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Zhao X, Song M, Zhao X, Xue C, Liu P, Ye C, He X, Mu Y, Hu B. Improvement of model simulation for summer PM 2.5 and O 3 through coupling with two new potential HONO sources in the North China Plain. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 950:175168. [PMID: 39094653 DOI: 10.1016/j.scitotenv.2024.175168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 07/11/2024] [Accepted: 07/29/2024] [Indexed: 08/04/2024]
Abstract
A large fraction of fine particulate matter (PM2.5) and ozone (O3) in the troposphere originates from secondary formation through photochemical processes, which remarkably contributes to the deterioration of regional air quality in China. The photochemical reactions initiated by hydroxyl radicals (OH) play vital roles in secondary PM2.5 and O3 formation. In contrast, the OH levels in polluted areas are underestimated by current chemical transport models (CTMs) because of the strongly unknown daytime sources of tropospheric nitric acid (HONO), which has been recognized as the dominant source of primary OH in polluted areas of China. In this study, the atmospheric HONO levels at two urban sites were found to be significantly underestimated by the WRF-Chem model based on available information on HONO sources. The HONO levels could be well reproduced by the WRF-Chem model after incorporating two new potential HONO sources from the photochemical reactions of NOx, as proposed in our previous study based on chamber experiment results. Comparing the simulations with available information of HONO sources, the simulated levels of atmospheric OH, secondary inorganic and organic aerosols (SIA and SOA), PM2.5 and daily maximum 8-h average (MDA8) O3 were evidently elevated or were closer to the observations over the North China Plain (NCP), with elevation percentages of 0.48-20.1 %, and a decrement percentage of -5.79 % for pNO3-. Additionally, the compensating errors in modeling PM2.5 and the gap in MDA8 O3 levels between observation and simulation in 2 + 26 cities became evidently smaller. The results of this study indicated that the empirical parameterization of two new potential HONO sources through photochemical reactions of NOx improved the model performance in modeling PM2.5 and O3 by narrowing the gap in daytime HONO levels between simulation and observation, although their detailed chemical mechanisms are still unknown and should be further investigated and explicitly parameterized.
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Affiliation(s)
- Xiaoxi Zhao
- Key Laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing 100089, China
| | - Min Song
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; School of Municipal and Environmental Engineering, Shandong Jianzhu University, Ji'nan 250101, China
| | - Xiujuan Zhao
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing 100089, China
| | - Chaoyang Xue
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Max Planck Institute for Chemistry, Mainz 55128, Germany
| | - Pengfei Liu
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Can Ye
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China
| | - Xiaowei He
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yujing Mu
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Bo Hu
- Key Laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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2
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Yan Q, Liu X, Kong S, Zhang W, Gao Q, Zhang Y, Li H, Wang H, Xiao T, Li J. Hourly emission amounts and concentration of water-soluble ions in primary particles from residential coal burning in rural northern China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 359:124641. [PMID: 39122172 DOI: 10.1016/j.envpol.2024.124641] [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: 05/20/2024] [Revised: 07/27/2024] [Accepted: 07/29/2024] [Indexed: 08/12/2024]
Abstract
Residential coal burning (RCB) stands as an important contributor to ambient pollutants in China. For the effective execution of air pollution control policies, it is essential to maintain precise emission inventories of RCB. The absence of hourly emission factors (EFs) combined with the inaccuracies in the spatial-temporal distribution of activity data, constrained the quality of residential coal combustion emission inventories, thereby impeding the estimation of air pollutant emissions. This study revised the hourly EFs for PM2.5 and water-soluble ions (WSIs) emitted from RCB in China. The hourly emission inventories for PM2.5 and WSIs derived from RCB illustrate the diurnal fluctuations in emission patterns. This study found that the emissions of PM2.5, NH4+, Cl-, and SO42- showed similar emission features with emission of 106.8 Gg, 1417.6, 356.8, and 5868.5 ton in erupt period. The results provide basic data for evaluating RCB emission reduction policies, simulating particles, and preventing air pollution in both sub-regions and time periods. The spatial emission and simulated concentration distribution of PM2.5 and WSIs indicated that emission hotspot shifted from North China Plain (NCP) to Northeast region in China. The emissions in China were well-controlled in '2 + 26' region (R28) priority region, with hotspots decreasing by 99.6% in BTH region. The RCB became the dominant contributor to ambient PM2.5 with a ratio in the range of 16.2-23.7% in non-priority region.
