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Gu Y, Liu B, Meng H, Song S, Dai Q, Shi L, Feng Y, Hopke PK. Source apportionment of consumed volatile organic compounds in the atmosphere. JOURNAL OF HAZARDOUS MATERIALS 2023; 459:132138. [PMID: 37531767 DOI: 10.1016/j.jhazmat.2023.132138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 07/12/2023] [Accepted: 07/23/2023] [Indexed: 08/04/2023]
Abstract
Conventional source apportionments of ambient volatile organic compounds (VOCs) have been based on observed and initial concentrations after photochemical correction. However, these results have not been related to ozone (O3) and secondary organic aerosol (SOA) formation. Thus, the apportioned contributions could not effectively support secondary pollution control development. Source apportionment of the VOCs consumed in forming O3 and SOA is needed. A consumed VOC source apportionment approach was developed and applied to hourly speciated VOCs data from June to August 2022 measured in Laoshan, Qingdao. Biogenic emissions (56.3%), vehicle emissions (17.2%), and gasoline evaporation (9.37%) were the main sources of consumed VOCs. High consumed VOCs from biogenic emissions mainly occurred during transport from parks to the southwest and northwest of study site. During the O3 pollution period, biogenic emissions (46.3%), vehicle emissions (24.2%), and gasoline evaporation (14.3%) provided the largest contributions to the consumed VOCs. However, biogenic emissions contribution increased to 57.1% during the non-O3 pollution period, and vehicle emissions and gasoline evaporation decreased to 16.5% and 9.01%, respectively. Biogenic emissions and the mixed source of combustion sources and solvent use contributed the most to O3 and SOA formation potentials during the O3 pollution period, respectively.
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Affiliation(s)
- Yao Gu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
| | - He Meng
- Qingdao Eco-environment Monitoring Center of Shandong Province, Qingdao 266003, China
| | - Shaojie Song
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Laiyuan Shi
- Qingdao Eco-environment Monitoring Center of Shandong Province, Qingdao 266003, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Philip K Hopke
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA; Institute for a Sustainable Environment, Clarkson University, Potsdam, NY 13699, USA
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Vrekoussis M, Pikridas M, Rousogenous C, Christodoulou A, Desservettaz M, Sciare J, Richter A, Bougoudis I, Savvides C, Papadopoulos C. Local and regional air pollution characteristics in Cyprus: A long-term trace gases observations analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 845:157315. [PMID: 35839895 DOI: 10.1016/j.scitotenv.2022.157315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 06/22/2022] [Accepted: 07/08/2022] [Indexed: 06/15/2023]
Abstract
Observations of key gaseous trace pollutants, namely NO, NOy, CO, SO2 and O3, performed at several curb, residential, industrial, background and free-troposphere sites were analyzed to assess the temporal and spatial variability of pollution in Cyprus. Notably, the analysis utilized one of the longest datasets of 17 years of measurements (2003-2019) in the East Mediterranean and the Middle East (EMME). This region is considered a regional hotspot of ozone and aerosol pollution. A trend analysis revealed that at several stations, a statistically significant decrease in primary pollutant concentration is recorded, most likely due to pollution control strategies. In contrast, at four stations, a statistically significant increase in ozone levels, ranging between 0.36 ppbv y-1 and 0.82 ppbv y-1, has been observed, attributed to the above strategies targeting the reduction of nitrogen oxides (NOx) but not that of Volatile Organic Compounds (VOCs). The NO and NOy, and CO levels at the Agia Marina regional background station were two orders of magnitude and four times lower, respectively, than the ones of the urban centers. The latter denotes that local emissions are not negligible and control a large fraction of the observed interannual and diurnal variability. Speciation analysis showed that traffic and other local emissions are the sources of urban NO and NOy. At the same time, 46 % of SO2 and 40 % of CO, on average, originate from long-range regional transport. Lastly, a one-year analysis of tropospheric NO2 vertical columns from the TROPOMI satellite instrument revealed a west-east low-to-high gradient over the island, with all major hotspots, including cities and powerplants, being visible from space. With the help of an unsupervised machine learning approach, it was found that these specific hotspots contribute overall around 10 % to the total NO2 tropospheric columns.
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Affiliation(s)
- M Vrekoussis
- Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Cyprus; Institute of Environmental Physics and Remote Sensing (IUP), University of Bremen, Germany; Center of Marine Environmental Sciences (MARUM), University of Bremen, Germany.
