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Xie R, Xing Q, Gao J, Wang X, Xu W, Lv Z, Yi W, Zhao J, Luo Z, Wu X, Liu H. Investigation on the effect of ship emissions on the air quality: A case study in Hainan Island, China. J Environ Sci (China) 2025; 156:114-125. [PMID: 40412918 DOI: 10.1016/j.jes.2024.08.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 08/08/2024] [Accepted: 08/08/2024] [Indexed: 05/27/2025]
Abstract
This paper presents an air quality simulation model that incorporates shipping activities and weather conditions, with a case study of Hainan Island to examine the impact of ship emissions on air quality. The findings reveal that the density of automatic identification system (AIS) signals is particularly high in the southern coastal regions. The results showed that the annual ship emissions recorded the highest density of 896.7 tons/0.01°, 49.8 tons/0.01°, 1139.7 tons/0.01°, and 122,000 tons/0.01° for sulfur oxides (SOx), particulate matter (PM), nitrogen oxides (NOx), and carbon dioxide (CO2), respectively. Furthermore, the partial distributions of these emissions were not significantly affected by the seasons. Ships within twelve nautical miles of Hainan coastlines emit approximately 2817.7 tons of SOx, 14,686.4 tons of NOx, 630.4 tons of PM2.5, and 416.9 tons of hydrocarbons (HC) annually. These emissions are primarily concentrated in the sea areas surrounding the ports of Haikou, Yangpu, Basuo, and Sanya. Ships manufactured between 2000 and 2010 have contributed significantly to air pollution, with SOx and HC emissions accounting for approximately 51 % and 56 % of total emissions, respectively. However, for ships manufactured after 2016, these proportions have dropped to approximately 10 %. In terms of air pollutants from ship emissions in Hainan Island, the spatial distribution of their contributions is significantly uneven. The impact of PM2.5 differs significantly depending on the season, with the concentrations being substantially higher during Spring. However, the proportions of O3 and other pollutants do not vary significantly, except during Spring.
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Affiliation(s)
- Rongfu Xie
- School of Ecology, Hainan University, Haikou 570228, China; Hainan Research Academy of Environmental Sciences, Haikou 571126, China
| | - Qiao Xing
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China
| | - Jianbing Gao
- School of Mechanical Engineering, Beijing Institute of Technology, Beijing 10081, China
| | - Xiaochen Wang
- Shaanxi Key Laboratory of New Transportation Energy and Automotive Energy Saving, School of Energy and Electrical Engineering, Chang'an University, Xi'an 710064, China
| | - Wenshuai Xu
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China
| | - Zhaofeng Lv
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Wen Yi
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Junchao Zhao
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Zhenyu Luo
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Xiaochen Wu
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China.
| | - Huan Liu
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China.
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Liu J, Wang S, Zhang Y, Yan Y, Zhu J, Zhang S, Wang T, Tan Y, Zhou B. Investigation of formaldehyde sources and its relative emission intensity in shipping channel environment. J Environ Sci (China) 2024; 142:142-154. [PMID: 38527880 DOI: 10.1016/j.jes.2023.06.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 06/12/2023] [Accepted: 06/13/2023] [Indexed: 03/27/2024]
Abstract
Formaldehyde (HCHO) is considered one of the most abundant gas-phase carbonyl compounds in the atmosphere, which can be directly emitted through transportation sources. Long-Path Differential Optical Absorption Spectroscopy (LP-DOAS) was used to observe HCHO in the river channel of Wusong Wharf in Shanghai, China for the whole year of 2019. Due to the impact of ship activity, the annual average HCHO level in the channel is about 2.5 times higher than that in the nearby campus environment. To explain the sources of HCHO under different meteorological conditions, the tracer-pair of CO and Ox (NO2+O3) was used on the clustered air masses. The results of the source appointment show that primary, secondary and background account for 24.14% (3.34 ± 1.19 ppbv), 44.78% (6.20 ± 2.04 ppbv) and 31.09% (4.31 ± 2.33 ppbv) of the HCHO in the channel when the air masses were from the mixed direction of the city and channel, respectively. By performing background station subtraction at times of high primary HCHO values and resolving the plume peaks, directly emitted HCHO/NO2 in the channel environment and plume were determined to be mainly distributed between 0.2 and 0.3. General cargo ships with higher sailing speeds or main engine powers tend to have higher HCHO/NO2 levels. With the knowledge of NO2 (or NOx) emission levels from ships, this study may provide data support for the establishment of HCHO emission factors.
