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Zhang Z, Zhang Y, Zhong S, Fang J, Bai B, Huang C, Ge X. Anthropogenic-driven changes in concentrations and sources of winter volatile organic compounds in an urban environment in the Yangtze River Delta of China between 2013 and 2021. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 942:173713. [PMID: 38848910 DOI: 10.1016/j.scitotenv.2024.173713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 05/28/2024] [Accepted: 05/31/2024] [Indexed: 06/09/2024]
Abstract
Volatile organic compounds (VOCs) serve as crucial precursors to surface ozone and secondary organic aerosols (SOA). In response to severe air pollution challenges, China has implemented key air quality control policies from 2013 to 2021. Despite these efforts, a comprehensive understanding of the chemical composition and sources of urban atmospheric VOCs and their responses to emission reduction measures remains limited. Our study focuses on analyzing VOCs composition and concentrations during the winters of 2013 and 2021 through online field observations in urban Nanjing, a typical city in the Yangtze River Delta region of China. Using a machine learning approach, we found a notable reduction in total VOCs concentration from 52.4 ± 30.4 ppb to 33.9 ± 21.6 ppb between the two years, with dominant contributions (approximately 94.3 %) associated with anthropogenic emission control. Furthermore, alkanes emerged as the major contributors (48.6 %) to such anthropogenic-driven decline. The total SOA formation potential decreased by approximately 27.4 %, with aromatics identified as the major contributing species. Positive matrix factorization analysis identified six sources. In 2013, prominent contributors were solid fuel combustion (43.6 %), vehicle emission (16.7 %), and paint and solvent use (12.8 %). By 2021, major sources shifted to solid fuel combustion (31.9 %), liquefied petroleum gas and natural gas (26.8 %), and vehicle emission (25.5 %). Solid fuel combustion emerged as the primary driver for total VOCs reduction. The lifetime carcinogenic risk in 2021 decreased by 72.6 % relative to 2013, emphasizing the need to address liquefied petroleum gas and natural gas source, and vehicle emissions for improved human health. Our findings contribute critical insights for policymakers working on effective air quality management.
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Affiliation(s)
- Zihang Zhang
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China
| | - Yunjiang Zhang
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China.
| | - Sheng Zhong
- Jiangsu Environmental Monitoring Center, Nanjing, China.
| | - Jie Fang
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China
| | - Baoru Bai
- Sinopec Engineering Incorporation, Beijing, China
| | - Cheng Huang
- Shanghai Environmental Monitoring Center, Shanghai, China.
| | - Xinlei Ge
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China
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Pei C, Yang W, Zhang Y, Song W, Xiao S, Wang J, Zhang J, Zhang T, Chen D, Wang Y, Chen Y, Wang X. Decrease in ambient volatile organic compounds during the COVID-19 lockdown period in the Pearl River Delta region, south China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 823:153720. [PMID: 35149077 PMCID: PMC8821021 DOI: 10.1016/j.scitotenv.2022.153720] [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: 12/22/2021] [Revised: 01/30/2022] [Accepted: 02/03/2022] [Indexed: 05/22/2023]
Abstract
During the COVID-19 lockdown, ambient ozone levels are widely reported to show much smaller decreases or even dramatical increases under substantially reduced precursor NOx levels, yet changes in ambient precursor volatile organic compounds (VOCs) have been scarcely reported during the COVID-19 lockdown, which is an opportunity to examine the impacts of dramatically changing anthropogenic emissions on ambient VOC levels in megacities where ozone formation is largely VOC-limited. In this study, ambient VOCs were monitored online at an urban site in Guangzhou in the Pearl River Delta region before, during, and after the COVID-19 lockdown. The average total mixing ratios of VOCs became 19.1% lower during the lockdown than before, and those of alkanes, alkenes and aromatics decreased by 19.0%, 24.8% and 38.2%, respectively. The levels of light alkanes (C < 6) decreased by only 13.0%, while those of higher alkanes (C ≥ 6) decreased by 67.8% during the lockdown. Disappeared peak VOC levels in morning rush hours and the drop in toluene to benzene ratios during the lockdown suggested significant reductions in vehicle exhaust and industrial solvent emissions. Source apportioning by positive matrix factorization model revealed that reductions in industrial emissions, diesel exhaust (on-road diesel vehicles and off-road diesel engines) and gasoline-related emissions could account for 48.9%, 42.2% and 8.8%, respectively, of the decreased VOC levels during the lockdown. Moreover, the reduction in industrial emissions could explain 56.0% and 70.0% of the reductions in ambient levels of reactive alkenes and aromatics, respectively. An average increase in O3-1 h by 17% and a decrease in the daily maximum 8-h average ozone by 11% under an average decrease in NOx by 57.0% and a decrease in VOCs by 19.1% during the lockdown demonstrated that controlling emissions of precursors VOCs and NOx to prevent ambient O3 pollution in megacities such as Guangzhou remains a highly challenging task.
