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Liu Y, Xu X, Ji D, He J, Wang Y. Examining trends and variability of PM 2.5-associated organic and elemental carbon in the megacity of Beijing, China: Insight from decadal continuous in-situ hourly observations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 938:173331. [PMID: 38777070 DOI: 10.1016/j.scitotenv.2024.173331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Revised: 04/24/2024] [Accepted: 05/15/2024] [Indexed: 05/25/2024]
Abstract
Organic carbon (OC) and elemental carbon (EC) in fine particulate matter (PM2.5) play pivotal roles in impacting human health, air quality, and climate change dynamics. Long-term monitoring datasets of OC and EC in PM2.5 are indispensable for comprehending their temporal variations, spatial distribution, evolutionary patterns, and trends, as well as for assessing the effectiveness of clean air action plans. This study presents and scrutinizes a comprehensive 10-year hourly dataset of PM2.5-bound OC and EC in the megacity of Beijing, China, spanning from 2013 to 2022. Throughout the entire study period, the average concentrations of OC and EC were recorded at 8.8 ± 8.7 and 2.5 ± 3.0 μg/m3, respectively. Employing the seasonal and trend decomposition methodology, specifically the locally estimated scatter plot smoothing method combined with generalized least squares with the autoregressive moving average method, the study observed a significant decline in OC and EC concentrations, reducing by 5.8 % yr-1 and 9.9 % yr-1 at rates of 0.8 and 0.4 μg/m3 yr-1, respectively. These declining trends were consistently verified using Theil-Sen method. Notably, the winter months exhibited the most substantial declining trends, with rates of 9.3 % yr-1 for OC and 10.9 % yr-1 for EC, aligning with the positive impact of the implemented clean air action plan. Weekend spikes in OC and EC levels were attributed to factors such as traffic regulations and residential emissions. Diurnal variations showcased higher concentrations during nighttime and lower levels during daytime. Although meteorological factors demonstrated an overall positive impact with average reduction in OC and EC concentrations by 8.3 % and 8.7 %, clean air action plans including the Air Pollution Prevention and Control Action Plan (2013-2017) and the Three-Year Action Plan to Win the Blue Sky War (2018-2020) have more contributions in reducing the OC and EC concentrations with mass drop rates of 87.1 % and 89.2 % and 76.7 % and 96.7 %, respectively. Utilizing the non-parametric wind regression method, significant concentration hotspots were identified at wind speeds of ≤2 m/s, with diffuse signals recorded in the southwestern wind sectors at wind speeds of approximately 4-5 m/s. Interannual disparities in potential source regions of OC and EC were evident, with high potential source areas observed in the southern and northwestern provinces of Beijing from 2013 to 2018. In contrast, during 2019-2022, potential source areas with relatively high values of potential source contribution function were predominantly situated in the southern regions of Beijing. This analysis, grounded in observational data, provides insights into the decadal changes in the major atmospheric composition of PM2.5 and facilitates the evaluation of the efficacy of control policies, particularly relevant for developing countries.
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Affiliation(s)
- Yu Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Xiaojuan Xu
- University of Chinese Academy of Sciences, Beijing 100049, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Dongsheng Ji
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China.
| | - Jun He
- Department of Chemical and Environmental Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, Ningbo 315100, China
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
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Liu Q, Liu Y, Yang Z, Qi X, Schauer JJ. High loadings of carbonaceous aerosols from wood smoke in the atmosphere of Beijing from 2015 to 2017: Implications for energy transition policy. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 344:123240. [PMID: 38154780 DOI: 10.1016/j.envpol.2023.123240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 12/09/2023] [Accepted: 12/25/2023] [Indexed: 12/30/2023]
Abstract
Recently, biomass has been regarded as a promising option for solid energy in China, which is promoted in the residential sector and firing power plants. We collected 200 PM2.5 samples (particulate matter with a aerodynamic diameter smaller than 2.5 μm) at multi-sites across Beijing from three individual sampling cases from 2015 to 2017. The levels of OC, OC fractions, EC, EC fractions, as well as K+ were measured. Then, we adopted the Positive Matrix Factorization 5.0 to apportion the sources of carbonaceous aerosols. The source apportionment results were compared with the estimates of source contribution using the bottom-up technical method with the latest emission inventories after the Action Plan was put into effect in 2013. Our results demonstrate that high pollution of carbonaceous aerosols originated from wood smoking based on the receptor modeling and bottom-up technical method in Beijing from 2015 to 2017. Future energy transition policy should focus on the technologies and regulations for reducing emissions from renewable biomass fuel combustion. This study highlights the importance of regulations that address emissions controls on fuels replacing coal combustion to meet the needs to mitigate air pollution from primary energy use.
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Affiliation(s)
- Qingyang Liu
- Institute of Analysis and Testing, Beijing Academy of Science and Technology (Beijing Center for Physical and Chemical Analysis), Beijing, 100089, China; College of Biology and the Environment, Nanjing Forestry University, Nanjing, 210037, China
| | - Yanju Liu
- Institute of Analysis and Testing, Beijing Academy of Science and Technology (Beijing Center for Physical and Chemical Analysis), Beijing, 100089, China; Beijing Milu Ecological Research Center, Beijing, 100074, China.
| | - Zheng Yang
- Beijing Milu Ecological Research Center, Beijing, 100074, China
| | - Xuekui Qi
- Institute of Analysis and Testing, Beijing Academy of Science and Technology (Beijing Center for Physical and Chemical Analysis), Beijing, 100089, China
| | - James J Schauer
- Environmental Chemistry and Technology Program, University of Wisconsin-Madison, Madison, WI, 53706, USA
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Ding S, Liu D, Zhao D, Tian P, Huang M, Ding D. Characteristics of atmospheric black carbon and its wet scavenging in Nanning, South China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166747. [PMID: 37659526 DOI: 10.1016/j.scitotenv.2023.166747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Revised: 08/16/2023] [Accepted: 08/30/2023] [Indexed: 09/04/2023]
Abstract
Based on in-situ measurement of black carbon (BC) and carbon monoxide (CO), the characteristics of BC emissions and wet scavenging were comprehensively investigated in Nanning, South China. The average annual BC concentration was 1.02 ± 0.53 μg m-3 with higher pollution levels during winter. In winter, a higher net BC/CO (ΔBC/ΔCO) ratio of 3.3 ± 0.3 ng m-3 ppb-1 along with an increased absorption Ångström exponent (AAE) and BC mass from biomass burning (BCbb), indicated a significant contribution of biomass burning to BC emissions. However, emissions from the traffic sector consistently exerted a dominant influence throughout the year. Cluster analysis of backward trajectories identified three types of air masses with distinct origins. Cluster #1 originated from Guangxi province and its vicinity, intermittently influencing the sampling site throughout the year with varying effects between winter and summer. This air mass brought in clean sea breeze in summer whereas transported a higher proportion of BCbb to the site during wintertime due to local open biomass burning. Cluster #3 primarily arrived in autumn and winter (October-December) from polluted central China, resulting in substantially high BC mass at the site. Cluster #2 coincided with the period (January-March) when extensive surface open biomass burning events occurred in Southeast Asia (SEA) regions. These BC aerosols in cluster#2 initially rose to higher altitudes above SEA before being regionally transported, but were significantly scavenged by clouds and precipitation during vertical uplift. The remaining BC exhibited a notably lower BC loss rate on relative humidity (RH) of -0.01 ng m-3 ppb-1 %-1 compared to cluster #1 (-0.03) and cluster #3 (-0.06), corresponding to an average BC transport efficiency of 0.85, 0.73, and 0.53, respectively. Nonetheless, air masses in cluster #2 could still transport considerably high BC mass to Nanning due to dry conditions and less wet scavenging along trajectory pathways. These findings provide valuable insights for policymakers and government officials in regulating and mitigating BC pollution in South China.