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Affiliation(s)
- Qin Yan
- Institute of Atmospheric Environment, Chinese Research Academy of Environmental Sciences, Beijing, China; Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan, China
| | - Xi Liu
- School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China
| | - Shaofei Kong
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan, China; Research Centre for Complex Air Pollution of Hubei Province, Wuhan, China.
| | - Wenjie Zhang
- Institute of Atmospheric Environment, Chinese Research Academy of Environmental Sciences, Beijing, China.
| | - Qingxian Gao
- Institute of Atmospheric Environment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Yuzhe Zhang
- Institute of Atmospheric Environment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Hui Li
- Institute of Atmospheric Environment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Han Wang
- Institute of Atmospheric Environment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Tingyu Xiao
- Institute of Atmospheric Environment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Junhong Li
- Institute of Atmospheric Environment, Chinese Research Academy of Environmental Sciences, Beijing, China
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3
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Quan J, Huo J, Zhang C, Pan Y, Ma P, Liao Z, Cheng Z, Jia X, Wang Q, Fu Q, Mu Y, Hu F. High organic aerosol in the low layer over a rural site in the North China Plain (NCP): Observations based on large tethered balloon. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 915:170039. [PMID: 38219998 DOI: 10.1016/j.scitotenv.2024.170039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 01/02/2024] [Accepted: 01/07/2024] [Indexed: 01/16/2024]
Abstract
High mass concentration of organic aerosol (OA) and its fraction in PM2.5 (particle matter with radius <2.5 μm) were observed in the low layer over a rural site of the North China Plain (NCP) in winter 2018. The mass fraction of OA in PM2.5 was 65.5 % at ground level (5 m above ground), and decreased to 37.1 % in layer of 200-1000 m. In addition, there was a sharp decrease of OA at around the top of planetary boundary layer (PBL), which was distinctly different from the vertical distributions of secondary inorganic aerosols (SIA, e.g., nitrate (NO3-), ammonium (NH4+), and sulfate (SO42-)). The altitude with sharp decrease of OA was very low in the morning and evening, e.g., the sharp decrease of OA occurred at a height <50 m at nighttime on Dec. 19, while was elevated in the noon with the PBL development. Furthermore, OA at ground level exhibited a distinct diurnal variation with a night-to-day ratio of 2.3, which was much larger than those of SIA and inactive CO. All the above results indicated the extremely high OA concentration at the rural site was mainly attributed to direct emission from local sources, such as the combustion of coal and biomass for heating. The extremely high OA could be expected in vest rural areas of the NCP in winter because the farmer activities are very similar to the investigated rural site, underscoring the urgency to mitigate OA emission in rural area for improving the local as well as the regional air quality.
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Affiliation(s)
- Jiannong Quan
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing 100089, China.
| | - Juntao Huo
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Chenglong Zhang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yubing Pan
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing 100089, China
| | - Pengkun Ma
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing 100089, China
| | - Zhiheng Liao
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing 100089, China
| | - Zhigang Cheng
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing 100089, China
| | - Xingcan Jia
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing 100089, China
| | - Qianqian Wang
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing 100089, China
| | - Qingyan Fu
- Shanghai Environmental Monitoring Center, Shanghai 200235, China; Shanghai Academy of Environmental Sciences, Shanghai 200235, China.
| | - Yujing Mu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Fei Hu
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
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Zhao X, Zhao X, Liu P, Chen D, Zhang C, Xue C, Liu J, Xu J, Mu Y. Transport Pathways of Nitrate Formed from Nocturnal N 2O 5 Hydrolysis Aloft to the Ground Level in Winter North China Plain. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:2715-2725. [PMID: 36722840 DOI: 10.1021/acs.est.3c00086] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Particulate nitrate (NO3-) has currently become the major component of fine particles in the North China Plain (NCP) during winter haze episodes. However, the contributions of formation pathways to ground NO3- in the NCP are not fully understood. Herein, the NO3- formation pathways were comprehensively investigated based on model simulations combined with two-month field measurements at a rural site in the winter NCP. The results indicated that the nocturnal chemistry of N2O5 hydrolysis aloft could contribute evidently to ground NO3- at the rural site during the pollution episodes with high aerosol water contents, achieving the contribution percentages of 25.2-30.4% of the total. In addition to the commonly proposed vertical mixing of breaking nocturnal boundary layer in the early morning, two additional transport pathways (frontal downdrafts and downslope mountain breezes) in the nighttime were found to make higher contributions to ground NO3-. Considering the dominant role (69.6-74.8%) of diurnal chemistry in NO3- formation, reduction of NOx emissions in the daytime may be an effective control measure for reducing regional NO3- in the NCP.
