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Diao L, Xu Z, Song D, Zhu C, Li X, Zhou X, Jing X, Yu L, Liu B. Dry deposition fluxes and inhalation risks of toxic elements in total suspended particles in the Bohai Rim region: Long-term trends and potential sources. JOURNAL OF HAZARDOUS MATERIALS 2024; 474:134692. [PMID: 38810575 DOI: 10.1016/j.jhazmat.2024.134692] [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: 02/22/2024] [Revised: 04/23/2024] [Accepted: 05/20/2024] [Indexed: 05/31/2024]
Abstract
Long-term changes in dry deposition fluxes (DDF) and health risks for toxic elements (TE) in total suspended particles (TSP) in the Bohai Rim region are important for assessing control effects of pollution sources. Thus, we investigated the trends in DDF and concentrations for TSP and TE and health risks of TE in eight cities in the region from 2011-2020. TSP concentration and DDF showed general downward trends. Compared to the before Clear Air Action Plan (BCAAP, 2011-2012) period, concentration and DDF of TE over the Clear Air Action Plan (CAAP, 2013-2017) period substantially decreased, with the highest decrease rates in Zn, Cd, and Cr. During the study period, non-carcinogenic (HI) and total carcinogenic (TCR) risks for children and adults were 0.09 and 0.04, and 1.54 × 10-5 and 2.65 × 10-5, respectively, with Cr6+ and As being dominant contributors. Compared to the BCAAP period, HI and TCR over the CAAP period decreased by 36.8 % and 32.4 %, respectively. However, their risks increased over the Blue Sky Protection Campaign (BSPC, 2018-2020) period. Potential source contribution function suggested substantial changes in potential risk areas over different control periods, with the BSPC primarily being on land and the Yellow Sea.
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Affiliation(s)
- Liuli Diao
- National Marine Environmental Monitoring Center, Dalian 116023, China
| | - Zizhou Xu
- National Marine Environmental Monitoring Center, Dalian 116023, China
| | - Derui Song
- National Marine Environmental Monitoring Center, Dalian 116023, China.
| | - Cheng Zhu
- National Marine Environmental Monitoring Center, Dalian 116023, China
| | - Xuchun Li
- National Marine Environmental Monitoring Center, Dalian 116023, China
| | - Xiaoyu Zhou
- National Marine Environmental Monitoring Center, Dalian 116023, China
| | - Xindi Jing
- National Marine Environmental Monitoring Center, Dalian 116023, China
| | - Limin Yu
- National Marine Environmental Monitoring Center, Dalian 116023, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
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2
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Gao X, Li W, Sun X, Hao Y, Sun M, Yang Y, Wu G, Zhou Y. The important role of nitrate in iron and manganese dissolution and sulfate formation in fine particles at a coastal site in Northern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 921:170318. [PMID: 38280608 DOI: 10.1016/j.scitotenv.2024.170318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 01/17/2024] [Accepted: 01/18/2024] [Indexed: 01/29/2024]
Abstract
Bioavailable transition trace elements, such as soluble iron (Fes) and soluble manganese (Mns) in aerosols, play a crucial role in atmospheric sulfate formation and marine ecosystems. In this study conducted during the spring of 2017 in Qingdao, a coastal city in Northern China, we applied a combined approach of multiple linear regression (MLR) incorporating the results of positive matrix factorization (PMF) to estimate the solubility of Fe and Mn from various sources. PMF analysis showed that dust was the largest contributor to total Fe (FeT) (45.5 %), followed by non-ferrous smelting (20.3 %) and secondary formation processes (17.8 %). However, secondary formation processes (33.2 %), vehicle exhaust (19.3 %) and aqueous-phase processes (19.0 %) were found to be the primary contributors to Fes. For total Mn (MnT) and Mns, dust (21.2 % ∼ 35.0 %), secondary formation processes (20.3 % ∼ 25.6 %) and industry (12.6 % ∼ 16.3 %) were identified as the dominant contributors. The solubilities of Fe and Mn varied significantly depending on their sources. Interestingly, nitrate played a more pronounced role than sulfate in facilitating the dissolution of Fe and Mn during the acid processing due to the high molar ratio of NO3-/2SO42- (1.72 ± 0.54) under the average RH of 56 % ± 15 %. This phenomenon suggested that the acid processing was primarily triggered by nitrate formation due to the low deliquescence relative humidity (DRH) of nitrate. Additionally, we discovered that the catalytic oxidation of SO2 in aerosol water was primarily driven by Fe rather than Mn, serving as a more significant pathway for sulfate formation within a pH range of 2.0 to 4.4. These findings provide valuable insights into the impact of acidification on the dissolution of Fe and Mn under conditions of moderate RH in the real ambient atmosphere with the increasing of NO3-/2SO42- molar ratio.
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Affiliation(s)
- Xiaomei Gao
- School of Water Conservancy and Environment, University of Jinan, Jinan, Shandong, China
| | - Wenshuai Li
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Xiaoyan Sun
- Jinan Ecological and Environmental Monitoring Center, Jinan, Shandong, China
| | - Yu Hao
- North China Sea Data and Information Service, State Oceanic Administration, Qingdao, Shandong, China.
| | - Mingge Sun
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Yiyan Yang
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Guanru Wu
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Yang Zhou
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China.
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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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Bui LT, Lai HTN, Nguyen PH. Benefits of Short-term Premature Mortality Reduction Attributed to PM 2.5 Pollution: A Case Study in Long an Province, Vietnam. ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2023; 85:245-262. [PMID: 37468649 DOI: 10.1007/s00244-023-01012-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 06/28/2023] [Indexed: 07/21/2023]
Abstract
PM2.5 pollution exposure is the leading cause of disease burden globally, especially in low- and middle-income countries, including Vietnam. Therefore, economic damage in this context must be quantified. Long An province in the Southern Key Economic (SKE) region was selected as a research area. This study aimed to evaluate PM2.5-related human health effects causing early deaths attributable to respiratory, cardiovascular, and circulatory diseases in all ages and genders. Health end-points and health impact estimation, economic loss model, groups of PM2.5 concentration data, data of exposed population, data of baseline premature mortality rate, and data of health impact functions were used. Hourly PM2.5 concentration data sets were generated specifically using the coupled Weather Research and Forecasting Model (WRF)/Community Multiscale Air Quality Modelling System (CMAQ) models. Daily PM2.5 pollution levels considered mainly in the dry season (from January to April 2018) resulted in 12.9 (95% CI - 0.6; 18.7) all-cause premature deaths per 100,000 population, of which 7.8 (95% CI 1.1; 7.1), 1.5 (95% CI - 0.2; 3.1), and 3.6 (95% CI - 1.5; 8.5) were due to respiratory diseases (RDs; 60.54%), cardiovascular diseases (CVDs; 11.81%), and circulatory system diseases (CSDs; 27.65%) per 100,000 population, respectively. The total economic losses due to acute PM2.5 exposure-related premature mortality cases reached 62.0 (95% CI - 2.7; 89.6) billion VND, equivalent to 8.3 (95% CI - 0.4; 12.0) million USD. The study outcomes contributed remarkably to the generation and development of data sources for effectively managing ambient air quality in Long An.