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Affiliation(s)
- Shuo Ding
- Department of Environmental Engineering, College of Quality and Safety Engineering, China Jiliang University, Hangzhou 310018, China; Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou 310058, China
| | - Dantong Liu
- Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou 310058, China.
| | - Delong Zhao
- Beijing Weather Modification Office, Beijing 100089, China
| | - Ping Tian
- Beijing Weather Modification Office, Beijing 100089, China
| | - Mengyu Huang
- Beijing Weather Modification Office, Beijing 100089, China
| | - Deping Ding
- Beijing Weather Modification Office, Beijing 100089, China
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Zhao H, Niu Z, Zhou W, Wang S, Feng X, Wu S, Lu X, Du H. Comparing sources of carbonaceous aerosols during haze and nonhaze periods in two northern Chinese cities. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 346:119024. [PMID: 37738728 DOI: 10.1016/j.jenvman.2023.119024] [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: 02/23/2023] [Revised: 09/02/2023] [Accepted: 09/14/2023] [Indexed: 09/24/2023]
Abstract
Radiocarbon (14C), stable carbon isotope (13C), and levoglucosan in PM2.5 were measured in two northern Chinese cities during haze events and nonhaze periods in January 2019, to ascertain the sources and their differences in carbonaceous aerosols between the two periods. The contribution of primary vehicle emissions (17.8 ± 3.7%) to total carbon in Beijing during that haze event was higher than that of primary coal combustion (7.3 ± 4.2%), and it increased significantly (7.1%) compared to the nonhaze period. The contribution of primary vehicle emissions (4.1 ± 2.8%) was close to that of primary coal combustion (4.3 ± 3.3%) during the haze event in Xi'an, and the contribution of primary vehicle emissions decreased by 5.8% compared to the nonhaze period. Primary biomass burning contributed 21.1 ± 10.5% during the haze event in Beijing and 40.9 ± 6.6% in Xi'an (with an increase of 3.3% compared with the nonhaze period). The contribution of secondary fossil fuel sources to total secondary organic carbon increased by 29.2% during the haze event in Beijing and by 18.4% in Xi'an compared to the nonhaze period. These results indicate that specific management measures for air pollution need to be strengthened in different Chinese cities in the future, that is, controlling vehicle emissions in Beijing and restricting the use of coal and biomass fuels in winter in Xi'an.
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Affiliation(s)
- Huiyizhe Zhao
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Shaanxi Provincial Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, 710061, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhenchuan Niu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Institute of Global Environmental Change, Xi'an Jiaotong University, Xi'an, 710049, China; Open Studio for Oceanic-Continental Climate and Environment Changes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao, 266061, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Weijian Zhou
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Open Studio for Oceanic-Continental Climate and Environment Changes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao, 266061, China; Shaanxi Provincial Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, 710061, China
| | - Sen Wang
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, China
| | - Xue Feng
- National Observation and Research Station of Regional Ecological Environment Change and Comprehensive Management in the Guanzhong Plain, Shaanxi, China; Xi'an Institute for Innovative Earth Environment Research, Xi'an, China
| | - Shugang Wu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Shaanxi Provincial Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, 710061, China
| | - Xuefeng Lu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Shaanxi Provincial Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, 710061, China
| | - Hua Du
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Shaanxi Provincial Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an, 710061, China
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5
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Zhao K, Zhang Y, Shang J, Schauer JJ, Huang W, Tian J, Yang S, Fang D, Zhang D. Impact of Beijing's "Coal to Electricity" program on ambient PM 2.5 and the associated reactive oxygen species (ROS). J Environ Sci (China) 2023; 133:93-106. [PMID: 37451793 DOI: 10.1016/j.jes.2022.06.038] [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: 02/06/2022] [Revised: 06/10/2022] [Accepted: 06/25/2022] [Indexed: 07/18/2023]
Abstract
The Beijing "Coal to Electricity" program provides a unique opportunity to explore air quality impacts by replacing residential coal burning with electrical appliances. In this study, the atmospheric ROS (Gas-phase ROS and Particle-phase ROS, abbreviated to G-ROS and P-ROS) were measured by an online instrument in parallel with concurrent PM2.5 sample collections analyzed for chemical composition and cellular ROS in a baseline year (Coal Use Year-CUY) and the first year following implementation of the "Coal to Electricity" program (Coal Ban Year-CBY). The results showed PM2.5 concentrations had no significant difference between the two sampling periods, but the activities of G-ROS, P-ROS, and cellular ROS in CBY were 8.72 nmol H2O2/m3, 9.82 nmol H2O2/m3, and 2045.75 µg UD /mg PM higher than in CUY. Six sources were identified by factor-analysis from the chemical components of PM2.5. Secondary sources (SECs) were the dominant source of PM2.5 in the two periods, with 15.90% higher contribution in CBY than in CUY. Industrial Emission & Coal Combustion sources (Ind. & CCs), mainly from regional transport, also increased significantly in CBY. The contributions of Aged Sea Salt & Residential Burning sources to PM2.5 decreased 5.31% from CUY to CBY. The correlation results illustrated that Ind. & CCs had significant positive correlations with atmospheric ROS, and SECs significantly associated with cellular ROS, especially nitrates (r = 0.626, p = 0.000). Therefore, the implementation of the "Coal to Electricity" program reduced PM2.5 contributions from coal and biomass combustion, but had little effect on the improvement of atmospheric and cellular ROS.
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Affiliation(s)
- Kaining Zhao
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China; Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing 101408, China
| | - Yuanxun Zhang
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China; CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Sciences, Xiamen 361021, China; Institute of Eco-Environmental Forensics, Shandong University, Qingdao 266237, China.
| | - Jing Shang
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
| | - James J Schauer
- Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, 53718, USA
| | - Wei Huang
- Institute of Environmental Reference Materials of Environmental Development Center of Ministry of Ecology and Environment, Beijing 100029, China
| | - Jingyu Tian
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China
| | - Shujian Yang
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China
| | - Dongqing Fang
- Meteorological Observation Center of China Meteorological Administration, Beijing 100081, China
| | - Dong Zhang
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China
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Wang N, Zhou L, Feng M, Song T, Zhao Z, Song D, Tan Q, Yang F. Progressively narrow the gap of PM 2.5 pollution characteristics at urban and suburban sites in a megacity of Sichuan Basin, China. J Environ Sci (China) 2023; 126:708-721. [PMID: 36503796 DOI: 10.1016/j.jes.2022.05.017] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 05/07/2022] [Accepted: 05/09/2022] [Indexed: 06/17/2023]
Abstract
Nowadays, the fine particle pollution is still severe in some megacities of China, especially in the Sichuan Basin, southwestern China. In order to understand the causes, sources, and impacts of fine particles, we collected PM2.5 samples and analyzed their chemical composition in typical months from July 2018 to May 2019 at an urban and a suburban (background) site of Chengdu, a megacity in this region. The daily average concentrations of PM2.5 ranged from 5.6-102.3 µg/m3 and 4.3-110.4 µg/m3 at each site. Secondary inorganics and organic matters were the major components in PM2.5 at both sites. The proportion of nitrate in PM2.5 has exceeded sulfate and become the primary inorganic component. SO2 was easier to transform into sulfate in urban areas because of Mn-catalytic heterogeneous reactions. In contrast, NO2 was easily converted in suburbs with high aerosol water content. Furthermore, organic carbon in urban was much greater than that in rural, other than elemental carbon. Element Cr and As were the key cancer risk drivers. The main sources of PM2.5 in urban and suburban areas were all secondary aerosols (42.9%, 32.1%), combustion (16.0%, 25.2%) and vehicle emission (15.2%, 19.2%). From clean period to pollution period, the contributions from combustion and secondary aerosols increased markedly. In addition to tightening vehicle controls, urban areas need to restrict emissions from steel smelters, and suburbs need to minimize coal and biomass combustion in autumn and winter.
