1
|
Manzueta R, Kumar P, Ariño AH, Martín-Gómez C. Strategies to reduce air pollution emissions from urban residential buildings. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 951:175809. [PMID: 39197781 DOI: 10.1016/j.scitotenv.2024.175809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2024] [Revised: 08/02/2024] [Accepted: 08/24/2024] [Indexed: 09/01/2024]
Abstract
As cities continue to grow, developing mitigation strategies is crucial to minimize the corresponding increase in air pollutants. One source of potentially controllable air pollution is the emissions from residential buildings. We conducted a literature review to systematically examine air pollution emissions from residential buildings in urban areas, identifying pollutants and their sources; investigated mitigation-aimed intervention types by field of application or study, and finally listed and discussed strategies to reduce the concentration of air pollutants in residential buildings. Our compilation shows that among the nature-based solutions, green walls offered the highest relative reduction of air pollution (-15 % NO2 and -23 % PM10). Of the construction-based solutions, already-available photocatalytic paint can achieve reductions of 25 % NO, 23 % NOx and 19 % NO2 as is. Industrial-based solutions promise high levels of reduction, but these must be adapted to residential buildings. The integration of various existing and potentially adapted mitigation solutions may achieve even higher pollution reduction rates in urban areas.
Collapse
Affiliation(s)
- Robiel Manzueta
- Department of Construction, Building Services and Structures, Universidad de Navarra, Pamplona 31008, Spain; Global Centre for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, United Kingdom.
| | - Prashant Kumar
- Global Centre for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, United Kingdom; Institute for Sustainability, University of Surrey, Guildford GU2 7XH, United Kingdom.
| | - Arturo H Ariño
- Department of Environmental Biology and Institute of Biodiversity and Environment (BIOMA), Universidad de Navarra, Pamplona 31008, Spain.
| | - César Martín-Gómez
- Department of Construction, Building Services and Structures, Universidad de Navarra, Pamplona 31008, Spain.
| |
Collapse
|
2
|
Huang Y, Wang Q, Ou X, Sheng D, Yao S, Wu C, Wang Q. Identification of response regulation governing ozone formation based on influential factors using a random forest approach. Heliyon 2024; 10:e36303. [PMID: 39224321 PMCID: PMC11367417 DOI: 10.1016/j.heliyon.2024.e36303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 08/04/2024] [Accepted: 08/13/2024] [Indexed: 09/04/2024] Open
Abstract
The pursuit of enhanced scientific, refined, and precise ozone and air quality control continues to pose significant challenges. Using data visualization techniques and random forest (RF) algorithms, the temporal distribution of atmospheric pollutants and the interrelationship between O3 concentration and its influential factors were investigated with one-year monitoring data in Deqing county in 2021. The local atmospheric conditions predominantly belonged to NOx-sensitive and transition zone. Extremely high O3 concentration were primarily observed when temperatures (T) exceeded 30 °C, with relative humidity (RH) ranging between 30 and 60 %. NO2, RH and T were identified as the top 3 important factors, and O3 concentration have stronger linearly relationship to RH and T, while stronger nonlinearly relationship to NO2. By employing an optimized RF model, controlling consistent mild and high reaction atmospheric conditions, the O3 concentration response to the change of individual influencing factors was acquired. The O3 concentration increased and then decreased in response to the increasing NO2 concentration, displaying a characteristic inflection point at 10 μg m-3. More reactive radicals produced at higher VOCs concentration and continuing NOx cycle at lower NO2 concentration, resulting in the acceleration in the direction of producing more O3. Therefore, the significant different O3 response to variation of VOCs and NOx concentration between mild and high reaction atmospheric conditions, as well as the existing of oxidant elevation should be considered in local air quality control. This study demonstrates the efficacy of ML methods in simulating nonlinear response of O3, supports the understanding of local O3 formation and quick guidance for precise local O3 pollution control and the related strategies.
Collapse
Affiliation(s)
- Yan Huang
- Ecological Environmental Monitoring Station of Deqing County, Huzhou, 313200, China
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Qingqing Wang
- Ecological Environmental Monitoring Station of Deqing County, Huzhou, 313200, China
| | - Xiaojie Ou
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Dongping Sheng
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Shengdong Yao
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Chengzhi Wu
- Trinity Consultants, Inc. (China Office), Hangzhou, 310012, China
| | - Qiaoli Wang
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| |
Collapse
|
3
|
Yu S, Ma T, Zhang L, Li Q, Zhou M. Coupling sedimentary records of anthropogenic metal(loid)s in urban waterscape parks with the "Coal to Gas" transition. JOURNAL OF HAZARDOUS MATERIALS 2024; 473:134713. [PMID: 38788570 DOI: 10.1016/j.jhazmat.2024.134713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Revised: 04/11/2024] [Accepted: 05/22/2024] [Indexed: 05/26/2024]
Abstract
Energy consumption structure has been adjusted worldwide as a measure to reduce CO2 emission and mitigate air pollution. The "Coal to Gas" transition in mainland China has successfully controlled air pollution in recent decades, but its impacts on the environment beyond air quality improvement remain unknown. With 210Pb dating, this study chronicled profiles of eight anthropogenic metal(loid)s in sediment core from 14 waterscape parks across the Ring Road Network of Beijing, China. Six sediment cores were dated showing a timing coupling of metal(loid) loadings with annual coal consumption during the increasing period before 2000. Two downwind sediment cores in downtown Beijing presented such couplings in both increasing and descending periods for coal consumption before and after 2000, respectively, close to the tipping point observed in 2002 for primary energy consumption efficiency. Evidence from stable Pb isotope composition and exceedances of Cu loadings against sediment quality guidelines of China and the USA suggest that vehicular sources have been dominating metal(loid) loadings in sedimentation in these waterscape parks after the "Coal to Gas" transition. These findings would be helpful in identifying environmental impact patterns resulting from shifts in energy consumption structure and dominance of emission sources thereafter.
Collapse
Affiliation(s)
- Shen Yu
- Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; The Xiamen Key Laboratory of Smart Management on the Urban Environment, Xiamen 361021, China; Zhejiang A & F University, Hangzhou 311300, China.
| | - Tao Ma
- Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Linlin Zhang
- Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qi Li
- Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; The Xiamen Key Laboratory of Smart Management on the Urban Environment, Xiamen 361021, China
| | - Min Zhou
- Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; The Xiamen Key Laboratory of Smart Management on the Urban Environment, Xiamen 361021, China; Zhejiang A & F University, Hangzhou 311300, China
| |
Collapse
|
4
|
Wei X, Zhu Y, Gao Y, Gao H, Yao X. Statistical analysis and environmental impact of pre-existing particle growth events in a Northern Chinese coastal megacity: A 725-day study in 2010-2018. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 933:173227. [PMID: 38750744 DOI: 10.1016/j.scitotenv.2024.173227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 05/11/2024] [Accepted: 05/12/2024] [Indexed: 05/18/2024]
Abstract
Pre-existing particles usually constitute the major fraction of atmospheric particles, except during some episodes in the presence of strong emissions and/or secondary generation of fresh particles. Previous case studies have investigated the growth of pre-existing particles and their potential environmental and climate impacts. However, there is limited knowledge about the statistical characteristics of these growth events and related effects. In this study, we examine pre-existing particle growth events using a large dataset (725 days from 2010 to 2018) collected at a coastal megacity in northern China. The occurrence frequency of pre-existing particle growth events was 12.4 % (90 out of 725 days). When these events were related to measured criteria air pollutants, no significant differences were found in PM2.5, SO2, NO2 and NO2 + O3 concentrations between periods with and without pre-existing particle growth events. These 90-day events can be further classified into two categories, i.e., Category 1, with 68 % of events representing the growth of pre-existing particles alone, and Category 2, with 32 % of events representing the simultaneous growth of pre-existing and newly formed particles. In Category 2, the growth rates of pre-existing particles and newly formed particles were close in 21 % of the cases, while pre-existing particles exhibited significantly larger growth rates in 69 % of the cases. Conversely, in 10 % of the cases, the growth rates of newly formed particles were larger. The different growth rate mechanisms were discussed in terms of the volatility of atmospheric condensation vapors. In addition, we present case studies on the impact of pre-existing particle growth on cloud condensation nuclei simultaneously measured, specifically considering the chemistry of condensation vapors and pre-existing particles.
Collapse
Affiliation(s)
- Xing Wei
- Key Laboratory of Marine Environment and Ecology (MoE), Frontiers Sci Ctr Deep Ocean Multispheres & Earth, Sanya Oceanographic Institution, Ocean University of China, Qingdao, China
| | - Yujiao Zhu
- Environment Research Institute, Shandong University, Qingdao 266237, China
| | - Yang Gao
- Key Laboratory of Marine Environment and Ecology (MoE), Frontiers Sci Ctr Deep Ocean Multispheres & Earth, Sanya Oceanographic Institution, Ocean University of China, Qingdao, China; Laboratory for Marine Ecology and Environmental Sciences, Laoshan Laboratory, Qingdao, China
| | - Huiwang Gao
- Key Laboratory of Marine Environment and Ecology (MoE), Frontiers Sci Ctr Deep Ocean Multispheres & Earth, Sanya Oceanographic Institution, Ocean University of China, Qingdao, China; Laboratory for Marine Ecology and Environmental Sciences, Laoshan Laboratory, Qingdao, China
| | - Xiaohong Yao
- Key Laboratory of Marine Environment and Ecology (MoE), Frontiers Sci Ctr Deep Ocean Multispheres & Earth, Sanya Oceanographic Institution, Ocean University of China, Qingdao, China; Laboratory for Marine Ecology and Environmental Sciences, Laoshan Laboratory, Qingdao, China.
| |
Collapse
|
5
|
Wang X, Dewancker BJ, Tian D, Zhuang S. Exploring the Burden of PM2.5-Related Deaths and Economic Health Losses in Beijing. TOXICS 2024; 12:377. [PMID: 38922057 PMCID: PMC11209575 DOI: 10.3390/toxics12060377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 05/12/2024] [Accepted: 05/14/2024] [Indexed: 06/27/2024]
Abstract
Air pollution is one of the major global public health challenges. Using annual fine particulate matter (PM2.5) concentration data from 2016 to 2021, along with the global exposure mortality model (GEMM), we estimated the multi-year PM2.5-pollution-related deaths divided by different age groups and diseases. Then, using the VSL (value of statistical life) method, we assessed corresponding economic losses and values. The number of deaths attributed to PM2.5 in Beijing in 2021 fell by 33.74 percent from 2016, while health economic losses would increase by USD 4.4 billion as per capita disposable income increases year by year. In 2021, the average annual concentration of PM2.5 in half of Beijing's municipal administrative districts is less than China's secondary ambient air quality standard (35 μg/m3), but it can still cause 48,969 deaths and corresponding health and economic losses of USD 16.31 billion, equivalent to 7.9 percent of Beijing's GDP. Therefore, it is suggested that more stringent local air quality standards should be designated to protect public health in Beijing.
Collapse
Affiliation(s)
- Xiaoqi Wang
- Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan;
| | - Bart Julien Dewancker
- Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan;
| | - Dongwei Tian
- School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing 100044, China;
| | - Shao Zhuang
- School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China;
| |
Collapse
|
6
|
Bai J, Zhang M, Shao L, Jones TP, Feng X, Huang M, BéruBé KA. Hemolytic Properties of Fine Particulate Matter (PM 2.5) in In Vitro Systems. TOXICS 2024; 12:246. [PMID: 38668469 PMCID: PMC11054038 DOI: 10.3390/toxics12040246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 03/22/2024] [Accepted: 03/25/2024] [Indexed: 04/29/2024]
Abstract
Epidemiological studies have suggested that inhalation exposure to particulate matter (PM) air pollution, especially fine particles (i.e., PM2.5 (PM with an aerodynamic diameter of 2.5 microns or less)), is causally associated with cardiovascular health risks. To explore the toxicological mechanisms behind the observed adverse health effects, the hemolytic activity of PM2.5 samples collected during different pollution levels in Beijing was evaluated. The results demonstrated that the hemolysis of PM2.5 ranged from 1.98% to 7.75% and demonstrated a clear dose-response relationship. The exposure toxicity index (TI) is proposed to represent the toxicity potential of PM2.5, which is calculated by the hemolysis percentage of erythrocytes (red blood cells, RBC) multiplied by the mass concentration of PM2.5. In a pollution episode, as the mass concentration increases, TI first increases and then decreases, that is, TI (low pollution levels) < TI (heavy pollution levels) < TI (medium pollution levels). In order to verify the feasibility of the hemolysis method for PM toxicity detection, the hemolytic properties of PM2.5 were compared with the plasmid scission assay (PSA). The hemolysis results had a significant positive correlation with the DNA damage percentages, indicating that the hemolysis assay is feasible for the detection of PM2.5 toxicity, thus providing more corroborating information regarding the risk to human cardiovascular health.