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Affiliation(s)
- Chenglei Pei
- State Key Laboratory of Organic Geochemistry, Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; Guangzhou Sub-branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510060, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weiqiang Yang
- State Key Laboratory of Organic Geochemistry, Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; Guangdong Provincial Academy of Environmental Sciences, Guangzhou 510045, China
| | - Yanli Zhang
- State Key Laboratory of Organic Geochemistry, Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China
| | - Wei Song
- State Key Laboratory of Organic Geochemistry, Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Shaoxuan Xiao
- State Key Laboratory of Organic Geochemistry, Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jun Wang
- State Key Laboratory of Organic Geochemistry, Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinpu Zhang
- State Key Laboratory of Organic Geochemistry, Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; Guangzhou Sub-branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510060, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tao Zhang
- State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510308, China
| | - Duohong Chen
- State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510308, China
| | - Yujun Wang
- Guangzhou Sub-branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510060, China
| | - Yanning Chen
- Guangzhou Sub-branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510060, China
| | - Xinming Wang
- State Key Laboratory of Organic Geochemistry, Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Assessment of Fine Particulate Matter for Port City of Eastern Peninsular India Using Gradient Boosting Machine Learning Model. ATMOSPHERE 2022. [DOI: 10.3390/atmos13050743] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
An assessment and prediction of PM2.5 for a port city of eastern peninsular India is presented. Fifteen machine learning (ML) regression models were trained, tested and implemented to predict the PM2.5 concentration. The predicting ability of regression models was validated using air pollutants and meteorological parameters as input variables collected from sites located at Visakhapatnam, a port city on the eastern side of peninsular India, for the assessment period 2018–2019. Highly correlated air pollutants and meteorological parameters with PM2.5 concentration were evaluated and presented during the period under study. It was found that the CatBoost regression model outperformed all other employed regression models in predicting PM2.5 concentration with an R2 score (coefficient of determination) of 0.81, median absolute error (MedAE) of 6.95 µg/m3, mean absolute percentage error (MAPE) of 0.29, root mean square error (RMSE) of 11.42 µg/m3 and mean absolute error (MAE) of 9.07 µg/m3. High PM2.5 concentration prediction results in contrast to Indian standards were also presented. In depth seasonal assessments of PM2.5 concentration were presented, to show variance in PM2.5 concentration during dominant seasons.
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Temporal and Spatial Patterns of Biomass Burning Fire Counts and Carbon Emissions in the Beijing–Tianjin–Hebei (BTH) Region during 2003–2020 Based on GFED4. ATMOSPHERE 2022. [DOI: 10.3390/atmos13030459] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Biomass burning (BB) plays an important role in the formation of heavy pollution events during harvest seasons in the Beijing–Tianjin–Hebei (BTH) region by releasing trace gases and particulate matter into the atmosphere. A better understanding of spatial-temporal variations of BB in BTH is required to assess its impacts on air quality, especially on heavy haze pollution. The fourth version of the Global Fire Emissions Database (GFED4)’s fire counts and carbon emissions data were used in this research, which shows the varying number of fire counts in China from 2003 to 2020 demonstrated a fluctuating but generally rising trend, with a peak in 2013. Most fire counts were concentrated in three key periods: March (11%), June–July (33%), and October (9.68%). The increase in fire counts will inevitably lead to the growth of carbon emissions. The four major vegetation types of the fires were agriculture (58.1%), followed by grassland (35.5%), and forest (4.1%), with the fewest in peat. In addition, a separate study for the year 2020 found that the fire counts and carbon emissions were different for this year, with the overall average trend in the study time. For example, the monthly peak fire counts changed from June to March. The cumulative emissions of carbon, CO, CO2, CH4, dry matter, and particulate matter from BB in BTH reached 201 Gg, 39 Gg, 670 Gg, 2 Gg, 417 Gg, and 3 Gg in 2020, respectively.
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Su Y, Cui B, Luo Y, Wang J, Wang X, Ouyang Z, Wang X. Leaf Functional Traits Vary in Urban Environments: Influences of Leaf Age, Land-Use Type, and Urban–Rural Gradient. Front Ecol Evol 2021. [DOI: 10.3389/fevo.2021.681959] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
An increasing number of studies have focused on the response and adaptation of plants to urbanization by comparing differences in leaf functional traits between urban and rural sites. However, considerable uncertainties remain because differences in land-use type have not frequently been taken into account when assessing the effect of urbanization on leaf traits. In this study, we sampled the needles of Chinese pine (Pinus tabuliformis Carr.) in areas with three land-use types (roadsides, parks, and neighborhoods) along an urban–rural gradient in Beijing, China to determine the effect of urbanization on leaf functional traits. There were significant differences in the values of leaf functional traits between the needles of the current and previous year and across land-use types. Pines growing on roadsides had leaves with smaller length, width, and area, as well as lower stomatal density, compared with those growing in parks and neighborhoods. This implies that on roadsides, plant capacity to acquire resources (e.g., light and carbon dioxide) was degraded. Stomatal density, leaf width, and leaf P concentration increased with increasing distance from the city center, while leaf K concentration decreased with increasing distance from the city center. Importantly, there were significant differences in the urban–rural gradient of leaf functional traits between leaves of different ages, and across land-use types. Leaf age was the most important factor influencing leaf nutrient traits, while land-use type was the most important factor influencing leaf morphological traits in urban environments. Thus, considering the effects of the plant characteristic and land-use type on traits is important for assessing the urban–rural gradients of plant functional traits.
