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Cheng Y, Zhong YJ, Liu JM, Cao XB, Zhang Q, He KB. Response of Harbin aerosol to latest clean air actions in China. JOURNAL OF HAZARDOUS MATERIALS 2024; 467:133728. [PMID: 38335619 DOI: 10.1016/j.jhazmat.2024.133728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/20/2024] [Accepted: 02/03/2024] [Indexed: 02/12/2024]
Abstract
Cities in Northeast China, e.g., Harbin, were brought to the forefront of air pollution control by a national-level policy promulgated in 2021, i.e., the Circular on Further Promoting the Pollution Prevention and Control Battle (the FP3CB Circular) which aimed at eliminating heavy or severe air pollution events. In this study, we explored the response of Harbin aerosol to the FP3CB Circular, based on observational results from two campaigns conducted during 2020-2021 and 2021-2022. A clear decreasing trend was identified for the impact of domestic biomass burning between the two winters, presumably driven by the clean heating actions. The 2021-2022 winter was also characterized by reduced formation of secondary organic aerosol but enhanced production of nitrate, which could be attributed to the less humid conditions but higher temperatures, respectively, compared to the 2020-2021 winter. The overall effect of these changes was a decrease in the contribution of organic species to wintertime aerosol in Harbin. In addition, the number of heavy or severe pollution days rebounded in the 2021-2022 winter compared to 2020-2021 (5 vs. 3), indicating that the emissions of primary particles and gaseous precursors must be further reduced to achieve the ambitious goals of the FP3CB Circular.
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Affiliation(s)
- Yuan Cheng
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Ying-Jie Zhong
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Jiu-Meng Liu
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China.
| | - Xu-Bing Cao
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Ke-Bin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
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Wang Y, Liang L, Xu W, Liu C, Cheng H, Liu Y, Zhang G, Xu X, Yu D, Wang P, Song Q, Liu J, Cheng Y. Influence of meteorological factors on open biomass burning at a background site in Northeast China. J Environ Sci (China) 2024; 138:1-9. [PMID: 38135377 DOI: 10.1016/j.jes.2023.02.043] [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: 11/22/2022] [Revised: 02/22/2023] [Accepted: 02/22/2023] [Indexed: 12/24/2023]
Abstract
Biomass burning (BB) is a very important emission source that significantly adversely impacts regional air quality. BB produces a large number of primary organic aerosol (POA) and black carbon (BC). Besides, BB also provides many precursors for secondary organic aerosol (SOA) generation. In this work, the ratio of levoglucosan (LG) to organic carbon (OC) and the fire hotspots map was used to identify the open biomass burning (OBB) events, which occurred in two representative episodes, October 13 to November 30, 2020, and April 1 to April 30, 2021. The ratio of organic aerosol (OA) to reconstructed PM2.5 concentration (PM2.5*) increased with the increase of LG/OC. When LG/OC ratio is higher than 0.03, the highest OA/PM2.5* ratio can reach 80%, which means the contribution of OBB to OA is crucial. According to the ratio of LG to K+, LG to mannosan (MN) and the regional characteristics of Longfengshan, it can be determined that the crop residuals are the main fuel. The occurrence of OBB coincides with farmers' preferred choices, i.e., burning biomass in "bright weather". The "bright weather" refers to the meteorological conditions with high temperature, low humidity, and without rain. Meteorological factors indirectly affect regional biomass combustion pollution by influencing farmers' active choices.
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Affiliation(s)
- Yulong Wang
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Linlin Liang
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Wanyun Xu
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Chang Liu
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Hongbing Cheng
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Yusi Liu
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Gen Zhang
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Xiaobin Xu
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Dajiang Yu
- Longfengshan Regional Background Station, China Meteorological Administration, Heilongjiang 150200, China
| | - Peng Wang
- Longfengshan Regional Background Station, China Meteorological Administration, Heilongjiang 150200, China
| | - Qingli Song
- Heilongjiang Climate Center, Heilongjiang 150030, China
| | - Jiumeng Liu
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China.