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Affiliation(s)
- Jiaqi Liu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Shanshan Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China; Institute of Eco-Chongming (IEC), No. 20 Cuiniao Road, Shanghai 202162, China.
| | - Yan Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China; Institute of Eco-Chongming (IEC), No. 20 Cuiniao Road, Shanghai 202162, China; National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Fudan University, Shanghai 200438, China; Institute of Digitalized Sustainable Transformation, Big Data Institute, Fudan University, Shanghai 200433, China
| | - Yuhao Yan
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Jian Zhu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Sanbao Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Tianyu Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Yibing Tan
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Bin Zhou
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China; Institute of Eco-Chongming (IEC), No. 20 Cuiniao Road, Shanghai 202162, China; Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China.
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Huang ZY, Yuan CS, Yen PH, Tu IC, Tseng YL. Temporal variations and chemical characteristics of marine PM 2.5 at Dongsha Islands, South China Sea: Three-year measurement. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 356:124378. [PMID: 38885829 DOI: 10.1016/j.envpol.2024.124378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 06/12/2024] [Accepted: 06/14/2024] [Indexed: 06/20/2024]
Abstract
The study of long-range transport effects on marine fine particles (PM2.5), particularly in remote sites such as the Dongsha Islands, is pivotal for advancing our understanding of air pollution dynamics on a regional scale and for formulating effective environmental policies. PM2.5 concentrations were examined over three consecutive years and grouped based on their transport routes. The backward trajectory simulation revealed that high PM2.5 concentrations were observed in the West Channel, originating from North and Central China, the Korean Peninsula, and the Japanese Islands, opposed to the East Channel. High PM2.5 concentrations, commonly observed in winter and spring, were mainly attributed to the Asian Northeastern Monsoons. Water-soluble inorganic ions constituted the major components, accounting for 37.8-48.7% of PM2.5, and followed by metal elements (15.5-20.0%), carbons (7.5-13.3%), levoglucosan (0.01-0.17%), and organic aerosols (0.2-2.2%). Secondary inorganic aerosols as the dominant source accounted for 8.3-24.7% of PM2.5, while sea salts were the secondary major contributor. High levoglucosan contribution (3.8-7.2%) in winter and spring was attributed to biomass burning, mainly from the Indochina Peninsula. Chemical mass balance receptor modeling resolved that major sources of PM2.5 were secondary sulfate, sea salts, fugitive dust, and industrial boilers. This study concluded that the long-range transport of PM2.5 gradually increased since fall, contributing 52.1-74.3%, highlighting its substantial impact on PM2.5 in all seasons except summer.
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Affiliation(s)
- Zi-You Huang
- Institute of Environmental Engineering, National Sun Yat-sen University, 70, Lian-Hai Road, Kaohsiung, 804, Taiwan
| | - Chung-Shin Yuan
- Institute of Environmental Engineering, National Sun Yat-sen University, 70, Lian-Hai Road, Kaohsiung, 804, Taiwan; Aerosol Science Research Center, National Sun Yat-sen University, 70, Lian-Hai Road, Kaohsiung, 804, Taiwan.