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Zhao S, Hu B, Liu H, Du C, Xia X, Wang Y. The influence of aerosols on the NO 2 photolysis rate in a suburban site in North China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 767:144788. [PMID: 33636767 DOI: 10.1016/j.scitotenv.2020.144788] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 12/15/2020] [Accepted: 12/19/2020] [Indexed: 06/12/2023]
Abstract
The photolysis of NO2 is an important driving force of tropospheric ozone. The intensity of this photolysis reaction affects atmospheric oxidation and photochemical pollution process. Photolysis rate of nitrogen dioxide (JNO2) is affected by aerosols, temperature, solar zenith angle (SZA), clouds, and so on. Among them, aerosol is an important influencing factor because of its complicated and irregular change; aerosol quantitative effect on JNO2 is constructive for the coordinated control of O3 and particulate matter. In order to quantitatively assess the impact of aerosols on JNO2 in the long-term, the reconstructed JNO2 data in a suburban site in North China from 2005 to 2019 are used. We found that JNO2 and aerosol optical depth (AOD) presented logarithmic relations under different solar zenith angle (SZA) levels, the aerosol attenuation effect on JNO2 decreased as AOD increased. Two main influencing factors of JNO2, SZA, and AOD, were fitted into a quadratic polynomial to quantify the AOD effect on JNO2. The results showed that the average annual AOD effect on JNO2 in Xianghe from 2005 to 2019 was -28.6% compared to an aerosol free atmosphere; the seasonal mean AOD effect in spring, summer, autumn, and winter was -27.1% and -35.1%, -25.5% and -26.3%, respectively. During the study period, JNO2 increased with an average of 5 × 10-5 s-1 per year, while the annual average aerosol optical depth (AOD) was 0.80 ± 0.10, showing an overall downward trend. Annual mean AOD attenuation effect on JNO2 decreased over time; the decreases were larger in spring and summer, and smaller in autumn and winter.
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Affiliation(s)
- Shuman Zhao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Bo Hu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
| | - Hui Liu
- Shanxi Meteorological Observatory, Xi'an 710014, China
| | - Chaojie Du
- State Key Laboratory of Earth Surface Processes and Resource Ecology/Academy of Disaster Reduction and Emergency Management, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Xiangao Xia
- Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), Beijing 100029, China
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of the Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Science, Xiamen 361021, China
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Yan G, Zhang P, Yang J, Zhang J, Zhu G, Cao Z, Fan J, Liu Z, Wang Y. Chemical characteristics and source apportionment of PM 2.5 in a petrochemical city: Implications for primary and secondary carbonaceous component. J Environ Sci (China) 2021; 103:322-335. [PMID: 33743913 DOI: 10.1016/j.jes.2020.11.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 11/14/2020] [Accepted: 11/15/2020] [Indexed: 06/12/2023]
Abstract
To study the pollution features and underlying mechanism of PM2.5 in Luoyang, a typical developing urban site in the central plain of China, 303 PM2.5 samples were collected from April 16 to December 29, 2015 to analyze the elements, water soluble inorganic ions, organic carbon and elemental carbon. The annual mean concentration of PM2.5 was 142.3 μg/m3, and 75% of the daily PM2.5 concentrations exceeded the 75 μg/m3. The secondary inorganic ions, organic matter and mineral dust were the most abundant species, accounting for 39.6%, 19.2% and 9.3% of the total mass concentration, respectively. But the major chemical components showed clear seasonal dependence. SO42- was most abundant specie in spring and summer, which related to intensive photochemical reaction under high O3 concentration. In contrast, the secondary organic carbon and ammonium while primary organic carbon and ammonium significantly contributed to haze formation in autumn and winter, respectively. This indicated that the collaboration effect of secondary inorganic aerosols and carbonaceous matters result in heavy haze in autumn and winter. Six main sources were identified by positive matrix factorization model: industrial emission, combustion sources, traffic emission, mineral dust, oil combustion and secondary sulfate, with the annual contribution of 24%, 20%, 24%, 4%, 5% and 23%, respectively. The potential source contribution function analysis pointed that the contribution of the local and short-range regional transportation had significant impact. This result highlighted that local primary carbonaceous and precursor of secondary carbonaceous mitigation would be key to reduce PM2.5 and O3 during heavy haze episodes in winter and autumn.
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Affiliation(s)
- Guangxuan Yan
- School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang 453007, China.
| | - Puzhen Zhang
- School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang 453007, China
| | - Jie Yang
- School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang 453007, China
| | - Jingwen Zhang
- School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang 453007, China
| | - Guifen Zhu
- School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang 453007, China
| | - Zhiguo Cao
- School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang 453007, China
| | - Jing Fan
- School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang 453007, China.