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Affiliation(s)
- Long Ta Bui
- Laboratory for Environmental Modelling, Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam.
- Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam.
| | - Han Thi Ngoc Lai
- Laboratory for Environmental Modelling, Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam
- Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam
| | - Phong Hoang Nguyen
- Laboratory for Environmental Modelling, Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam
- Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam
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Bui LT, Nguyen NHT, Nguyen PH. Chronic and acute health effects of PM 2.5 exposure and the basis of pollution control targets. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:79937-79959. [PMID: 37291347 DOI: 10.1007/s11356-023-27936-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 05/22/2023] [Indexed: 06/10/2023]
Abstract
Ho Chi Minh City (HCMC) is changing and expanding quickly, leading to environmental consequences that seriously threaten human health. PM2.5 pollution is one of the main causes of premature death. In this context, studies have evaluated strategies to control and reduce air pollution; such pollution-control measures need to be economically justified. The objective of this study was to assess the socio-economic damage caused by exposure to the current pollution scenario, taking 2019 as the base year. A methodology for calculating and evaluating the economic and environmental benefits of air pollution reduction was implemented. This study aimed to simultaneously evaluate the impacts of both short-term (acute) and long-term (chronic) PM2.5 pollution exposure on human health, providing a comprehensive overview of economic losses attributable to such pollution. Spatial partitioning (inner-city and suburban) on health risks of PM2.5 and detailed construction of health impact maps by age group and sex on a spatial resolution grid (3.0 km × 3.0 km) was performed. The calculation results show that the economic loss from premature deaths due to short-term exposure (approximately 38.86 trillion VND) is higher than that from long-term exposure (approximately 14.89 trillion VND). As the government of HCMC has been developing control and mitigation solutions for the Air Quality Action Plan towards short- and medium-term goals in 2030, focusing mainly on PM2.5, the results of this study will help policymakers develop a roadmap to reduce the impact of PM2.5 during 2025-2030.
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Affiliation(s)
- Long Ta Bui
- Laboratory for Environmental Modelling, Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam.
- Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam.
| | - Nhi Hoang Tuyet Nguyen
- Laboratory for Environmental Modelling, Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam
- Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam
| | - Phong Hoang Nguyen
- Laboratory for Environmental Modelling, Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam
- Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam
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Ta Bui L, Nguyen PH. Assessment of rice yield and economic losses caused by ground-level O 3 exposure in the Mekong delta region, Vietnam. Heliyon 2023; 9:e17883. [PMID: 37519663 PMCID: PMC10372206 DOI: 10.1016/j.heliyon.2023.e17883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 06/28/2023] [Accepted: 06/30/2023] [Indexed: 08/01/2023] Open
Abstract
The Lower Mekong Delta region (LMD) accounts for 90% of Vietnam's rice exports; however, the air quality in the LMD is remarkably reduced by ground-level ozone (O3) pollution. This study aimed to quantify the relative yield and economic value losses in rice-growing crop seasons affected by ground-level O3 concentrations across the LMD. The results of this study can serve as a basis for extensive assessments for the following years and support environmental managers to propose control measures of O3 precursor emissions (NOx and VOCs) from man-made sectors, as well as build protective solutions for rice farming in LMD. Two ground-level O3 exposure metrics of M7 and AOT40 reflecting ground-level O3 pollution impacts, combined with the model of exposure-relative yield relationship (or surface O3-crop models), were used to assess losses of crop production (CPL) and economic cost losses (ECL) caused by rice crop yield reductions. For the M7 metric of ground-level O3 exposure, the average value was 14.746 ppbV, with levels ranging from 13.959 ppbV to 15.502 ppbV, and the affected area was spread across 1309.39 thousand hectares. The AOT40 exposure metric reached an average value of 11.490 ppbV, with a range of 0.000-31.665 ppbV. The highest exposure level was 17.503-31.653 ppbV, covering an area of 747.01 thousand hectares. The total CPL of the three rice crops over the LMD was 9593.52 tonnes (accounting for 0.039% of the total value of rice production in the region), with a total corresponding EPL of 62.405 billion VND (equivalent to 2761.01 thousand USD). The results are considered a baseline study to serve as a basis for extensive assessments for the following years and support for the environmental managers to propose control measures of O3 precursor emissions (NOx and VOCs) from man-made sectors as well as build protective solutions in rice farming in LMD shortly.
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Affiliation(s)
- Long Ta Bui
- Laboratory for Environmental Modelling, Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Viet Nam
- Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Viet Nam
| | - Phong Hoang Nguyen
- Laboratory for Environmental Modelling, Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Viet Nam
- Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Viet Nam
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Zhang J, Bian L, Dong F, Zeng Y, Nie J, Lv Z, He P, He J, Liu C, Yu W, Yi Z, Yu J, Huo T. Mineralogy and phase transition mechanisms of atmospheric mineral particles: Migration paths, sources, and volatile organic compounds. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 330:121789. [PMID: 37164219 DOI: 10.1016/j.envpol.2023.121789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 05/04/2023] [Accepted: 05/06/2023] [Indexed: 05/12/2023]
Abstract
Inorganic mineral particles play an important role in the formation of atmospheric aerosols in the Sichuan Basin. Atmospheric haze formation is accompanied by the phase transition of mineral particles under high humidity and stable climatic conditions. Backward trajectory analysis was used in this study to determine the migration trajectory of atmospheric mineral particles. Furthermore, Positive matrix factorization (PMF) was used to analyze the sources of atmospheric mineral particles. The phase transition mechanisms of atmospheric mineral particles were studied using ion chromatography, inductively coupled plasma emission spectrometry, total organic carbon analysis, X-ray diffraction, Fourier-transform infrared spectroscopy, scanning electron microscopy coupled with energy dispersive spectrometry, and grand canonical Monte Carlo methods. Three migration and phase transition paths were identified for the mineral particles. Sources of atmospheric mineral particles included combustion, vehicle emissions, industrial emissions, agricultural sources, and mineral dust. The main mineral phases in atmospheric particles, calcite and dolomite, were transformed into gypsum, and muscovite may be transformed into kaolinite. The phase transition of mineral particles seriously affects the formation of aerosols and worsens haze. Typically, along the Nanchong-Suining-Neijiang-Zigong-Yibin path, calcite is converted into gypsum under the influence of man-made inorganic pollution gases, which worsen the haze conditions and cause slight air pollution for 3-5 days. However, along the Guangyuan-Mianyang-Deyang-Chengdu-Meishan-Ya'an path, anthropogenic volatile organic compounds (VOCs) hindered gypsum formation from dolomite. Furthermore, dolomite and VOCs formed stable adsorption systems (system energies from -0.41 to -4.76 eV, long bonds from 0.20 to 0.24 nm). The adsorption system of dolomite and m/p-xylene, with low system energy (-1.46 eV/-1.33 eV) and significant correlation (r2 = 0.991, p < 0.01), was the main cause of haze formation. Consequently, calcite gypsification and dolomite-VOC synergism exacerbated regional haze conditions. This study provides a theoretical reference for the mechanism of aerosol formation in basin climates.