Collapse
Affiliation(s)
- Jiahui Bai
- State Key Laboratory of Coal Resources and Safe Mining, College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing 100083, China; (J.B.); (X.F.); (M.H.)
| | - Mengyuan Zhang
- Postdoctoral Research Base, School of Resource and Environment, Henan Institute of Science and Technology, Xinxiang 453000, China
| | - Longyi Shao
- State Key Laboratory of Coal Resources and Safe Mining, College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing 100083, China; (J.B.); (X.F.); (M.H.)
| | - Timothy P. Jones
- School of Earth and Environmental Sciences, Cardiff University, Museum Avenue, Cardiff CF10 3YE, UK;
| | - Xiaolei Feng
- State Key Laboratory of Coal Resources and Safe Mining, College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing 100083, China; (J.B.); (X.F.); (M.H.)
| | - Man Huang
- State Key Laboratory of Coal Resources and Safe Mining, College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing 100083, China; (J.B.); (X.F.); (M.H.)
| | - Kelly A. BéruBé
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, UK;
| |
Collapse
|
7
|
Peng L, Ti C, Yin B, Dong W, Li M, Tao L, Yan X. Traceability of atmospheric ammonia in a suburban area of the Beijing-Tianjin-Hebei region. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:167935. [PMID: 37866588 DOI: 10.1016/j.scitotenv.2023.167935] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 10/16/2023] [Accepted: 10/17/2023] [Indexed: 10/24/2023]
Abstract
Ammonia (NH3) is one of the most important sources that have been linked to the formation of PM2.5. Therefore, it is important to study the source contributions to atmospheric NH3 for air pollution control. Here we used 15N natural abundance (expressed by δ15N) values to quantify the source contributions to atmospheric NH3 in the Beijing-Tianjin-Hebei (BTH) region, which suffers from the country's worst air pollution. Results showed that from 2017 to 2019, the annual mean δ15N-NH3 value at the livestock site (-27.5 ± 6.0 ‰) was lower than at cropland (-20.7 ± 6.0 ‰) and rural residential sites (-22.1 ± 7.4 ‰), while their concentrations were the opposite. Seasonal mean δ15N-NH3 values were the highest in winter and lowest in summer, whereas monthly mean δ15N-NH3 values were the highest in January and lowest in June. The isotope mixing model results showed that agricultural sources account for 64.5 ± 13.5 % of year-round total NH3 emissions, while industrial and other sources contributed 27.4 and 8.1 %, respectively. However, the contribution of industrial sources was higher than that of agricultural sources in January. Our results indicated that the contribution of agricultural sources has decreased after the implementation of air pollution control policies in this region suggesting that NH3 abatement from agricultural sources is effective. However, further refinement of agricultural emission abatement measures will be required, accompanied by a greater focus on controlling winter non-agricultural sources.
Collapse
Affiliation(s)
- Lingyun Peng
- State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro-Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chaopu Ti
- State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro-Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Bin Yin
- State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro-Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
| | - Wenxu Dong
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050021, China
| | - Miao Li
- State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro-Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
| | - Limin Tao
- State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro-Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
| | - Xiaoyuan Yan
- State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro-Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China; University of Chinese Academy of Sciences, Beijing 100049, China
| |
Collapse
|
8
|
Zhang L, Wang L, Liu B, Tang G, Liu B, Li X, Sun Y, Li M, Chen X, Wang Y, Hu B. Contrasting effects of clean air actions on surface ozone concentrations in different regions over Beijing from May to September 2013-2020. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 903:166182. [PMID: 37562614 DOI: 10.1016/j.scitotenv.2023.166182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 08/06/2023] [Accepted: 08/07/2023] [Indexed: 08/12/2023]
Abstract
Due to the nonlinear impacts of meteorology and precursors, the response of ozone (O3) trends to emission changes is very complex over different regions in megacity Beijing. Based on long-term in-situ observations at 35 air quality sites (four categories, i.e., urban, traffic, northern suburban and southern suburban sites) and satellite data, spatiotemporal variability of O3, gaseous precursors, and O3-VOCs-NOx sensitivity were explored through multiple metrics during the warm season from 2013 to 2020. Additionally, the contribution of meteorology and emissions to O3 was separated by a machine-learning-based de-weathered method. The annual averaged MDA8 O3 and O3 increased by 3.7 and 2.9 μg/m3/yr, respectively, with the highest at traffic sites and the lowest in northern suburb, and the rate of Ox (O3 + NO2) was 0.2 μg/m3/yr with the highest in southern suburb, although NO2 declined strongly and HCHO decreased slightly. However, the increment of O3 and Ox in the daytime exhibited decreasing trends to some extent. Additionally, NOx abatements weakened O3 loss through less NO titration, which drove narrowing differences in urban-suburban O3 and Ox. Due to larger decrease of NO2 in urban region and HCHO in northern suburb, the extent of VOCs-limited regime fluctuated over Beijing and northern suburb gradually shifted to transition or NOx-limited regime. Compared with the directly observed trends, the increasing rate of de-weathered O3 was lower, which was attributed to favorable meteorological conditions for O3 generation after 2017, especially in June (the most polluted month); whereas the de-weathered Ox declined except in southern suburb. Overall, clean air actions were effective in reducing the atmospheric oxidation capacity in urban and northern suburban regions, weakening local photochemical production over Beijing and suppressing O3 deterioration in northern suburb. Strengthening VOCs control and keeping NOx abatement, especially in June, will be vital to reverse O3 increase trend in Beijing.
Collapse
Affiliation(s)
- Lei Zhang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Lili Wang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Zhejiang Key Laboratory of Ecological and Environmental Big Data (2022P10005), Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China.
| | - Boya Liu
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Guiqian Tang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Baoxian Liu
- Beijing Key Laboratory of Airborne Particulate Matter Monitoring Technology, Beijing Municipal Ecological Environmental Monitoring Center, Beijing 100048, China
| | - Xue Li
- Beijing Municipal Ecology and Environment Bureau, Beijing 100048, China
| | - Yang Sun
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Mingge Li
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute Chinese Academy of Sciences, Beijing 100101, China
| | - Xianyan Chen
- National Climate Center, China Meteorological Administration, Beijing 100081, China
| | - Yuesi Wang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Bo Hu
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| |
Collapse
|
9
|
Wang W, Shao L, Li X, Li Y, Lyu R, Zhou X. Changes of water-soluble inorganic sulfate and nitrate during severe dust storm episodes in a coastal city of North China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 335:122288. [PMID: 37544180 DOI: 10.1016/j.envpol.2023.122288] [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: 05/20/2023] [Revised: 07/16/2023] [Accepted: 07/28/2023] [Indexed: 08/08/2023]
Abstract
Dust storms are one of the largest sources of non-exhaust emissions in China, which can adversely affect air quality and human health during long-distance transportation. To study the influence of dust storms on aerosol particle composition, samples of fine aerosol (PM2.5) were collected before, during, and after the severe dust storm episodes in a coastal city of North China. Then the water-soluble inorganic ions in the filters were analyzed. The results showed that the chemical composition varied significantly in different sampling periods. Before the dust storm periods (Phase 1), the weather was characterized by high relative humidity. NO3- was the main water-soluble inorganic ion, accounting for about 1/3 of the total mass of PM2.5, which is very different from the situation a few years ago when sulfate was the dominant. The results indicated that the chemical composition of the atmosphere in China has changed significantly after the implementation of strict air pollution control measures. During the severe dust storm periods (within a few hours after the dust invasion, Phase 2), the proportion of Ca2+ in PM2.5 was high; the sulfate formation was limited due to adiabatic air mass affected by the cold front, and the sulfate content might be mainly from desert soil. However, a small amount of nitrate can be formed during their long-distance transportation. After the dust storm periods (Phase 3), dust plums and local polluted air mass mixed well. The proportion of secondary inorganic ions increased, and nitrate formation was still the main. The changes in the chemical composition from a few years ago during Phase 1 and the sharp changes in different water-soluble inorganic ions during different Phases should be carefully considered to evaluate their implications for air quality and human health.
Collapse
Affiliation(s)
- Wenhua Wang
- School of Resources and Civil Engineering, Northeastern University, Shenyang, 110819, China; School of Resources and Materials, Northeastern University at Qinhuangdao, Qinhuangdao, 066004, China
| | - Longyi Shao
- State Key Laboratory of Coal Resources and Safe Mining & College of Geosciences and Surveying Engineering, China University of Mining and Technology, Beijing, 100083, China.
| | - Xian Li
- School of Resources and Civil Engineering, Northeastern University, Shenyang, 110819, China; School of Resources and Materials, Northeastern University at Qinhuangdao, Qinhuangdao, 066004, China
| | - Yaowei Li
- Hebei Center for Ecological and Environmental Geology Research, Hebei GEO University, Shijiazhuang, 050031, China
| | - Ruihe Lyu
- College of Marine Resources and Environment, Hebei Normal University of Science & Technology, Qinhuangdao, 066004, China
| | - Xiuyan Zhou
- School of Resources and Civil Engineering, Northeastern University, Shenyang, 110819, China; School of Resources and Materials, Northeastern University at Qinhuangdao, Qinhuangdao, 066004, China.
| |
Collapse
|
10
|
Chen Y, Liu H, Alatalo JM, Jiang B. Air quality characteristics during 2016-2020 in Wuhan, China. Sci Rep 2023; 13:8477. [PMID: 37231046 DOI: 10.1038/s41598-023-35465-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 05/18/2023] [Indexed: 05/27/2023] Open
Abstract
Implementation of a clean air policy in China has high national importance. Here, we analyzed tempo-spatial characteristics of the concentrations of PM2.5 (PM2.5_C), PM10 (PM10_C), SO2 (SO2 _C), NO2 (NO2 _C), CO (CO _C), and maximum 8-h average O3 (O3_8h_C), monitored at 22 stations throughout the mega-city of Wuhan from January 2016 to December 2020, and their correlations with the meteorological and socio-economic factors. PM2.5_C, PM10_C, SO2 _C, NO2 _C, and CO _C showed similar monthly and seasonal trends, with minimum value in summer and maximum value in winter. However, O3_8h_C showed an opposite monthly and seasonal change pattern. In 2020, compared to the other years, the annual average PM2.5_C, PM10_C, SO2 _C, NO2 _C, and CO _C were lower. PM2.5_C and PM10_C were higher in urban and industrial sites and lower in the control site. The SO2_C was higher in industrial sites. The NO2_C was lower, and O3_8h_C was higher in suburban sites, while CO showed no spatial differences in their concentrations. PM2.5 _C, PM10 _C, SO2 _C, NO2 _C, and CO _C had positive correlations with each other, while O3_8h_C showed more complex correlations with the other pollutants. PM2.5_C, PM10_C, SO2 _C, and CO _C presented a significantly negative association with temperature and precipitation, while O3 was significantly positively associated with temperature and negatively associated with relative air humidity. There was no significant correlation between air pollutants and wind speed. Gross domestic product, population, number of automobiles, and energy consumption play an important role in the dynamics of air quality concentrations. These all provided important information for the decision and policy-makers to effectively control the air pollution in Wuhan.
Collapse
Affiliation(s)
- Yuanyuan Chen
- CAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, China
| | - Hongtao Liu
- CAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Juha M Alatalo
- Environmental Science Center, Qatar University, Doha, Qatar
| | - Bo Jiang
- Changjiang Water Resources Protection Institute, Wuhan, 430051, China.
- Key Laboratory of Ecological Regulation of Non-Point Source Pollution in Lake and Reservoir Water Resources, Changjiang Water Resources Commission, Wuhan, 430051, China.
| |
Collapse
|
11
|
Bedregal P, Ubillus M, Cáceres-Rivero C, Olivera P, Garay R, Rojas J, Zafra R, Urdanivia R. Determination of atmospheric aerosol components in an urban area to evaluate the air quality and identify the sources of contamination. J Radioanal Nucl Chem 2023; 332:1-8. [PMID: 36816985 PMCID: PMC9930019 DOI: 10.1007/s10967-023-08805-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 01/27/2023] [Indexed: 02/19/2023]
Abstract
The need to generate objective evidence and reliable information for decision makers to improve environmental policies for a better air quality, led us to evaluate the atmospheric aerosol components in the urban area of Carabayllo, by monitoring PM2.5 and PM10 to determine mass concentration and analyzing PM10 using k 0-INAA and ICP-MS for metals quantification, ion chromatography for anions and the NIOSH method to determine organic and elemental carbon. The results obtained from mass concentration of PM2.5 and PM10 exceeded the permissible breathing annual average of WHO guidelines of 15 µgm-3 and 45 µgm-3, respectively, which evidence an unhealthy air quality. Likewise, using the model Positive Matrix Factorization five sources of pollutants were defined: metallurgical industry, sea salt, industrial activity, dust and non-exhaust emissions and vehicle emissions.