| | - Zirui Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing 100029, China
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing 100029, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Science, Xiamen 361021, China; University of Chinese Academy of Science, Beijing 100049, China
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Wang H, Miao Q, Shen L, Yang Q, Wu Y, Wei H, Yin Y, Zhao T, Zhu B, Lu W. Characterization of the aerosol chemical composition during the COVID-19 lockdown period in Suzhou in the Yangtze River Delta, China. J Environ Sci (China) 2021; 102:110-122. [PMID: 33637237 PMCID: PMC7508540 DOI: 10.1016/j.jes.2020.09.019] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Revised: 09/17/2020] [Accepted: 09/18/2020] [Indexed: 05/09/2023]
Abstract
To control the spread of COVID-19, rigorous restrictions have been implemented in China, resulting in a great reduction in pollutant emissions. In this study, we evaluated the air quality in the Yangtze River Delta during the COVID-19 lockdown period using satellite and ground-based data, including particle matter (PM), trace gases, water-soluble ions (WSIs) and black carbon (BC). We found that the impacts of lockdown policy on air quality cannot be accurately assessed using MODIS aerosol optical depth (AOD) data, whereas the tropospheric nitrogen dioxide (NO2) vertical column density can well reflect the influences of these restrictions on human activities. Compared to the pre-COVID period, the PM2.5, PM10, NO2, carbon monoxide (CO), BC and WSIs during the lockdown in Suzhou were observed to decrease by 37.2%, 38.3%, 64.5%, 26.1%, 53.3% and 58.6%, respectively, while the sulfur dioxide (SO2) and ozone (O3) increased by 1.5% and 104.7%. The WSIs ranked in the order of NO3- > NH4+ > SO42- > Cl- > Ca2+ > K+ > Mg2+ > Na+ during the lockdown period. By comparisons with the ion concentrations during the pre-COVID period, we found that the ions NO3-, NH4+, SO42-, Cl-, Ca2+, K+ and Na+ decreased by 66.3%, 48.8%, 52.9%, 56.9%, 57.9% and 76.3%, respectively, during the lockdown, in contrast to Mg2+, which increased by 30.2%. The lockdown policy was found to have great impacts on the diurnal variations of Cl-, SO42-, Na+ and Ca2+.
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Affiliation(s)
- Honglei Wang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science &Technology, Nanjing 210044, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
| | - Qing Miao
- Suzhou Environmental Monitoring Center, Suzhou 215000, China
| | - Lijuan Shen
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science &Technology, Nanjing 210044, China
| | - Qian Yang
- Suzhou Environmental Monitoring Center, Suzhou 215000, China
| | - Yezheng Wu
- Suzhou Environmental Monitoring Center, Suzhou 215000, China
| | - Heng Wei
- Suzhou Environmental Monitoring Center, Suzhou 215000, China
| | - Yan Yin
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science &Technology, Nanjing 210044, China
| | - Tianliang Zhao
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science &Technology, Nanjing 210044, China
| | - Bin Zhu
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science &Technology, Nanjing 210044, China
| | - Wen Lu
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science &Technology, Nanjing 210044, China
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Wang Y, Liao H. Effect of emission control measures on ozone concentrations in Hangzhou during G20 meeting in 2016. CHEMOSPHERE 2020; 261:127729. [PMID: 32763646 DOI: 10.1016/j.chemosphere.2020.127729] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 07/13/2020] [Accepted: 07/14/2020] [Indexed: 06/11/2023]
Abstract
The effect of emission control measures on ozone (O3) concentrations in Hangzhou during G20 (The Group of Twenty Finance Ministers and Central Bank Governors) meeting during 24 August to 6 September of 2016 was evaluated using the nested version of a global chemical transport model. During G20, observed concentrations of PM10, PM2.5, SO2, NO2, and CO were all below national air quality standards, whereas those of MDA8 O3 were above national standard (with an averaged value of 160.2 μg m-3) but had a decreasing trend. Model sensitivity studies show that, MDA8 O3 concentrations in Hangzhou during G20 were reduced by 11.3 μg m-3 (6.8%), 14.8 μg m-3 (8.9%), and 19.5 μg m-3 (11.7%) with emission control measures in the core area, Zhejiang province, and the Yangtze River Delta (YRD) region, respectively, indicating that control measures were the most effective when carried out jointly in YRD. Considering the ratios of NOx to VOCs during G20, Hangzhou and most areas of Zhejiang province were in transitional regime; reductions in either NOx or VOCs could reduce O3 concentrations. We also quantified how sensitive O3 concentrations respond to emission reductions in sectors of industry, power, residential and transportation in the whole of YRD during G20. The removal of emissions in industry and transportation sectors would lead to the largest reductions of 17.6 μg m-3 (10.5%) and 12.3 μg m-3 (7.4%) in MDA8 O3 concentrations in Hangzhou during G20, respectively. This study has important implications for the control of high O3 levels in eastern China.
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Affiliation(s)
- Ye Wang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Hong Liao
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.
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10
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Ambient Gaseous Pollutants in an Urban Area in South Africa: Levels and Potential Human Health Risk. ATMOSPHERE 2020. [DOI: 10.3390/atmos11070751] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Urban air pollution from gaseous pollutants is a growing public health problem in many countries including South Africa. Examining the levels, trends and health risk of exposure to ambient gaseous pollutants will assist in understanding the effectiveness of existing control measures and plan for suitable management strategies. This study determined the concentration levels and non-cancer risk of CO, SO2, NO2, and O3 at an industrial area in Pretoria West, South Africa. We utilised a set of secondary data for CO, NO2, SO2, and O3 that was obtained from a monitoring station. Analysis of the hourly monitored data was done. Their non-cancer risk (HQ) was determined using the human health risk assessment model for different age categories. The annual levels of NO2 (39.442 µg/m3), SO2 (22.464 µg/m3), CO (722.003 µg/m3) and the 8-hour concentration of CO (649.902 µg/m3) and O3 (33.556 µg/m3) did not exceed the South African National Ambient Air Quality Standards for each pollutant. The HQ for each pollutant across exposed groups (except children) was less than 1. This indicates that the recorded levels could not pose non-cancer risk to susceptible individuals.