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Affiliation(s)
- Jiao Zhang
- Key Laboratory of Solid Waste Treatment and Resource Recycle, School of Environment and Resource, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
| | - Liang Bian
- Key Laboratory of Solid Waste Treatment and Resource Recycle, School of Environment and Resource, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China; State Key Laboratory of Environment-friendly Energy Materials, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China.
| | - Faqin Dong
- Key Laboratory of Solid Waste Treatment and Resource Recycle, School of Environment and Resource, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
| | - Yingying Zeng
- Key Laboratory of Solid Waste Treatment and Resource Recycle, School of Environment and Resource, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
| | - Jianan Nie
- Key Laboratory of Solid Waste Treatment and Resource Recycle, School of Environment and Resource, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
| | - Zhenzhen Lv
- School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
| | - Ping He
- School of Materials and Chemistry, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
| | - Jing He
- Key Laboratory of Solid Waste Treatment and Resource Recycle, School of Environment and Resource, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
| | - Chang Liu
- Key Laboratory of Solid Waste Treatment and Resource Recycle, School of Environment and Resource, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
| | - Wenxin Yu
- School of Computer and Technology, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
| | - Zao Yi
- School of Mathematics and Physics, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
| | - Jieyu Yu
- Key Laboratory of Solid Waste Treatment and Resource Recycle, School of Environment and Resource, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
| | - Tingting Huo
- Key Laboratory of Solid Waste Treatment and Resource Recycle, School of Environment and Resource, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China
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Wen C, Lang J, Zhou Y, Fan X, Bian Z, Chen D, Tian J, Wang P. Emission and influences of non-road mobile sources on air quality in China, 2000-2019. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 324:121404. [PMID: 36893973 DOI: 10.1016/j.envpol.2023.121404] [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: 12/14/2022] [Revised: 02/16/2023] [Accepted: 03/05/2023] [Indexed: 06/18/2023]
Abstract
Non-road mobile sources (NRMS) are potential important contributors to air pollution in China. However, their extreme impact on air quality had been seldom studied. In this study, the emission inventory of NRMS in mainland China during 2000-2019 was established. Then, the validated WRF-CAMx-PSAT model was applied to simulate the contribution to the atmospheric PM2.5, NO3-, and NOx. Results showed that emissions increased rapidly since 2000 and reached a peak in 2014-2015, with an annual average change rate (AACR) of 8.7-10.0%; after then, the emissions were relatively stable (AACR, -1.4-1.5%). The modeling results indicated that NRMS has become a crucial contributor to the air quality in China: from 2000 to 2019, the contribution to PM2.5, NOx, and NO3- significantly increased by 131.1%, 43.9%, and 61.7%; and for NOx, the contribution ratio in 2019 reached 24.1%. Further analysis showed that the reduction (-0.8% and -0.5%) of the NOx and NO3- contribution ratios was much lower than that (-4.8%) of NOx emissions from 2015 to 2019, implying that the control of NRMS lagged behind the national overall pollution control level. The contribution ratio of agricultural machinery (AM) and construction machinery (CM) to PM2.5, NOx, NO3- in 2019 was 2.6%, 11.3%, 8.3% and 2.5%, 12.6%, 6.8%, respectively. Although the contribution was much lower, the contribution ratio of civil aircraft had the fastest growth (202-447%). Moreover, an interesting phenomenon was that AM and CM had opposite contribution sensitivity characteristics for air pollutants: CM had a higher Contribution Sensitivity Index (CSI) for primary pollutants (e.g., NOx), ∼1.1 times that of AM; while AM had a higher CSI for secondary pollutants (e.g., NO3-), ∼1.5 times that of CM. This work can provide a deeper understanding for the environmental impact of NRMS emissions and for the control strategy formulation of NRMS.
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Affiliation(s)
- Chaoyu Wen
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing, 100124, China
| | - Jianlei Lang
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing, 100124, China; Beijing Laboratory for Intelligent Environmental Protection, Beijing University of Technology, Beijing, 100124, China.
| | - Ying Zhou
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing, 100124, China
| | - Xiaohan Fan
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing, 100124, China
| | - Zejun Bian
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing, 100124, China
| | - Dongsheng Chen
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing, 100124, China
| | - Jingjing Tian
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing, 100124, China
| | - Peiruo Wang
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing, 100124, China
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Xiong X, Wang Z, Cheng C, Li M, Yun L, Liu S, Mao L, Zhou Z. Long-Term Observation of Mixing States and Sources of Vanadium-Containing Single Particles from 2020 to 2021 in Guangzhou, China. TOXICS 2023; 11:339. [PMID: 37112565 PMCID: PMC10144789 DOI: 10.3390/toxics11040339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 03/29/2023] [Accepted: 03/30/2023] [Indexed: 06/19/2023]
Abstract
The distribution of vanadium (V) in aerosols is commonly used to track ship exhaust emissions, yet the atmospheric abundance of V has been greatly reduced due to the implementation of a clean fuel policy. Recent research mainly discussed the chemical compositions of ship-related particles during specific events, yet few studies focus on the long-term changes of V in the atmosphere. In this study, a single-particle aerosol mass spectrometer was used to measure V-containing particles from 2020 to 2021 in Huangpu Port in Guangzhou, China. The long-term trend of the particle counts of V-containing particles declined annually, but the relative abundance of V-containing particles in the total single particles increased in summer due to the influence of ship emissions. Positive matrix factorization revealed that in June and July 2020, 35.7% of the V-containing particles were from ship emissions, followed by dust and industrial emissions. Furthermore, more than 80% of the V-containing particles were found mixing with sulfate and 60% of the V-containing particles were found mixing with nitrate, suggesting that the majority of the V-containing particles were secondary particles processed during the transport of ship emissions to urban areas. Compared with the small changes in the relative abundance of sulfate in the V-containing particles, the relative abundance of nitrate exhibited clear seasonal variations, with a high abundance in winter. This may have been due to the increased production of nitrate from high concentrations of precursors and a suitable chemical environment. For the first time, the long-term trends of V-containing particles in two years are investigated to demonstrate changes in their mixing states and sources after the clean fuel policy, and to suggest the cautious application of V as an indicator of ship emissions.