Collapse
Affiliation(s)
- Patricia Bedregal
- Laboratorio de Técnicas Analíticas, Instituto Peruano de Energia Nuclear, IPEN, Av. Canada 1480, San Borja, Lima, 15034 Peru
| | - Marco Ubillus
- Laboratorio de Técnicas Analíticas, Instituto Peruano de Energia Nuclear, IPEN, Av. Canada 1480, San Borja, Lima, 15034 Peru
| | - Cynthia Cáceres-Rivero
- Laboratorio de Técnicas Analíticas, Instituto Peruano de Energia Nuclear, IPEN, Av. Canada 1480, San Borja, Lima, 15034 Peru
| | - Paula Olivera
- Laboratorio de Técnicas Analíticas, Instituto Peruano de Energia Nuclear, IPEN, Av. Canada 1480, San Borja, Lima, 15034 Peru
| | - Roy Garay
- Subdirección de Control Ambiental, Servicio Nacional de Meteorología e Hidrología, SENAMHI, Jr. Cahuide 785, Jesús María, Lima, Perú
| | - Jhojan Rojas
- Subdirección de Control Ambiental, Servicio Nacional de Meteorología e Hidrología, SENAMHI, Jr. Cahuide 785, Jesús María, Lima, Perú
| | - Rafael Zafra
- Facultad de Química, Universidad Nacional Federico Villarreal, Jr. Chepen 290, El Agustino, Lima, Perú
| | - Renato Urdanivia
- Dirección de Evaluación Ambiental, Organismo de Evaluación y Fiscalización Ambiental, OEFA, Av. Faustino Sánchez Carrión 603, Jesús María, Lima, Perú
| |
Collapse
|
12
|
Xia C, Sun J, Hu X, Shen X, Zhang Y, Zhang S, Wang J, Liu Q, Lu J, Liu S, Zhang X. Effects of hygroscopicity on aerosol optical properties and direct radiative forcing in Beijing: Based on two-year observations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159233. [PMID: 36208762 DOI: 10.1016/j.scitotenv.2022.159233] [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: 06/07/2022] [Revised: 09/16/2022] [Accepted: 09/30/2022] [Indexed: 06/16/2023]
Abstract
The influence of relative humidity on aerosol properties and the direct radiative forcing of PM10 and PM1 were investigated in Beijing from January 2018 to December 2019. The annual mean scattering hygroscopic growth factor at RH = 80 % [f(80 %)] of PM10 and PM1 were 1.60 ± 0.24 and 1.58 ± 0.22, respectively. The variation of aerosol hygroscopic growth factors of PM10 and PM1 aerosols was similar, which is mainly due to the fact that aerosol scattering in Beijing is dominated by fine particles. The seasonal mean f(80 %) of PM10 from spring to winter were 1.66 ± 0.23, 1.71 ± 0.25, 1.51 ± 0.20, 1.49 ± 0.16, respectively, which were higher in spring and summer, and lower in autumn and winter. The diurnal variation of f(80 %) was relatively higher from 12:00 to 18:00, which could be related to the formation of secondary aerosols by photochemical reactions. f(80 %) shows a strong positive relationship with both the scattering Angström exponent (SAE) and the single scattering albedo (ω0) under dry conditions; therefore, the scattering hygroscopic growth factor could be estimated using these two parameters. The upscatter fraction (β) and single scattering albedo, which are the key aerosol optical properties for the calculation of direct radiative forcing, are also RH-dependent. As RH increases, the upscatter fraction (backscatter fraction) decreases and ω0 increases. The aerosol radiative forcing at RH 80 % was 1.48 times as that in the dry state. The sensitivity experiment showed that the variation in the scattering coefficient with relative humidity had the greatest influence on radiation forcing, followed by β and ω0. The seasonal variation of ΔF(80 %)/ΔF(dry) coincides with that of the aerosol hygroscopic growth factor. Our study suggests that understanding the influence of relative humidity on aerosol properties and direct radiative forcing is important for accurately estimating the radiative forcing of aerosols.
Collapse
Affiliation(s)
- Can Xia
- School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China; State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Junying Sun
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Xinyao Hu
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaojing Shen
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Yangmei Zhang
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Sinan Zhang
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Jialing Wang
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Quan Liu
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Jiayuan Lu
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Shuo Liu
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Xiaoye Zhang
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| |
Collapse
|
13
|
Kuang B, Zhang F, Shen J, Shen Y, Qu F, Jin L, Tang Q, Tian X, Wang Z. Chemical characterization, formation mechanisms and source apportionment of PM 2.5 in north Zhejiang Province: The importance of secondary formation and vehicle emission. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158206. [PMID: 36028033 DOI: 10.1016/j.scitotenv.2022.158206] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/11/2022] [Accepted: 08/18/2022] [Indexed: 06/15/2023]
Abstract
PM2.5 affects air quality, therefore, chemical evolution, formation mechanism and source identification of PM2.5 are essential to help figure out mitigation measures. PM2.5 and its constituents were comprehensively characterized with highly time-resolved measurements from 2019 to 2020 in north Zhejiang Province (Shanxi, SX) for the first time, with an emphasis on the contribution of secondary formation and vehicle emission to PM2.5. Secondary inorganic ions (sulfate: 3.86 μg/m3, nitrate: 7.82 μg/m3 and ammonium: 4.59 μg/m3, SNA) were found to be the major components (54%) in PM2.5 (29.70 μg/m3). The highly consistence of nitrate, sulfate and secondary organic compounds (SOC) with Ox (NO2 + O3) or RH indicated the importance of photochemical oxidation and heterogeneous reaction in different scenarios. Higher atmospheric oxidative potential facilitated the SOC formation in spring. The PM2.5 mass was apportioned to eight sources resolved by positive matrix factorization (PMF): secondary nitrate (9.63 μg/m3), secondary sulfate (5.14 μg/m3), vehicle emission (7.26 μg/m3), coal combustion (2.39 μg/m3), biomass burning (1.38 μg/m3), soil dust (0.86 μg/m3), industry emission (0.50 μg/m3), and ship emission (0.32 μg/m3). Secondary nitrate (35%) and sulfate (19%) formation and vehicle emission (26%) were the main factors contributing to the PM2.5. Furthermore, the contribution of secondary nitrate formation increased with elevating PM2.5 concentration. Regional transport was synthetically studied by chemical and backward trajectory analysis, reflecting that secondary nitrate contributed severely to the air quality at SX, while vehicle emission contribution enhanced when atmosphere was stagnant. This study first provides long-term comprehensive chemical characterization and source apportionments of PM2.5 pollution in north Zhejiang, which may provide some guidance for the air pollution control.
Collapse
Affiliation(s)
- Binyu Kuang
- College of Environmental and Resource Sciences, Zhejiang University, Zhejiang Provincial Key Laboratory of Organic Pollution Process and Control, Hangzhou 310058, China
| | - Fei Zhang
- College of Environmental and Resource Sciences, Zhejiang University, Zhejiang Provincial Key Laboratory of Organic Pollution Process and Control, Hangzhou 310058, China
| | - Jiasi Shen
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
| | - Yemin Shen
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
| | - Fangqi Qu
- College of Environmental and Resource Sciences, Zhejiang University, Zhejiang Provincial Key Laboratory of Organic Pollution Process and Control, Hangzhou 310058, China
| | - Lingling Jin
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
| | - Qian Tang
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
| | - Xudong Tian
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China.
| | - Zhibin Wang
- College of Environmental and Resource Sciences, Zhejiang University, Zhejiang Provincial Key Laboratory of Organic Pollution Process and Control, Hangzhou 310058, China; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou 311200, China.
| |
Collapse
|
14
|
Mao Y, Liu W, Hu T, Shi M, Cheng C, Zhan C, Zhang L, Zhang J, Sweetman AJ, Jones KC, Xing X, Qi S. Impact of short-term control measures on air quality: A case study during the 7th Military World Games in central China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 311:119998. [PMID: 36007790 DOI: 10.1016/j.envpol.2022.119998] [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: 05/12/2022] [Revised: 08/01/2022] [Accepted: 08/15/2022] [Indexed: 06/15/2023]
Abstract
The 7th Military World Games held in Wuhan (WH) in Oct 2019 provided an opportunity to clarify the impact of short-term control measures on air quality. Fine particulate matters (PM2.5) were collected in WH, Huangshi (HS), and Huanggang (HG) during the control (Oct 13-28, 2019) and non-control periods (Oct 29- Nov 5, 2019). The results showed that air quality was good during the control period, with the concentrations of PM2.5 and gaseous pollutants being below the Grade Ⅱ of China Ambient Air Quality Standard. Concentrations of PM2.5 and its major chemical components in the control period were significantly lower than those in the non-control period, with reductions ranging from 17% (trace elements) to 46% (elemental carbon). However, higher contributions of secondary components such as SO42-, NO3-, NH4+ and secondary organic carbon (SOC) to PM2.5 were observed during the control period, suggesting the important role of secondary transformation. Potential source contribution function (PSCF) of PM2.5 showed that the main source regions were potentially located in surrounding cities Hubei Province, but regional transport can't be ignored. Six sources were identified by positive matrix factorization (PMF) for both control and non-control period. The contributions of combustion emissions and vehicle emissions were amplified in the control period, while the contribution of construction dust increased significantly when the control measures ended. Emission reductions contributed more to PM2.5 concentration decrease in WH (55%) than that in HS (51%) and HG (49%), which was consistent with the stricter control measures implemented in WH. These results indicated that short-term controls were effective at lowering PM2.5 concentration. However, the elevated contributions of secondary aerosols and the influence of regional transport on the study areas also need to be paid attention for air quality improvement in the future.
Collapse
Affiliation(s)
- Yao Mao
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies, China University of Geosciences, Wuhan, 430078, China; Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
| | - Weijie Liu
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies, China University of Geosciences, Wuhan, 430078, China
| | - Tianpeng Hu
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies, China University of Geosciences, Wuhan, 430078, China; Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
| | - Mingming Shi
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies, China University of Geosciences, Wuhan, 430078, China
| | - Cheng Cheng
- Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
| | - Changlin Zhan
- School of Environmental Science and Engineering, Hubei Key Laboratory of Mine Environmental Pollution Control and Remediation, Hubei Polytechnic University, Huangshi, 435003, China
| | - Li Zhang
- School of Environmental Science and Engineering, Hubei Key Laboratory of Mine Environmental Pollution Control and Remediation, Hubei Polytechnic University, Huangshi, 435003, China
| | - Jiaquan Zhang
- School of Environmental Science and Engineering, Hubei Key Laboratory of Mine Environmental Pollution Control and Remediation, Hubei Polytechnic University, Huangshi, 435003, China
| | - Andrew J Sweetman
- Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
| | - Kevin C Jones
- Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
| | - Xinli Xing
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies, China University of Geosciences, Wuhan, 430078, China.
| | - Shihua Qi
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies, China University of Geosciences, Wuhan, 430078, China
| |
Collapse
|
15
|
Ma Q, Wang W, Wu Y, Wang F, Jin L, Song X, Han Y, Zhang R, Zhang D. Haze caused by NO x oxidation under restricted residential and industrial activities in a mega city in the south of North China Plain. CHEMOSPHERE 2022; 305:135489. [PMID: 35777547 DOI: 10.1016/j.chemosphere.2022.135489] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 06/08/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
The formation of secondary aerosol species, including nitrate and sulfate, induces severe haze in the North China Plain. However, despite substantial reductions in anthropogenic pollutants due to severe restriction of residential and industrial activities in 2020 to stop the spread of COVID-19, haze still formed in Zhengzhou. We compared ionic compositions of PM2.5 during the period of the restriction with that immediately before the restriction and in the comparison period in 2019 to investigate the processes that caused the haze. The average concentration of PM2.5 was 83.9 μg m-3 in the restriction period, 241.8 μg m-3 before the restriction, and 94.0 μg m-3 in 2019. Nitrate was the largest contributor to the PM2.5 in all periods, with an average mass fraction of 24%-30%. The average molar concentration of total nitrogen compounds (NOx + nitrate) was 0.89 μmol m-3 in the restriction period, which was much lower than that in the non-restriction periods (1.85-2.74 μmol m-3). In contrast, the concentration of sulfur compounds (SO2 + sulfate) was 0.34-0.39 μmol m-3 in all periods. The conversion rate of NOx to nitrate (NOR) was 0.35 in the restriction period, significantly higher than that before the restriction (0.26) and in 2019 (0.25). NOR was higher with relative humidity in 40-80% in the restriction period than in the other two periods, whereas the conversion rate of SO2 to sulfate did not, indicating nitrate formation was more efficient during the restriction. When O3 occupied more than half of the oxidants (Ox = O3 + NO2), NOR increased rapidly with the ratio of O3 to Ox and was much higher in the daytime than nighttime. Therefore, haze in the restriction period was caused by increased NOx-to-nitrate conversion driven by photochemical reactions.
Collapse
Affiliation(s)
- Qingxia Ma
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, China; Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security, Kaifeng, 475004, China
| | - Weisi Wang
- Henan Ecological and Environmental Monitoring Center, Zhengzhou, 450000, China
| | - Yunfei Wu
- Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China.
| | - Fang Wang
- China West Normal University, Nanchong, 637000, China
| | - Liyuan Jin
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, China
| | - Xiaoyan Song
- College of Geosciences and Engineering, North China University of Water Resources and Electric Power, Zhengzhou, Henan, 450046, China
| | - Yan Han
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, China; Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security, Kaifeng, 475004, China
| | - Renjian Zhang
- Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Daizhou Zhang
- Faculty of Environmental and Symbiotic Sciences, Prefectural University of Kumamoto, Kumamoto, 862-8502, Japan.
| |
Collapse
|
16
|
Liu M, Wang W, Li J, Wang T, Xu Z, Song Y, Zhang W, Zhou L, Lian C, Yang J, Li Y, Sun Y, Tong S, Guo Y, Ge M. High fraction of soluble trace metals in fine particles under heavy haze in central China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 841:156771. [PMID: 35724777 DOI: 10.1016/j.scitotenv.2022.156771] [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: 04/16/2022] [Revised: 06/13/2022] [Accepted: 06/14/2022] [Indexed: 05/17/2023]
Abstract
Atmospheric trace metals are a key component of particulate matter and significantly influence the atmospheric process and human health. The dissolved fraction of trace metals represents their bioavailability and exhibits high chemical activity. However, the optimum measurement method for detecting the soluble fraction of trace metals is still undetermined. The impact of variations in pollution on the soluble fraction is largely unrevealed. Therefore, in this work, a one-month field observation was conducted in Central China and different extraction solvents were used to determine the proper measurement method for the soluble fraction of trace metals and investigate the variation pattern under different pollution conditions. The findings show that solvents with acidity near that of aerosol water can better reflect the actual soluble fraction of trace metals in fine particulate matter. The soluble fraction of trace metals tends to increase with pollution level increased, demonstrating unexpectedly high health risks and chemical activity under heavy haze conditions. Our results indicate that remediation and trace metal pollution control are urgently needed.
