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Shen W, Wang M, Dong X. Enhanced Aging of Black Carbon under Recent Clean Air Actions and Future Carbon Neutrality Scenario in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:13697-13706. [PMID: 39026181 DOI: 10.1021/acs.est.4c02030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
China has implemented strict emission control measures, but it is unclear how they affect black carbon (BC) aging and light absorption. Here, we use the Community Atmosphere Model version 6 (CAM6) with the four-mode version of the Modal Aerosol Module coupled with machine learning (MAM4-ML) to simulate BC aging during 2011-2018 and 2050/2100 following a carbon neutrality scenario (SSP1-2.6), respectively. During 2011-2018, the mass ratio of coatings to BC (RBC) widely increased (5.4% yr-1) over the east of China. The increased secondary organic aerosol (SOA) coatings dominate (88%) the increased RBC, while the sulfate coatings decrease. The drivers of BC coating changes come from the different magnitudes of emission reductions in secondary aerosol precursors (i.e., volatile organic compounds (VOCs) and SO2) and BC. During 2011-2018, the increased RBC enhances the BC mass absorption cross section (MAC, 0.7% yr-1). In 2050/2100 for SSP1-2.6, emission control leads to further increased RBC (95/145%) and BC MAC (12/17%). For both 2011-2018 and 2050/2100, the enhanced BC MAC partly offsets the declining direct radiative effect (DRE) of BC due to direct emission reduction. As a result, the full impact of direct emission reductions of BC on BC DRE is only 75% for 2011-2018 and 90/94% for 2050/2100.
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Affiliation(s)
- Wenxiang Shen
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- Joint International Research Laboratory of Atmospheric and Earth System Sciences and Institute for Climate and Global Change Research, Nanjing University, Nanjing 210023, China
| | - Minghuai Wang
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- Joint International Research Laboratory of Atmospheric and Earth System Sciences and Institute for Climate and Global Change Research, Nanjing University, Nanjing 210023, China
| | - Xinyi Dong
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- Joint International Research Laboratory of Atmospheric and Earth System Sciences and Institute for Climate and Global Change Research, Nanjing University, Nanjing 210023, China
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Chen P, Kang S, Hu Y, Pu T, Liu Y, Wang S, Rai M, Wang K, Tripathee L, Li C. South and Southeast Asia controls black carbon characteristics of Meili Snow Mountains in southeast Tibetan Plateau. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 927:172262. [PMID: 38583605 DOI: 10.1016/j.scitotenv.2024.172262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 04/04/2024] [Accepted: 04/04/2024] [Indexed: 04/09/2024]
Abstract
South and Southeast Asia (SSA) emitted black carbon (BC) exerts potential effects on glacier and snow melting and regional climate change in the Tibetan Plateau. In this study, online BC measurements were conducted for 1 year at a remote village located at the terminus of the Mingyong Glacier below the Meili Snow Mountains. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used to investigate the contribution and potential effect of SSA-emitted BC. In addition, variations in the light absorption characteristics of BC and brown carbon (BrC) were examined. The results indicated that the annual mean concentration of BC was 415 ± 372 ngm-3, with the highest concentration observed in April (monthly mean: 930 ± 484 ngm-3). BC exhibited a similar diurnal variation throughout the year, with two peaks observed in the morning (from 8:00 to 9:00 AM) and in the afternoon (from 4:00 to 5:00 PM), with even lower values at nighttime. At a short wavelength of 370 nm, the absorption coefficient (babs) reached its maximum value, and the majority of babs values were < 20 Mm-1, indicating that the atmosphere was not overloaded with BC. At the same wavelength, BrC substantially contributed to babs, with an annual mean of 25.2 % ± 12.8 %. SSA was the largest contributor of BC (annual mean: 51.1 %) in the study area, particularly in spring (65.6 %). However, its contributions reached 20.2 % in summer, indicating non-negligible emissions from activities in other regions. In the atmosphere, the SSA BC-induced radiative forcing (RF) over the study region was positive. While at the near surface, the RF exhibited a significant seasonal variation, with the larger RF values occurring in winter and spring. Overall, our findings highlight the importance of controlling BC emissions from SSA to protect the Tibetan Plateau against pollution-related glacier and snow cover melting.