| | - Po-Hsuan Yen
- Institute of Environmental Engineering, National Sun Yat-sen University, 70, Lian-Hai Road, Kaohsiung, 804, Taiwan
| | - I-Chieh Tu
- Institute of Environmental Engineering, National Sun Yat-sen University, 70, Lian-Hai Road, Kaohsiung, 804, Taiwan
| | - Yu-Lun Tseng
- Institute of Environmental Engineering, National Sun Yat-sen University, 70, Lian-Hai Road, Kaohsiung, 804, Taiwan
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Zhang Y, Li W, Li L, Li M, Zhou Z, Yu J, Zhou Y. Source apportionment of PM 2.5 using PMF combined online bulk and single-particle measurements: Contribution of fireworks and biomass burning. J Environ Sci (China) 2024; 136:325-336. [PMID: 37923442 DOI: 10.1016/j.jes.2022.12.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 11/21/2022] [Accepted: 12/12/2022] [Indexed: 11/07/2023]
Abstract
Fireworks (FW) could significantly worsen air quality in short term during celebrations. Due to similar tracers with biomass burning (BB), the fast and precise qualification of FW and BB is still challenging. In this study, online bulk and single-particle measurements were combined to investigate the contributions of FW and BB to the overall mass concentrations of PM2.5 and specific chemical species by positive matrix factorization (PMF) during the Chinese New Year in Hong Kong in February 2013. With combined information, fresh/aged FW (abundant 140K2NO3+ and 213K3SO4+ formed from 113K2Cl+ discharged by fresh FW) can be extracted from the fresh/aged BB sources, in addition to the Second Aerosol, Vehicles + Road Dust, and Sea Salt factors. The contributions of FW and BB were investigated during three high particle matter episodes influenced by the pollution transported from the Pearl River Delta region. The fresh BB/FW contributed 39.2% and 19.6% to PM2.5 during the Lunar Chinese New Year case. However, the contributions of aged FW/BB enhanced in the last two episodes due to the aging process, evidenced by high contributions from secondary aerosols. Generally, the fresh BB/FW showed more significant contributions to nitrate (35.1% and 15.0%, respectively) compared with sulfate (25.1% and 5.9%, respectively) and OC (14.8% and 11.1%, respectively) on average. In comparison, the aged FW contributed more to sulfate (13.4%). Overall, combining online bulk and single-particle measurement data can combine both instruments' advantages and provide a new perspective for applying source apportionment of aerosols using PMF.
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Affiliation(s)
- Yanjing Zhang
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong 266100, China
| | - Wenshuai Li
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong 266100, China
| | - Lei Li
- Institute of Atmospheric Environment Safety and Pollution Control, Jinan University, Guangdong 510632, China
| | - Mei Li
- Institute of Atmospheric Environment Safety and Pollution Control, Jinan University, Guangdong 510632, China
| | - Zhen Zhou
- Institute of Atmospheric Environment Safety and Pollution Control, Jinan University, Guangdong 510632, China
| | - Jianzhen Yu
- Institute of Environment, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China; Department of Chemistry, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China; Division of Environment, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Yang Zhou
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong 266100, China.
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Zhang X, Sun M, Aikawa M. Characteristics of PM 2.5-bound metals in Japan over six years: Spatial distribution, health risk, and source analysis. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 344:118750. [PMID: 37573701 DOI: 10.1016/j.jenvman.2023.118750] [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: 05/10/2023] [Revised: 07/12/2023] [Accepted: 08/09/2023] [Indexed: 08/15/2023]
Abstract
Air sampling campaigns were conducted at 100 survey sites across Japan from April 2014 to February 2020, and a comprehensive database of atmospheric particles was obtained. In this study, the characteristics of PM2.5 and 26 metals were investigated in depth. Spatially, the concentration of PM2.5 gradually increased from the northeast to the southwest of Japan. The pollution in Kitakyushu City was the most serious, reaching 19.8 μg m-3. As an important particle component, metals did not show obviously spatial variation in Japan, with a sum concentration of 0.4 μg m-3. Anthropogenic metals only accounted for about 8% of the total metals, but they could pose a serious threat to public health. For children, the non-carcinogenic risk and carcinogenic risk due to exposure to anthropogenic metals could not be neglected in Japan; the corresponding HI and CR values at 100 survey sites ranged from 2.7 to 15.0 and 4.1 × 10-5 to 3.4 × 10-4, respectively. Adults faced lower health risks than children, with HI values ranging from 0.2 to 2.0 and CR values ranging from 2.0 × 10-5 to 1.6 × 10-4. The integrated health risk assessment results showed that the coastal region of the Seto Inland Sea and the north Tohoku Region were the most heavily polluted areas of Japan; in this study, 20 survey sites were finally determined to be high-risk sites, among which pollution control for Niihama City, Kitakyushu City, Hachinohe City, and Shimonoseki City were of first priority. With further combination with a positive matrix factorization model, it can be known that these four cities mainly had five to seven metal sources, and their heavy pollution was mainly caused by ship emissions, industrial emissions, biomass burning, and coal combustion. Overall, our study comprehensively revealed the regional patterns of PM2.5-bound metal pollution across Japan, which can help in making cost-effective risk management policies with limited national/local budgets.