Collapse
Affiliation(s)
- Mingyuan Liu
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), Chemistry Academy of Sciences Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; Department of Ambient Air Quality Monitoring, China National Environmental Monitoring Centre, Beijing 100012, China
| | - Weigang Wang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), Chemistry Academy of Sciences Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China.
| | - Jie Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Tiantian Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, Department of Environmental Science, Peking University, Beijing 100871, China
| | - Zhenying Xu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, Department of Environmental Science, Peking University, Beijing 100871, China
| | - Yu Song
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, Department of Environmental Science, Peking University, Beijing 100871, China
| | - Wenyu Zhang
- Department of Clinical Research, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, China
| | - Li Zhou
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China
| | - Chaofan Lian
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), Chemistry Academy of Sciences Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Jinxing Yang
- Sanmenxia Environmental Monitoring Station, Sanmenxia 472400, China
| | - Yanyu Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Shengrui Tong
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), Chemistry Academy of Sciences Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Yucong Guo
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), Chemistry Academy of Sciences Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Maofa Ge
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), Chemistry Academy of Sciences Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| |
Collapse
|
17
|
Liu P, Shao L, Li Y, Jones T, Cao Y, Yang CX, Zhang M, Santosh M, Feng X, BéruBé K. Microplastic atmospheric dustfall pollution in urban environment: Evidence from the types, distribution, and probable sources in Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:155989. [PMID: 35580670 DOI: 10.1016/j.scitotenv.2022.155989] [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: 04/12/2022] [Revised: 05/10/2022] [Accepted: 05/11/2022] [Indexed: 06/15/2023]
Abstract
Airborne microplastics (MPs) pollution is an environmental problem of increasing concern, due to the ubiquity, persistence and potential toxicity of plastics in the atmosphere. In recent years, most studies on MPs have focused on aquatic and sedimentary environments, but little research has been done on MPs in the urban atmosphere. In this study, a total of ten dustfall samples were collected in a transect from north to south across urban Beijing. The compositions, morphologies, and sizes of the MPs in these dustfall samples were determined by means of Laser Direct Infrared (LDIR) imaging and Field Emission Scanning Electron Microscopy (FESEM). The number concentrations of MPs in the Beijing dustfall samples show an average of 123.6 items/g. The MPs concentrations show different patterns in the central, southern, and northern zones of Beijing. The number concentration of MPs was the highest in the central zone (224.76 items/g), as compared with the southern zone (170.55 items/g), and the northern zone (24.42 items/g). The LDIR analysis revealed nine compositional types of MPs, including Polypropylene (PP), Polyamide (PA), Polystyrene (PS), Polyethylene (PE), Polyethylene Terephthalate (PET), Silicone, Polycarbonate (PC), Polyurethane (PU) and Polyvinylchloride (PVC), among which PP was overall dominant. The PP dominates the MPs in the central zone (76.3%), and the PA dominates the MPs in the southern zone (55.86%), while the northern zone had a diverse combination of MPs types. The morphological types of the individual MPs particle include fragments, pellets, and fibers, among which fragments are dominant (70.9%). FESEM images show the presence of aged MPs in the Beijing atmosphere, which could pose a yet unquantified health risk to Beijing's residents. The average size of the MPs in the Beijing samples is 66.62 μm. Our study revealed that the numbers of fibrous MPs increase with the decrease in size. This pollution therefore needs to be carefully monitored, and methods of decreasing the sources and mitigations developed.
Collapse
Affiliation(s)
- Pengju Liu
- State Key Laboratory of Coal Resources and Safe Mining & College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Longyi Shao
- State Key Laboratory of Coal Resources and Safe Mining & College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China.
| | - Yaowei Li
- State Key Laboratory of Coal Resources and Safe Mining & College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China; Hebei Center for Ecological and Environmental Geology Research, Hebei GEO University, Shijiazhuang 050031, China
| | - Tim Jones
- School of Earth and Environmental Sciences, Cardiff University, Cardiff CF10, 3YE, Wales, UK
| | - Yaxin Cao
- State Key Laboratory of Coal Resources and Safe Mining & College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Cheng-Xue Yang
- Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing 100083, China
| | - Mengyuan Zhang
- State Key Laboratory of Coal Resources and Safe Mining & College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - M Santosh
- School of Earth Sciences and Resources, China University of Geoscience Beijing, Beijing 100083, China; Department of Earth Science, University of Adelaide, Adelaide, SA 5005, Australia
| | - Xiaolei Feng
- State Key Laboratory of Coal Resources and Safe Mining & College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Kelly BéruBé
- School of Biosciences, Cardiff University, Cardiff CF10 3AX, Wales, UK
| |
Collapse
|
18
|
Guo Y, Li K, Zhao B, Shen J, Bloss WJ, Azzi M, Zhang Y. Evaluating the real changes of air quality due to clean air actions using a machine learning technique: Results from 12 Chinese mega-cities during 2013-2020. CHEMOSPHERE 2022; 300:134608. [PMID: 35430204 DOI: 10.1016/j.chemosphere.2022.134608] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 03/12/2022] [Accepted: 04/11/2022] [Indexed: 06/14/2023]
Abstract
China has implemented two national clean air actions in 2013-2017 and 2018-2020, respectively, with the aim of reducing primary emissions and hence improving air quality at a national level. It is important to examine the effectiveness of such emission reductions and assess the resulting changes in air quality. However, such evaluation is difficult as meteorological factors can amplify, or obscure the changes of air pollutants, in addition to the emission reduction. In this study, we applied the random forest machine learning technique to decouple meteorological influences from emissions changes, and examined the deweathered trends of air pollutants in 12 Chinese mega-cities during 2013-2020. The observed concentrations of all criteria pollutants except O3 showed significant declines from 2013 to 2020, with PM2.5 annual decline rates of 6-9% in most cities. In contrast, O3 concentrations increased with annual growth rates of 1-9%. Compared with the observed results, all the pollutants showed smoothed but similar variation in trend and annual rate-of-change after weather normalization. The response of O3 to NO2 concentrations indicated significant regional differences in photochemical regimes, and the differences between observed and deweathered results provided implications for volatile organic compound emission reductions in O3 pollution mitigation. We further evaluated the effectiveness of first and second clean air actions by removing the meteorological influence. We found that the meteorology can make negative or positive contribution in reducing pollutant concentrations from emission reduction, depending on type of pollutants, locations, and time period. Among the 12 mega-cities, only Beijing showed a positive meteorological contribution in amplifying reductions in main pollutants except O3 during both clean air action periods. Considering the large and variable impact of meteorological effects in changing air quality, we suggest that similar deweathered analysis is needed as a routine policy evaluation tool on a regional basis.
Collapse
Affiliation(s)
- Yong Guo
- Department of Building Science, Tsinghua University, Beijing, China; Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Beijing, China
| | - Kangwei Li
- Univ Lyon, Université Claude Bernard Lyon 1, CNRS, IRCELYON, F-69626, Villeurbanne, France.
| | - Bin Zhao
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing, 100084, China
| | - Jiandong Shen
- Hangzhou Environmental Monitoring Center Station, Hangzhou, 310007, China
| | - William J Bloss
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Merched Azzi
- New South Wales Department of Planning, Industry and Environment, PO Box 29, Lidcombe, NSW, 1825, Australia
| | - Yinping Zhang
- Department of Building Science, Tsinghua University, Beijing, China; Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Beijing, China
| |
Collapse
|
19
|
Shen F, Hegglin MI, Luo Y, Yuan Y, Wang B, Flemming J, Wang J, Zhang Y, Chen M, Yang Q, Ge X. Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China. NPJ CLIMATE AND ATMOSPHERIC SCIENCE 2022; 5:54. [PMID: 35789740 PMCID: PMC9244310 DOI: 10.1038/s41612-022-00276-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 06/06/2022] [Indexed: 05/07/2023]
Abstract
The COVID-19 restrictions in 2020 have led to distinct variations in NO2 and O3 concentrations in China. Here, the different drivers of anthropogenic emission changes, including the effects of the Chinese New Year (CNY), China's 2018-2020 Clean Air Plan (CAP), and the COVID-19 lockdown and their impact on NO2 and O3 are isolated by using a combined model-measurement approach. In addition, the contribution of prevailing meteorological conditions to the concentration changes was evaluated by applying a machine-learning method. The resulting impact on the multi-pollutant Health-based Air Quality Index (HAQI) is quantified. The results show that the CNY reduces NO2 concentrations on average by 26.7% each year, while the COVID-lockdown measures have led to an additional 11.6% reduction in 2020, and the CAP over 2018-2020 to a reduction in NO2 by 15.7%. On the other hand, meteorological conditions from 23 January to March 7, 2020 led to increase in NO2 of 7.8%. Neglecting the CAP and meteorological drivers thus leads to an overestimate and underestimate of the effect of the COVID-lockdown on NO2 reductions, respectively. For O3 the opposite behavior is found, with changes of +23.3%, +21.0%, +4.9%, and -0.9% for CNY, COVID-lockdown, CAP, and meteorology effects, respectively. The total effects of these drivers show a drastic reduction in multi-air pollutant-related health risk across China, with meteorology affecting particularly the Northeast of China adversely. Importantly, the CAP's contribution highlights the effectiveness of the Chinese government's air-quality regulations on NO2 reduction.
Collapse
Affiliation(s)
- Fuzhen Shen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China
- Department of Meteorology, University of Reading, Reading, RG6 6BX UK
- Institute of Energy and Climate Research, IEK-7: Stratosphere, Forschungszentrum Jülich, 52425 Jülich, Germany
| | - Michaela I. Hegglin
- Department of Meteorology, University of Reading, Reading, RG6 6BX UK
- Institute of Energy and Climate Research, IEK-7: Stratosphere, Forschungszentrum Jülich, 52425 Jülich, Germany
| | | | - Yue Yuan
- Jining Meteorological Bureau, 272000 Shandong, China
| | - Bing Wang
- Henley Business School, University of Reading, Reading, RG6 6UD UK
| | | | - Junfeng Wang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138 USA
| | - Yunjiang Zhang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China
| | - Mindong Chen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China
| | - Qiang Yang
- Hongkong University of Science and Technology, 999007 Hong Kong, China
| | - Xinlei Ge
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China
| |
Collapse
|
20
|
High-Resolution Urban Air Quality Mapping for Multiple Pollutants Based on Dense Monitoring Data and Machine Learning. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19138005. [PMID: 35805664 PMCID: PMC9265361 DOI: 10.3390/ijerph19138005] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/28/2022] [Accepted: 06/28/2022] [Indexed: 12/10/2022]
Abstract
Spatially explicit urban air quality information is important for urban fine-management and public life. However, existing air quality measurement methods still have some limitations on spatial coverage and system stability. A micro station is an emerging monitoring system with multiple sensors, which can be deployed to provide dense air quality monitoring data. Here, we proposed a method for urban air quality mapping at high-resolution for multiple pollutants. By using the dense air quality monitoring data from 448 micro stations in Lanzhou city, we developed a decision tree model to infer the distribution of citywide air quality at a 500 m × 500 m × 1 h resolution, with a coefficient of determination (R2) value of 0.740 for PM2.5, 0.754 for CO and 0.716 for SO2. Meanwhile, we also show that the deployment density of the monitoring stations can have a significant impact on the air quality inference results. Our method is able to show both short-term and long-term distribution of multiple important pollutants in the city, which demonstrates the potential and feasibility of dense monitoring data combined with advanced data science methods to support urban atmospheric environment fine-management, policy making, and public health studies.
Collapse
|
21
|
Long-Term Variations of Meteorological and Precursor Influences on Ground Ozone Concentrations in Jinan, North China Plain, from 2010 to 2020. ATMOSPHERE 2022. [DOI: 10.3390/atmos13060994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Ground-level ozone (O3) pollution in the North China Plain has become a serious environmental problem over the last few decades. The influence of anthropogenic emissions and meteorological conditions on ozone trends have become the focus of widespread research. We studied the long-term ozone trends at urban and suburban sites in a typical city in North China and quantified the contributions of anthropogenic and meteorological factors. The results show that urban O3 increased and suburban O3 decreased from 2010 to 2020. The annual 90th percentile of the maximum daily 8-h average of ozone in urban areas increased by 3.01 μgm−3year−1 and, in suburban areas, it decreased by 3.74 μgm−3year−1. In contrast to the meteorological contributions, anthropogenic impacts are the decisive reason for the different ozone trends in urban and suburban areas. The rapid decline in nitrogen oxides (NOX) in urban and suburban areas has had various effects. In urban areas, this leads to a weaker titration of NOX and enhanced O3 formation, while in suburban areas, this weakens the photochemical production of O3. Sensitivity analysis shows that the O3 formation regime is in a transition state in both the urban and suburban areas. However, this tends to be limited to volatile organic compounds (VOCs) in urban areas and to NOX in suburban areas. One reasonable approach to controlling ozone pollution should be to reduce nitrogen oxide emissions while strengthening the control of VOCs.