| | - M Pikridas
- Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Cyprus
| | - C Rousogenous
- Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Cyprus
| | - A Christodoulou
- Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Cyprus; IMT Lille Douai, Institut Mines-Télécom, Univ. Lille, Centre for Energy and Environment, Lille, France
| | - M Desservettaz
- Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Cyprus
| | - J Sciare
- Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Cyprus
| | - A Richter
- Institute of Environmental Physics and Remote Sensing (IUP), University of Bremen, Germany
| | - I Bougoudis
- Institute of Environmental Physics and Remote Sensing (IUP), University of Bremen, Germany
| | - C Savvides
- Ministry of Labour, Welfare and Social Insurance, Department of Labour Inspection (DLI), Nicosia, Cyprus
| | - C Papadopoulos
- Ministry of Labour, Welfare and Social Insurance, Department of Labour Inspection (DLI), Nicosia, Cyprus
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Yang Y, Liu B, Hua J, Yang T, Dai Q, Wu J, Feng Y, Hopke PK. Global review of source apportionment of volatile organic compounds based on highly time-resolved data from 2015 to 2021. ENVIRONMENT INTERNATIONAL 2022; 165:107330. [PMID: 35671590 DOI: 10.1016/j.envint.2022.107330] [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: 02/09/2022] [Revised: 05/27/2022] [Accepted: 05/28/2022] [Indexed: 06/15/2023]
Abstract
Highly time-resolved data for volatile organic compounds (VOCs) can now be monitored. Source analyses of such high time-resolved concentrations provides key information for controlling VOC emissions. This work reviewed the literature on VOCs source analyses published from 2015 to 2021, and assesses the state-of-the-art and the existing issues with these studies. Gas chromatography system and direct-inlet mass spectrometry are the main monitoring tools. Quality control (QC) of the monitoring process is critical prior to analysis. QC includes inspection and replacement of instrument consumables, calibration curve corrections, and reviewing the data. Approximately 54% published papers lacked details on the quantitative evaluation of the effectiveness of QC measures. Among the reviewed works, the number of monitored species varied from 5 to 119, and fraction of papers with more than 90 monitored species increased yearly. US EPA PMF v5.0 was the most commonly used (∼86%) for VOC source analyses. However, conventional source apportionment directly uses the measured VOCs and may be problematic given the impacts of dispersion and photochemical losses, uncertainty setting of VOCs data, factor resolution, and factor identification. Excluding species with high-reactivity or estimation of corrected concentrations were often applied to reduce the influence of photochemical reactions on the results. However, most reports did not specify the selection criteria or the specific error fraction values in the uncertainty estimation. Model diagnostic indexes were used in 99% of the reports for PMF analysis to determine the factor resolution. Due to lack of known local source profiles, factor identification was mainly achieved using marker species and characteristic species ratios. However, multiple sources had high-collinearity and the same species were often used to identify different sources. Vehicle emissions and fuel evaporation were the primary contributors to VOCs around the world. Contribution of coal combustion in China was substantially higher than in other countries.
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Affiliation(s)
- Yang Yang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
| | - Jing Hua
- Tianjin Ecology and Environment Bureau, Tianjin 300191, China
| | - Tao Yang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Jianhui Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Philip K Hopke
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA; Institute for a Sustainable Environment, Clarkson University, Potsdam, NY 13699, USA
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What Are the Sectors Contributing to the Exceedance of European Air Quality Standards over the Iberian Peninsula? A Source Contribution Analysis. SUSTAINABILITY 2022. [DOI: 10.3390/su14052759] [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
The Iberian Peninsula, located in southwestern Europe, is exposed to frequent exceedances of different threshold and limit values of air pollution, mainly related to particulate matter, ozone, and nitrous oxide. Source apportionment modeling represents a useful modeling tool for evaluating the contribution of different emission sources or sectors and for designing useful mitigation strategies. In this sense, this work assesses the impact of various emission sectors on air pollution levels over the Iberian Peninsula using a source contribution analysis (zero-out method). The methodology includes the use of the regional WRF + CHIMERE modeling system (coupled to EMEP emissions). In order to represent the sensitivity of the chemistry and transport of gas-phase pollutants and aerosols, several emission sectors have been zeroed-out to quantify the influence of different sources in the area, such as on-road traffic or other mobile sources, combustion in energy generation, industrial emissions or agriculture, among others. The sensitivity analysis indicates that large reductions of precursor emissions (coming mainly from energy generation, road traffic, and maritime-harbor emissions) are needed for improving air quality and attaining the thresholds set in the European Directive 2008/50/EC over the Iberian Peninsula.
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Liu C, Shi K. A review on methodology in O 3-NOx-VOC sensitivity study. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 291:118249. [PMID: 34600066 DOI: 10.1016/j.envpol.2021.118249] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 08/26/2021] [Accepted: 09/26/2021] [Indexed: 06/13/2023]
Abstract
Gaining insight into the response of surface ozone (O3) formation to its precursors plays an important role in the policy-making of O3 pollution control. However, the real atmosphere is an open and dissipative system, and its complexity poses a great challenge to the study of nonlinear relations between O3 and its precursors. At present, model-based methods based on reductionism try to restore the real atmospheric photochemical system, by coupling meteorological model and chemical transport model in temporal and spatial resolution completely. Nevertheless, large inconsistencies between predictions and true values still exist, due to the great uncertainty originated from emission inventory, photochemical reaction mechanism and meteorological factors. Recently, based on field observations, some nonlinear methods have successfully revealed the complex emergent properties (long-term persistence, multi-fractal, etc) in coupling correlation between O3 and its precursors at different time scales. The emergent properties are closely associated with the intrinsic dynamics of atmospheric photochemical system. Taking them into account when building O3 prediction model, is helpful to reduce the uncertainty in the results. Nonlinear methods (fractal, chaos, etc) based on holism can give new insights into the nonlinear relations between O3 and its precursors. Changes of thinking models in methodology are expected to improve the precision of forecasting O3 concentration. This paper has reviewed the advances of different methods for studying the sensitivity of O3 formation to its precursors during the past few decades. This review highlights that it is necessary to incorporate the emergent properties obtained by nonlinear methods into the modern models, for assessing O3 formation under combined air pollution environment more accurately. Moreover, the scaling property of coupling correlation detected in the real observations of O3 and its precursors could be used to test and improve the simulation performance of modern models.