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Affiliation(s)
- Pengfei Chen
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shichang Kang
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Yuling Hu
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Tao Pu
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Yajun Liu
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Shijin Wang
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China; Yulong Snow Mountain National Field Observation and Research Station for Cryosphere and Sustainable Development, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Mukesh Rai
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Ke Wang
- Key Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China
| | - Lekhendra Tripathee
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Chaoliu Li
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China; University of Chinese Academy of Sciences, Beijing 100049, China
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Rodríguez J, Villalobos AM, Castro-Molinare J, Jorquera H. Local and NON-LOCAL source apportionment of black carbon and combustion generated PM 2.5. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 346:123568. [PMID: 38382732 DOI: 10.1016/j.envpol.2024.123568] [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: 11/05/2023] [Revised: 02/11/2024] [Accepted: 02/12/2024] [Indexed: 02/23/2024]
Abstract
Current methods for measuring black carbon aerosol (BC) by optical methods apportion BC to fossil fuel and wood combustion. However, these results are aggregated: local and non-local combustion sources are lumped together. The spatial apportioning of carbonaceous aerosol sources is challenging in remote or suburban areas because non-local sources may be significant. Air quality modeling would require highly accurate emission inventories and unbiased dispersion models to quantify such apportionment. We propose FUSTA (FUzzy SpatioTemporal Apportionment) methodology for analyzing aethalometer results for equivalent black carbon coming from fossil fuel (eBCff) and wood combustion (eBCwb). We applied this methodology to ambient measurements at three suburban sites around Santiago, Chile, in the winter season 2021. FUSTA results showed that local sources contributed ∼80% to eBCff and eBCwb in all sites. By using PM2.5 - eBCff and PM2.5 - eBCwb scatterplots for each fuzzy cluster (or source) found by FUSTA, the estimated lower edge lines showed distinctive slopes in each measurement site. These slopes were larger for non-local sources (aged aerosols) than for local ones (fresh emissions) and were used to apportion combustion PM2.5 in each site. In sites Colina, Melipilla and San Jose de Maipo, fossil fuel combustion contributions to PM2.5 were 26 % (15.9 μg m-3), 22 % (9.9 μg m-3), and 22 % (7.8 μg m-3), respectively. Wood burning contributions to PM2.5 were 22 % (13.4 μg m-3), 19 % (8.9 μg m-3) and 22% (7.3 μg m-3), respectively. This methodology generates a joint source apportionment of eBC and PM2.5, which is consistent with available chemical speciation data for PM2.5 in Santiago.
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Affiliation(s)
- Jessika Rodríguez
- Departamento de Ingeniería Química y Bioprocesos, Pontificia Universidad Católica de Chile, Avda. Vicuña Mackenna 4860, Santiago 7820436, Chile; Center for Sustainable Urban Development (CEDEUS), Los Navegantes 1963, Providencia, Santiago 7520246, Chile
| | - Ana María Villalobos
- Departamento de Ingeniería Química y Bioprocesos, Pontificia Universidad Católica de Chile, Avda. Vicuña Mackenna 4860, Santiago 7820436, Chile
| | - Julio Castro-Molinare
- Gestion Ambiental Consultores, General del Canto 421, piso 6, Santiago 7500588, Chile
| | - Héctor Jorquera
- Departamento de Ingeniería Química y Bioprocesos, Pontificia Universidad Católica de Chile, Avda. Vicuña Mackenna 4860, Santiago 7820436, Chile; Center for Sustainable Urban Development (CEDEUS), Los Navegantes 1963, Providencia, Santiago 7520246, Chile.