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Huang X, Zhang Y, Wang Y, Ou Y, Chen D, Pei C, Huang Z, Zhang Z, Liu T, Luo S, Huang X, Song W, Ding X, Shao M, Zou S, Wang X. Evaluating the effectiveness of multiple emission control measures on reducing volatile organic compounds in ambient air based on observational data: A case study during the 2010 Guangzhou Asian Games. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 723:138171. [PMID: 32392684 DOI: 10.1016/j.scitotenv.2020.138171] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 03/22/2020] [Accepted: 03/22/2020] [Indexed: 06/11/2023]
Abstract
Volatile organic compounds (VOCs) play a crucial role in modulating air pollution by ozone and fine particles, particularly in urban areas. While in recent years short-term intervention actions for better air quality during big events in China did present good opportunities to examine the effectiveness of control measures in reducing anthropogenic VOCs emission, it is highly challenging to interpret the real effect of a specific control measure based on field monitoring data when a cocktail of control measures were adopted. Here we took the air quality intervention actions during the 16th Asian Games (AG) in Guangzhou as a case study to explore the impact of short-term multiple measures on VOCs reduction. The average mass concentrations of VOCs decreased by 52-68% during the AG. These percentages could not reflect emission reduction rates as the concentration might be also heavily impacted by dispersion conditions. Diagnostic ratios, such as methyl tert-butyl ether to carbon monoxide (MTBE/CO) and i-pentane/CO, decreased by over 60% during the AG, suggesting a substantial reduction in gasoline related emissions. A method linking emission reduction rates of two sources with their contribution percentages before and during the AG by using a receptor model was further formulated. With the available reduction rate of 34% for vehicular exhaust obtained during the traffic restriction drill in our previous study, VOCs emissions from gasoline evaporation and solvent use reduced by 45.7% and 13.6% during the AG, respectively. Total VOCs emissions decreased by 25.3% on average during the AG, and the emission control of vehicular exhaust, oil evaporation, and solvent use accounted for 17.0%, 6.3% and 2.0% of total VOCs emission reduction, respectively. This study presented an observed-based method with diagnostic/quantitative approaches to single out the effectiveness of each control measures in reducing VOCs emissions.
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Affiliation(s)
- Xinyu Huang
- School of Marine Sciences, Sun Yat-sen University, Guangzhou 510006, China; State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Yanli Zhang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
| | - Yujun Wang
- Guangzhou Environmental Monitoring Center, Guangzhou 510030, China
| | - Yubo Ou
- Guangdong Environmental Monitoring Center, Guangzhou 510308, China
| | - Duohong Chen
- Guangdong Environmental Monitoring Center, Guangzhou 510308, China
| | - Chenglei Pei
- Guangzhou Environmental Monitoring Center, Guangzhou 510030, China
| | - Zuzhao Huang
- Guangzhou Environmental Technology Center, Guangzhou 510180, China
| | - Zhou Zhang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Tengyu Liu
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Shilu Luo
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoqing Huang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Song
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Xiang Ding
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Min Shao
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Shichun Zou
- School of Marine Sciences, Sun Yat-sen University, Guangzhou 510006, China
| | - Xinming Wang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
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12
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Feng X, Li Q, Tao Y, Ding S, Chen Y, Li XD. Impact of Coal Replacing Project on atmospheric fine aerosol nitrate loading and formation pathways in urban Tianjin: Insights from chemical composition and 15N and 18O isotope ratios. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 708:134797. [PMID: 31784160 DOI: 10.1016/j.scitotenv.2019.134797] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 09/29/2019] [Accepted: 10/02/2019] [Indexed: 06/10/2023]
Abstract
The 'Coal Replacing Project' (CRP), replacing coal with cleaner energy like natural gas and electricity, was implemented in North China to curb PM2.5 pollution; therefore, it is important to explore the sources and transformation mechanisms of PM2.5 nitrate under this strategy for examining its effectiveness. In this study, daytime and nighttime PM2.5 samples of one summer (Jul-2016, C1) and two winters (Jan-2017, C2 and Jan-2018, C3, before and during the CRP, respectively) were collected in urban Tianjin. Concentrations of PM2.5 and water-soluble inorganic ions were analyzed, and δ15N and δ18O were used to calculate the contributions of different NOX sources to nitrate based on a Bayesian mixing model. The results showed that the average concentrations of PM2.5 and its dominant inorganic ions (SO42-, NO3-, NH4+) in C3 during the CRP, compared to C2, decreased by 62.13%, 79.69%, 55.14% and 38.84%, respectively, attesting the improvement of air quality during the CRP. According to the correlation between [NO3-/SO42-] and [NH4+/SO42-] as well as δ18O variations, the homogeneous formation pathway might be dominant in C1, while the heterogeneous pathway would be primary in C2 and C3 during the formation of nitrate. Moreover, the heterogeneous pathway contributed more in C3 than in C2. The dominant sources in C1 were biogenic soil emission (37.0% ± 9.9%) and mobile emission (25.7% ± 19.1%), while coal combustion (42.4% ± 13.8% in C2 and 34.9% ± 14.4% in C3) and biomass burning (31.0% ± 21.2% and 34.7% ± 22.7%) were the main sources in C2 and C3. In the winter, the contribution of coal combustion dropped by about 8% during the CRP (C3) in comparison with that in C2, suggesting the implementation of CRP played an important role in reducing NOX from coal combustion.