Collapse
|
22
|
Ma Q, Wang W, Liu D, Zhao R, Zhao J, Li W, Pan Y, Zhang D. Haze Occurrence Caused by High Gas-to-Particle Conversion in Moisture Air under Low Pollutant Emission in a Megacity of China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19116405. [PMID: 35681990 PMCID: PMC9179953 DOI: 10.3390/ijerph19116405] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 05/19/2022] [Accepted: 05/20/2022] [Indexed: 12/10/2022]
Abstract
Haze occurred in Zhengzhou, a megacity in the northern China, with the PM2.5 as high as 254 μg m−3 on 25 December 2019, despite the emergency response measure of restriction on the emission of anthropogenic pollutants which was implemented on December 19 for suppressing local air pollution. Air pollutant concentrations, chemical compositions, and the origins of particulate matter with aerodynamic diameter smaller than 2.5 µm (PM2.5) between 5–26 December were investigated to explore the reasons for the haze occurrence. Results show that the haze was caused by efficient SO2-to-suflate and NOx-to-nitrate conversions under high relative humidity (RH) condition. In comparison with the period before the restriction (5–18 December) when the PM2.5 was low, the concentration of PM2.5 during the haze (19–26 December) was 173 µg m−3 on average with 51% contributed by sulfate (31 µg m−3) and nitrate (57 µg m−3). The conversions of SO2-to-sulfate and NOx-to-nitrate efficiently produced sulfate and nitrate although the concentration of the two precursor gases SO2 and NOx was low. The high RH, which was more than 70% and the consequence of artificial water-vapor spreading in the urban air for reducing air pollutants, was the key factor causing the conversion rates to be enlarged in the constriction period. In addition, the last 48 h movement of the air parcels on 19–26 December was stagnant, and the air mass was from surrounding areas within 200 km, indicating weather conditions favoring the accumulation of locally-originated pollutants. Although emergency response measures were implemented, high gas-to-particle conversions in stagnant and moisture circumstances can still cause severe haze in urban air. Since the artificial water-vapor spreading in the urban air was one of the reasons for the high RH, it is likely that the spreading had unexpected side effects in some certain circumstances and needs to be taken into consideration in future studies.
Collapse
Affiliation(s)
- Qingxia Ma
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, College of Geography and Environmental Science, Henan University, Kaifeng 475004, China; (Q.M.); (D.L.); (J.Z.); (W.L.)
- Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security, Kaifeng 475004, China
| | - Weisi Wang
- Henan Ecological and Environmental Monitoring Center, Zhengzhou 450007, China;
| | - Dexin Liu
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, College of Geography and Environmental Science, Henan University, Kaifeng 475004, China; (Q.M.); (D.L.); (J.Z.); (W.L.)
| | - Rongke Zhao
- Henan Kaifeng College of Science Technology and Communication, Kaifeng 475004, China;
| | - Jingqi Zhao
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, College of Geography and Environmental Science, Henan University, Kaifeng 475004, China; (Q.M.); (D.L.); (J.Z.); (W.L.)
| | - Wanlong Li
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, College of Geography and Environmental Science, Henan University, Kaifeng 475004, China; (Q.M.); (D.L.); (J.Z.); (W.L.)
| | - Yanfang Pan
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, College of Geography and Environmental Science, Henan University, Kaifeng 475004, China; (Q.M.); (D.L.); (J.Z.); (W.L.)
- Correspondence: (Y.P.); (D.Z.)
| | - Daizhou Zhang
- Faculty of Environmental and Symbiotic Sciences, Prefectural University of Kumamoto, Kumamoto 862-8502, Japan
- Correspondence: (Y.P.); (D.Z.)
| |
Collapse
|
23
|
Liu X, Li Z, Zhang J, Guo M, Lu F, Xu X, Deginet A, Liu M, Dong Z, Hu Y, Liu M, Li Y, Wu M, Luo Y, Tao L, Lin H, Guo X. The association between ozone and ischemic stroke morbidity among patients with type 2 diabetes in Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 818:151733. [PMID: 34800453 DOI: 10.1016/j.scitotenv.2021.151733] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 11/12/2021] [Accepted: 11/12/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND The association between ozone and ischemic stroke has been widely reported; however, the association among patients with type 2 diabetes (T2D) has remained largely unknown. METHODS The time series data of daily morbidity and concentrations of ozone from 2014 to 2018 were collected in Beijing, China. A time-stratified case-crossover study combined with a distributed lag nonlinear model was used to estimate the ozone effect on stroke morbidity among T2D patients. Based on principal diagnosis, ischemic stroke cases were identified according to the International Classification of Diseases (I63), and a history of T2D was coded as E12. RESULTS A total of 149,757 hospital admissions for ischemic stroke among T2D patients were recorded in Beijing. Approximately U-shaped exposure-response curves were observed for ozone and ischemic stroke morbidity among T2D patients. With a reference at 54.91 μg/m3, extreme-low (5th: 9.59 μg/m3) ozone was significantly associated with a decreased risk for ischemic stroke [RR = 0.88, 95% confidence interval (CI): 0.80-0.98]. Subgroup analysis showed that extremely low-ozone (5th) level only had a significant protective effect in males and elderly population, with a RR value of 0.86 (95% CI: 0.76-0.97) and 0.85 (95% CI: 0.75-0.96), respectively. Extreme-high ozone (99th: 157.06 μg/m3) was significantly associated with an increased risk for ischemic stroke (RR = 1.33, 95% CI: 1.12-1.57). The effect size was 1.34 (95% CI: 1.10-1.63) for males and 1.32 (95% CI: 1.07-1.63) for females, and the difference was not significant (Z = -0.29, P = 0.77). The effect size in younger adults was significantly higher than that in participants aged ≥65 years [1.52 (95% CI: 1.21-1.91) vs. 1.22 (95% CI: 1.01-1.47), Z = -1.62, P < 0.05]. CONCLUSIONS U-shaped associations were observed between ozone and ischemic stroke morbidity in T2D patients. Men and elderly population are vulnerable to low-ozone level, and the younger adults are more susceptible to extremely high-ozone level than the elderly.
Collapse
Affiliation(s)
- Xiangtong Liu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Zhiwei Li
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Jie Zhang
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Moning Guo
- Beijing Municipal Health Commission Information Center, Beijing 100034, China.
| | - Feng Lu
- Beijing Municipal Health Commission Information Center, Beijing 100034, China.
| | - Xiaolin Xu
- The University of Queensland, Brisbane, Australia; School of Public Health, Zhejiang University, Hangzhou 310058, China.
| | - Aklilu Deginet
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Mengmeng Liu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Zhaomin Dong
- School of Space and Environment, Beihang University, Beijing 100191, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100191, China.
| | - Yaoyu Hu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Mengyang Liu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Yutong Li
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Mengqiu Wu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Yanxia Luo
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Lixin Tao
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Xiuhua Guo
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
| |
Collapse
|
24
|
An ambient air quality evaluation model based on improved evidence theory. Sci Rep 2022; 12:5753. [PMID: 35388022 PMCID: PMC8986843 DOI: 10.1038/s41598-022-09344-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 03/21/2022] [Indexed: 11/28/2022] Open
Abstract
It is significant to evaluate the air quality scientifically for the management of air pollution. As an air quality comprehensive evaluation problem, its uncertainty can be effectively addressed by the Dempster–Shafer (D–S) evidence theory. However, there is not enough research on air quality comprehensive assessment using D–S theory. Aiming at the counterintuitive fusion results of the D–S combination rule in the field of comprehensive decision, an improved evidence theory with evidence weight and evidence decision credibility (here namely DCre-Weight method) is proposed, and it is used to comprehensively evaluate air quality. First, this method determines the weights of evidence by the entropy weight method and introduces the decision credibility by calculating the dispersion of different evidence decisions. An algorithm case shows that the credibility of fusion results is improved and the uncertainty is well expressed. It can make reasonable fusion results and solve the problems of D–S. Then, the air quality evaluation model based on improved evidence theory (here namely the DCreWeight model) is proposed. Finally, according to the hourly air pollution data in Xi’an from June 1, 2014, to May 1, 2016, comparisons are made with the D–S, other improved methods of evidence theory, and a recent fuzzy synthetic evaluation method to validate the effectiveness of the model. Under the national AQCI standard, the MAE and RMSE of the DCreWeight model are 1.02 and 1.17. Under the national AQI standard, the DCreWeight model has the minimal MAE, RMSE, and maximal index of agreement, which validated the superiority of the DCreWeight model. Therefore, the DCreWeight model can comprehensively evaluate air quality. It can provide a scientific basis for relevant departments to prevent and control air pollution.
Collapse
|
25
|
Song Y, Zhang Y, Liu J, Zhang C, Liu C, Liu P, Mu Y. Rural vehicle emission as an important driver for the variations of summertime tropospheric ozone in the Beijing-Tianjin-Hebei region during 2014-2019. J Environ Sci (China) 2022; 114:126-135. [PMID: 35459478 DOI: 10.1016/j.jes.2021.08.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 07/31/2021] [Accepted: 08/01/2021] [Indexed: 10/19/2022]
Abstract
Tropospheric ozone (O3) pollution is increasing in the Beijing-Tianjin-Hebei (BTH) region despite a significant decline in atmospheric fine aerosol particles (PM2.5) in recent years. However, the intrinsic reason for the elevation of the regional O3 is still unclear. In this study, we analyzed the spatio-temporal variations of tropospheric O3 and relevant pollutants (PM2.5, NO2, and CO) in the BTH region based on monitoring data from the China Ministry of Ecology and Environment during the period of 2014-2019. The results showed that summertime O3 concentrations were constant in Beijing (BJ, 0.06 µg/(m3•year)) but increased significantly in Tianjin (TJ, 9.09 µg/(m3•year)) and Hebei (HB, 6.06 µg/(m3•year)). Distinct O3 trends between Beijing and other cities in BTH could not be attributed to the significant decrease in PM2.5 (from -5.08 to -6.32 µg/(m3•year)) and CO (from -0.053 to -0.090 mg/(m3•year)) because their decreasing rates were approximately the same in all the cities. The relatively stable O3 concentrations during the investigating period in BJ may be attributed to a faster decreasing rate of NO2 (BJ: -2.55 µg/(m3•year); TJ: -1.16 µg/(m3•year); HB: -1.34 µg/(m3•year)), indicating that the continued reduction of NOx will be an effective mitigation strategy for reducing regional O3 pollution. Significant positive correlations were found between daily maximum 8 hr average (MDA8) O3 concentrations and vehicle population and highway freight transportation in HB. Therefore, we speculate that the increase in rural NOx emissions due to the increase in vehicle emissions in the vast rural areas around HB greatly accelerates regional O3 formation, accounting for the significant increasing trends of O3 in HB.
Collapse
Affiliation(s)
- Yifei Song
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuanyuan Zhang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Junfeng Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chenglong Zhang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chengtang Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 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 Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yujing Mu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| |
Collapse
|
26
|
Dong C, Li J, Qi Y. Decomposing PM 2.5 air pollution rebounds in Northern China before COVID-19. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:28688-28699. [PMID: 34988793 PMCID: PMC8731191 DOI: 10.1007/s11356-021-17889-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 11/27/2021] [Indexed: 05/30/2023]
Abstract
China's efforts to curb air pollution have drastically reduced its concentrations of fine particulate matter (PM2.5) from 2013 to 2018 nationwide. However, few studies examined the most recent changes in PM2.5 concentrations and questioned if the previous PM2.5 declining trend was sustained or not. This study took a deep dive into the PM2.5 trend for 136 northern cities of China from 2015 to early 2020 before the coronavirus disease 2019 (the COVID-19 hereafter) crisis, using ground-based PM2.5 data notably adjusted for a key measurement method change. We find that mean PM2.5 concentrations in northern China increased by 5.16 µg/m3 in 2019, offsetting 80% of the large reduction achieved in 2018. The rebound was more significant during the heating seasons (HS; Nov to next Mar) over the 2 years: 10.49 µg/m3 from the 2017 HS to the 2019 HS. A multiple linear regression analysis further revealed that anthropogenic factors contributed to around 50% of the PM2.5 rebound in northern cities of China. Such a significant role of anthropogenic factors in driving the rebound was tightly linked to deep cuts in PM2.5 concentrations in the previous year, systemic adjustment of policy targets and mitigation measures by the government, and the rising marginal cost of these measures. These findings suggest the need to chart a more sustainable path for future PM2.5 emission reductions, with an emphasis on key regions during key pollution periods.
