to ambient PM2.5 concentrations, were assessed at two sampling sites in the Los Angeles Basin (N. Main Street and Rubidoux). The spatial and temporal variations of pollution source contributions obtained from dispersion-normalized positive matrix factorization, (DN-PMF) were interpreted with respect to site specific locations. Secondary nitrate and secondary sulfate were the major contributors to the ambient PM2.5 mass concentrations at both sites with substantial concentration decreases after 2008 that were likely due to the implementation of California specific programs including stricter NOx emissions control on motor vehicles. Biomass burning emissions also decreased over the study period at both sampling sites except for one event in December 2005 when strong winter storms and multiple floods led to unusually low atmospheric temperatures and likely increased residential wood burning. The large number of wildfires, trans-Pacific transport of mineral dust and regional dust transported by strong Santa Ana winds and agriculturally generated dust in Rubidoux contributed to poor air quality. Severe storms and devastating wildfires were also linked to the elevated pyrolyzed organic carbon (OP-rich) concentrations. The two distinct region-specific sources, describing fuel combustion in LA, were "residual oil" and "traffic", while separate "gasoline" and "diesel" vehicles sources were identified in Rubidoux. California emissions standards program which required replacement of conventional cars with electric or hybrid vehicles and standards for gasoline and diesel fuels, led to lower "traffic" contributions. Gasoline vehicle emissions after 2017 in Rubidoux also decreased. "Diesel" concentrations declined between 2007 and 2011 because of the recession from late 2007 to early 2009 and the Federal Heavy-Duty Diesel Rule.
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Affiliation(s)
- I Stanimirova
- Institute of Chemistry, University of Silesia in Katowice, Katowice, 40-006, Poland; Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA.
| | - David Q Rich
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA
| | - Armistead G Russell
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - P K Hopke
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA; Institute for Sustainable Environment, Clarkson University, Potsdam, NY, 13699, USA
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