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Li W, Wang Y, Yi Z, Guo B, Chen W, Che H, Zhang X. Evaluation of MERRA-2 and CAMS reanalysis for black carbon aerosol in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 343:123182. [PMID: 38123119 DOI: 10.1016/j.envpol.2023.123182] [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: 10/06/2023] [Revised: 11/24/2023] [Accepted: 12/15/2023] [Indexed: 12/23/2023]
Abstract
Black carbon (BC) constitutes a pivotal component of atmospheric aerosols, significantly impacting regional and global radiation balance, climate, and human health. In this study, we evaluated BC data in two prominent atmospheric composition reanalysis datasets: the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and the Copernicus Atmosphere Monitoring Service (CAMS), and analyzed the causes of their deviations. This assessment is based on observational data collected from 34 monitoring stations across China from 2006 to 2022. Our research reveals a significant and consistent decline in BC concentrations within China, amounting to a reduction exceeding 67.33%. However, both MERRA-2 and CAMS reanalysis data fail to capture this declining trend. The average annual decrease of BC in MERRA-2 from 2006 to 2022 is only 0.06 μg/m3 per year, while the BC concentration in CAMS even increased with an average annual value of 0.014 μg/m3 per year. In 2022, MERRA-2 had overestimated BC concentration by 20% compared to observational data, while CAMS had overestimated it by approximately 66%. In the regional BC concentration analysis, the data quality of the reanalysis data is better in the South China (RM = 0.59, RC = 0.53), followed by the North China (RM = 0.50, RC = 0.42). Reanalysis BC data in Northwest China and the Tibetan Plateau are difficult to use for practical analysis due to their big difference with observation. In a comparison of the anthropogenic BC emissions inventory used in the two atmospheric composition reanalysis datasets with the Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC) emissions inventory, we found that: Despite the significant decline in China's BC emissions, MERRA-2 still relies on the 2006 emissions inventory, while CAMS utilizes emission inventories that even show an increasing trend. These factors will undoubtedly lead to greater deviations between reanalysis and observational data.
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Affiliation(s)
- Weijie Li
- State Key Laboratory of Severe Weather & Institute of Artificial Intelligence for Meteorology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
| | - Yaqiang Wang
- State Key Laboratory of Severe Weather & Institute of Artificial Intelligence for Meteorology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China.
| | - Ziwei Yi
- State Key Laboratory of Severe Weather & Institute of Artificial Intelligence for Meteorology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bin Guo
- Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Shanghai, 200433, China
| | - Wencong Chen
- Wenzhou Meteorological Bureau, Wenzhou, 325000, China
| | - Huizheng Che
- State Key Laboratory of Severe Weather & Institute of Artificial Intelligence for Meteorology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
| | - Xiaoye Zhang
- State Key Laboratory of Severe Weather & Institute of Artificial Intelligence for Meteorology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
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Chen P, Kang S, Gan Q, Yu Y, Yuan X, Liu Y, Tripathee L, Wang X, Li C. Concentrations and light absorption properties of PM 2.5 organic and black carbon based on online measurements in Lanzhou, China. J Environ Sci (China) 2023; 131:84-95. [PMID: 37225383 DOI: 10.1016/j.jes.2022.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 04/21/2022] [Accepted: 08/02/2022] [Indexed: 05/26/2023]
Abstract
To elucidate the variations in mass concentrations of organic carbon (OC) and black carbon (BC) in PM2.5 and their light absorption characteristics in Lanzhou, we conducted one-year online measurements by using a newly developed total carbon analyzer (TCA08) coupled with an aethalometer (AE33) from July 2018 to July 2019. The mean OC and BC concentrations were 6.4 ± 4.4 and 2.0 ± 1.3 µg/m3, respectively. Clear seasonal variations were observed for both components, with winter having the highest concentrations, followed by autumn, spring, and summer. The diurnal variations of OC and BC concentrations were similar throughout the year, with daily two peaks occurring in the morning and evening, respectively. A relatively low OC/BC ratio (3.3 ± 1.2, n = 345) were observed, indicating that fossil fuel combustion was the primary source of the carbonaceous components. This is further substantiated by relatively low biomass burning contribution (fbiomass: 27.1% ± 11.3%) to BC using aethalometer based measurement though fbiomass value which increased significantly in winter (41.6% ± 5.7%). We estimated a considerable brown carbon (BrC) contribution to the total absorption coefficient (babs) at 370 nm (yearly average of 30.8% ± 11.1%), with a winter maximum of 44.2% ± 4.1% and a summer minimum of 19.2% ± 4.2%. Calculation of the wavelength dependence of total babs revealed an annual mean AAE370-520 value of 4.2 ± 0.5, with slightly higher values in spring and winter. The mass absorption cross-section of BrC also exhibited higher values in winter, with an annual mean of 5.4 ± 1.9 m2/g, reflecting the impact of emissions from increased biomass burning on BrC concentrations.