Collapse
Affiliation(s)
- Changgui Dong
- School of Public Administration and Policy, Renmin University of China, Beijing, 100872, China
- National Academy of Development and Strategy, Renmin University of China, Beijing, 100872, China
| | - Jiaying Li
- School of Public Administration and Policy, Renmin University of China, Beijing, 100872, China.
| | - Ye Qi
- Thrust of Innovation, Policy and Entrepreneurship and Institute for Public Policy, The Hong Kong University of Science and Technology, Hong Kong, China.
- School of Public Policy and Management, Tsinghua University, Beijing, 100084, China.
| |
Collapse
|
27
|
Li F, Tong S, Jia C, Zhang X, Lin D, Zhang W, Li W, Wang L, Ge M, Xia L. Sources of ambient non-methane hydrocarbon compounds and their impacts on O 3 formation during autumn, Beijing. J Environ Sci (China) 2022; 114:85-97. [PMID: 35459517 DOI: 10.1016/j.jes.2021.08.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 07/31/2021] [Accepted: 08/01/2021] [Indexed: 11/19/2022]
Abstract
The field observation of 54 non-methane hydrocarbon compounds (NMHCs) was conducted from September 1 to October 20 in 2020 during autumn in Haidian District, Beijing. The mean concentration of total NMHCs was 29.81 ± 11.39 ppbv during this period, and alkanes were the major components. There were typical festival effects of NMHCs with lower concentration during the National Day. Alkenes and aromatics were the dominant groups in ozone formation potential (OFP) and OH radical loss rate (LOH). The positive matrix factorization (PMF) running results revealed that vehicular exhaust became the biggest source in urban areas, followed by liquefied petroleum gas (LPG) usage, solvent usage, and fuel evaporation. The box model coupled with master chemical mechanism (MCM) was applied to study the impacts of different NMHCs sources on ozone (O3) formation in an O3 episode. The simulation results indicated that reducing NMHCs concentration could effectively suppress O3 formation. Moreover, reducing traffic-related emissions of NMHCs was an effective way to control O3 pollution at an urban site in Beijing.
Collapse
Affiliation(s)
- Fangjie Li
- College of Chemistry, Liaoning University, Shenyang 110036, China; State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Shengrui Tong
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China.
| | - Chenhui Jia
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Xinran Zhang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Deng Lin
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; Key Laboratory of Oasis Ecology, College of Resource and Environment Sciences, Xinjiang University, Urumqi 830046, China
| | - Wenqian Zhang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Weiran Li
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lili Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, Beijing 100029, China
| | - Maofa Ge
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lixin Xia
- College of Chemistry, Liaoning University, Shenyang 110036, China; Department of Chemical and Environmental Engineering, Yingkou Institute of Technology, Yingkou 115014, China.
| |
Collapse
|
28
|
Feng X, Shao L, Jones T, Li Y, Cao Y, Zhang M, Ge S, Yang CX, Lu J, BéruBé K. Oxidative potential and water-soluble heavy metals of size-segregated airborne particles in haze and non-haze episodes: Impact of the "Comprehensive Action Plan" in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 814:152774. [PMID: 34986423 DOI: 10.1016/j.scitotenv.2021.152774] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 12/14/2021] [Accepted: 12/25/2021] [Indexed: 05/17/2023]
Abstract
Air pollution is a major environmental health challenge in megacities, and as such a Comprehensive Action Plan (CAP) was issued in 2017 for Beijing, the capital city of China. Here we investigated the size-segregated airborne particles collected after the implementation of the CAP, intending to understand the change of oxidative potential and water-soluble heavy metal (WSHM) levels in 'haze' and 'non-haze' days. The DNA damage and the levels of WSHM were analyzed by Plasmid Scission Assay (PSA) and High-Resolution Inductively Coupled Plasma Mass Spectrometry (HR-ICP-MS) techniques. The PM mass concentration was higher in the fine particle size (0.43-2.1 μm) during haze days, except for the samples affected by mineral dust. The particle-induced DNA damage caused by fine sized particles (0.43-2.1 μm) exceeded that caused by the coarse sized particles (4.7-10 μm). The DNA damage from haze day particles significantly exceeded those collected on non-haze days. Prior to the instigation of the CAP, the highest value of DNA damage decreased, and DNA damage was seen in the finer size (0.43-1.1 μm). The Pearson correlation coefficient between the concentrations of water-soluble Pb, Cr, Cd and Zn were positively correlated with DNA damage, suggesting that these WSHM had significant oxidative potential. The mass concentrations of water-soluble trace elements (WSTE) and individual heavy metals were enriched in the finer particles between 0.43 μm to 1.1 μm, implying that smaller sized particles posed higher health risks. In contrast, the significant reduction in the mass concentration of water-soluble Cd and Zn, and the decrease of the maximum and average values of DNA damage after the CAP, demonstrated its effectiveness in restricting coal-burning emissions. These results have demonstrated that the Beijing CAP policy has been successful in reducing the toxicity of 'respirable' ambient particles.
Collapse
Affiliation(s)
- Xiaolei Feng
- State Key Laboratory of Coal Resources and Safe Mining, and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Longyi Shao
- State Key Laboratory of Coal Resources and Safe Mining, and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China.
| | - Tim Jones
- School of Earth and Environmental Sciences, Cardiff University, Park Place, Cardiff CF10 3AT, Wales, UK
| | - Yaowei Li
- State Key Laboratory of Coal Resources and Safe Mining, and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Yaxin Cao
- State Key Laboratory of Coal Resources and Safe Mining, and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Mengyuan Zhang
- State Key Laboratory of Coal Resources and Safe Mining, and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Shuoyi Ge
- State Key Laboratory of Coal Resources and Safe Mining, and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Cheng-Xue Yang
- Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing 100083, China
| | - Jing Lu
- State Key Laboratory of Coal Resources and Safe Mining, and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Kelly BéruBé
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, Wales, UK
| |
Collapse
|
29
|
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.
Collapse
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
| |
Collapse
|
30
|
Xue J, Zhao T, Luo Y, Miao C, Su P, Liu F, Zhang G, Qin S, Song Y, Bu N, Xing C. Identification of ozone sensitivity for NO 2 and secondary HCHO based on MAX-DOAS measurements in northeast China. ENVIRONMENT INTERNATIONAL 2022; 160:107048. [PMID: 34959197 DOI: 10.1016/j.envint.2021.107048] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 12/11/2021] [Accepted: 12/13/2021] [Indexed: 06/14/2023]
Abstract
In this study, tropospheric formaldehyde (HCHO) vertical column densities (VCDs) were measured using multi-axis differential optical absorption spectroscopy (MAX-DOAS) from January to November 2019 in Shenyang, Northeast China. The maximum HCHO VCD value appeared in the summer (1.74 × 1016 molec/cm2), due to increased photo-oxidation of volatile organic compounds (VOCs). HCHO concentrations increased from 08:00 and peaked near 13:00, which was mainly attributed to the increased release of isoprene from plants and enhanced photolysis at noon. The HCHO VCDs observed by MAX-DOAS and OMI have a good correlation coefficient (R) of 0.78, and the contributions from primary and secondary HCHO sources were distinguished by the multi-linear regression model. The anthropogenic emissions showed unobvious seasonal variations, and the primary HCHO was relatively stable in Shenyang. Secondary HCHO contributed 82.62%, 83.90%, 78.90%, and 41.53% to the total measured ambient HCHO during the winter, spring, summer, and autumn, respectively. We also found a good correlation (R = 0.78) between enhanced vegetation index (EVI) and HCHO VCDs, indicating that the oxidation of biogenic volatile organic compounds (BVOCs) was the main source of HCHO. The ratio of secondary HCHO to nitrogen dioxide (NO2) was used as the tracer to analyze O3-NOx-VOC sensitivities. We found that the VOC-limited, VOC-NOx-limited, and NOx-limited regimes made up 93.67%, 6.23%, 0.11% of the overall measurements, respectively. In addition, summertime ozone (O3) sensitivity changed from VOC-limited in the morning to VOC-NOx-limited in the afternoon. Therefore, this study offers information on HCHO sources and corresponding O3 production sensitivities to support strategic management decisions.
Collapse
Affiliation(s)
- Jiexiao Xue
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Ting Zhao
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Yifu Luo
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Congke Miao
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Pinjie Su
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Feng Liu
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Guohui Zhang
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Sida Qin
- Liaoning Science and Technology Center for Ecological and Environmental Protection, Shenyang 110161, China
| | - Youtao Song
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Naishun Bu
- School of Environmental Science, Liaoning University, Shenyang 110036, China; Key Laboratory of Wetland Ecology and Environment Research in Cold Regions of Heilongjiang Province, Harbin University, 150086, China.
| | - Chengzhi Xing
- Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China.
| |
Collapse
|
31
|
Ban J, Ma R, Zhang Y, Li T. PM 2.5-associated risk for cardiovascular hospital admission and related economic burdens in Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 799:149445. [PMID: 34365258 DOI: 10.1016/j.scitotenv.2021.149445] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/30/2021] [Accepted: 07/30/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND The study of ambient air particulate matter (PM2.5)-associated health and economic burdens of cardiovascular disease are crucial for air pollution control and disease prevention strategies. Quantified evidence remains inadequate. OBJECTIVES This study aimed to estimate the PM2.5 associated risk in cardiovascular hospital admission as well as attributable health burdens and economic costs. METHODS A total of 2,202,244 hospital admission records of cardiovascular disease and six common clinical subtypes in Beijing were included. A time-stratified case-crossover design was applied to estimate the associations and the concentration-response curve. Then, the annual average additional hospital admissions, days of hospital stay, and hospital expenditures were evaluated from 2013 to 2017 and compared between 2017 and 2013. RESULTS The results showed that each 10 μg/m3 increase in previous-day PM2.5 concentration was associated with a risk increase of 0.44% (95%CI: 0.40%, 0.47%) for cardiovascular disease, 0.66% (95%CI: 0.58%, 0.73%) for angina pectoris, 0.53% (95%CI: 0.39%, 0.66%) for chronic ischemic heart disease, 0.48% (95%CI: 0.34%, 0.63%) for myocardial infarction, 0.44% (95%CI: 0.29%, 0.60%) for hypertensive heart disease and 0.40% (95%CI: 0.27%, 0.52%) for ischemic stroke. There were 1938 PM2.5 attributed additional hospital admissions, resulting in 21,668 additional days in hospital, along with 5527.12 and 1947.04 ten-thousand of additional total hospital cost and self-afforded cost, respectively. Compared with 2013, the above-mentioned four burdens decreased by 18.17%, 28.80%, 18.90% and 13.72% in 2017, respectively. CONCLUSION PM2.5 exposure was significantly associated with substantial burdens of cardiovascular hospital admission and economic expenditures. The results highlight the necessity of continuous PM2.5 control from the perspective of healthy and sustainable city development in urban China.
Collapse
Affiliation(s)
- Jie Ban
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Runmei Ma
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Yi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
| |
Collapse
|
32
|
Jonidi Jafari A, Charkhloo E, Pasalari H. Urban air pollution control policies and strategies: a systematic review. JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE & ENGINEERING 2021; 19:1911-1940. [PMID: 34900316 PMCID: PMC8617239 DOI: 10.1007/s40201-021-00744-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Accepted: 09/20/2021] [Indexed: 06/01/2023]
Abstract
A wide range of policies, strategies, and interventions have been implemented to improve air quality all over the world. This systematic review comprehensively appraises the policies and strategies on air pollutants controls enacted in different countries, worldwide. Three databases, Web of Science, PubMed and Scopus, were used for the search. After screening, a total of 114 eligible manuscripts were selected from 2219 documents for further analysis. Selected articles were divided into two categories: (1) articles focusing on introducing the policies and strategies enacted for controlling air pollution in different countries, and (2) articles which focused on different policies and strategies to control one or more specific pollutants. In the former one, urban air pollution control strategies and policies were divided into four categories, namely, general strategies and policies, transportation, energy, and industry. In case of latter category, policies and strategies focused on controlling six pollutants (PM, SO2, NO2, VOCS, O3 and photochemical smog). The results indicated that, the most common policies and strategies enacted in most countries are pertinent to the transportation sector. Changing energy sources, in particular elimination or limited use of solid fuels, was reported as an effective action by governments to reduce air pollution. Overall, most policies enacted by governments can be divided into three general categories: (a) incentive policies such as implementing a free public transportation program to use fewer private cars, (b) supportive policies such as paying subsidies to change household fuels, and (c) punitive policies such as collecting tolls for cars to enter the congestion charging areas. Depending on the circumstances, these policies are implemented alone or jointly. In addition to the acceptance of international agreements to reduce air pollution by governments, greater use of renewable energy, clean fuels, and low-pollution or no-pollution vehicles such as electric vehicles play an important role in reducing air pollution.