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Affiliation(s)
- Ning Wang
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China
| | - Li Zhou
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China.
| | - Miao Feng
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Tianli Song
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China
| | - Zhuoran Zhao
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China
| | - Danlin Song
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Qinwen Tan
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Fumo Yang
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China.
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7
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Zhou R, Yan C, Yang Q, Niu H, Liu J, Xue F, Chen B, Zhou T, Chen H, Liu J, Jin Y. Characteristics of wintertime carbonaceous aerosols in two typical cities in Beijing-Tianjin-Hebei region, China: Insights from multiyear measurements. ENVIRONMENTAL RESEARCH 2023; 216:114469. [PMID: 36195159 DOI: 10.1016/j.envres.2022.114469] [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: 07/18/2022] [Revised: 09/09/2022] [Accepted: 09/28/2022] [Indexed: 06/16/2023]
Abstract
In order to investigate the impact of "Blue Sky War" implemented during 2018-2020 on carbonaceous aerosols in Beijing-Tianjin-Hebei (BTH) region, China, fine particulate matter (PM2.5) samples were collected simultaneously in Tianjin and Handan in three consecutive winters from 2018 to 2020. Organic carbon (OC) and elemental carbon (EC) in PM2.5 were measured with the same thermal-optical methods and analysis protocols. Significant reductions in primary organic carbon (POC) and EC concentrations were observed both in Tianjin and Handan, with decreasing rates of 0.65 and 2.95 μg m-3 yr-1 for POC and 0.13 and 0.64 μg m-3 yr-1 for EC, respectively. The measured absorption coefficients of EC (babs, EC) also decreased year by year, with a decreasing rate of 1.82 and 6.16 Mm-1 yr-1 in Tianjin and Handan, respectively. The estimated secondary organic carbon (SOC) concentrations decreased first and then increased in both Tianjin and Handan, accounting for more than half of the total OC in winter of 2020-2021 and with increasing contributions especially in highly polluted days. SOC was recognized as one of key factors influencing EC light absorption. EC in the two cities was relatively more related to coal combustion and industrial sources. The reductions of primary carbonaceous components may be attributed to the air quality regulations targeting coal combustion and industrial sources emissions in BTH area. Potential source contribution function (PSCF) analysis results indicated that the major source areas of OC and EC in Tianjin were the southwest region of the sampling site, while the southeast areas for Handan. These findings demonstrated the effectiveness of air quality regulation in primary emissions in typical polluted cities in BTH region and highlighted the needs for further control and in-depth investigation of SOC formation along with implementation of air pollution control act in the future.
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Affiliation(s)
- Ruizhi Zhou
- Environment Research Institute, Shandong University, Qingdao, 266237, China
| | - Caiqing Yan
- Environment Research Institute, Shandong University, Qingdao, 266237, China; State Key Laboratory of Organic Geochemistry and Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China.
| | - Qiaoyun Yang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Hongya Niu
- Key Laboratory of Resource Exploration Research of Hebei Province, Hebei University of Engineering, Handan, 056038, China
| | - Junwen Liu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou, 511443, China
| | - Fanli Xue
- Key Laboratory of Resource Exploration Research of Hebei Province, Hebei University of Engineering, Handan, 056038, China
| | - Bing Chen
- Environment Research Institute, Shandong University, Qingdao, 266237, China
| | - Taomeizi Zhou
- Environment Research Institute, Shandong University, Qingdao, 266237, China
| | - Haibiao Chen
- Environment Research Institute, Shandong University, Qingdao, 266237, China
| | - Junyi Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Yali Jin
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
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8
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Yang Y, Zhao D, Huang Y, Tian P, Liu D, Huang M, He H, Ding D, Li Y, Zhao C. Effects of black carbon aerosol on air quality and vertical meteorological factors in early summer in Beijing. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 847:157529. [PMID: 35872195 DOI: 10.1016/j.scitotenv.2022.157529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 07/12/2022] [Accepted: 07/16/2022] [Indexed: 06/15/2023]
Abstract
Black carbon (BC) aerosols have effects on the atmospheric thermal vertical structure due to its radiation absorption characteristics, hereby influencing the boundary layer characteristics and pollutant diffusion. This study focuses on the BC effects under different atmospheric conditions on air quality and vertical meteorological conditions. Four days flight observation combined with surface wind profiler radar data were used to investigate the vertical profiles of BC and wind speed over Beijing urban area in early summer. The vertical profiles of BC concentration and wind speed in the boundary layer had a negative correlation, both having abrupt changes near the boundary layer height under stagnant weather conditions. The chemical transport model showed the increase of BC under stagnant conditions could cause aggravation of the stability of the boundary layer, thereby increasing the accumulation of pollutants. In particular, BC leads to the changes in the temperature profile, which will modify relative humidity and indirectly lead to the changes in the vertical profile of aerosol optical properties. However, if the early accumulation of BC was absent under more turbulent conditions, the effects of BC on air quality and meteorological conditions were limited.
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Affiliation(s)
- Yan Yang
- Beijing Weather Modification Center, Beijing, China; Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources, Beijing, China; Field Experiment Base of Cloud and Precipitation Research in North China, China Meteorological Administration, Beijing, China
| | - Delong Zhao
- Beijing Weather Modification Center, Beijing, China; Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources, Beijing, China; Field Experiment Base of Cloud and Precipitation Research in North China, China Meteorological Administration, Beijing, China.
| | - Yu Huang
- Beijing Weather Modification Center, Beijing, China; Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources, Beijing, China; Field Experiment Base of Cloud and Precipitation Research in North China, China Meteorological Administration, Beijing, China
| | - Ping Tian
- Beijing Weather Modification Center, Beijing, China; Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources, Beijing, China; Field Experiment Base of Cloud and Precipitation Research in North China, China Meteorological Administration, Beijing, China
| | - Dantong Liu
- Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou, Zhejiang, China
| | - Mengyu Huang
- Beijing Weather Modification Center, Beijing, China; Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources, Beijing, China; Field Experiment Base of Cloud and Precipitation Research in North China, China Meteorological Administration, Beijing, China
| | - Hui He
- Beijing Weather Modification Center, Beijing, China; Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources, Beijing, China; Field Experiment Base of Cloud and Precipitation Research in North China, China Meteorological Administration, Beijing, China
| | - Deping Ding
- Beijing Weather Modification Center, Beijing, China; Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources, Beijing, China; Field Experiment Base of Cloud and Precipitation Research in North China, China Meteorological Administration, Beijing, China
| | - Yiyu Li
- Shanxi Weather Modification Center, Shanxi, China.