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Affiliation(s)
- Xiaoqing Feng
- Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, PR China
| | - Qinkai Li
- Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, PR China
| | - Yuele Tao
- Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, PR China
| | - Shiyuan Ding
- Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, PR China; Tianjin Key Laboratory of Earth Critical Zone Science and Sustainable Development in Bohai Rim, Tianjin 300072, PR China
| | - Yingying Chen
- Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, PR China
| | - Xiao-Dong Li
- Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, PR China; Tianjin Key Laboratory of Earth Critical Zone Science and Sustainable Development in Bohai Rim, Tianjin 300072, PR China.
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Burns J, Boogaard H, Polus S, Pfadenhauer LM, Rohwer AC, van Erp AM, Turley R, Rehfuess E. Interventions to reduce ambient particulate matter air pollution and their effect on health. Cochrane Database Syst Rev 2019; 5:CD010919. [PMID: 31106396 PMCID: PMC6526394 DOI: 10.1002/14651858.cd010919.pub2] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Ambient air pollution is associated with a large burden of disease in both high-income countries (HICs) and low- and middle-income countries (LMICs). To date, no systematic review has assessed the effectiveness of interventions aiming to reduce ambient air pollution. OBJECTIVES To assess the effectiveness of interventions to reduce ambient particulate matter air pollution in reducing pollutant concentrations and improving associated health outcomes. SEARCH METHODS We searched a range of electronic databases with diverse focuses, including health and biomedical research (CENTRAL, Cochrane Public Health Group Specialised Register, MEDLINE, Embase, PsycINFO), multidisciplinary research (Scopus, Science Citation Index), social sciences (Social Science Citation Index), urban planning and environment (Greenfile), and LMICs (Global Health Library regional indexes, WHOLIS). Additionally, we searched grey literature databases, multiple online trial registries, references of included studies and the contents of relevant journals in an attempt to identify unpublished and ongoing studies, and studies not identified by our search strategy. The final search date for all databases was 31 August 2016. SELECTION CRITERIA Eligible for inclusion were randomized and cluster randomized controlled trials, as well as several non-randomized study designs, including controlled interrupted time-series studies (cITS-EPOC), interrupted time-series studies adhering to EPOC standards (ITS-EPOC), interrupted time-series studies not adhering to EPOC standards (ITS), controlled before-after studies adhering to EPOC standards (CBA-EPOC), and controlled before-after studies not adhering to EPOC standards (CBA); these were classified as main studies. Additionally, we included uncontrolled before-after studies (UBA) as supporting studies. We included studies that evaluated interventions to reduce ambient air pollution from industrial, residential, vehicular and multiple sources, with respect to their effect on mortality, morbidity and several air pollutant concentrations. We did not restrict studies based on the population, setting or comparison. DATA COLLECTION AND ANALYSIS After a calibration exercise among the author team, two authors independently assessed studies for inclusion, extracted data and assessed risk of bias. We conducted data extraction, risk of bias assessment and evidence synthesis only for main studies; we mapped supporting studies with regard to the types of intervention and setting. To assess risk of bias, we used the Graphic Appraisal Tool for Epidemiological studies (GATE) for correlation studies, as modified and employed by the Centre for Public Health Excellence at the UK National Institute for Health and Care Excellence (NICE). For each intervention category, i.e. those targeting industrial, residential, vehicular and multiple sources, we synthesized evidence narratively, as well as graphically using harvest plots. MAIN RESULTS We included 42 main studies assessing 38 unique interventions. These were heterogeneous with respect to setting; interventions were implemented in countries across the world, but most (79%) were implemented in HICs, with the remaining scattered across LMICs. Most interventions (76%) were implemented in urban or community settings.We identified a heterogeneous mix of interventions, including those aiming to address industrial (n = 5), residential (n = 7), vehicular (n = 22), and multiple sources (n = 4). Some specific interventions, such as low emission zones and stove exchanges, were assessed by several studies, whereas others, such as a wood burning ban, were only assessed by a single study.Most studies assessing health and air quality outcomes used routine monitoring data. Studies assessing health outcomes mostly investigated effects in the general population, while few studies assessed specific subgroups such as infants, children and the elderly. No identified studies assessed unintended or adverse effects.The judgements regarding the risk of bias of studies were mixed. Regarding health outcomes, we appraised eight studies (47%) as having no substantial risk of bias concerns, five studies (29%) as having some risk of bias concerns, and four studies (24%) as having serious risk of bias concerns. Regarding air quality outcomes, we judged 11 studies (31%) as having no substantial risk of bias concerns, 16 studies (46%) as having some risk of bias concerns, and eight studies (23%) as having serious risk of bias concerns.The evidence base, comprising non-randomized studies only, was of low or very low certainty for all intervention categories and primary outcomes. The narrative and graphical synthesis showed that evidence for effectiveness was mixed across the four intervention categories. For interventions targeting industrial, residential and multiple sources, a similar pattern emerged for both health and air quality outcomes, with essentially all studies observing either no clear association in either direction or a significant association favouring the intervention. The evidence base for interventions targeting vehicular sources was more heterogeneous, as a small number of studies did observe a significant association favouring the control. Overall, however, the evidence suggests that the assessed interventions do not worsen air quality or health. AUTHORS' CONCLUSIONS Given the heterogeneity across interventions, outcomes, and methods, it was difficult to derive overall conclusions regarding the effectiveness of interventions in terms of improved air quality or health. Most included studies observed either no significant association in either direction or an association favouring the intervention, with little evidence that the assessed interventions might be harmful. The evidence base highlights the challenges related to establishing a causal relationship between specific air pollution interventions and outcomes. In light of these challenges, the results on effectiveness should be interpreted with caution; it is important to emphasize that lack of evidence of an association is not equivalent to evidence of no association.We identified limited evidence for several world regions, notably Africa, the Middle East, Eastern Europe, Central Asia and Southeast Asia; decision-makers should prioritize the development and implementation of interventions in these settings. In the future, as new policies are introduced, decision-makers should consider a built-in evaluation component, which could facilitate more systematic and comprehensive evaluations. These could assess effectiveness, but also aspects of feasibility, fidelity and acceptability.The production of higher quality and more uniform evidence would be helpful in informing decisions. Researchers should strive to sufficiently account for confounding, assess the impact of methodological decisions through the conduct and communication of sensitivity analyses, and improve the reporting of methods, and other aspects of the study, most importantly the description of the intervention and the context in which it is implemented.