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Affiliation(s)
- Xin Xiong
- 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
| | - Zaihua Wang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
- Institute of Resources Utilization and Rare Earth Development, Guangdong Academy of Sciences, Guangzhou 510650, China
| | - Chunlei Cheng
- 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
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy Science, Xi’an 710061, China
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Mei Li
- 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
| | - Lijun Yun
- 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
| | - Sulin Liu
- 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
| | - Liyuan Mao
- 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
| | - Zhen Zhou
- 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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Zhang X, Feng X, Tian J, Zhang Y, Li Z, Wang Q, Cao J, Wang J. Dynamic harmonization of source-oriented and receptor models for source apportionment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 859:160312. [PMID: 36403825 DOI: 10.1016/j.scitotenv.2022.160312] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 11/15/2022] [Accepted: 11/15/2022] [Indexed: 06/16/2023]
Abstract
Millions of premature mortalities are caused by the air pollution of fine particulate matter with aerodynamic diameters less than 2.5 μm (PM2.5) globally per year. To effectively control the dominant emission sources and abate air pollution, source apportionment of PM2.5 is normally conducted to quantify the contributions of various sources, but the results of different methods might be inconsistent. In this study, we dynamically harmonized the results from the two dominant source apportionment methods, the source-oriented and receptor models, by updating the emission inventories of primary PM2.5 from the major sectors based on the Bayesian Inference. An adjoint model was developed to efficiently construct the source-receptor sensitivity matrix, which was the critical information for the updates, and depicted the response of measurements to the changes in the emissions of various sources in different regions. The harmonized method was applied to a measurement campaign in Beijing from January to February 2021. The results suggested a significant reduction of primary PM2.5 emissions in Beijing. Compared with the baseline emission inventory of 2017, the primary PM2.5 emissions from the local residential combustion and industry in Beijing had significantly declined by about 90 % during the investigated period of the year, and the traffic emission decreased by about 50 %. The proposed methods successfully identified the temporally dynamic changes in the emissions induced by the Spring Festival. The methods could be a promising pathway for the harmonization of source-oriented and receptor source apportionment models.
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Affiliation(s)
- Xiaole Zhang
- Institute of Environmental Engineering (IfU), ETH Zürich, Zürich CH-8093, Switzerland; Laboratory for Advanced Analytical Technologies, Empa, Dübendorf CH-8600, Switzerland; Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing, China
| | - Xiaoxiao Feng
- Institute of Environmental Engineering (IfU), ETH Zürich, Zürich CH-8093, Switzerland; Laboratory for Advanced Analytical Technologies, Empa, Dübendorf CH-8600, Switzerland
| | - Jie Tian
- Key Laboratory of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
| | - Yong Zhang
- Key Laboratory of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
| | - Zhiyu Li
- Key Laboratory of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
| | - Qiyuan Wang
- Key Laboratory of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
| | - Junji Cao
- Key Laboratory of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
| | - Jing Wang
- Institute of Environmental Engineering (IfU), ETH Zürich, Zürich CH-8093, Switzerland; Laboratory for Advanced Analytical Technologies, Empa, Dübendorf CH-8600, Switzerland.
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11
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Bui LT, Nguyen PH. Ground-level ozone in the Mekong Delta region: precursors, meteorological factors, and regional transport. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:23691-23713. [PMID: 36323970 DOI: 10.1007/s11356-022-23819-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 10/21/2022] [Indexed: 06/16/2023]
Abstract
The Mekong Delta region (MDR), also known as Vietnam's rice bowl, produced a bountiful harvest of about 23.8 million tons in 2020, accounting for 55.7% of the country's total production, providing food security for 20% of the world population. With the rapid pace of industrialisation and urbanisation, the concentration of ozone in the lower atmosphere has risen to a level that reduces crop yields, especially rice, and is therefore the subject of research. This study aims to simulate the spatiotemporal distribution of ground-level ozone in the area and evaluate the impact of precursor emissions and meteorological factors on the spatiotemporal distributions of ozone concentrations. The study area was divided into seven zones, including six agro-ecological zones (AEZs) and one low-mountainous area, mainly to clarify the role of emissions in each AEZ. The simulation results showed that ground-level O3 in the MDR ranged from 40.39 to 52.13 µg/m3. In six agro-ecological zones, the average annual ground-level O3 concentration was relatively high and was the highest in zone 6 (CPZ) and zone 3 (LXZ) with values of 96.18 µg/m3 (exceeding 1.60 times the WHO Guidelines 2021) and 94.86 µg/m3 (exceeding 1.58 times the WHO Guidelines 2021), respectively. In each zone, the annual average O3 concentration tended to gradually increase from the inner delta to coastal areas. Two types of precursors, NOx and NMVOCs, are the main contributors to O3 pollution, with the largest contribution coming from zone 1 (FAZ) with 91.5 thousand tons of NOx/year and 455.2 thousand tons of NMVOCs/year. Among the meteorological factors considered, temperature (T), relative humidity (RH), and surface pressure (P) were the three main factors that contributed to the increase in ground-level ozone. The spatio-temporal distribution of ground-level O3 in the MDR was influenced by emission precursors from different zones as well as meteorological factors. The present results can help policy-makers formulate plans for agro-industrial development in the entire region.
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Affiliation(s)
- Long Ta Bui
- Laboratory for Environmental Modelling, Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam.
- Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam.
| | - Phong Hoang Nguyen
- Laboratory for Environmental Modelling, Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam
- Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam
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12
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Liu Z, Zhang H, Zhang Y, Liu X, Ma Z, Xue L, Peng X, Zhao J, Gong W, Peng Q, Du J, Wang J, Tan Y, He L, Sun Y. Characterization and sources of trace elements in PM 1 during autumn and winter in Qingdao, Northern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 811:151319. [PMID: 34757104 DOI: 10.1016/j.scitotenv.2021.151319] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 10/08/2021] [Accepted: 10/26/2021] [Indexed: 06/13/2023]
Abstract
Atmospheric sub-micrometer particles (PM1, particles with an aerodynamic diameter ≤ 1.0 μm) monitoring in Qingdao, a coastal city in Northern China, was conducted for two consecutive years from November 1, 2018 to January 31, 2019 (hereafter referred to as OP2018-2019) and from October 28, 2019 to January 20, 2020 (hereafter referred to as OP2019-2020). The results showed that compared with OP2018-2019, the concentrations of V, Ni, As, Pb, and Cd in PM1 in OP2019-2020 decreased by 61.9%, 31.4%, 49.2%, 25.4%, and 27.1%, respectively. For the indicators of ship emission sources, a significant reduction in V (73.3%) and Ni (22.1%) concentrations were observed after the implementation of the updated Domestic Emission Control Area (DECA 2.0) policy for ships since January 1, 2019 proposed by the Ministry of Transportation. This result demonstrated that the implementation of the DECA 2.0 policy had a significant effect on reducing ship emissions. The Field Emission Scanning Electron Microscope analysis identified the impact of ship emission sources, while the inconsistent distribution of V and Ni revealed other potential sources of Ni. The V/Ni ratios during the pre-policy and post-policy periods decreased by 40.7%. Along with the further implementation of the domestic coastal ship pollution control zone policy, V/Ni ratio should be cautiously used as a parameter for ship emission sources. The positive matrix factorization method identified five source factors: coal combustion/biomass burning (47.8%), crustal sources (21.2%), vehicle exhaust/road dust (15.1%), industrial emissions (11.1%), and ship emissions (4.9%). The contribution rates of ship emission sources before and after the DECA 2.0 policy were analyzed and found to be 5.6% and 3.4%. The potential source contribution factor analysis of As showed that the potential emission source areas were significantly reduced in OP2019-2020, which might be related to the coal fired cleanup operations conducted in Beijing-Tianjin-Hebei and surrounding areas.