| | - Chun Zhao
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei, China
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Dai L, Zhang L, Chen D, Zhao Y. Assessment of carbonaceous aerosols in suburban Nanjing under air pollution control measures: Insights from long-term measurements. ENVIRONMENTAL RESEARCH 2022; 212:113302. [PMID: 35472461 DOI: 10.1016/j.envres.2022.113302] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 04/03/2022] [Accepted: 04/09/2022] [Indexed: 06/14/2023]
Abstract
The concentrations of organic carbon (OC) and elemental carbon (EC) in fine particulate matter (PM2.5) were analyzed using a semicontinuous carbon analyzer to characterize their carbonaceous components at the Nanjing University site from August 2013 to December 2018. OC was divided by the minimum R squared (MRS) method into primary organic carbon (POC) and secondary organic carbon (SOC). The results showed that annual mean POC and EC concentrations declined from 10.00 to 3.62 μg m-3 and from 6.73 to 3.40 μg m-3, respectively, during 2013-2018. The apparent reduction in POC and EC concentrations indicated that the implementation of air pollution control measures helped reduce carbonaceous aerosol pollution. Higher concentrations of POC and EC were recorded during the cold season and lower in the warm season. The annual mean SOC concentrations varied between 4.35 and 3.18 μg m-3 from 2013 to 2018. Elevated SOC was observed during the warm season, most likely attributable to the enhanced photochemical activity at high temperatures. Regarding the diurnal variation, the high concentrations of POC and EC were observed at night and in the morning due to stronger primary emissions and accumulations of pollutants with low boundary-layer heights, while the peak of SOC was observed at approximately noon due to the increases in photochemical activity. Nonparametric wind regression analysis showed the higher concentrations of POC, SOC and EC in the northwesterly, southwesterly to southeasterly, and southwesterly winds with high speeds. Concentration-weighted trajectory (CWT) analysis suggests that the areas with potentially high contributions to POC and EC changed from the north to the western areas of China, and that northern China played an increasingly important role in the SOC concentration of Nanjing. These results demonstrate that controlling emissions from the western and the northern areas in China may further alleviate carbonaceous aerosol pollution in Nanjing.
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Affiliation(s)
- Liang Dai
- State Key Laboratory of Pollution Control and Resource Reuse and School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu, 210023, China
| | - Lei Zhang
- State Key Laboratory of Pollution Control and Resource Reuse and School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu, 210023, China
| | - Dong Chen
- Jiangsu Provincial Academy of Environmental Science, 176 North Jiangdong Rd., Nanjing, Jiangsu, 210036, China
| | - Yu Zhao
- State Key Laboratory of Pollution Control and Resource Reuse and School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu, 210023, China; Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science and Technology, Jiangsu, 210044, China.
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10
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Liu Y, Xu X, Yang X, He J, Zhang W, Liu X, Ji D, Wang Y. Significant contribution of secondary particulate matter to recurrent air pollution: Evidence from in situ observation in the most polluted city of Fen-Wei Plain of China. J Environ Sci (China) 2022; 114:422-433. [PMID: 35459505 DOI: 10.1016/j.jes.2021.09.030] [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: 06/01/2021] [Revised: 09/18/2021] [Accepted: 09/24/2021] [Indexed: 06/14/2023]
Abstract
Particulate matter (PM) pollution in high emission regions will affect air quality, human health and climate change on both local and regional scales, and thus attract worldwide attention. In this study, a comprehensive study on PM2.5 and its chemical composition were performed in Yuncheng (the most polluted city of Fen-Wei Plain of China) from November 28, 2020 to January 24, 2021. The average concentration of PM2.5 was 87.8 ± 52.0 μg/m3, which were apparently lower than those observed during the same periods of past five years, attributable to the clean air action plan implemented in this region. NO3- and organic carbon (OC) were the dominant particulate components, which on average contributed 22.6% and 16.5% to PM2.5, respectively. The fractions of NO3-, NH4+, OC and trace metals increased while those of crustal materials and elemental carbon decreased with the degradation of PM2.5 pollution. Six types of PM2.5 sources were identified by the PMF model, including secondary inorganic aerosol (35.3%), coal combustion (28.7%), vehicular emission (20.7%), electroplating industry (8.6%), smelt industry (3.9%) and dust (2.8%). Locations of each identified source were pinpointed based on conditional probability function, potential source contribution function and concentration weighted trajectory, which showed that the geographical distribution of the sources of PM2.5 roughly agreed with the areas of high emission. Overall, this study provides valuable information on atmospheric pollution and deems beneficial for policymakers to take informed action to sustainably improve air quality in highly polluted region.
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Affiliation(s)
- Yu Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Xiaojuan Xu
- Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Xiaoyang Yang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jun He
- Natural Resources and Environment Research Group, Department of Chemical and Environmental Engineering, University of Nottingham Ningbo China, Ningbo 315100, China
| | - Wenjie Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Xingang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Dongsheng Ji
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China.
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
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11
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Feng Z, Zheng F, Liu Y, Fan X, Yan C, Zhang Y, Daellenbach KR, Bianchi F, Petäjä T, Kulmala M, Bao X. Evolution of organic carbon during COVID-19 lockdown period: Possible contribution of nocturnal chemistry. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 808:152191. [PMID: 34875334 PMCID: PMC8651497 DOI: 10.1016/j.scitotenv.2021.152191] [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: 09/25/2021] [Revised: 11/15/2021] [Accepted: 12/01/2021] [Indexed: 05/03/2023]
Abstract
Carbonaceous aerosol is one of the main components of atmospheric particulate matter, which is of great significance due to its role in climate change, earth's radiation balance, visibility, and human health. In this work, carbonaceous aerosols were measured in Shijiazhuang and Beijing using the OC/EC analyzer from December 1, 2019 to March 15, 2020, which covered the Coronavirus Disease 2019 (COVID-19) pandemic. The observed results show that the gas-phase pollutants, such as NO, NO2, and aerosol-phase pollutants (Primary Organic Compounds, POC) from anthropogenic emissions, were significantly reduced during the lockdown period due to limited human activities in North China Plain (NCP). However, the atmospheric oxidation capacity (Ox/CO) shows a significantly increase during the lockdown period. Meanwhile, additional sources of nighttime Secondary Organic Carbon (SOC), Secondary Organic Aerosol (SOA), and babs, BrC(370 nm) are observed and ascribed to the nocturnal chemistry related to NO3 radical. The Potential Source Contribution Function (PSCF) analysis indicates that the southeast areas of the NCP region contributed more to the SOC during the lockdown period than the normal period. Our results highlight the importance of regional nocturnal chemistry in SOA formation.
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Affiliation(s)
- Zemin Feng
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Feixue Zheng
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Yongchun Liu
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China; College of Chemistry and Chemical Engineering, China West Normal University, Nanchong 637002, China.
| | - Xiaolong Fan
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Chao Yan
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Yusheng Zhang
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Kaspar R Daellenbach
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Federico Bianchi
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Tuukka Petäjä
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Markku Kulmala
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China; Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Xiaolei Bao
- Hebei Provincial Academy of Environmental Sciences, Shijiazhuang 050037, China; Hebei Chemical & Pharmaceutical College, Shijiazhuang 050026, China.