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Affiliation(s)
- Xiaoxi Zhao
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing100085, China
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing100089, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Xiujuan Zhao
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing100089, China
| | - Pengfei Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing100085, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Dan Chen
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing100089, China
| | - Chenglong Zhang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing100085, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Chaoyang Xue
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing100085, China
- Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), CNRS-Université Orléans-CNES, CEDEX 2, Orléans45071, France
| | - Junfeng Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing100085, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Jing Xu
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing100089, China
| | - Yujing Mu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing100085, China
- University of Chinese Academy of Sciences, Beijing100049, China
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5
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Li Z, Liu J, Zhai Z, Liu C, Ren Z, Yue Z, Yang D, Hu Y, Zheng H, Kong S. Heterogeneous changes of chemical compositions, sources and health risks of PM 2.5 with the "Clean Heating" policy at urban/suburban/industrial sites. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 854:158871. [PMID: 36126707 DOI: 10.1016/j.scitotenv.2022.158871] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 09/05/2022] [Accepted: 09/15/2022] [Indexed: 06/15/2023]
Abstract
China has enacted the "Clean Heating" (CH) policy in north China. The domain-specific impacts on PM2.5 constituents and sources in small cities are still lacking, which obstruct the further policy optimization. Here, we performed an intensive observation covering the heating period (HP) and pre-heating period (PHP) in winter of 2017 at urban (UR), industrial (IS), and suburban (SUR) sites in one of the "2 + 26" cities. The mean PM2.5 concentrations at UR and IS decreased by 15.2 % and 4.6 %, while increased by 9.8 % at SUR in the HP compared with the PHP, indicating the heterogeneous responses. The lowest contribution percentages of coal combustion (14.6 %) and industrial emissions (17.1 %) to PM2.5 at UR in the HP implied the CH policy played more effective role. The most increase in NO3-/SO42- ratio by 26.8 % and the highest NO3- concentration at UR in the HP were linked mainly with the thermal-NOx emitted from natural gas (NG) burning in view of NOx emission reductions from other sources. The highest concentrations of OC, SO42-, K+, and Cl-, and contribution percentages of biomass burning (20.0 %) and coal combustion (24.8 %) to PM2.5 at SUR in the HP evidenced the enhanced usage of biomass/coal. Coal banning in the HP at IS and UR led to the obvious decreases in OC, SO42-, As, and Sb. Secondary nitrate became the largest PM2.5 source at IS and UR in the HP. Coal banning, emission control on large-size enterprises and ignored control on small-size enterprises efficiently modified the concentrations and health risks of heavy metals. The lowest carcinogenic risks moved from SUR in the PHP to UR in the HP. The policies on de-NOx of NG-burning related enterprises, reduction of biomass/coal usage in suburban area, and strict regulation of small-size enterprises were urgently need to further improve the air quality.
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Affiliation(s)
- Zhiyong Li
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University, Baoding 071003, China; MOE Key Laboratory of Resources and Environmental Systems Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China.
| | - Jixiang Liu
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University, Baoding 071003, China
| | - Zhen Zhai
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University, Baoding 071003, China
| | - Chen Liu
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University, Baoding 071003, China
| | - Zhuangzhuang Ren
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University, Baoding 071003, China
| | - Ziyuan Yue
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University, Baoding 071003, China
| | - Dingyuan Yang
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University, Baoding 071003, China
| | - Yao Hu
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074,China
| | - Huang Zheng
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074,China
| | - Shaofei Kong
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074,China.