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Affiliation(s)
- Ziyang Liu
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
| | - Houyong Zhang
- Jinan Eco-environment Monitoring Center of Shandong Province, Jinan 250100, China
| | - Yisheng Zhang
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangdong 511486, China.
| | - Xiaohuan Liu
- Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao 266100, China
| | - Zizhen Ma
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
| | - Lian Xue
- Qingdao Eco-environment Monitoring Center of Shandong Province, Qingdao 266003, China
| | - Xing Peng
- School of Environment and Energy, Peking University, Shenzhen 518055, China
| | - Jiaojiao Zhao
- Jinan Eco-environment Monitoring Center of Shandong Province, Jinan 250100, China
| | - Weiwei Gong
- Laboratory of Transport Pollution Control and Monitoring Technology, Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
| | - Qianqian Peng
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
| | - Jinhua Du
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
| | - Jiao Wang
- Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao 266100, China
| | - Yuran Tan
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
| | - Lingyan He
- School of Environment and Energy, Peking University, Shenzhen 518055, China
| | - Yingjie Sun
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
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13
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Recent Advances in Studying Air Quality and Health Effects of Shipping Emissions. ATMOSPHERE 2021. [DOI: 10.3390/atmos12010092] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
The increase of global commerce and tourism makes the shipping sector an important contributor of atmospheric particles and gaseous pollutants. These have impacts on both health and climate, especially in populated coastal areas. Maritime activities could be an important driver for economic and social development, however, they are also an environmental pressure. Several policies were implemented in the last decades, at local/regional or international levels, mainly focused on reducing the content of sulphur in marine fuels. The last international IMO-2020 regulation was enforced on 1 January 2020. This work reviews some recent studies on this topic delineating current knowledge of the impacts of maritime emissions on air quality and health and the future projections relative to the benefits of the implementation of the new IMO-2020 regulation. In addition, future perspectives for further mitigation strategies are discussed.
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Liu B, Wu J, Wang J, Shi L, Meng H, Dai Q, Wang J, Song C, Zhang Y, Feng Y, Hopke PK. Chemical characteristics and sources of ambient PM 2.5 in a harbor area: Quantification of health risks to workers from source-specific selected toxic elements. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 268:115926. [PMID: 33153802 DOI: 10.1016/j.envpol.2020.115926] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 10/21/2020] [Accepted: 10/22/2020] [Indexed: 06/11/2023]
Abstract
Samples of ambient PM2.5 were collected in the Qingdao harbor area between 21 March and May 25, 2016, and analyzed to investigate the compositions and sources of PM2.5 and to assess source-specific selected toxic element health risks to workers via a combination of positive matrix factorization (PMF) and health risk (HR) assessment models. The mean concentration of PM2.5 in harbor area was 48 μg m-3 with organic matter (OM) dominating its mass. Zn and V concentrations were significantly higher than the other selected toxic elements. The hazard index (HI) and cancer risk (Ri) of all selected toxic elements were lower than the United States Environmental Protection Agency (USEPA) limits. There were no non-cancer and cancer risks for workers in harbor area. The contributions from industrial emissions (IE), ship emissions (SE), vehicle emissions (VE), and crustal dust and coal combustion (CDCC) to selected toxic elements were 39.0%, 12.8%, 24.0%, and 23.0%, respectively. The HI values of selected toxic elements from IE, CDCC, SE, and VE were 1.85 × 10-1, 7.08 × 10-2, 6.36 × 10-2, and 3.37 × 10-2, respectively; these are lower than the USEPA limits. The total cancer risk (Rt) value from selected toxic elements in CDCC was 2.04 × 10-7, followed by IE (6.40 × 10-8), SE (2.26 × 10-8), and VE (2.18 × 10-8). CDCC and IE were the likely sources of cancer risk in harbor area. The Bo Sea and coast were identified as the likely source areas for health risks from IE via potential source contribution function (PSCF) analysis based on the results of PMF-HR modelling. Although the source-specific health risks were below the recommended limit values, this work illustrates how toxic species in PM2.5 health risks can be associated with sources such that control measures could be undertaken if the risks warranted it.
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Affiliation(s)
- Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Jianhui Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
| | - Jing Wang
- Qingdao Ecological and Environmental Monitoring Centre of Shandong Province, Qingdao, 266003, China
| | - Laiyuan Shi
- Qingdao Ecological and Environmental Monitoring Centre of Shandong Province, Qingdao, 266003, China
| | - He Meng
- Qingdao Ecological and Environmental Monitoring Centre of Shandong Province, Qingdao, 266003, China
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Jiao Wang
- College of Environmental Science and Engineering, Key Laboratory of Marine Environmental Science and Ecology (Ministry of Education), Ocean University of China, Qingdao, Shandong, 266100, China
| | - Congbo Song
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Philip K Hopke
- Center for Air Resources Engineering and Science, Clarkson University, Potsdam, NY, 13699, USA; Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, 14642, USA
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15
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Merico E, Conte M, Grasso FM, Cesari D, Gambaro A, Morabito E, Gregoris E, Orlando S, Alebić-Juretić A, Zubak V, Mifka B, Contini D. Comparison of the impact of ships to size-segregated particle concentrations in two harbour cities of northern Adriatic Sea. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 266:115175. [PMID: 32683088 DOI: 10.1016/j.envpol.2020.115175] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 06/29/2020] [Accepted: 07/02/2020] [Indexed: 06/11/2023]
Abstract
Detailed information on in-harbour shipping contribution to size segregated particles in coastal cities are scarce, especially in the busy Mediterranean basin. This poses issues for human exposure and air quality in urban harbour agglomerates, where only criteria pollutants (i.e. PM10 and/or PM2.5) are usually monitored. In this work, particle number and mass size distributions, in a large size range (0.01-31 μm), were obtained in two coastal cities of northern Adriatic Sea: Venice (Italy) and Rijeka (Croatia). Three size ranges were investigated: nanoparticles (diameter D < 0.25 μm); fine particles (0.25<D < 1 μm), and coarse particles (D > 1 μm). Absolute concentrations were larger in Venice for all size ranges showing, using analysis of daily trends, a large influence of local meteorology and boundary-layer dynamics. Contribution of road transport was larger (in relative terms) in Rijeka compared to Venice. The highest contributions of shipping were in Venice, mainly because of the larger ship traffic. Maximum impact was on nanoparticles 7.4% (Venice) and 1.8% (Rijeka), the minimum was on fine range 1.9% (Venice) and <0.2% (Rijeka) and intermediate values were found in the coarse fraction 1.8% (Venice) and 0.5% (Rijeka). Contribution of shipping to mass concentration was not distinguishable from uncertainty in Rijeka (<0.2% for PM1, PM2.5, and PM10) and was about 2% in Venice. Relative contributions as function of particles size show remarkable similitudes: a maximum for nanoparticles, a quick decrease and a successive secondary maximum (2-3 times lower than the first) in the fine range. For larger diameters, the relative contributions reach a minimum at 1-1.5 μm and there is a successive increase in the coarse range. Size distributions showed a not negligible contribution of harbour emissions to nanoparticle and fine particle number concentrations, compared to PM2.5 or PM10, indicating them as a better metric to monitor shipping impacts compared to mass concentrations (PM2.5 or PM10).