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Xiao HW, Mao DY, Huang LL, Xiao HY, Wu JF. Evaluation of black carbon source apportionment based on one year's daily observations in Beijing. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 773:145668. [PMID: 33940754 DOI: 10.1016/j.scitotenv.2021.145668] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 01/24/2021] [Accepted: 02/02/2021] [Indexed: 06/12/2023]
Abstract
Combustion-derived black carbon (BC) is increasingly recognized as a significant pollutant that can have adverse effects on the atmospheric environment, human health, and regional climate. Fossil fuel combustion is the main source of BC, yet understanding of the relative contributions to BC from coal and liquid fuel combustion remains incomplete. Moreover, few studies have assessed the relative contributions based on long-term continuous daily field observations. This study adopted a Bayesian model of a three-dimensional array of a stable carbon isotope and the ratios of non-sea-salt K+ to BC and ΔBC/ΔCO of one year's daily observations (from September 1, 2017 to August 31, 2018) to constrain source apportionment of BC in Beijing (China). Results showed that both the BC and the carbon isotope concentrations exhibited strong seasonal variability, and that the annual BC concentration has decreased significantly in recent years. The Bayesian model results also revealed that the relative contributions from the combustion of coal, liquid fuel, and biomass were 42% ± 18%, 42% ± 18%, and 16% ± 11%, respectively, with a larger contribution from coal (liquid fuel) combustion in winter and spring (summer and autumn). The seasonal variation of source appointment was attributed to local and regional fuel combustion coupled with meteorological conditions. With increasing PM2.5 level, the BC concentration derived from biomass burning increased fastest, followed by that derived from coal combustion. But concentration of secondary inorganic ions increased faster than BC as PM2.5 increased.
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Affiliation(s)
- Hong-Wei Xiao
- Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution, East China University of Technology, Nanchang 330013, China
| | - Dong-Yang Mao
- Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution, East China University of Technology, Nanchang 330013, China
| | - Li-Lei Huang
- Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution, East China University of Technology, Nanchang 330013, China
| | - Hua-Yun Xiao
- Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution, East China University of Technology, Nanchang 330013, China; School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Jing-Feng Wu
- Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami 33149, USA
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13
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Chen D, Liao H, Yang Y, Chen L, Wang H. Simulated aging processes of black carbon and its impact during a severe winter haze event in the Beijing-Tianjin-Hebei region. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 755:142712. [PMID: 33049531 DOI: 10.1016/j.scitotenv.2020.142712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 09/18/2020] [Accepted: 09/27/2020] [Indexed: 06/11/2023]
Abstract
Black carbon (BC) can mitigate or worsen air pollution by perturbing meteorological conditions. BC aging processes strongly influence the evolution of the particle size, concentration, and optical properties of BC, which determine its influence on meteorology. Here, we use the online coupled Weather Research and Forecasting-Chemistry (WRF-Chem) model to quantify the role of BC aging processes, including physical processes (PP) and absorption enhancement (AE), in causing BC-induced meteorological changes and their associated feedbacks to PM2.5 (particulate matter less than 2.5 μm in diameter) and O3 concentrations during a severe haze event in the Beijing-Tianjin-Hebei (BTH) region during 21-27 February 2014. Our results show that, compared to those from the simulation without PP, the simulated near-surface BC concentration and BC mass loading in the BTH region decreased by 6.6% and 12.1%, respectively, when PP were included. PP increased the proportion of large BC (particle diameter greater than 0.312 μm) below 1000 m from 28 to 33% to 59-64% in the BTH region. When both PP and AE were included in the simulation, the reduction in PBL height due to the BC-PBL interaction was 116.3 m (20.7%), compared to reductions of 75.7 m (13.5%) without AE and 66.6 m (11.9%) without PP and AE. However, during this haze event, anomalous northeasterly winds were produced by the direct radiative effect of BC, which further affected aerosol mixing and transport. Due to their combined impacts on multiple meteorological factors, the direct radiative effects of BC without PP and AE, without AE, and with PP and AE increased the surface concentrations of PM2.5 by 8.3 μg m-3 (by 6.1% relative to the mean value), 6.1 μg m-3 (4.5%) and 9.6 μg m-3 (7.0%), respectively, but decreased the surface O3 concentrations by 2.8 ppbv (7.4%), 4.0 ppbv (9.0%) and 5.0 ppbv (10.8%) on average in the BTH region during 21-27 February 2014.
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Affiliation(s)
- Donglin Chen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Engineering Technology Research Center of Environmental Cleaning Materials, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China
| | - Hong Liao
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Engineering Technology Research Center of Environmental Cleaning Materials, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China.
| | - Yang Yang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Engineering Technology Research Center of Environmental Cleaning Materials, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China.
| | - Lei Chen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Engineering Technology Research Center of Environmental Cleaning Materials, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China
| | - Hailong Wang
- Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
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14
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Cong L, Mo L, Yan G, Ma W, Wu Y, Liu J, Zhai J, Wang Y, Zhang Z. Assessing the spatiotemporal characteristics of dry deposition flux in forests and wetlands. ENVIRONMENTAL TECHNOLOGY 2020; 41:1615-1626. [PMID: 30376793 DOI: 10.1080/09593330.2018.1543355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2018] [Accepted: 10/28/2018] [Indexed: 06/08/2023]
Abstract
Forests and wetlands, as two important ecosystems, play a crucial role in reducing the concentration of particulate matters. The main purpose of this study is to reveal the contribution of forest and wetland ecosystems to the reduction of particulate matter. We collected the concentration and meteorological data during the daytime in a forest and a wetland in the Olympic Park in Beijing. The main results are as follows: daily variation in the PM10 and PM2.5 concentration had the similar trend with the lowest value at midday and relatively high values in the morning and at nightfall. In the forest ecosystem, the trend of PM10 concentration at three heights followed the order: 6 m > 10 m > 1.5 m, while that of the PM2.5 followed the order 1.5 m > 10 m > 6 m. In the wetland, PM10 and PM2.5 concentrations at the three heights exhibited the same trend: 10 m > 1.5 m > 6 m. It is a comprehensive impact on concentration which may include vegetation collection rate, meteorological conditions and some kind of human activities. The PM deposition velocity of wetland was higher than that of forest, and showed the highest values in winter both in PM2.5 and PM10. The PM deposition flux in wetland was lower than forest only in autumn, and the value of deposition flux was higher than forest in other seasons. PM concentrations was positively correlated with relative humidity but negatively correlated with temperature and wind velocity.