Collapse
Affiliation(s)
- Ahmad Jonidi Jafari
- Research Center for Environmental Health Technology, Iran University of Medical Sciences, Tehran, Iran
- Department of Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
| | - Esmail Charkhloo
- Research Center for Environmental Health Technology, Iran University of Medical Sciences, Tehran, Iran
- Department of Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
| | - Hasan Pasalari
- Research Center for Environmental Health Technology, Iran University of Medical Sciences, Tehran, Iran
- Department of Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
| |
Collapse
|
33
|
Zhu L, Zhang Y, Wu Z, Zhang C. Spatio-Temporal Characteristics of SO 2 across Weifang from 2008 to 2020. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182212206. [PMID: 34831963 PMCID: PMC8624775 DOI: 10.3390/ijerph182212206] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 11/14/2021] [Accepted: 11/16/2021] [Indexed: 11/30/2022]
Abstract
China has achieved good results in SO2 pollution control, but SO2 pollution still exists in some areas. Analyzing the spatio-temporal distribution of SO2 is critical for regional SO2 pollution prevention and control. Compared with existing air pollution studies that paid more attention to PM2.5, NO2 and O3, and focused on the macro scale, this study took the small-scale Weifang city as the research area, analyzed the temporal and spatial changes in SO2, discussed the migration trajectory of SO2 pollution and explored the impact of wind on SO2 pollution. The results show that the average annual concentration of SO2 in Weifang has exhibited a downward trend in the past 13 years, showing the basic characteristics of “highest in winter, lowest in summer and slightly higher in spring and autumn”, “highest on Sunday, lowest on Thursday and gradually decreasing from Monday to Thursday” and “highest at 9 a.m., lowest at 4 p.m. and gradually increasing from midnight to 9 a.m.”. SO2 concentration showed obvious spatial heterogeneity: higher in the north and lower in the south. In addition, Shouguang, Changyi and Gaomi were seriously polluted. The SO2 pollution shifted from south to northeast. The clean wind direction (southeast wind and northeast wind) of Weifang city accounted for about 41%, and the pollution wind direction (northwest wind and west wind) accounted for about 7%. Drawing from the multi-scale analysis, vegetation, precipitation, temperature, transport situation and human activity were the most relevant factors. Limited to data collection, more quantitative research is needed to gain insight into the influence mechanism in the future.
Collapse
|
34
|
Lin C, Lau AKH, Fung JCH, Song Y, Li Y, Tao M, Lu X, Ma J, Lao XQ. Removing the effects of meteorological factors on changes in nitrogen dioxide and ozone concentrations in China from 2013 to 2020. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 793:148575. [PMID: 34175602 DOI: 10.1016/j.scitotenv.2021.148575] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 05/27/2021] [Accepted: 06/16/2021] [Indexed: 06/13/2023]
Abstract
Previous studies on long-term ozone (O3) variations in China have reported inconsistent conclusions on the role of meteorological factors in controlling said variations. In this study, we used an observation-based decomposition model to conduct an up-to-date investigation of the effects of meteorological factors on the variations in nitrogen dioxide (NO2) and O3 concentrations in China in the summer from 2013 to 2020. The variations in NO2 and O3 concentrations after removing the major meteorological effects were then analyzed to improve our understanding of O3 formation regimes. Ground measurements show that both NO2 and O3 concentrations decreased in eastern, central, and southeastern China (e.g., NO2 and O3 concentrations in Wuhan reduced by 4.3 and 6.2 ppb, respectively), which was not anticipated. Analyses of meteorological effects showed that reduced wind strength, decreased temperature, and increased relative humidity significantly reduced O3 concentrations in eastern and central China (e.g., by 10.5 ppb in Wuhan). After removing the major meteorological effects, the O3 trends were reversed in eastern and central China (e.g., increased by 4.9 ppb in Wuhan). The contrasting trends in NO2 and O3 concentrations suggest that their O3 formations were sensitive to volatile organic compounds (VOC-limited regime). In southeastern China, both NO2 and O3 concentrations decreased, implying that the O3 formation regimes changed to mixed sensitive or nitrogen oxide-limited (NOx-limited) regimes. The meteorological effects varied by region and may play a dominant role in controlling the long-term O3 variation. Our results indicate that the attribution of O3 variation to emission control without accounting for meteorological effects can be misleading.
Collapse
Affiliation(s)
- Changqing Lin
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Alexis K H Lau
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong, China; Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, The Hong Kong University of Science and Technology, Hong Kong, China.
| | - Jimmy C H Fung
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, The Hong Kong University of Science and Technology, Hong Kong, China; Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Yushan Song
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong, China; Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Ying Li
- Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Minghui Tao
- Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
| | - Xingcheng Lu
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Jun Ma
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China
| | - Xiang Qian Lao
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| |
Collapse
|
35
|
Huang L, Wei Y, Zhang L, Ma Z, Zhao W. Estimates of emission strengths of 43 VOCs in wintertime residential indoor environments, Beijing. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 793:148623. [PMID: 34328960 DOI: 10.1016/j.scitotenv.2021.148623] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 06/10/2021] [Accepted: 06/19/2021] [Indexed: 06/13/2023]
Abstract
There are many sources of volatile organic compounds (VOCs) in indoor environments, leading to much higher total indoor VOC concentrations than outdoor counterparts. Given the potential health hazards associated with VOC exposure, it is necessary to estimate the indoor VOC emission strengths. In this study, the indoor and outdoor concentrations of 43 VOCs were concurrently measured in 8 urban residences, Beijing. The indoor/outdoor concentration ratio was used to screen out 36 species having significant indoor sources. A one-compartment steady-state model was developed to estimate the indoor emission strengths of these VOCs, in which ventilation and reaction with ozone were included as sink routes. The order of VOCs in terms of indoor emission strength was d-limonene (a median value of 1.05 g/h), α-pinene (82.50 mg/h), styrene (24.12 mg/h), ß-pinene (9.70 mg/h), formaldehyde (1.97 mg/h), n-dodecane (1.82 mg/h), n-pentadecane (1.66 mg/h), n-hexadecane (1.62 mg/h), n-undecane (1.20 mg/h), acetaldehyde (1.05 mg/h) and 1, 4-dichlorobenzene (0.80 mg/h). The sum of estimates of those VOCs accounted for >95% of total emission strength. Specific indoor sources of those VOCs in the tested homes were identified. Air exchange rate, indoor temperature and air humidity were found to pose significant impacts to the indoor emission strengths of VOCs.
Collapse
Affiliation(s)
- Lihui Huang
- Department of Environmental Engineering, School of Water and Environment, Chang'an University, Xi'an 710054, China; Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region, Ministry of Education, School of Water and Environment, Chang'an University, Xi'an 710054, China; Institute of Built Environment, Department of Building Science, Tsinghua University, Beijing 100084, China.
| | - Yanru Wei
- Department of Environmental Engineering, School of Water and Environment, Chang'an University, Xi'an 710054, China
| | - Liyuan Zhang
- Department of Environmental Engineering, School of Water and Environment, Chang'an University, Xi'an 710054, China; Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region, Ministry of Education, School of Water and Environment, Chang'an University, Xi'an 710054, China
| | - Zhe Ma
- Department of Environmental Engineering, School of Water and Environment, Chang'an University, Xi'an 710054, China
| | - Weiping Zhao
- Institute of Built Environment, Department of Building Science, Tsinghua University, Beijing 100084, China; School of Civil Engineering, Hefei University of Technology, Hefei, Anhui 230001, China
| |
Collapse
|
36
|
Zhang X, Li H, Wang X, Zhang Y, Bi F, Wu Z, Liu Y, Zhang H, Gao R, Xue L, Zhang Q, Chen Y, Chai F, Wang W. Heavy ozone pollution episodes in urban Beijing during the early summertime from 2014 to 2017: Implications for control strategy. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 285:117162. [PMID: 33965854 DOI: 10.1016/j.envpol.2021.117162] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 04/11/2021] [Accepted: 04/13/2021] [Indexed: 06/12/2023]
Abstract
Ground-level ozone (O3) has become the principal air pollutant in Beijing during recent summers. In this context, an investigation of ambient concentrations and variation characteristics of O3 and its precursors in May and June from 2014 to 2017 in a typical urban area of Beijing was carried out, and the formation sensitivity and different causes of heavy O3 pollution (HOP, daily maximum 8-h O3 (MDA8h O3)>124 ppbv) were analyzed. The results showed that the monthly assessment values of the O3 concentrations (the 90th percentile MDA8h O3 within one month) were highest in May or June from 2014 to 2017, and the values presented an overall increasing trend. During this period, the number of O3 pollution days (MDA8h O3 > 75 ppbv) also showed an increasing trend. During the HOP episodes, the concentrations of volatile organic compounds (VOCs), nitrogen oxides (NOX), and carbon monoxide (CO) were higher than their respective mean values in May and June, and the meteorological conditions were more conducive to atmospheric photochemical reactions. The HOP episodes were mainly caused by local photochemical formation. From 2014 to 2017, O3 formation during the HOP episodes shifted from VOC and NOX mixed-limited to VOC-limited conditions, and O3 formation was most sensitive to anthropogenic VOCs. Six categories of VOC sources were identified, among which vehicular exhaust contributed the most to anthropogenic VOCs. The VOC concentrations and OFPs of anthropogenic sources have decreased significantly in recent years, indicating that VOC control measures have been effective in Beijing. Nevertheless, NOX concentrations did not show an evident decreasing trend in the same period. Therefore, more attention should be devoted to O3 pollution control in May and June; control measure adjustments are needed according to the changes in O3 precursors, and coordinated control of VOCs and NOX should be strengthened in long-term planning.
Collapse
Affiliation(s)
- Xin Zhang
- Environment Research Institute, Shandong University, Qingdao, 266237, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Hong Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Xuezhong Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Yujie Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Fang Bi
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Zhenhai Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Yuhong Liu
- Environment Research Institute, Shandong University, Qingdao, 266237, China
| | - Hao Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Rui Gao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Likun Xue
- Environment Research Institute, Shandong University, Qingdao, 266237, China
| | - Qingzhu Zhang
- Environment Research Institute, Shandong University, Qingdao, 266237, China
| | - Yizhen Chen
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Fahe Chai
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Wenxing Wang
- Environment Research Institute, Shandong University, Qingdao, 266237, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| |
Collapse
|
37
|
Xu M, Qin Z, Zhang S, Xie Y. Health and economic benefits of clean air policies in China: A case study for Beijing-Tianjin-Hebei region. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 285:117525. [PMID: 34380223 DOI: 10.1016/j.envpol.2021.117525] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 05/16/2021] [Accepted: 05/17/2021] [Indexed: 05/22/2023]
Abstract
Exposure to PM2.5 is associated with many adverse health effects, leading to additional social costs. The Blue Sky Protection Campaign (BSPC) has been implemented in 2018 in the Beijing-Tianjin-Hebei (BTH) area to control air pollution. This study assesses PM2.5-related health and economic benefits of the BSPC in the BTH region. Results show that by 2020, PM2.5 reduction can avoid 3561 thousand morbidity cases (equivalent to a 24% reduction in the 2020 baseline scenario) and 24 thousand premature deaths (12%) in the BTH region, with the majority benefit in Hebei. By 2030, the avoided morbidity and mortality cases will be 2943 (18%) thousand and 20 (9%) thousand, respectively. PM2.5 reductions are highly effective in reducing work time loss, which will decrease the total annual work time by 1.7 × 108 h (24%) in the BTH region by 2020. From the economic aspect, the reduced PM2.5 concentration will save 30 million USD (25%) health expenditures and avoid 60 billion USD (13%) economic loss by using the value of statistical life (VSL) by 2020. In 2030, the health expenditures and economic loss will also decrease significantly, with 17 million USD (18%) and 63 billion USD (10%), respectively, in the BTH region. Besides, the economic benefits far exceed the policy costs of the BSPC, and the Δ benefit/Δ cost ratios of Beijing are significantly higher than those of Hebei. The BSPC in BTH has significant positive health and economic impacts. This study can provide a basis for future PM2.5-related health risk studies at an urban level in China.
Collapse
Affiliation(s)
- Meng Xu
- School of Economics and Management, Beihang University, Beijing, 100191, China.
| | - Zhongfeng Qin
- School of Economics and Management, Beihang University, Beijing, 100191, China; Key Laboratory of Complex System Analysis, Management and Decision (Beihang University), Ministry of Education, Beijing 100191, China.
| | - Shaohui Zhang
- School of Economics and Management, Beihang University, Beijing, 100191, China; International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361, Laxenburg, Austria.
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, 100191, China; Future Cities Lab, Beihang University, China.
| |
Collapse
|
38
|
Li H, Ma Y, Duan F, Zhu L, Ma T, Yang S, Xu Y, Li F, Huang T, Kimoto T, Zhang Q, Tong D, Wu N, Hu Y, Huo M, Zhang Q, Ge X, Gong W, He K. Stronger secondary pollution processes despite decrease in gaseous precursors: A comparative analysis of summer 2020 and 2019 in Beijing. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 279:116923. [PMID: 33751950 DOI: 10.1016/j.envpol.2021.116923] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 03/04/2021] [Accepted: 03/05/2021] [Indexed: 06/12/2023]
Abstract
To control the spread of COVID-19, China implemented a series of lockdowns, limiting various offline interactions. This provided an opportunity to study the response of air quality to emissions control. By comparing the characteristics of pollution in the summers of 2019 and 2020, we found a significant decrease in gaseous pollutants in 2020. However, particle pollution in the summer of 2020 was more severe; PM2.5 levels increased from 35.8 to 44.7 μg m-3, and PM10 increased from 51.4 to 69.0 μg m-3 from 2019 to 2020. The higher PM10 was caused by two sandstorm events on May 11 and June 3, 2020, while the higher PM2.5 was the result of enhanced secondary formation processes indicated by the higher sulfate oxidation rate (SOR) and nitrate oxidation rate (NOR) in 2020. Higher SOR and NOR were attributed mainly to higher relative humidity and stronger oxidizing capacity. Analysis of PMx distribution showed that severe haze occurred when particles within Bin2 (size ranging 1-2.5 μm) dominated. SO42-(1/2.5) and SO42-(2.5/10) remained stable under different periods at 0.5 and 0.8, respectively, indicating that SO42- existed mainly in smaller particles. Decreases in NO3-(1/2.5) and increases in NO3-(2.5/10) from clean to polluted conditions, similar to the variations in PMx distribution, suggest that NO3- played a role in the worsening of pollution. O3 concentrations were higher in 2020 (108.6 μg m-3) than in 2019 (96.8 μg m-3). Marked decreases in fresh NO alleviated the titration of O3. Furthermore, the oxidation reaction of NO2 that produces NO3- was dominant over the photochemical reaction of NO2 that produces O3, making NO2 less important for O3 pollution. In comparison, a lower VOC/NOx ratio (less than 10) meant that Beijing is a VOC-limited area; this indicates that in order to alleviate O3 pollution in Beijing, emissions of VOCs should be controlled.