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Affiliation(s)
- Pengfei Chen
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shichang Kang
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Qinyi Gan
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Ye Yu
- Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, CAS, Lanzhou 730000, China
| | - Xianlei Yuan
- Xinjiang Bayingolin Mongolian Autonomous Prefecture Meteorological Bureau, Korla 841000, China
| | - Yajun Liu
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
| | - Lekhendra Tripathee
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
| | - Xiaoxiang Wang
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
| | - Chaoliu Li
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China; University of Chinese Academy of Sciences, Beijing 100049, China
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Cui C, Liu Y, Chen L, Liang S, Shan M, Zhao J, Liu Y, Yu S, Sun Y, Mao J, Zhang H, Gao S, Ma Z. Assessing public health and economic loss associated with black carbon exposure using monitoring and MERRA-2 data. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 313:120190. [PMID: 36122658 DOI: 10.1016/j.envpol.2022.120190] [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: 11/10/2021] [Revised: 09/10/2022] [Accepted: 09/12/2022] [Indexed: 06/15/2023]
Abstract
Black carbon (BC) exposure in China continues to be relatively high, prompting researchers to assess BC exposure levels using data from monitoring sites, satellite remote sensing, and models. However, data regarding the application of a combined strategy comprising the analysis of monitoring data and various types of data to simulate BC exposure levels are lacking. Hence, the current study seeks to estimate short- and long-term BC exposure levels by combining national monitoring data with data from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2). Furthermore, this study attempts to improve the spatio-temporal resolution of BC exposure levels using Bayesian maximum entropy (BME). The BME model performed well in terms of estimating short- (R2 = 0.74 and RMSE = 1.76 μg/m3) and long-term (R2 = 0.76 and RMSE = 1.3 μg/m3) exposure. Premature mortalities and economic losses were also assessed by applying localised concentration-response coefficients simulated in China. A total of 74,500 (95% confidence interval (CI): 23,900-124,500) and 538,400 (95% CI: 495,000-581,300) all-cause premature mortality cases were found to be associated with short- and long-term BC exposure, respectively. Meanwhile, short-term BC exposure was associated with economic losses ranging from 7.5 to 13.2 billion US dollars (USD) (1 USD = 6.36 RMB on January 19, 2022) based on amended human capital (AHC) and willingness to pay (WTP), accounting for 0.06%-0.1% of China's total gross domestic product (GDP) in 2017 (1.2 × 104 billion USD), respectively. The economic losses for long-term exposure varied from 53 to 93.2 billion USD based on AHC and WTP, accounting for 0.4%-0.8% of China's total GDP in 2017, respectively.
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Affiliation(s)
- Chen Cui
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China
| | - Yusi Liu
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry of China Meteorology Administration, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
| | - Li Chen
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China.
| | - Shuang Liang
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China
| | - Mei Shan
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China
| | - Jingwen Zhao
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China
| | - Yaxin Liu
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China
| | - Shunbang Yu
- School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Yanling Sun
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China
| | - Jian Mao
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China
| | - Hui Zhang
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China
| | - Shuang Gao
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China
| | - Zhenxing Ma
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China
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Xie F, Lin YC, Ren L, Gul C, Wang JQ, Cao F, Zhang YX, Xie T, Wu JY, Zhang YL. Decrease of atmospheric black carbon and CO 2 concentrations due to COVID-19 lockdown at the Mt. Waliguan WMO/GAW baseline station in China. ENVIRONMENTAL RESEARCH 2022; 211:112984. [PMID: 35245534 PMCID: PMC8887961 DOI: 10.1016/j.envres.2022.112984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 01/22/2022] [Accepted: 02/18/2022] [Indexed: 06/14/2023]
Abstract
The Coronavirus Disease 2019 (COVID-19) lockdown policy reduced anthropogenic emissions and impacted the atmospheric chemical characteristics in Chinese urban cities. However, rare studies were conducted at the high mountain site. In this work, in-situ measurements of light absorption by carbonaceous aerosols and carbon dioxide (CO2) concentrations were conducted at Waliguan (WLG) over the northeastern Tibetan Plateau of China from January 3 to March 30, 2020. The data was employed to explore the influence of the COVID-19 lockdown on atmospheric chemistry in the background-free troposphere. During the sampling period, the light absorption near-infrared (>470 nm) was mainly contributed by BC (>72%), however, BC and brown carbon (BrC) contributed equally to light absorption in the short wavelength (∼350 nm). The average BC concentrations in the pre-, during and post-lockdown were 0.28 ± 0.25, 0.18 ± 0.16, and 0.28 ± 0.20 μg m-3, respectively, which decreased by approximately 35% during the lockdown period. Meanwhile, CO2 also showed slight decreases during the lockdown period. The declined BC was profoundly attributed to the reduced emissions (∼86%), especially for the combustion of fossil fuels. Moreover, the declined light absorption of BC, primary and secondary BrC decreased the solar energy absorbance by 35, 15, and 14%, respectively. The concentration weighted trajectories (CWT) analysis suggested that the decreased BC and CO2 at WLG were exclusively associated with the emission reduction in the eastern region of WLG. Our results highlighted that the reduced anthropogenic emissions attributed to the lockdown in the urban cities did impact the atmospheric chemistry in the free troposphere of the Tibetan Plateau.