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6
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Hong X, Yang K, Liang H, Shi Y. Characteristics of Water-Soluble Inorganic Ions in PM 2.5 in Typical Urban Areas of Beijing, China. ACS OMEGA 2022; 7:35575-35585. [PMID: 36249358 PMCID: PMC9558696 DOI: 10.1021/acsomega.2c02919] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 09/16/2022] [Indexed: 06/16/2023]
Abstract
Following the implementation of "coal-to-gas conversion" policy in the Haidian District of Beijing during summer, the present comparative study was performed employing 41 PM2.5 samples as precursors to analyze the characteristics of water-soluble inorganic ions. The concentrations of water-soluble inorganic ions in PM2.5 were analyzed by ion chromatography, and the occurrence form of ions was characterized via time-of-flight secondary ion mass spectrometry (TOF-SIMS). Results revealed that the daily average mass concentration of PM2.5 in Beijing during the sampling period was 94.28 ± 52.49 μg/m3. As compared to the winter of 2016, the average daily PM2.5 concentration in Beijing decreased by 29 μg/m3 in 2017 (28.2% decrease), with a remarkable decline in the number of days with pollution. During the pollution period, the concentrations of NO3 -, SO4 2-, and NH4 + were significantly higher in PM2.5 as compared to the cleaning period. The ratio of the concentrations of [NO3 -]/[SO4 2-] was greater than 1, and the contribution from mobile sources was relatively large, indicating that the implementation of the "coal-to-gas conversion" policy in Beijing has led to the reduction of SO4 2- emissions from fixed sources, such as coal. Furthermore, TOF-SIMS analysis results showed that NH4 + tended to exist in the form of molecular ammonium sulfate or ammonium hydrogen sulfate during the period of pollution.
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Affiliation(s)
- Xiuping Hong
- Huaibei
Normal University, Huaibei 235000, China
| | - Kang Yang
- School
of Chemical & Environmental Engineering, CUMTB, Beijing 100083, China
| | - Handong Liang
- State
Key Laboratory of Coal Resources and Safe Mining, CUMTB, Beijing 100083, China
| | - Yunyun Shi
- School
of Chemical & Environmental Engineering, CUMTB, Beijing 100083, China
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Wang Z, Yan J, Zhang P, Li Z, Guo C, Wu K, Li X, Zhu X, Sun Z, Wei Y. Chemical characterization, source apportionment, and health risk assessment of PM 2.5 in a typical industrial region in North China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:71696-71708. [PMID: 35604610 DOI: 10.1007/s11356-022-19843-2] [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: 11/25/2021] [Accepted: 03/17/2022] [Indexed: 06/15/2023]
Abstract
To clarify the chemical characteristics, source contributions, and health risks of pollution events associated with high PM2.5 in typical industrial areas of North China, manual sampling and analysis of PM2.5 were conducted in the spring, summer, autumn, and winter of 2019 in Pingyin County, Jinan City, Shandong Province. The results showed that the total concentration of 29 components in PM2.5 was 53.4 ± 43.9 μg·m-3, including OC/EC, water-soluble ions, inorganic elements, and metal elements. The largest contribution was from the NO3- ion, at 14.6 ± 14.2 μg·m-3, followed by organic carbon (OC), SO42-, and NH4+, with concentrations of 9.3 ± 5.5, 9.1 ± 6.4, and 8.1 ± 6.8 μg·m-3, respectively. The concentrations of OC, NO3-, and SO42- were highest in winter and lowest in summer, whereas the NH4+ concentration was highest in winter and lowest in spring. Typical heavy metals had higher concentrations in autumn and winter, and lower concentrations in spring and summer. The annual average sulfur oxidation rate (SOR) and nitrogen oxidation rate (NOR) were 0.30 ± 0.14 and 0.21 ± 0.12, respectively, with the highest SO2 emission and conversion rates in winter, resulting in the SO42- concentration being highest in winter. The average concentration of secondary organic carbon in 2019 was 2.8 ± 1.9 μg·m-3, and it comprised approximately 30% of total OC. The concentrations of 18 elements including Na, Mg, and Al were between 2.3 ± 1.6 and 888.1 ± 415.2 ng·m-3, with Ni having the lowest concentration and K the highest. The health risk assessment for typical heavy metals showed that Pb poses a potential carcinogenic risk for adults, whereas As may pose a carcinogenic risk for adults, children, and adolescents. The non-carcinogenic risk coefficients for all heavy metals were lower than 1.0, indicating that the non-carcinogenic risk was negligible. Positive matrix factorization analysis indicated that coal-burning emissions contributed the largest fraction of PM2.5, accounting for 35.9% of the total. The contribution of automotive emissions is similar to that of coal, at 32.1%. The third-largest contributor was industrial sources, which accounted for 17.2%. The contributions of dust and other emissions sources to PM2.5 were 8.4% and 6.4%, respectively. This study provides reference data for policymakers to improve the air quality in the NCP.