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Affiliation(s)
- Jacob Burns
- Ludwig‐Maximilians‐University MunichInstitute for Medical Informatics, Biometry and Epidemiology, Pettenkofer School of Public HealthMarchioninistr. 15MunichGermany
| | | | - Stephanie Polus
- Ludwig‐Maximilians‐University MunichInstitute for Medical Informatics, Biometry and Epidemiology, Pettenkofer School of Public HealthMarchioninistr. 15MunichGermany
| | - Lisa M Pfadenhauer
- Ludwig‐Maximilians‐University MunichInstitute for Medical Informatics, Biometry and Epidemiology, Pettenkofer School of Public HealthMarchioninistr. 15MunichGermany
| | - Anke C Rohwer
- Stellenbosch UniversityCentre for Evidence‐based Health Care, Faculty of Medicine and Health SciencesFrancie van Zijl DriveCape TownSouth Africa7505
| | | | - Ruth Turley
- Cardiff UniversityCentre for the Development and Evaluation of Complex Interventions for Public Health Improvement (DECIPHer)1 Museum PlaceCardiffUKCF10 3BD
| | - Eva Rehfuess
- Ludwig‐Maximilians‐University MunichInstitute for Medical Informatics, Biometry and Epidemiology, Pettenkofer School of Public HealthMarchioninistr. 15MunichGermany
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Liu B, Bi X, Zhang J, Yuan J, Xiao Z, Dai Q, Feng Y, Zhang Y. Insight into the critical factors determining the particle number concentrations during summer at a megacity in China. J Environ Sci (China) 2019; 75:169-180. [PMID: 30473282 DOI: 10.1016/j.jes.2018.03.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Revised: 01/28/2018] [Accepted: 03/16/2018] [Indexed: 06/09/2023]
Abstract
To identify the critical factors impacting the number concentration of particles with the aerodynamic diameters less than 2.5μm (PNC2.5), the continuous measurement of PNC2.5, chemical components in PM2.5, gaseous pollutants and meteorological conditions were conducted at an urban site in Tianjin in June 2015. Results indicated that the average PNC2.5 was 2839±2430 dN/dlogDp 1/cm3 during the campaign. Compared to other meteorological parameters, the relative humidity (RH) had the strongest relationship with PNC2.5, with a Pearson's correlation coefficient of 0.53, and RH larger than 30% influenced strongly PNC2.5. The important influence of secondary reactions on PNC2.5 was inferred due to higher correlation coefficients between PNC2.5 and SO42-, NO3-, NH4+ (r=0.78-0.89; p<0.01) and between PNC2.5 and ratios that represent the conversion of nitrogen and sulfur oxides to particulate matter (r=0.42-0.49; p<0.01). Under specific RH conditions, there were even stronger correlations between PNC2.5 and NO3-, SO42-, NH4+, while those between PNC2.5 and EC, OC were relatively weak, especially when RH exceeded 50%. Principal component analysis (PCA) and Pearson's correlation analysis indicated that secondary sources, vehicle emission and coal combustion might be major contributors to PNC2.5. Backward trajectory and potential source contribution function (PSCF) analysis suggested that the transport of air masses originated from these regions around Tianjin (Liaoning, Hebei, Shandong and Jiangsu) influenced critically PNC2.5. The north of Jiangsu, the west of Shandong, and the east of Hebei were distinguished as major potential source-areas of PNC2.5 by PSCF model.