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Affiliation(s)
- E Merico
- Institute of Atmospheric Sciences and Climate, National Research Council of Italy (ISAC-CNR), Str. Prv. Lecce-Monteroni km 1.2, Lecce, Italy.
| | - M Conte
- Institute of Atmospheric Sciences and Climate, National Research Council of Italy (ISAC-CNR), Str. Prv. Lecce-Monteroni km 1.2, Lecce, Italy
| | - F M Grasso
- Institute of Atmospheric Sciences and Climate, National Research Council of Italy (ISAC-CNR), Str. Prv. Lecce-Monteroni km 1.2, Lecce, Italy
| | - D Cesari
- Institute of Atmospheric Sciences and Climate, National Research Council of Italy (ISAC-CNR), Str. Prv. Lecce-Monteroni km 1.2, Lecce, Italy
| | - A Gambaro
- Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Via Torino 155, Venice Mestre, Italy
| | - E Morabito
- Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Via Torino 155, Venice Mestre, Italy
| | - E Gregoris
- Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Via Torino 155, Venice Mestre, Italy; Institute of Polar Sciences, National Research Council of Italy (ISP-CNR), Via Torino 155, Venice Mestre, Italy
| | - S Orlando
- Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Via Torino 155, Venice Mestre, Italy
| | - A Alebić-Juretić
- Faculty of Medicine, University of Rijeka, Braće Branchetta 20, Rijeka, Croatia
| | - V Zubak
- Teaching Institute of Public Health, Krešimirova 52a, Rijeka, Croatia
| | - B Mifka
- Department of Physics, University of Rijeka, Radmile Matejčić 2, Rijeka, Croatia
| | - D Contini
- Institute of Atmospheric Sciences and Climate, National Research Council of Italy (ISAC-CNR), Str. Prv. Lecce-Monteroni km 1.2, Lecce, Italy
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16
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Almeida SM, Manousakas M, Diapouli E, Kertesz Z, Samek L, Hristova E, Šega K, Alvarez RP, Belis CA, Eleftheriadis K. Ambient particulate matter source apportionment using receptor modelling in European and Central Asia urban areas. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 266:115199. [PMID: 32777678 DOI: 10.1016/j.envpol.2020.115199] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 06/21/2020] [Accepted: 07/05/2020] [Indexed: 05/12/2023]
Abstract
This work presents the results of a PM2.5 source apportionment study conducted in urban background sites from 16 European and Asian countries. For some Eastern Europe and Central Asia cities this was the first time that quantitative information on pollution source contributions to ambient particulate matter (PM) has been performed. More than 2200 filters were sampled and analyzed by X-Ray Fluorescence (XRF), Particle-Induced X-Ray Emission (PIXE), and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) to measure the concentrations of chemical elements in fine particles. Samples were also analyzed for the contents of black carbon, elemental carbon, organic carbon, and water-soluble ions. The Positive Matrix Factorization receptor model (EPA PMF 5.0) was used to characterize similarities and heterogeneities in PM2.5 sources and respective contributions in the cities that the number of collected samples exceeded 75. At the end source apportionment was performed in 11 out of the 16 participating cities. Nine major sources were identified to have contributed to PM2.5: biomass burning, secondary sulfates, traffic, fuel oil combustion, industry, coal combustion, soil, salt and "other sources". From the averages of sources contributions, considering 11 cities 16% of PM2.5 was attributed to biomass burning, 15% to secondary sulfates, 13% to traffic, 12% to soil, 8.0% to fuel oil combustion, 5.5% to coal combustion, 1.9% to salt, 0.8% to industry emissions, 5.1% to "other sources" and 23% to unaccounted mass. Characteristic seasonal patterns were identified for each PM2.5 source. Biomass burning in all cities, coal combustion in Krakow/POL, and oil combustion in Belgrade/SRB and Banja Luka/BIH increased in Winter due to the impact of domestic heating, whereas in most cities secondary sulfates reached higher levels in Summer as a consequence of the enhanced photochemical activity. During high pollution days the largest sources of fine particles were biomass burning, traffic and secondary sulfates.
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Affiliation(s)
- S M Almeida
- Centro de Ciências e Tecnologias Nucleares, Instituto Superior Técnico, Universidade de Lisboa, Estrada Nacional 10, 2695-066, Bobadela-LRS, Portugal.
| | - M Manousakas
- Environmental Radioactivity Laboratory, INRaSTES, National Centre for Scientific Research "Demokritos", Patriarhou Gregoriou E' and Neapoleos, Agia Paraskevi, 15341, Athens, Greece; Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), 5232, Villigen-PSI, Switzerland
| | - E Diapouli
- Environmental Radioactivity Laboratory, INRaSTES, National Centre for Scientific Research "Demokritos", Patriarhou Gregoriou E' and Neapoleos, Agia Paraskevi, 15341, Athens, Greece
| | - Z Kertesz
- ICER Centre, Institute for Nuclear Research, Bem ter 18C, 4026, Debrecen, Hungary
| | - L Samek
- AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, ul. Mickiewicza 30, 30-059, Krakow, Poland
| | - E Hristova
- National Institute of Meteorology and Hydrology Bulgarian Academy of Sciences, 66 Tzarigradko Chaussee, 1784, Sofia, Bulgaria
| | - K Šega
- Environmental Hygiene Unit, Institute for Medical Research and Occupational Health (IMROH), Ksaverska cesta 2, P.O. Box 291, 10001, Zagreb, Croatia
| | - R Padilla Alvarez
- International Atomic Energy Agency, Department of Nuclear Sciences and Applications, Division of Physical and Chemical Sciences, Physics Section, Nuclear Science and Instrumentation Laboratory, Vienna International Centre, Wagramer strasse 5, P.O. Box 100, 1400, Vienna, Austria
| | - C A Belis
- European Commission, Joint Research Centre, Directorate Energy, Transport and Climate, Via Enrico Fermi 2749, Ispra (VA), 21027, Italy
| | - K Eleftheriadis
- Environmental Radioactivity Laboratory, INRaSTES, National Centre for Scientific Research "Demokritos", Patriarhou Gregoriou E' and Neapoleos, Agia Paraskevi, 15341, Athens, Greece
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17
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Health Impact of Air Pollution from Shipping in the Baltic Sea: Effects of Different Spatial Resolutions in Sweden. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17217963. [PMID: 33138267 PMCID: PMC7663031 DOI: 10.3390/ijerph17217963] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 10/23/2020] [Accepted: 10/27/2020] [Indexed: 02/06/2023]
Abstract
In 2015, stricter regulations to reduce sulfur dioxide emissions and particulate air pollution from shipping were implemented in the Baltic Sea. We investigated the effects on population exposure to particles <2.5 µm (PM2.5) from shipping and estimated related morbidity and mortality in Sweden’s 21 counties at different spatial resolutions. We used a regional model to estimate exposure in Sweden and a city-scale model for Gothenburg. Effects of PM2.5 exposure on total mortality, ischemic heart disease, and stroke were estimated using exposure–response functions from the literature and combining them into disability-adjusted life years (DALYS). PM2.5 exposure from shipping in Gothenburg decreased by 7% (1.6 to 1.5 µg/m3) using the city-scale model, and 35% (0.5 to 0.3 µg/m3) using the regional model. Different population resolutions had no effects on population exposures. In the city-scale model, annual premature deaths due to shipping PM2.5 dropped from 97 with the high-sulfur scenario to 90 in the low-sulfur scenario, and in the regional model from 32 to 21. In Sweden, DALYs lost due to PM2.5 from Baltic Sea shipping decreased from approximately 5700 to 4200. In conclusion, sulfur emission restrictions for shipping had positive effects on health, but the model resolution affects estimations.