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Affiliation(s)
- Zhanshan Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Jiayi Yan
- The Ecological Environment Monitoring Center of Linyi, Shandong province, Linyi, 276000, China
| | - Puzhen Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Zhigang Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Chen Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Kai Wu
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, 610225, China
- Department of Land, Air, and Water Resources, University of California, Davis, CA, USA
| | - Xiaoqian Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Xiaojing Zhu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Zhaobin Sun
- Institute of Urban Meteorology, China Meteorological Administration, Beijing, 100089, China
| | - Yongjie Wei
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
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8
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He Z, Liu P, Zhao X, He X, Liu J, Mu Y. Responses of surface O 3 and PM 2.5 trends to changes of anthropogenic emissions in summer over Beijing during 2014-2019: A study based on multiple linear regression and WRF-Chem. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 807:150792. [PMID: 34619192 DOI: 10.1016/j.scitotenv.2021.150792] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 09/29/2021] [Accepted: 09/30/2021] [Indexed: 06/13/2023]
Abstract
Owing to the implementation of air pollution control actions, anthropogenic emissions in Beijing have changed in recent years. Understanding the impact of changes in anthropogenic emissions on O3 and PM2.5 trends is helpful for developing air quality management strategies. Herein, we investigated the variations of air pollutants in summer over Beijing using long-term data sets from 2014 to 2019, and explored the responses of O3 and PM2.5 trends to changes in anthropogenic emissions based on multiple linear regression (MLR) analysis and WRF-Chem model. The results indicated a significant decrease in PM2.5, but a near constant level of O3 during 2014-2019. The decrease rate of PM2.5, which was lower than that of SO2, might be due to the effect of NO2 on atmospheric PM2.5. Both the slightly increasing correlations between PM2.5 and NO2 and the WRF-Chem model simulations implied that atmospheric PM2.5 in Beijing is trending to be more sensitive to NOx than SO2. The emissions of NOx and VOCs from industry and transportation were found to make great contribution to O3 production in Beijing. Due to the titration of NOx in VOC-limited regime, the relatively low emission ratios of NOx and VOCs from industry and transportation in Beijing provided convincing evidence for the persistently high O3 concentrations during 2014-2019. However, the noticeable increase of the O3 trends in other areas (e.g., Hebei, Tianjin) could be explained by the significant decline in the emission ratios of NOx and VOCs from anthropogenic emissions especially industry during 2014-2019. Controlling the emission of NOx can substantially reduce PM2.5 pollution, but may aggravate O3 pollution, and thus effective VOC emission control strategies need to be considered for simultaneously controlling O3 and PM2.5 pollution in Beijing and other regions of China.
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Affiliation(s)
- Zhouming He
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, 100049, China
| | - Pengfei Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; Center for Excellence in Urban Atmospheric Environment, Institute of Regional Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Xiaoxi Zhao
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, 100049, China
| | - Xiaowei He
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, 100049, China
| | - Junfeng Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, 100049, China; Center for Excellence in Urban Atmospheric Environment, Institute of Regional Environment, Chinese Academy of Sciences, Xiamen 361021, China.