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Affiliation(s)
- Ling Cong
- College of Nature Conservation, Beijing Forestry University, Beijing, People's Republic of China
| | - Lichun Mo
- College of Nature Conservation, Beijing Forestry University, Beijing, People's Republic of China
| | - Guoxin Yan
- College of Nature Conservation, Beijing Forestry University, Beijing, People's Republic of China
| | - Wenmei Ma
- College of Nature Conservation, Beijing Forestry University, Beijing, People's Republic of China
| | - Yanan Wu
- College of Nature Conservation, Beijing Forestry University, Beijing, People's Republic of China
| | - Jiakai Liu
- College of Nature Conservation, Beijing Forestry University, Beijing, People's Republic of China
| | - Jiexiu Zhai
- College of Nature Conservation, Beijing Forestry University, Beijing, People's Republic of China
| | - Yu Wang
- College of Nature Conservation, Beijing Forestry University, Beijing, People's Republic of China
| | - Zhenming Zhang
- College of Nature Conservation, Beijing Forestry University, Beijing, People's Republic of China
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Kong L, Tan Q, Feng M, Qu Y, An J, Liu X, Cheng N, Deng Y, Zhai R, Wang Z. Investigating the characteristics and source analyses of PM 2.5 seasonal variations in Chengdu, Southwest China. CHEMOSPHERE 2020; 243:125267. [PMID: 31734594 DOI: 10.1016/j.chemosphere.2019.125267] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 10/15/2019] [Accepted: 10/29/2019] [Indexed: 06/10/2023]
Abstract
In 2015, comprehensive observations were carried out in Chengdu, Sichuan Province, China, to elucidate the seasonal variation characteristics of the concentrations, chemical compositions, and the sources of PM2.5 pollution. The meteorological parameters, gaseous pollutants and chemical compositions of PM2.5 were measured. The annual average concentration of PM2.5 in Chengdu was 67.44 ± 48.78 μg/m3. The highest seasonal PM2.5 mass concentration occurred in winter with an average of 103.04 ± 66.76 μg/m3, followed by spring, autumn, and summer, and the wind speed had an important impact on the diffusion of PM2.5. The seasonal variation characteristics of chemical components in PM2.5 were analysed. The contribution and chemical conversion ability of secondary aerosols increased with increasing of PM2.5 concentration. Source appointment of positive matrix factorization (PMF) shows that the main sources of PM2.5 were secondary aerosols, coal combustion, biomass burning, vehicle emissions, dust and industrial sources, which have more obvious seasonal differences than other sources, and secondary aerosols and coal combustion were the major sources. Conditional probability function (CPF) analysis showed that the local sources of high PM2.5 concentrations were mainly from the eastern and southeastern areas of Chengdu. Potential source contribution function (PSCF), concentration weighted trajectory (CWT) and backward trajectory cluster analyses indicated that the southern, southeast and eastern parts of the Sichuan Basin were the most likely potential sources of PM2.5, and the unique geographical and topographical factors in Chengdu play important roles in the transport and diffusion of pollutants in this region.
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Affiliation(s)
- Liuwei Kong
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Qinwen Tan
- Chengdu Academy of Environmental Sciences, Chengdu, 610072, China
| | - Miao Feng
- Chengdu Academy of Environmental Sciences, Chengdu, 610072, China
| | - Yu Qu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Junling An
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Xingang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China.
| | - Nianliang Cheng
- Beijing Municipal Environmental Monitoring Center, Beijing, 100048, China
| | - Yijun Deng
- Yuncheng Municipal Ecological Environment Bureau, Yuncheng, 044000, China
| | - Ruixiao Zhai
- Yuncheng Municipal Ecological Environment Bureau, Yuncheng, 044000, China
| | - Zheng Wang
- Yuncheng Municipal Ecological Environment Bureau, Yuncheng, 044000, China
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Liu Z, Hu B, Ji D, Cheng M, Gao W, Shi S, Xie Y, Yang S, Gao M, Fu H, Chen J, Wang Y. Characteristics of fine particle explosive growth events in Beijing, China: Seasonal variation, chemical evolution pattern and formation mechanism. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 687:1073-1086. [PMID: 31412445 DOI: 10.1016/j.scitotenv.2019.06.068] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 04/26/2019] [Accepted: 06/04/2019] [Indexed: 06/10/2023]
Abstract
Fine particle explosive growth (FPEG) events are frequently observed in heavy haze episodes in Beijing, the characteristics and formation mechanism of which remain not fully understood. In this study, a five year (2013-2017) online observation was conducted in Beijing and the chemical evolution pattern of FPEG events was analyzed to understand its formation mechanism. A total of 132 FPEG events were identified, and steadily decreased from 39 events in 2013 to 19 events in 2017. More than 70% of the FPEG events occurred in winter and autumn, which coincides with adverse weather conditions and enhanced primary emissions. Organic matter (OM) was the dominated components (~30%) in PM2.5, but it only accounted for 10% of total FPEG events as a driven factor, because its contribution usually decreased when the FPEG events developed. In contrast, the secondary inorganic species were the dominated driven factors, and sulfate-driven events accounted >50%. During the period of 2013-2017, the contribution from regional sources decreased significantly mainly due to the reduction of emissions from regional sources, while the contribution from local sources remained largely unchanged, indicating that the local secondary transformation played a leading role in promoting the FPEG events. The low nitrogen oxidation rates (NOR, 0.12 ± 0.07) and the weak increase trend of NOR with elevated RH were observed, indicating the formation of which might be promoted by the homogenous reaction between HNO3 and NH3. In contrast, a significant increase in sulfur oxidation rate (SOR, 0.50 ± 0.19) was observed when RH > 50%, suggesting enhanced heterogeneous oxidation of SO2 in FPEG events. In addition, our analysis suggest the S (IV) heterogeneous oxidation rates in FPEG events depend mainly on the aerosol liquid water content (ALWC) in addition to the aerosol acidity. This study provides observational evidence for understanding the formation mechanism of FPEG events in Beijing.
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Affiliation(s)
- Zirui Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Bo Hu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Dongsheng Ji
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Mengtian Cheng
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Wenkang Gao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Shuzhen Shi
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China; Department of Environmental Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Yuzhu Xie
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Shuanghong Yang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China; Department of Environmental Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Meng Gao
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Hongbo Fu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Jianming Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China.
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Yang W, Xie S, Zhang Z, Hu J, Zhang L, Lei X, Zhong L, Hao Y, Shi F. Characteristics and sources of carbonaceous aerosol across urban and rural sites in a rapidly urbanized but low-level industrialized city in the Sichuan Basin, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2019; 26:26646-26663. [PMID: 31292872 DOI: 10.1007/s11356-019-05242-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Accepted: 04/22/2019] [Indexed: 06/09/2023]
Abstract
Organic carbon (OC) and elemental carbon (EC) were measured in 24 h fine particulate matter (PM2.5) samples collected from May 2015 to April 2016 at urban and rural sites in Nanchong, a rapidly urbanized but low-level industrialized city in the Sichuan Basin, China. The annual average PM2.5, OC, and EC concentrations at urban sites were 45.6-55.7, 8.5-11.5, and 2.8-3.4 μg m-3, respectively, which were similar to the corresponding values (48.3, 10.6, and 3.3 μg m-3) at the rural site. The PM2.5 concentrations displayed strong monthly variations, with the highest (78.8-105.0 μg m-3) in January or February. Likewise, daily OC and EC concentrations exhibited high values in October (only for OC) and December 2015 to February 2016. Correlation, positive matrix factorization, and concentration weighted trajectory analyses were combined to investigate the sources of carbonaceous aerosol. The results indicated that OC and EC were mainly from biomass burning (60.7% and 45.8%) and coal combustion (30.2% and 25.7%), followed by vehicle emissions and road dust. The enhanced emissions from residential coal and biofuel uses in winter and straw combustion in October contributed to higher concentrations of OC and EC during these months. The contributions of biomass burning to OC and EC were significantly higher at the rural site (69.2% and 51.8%) than urban sites (56.3-58.6% and 37.8-41.5%). In addition to local emissions, the high concentrations of OC and EC at Nanchong were also influenced by regional transport in the basin.