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Affiliation(s)
- Xi Zhang
- Faculty of Environmental Engineering, The University of Kitakyushu, 1-1, Hibikino, Wakamatsu, Kitakyushu, Fukuoka, 808-0135, Japan.
| | - Meng Sun
- Faculty of Environmental Engineering, The University of Kitakyushu, 1-1, Hibikino, Wakamatsu, Kitakyushu, Fukuoka, 808-0135, Japan
| | - Masahide Aikawa
- Faculty of Environmental Engineering, The University of Kitakyushu, 1-1, Hibikino, Wakamatsu, Kitakyushu, Fukuoka, 808-0135, Japan.
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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, Aikawa M. The variation of PM 2.5 from ship emission under low-sulfur regulation: A case study in the coastal suburbs of Kitakyushu, Japan. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159968. [PMID: 36347285 DOI: 10.1016/j.scitotenv.2022.159968] [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: 08/13/2022] [Revised: 10/27/2022] [Accepted: 11/01/2022] [Indexed: 06/16/2023]
Abstract
From January 1, 2020, the International Maritime Organization (IMO) regulation about the limit of fuel sulfur content to 0.5 % become effective, and ships commonly install sulfur scrubbers or use low-sulfur fuel or liquefied natural gas to replace sulfur-rich heavy fuel oil. In this study, the 4-year PM2.5 sampling in the coastal suburbs of Kitakyushu, Japan clearly indicated the significant effects of relevant regulation and countermeasures on particle emissions in this receptor site. From the perspective of air quality, an obvious decrease in the mass concentration of ship-emitted particles was observed in 2020, and the contribution of sulfate could reach 60 %. The ammonium concentration was mainly controlled by sulfate and nitrate, and its reduction also could not be ignored, accounting for about 17 %. In terms of public health, the particle exposure risk also changed greatly, mainly due to the reduction of risk levels for As, W, Sb, V, Ni, and Cd; the lowest non-carcinogenic risk and carcinogenic risk for both adults (HI = 1.2 and CR = 5.7 × 10-5) and children (HI = 9.9 and CR = 1.1 × 10-4) all occurred in 2020. However, these reduced health risks were still not within the safe level (except for the carcinogenic risk for adults), a fact that requires continued attention. This result exposed the deficiency of current countermeasures regarding the IMO's fuel sulfur content limit in Kitakyushu City, and increasing the proportion of ships using clean fuels (liquefied natural gas, methanol, etc.) would surely alleviate the particle pollution caused by ship emissions.
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Affiliation(s)
- Xi Zhang
- Faculty of Environmental Engineering, The University of Kitakyushu, 1-1, Hibikino, Wakamatsu, Kitakyushu, Fukuoka 808-0135, Japan
| | - Masahide Aikawa
- Faculty of Environmental Engineering, The University of Kitakyushu, 1-1, Hibikino, Wakamatsu, Kitakyushu, Fukuoka 808-0135, Japan.