| | - Yuan Cheng
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China
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Cheng Y, Zhong YJ, Liu JM, Cao XB, Yu QQ, Zhang Q, He KB. Considerable contribution of secondary aerosol to wintertime haze pollution in new target of the latest clean air actions in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 335:122362. [PMID: 37567407 DOI: 10.1016/j.envpol.2023.122362] [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: 05/29/2023] [Revised: 07/24/2023] [Accepted: 08/09/2023] [Indexed: 08/13/2023]
Abstract
Fine particulate matter (PM2.5) in Northeast China was targeted by national-level clean air policy for the first time in 2022, with the release of Action Plan to eliminate heavy air pollution events. In this study, we investigated sources of PM2.5 during three successive winters in Harbin, a megacity in Northeast China, based on observational results from several recent campaigns in 2018-2021. During the 2020-2021 campaign, daytime and nighttime samples were collected in specific months in addition to 24-h integrated measurements, and the two sets of samples were combined in different ways to run a positive matrix factorization model. The source apportionment results suggested that the resolved secondary organic carbon (SOCPMF) had an uncertainty of ∼12%. Secondary aerosols were found to show the following features for the typical winters without agricultural fires. First, SOCPMF could be properly constrained by results from another widely-used approach for SOC estimation, the elemental carbon-tracer method. Second, secondary PM2.5 calculated using SOCPMF and secondary inorganic ions were generally in line with the independent estimations based on air quality data. Third, secondary components accounted for more than 50% of PM2.5 on average and contributed even more significantly during severe haze episodes, which were the focus of the latest Action Plan. This study also found that the wintertime PM2.5 decreased more slowly during 2017-2021 compared to 2013-2017, by ∼1 and 10 μg/m3 per year, respectively, for the metropolitan area where Harbin is located at. Our results highlighted the importance of secondary aerosols for further improving air quality in Northeast China, and for avoiding heavy pollution as required by the latest Action Plan.
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Affiliation(s)
- Yuan Cheng
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, China
| | - Ying-Jie Zhong
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, China
| | - Jiu-Meng Liu
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, China.
| | - Xu-Bing Cao
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, China
| | - Qin-Qin Yu
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Ke-Bin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
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Yang X, Zhao C, Zhao W, Fan H, Yang Y. Characterization of global fire activity and its spatiotemporal patterns for different land cover types from 2001 to 2020. ENVIRONMENTAL RESEARCH 2023; 227:115746. [PMID: 36966994 DOI: 10.1016/j.envres.2023.115746] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 03/07/2023] [Accepted: 03/22/2023] [Indexed: 05/08/2023]
Abstract
Fire is a widespread phenomenon that plays an important role in Earth's ecosystems. This study investigated the global spatiotemporal patterns of burned areas, daytime and nighttime fire counts, and fire radiative power (FRP) from 2001 to 2020. The month with the largest burned area, daytime fire count, and FRP presented a bimodal distribution worldwide, with dual peaks in early spring (April) and summer (July and August), while the month with the largest nighttime fire count and FRP showed a unimodal distribution, with a peak in July. Although the burned area showed decline at the global scale, a significant increase occurred in temperate and boreal forest regions, where nighttime fire occurrence and intensity have consistently increased in recent years. The relationships among burned area, fire count, and FRP were further quantified in 12 typical fire-prone regions. The burned area and fire count exhibited a humped relationship with FRP in most tropical regions, whereas the burned area and fire count constantly increased when the FRP was below approximately 220 MW in temperate and boreal forest regions. Meanwhile, the burned area and FRP generally increased with the fire count in most fire-prone regions, indicating an increased risk of more intense and larger fires as the fire count increased. The spatiotemporal dynamics of burned areas for different land cover types were also explored in this study. The results suggest that the burned areas in forest, grassland, and cropland showed dual peaks in April and from July to September while the burned areas in shrubland, bareland, and wetlands usually peaked in July or August. Significant increases in forest burned area were observed in temperate and boreal forest regions, especially in the western U.S. and Siberia, whereas significant increases in cropland burned area were found in India and northeastern China.
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Affiliation(s)
- Xingchuan Yang
- College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China
| | - Chuanfeng Zhao
- Department of Atmospheric and Oceanic Sciences, Laboratory for Climate and Ocean-Atmosphere Studies, School of Physics, Peking University, Beijing, 100871, China.
| | - Wenji Zhao
- College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China.