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Affiliation(s)
- Wenwen Yang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Science and Engineering, Peking University, No. 5 Yiheyuan Rd, Beijing, 100871, China
| | - Shaodong Xie
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Science and Engineering, Peking University, No. 5 Yiheyuan Rd, Beijing, 100871, China.
| | - Ziquan Zhang
- Nanchong Environmental Monitoring Center, No. 118 Wannian West Rd, Shunqing District, Nanchong, 637000, Sichuan, China
| | - Jian Hu
- Nanchong Environmental Monitoring Center, No. 118 Wannian West Rd, Shunqing District, Nanchong, 637000, Sichuan, China
| | - Lingyun Zhang
- Nanchong Environmental Monitoring Center, No. 118 Wannian West Rd, Shunqing District, Nanchong, 637000, Sichuan, China
| | - Xiong Lei
- Nanchong Environmental Monitoring Center, No. 118 Wannian West Rd, Shunqing District, Nanchong, 637000, Sichuan, China
| | - Lijian Zhong
- Nanchong Environmental Monitoring Center, No. 118 Wannian West Rd, Shunqing District, Nanchong, 637000, Sichuan, China
| | - Yufang Hao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Science and Engineering, Peking University, No. 5 Yiheyuan Rd, Beijing, 100871, China
| | - Fangtian Shi
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Science and Engineering, Peking University, No. 5 Yiheyuan Rd, Beijing, 100871, China
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18
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Ji D, Gao M, Maenhaut W, He J, Wu C, Cheng L, Gao W, Sun Y, Sun J, Xin J, Wang L, Wang Y. The carbonaceous aerosol levels still remain a challenge in the Beijing-Tianjin-Hebei region of China: Insights from continuous high temporal resolution measurements in multiple cities. ENVIRONMENT INTERNATIONAL 2019; 126:171-183. [PMID: 30798198 DOI: 10.1016/j.envint.2019.02.034] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 02/11/2019] [Accepted: 02/12/2019] [Indexed: 05/28/2023]
Abstract
Carbonaceous aerosols in high emission areas attract worldwide attention of the scientific community and the public due to their adverse impacts on the environment, human health and climate. However, long-term continuous hourly measurements are scarce on the regional scale. In this study, a one-year hourly measurement (from December 1, 2016 to November 30, 2017) of organic carbon (OC) and elemental carbon (EC) in airborne fine particles was performed using semi-continuous OC/EC analyzers in Beijing, Tianjin, Shijiazhuang and Tangshan in the Beijing-Tianjin-Hebei (BTH) region in China, which is one of high emission areas in China, even in the world. Marked spatiotemporal variations were observed. The highest concentrations of OC (22.8 ± 30.6 μg/m3) and EC (5.4 ± 6.5 μg/m3) occurred in Shijiangzhuang while the lowest concentrations of OC (11.0 ± 10.7 μg/m3) and EC (3.1 ± 3.6 μg/m3) were obtained in Beijing and Tianjin, respectively. Pronounced monthly, seasonal and diurnal variations of OC and EC were recorded. Compared to published data from the past two decades for the BTH region, our OC and EC levels were lower, implying some effect of recent measures for improving the air quality. Significant correlations of OC versus EC (p < 0.001) were found throughout the study period with high slopes and correlation coefficients in winter, but low slopes and correlation coefficients in summer. The estimated secondary OC (SOC), based on the minimum R squared (MRS) method, represented 29%, 47%, 38% and 48% of the OC for Beijing, Tianjin, Shijiazhuang and Tangshan, respectively. These percentages are larger than previous ones obtained for the BTH region in the past decade. There were obvious differences in the potential source regions of OC and EC among the four cities. Obvious prominent potential source areas of OC and EC were observed for Beijing, which were mainly located in the central and western areas of Inner Mongolia and even extended to the Mongolian regions, which is different from the findings in previous studies. For all sites, adjacent areas of the main provinces in northern China were found to be important potential source areas.
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Affiliation(s)
- Dongsheng Ji
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China.
| | - Meng Gao
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Willy Maenhaut
- Department of Chemistry, Ghent University, Gent 9000, Belgium.
| | - Jun He
- International Doctoral Innovation Centre, Department of Chemical and Environmental Engineering, University of Nottingham Ningbo China, Ningbo 315100, China
| | - Cheng Wu
- Institute of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China; Guangdong Provincial Engineering Research Center for On-Line Source Apportionment System of Air Pollution, Guangzhou 510632, China
| | - Linjun Cheng
- China National Environmental Monitoring Center, Beijing 100012, China
| | - Wenkang Gao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Yang Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Jiaren Sun
- South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China
| | - Jinyuan Xin
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Lili Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China; Atmosphere Sub-Center of Chinese Ecosystem Research Network, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100191, China
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19
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San Miguel EG, Hernández-Ceballos MA, García-Mozo H, Bolívar JP. Evidences of different meteorological patterns governing 7Be and 210Pb surface levels in the southern Iberian Peninsula. JOURNAL OF ENVIRONMENTAL RADIOACTIVITY 2019; 198:1-10. [PMID: 30557786 DOI: 10.1016/j.jenvrad.2018.12.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 11/30/2018] [Accepted: 12/03/2018] [Indexed: 06/09/2023]
Abstract
7Be, 210Pb and PM10 levels in surface air have been simultaneously measured at two sampling sites in the southern Iberian Peninsula for a period of two years. Each site covers one different meteorological area of the Guadalquivir valley, from the mouth (Huelva) to the middle point (Cordoba). The objective of the present study is to analyse the spatial variability of both natural radionuclides, and to identify and characterise the meteorological patterns associated with similar and different surface concentration levels in this complex region. Concentrations are similar in both sampling sites. 7Be level is in the 0.6-15.5 mBq m-3 range in Huelva and 1.2-13.3 mBq m-3 in Córdoba, 210Pb activity concentrations are between 0.04 and 2.30 mBq m-3 in Huelva, and between 0.03 and 1.2 mBq m-3 in Cordoba, and PM10 concentrations are found to be in the 5.1-81.3 μg m-3 range in Huelva, and 8.2-76.3 μg m-3 in Cordoba, respectively. A linear regression analysis indicates more regional variability for 210Pb than for 7Be between simultaneous measurements. Principal components analysis (PCA) is applied to the datasets and the results reveal that aerosol behaviour is mainly represented by two components, which explain 82% of the total variance. The analysis of surface measurements and meteorological parameters revealed that component F1 groups sampling periods in which the influence of similar meteorological conditions over the region lead to similar 7Be, 210Pb and PM10 concentration levels in both sampling sites. On the other hand, component F2 detaches the 7Be, 210Pb and PM10 concentration levels between monitoring sites, and the meteorological analysis shows how surface concentrations within this component are associated with the development of different mesoscale circulations in each part of the valley. The identification of sampling periods characterised by differences in surface concentrations and wind patterns between stations suggests that the valley could not be considered as one single unit for certain meteorological scenarios. These results evidence how the understanding of wind characteristics within a complex terrain provide some essential knowledge in the regionalization and/or optimization of monitoring networks.