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Mani SA, Peltier RE, Le Mestre M, Gunkel-Grillon P, Shah S, Mani FS. Black carbon and elemental characterization of PM 2.5 in dense traffic areas in two cities in Fiji, a Small Island Developing State. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 845:157136. [PMID: 35798099 DOI: 10.1016/j.scitotenv.2022.157136] [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: 04/04/2022] [Revised: 06/06/2022] [Accepted: 06/29/2022] [Indexed: 06/15/2023]
Abstract
PM2.5 characterizations are essential in understanding its impact on the health of the exposed population. Sampled PM2.5 by Mani et al. (2020) was characterized to determine atmospheric metal concentration and inhalation health risk in Suva and Lautoka Cities, the only two cities in Fiji and one of the largest in the South Pacific Islands. Twenty-two elements (Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Mo, Na, Ni, P, Pb, S, Si, Sr, V, Zn) were analyzed using ICP-OES. Black Carbon (BC) sampling was also done at three different sites in Suva City, namely, Fiji National University Samabula Intersection site, Suva City Bus Station site and the Reservoir Road Community Settlement Site as well as at Lautoka City Bus Station. Mean BC concentrations over the sampling period were found to be 3.9 ± 2.9 (median = 3.3 μg/m3), 2.6 ± 2.7 μg/m3 (median = 1.7 μg/m3), 2.4 ± 2.3 μg/m3 (median = 1.7 μg/m3) and 4.0 ± 4.7 μg/m3 (median = 2.4 μg/m3) respectively. Health risk assessments (Carcinogenic Risk (CR) and Non-Carcinogenic Risk (HQ)) were also done to assess the risk of inhalation exposure in adults and children. The Hazard Index for children in Lautoka (HI = 1.03) was found to slightly exceed the safe level of 1. This study provides the first inventory of atmospheric particulate bound metal concentrations and diurnal BC profiles in Fiji and informs policy makers and scientists for further studies.
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Affiliation(s)
- S A Mani
- School of Agriculture, Geography, Environment, Ocean and Natural Sciences, University of the South Pacific, Suva, Fiji.
| | - R E Peltier
- Department of Environmental Health Science, University of Massachusetts Amherst, USA.
| | - M Le Mestre
- Institute of Pure and Applied Sciences, University of New Caledonia, New Caledonia.
| | - P Gunkel-Grillon
- Institute of Pure and Applied Sciences, University of New Caledonia, New Caledonia.
| | - S Shah
- Department of Chemistry, Fiji National University, Fiji.
| | - F S Mani
- School of Agriculture, Geography, Environment, Ocean and Natural Sciences, University of the South Pacific, Suva, Fiji.
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Lin Q, Dai W, Chen JQ, Jin Y, Yang Y, Wang YY, Zhang BF, Fan JM, Lou LP, Shen ZG, Shen CF, Mao JD. Airborne lead: A vital factor influencing rice lead accumulation in China. JOURNAL OF HAZARDOUS MATERIALS 2022; 427:128169. [PMID: 34979386 DOI: 10.1016/j.jhazmat.2021.128169] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 12/05/2021] [Accepted: 12/27/2021] [Indexed: 06/14/2023]
Abstract
Traditionally, lead (Pb) in rice grains has been thought to be mostly derived from soil, and the contribution of aerosol Pb remains so far unknown. Based on a meta-analysis, we surprisingly found rice Pb content decreased proportionally with urban atmospheric Pb concentrations in major rice-growing provinces in China during 2001-2015, suggestive of the strong influence of long-range Pb transport on agricultural environment. With the combination of field survey, field experiment, as well as a predictive model, we confirmed high contribution of atmospheric exposure to rice grain Pb in China. We for the first time developed a predictive mathematical model which revealed that aerosol Pb accumulation ratios of rice grains were related to both grain weight and accumulation types. We successfully predicted the national-scale rice Pb in China on the basis of the public data of urban PM2.5 from 19 rice-growing provinces and proposed a seasonal atmospheric Pb limit of 0.20 µg m-3 based on the safe threshold level of Pb in rice, which was much lower than the current limit of 1 µg m-3 set in China.
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Affiliation(s)
- Qi Lin
- Department of Environmental Engineering, Zhejiang University, Key Laboratory of Water Pollution Control and Environmental Safety of Zhejiang Province, Hangzhou, Zhejiang Province 310058, PR China.