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Zhao J, Zhang Y, Patton AP, Ma W, Kan H, Wu L, Fung F, Wang S, Ding D, Walker K. Projection of ship emissions and their impact on air quality in 2030 in Yangtze River delta, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 263:114643. [PMID: 33618465 DOI: 10.1016/j.envpol.2020.114643] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Revised: 04/17/2020] [Accepted: 04/19/2020] [Indexed: 06/12/2023]
Abstract
China has been in the implementation phase of Domestic Ship Emission Control Areas (DECAs) regulation to reduce emissions of air pollutants from ships near populated areas since 2016. The Yangtze River Delta (YRD) is one of the busiest port clusters in the world, accounting for 11% of global seaborne cargo throughput, so future improvements in shipping emission controls may still be important in this region. To assess the impact of future ship emissions on air quality of coastal areas, this study evaluates emissions reductions and air quality in 2030 for three scenarios (business as usual, stricter regulations, and aspirational policies) representing increasing levels of control compared with a base year of 2015. We projected ship emissions in the region using a bottom-up approach developed in this study and based on the historical ship automatic identification system (AIS) activity data. We then predicted air quality across the YRD region in 2030 using the Community Multiscale Air Quality (CMAQ) model. The annual average contributions of ship emissions to ambient PM2.5 would decrease by 70.9%, 80.4%, and 86.2% relative to 2015 under the three scenarios, with the largest reductions of more than 4.1 μg/m3 near Shanghai Port under the aspirational scenario. Reductions in ship emissions generally led to lower levels of PM2.5, particularly in most of the coastal cities in the YRD. Compared with a business-as-usual approach the aspirational scenario reduced SO2, NOx and PM2.5 concentrations from shipping by 71.8%, 61.1% and 52.5%, respectively. It was also more effective than the stricter regulation scenario, suggesting that the requirement to use 0.1% sulfur fuel within a 100Nm DECA would have additional benefits to ambient PM2.5 concentrations beyond 12Nm DECA area. This study provides evidence to inform deliberations on the potential air quality benefits of future control policies for ship emissions in China.
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Affiliation(s)
- Junri Zhao
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China; Big Data Institute for Carbon Emission and Environmental Pollution, Fudan University, Shanghai, 200433, China
| | - Yan Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China; Shanghai Institute of Eco-Chongming (SIEC), Shanghai, 200062, China; Institute of Atmospheric Science, Fudan University, Shanghai, 200438, China.
| | - Allison P Patton
- Health Effects Institute, 75 Federal Street, Suite 1400, Boston, MA, 02110-1817, USA
| | - Weichun Ma
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China; Shanghai Institute of Eco-Chongming (SIEC), Shanghai, 200062, China; Big Data Institute for Carbon Emission and Environmental Pollution, Fudan University, Shanghai, 200433, China
| | - Haidong Kan
- Public Health School, Fudan University, Shanghai, 200032, China
| | - Libo Wu
- Big Data Institute for Carbon Emission and Environmental Pollution, Fudan University, Shanghai, 200433, China
| | - Freda Fung
- Natural Resources Defense Council, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Dian Ding
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Katherine Walker
- Health Effects Institute, 75 Federal Street, Suite 1400, Boston, MA, 02110-1817, USA
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Guo X, Wu H, Chen D, Ye Z, Shen Y, Liu J, Cheng S. Estimation and prediction of pollutant emissions from agricultural and construction diesel machinery in the Beijing-Tianjin-Hebei (BTH) region, China ☆. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 260:113973. [PMID: 31991351 DOI: 10.1016/j.envpol.2020.113973] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 01/10/2020] [Accepted: 01/11/2020] [Indexed: 05/19/2023]
Abstract
Both agricultural and construction machinery are important non-road sources of atmospheric pollution, with total hydrocarbons (THC), nitrogen oxides (NOx) and particulate matter (PM) emissions accounting for more than 60% of the total emissions from all non-road mobile sources in China. However, there exist relatively few efforts to establish the emission inventory for these machineries. This study attempted to estimate and predict air pollutant emissions from agricultural and construction diesel machinery, using the Beijing-Tianjin-Hebei (BTH) region as the case study area. The results show that total emissions of PM10, PM2.5, THC, NOX, CO and SO2 in 2015 were 41.10, 38.80, 86.14, 520.41, 379.01 and 17.32 Kt respectively. The contribution of agricultural machinery was slightly higher than that of construction machinery, accounting for 60-71% of the total. Moreover, emissions of various pollutants (except SO2) from agricultural machinery were mainly distributed in central Hebei (Cangzhou, Shijiazhuang and Baoding), while emissions from construction machinery were mainly distributed in Beijing and Tianjin. The prediction suggest that the total emissions of agricultural and construction diesel machinery in the BTH region would increase by 6% in 2020 and 9% in 2025. Moreover, pollutant emissions from construction machinery would contribute from 29% to 40% in 2015 to 34%-61% in 2025. These results could provide important information for making effective mitigation measures of non-road mobile sources.
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Affiliation(s)
- Xiurui Guo
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China.
| | - Hongkan Wu
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China
| | - Dongsheng Chen
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China.
| | - Zhilan Ye
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China
| | - Yaqian Shen
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China
| | - Junfang Liu
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China
| | - Shuiyuan Cheng
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China
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Wan Q, Liu Z, Yang M, Deng P, Tang N, Liu Y. Triptolide ameliorates fine particulate matter-induced podocytes injury via regulating NF-κB signaling pathway. BMC Mol Cell Biol 2020; 21:4. [PMID: 32013860 PMCID: PMC6998203 DOI: 10.1186/s12860-020-0248-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Accepted: 06/02/2019] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND PM2.5 is associated closely with an increased risk of membranous nephropathy (MN), however, whether PM2.5 could induce podocytes injury, the underlying pathology for MN, has not be thoroughly studied. Triptolide, an active component in Tripterygium wilfordii Hook F, is frequently used to treat MN in China, but its effects on PM2.5-induced podocytes injury is still largely unknown. Therefore, we evaluated the effects of PM2.5 on podocytes, and explored whether triptolide could improve PM2.5-induced podocytes injury and the possible underlying mechanisms. RESULTS Podocytes were incubated with PM2.5 after being pre-treated with triptolide, viability, apoptosis rate and migratory capacity of podocytes were determined by CCK-8 assay, flow cytometry and Transwell assay, respectively. Additionally, the levels of lactate dehydrogenase (LDH), malondialdehyde (MDA), and superoxide dismutase (SOD) in podocytes, the cytoskeleton of podocytes, the protein expressions of nephrin, podocin, Bcl-2, Bax, nuclear factor kappa-B/p65 (NF-κB/p65) and phospho-inhibitor of NF-κB (p-IκBα) were measured. Our data showed that PM2.5 treatment significantly increased the disorganization of F-actin stress fibers, the damaged structural integrity of nucleus, the deranged and dissociated cytoskeleton in podocytes, increased the podocytes apoptosis rate, the levels of MDA and LDH, markedly up-regulated the protein expression of Bax, NF-κB/p65 and p-IκBα, down-regulated the protein expression of nephrin, podocin and Bcl-2, and significantly decreased the level of SOD, the migration rate and the viability of podocytes, compared with those of the untreated podocytes. These effects of PM2.5 on podocytes, however, were reversed by triptolide administration. CONCLUSION These results suggest that triptolide could prevent against PM2.5-induced podocytes injury via suppressing NF-κB signaling pathway.