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Affiliation(s)
- E G San Miguel
- Department of Integrated Sciences, Area of Applied Physics, University of Huelva, 21071, Huelva, Spain; Research Center on Natural Resources, Health and the Environment (RENSMA), University of Huelva, 21071, Huelva, Spain.
| | | | - H García-Mozo
- Department of Botany, Ecology and Plant Physiology, Agrifood, Campus of International Excellence (CeiA3), University of Córdoba, Córdoba, Spain
| | - J P Bolívar
- Department of Integrated Sciences, Area of Applied Physics, University of Huelva, 21071, Huelva, Spain; Research Center on Natural Resources, Health and the Environment (RENSMA), University of Huelva, 21071, Huelva, Spain
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20
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Liu JM, Du ZY, Gordon M, Liang LL, Ma YL, Zheng M, Cheng Y, He KB. The characteristics of carbonaceous aerosol in Beijing during a season of transition. CHEMOSPHERE 2018; 212:1010-1019. [PMID: 30286530 DOI: 10.1016/j.chemosphere.2018.08.151] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 08/29/2018] [Accepted: 08/29/2018] [Indexed: 06/08/2023]
Abstract
Carbonaceous aerosol was measured during fall of 2010 in Beijing. Daily variation of organic carbon (OC) was found to coincide with that of relative humidity (RH), and the OC to elemental carbon (EC) ratios were more than doubled during the more humid periods (RH above 0.75) compared to other conditions. This large increase in OC/EC could not be explained by the variations of primary biomass burning emissions but was accompanied by a five-fold increase in the sulfate to EC ratio. It was then inferred that secondary organic aerosol (SOA) formation was enhanced under the more humid conditions, presumably through aqueous-phase processes. This enhanced SOA formation might be partially associated with particles externally mixed with black carbon, as indicated by the RH-dependent relationships between aerosol optical attenuation and EC loading. In addition, organic aerosols exhibited different properties between the more humid and the other periods, such that they were less volatile and charred more significantly during thermal-optical analysis in the former case. These differences coincided with the evidence of enhanced SOA formation under the more humid conditions. This study highlights the necessity of incorporating aqueous-phase chemistry into air quality models for SOA.
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Affiliation(s)
- Jiu-Meng Liu
- School of Environment, Harbin Institute of Technology, Harbin, China
| | - Zhen-Yu Du
- National Research Center for Environmental Analysis and Measurement, Beijing, China
| | - Mark Gordon
- Department of Earth and Space Science and Engineering, York University, Toronto, Ontario, Canada
| | - Lin-Lin Liang
- State Key Laboratory of Severe Weather and Key Laboratory for Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China
| | - Yong-Liang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Mei Zheng
- College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Yuan Cheng
- School of Environment, Harbin Institute of Technology, Harbin, China.
| | - Ke-Bin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
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21
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Qi M, Jiang L, Liu Y, Xiong Q, Sun C, Li X, Zhao W, Yang X. Analysis of the Characteristics and Sources of Carbonaceous Aerosols in PM 2.5 in the Beijing, Tianjin, and Langfang Region, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:E1483. [PMID: 30011803 PMCID: PMC6069050 DOI: 10.3390/ijerph15071483] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2018] [Revised: 07/06/2018] [Accepted: 07/08/2018] [Indexed: 11/21/2022]
Abstract
PM2.5 samples from Beijing, Tianjin, and Langfang were simultaneously collected from 20 November 2016 to 25 December 2016, and the organic carbon (OC) and elemental carbon (EC) content in the samples were measured and analyzed. The pollution characteristics and sources of OC and EC in atmospheric PM2.5 for three adjacent cities were discussed. The average mass concentrations of OC in PM2.5 in Beijing, Tianjin, and Langfang were 27.93 ± 23.35 μg/m³, 25.27 ± 12.43 μg/m³, and 52.75 ± 37.97 μg/m³, respectively, and the mean mass concentrations of EC were 6.61 ± 5.13 μg/m³, 6.14 ± 2.84 μg/m³, and 12.06 ± 6.81 μg/m³, respectively. The average mass concentration of total carbon (TC) accounted for 30.5%, 24.8%, and 49% of the average mass concentration of PM2.5 in the atmosphere. The total carbonaceous matter (TCA) in Beijing, Tianjin, and Langfang was 51.29, 46.57, and 96.45 μg/m³, respectively. The TCA was the main component of PM2.5 in the region. The correlation between OC and EC in the three cities showed R² values of 0.882, 0.633, and 0.784 for Beijing, Tianjin, and Langfang, respectively, indicating that the sources of urban carbonaceous aerosols had good consistency and stability. The OC/EC values of the three sampling points were 4.48 ± 1.45, 4.42 ± 1.77, and 4.22 ± 1.29, respectively, considerably greater than 2, indicating that the main sources of pollution were automobile exhaust, and the combustion of coal and biomass. The OC/EC minimum ratio method was used to estimate the secondary organic carbon (SOC) content in Beijing, Tianjin and Langfang. Their values were 10.73, 10.71, and 19.51, respectively, which accounted for 38%, 42%, and 37% of the average OC concentration in each city, respectively. The analysis of the eight carbon components showed that the main sources of pollutants in Beijing, Tianjin, and Langfang were exhaust emissions from gasoline vehicles, but the combustion of coal and biomass was relatively low. The pollution of road dust was more serious in Tianjin than in Beijing and Langfang. The contribution of biomass burning and coal-burning pollution sources to atmospheric carbon aerosols in Langfang was more prominent than that of Beijing and Tianjin.
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Affiliation(s)
- Mengxi Qi
- Beijing Key Laboratory of Resources Environment and Geographic Information System, Capital Normal University, Beijing 100048, China.
- Base of the State Key Laboratory of Urban Environmental Process and Digital Modelling, Beijing 100048, China.
| | - Lei Jiang
- Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China.
| | - Yixuan Liu
- Beijing Key Laboratory of Resources Environment and Geographic Information System, Capital Normal University, Beijing 100048, China.
- Base of the State Key Laboratory of Urban Environmental Process and Digital Modelling, Beijing 100048, China.
| | - Qiulin Xiong
- Beijing Key Laboratory of Resources Environment and Geographic Information System, Capital Normal University, Beijing 100048, China.
- Base of the State Key Laboratory of Urban Environmental Process and Digital Modelling, Beijing 100048, China.
| | - Chunyuan Sun
- Beijing Key Laboratory of Resources Environment and Geographic Information System, Capital Normal University, Beijing 100048, China.
- Base of the State Key Laboratory of Urban Environmental Process and Digital Modelling, Beijing 100048, China.
| | - Xing Li
- Beijing Key Laboratory of Resources Environment and Geographic Information System, Capital Normal University, Beijing 100048, China.
- Base of the State Key Laboratory of Urban Environmental Process and Digital Modelling, Beijing 100048, China.
| | - Wenji Zhao
- Beijing Key Laboratory of Resources Environment and Geographic Information System, Capital Normal University, Beijing 100048, China.
- Base of the State Key Laboratory of Urban Environmental Process and Digital Modelling, Beijing 100048, China.
| | - Xingchuan Yang
- Beijing Key Laboratory of Resources Environment and Geographic Information System, Capital Normal University, Beijing 100048, China.
- Base of the State Key Laboratory of Urban Environmental Process and Digital Modelling, Beijing 100048, China.
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