| | - Wei Dai
- Department of Environmental Engineering, Zhejiang University, Key Laboratory of Water Pollution Control and Environmental Safety of Zhejiang Province, Hangzhou, Zhejiang Province 310058, PR China
| | - Jun-Qiao Chen
- Department of Environmental Engineering, Zhejiang University, Key Laboratory of Water Pollution Control and Environmental Safety of Zhejiang Province, Hangzhou, Zhejiang Province 310058, PR China
| | - Yu Jin
- Department of Environmental Engineering, Zhejiang University, Key Laboratory of Water Pollution Control and Environmental Safety of Zhejiang Province, Hangzhou, Zhejiang Province 310058, PR China
| | - Yue Yang
- Department of Environmental Engineering, Zhejiang University, Key Laboratory of Water Pollution Control and Environmental Safety of Zhejiang Province, Hangzhou, Zhejiang Province 310058, PR China
| | - Yi-Yi Wang
- Hangzhou Environmental Monitoring Central Station, Hangzhou, Zhejiang Province 310007, PR China
| | - Bao-Feng Zhang
- Hangzhou Environmental Monitoring Central Station, Hangzhou, Zhejiang Province 310007, PR China
| | - Jia-Ming Fan
- Department of Environmental Engineering, Zhejiang University, Key Laboratory of Water Pollution Control and Environmental Safety of Zhejiang Province, Hangzhou, Zhejiang Province 310058, PR China
| | - Li-Ping Lou
- Department of Environmental Engineering, Zhejiang University, Key Laboratory of Water Pollution Control and Environmental Safety of Zhejiang Province, Hangzhou, Zhejiang Province 310058, PR China
| | - Zhen-Guo Shen
- College of Life Sciences, Nanjing Agricultural University, Nanjing, Jiangsu Province 210095, PR China
| | - Chao-Feng Shen
- Department of Environmental Engineering, Zhejiang University, Key Laboratory of Water Pollution Control and Environmental Safety of Zhejiang Province, Hangzhou, Zhejiang Province 310058, PR China
| | - Jing-Dong Mao
- Department of Chemistry and Biochemistry, Old Dominion University, 4541 Hampton Boulevard, Norfolk, VA 23529, United States
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10
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Zhang X, Eto Y, Aikawa M. Risk assessment and management of PM 2.5-bound heavy metals in the urban area of Kitakyushu, Japan. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 795:148748. [PMID: 34328942 DOI: 10.1016/j.scitotenv.2021.148748] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 06/24/2021] [Accepted: 06/25/2021] [Indexed: 06/13/2023]
Abstract
The sampling campaign of PM2.5 was carried out in Kitakyushu City on the western edge of Japan from 2013 to 2019, and 29 heavy metals loaded in PM2.5 were measured in this study. During the whole sampling period, the PM2.5 mass concentration ranged from 6.3 μg·m-3 to 57.5 μg·m-3, with a median value of 21.3 μg·m-3, and the sum concentration of heavy metals only accounted for 3%. According to the enrichment factor (EF) and geo-accumulation index (Igeo) analysis, it can be known that Se, Mo, Pb, As, Zn, W, Sb, Cu, V, Cr, Ni, and Cs were mainly from anthropogenic sources, which had EF values larger than 10 and Igeo values larger than 0. The comprehensive ecological risk index for these 12 anthropogenic metals was far greater than 600. This large index showed severe metal pollution and very high ecological risk in the urban area of Kitakyushu, Japan, which should be paid great attention. The human health assessment result further revealed that children living at the sampling site faced severe non-carcinogenic risk (HI = 7.8) and moderate carcinogenic risk (CR = 1.2 × 10-4), and oral ingestion was basically the most important exposure pathway, followed by dermal contact and inhalation. The priority control metals included Mo, Se, As, Pb, Sb, and Cr; moreover, the concentration-weighted trajectory analysis (CWT) indicated that Mo, Sb, and Cr were from ship emissions because some shipping routes around the Kyushu area were identified as their potential pollution source regions, while Se, As, and Pb were carried by the air masses from the Asian landmass. Overall, although the PM2.5 concentration in the urban area of Kitakyushu, Japan was not high, the heavy metal risk cannot be overlooked; it is necessary to strengthen the source control of high-risk metals and raise public protection awareness.