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Affiliation(s)
- Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Xiaohui Bi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China.
| | - Jiaying Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Jie Yuan
- Tianjin Environmental Monitoring Center, Tianjin 300191, China
| | - Zhimei Xiao
- Tianjin Environmental Monitoring Center, Tianjin 300191, China
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
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Xu R, Tie X, Li G, Zhao S, Cao J, Feng T, Long X. Effect of biomass burning on black carbon (BC) in South Asia and Tibetan Plateau: The analysis of WRF-Chem modeling. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 645:901-912. [PMID: 30032086 DOI: 10.1016/j.scitotenv.2018.07.165] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 07/10/2018] [Accepted: 07/13/2018] [Indexed: 06/08/2023]
Abstract
The focus of this study is to evaluate the impact of biomass burning (BB) from South Asia and Southeast Asia on the glaciers over the Tibetan Plateau. The seasonality and long-term trend of biomass fires measured by Terra and Aqua satellite data from 2010 to 2016 are used in this study. The analysis shows that the biomass burnings were widely dispersed in the continental of Indian and Southeast Asia and existed a strong seasonal variation. The biomass burnings in winter (January) were relatively weak and scattered and were significantly enhanced in spring (April). The highest biomass burnings located in two regions. One was along the foothill of Himalayas, where is a dense population area, and the second located in Southeast Asia. Because these two high biomass burning regions are close to the Tibetan Plateau, they could have important effects on the BC deposition over the glaciers of the Tibetan Plateau. In order to study the effect of BB emissions on the deposition over the glaciers in the Tibetan Plateau, a regional chemical model (WRF-Chem; Weather Research and Forecasting Chemical model) was applied to simulate the BC distributions and the transport from BB emission regions to the glaciers in Tibetan Plateau. The result shows that in winter (January), due to the relatively weak BB emissions, the effect of BB emissions on BC concentrations was not significant. The BC concentrations resulted from BB emissions ranged from 0.1 to 2.0 μg/m3, with high concentrations distributed along the foothill of Himalayas and the southeastern Asia region. Due to the relative low BC concentrations, there was insignificant effect of BB emissions on the deposition over the glaciers in the Tibetan Plateau in winter. However, the BB emissions were highest in spring (April), producing high BC concentrations. For example, along the Himalayas Mountain and in the southeastern Asia region, The BC concentrations ranged from 2.0 to 6.0 μg/m3. In addition to the high BC concentrations, there were also west and south prevailing winds in these regions. As a result, the BC particles were transported to the glaciers in the Tibetan Plateau, causing significant deposition of BC particles on the snow surface of the glaciers. This study suggests that the biomass burning emissions have important effects on the BC deposition over the glaciers in the Tibetan Plateau, and the contaminations of glaciers could have significant impact on the melting of snow in the Tibetan Plateau, causing some severe environmental problems, such as the water resources.
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Affiliation(s)
- Ruiguang Xu
- State Kay Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; College of Energy and Environmental Engineering, Hebei University of Engineering, Handan 056038, China; Postdoctoral Research Station of Xi'an Chan-Ba Ecological District(CBE) Management Committee, Xi'an 710024, China
| | - Xuexi Tie
- State Kay Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; National Center for Atmospheric Research (NCAR), Boulder, CO 80303, USA.
| | - Guohui Li
- State Kay Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
| | - Shuyu Zhao
- State Kay Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
| | - Junji Cao
- State Kay Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
| | - Tian Feng
- State Kay Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
| | - Xin Long
- State Kay Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
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Spatiotemporal Characteristics of Air Pollutants (PM10, PM2.5, SO2, NO2, O3, and CO) in the Inland Basin City of Chengdu, Southwest China. ATMOSPHERE 2018. [DOI: 10.3390/atmos9020074] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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17
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He HD, Qiao ZX, Pan W, Lu WZ. Multiscale multifractal properties between ground-level ozone and its precursors in rural area in Hong Kong. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2017; 196:270-277. [PMID: 28288361 DOI: 10.1016/j.jenvman.2017.02.024] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2016] [Revised: 02/01/2017] [Accepted: 02/11/2017] [Indexed: 06/06/2023]
Abstract
In rural area, due to the reduction of NOx and CO emitted from vehicle exhausts, the ozone photochemical reaction exhibits relatively weak effect and ozone formation presents different pattern with its precursors in contrast to urban situation. Hence, in this study, we apply detrended cross-correlation analysis to investigate the multifractal properties between ozone and its precursors in a rural area in Hong Kong. The observed databases of ozone, NO2, NOx and CO levels during 2005-2014 are obtained from a rural monitoring station in Hong Kong. Based on the collected database, the cross-correlation analysis is carried out firstly to examine the cross-correlation patterns and the results indicate that close interactive relations exist between them. Then the detrended cross-correlation analysis is performed for further analysis. The multifractal characters occur between ozone and its precursors. The long-term cross-correlations behaviors in winter are verified to be stronger than that in other seasons. Additionally, the method is extended on daily averaged data to explore the multifractal property on various time scales. The long-term cross-correlation behavior of ozone vs NO2 and NOx on daily basis becomes weaker while that of ozone vs CO becomes stronger. The multifractal properties for all pairs in summer are found to be the strongest among the whole year. These findings successfully illustrate that the multifractal analysis is a useful tool for describing the temporal scaling behaviors of ozone trends in different time series in rural areas.
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Affiliation(s)
- Hong-di He
- Logistics Research Center, Shanghai Maritime University, Shanghai, 200135, China.
| | - Zhong-Xia Qiao
- Logistics Research Center, Shanghai Maritime University, Shanghai, 200135, China
| | - Wei Pan
- Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong
| | - Wei-Zhen Lu
- Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong.
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