Collapse
Affiliation(s)
- Hui Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Yongliang Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China.
| | - Lidan Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Shuo Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Yunzhi Xu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Fan Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Tao Huang
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Takashi Kimoto
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Qinqin Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| | - Dan Tong
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Nana Wu
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Yunxing Hu
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Mingyu Huo
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Xiang Ge
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Wanru Gong
- Kimoto Electric Co. Ltd, Funahashi-Cho, Tennouji-Ku Osaka, 543-0024, Japan
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
| |
Collapse
|
39
|
Hu X, Sun J, Xia C, Shen X, Zhang Y, Zhang X, Zhang S. Simultaneous measurements of PM 1 and PM 10 aerosol scattering properties and their relationships in urban Beijing: A two-year observation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 770:145215. [PMID: 33515892 DOI: 10.1016/j.scitotenv.2021.145215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 01/12/2021] [Accepted: 01/12/2021] [Indexed: 06/12/2023]
Abstract
The aerosol scattering properties of submicron (PM1) and sub-10 μm particles (PM10) under dry conditions (RH <30%) were investigated in Beijing from 2018 to 2019. Using the simultaneous measurement of PM1 and PM10, the scattering properties of super micron (PM10-1) particles were also calculated. At 550 nm, the average of scattering coefficient (σsp) and asymmetry parameter (g) were 208.7 ± 204.9 Mm-1 and 0.61 ± 0.04 for PM10, 140.6 ± 130.2 Mm-1 and 0.60 ± 0.04 for PM1, and 69.8 ± 82.2 Mm-1 and 0.62 ± 0.04 for PM10-1, respectively, while the backscattering ratio (b) values were 0.13 ± 0.02 for PM10 and PM1, and 0.12 ± 0.02 for PM10-1. The mass scattering efficiencies (MSE) for PM10, PM1 and PM10-1 were 2.43 ± 2.37, 3.67 ± 0.96, and 1.73 ± 1.82 m2 g-1, respectively. In 2019, σsp decreased by approximately 18.4% for PM10, and 16.7% for PM1 compared with those in 2018, which was quite similar to the decrease of 17% and 19% for PM10 and PM2.5 mass concentrations during the same time period. The scattering Ångström exponent (SAE450/700), which was 1.88 ± 0.29 for PM1 and 1.50 ± 0.27 for PM10 indicated size distributions dominated by fine mode aerosols. This is also evidenced by the high submicron scattering ratio (Rsp) (71.1% ± 7.9%). The high SAE, Rsp, and high PM1 σsp in the study suggest that control of fine particle pollution is important to reduce overall PM pollution in urban Beijing. In addition, with an increase in σsp, b, Rsp, and SAE gradually decreased, while g and MSE increased. The clearly scattering coefficient-dependent MSE suggests that high aerosol loading and high MSE both play an important role in degraded visibility during heavy pollution periods.
Collapse
Affiliation(s)
- Xinyao Hu
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Junying Sun
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China.
| | - Can Xia
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; Nanjing University of Information Science & Technology, Nanjing 210000, China
| | - Xiaojing Shen
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Yangmei Zhang
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Xiaoye Zhang
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Sinan Zhang
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| |
Collapse
|
40
|
Cao Y, Shao L, Jones T, Oliveira MLS, Ge S, Feng X, Silva LFO, BéruBé K. Multiple relationships between aerosol and COVID-19: A framework for global studies. GONDWANA RESEARCH : INTERNATIONAL GEOSCIENCE JOURNAL 2021; 93:243-251. [PMID: 33584115 PMCID: PMC7871891 DOI: 10.1016/j.gr.2021.02.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 02/03/2021] [Accepted: 02/03/2021] [Indexed: 05/03/2023]
Abstract
COVID-19 (Corona Virus Disease 2019) is a severe respiratory syndrome currently causing a human global pandemic. The original virus, along with newer variants, is highly transmissible. Aerosols are a multiphase system consisting of the atmosphere with suspended solid and liquid particles, which can carry toxic and harmful substances; especially the liquid components. The degree to which aerosols can carry the virus and cause COVID-19 disease is of significant research importance. In this study, we have discussed aerosol transmission as the pathway of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), and the aerosol pollution reduction as a consequence of the COVID-19 lockdown. The aerosol transmission routes of the SARS-CoV-2 can be further subdivided into proximal human-exhaled aerosol transmission and potentially more distal ambient aerosol transmission. The human-exhaled aerosol transmission is a direct dispersion of the SARS-CoV-2. The ambient aerosol transmission is an indirect dispersion of the SARS-CoV-2 in which the aerosol acts as a carrier to spread the virus. This indirect dispersion can also stimulate the up-regulation of the expression of SARS-CoV-2 receptor ACE-2 (Angiotensin Converting Enzyme 2) and protease TMPRSS2 (Transmembrane Serine Protease 2), thereby increasing the incidence and mortality of COVID-19. From the aerosol quality data around the World, it can be seen that often atmospheric pollution has significantly decreased due to factors such as the reduction of traffic, industry, cooking and coal-burning emissions during the COVID-19 lockdown. The airborne transmission potential of SARS-CoV-2, the infectivity of the virus in ambient aerosols, and the reduction of aerosol pollution levels due to the lockdowns are crucial research subjects.
Collapse
Affiliation(s)
- Yaxin Cao
- State Key Laboratory of Coal Resources and Safe Mining and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Longyi Shao
- State Key Laboratory of Coal Resources and Safe Mining and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Tim Jones
- School of Earth and Environmental Sciences, Cardiff University, Cardiff, CF10, 3YE, Wales, UK
| | - Marcos L S Oliveira
- Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, 080002 Barranquilla, Atlántico, Colombia
- Departamento de Ingeniería Civil y Arquitectura, Universidad de Lima, Avenida Javier Prado Este 4600 - Santiago de Surco 1503, Peru
| | - Shuoyi Ge
- State Key Laboratory of Coal Resources and Safe Mining and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Xiaolei Feng
- State Key Laboratory of Coal Resources and Safe Mining and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Luis F O Silva
- Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, 080002 Barranquilla, Atlántico, Colombia
| | - Kelly BéruBé
- School of Biosciences, Cardiff University, Cardiff CF10 3AX, Wales, UK
| |
Collapse
|
41
|
Xue Y, Wu T, Cui Y, Gong B, Li X, Qin X, Cao X, Liu X, Ai Y, Han J, Jin T. Energy consumption and pollutant emission of diesel-fired combustion from 2009 to 2018 in Beijing, China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2021; 285:112137. [PMID: 33588167 DOI: 10.1016/j.jenvman.2021.112137] [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] [Received: 11/09/2020] [Revised: 01/16/2021] [Accepted: 02/03/2021] [Indexed: 06/12/2023]
Abstract
Diesel-fired combustion is one of the main sources of air pollution in the world. In this study, to better understand the energy consumption and main air pollutant emissions of diesel-fired combustion, a practical investigation and historical data analyses were conducted to determine the variations and driving forces of diesel consumption, the distribution of diesel consumption, and the contribution of emissions among various industries. Based on the results of this study, future control measures can be proposed for diesel-fired combustion. The results show that economic development led to an increase in the total volume of passengers and freight transportation, and the number of diesel vehicles increased from 0.16 million in 2009 to 0.25 million in 2018. However, diesel consumption in Beijing decreased from 2.4 Mt in 2009 to 1.8 Mt in 2018 due to the dominant driving forces, such as structural optimization of the diesel vehicle fleet and stricter limit standards for single-vehicle fuel consumption. The use of diesel vehicles in the logistics and transportation industries and the use of diesel-fired machinery in the construction industry were the two main sources of diesel consumption, accounting for 55% and 23% of the total, respectively. The main air pollutant emissions from diesel-fired combustion from 2009 to 2018 first increased and then decreased, while the NOX emissions peaked at 74,800 tons in 2014, which was affected by the structural optimization of the vehicle fleet and the elimination of old diesel trucks. The emissions finally decreased to 54,000 tons in 2018, which was approximately 89% of the amount in 2009. However, the continuously increasing contribution of diesel combustion to the total emissions requires more attention. The electrification of diesel vehicles and the structural upgrading of diesel vehicles have played important roles in mitigating the emissions of diesel combustion. Our study suggests that consumption control targets should be set, reduction plans for key industries such as the logistics and transportation, construction, and tourism industries should be developed, and low-emission zones should be created to promote the elimination and updating of low-emission diesel vehicles and machinery.
Collapse
Affiliation(s)
- Yifeng Xue
- National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing, 100037, China
| | - Tongran Wu
- National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing, 100037, China
| | - Yangyang Cui
- National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing, 100037, China
| | - Baohan Gong
- Beijing Vehicle Emission Management Center, Beijing, 100176, China
| | - Xueyao Li
- Tianjin Key Laboratory of Urban Transport Emission Research, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Xin Qin
- Beijing Vehicle Emission Management Center, Beijing, 100176, China
| | - Xizi Cao
- National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing, 100037, China
| | - Xinyu Liu
- National Engineering Research Center of Urban Environmental Pollution Control, Beijing Municipal Research Institute of Environmental Protection, Beijing, 100037, China
| | - Yi Ai
- School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China
| | - Jinxiu Han
- School of Geography Earth and Environmental Sciences, The University of Birmingham, Birmingham, B15 2TT, UK
| | - Taosheng Jin
- Tianjin Key Laboratory of Urban Transport Emission Research, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
| |
Collapse
|
42
|
A Higher-Order Graph Convolutional Network for Location Recommendation of an Air-Quality-Monitoring Station. REMOTE SENSING 2021. [DOI: 10.3390/rs13081600] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
The location recommendation of an air-quality-monitoring station is a prerequisite for inferring the air-quality distribution in urban areas. How to use a limited number of monitoring equipment to accurately infer air quality depends on the location of the monitoring equipment. In this paper, our main objective was how to recommend optimal monitoring-station locations based on existing ones to maximize the accuracy of a air-quality inference model for inferring the air-quality distribution of an entire urban area. This task is challenging for the following main reasons: (1) air-quality distribution has spatiotemporal interactions and is affected by many complex external influential factors, such as weather and points of interest (POIs), and (2) how to effectively correlate the air-quality inference model with the monitoring station location recommendation model so that the recommended station can maximize the accuracy of the air-quality inference model. To solve the aforementioned challenges, we formulate the monitoring station location as an urban spatiotemporal graph (USTG) node recommendation problem in which each node represents a region with time-varying air-quality values. We design an effective air-quality inference model-based proposed high-order graph convolution (HGCNInf) that could capture the spatiotemporal interaction of air-quality distribution and could extract external influential factor features. Furthermore, HGCNInf can learn the correlation degree between the nodes in USTG that reflects the spatiotemporal changes in air quality. Based on the correlation degree, we design a greedy algorithm for minimizing information entropy (GMIE) that aims to mark the recommendation priority of unlabeled nodes according to the ability to improve the inference accuracy of HGCNInf through the node incremental learning method. Finally, we recommend the node with the highest priority as the new monitoring station location, which could bring about the greatest accuracy improvement to HGCNInf.
Collapse
|
43
|
The Impact of the COVID-19 Emergency on Local Vehicular Traffic and Its Consequences for the Environment: The Case of the City of Reggio Emilia (Italy). SUSTAINABILITY 2020. [DOI: 10.3390/su13010118] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The COVID-19 health emergency has imposed the need to limit and/or stop non-essential economic and commercial activities and movement of people. The objective of this work is to report an assessment of the change in vehicle flows and in air quality of a specific study area in the north of Italy, comparing the periods February–May 2020 and February–May 2019. Circulating vehicles have been measured at nine characteristic points of the local road network of the city of Reggio Emilia (Italy), while atmospheric pollutant concentrations have been analysed using data extracted from the regional air quality monitoring network. The results highlight a rapid decline in the number of vehicles circulating in 2020 (with values of up to −82%). This has contributed to a reduction in air concentrations of pollutants, in particular for NO2 and CO (over 30% and over 22%, respectively). On the other hand, O3 has increased (by about +13%), but this is expected. Finally, the particulate matter grew (about 30%), with a behaviour similar to the whole regional territory. The empirical findings of this study provide some indications and useful information to assist in understanding the effects of traffic blocking in urban areas on air quality.
Collapse
|