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Affiliation(s)
- Xi Zhang
- Faculty of Environmental Engineering, The University of Kitakyushu, 1-1, Hibikino, Wakamatsu, Kitakyushu, Fukuoka 808-0135, Japan
| | - Yuko Eto
- Institute of Health and Environmental Sciences, City of Kitakyushu, 1-2-1 Shin-ike, Tobata-ku, Kitakyushu, Fukuoka 804-0082, Japan
| | - Masahide Aikawa
- Faculty of Environmental Engineering, The University of Kitakyushu, 1-1, Hibikino, Wakamatsu, Kitakyushu, Fukuoka 808-0135, Japan.
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11
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Lin L, Li T, Sun M, Liang Q, Ma Y, Wang F, Duan J, Sun Z. Effect of particulate matter exposure on the prevalence of allergic rhinitis in children: A systematic review and meta-analysis. CHEMOSPHERE 2021; 268:128841. [PMID: 33172665 DOI: 10.1016/j.chemosphere.2020.128841] [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: 05/16/2020] [Revised: 10/08/2020] [Accepted: 10/29/2020] [Indexed: 05/22/2023]
Abstract
Among various air pollutants, particulate matter (PM) is the most harmful and representative pollutant. At the same time, allergic rhinitis (AR) is getting more and more attention, so we explore the relationship between PM and the prevalence of AR among children. Then, PubMed, Web of Science, Google Scholar was used to search for relevant studies up to January 2020. Literature quality assessment was processed using the Newcastle-Ottawa Scale (NOS) evaluation scale. Adjusted odds ratio (OR) with corresponding 95% confidence interval (CI) was retrieved from individual studies and pooled to generate a summary effect via STATA software. Besides, we test the result stability by Egger's test and funnel plot, and using the trim-and-fill method to modify the possible asymmetric funnel graph. 21 studies were included in the meta-analysis. 9 articles reported about PM2.5 on childhood AR (1.09, 95%CI: 1.01, 1.17, per 10 μg/m3 increase). 15 articles reported about PM10 on childhood AR (1.06, 95%CI: 1.02,1.11, per 10 μg/m3 increase), PM2.5 exposure has a bigger effect on children AR than PM10. In addition, a series of subgroup analysis was performed, and we found that PM2.5 and PM10 have different performances in different subgroups. In addition to this, we analyzed the sources of heterogeneity of the study. Apart from the results we got all have good stability without publication bias. Therefore, it can be concluded that exposure to PM may increase the prevalence of AR among children.
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Affiliation(s)
- Lisen Lin
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China
| | - Tianyu Li
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China
| | - Mengqi Sun
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China
| | - Qingqing Liang
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China
| | - Yuexiao Ma
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China
| | - Fenghong Wang
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China
| | - Junchao Duan
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China.
| | - Zhiwei Sun
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China.
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12
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Wang F, Yu H, Wang Z, Liang W, Shi G, Gao J, Li M, Feng Y. Review of online source apportionment research based on observation for ambient particulate matter. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 762:144095. [PMID: 33360453 DOI: 10.1016/j.scitotenv.2020.144095] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 11/13/2020] [Accepted: 11/20/2020] [Indexed: 06/12/2023]
Abstract
Particulate matter source apportionment (SA) is the basis and premise for preventing and controlling haze pollution scientifically and effectively. Traditional offline SA methods lack the capability of handling the rapid changing pollution sources during heavy air pollution periods. With the development of multiple online observation techniques, online SA of particulate matter can now be realized with high temporal resolution, stable and reliable continuous observation data on particle compositions. Here, we start with a summary of online measuring instruments for monitoring particulate matters that contains both online mass concentration (online MC) measurement, and online mass spectrometric (online MS) techniques. The former technique collects ambient particulate matter onto filter membrane and measures the concentrations of chemical components in the particulate matter subsequently. The latter technique could be further divided into two categories: bulk measurement and single particle measurement. Aerosol Mass Spectrometers (AMS) could provide mass spectral information of chemical components of non-refractory aerosols, especially organic aerosols. While the emergence of single-particle aerosol mass spectrometer (SPAMS) technology can provide large number of high time resolution data for online source resolution. This is closely followed by an overview of the methods and results of SA. However, online instruments are still facing challenges, such as abnormal or missing measurements, that could impact the accuracy of online dataset. Machine leaning algorithm are suited for processing the large amount of online observation data, which could be further considered. In addition, the key research challenges and future directions are presented including the integration of online dataset from different online instruments, the ensemble-trained source apportionment approach, and the quantification of source-category-specific human health risk based on online instrumentation and SA methods.