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Affiliation(s)
- Qiang Wan
- Department of Medical Cardiology, The Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, 330006, China.
| | - Zhongyong Liu
- Department of Medical Cardiology, The Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, 330006, China
| | - Ming Yang
- Key Laboratory of Modern Preparation of Traditional Chinese Medicine of Ministry of Education, Jiangxi University of Traditional Chinese Medicine, Nanchang, 330004, China
| | - Peng Deng
- Department of Medical Cardiology, The Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, 330006, China
| | - Nana Tang
- Department of Medical Cardiology, The Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, 330006, China
| | - Yanwei Liu
- Department of Medical Cardiology, The Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, 330006, China
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Sorte S, Rodrigues V, Borrego C, Monteiro A. Impact of harbour activities on local air quality: A review. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 257:113542. [PMID: 31733971 DOI: 10.1016/j.envpol.2019.113542] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2019] [Revised: 10/29/2019] [Accepted: 10/29/2019] [Indexed: 06/10/2023]
Abstract
Several harbour activities cause negative environmental impacts in the harbours' surrounding areas, namely the degradation of air quality. This paper intends to comprehensively review the status of the air quality measured in harbour areas. The published studies show a limited number of available air quality monitoring data in harbours areas, mostly located in Europe (71%). Measured concentrations of the main air pollutants were compiled and intercompared, for different countries worldwide allowing a large spatial representativeness. The higher NO2 and PM10 concentrations were found in Europe - ranging between 12 and 107 μg/m3 and 2-50 μg/m3, respectively, while the higher concentrations of PM2.5 were found in Asia (25-70 μg/m3). In addition, the lower levels of SO2 monitored in recent years suggest that current mitigation strategies adopted across Europe were very efficient in promoting the reduction of SO2 concentrations. Part of the reviewed studies also estimated the contributions from ship emissions to PM concentration through the application of source apportionment methods, with an average of 5-15%. In some specific harbour areas in Asia, ships can contribute up to 7-26% to the local fine particulate matter concentrations. This review confirms that emissions from the maritime transport sector should be considered as a significant source of particulate matter in harbour areas, since this pollutant concentrations are frequently exceeding the established standard legal limit values. Therefore, the results from this review boost the implementation of mitigation measures, aiming to reduce, in particular, particulate matter emissions.
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Affiliation(s)
- Sandra Sorte
- CESAM, Department of Environment and Planning, University of Aveiro, 3810-193, Aveiro, Portugal.
| | - Vera Rodrigues
- CESAM, Department of Environment and Planning, University of Aveiro, 3810-193, Aveiro, Portugal
| | - Carlos Borrego
- CESAM, Department of Environment and Planning, University of Aveiro, 3810-193, Aveiro, Portugal
| | - Alexandra Monteiro
- CESAM, Department of Environment and Planning, University of Aveiro, 3810-193, Aveiro, Portugal
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Liang Z, Zhao X, Chen J, Gao L, Zhu A, Wang Z, Li S, Shan J, Long Y, Yan C, Zhang K. Seasonal characteristics of chemical compositions and sources identification of PM 2.5 in Zhuhai, China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2019; 41:715-728. [PMID: 30116925 DOI: 10.1007/s10653-018-0164-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Accepted: 07/27/2018] [Indexed: 06/08/2023]
Abstract
Fine particulate matter is associated with adverse health effects, but exactly which characteristics of PM2.5 are responsible for this is still widely debated. We evaluated seasonal dynamics of the composition and chemical characteristics of PM2.5 in Zhuhai, China. PM2.5 characteristics at five selected sites within Zhuhai city were analyzed. Sampling began on January 10, 2015, and was conducted for 1 year. The ambient mass concentration, carbon content (organic and elemental carbon, OC and EC), level of inorganic ions, and major chemical composition of PM2.5 were also determined. Average concentrations of PM2.5 were lower than the National Ambient Air Quality Standard (NAAQS) 24-h average of 65 μg/m3. The daily PM2.5 concentration in Zhuhai city exhibited clear seasonal dynamics, with higher daily PM2.5 concentrations in autumn and winter than in spring and summer. Carbon species (OC and EC) and water-soluble ions were the primary components of the PM2.5 fraction of particles. Apart from OC and EC, chemical species in PM2.5 were mainly composed of NH4+ and SO42-. There was a marked difference between the summer and winter periods: the concentrations of OC and EC in winter were roughly 3.4 and 4.0 times than those in summer, while NH4+, SO42-, NO3-, and Na+ were 3.2, 4.5, 28.0, and 5.7 times higher in winter than those in summer, respectively. The results of chemical analysis were consistent with three sources dominating PM2.5: coal combustion, biomass burning, and vehicle exhaust; road dust and construction; and from reaction of HCl and HNO3 with NH3 to form NH4Cl and NH4NO3. However, additional work is needed to improve the mass balance and to obtain the source profiles necessary to use these data for source apportionment.
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Affiliation(s)
- Zuobing Liang
- Center for Water Resources and Environment, School of Geographic Science and Planning, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou, 510275, People's Republic of China
| | - Xinfeng Zhao
- Zhuhai Environmental Protection Monitoring Station, Zhuhai, 519000, People's Republic of China.
| | - Jianyao Chen
- Center for Water Resources and Environment, School of Geographic Science and Planning, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou, 510275, People's Republic of China.
| | - Lei Gao
- Center for Water Resources and Environment, School of Geographic Science and Planning, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou, 510275, People's Republic of China
| | - Aiping Zhu
- Center for Water Resources and Environment, School of Geographic Science and Planning, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou, 510275, People's Republic of China
| | - Zhuowei Wang
- Center for Water Resources and Environment, School of Geographic Science and Planning, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou, 510275, People's Republic of China
| | - Shaoheng Li
- Center for Water Resources and Environment, School of Geographic Science and Planning, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou, 510275, People's Republic of China
| | - Jiju Shan
- Center for Water Resources and Environment, School of Geographic Science and Planning, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou, 510275, People's Republic of China
| | - Yuemin Long
- Center for Water Resources and Environment, School of Geographic Science and Planning, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou, 510275, People's Republic of China
| | - Chang Yan
- Center for Water Resources and Environment, School of Geographic Science and Planning, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou, 510275, People's Republic of China
| | - Kai Zhang
- Center for Water Resources and Environment, School of Geographic Science and Planning, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou, 510275, People's Republic of China
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