| | - Hao Fan
- State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Yikun Yang
- Department of Atmospheric and Oceanic Sciences, Laboratory for Climate and Ocean-Atmosphere Studies, School of Physics, Peking University, Beijing, 100871, China
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Li Q, Zhang K, Li R, Yang L, Yi Y, Liu Z, Zhang X, Feng J, Wang Q, Wang W, Huang L, Wang Y, Wang S, Chen H, Chan A, Latif MT, Ooi MCG, Manomaiphiboon K, Yu J, Li L. Underestimation of biomass burning contribution to PM 2.5 due to its chemical degradation based on hourly measurements of organic tracers: A case study in the Yangtze River Delta (YRD) region, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 872:162071. [PMID: 36775179 DOI: 10.1016/j.scitotenv.2023.162071] [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: 09/29/2022] [Revised: 02/01/2023] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
Biomass burning (BB) has significant impacts on air quality and climate change, especially during harvest seasons. In previous studies, levoglucosan was frequently used for the calculation of BB contribution to PM2.5, however, the degradation of levoglucosan (Lev) could lead to large uncertainties. To quantify the influence of the degradation of Lev on the contribution of BB to PM2.5, PM2.5-bound biomass burning-derived markers were measured in Changzhou from November 2020 to March 2021 using the thermal desorption aerosol gas chromatography-mass spectrometry (TAG-GC/MS) system. Temporal variations of three anhydro-sugar BB tracers (e.g., levoglucosan, mannosan (Man), and galactosan (Gal)) were obtained. During the sampling period, the degradation level of air mass (x) was 0.13, indicating that ~87 % of levoglucosan had degraded before sampling in Changzhou. Without considering the degradation of levoglucosan in the atmosphere, the contribution of BB to OC were 7.8 %, 10.2 %, and 9.3 % in the clean period, BB period, and whole period, respectively, which were 2.4-2.6 times lower than those (20.8 %-25.9 %) considered levoglucosan degradation. This illustrated that the relative contribution of BB to OC could be underestimated (~14.9 %) without considering degradation of levoglucosan. Compared to the traditional method (i.e., only using K+ as BB tracer), organic tracers (Lev, Man, Gal) were put into the Positive Matrix Factorization (PMF) model in this study. With the addition of BB organic tracers and replaced K+ with K+BB (the water-soluble potassium produced by biomass burning), the overall contribution of BB to PM2.5 was enhanced by 3.2 % after accounting for levoglucosan degradation based on the PMF analysis. This study provides useful information to better understand the effect of biomass burning on the air quality in the Yangtze River Delta region.
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Affiliation(s)
- Qing Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Kun Zhang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Rui Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Liumei Yang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Yanan Yi
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Zhiqiang Liu
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China; Jiangsu Changhuan Environment Technology Co., Ltd., Changzhou, Jiangsu, China
| | - Xiaojuan Zhang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China; Jiangsu Changhuan Environment Technology Co., Ltd., Changzhou, Jiangsu, China
| | - Jialiang Feng
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Qiongqiong Wang
- Department of Chemistry, Hong Kong University of Science & Technology, Hong Kong, China
| | - Wu Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Ling Huang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Yangjun Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Shunyao Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Hui Chen
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Andy Chan
- Department of Civil Engineering, University of Nottingham Malaysia, Semenyih, Selangor, Malaysia
| | - Mohd Talib Latif
- Department of Earth Science and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Maggie Chel Gee Ooi
- Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Kasemsan Manomaiphiboon
- The Joint Graduate School of Energy and Environment, King Mongkut's University of Technology Thonburi, Bangkok, Thailand
| | - Jianzhen Yu
- Department of Chemistry, Hong Kong University of Science & Technology, Hong Kong, China; Division of Environment & Sustainability, Hong Kong University of Science & Technology, Hong Kong, China
| | - Li Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China.
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Zhou Y, Xia X, Lang J, Zhao B, Chen D, Mao S, Zhang Y, Liu J, Li J. A coupled framework for estimating pollutant emissions from open burning of specific crop residue: A case study for wheat. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 844:156731. [PMID: 35772556 DOI: 10.1016/j.scitotenv.2022.156731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/08/2022] [Accepted: 06/12/2022] [Indexed: 06/15/2023]
Abstract
Crop residue open burning is considered to be one of the main sources of pollutant emissions from rural areas. It is necessary to accurately establish an emissions inventory of specific crops which could reflect the specific spatiotemporal distribution characteristics of crop residue burning emissions. However, the information for emission estimation of specific crop in each province and year is seriously data-deficient, resulting in a large uncertainty in the emissions inventory. In this study, taking the open burning of wheat residue as an example, we propose a framework for estimating pollutant emissions for specific crop residue by combining phenological information, land use data, field investigation/statistical data, and fire detection information. The wheat residue open burning proportion (OBP) and the corresponding pollutant emissions were estimated for each province in mainland China from 2003 to 2019. The national average OBP and emissions of wheat crop residue open burning first increased and then decreased during this period, with the peak in 2012. The gridded spatial distribution showed that high-emission areas were mainly concentrated in central-eastern China, and the emission areas gradually shifted from south to north from April to September. The change of daily emissions from large-scale concentrated emissions to small-scale emissions demonstrated that straw open burning prohibition policies were effective in reducing the annual emissions and peak daily emissions. This study provides a promising method for the combination of data from multiple sources to estimate open burning of crop residues. The method can be used to obtain accurate and detailed emissions data to support research into biomass burning and the development of targeted mitigation strategies.
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Affiliation(s)
- Ying Zhou
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China.
| | - Xiangchen Xia
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Jianlei Lang
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Beibei Zhao
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
| | - Dongsheng Chen
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Shushuai Mao
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Yuying Zhang
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Jing Liu
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Jia Li
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
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