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Affiliation(s)
- Feng Wang
- 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
| | - Haofei Yu
- Department of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL, USA
| | - Zhenyu Wang
- 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
| | - Weiqing Liang
- 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
| | - Guoliang Shi
- 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.
| | - Jian Gao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 10084, China.
| | - Mei Li
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line 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.
| | - 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
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13
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Zhang H, Zhang L, Yang L, Zhou Q, Zhang X, Xing W, Hayakawa K, Toriba A, Tang N. Impact of COVID-19 Outbreak on the Long-Range Transport of Common Air Pollutants in KUWAMS. Chem Pharm Bull (Tokyo) 2021; 69:237-245. [DOI: 10.1248/cpb.c20-00692] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
- Hao Zhang
- Graduate School of Medical Sciences, Kanazawa University
| | - Lulu Zhang
- Graduate School of Medical Sciences, Kanazawa University
| | - Lu Yang
- Graduate School of Medical Sciences, Kanazawa University
| | - Quanyu Zhou
- Graduate School of Medical Sciences, Kanazawa University
| | - Xuan Zhang
- Graduate School of Medical Sciences, Kanazawa University
| | - Wanli Xing
- Graduate School of Medical Sciences, Kanazawa University
| | - Kazuichi Hayakawa
- Institute of Nature and Environmental Technology, Kanazawa University
| | - Akira Toriba
- Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University
| | - Ning Tang
- Institute of Nature and Environmental Technology, Kanazawa University
- Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University
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14
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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: 3.0] [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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15
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Jiang J, Aksoyoglu S, Ciarelli G, Baltensperger U, Prévôt ASH. Changes in ozone and PM 2.5 in Europe during the period of 1990-2030: Role of reductions in land and ship emissions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 741:140467. [PMID: 32886963 DOI: 10.1016/j.scitotenv.2020.140467] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 06/21/2020] [Accepted: 06/22/2020] [Indexed: 06/11/2023]
Abstract
Air pollution is among the top threats to human health and ecosystems despite the substantial decrease in anthropogenic emissions. Meanwhile, the role of ship emissions on air quality is becoming increasingly important with the growing maritime transport and less strict regulations. In this study, we modeled the air quality in Europe between 1990 and 2030 with ten-year intervals, using the regional air quality model CAMx version 6.50, to investigate the changes in the past (1990-2010) as well as the effects of different land and ship emission scenarios in the future (2020,2030). The modeled mean ozone levels decreased slightly during the first decade but then started increasing again especially in polluted areas. Results from the future scenarios suggest that by 2030 the peak ozone would decrease, leading to a decrease in the days exceeding the maximum daily 8-h average ozone (MDA8) limit values (60 ppb) by 51% in southern Europe relative to 1990. The model results show a decrease of 56% (6.3 μg m-3) in PM2.5 concentrations from 1990 to 2030 under current legislation, mostly due to a large drop in sulfate (representing up to 44% of the total PM2.5 decrease during 1990-2000) while nitrate concentrations were predicted to go down with an increasing rate (10% of total PM2.5 decrease during 1990-2000 while 36% during 2020-2030). The ship emissions if reduced according to the maximum technically feasible reduction (MTFR) scenario were predicted to contribute up to 19% of the decrease in the PM2.5 concentrations over land between 2010 and 2030. Ship emission reductions according to the MTFR scenario would lead to a decrease in the days with MDA8 exceeding EU limits by 24-28% (10-14 days) around the coastal regions. The results obtained in our study show the increasing importance of ship emission reductions, after a relatively large decrease in land emissions was achieved in Europe.
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Affiliation(s)
- Jianhui Jiang
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland.
| | - Sebnem Aksoyoglu
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland.
| | - Giancarlo Ciarelli
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA; Now at: Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Urs Baltensperger
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland
| | - André S H Prévôt
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland
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