| | - Yujing Mu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, 100049, China; Center for Excellence in Urban Atmospheric Environment, Institute of Regional Environment, Chinese Academy of Sciences, Xiamen 361021, China
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9
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Zhu X, Shen J, Li Y, Liu X, Xu W, Zhou F, Wang J, Reis S, Wu J. Nitrogen emission and deposition budget in an agricultural catchment in subtropical central China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 289:117870. [PMID: 34385131 DOI: 10.1016/j.envpol.2021.117870] [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: 01/31/2021] [Revised: 06/14/2021] [Accepted: 07/28/2021] [Indexed: 06/13/2023]
Abstract
The study of emissions and depositions of atmospheric reactive nitrogen species (Nrs) in a region is important to uncover the sources and sinks of atmospheric Nrs in the region. In this study, atmospheric total Nrs depositions including both wet-only and dry deposition were monitored simultaneously across major land-use types in a 105 km2 catchment called Jinjing River Catchment (JRC) in subtropical central China from 2015 to 2016. Based on activity data and emission factors for the main Nrs emission sources, ammonia (NH3) and nitrogen oxides (NOx) emission inventories for the catchment were also compiled. The estimated total Nrs deposition in JRC was 35.9 kg N ha-1 yr-1, with approximately 49.7 % attributed to reduced compounds (NHx), and 40.5 % attributed to oxidized (NOy). The total Nrs emission rate in JRC was 80.4 kg N ha-1 yr-1, with 61.5 and 18.9 kg N ha-1 yr-1 from NH3 and NOx emissions, respectively. Livestock excretion and fertilization were the two main contributing emission sources for NH3, while vehicle sources contributed the bulk of NOx emissions. The net atmospheric budgets of Nrs in paddy field, forest, and tea field were +3.7, -36.1, and +23.8 kg N ha-1 yr-1, respectively. At the catchment scale, the net atmospheric budget of Nrs was +47.7 kg N ha-1 yr-1, with +43.7 kg N ha-1 yr-1 of NHx and +4.0 kg N ha-1 yr-1 of NOy, indicating that the subtropical catchment was net sources of atmospheric Nrs. Considering that excessive atmospheric Nr emissions and deposition may cause adverse effects on the environment, effects should be conducted to mitigate the Nrs emissions from agriculture and transportation, and increasing the area of forest is good for reducing the net positive budget of atmospheric Nrs in the subtropical catchments in China.
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Affiliation(s)
- Xiao Zhu
- Key Laboratory of Agro-ecological Processes in Subtropical Region and Changsha Research Station for Agricultural & Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jianlin Shen
- Key Laboratory of Agro-ecological Processes in Subtropical Region and Changsha Research Station for Agricultural & Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China.
| | - Yong Li
- Key Laboratory of Agro-ecological Processes in Subtropical Region and Changsha Research Station for Agricultural & Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China
| | - Xuejun Liu
- College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Wen Xu
- College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Feng Zhou
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Juan Wang
- Key Laboratory of Agro-ecological Processes in Subtropical Region and Changsha Research Station for Agricultural & Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China
| | - Stefan Reis
- UK Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK; University of Exeter Medical School, European Centre for Environment and Health, Knowledge Spa, Truro, TR1 3HD, UK
| | - Jinshui Wu
- Key Laboratory of Agro-ecological Processes in Subtropical Region and Changsha Research Station for Agricultural & Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China
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Wang Y, Liu B, Zhang Y, Dai Q, Song C, Duan L, Guo L, Zhao J, Xue Z, Bi X, Feng Y. Potential health risks of inhaled toxic elements and risk sources during different COVID-19 lockdown stages in Linfen, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 284:117454. [PMID: 34062435 PMCID: PMC8164380 DOI: 10.1016/j.envpol.2021.117454] [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: 02/05/2021] [Revised: 05/19/2021] [Accepted: 05/21/2021] [Indexed: 05/09/2023]
Abstract
Levels of toxic elements in ambient PM2.5 were measured from 29 October 2019 to 30 March 2020 in Linfen, China, to assess the health risks they posed and to identify critical risk sources during different periods of the COVID-19 lockdown and haze episodes using positive matrix factorization (PMF) and a health-risk assessment model. The mean PM2.5 concentration during the study period was 145 μg/m3, and the 10 investigated toxic elements accounted for 0.31% of the PM2.5 mass. The total non-cancer risk (HI) and total cancer risk (TCR) of the selected toxic elements exceed the US EPA limits for children and adults. The HI for children was 2.3 times that for adults for all periods, which is likely due to the high inhalation rate per unit body weight for children. While the TCR for adults was 1.7 times that of children, which is mainly attributed to potential longer exposure duration for adults. The HI and TCR of the toxic elements during full lockdown were reduced by 66% and 58%, respectively, compared to their pre-lockdown levels. The HI and TCR were primarily attributable to Mn and As, respectively. Health risks during haze episodes were significantly higher than the average levels during COVID-19 lockdowns, though the HI and TCR of the selected toxic elements during full-lockdown haze episodes were 68% and 17% lower, respectively, than were the levels during pre-lockdown haze episodes. During the study period, fugitive dust and steel-related smelting were the highest contributors to HI and TCR, respectively, and decreased in these emission sources contributed the most to the lower health risks observed during the full lockdown. There, the control of these sources is critical to effectively reduce public health risks.