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Affiliation(s)
- Feng Xie
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Yu-Chi Lin
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Lei Ren
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China; Mt. Waliguan Background Station, China Meteorological Administration (CMA), Qinghai, China
| | - Chaman Gul
- Reading Academy, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, 210044, China
| | - Jian-Qiong Wang
- Mt. Waliguan Background Station, China Meteorological Administration (CMA), Qinghai, China
| | - Fang Cao
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Yi-Xuan Zhang
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Tian Xie
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Ji-Yan Wu
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Yan-Lin Zhang
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
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Liu X, Zheng M, Liu Y, Jin Y, Liu J, Zhang B, Yang X, Wu Y, Zhang T, Xiang Y, Liu B, Yan C. Intercomparison of equivalent black carbon (eBC) and elemental carbon (EC) concentrations with three-year continuous measurement in Beijing, China. ENVIRONMENTAL RESEARCH 2022; 209:112791. [PMID: 35101394 DOI: 10.1016/j.envres.2022.112791] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Revised: 12/31/2021] [Accepted: 01/20/2022] [Indexed: 06/14/2023]
Abstract
Due to the lack of black carbon (BC) measurement data in some cases, elemental carbon (EC) is often used as a surrogate of BC, with a simple assumption that they are interchangeable. Such assumption will inevitably lead to uncertainties in radiative forcing estimation and health impact assessment. In order to quantitatively and systematically evaluate the relationship between BC and EC as well as factors responsible for their difference, 3-year collocated equivalent BC (eBC) and EC measurements with 1-h resolution were performed in Beijing, China continuously from 2016 to 2019. EBC concentration was measured by the multi-wavelength aethalometer (AE-33) based on optical analysis, while EC concentration was determined by semi-continuous OC/EC analyzer with thermal-optical method. The results showed that around 90% of eBC concentration was higher than that of EC, with average difference between eBC and EC as 1.21 μg m-3 (accounting for 33% of average eBC in Beijing). EBC and EC concentrations exhibited strong correlation (r = 0.90) during the whole study period, but the slopes (or eBC/EC ratio) and correlation coefficients varied across seasons (spring: 1.67 and 0.94; summer: 0.91 and 0.65; fall: 1.15 and 0.88; winter: 1.09 and 0.91, respectively). Based on the information from shell/core ratios by Single Particle Soot Photometer (SP2), source apportionment results by positive matrix factorization model, and chemical composition of PM2.5, the differences between eBC and EC concentrations were found to be primarily related to BC aging process and secondary components as evidenced by strong positive correlation with secondary species (e.g., secondary organic carbon and nitrate). This study provided seasonal specific conversion factors of eBC and EC in Beijing and helpful reference for other areas, which will contribute new knowledge of carbonaceous aerosol and reduce uncertainty in assessing future climate change and health studies of BC.
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Affiliation(s)
- Xiaomeng Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Mei Zheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
| | - Yue 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
| | - Junyi Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Boya Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Xi Yang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Yazhen Wu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Tianle Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Yaxin Xiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Baoxian Liu
- Beijing Key Laboratory of Airborne Particulate Matter Monitoring Technology, Beijing Municipal Environmental Monitoring Center, Beijing, 100048, China
| | - Caiqing Yan
- Environment Research Institute, Shandong University, Qingdao, 266237, China.