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Affiliation(s)
- Yanyang Wang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Congbo Song
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Liqin Duan
- Linfen Municipal Ecological and Environmental Monitoring Center of Shanxi Province, Linfen, 041000, China
| | - Lili Guo
- Linfen Municipal Ecological and Environmental Monitoring Center of Shanxi Province, Linfen, 041000, China
| | - Jing Zhao
- Linfen Municipal Ecological and Environmental Monitoring Center of Shanxi Province, Linfen, 041000, China
| | - Zhigang Xue
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Xiaohui Bi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
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11
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Ye C, Chen H, Hoffmann EH, Mettke P, Tilgner A, He L, Mutzel A, Brüggemann M, Poulain L, Schaefer T, Heinold B, Ma Z, Liu P, Xue C, Zhao X, Zhang C, Zhang F, Sun H, Li Q, Wang L, Yang X, Wang J, Liu C, Xing C, Mu Y, Chen J, Herrmann H. Particle-Phase Photoreactions of HULIS and TMIs Establish a Strong Source of H 2O 2 and Particulate Sulfate in the Winter North China Plain. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:7818-7830. [PMID: 34019409 DOI: 10.1021/acs.est.1c00561] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
During haze periods in the North China Plain, extremely high NO concentrations have been observed, commonly exceeding 1 ppbv, preventing the classical gas-phase H2O2 formation through HO2 recombination. Surprisingly, H2O2 mixing ratios of about 1 ppbv were observed repeatedly in winter 2017. Combined field observations and chamber experiments reveal a photochemical in-particle formation of H2O2, driven by transition metal ions (TMIs) and humic-like substances (HULIS). In chamber experiments, steady-state H2O2 mixing ratios of 116 ± 83 pptv were observed upon the irradiation of TMI- and HULIS-containing particles. Correspondingly, H2O2 formation rates of about 0.2 ppbv h-1 during the initial irradiation periods are consistent with the H2O2 rates observed in the field. A novel chemical mechanism was developed explaining the in-particle H2O2 formation through a sequence of elementary photochemical reactions involving HULIS and TMIs. Dedicated box model studies of measurement periods with relative humidity >50% and PM2.5 ≥ 75 μg m-3 agree with the observed H2O2 concentrations and time courses. The modeling results suggest about 90% of the particulate sulfate to be produced from the SO2 reaction with OH and HSO3- oxidation by H2O2. Overall, under high pollution, the H2O2-caused sulfate formation rate is above 250 ng m-3 h-1, contributing to the sulfate formation by more than 70%.
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Affiliation(s)
- Can Ye
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hui Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Erik H Hoffmann
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Peter Mettke
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Andreas Tilgner
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Lin He
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Anke Mutzel
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Martin Brüggemann
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Laurent Poulain
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Thomas Schaefer
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Bernd Heinold
- Modeling of Atmospheric Processes Department, Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
| | - Zhuobiao Ma
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Pengfei Liu
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chaoyang Xue
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoxi Zhao
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chenglong Zhang
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fei Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Hao Sun
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Qing Li
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Lin Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Xin Yang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Jinhe Wang
- School of Municipal and Environmental Engineering, Co-Innovation Centre for Green Building of Shandong Province, Shandong Jianzhu University, Jinan 250101, China
| | - Cheng Liu
- Centre for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Chengzhi Xing
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Yujing Mu
- Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Centre 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
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
- Centre for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Hartmut Herrmann
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
- Atmospheric Chemistry Department (ACD), Leibniz Institute for Tropospheric Research (TROPOS), Leipzig 04318, Germany
- School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China
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