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9
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Characteristics and Source Apportionment of Black Carbon (BC) in a Suburban Area of Klang Valley, Malaysia. ATMOSPHERE 2021. [DOI: 10.3390/atmos12060784] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Black carbon (BC) is of concern due to its contribution to poor air quality and its adverse effects human health. We carried out the first real-time monitoring of BC in Malaysia using an AE33 Aethalometer. Measurements were conducted between 1 January and 31 May 2020 in a university area in a suburban location of the Klang Valley. The measurement period coincided with the implementation of a movement control order (MCO) in response to COVID-19. The mean concentration of BC before the MCO was 2.34 µg/m3 which decreased by 38% to 1.45 µg/m3 during the MCO. The BC is dominated by fossil-fuel sources (mean proportion BCff = 79%). During the MCO, the BCff concentration decreased by more than the BCbb concentration derived from biomass burning. BC and BCff show very strong diurnal cycles, which also show some weekday–weekend differences, with maxima during the night and just before noon, and minima in the afternoon. These patterns indicate strong influences on concentrations from both traffic emissions and boundary layer depth. BC was strongly correlated with NO2 (R = 0.71), another marker of traffic emission, but less strongly with PM2.5 (R = 0.52). The BC absorption Ångström exponent (AAE) ranged between 1.1 and 1.6. We observed pronounced diurnal cycles of lower AAE in daytime, corresponding to BCff contributions from traffic. Average AAE also showed a pronounced increase during the MCO. Our data provides a new reference for BC in suburban Malaysia for the public and policy-makers, and a baseline for future measurements.
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10
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Temporal Variability of Equivalent Black Carbon Components in Atmospheric Air in Southern Poland. ATMOSPHERE 2021. [DOI: 10.3390/atmos12010119] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This study assesses the air quality in Zabrze (southern Poland) based on the ambient concentrations of equivalent black carbon (eBC). eBC measurement campaigns were carried out from April 2019 to March 2020 using a modern AE33 Aethalometer, accompanied by parallel measurements of gaseous pollutants, PM10 and meteorological parameters. The use of the two-component AE33 model allows for the determination of the eBC from fossil fuel combustion (eBCff) and biomass burning (eBCbb). The obtained results showed a clear seasonal variability of eBC concentrations, with higher average levels in the heating season (4.70 µg·m−3) compared to the non-heating one (1.79 µg·m−3). In both seasons, the eBCff component had a dominant share in total eBC, which indicates significant emissions from the combustion of fossil fuels for heating purposes and from local traffic sources. The obtained results showed high correlation coefficients with gaseous and particulate pollutants, with the strongest relationship for eBC and carbon monoxide (CO). During the non-heating and heating period, both anticyclone and cyclone systems played an important role in shaping eBC, eBCff and eBCbb concentrations. High concentrations of all components occurred with a significant decrease in air temperature and solar radiation in winter.
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11
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Aerosol Direct Radiative Effects over China Based on Long-Term Observations within the Sun–Sky Radiometer Observation Network (SONET). REMOTE SENSING 2020. [DOI: 10.3390/rs12203296] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
To investigate aerosol radiative effects, the Sun–Sky Radiometer Observation Network (SONET) has performed long-term observations of columnar atmospheric aerosol properties at 20 distributed stations around China. The aerosol direct radiative forcing (RF) and efficiency (RFE, the rate at which the atmosphere is forced per unit of aerosol optical depth) were estimated using radiative transfer model simulations based on the ground-based observations dating back to 2009. Results of multi-year monthly average RF illustrated that: the dust-dominant aerosol population at arid and semi-arid sites exerted moderate cooling effects (−8.0~−31.2 W/m2) at the top and bottom of atmosphere (TOA and BOA); RF at continental background site was very weak (−0.8~−2.9 W/m2); fine-mode dominant aerosols at urban and suburban sites exerted moderate cooling effects (−9.3~−24.1 W/m2) at TOA but more significant cooling effects (−19.4~−50.6 W/m2) at BOA; RF at coastal sites was comparable with values of urban sites (−5.5~−19.5 W/m2 at TOA, and −15.6~−44.6 W/m2 at BOA), owing to combined influences by marine and urban–industrial aerosols. Differences between RFE at TOA and BOA indicated that coarse-mode dominant aerosols at arid, semi-arid, and continental background sites were less efficient to warm the atmosphere; but fine-mode dominant aerosols at urban, suburban, and coastal sites were shown to be more efficient to heat the atmosphere.
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