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Affiliation(s)
- Chunqiong Liu
- College of Environmental Sciences and Engineering, China West Normal University, Nanchong, Sichuan, China; College of Biology and Environmental Sciences, Jishou University, Jishou, Hunan, China
| | - Kai Shi
- College of Environmental Sciences and Engineering, China West Normal University, Nanchong, Sichuan, China; College of Biology and Environmental Sciences, Jishou University, Jishou, Hunan, China.
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Abstract
In the last twenty years, research activity around the environmental applications of metal–organic frameworks has bloomed due to their CO2 capture ability, tunable properties, porosity, and well-defined crystalline structure. Thus, hundreds of MOFs have been developed. However, the impact of their production on the environment has not been investigated as thoroughly as their potential applications. In this work, the environmental performance of various synthetic routes of MOF nanoparticles, in particular ZIF-8, is assessed through a life cycle assessment. For this purpose, five representative synthesis routes were considered, and synthesis data were obtained based on available literature. The synthesis included different solvents (de-ionized water, methanol, dimethylformamide) as well as different synthetic steps (i.e., hours of drying, stirring, precursor). The findings revealed that the main environmental weak points identified during production were: (a) the use of dimethylformamide (DMF) and methanol (MeOH) as substances impacting environmental sustainability, which accounted for more than 85% of the overall environmental impacts in those synthetic routes where they were utilized as solvents and as cleaning agents at the same time; (b) the electricity consumption, especially due to the Greek energy mix which is fossil-fuel dependent, and accounted for up to 13% of the overall environmental impacts in some synthetic routes. Nonetheless, for the optimization of the impacts provided by the energy use, suggestions are made based on the use of alternative, cleaner renewable energy sources, which (for the case of wind energy) will decrease the impacts by up to 2%.
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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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Guan Y, Wang L, Wang S, Zhang Y, Xiao J, Wang X, Duan E, Hou L. Temporal variations and source apportionment of volatile organic compounds at an urban site in Shijiazhuang, China. J Environ Sci (China) 2020; 97:25-34. [PMID: 32933737 DOI: 10.1016/j.jes.2020.04.022] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 04/09/2020] [Accepted: 04/12/2020] [Indexed: 05/22/2023]
Abstract
Shijiazhuang, the city with the worst air quality in China, is suffering from severe ozone pollution in summer. As the key precursors of ozone generation, it is necessary to control the Volatile Organic Compounds (VOCs) pollution. To have a better understanding of the pollution status and source contribution, the concentrations of 117 ambient VOCs were analyzed from April to August 2018 in an urban site in Shijiazhuang. Results showed that the monthly average concentration of total VOCs was 66.27 ppbv, in which, the oxygenated VOCs (37.89%), alkanes (33.89%), and halogenated hydrocarbons (13.31%) were the main composite on. Eight major sources were identified using Positive Matrix Factorization modeling with an accurate VOCs emission inventory as inter-complementary methods revealed that the petrochemical industry (26.24%), other industrial sources (15.19%), and traffic source (12.24%) were the major sources for ambient VOCs in Shijiazhuang. The spatial distributions of major industrial activities emissions were identified by using geographic information statistics system, which illustrated the VOCs was mainly from the north and southeast of Shijiazhuang. The inverse trajectory analysis using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and Potential Source Contribution Function (PSCF) clearly demonstrated the features of pollutant transport to Shijiazhuang. These findings can provide references for local governments regarding control strategies to reduce VOCs emissions.
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Affiliation(s)
- Yanan Guan
- Scshool of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; National and Local Joint Engineering Center of Volatile Organic Compounds & Odorous Pollution Control Technology, Shijiazhuang 050018, China
| | - Lei Wang
- Scshool of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
| | - Shujuan Wang
- Hebei Province Environmental Monitoring Center, Shijiazhuang 050018, China
| | - Yihao Zhang
- Scshool of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
| | - Jieying Xiao
- Scshool of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
| | - Xiaoli Wang
- Hebei Province Environmental Emergency and Heavy Pollution Weather Warning Center, Shijiazhuang 050018, China
| | - Erhong Duan
- Scshool of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; National and Local Joint Engineering Center of Volatile Organic Compounds & Odorous Pollution Control Technology, Shijiazhuang 050018, China.
| | - Li'an Hou
- Logistics Science and Technology Research Institute of Rocket Army, Beijing 100011, China
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Chen Y, Yan H, Yao Y, Zeng C, Gao P, Zhuang L, Fan L, Ye D. Relationships of ozone formation sensitivity with precursors emissions, meteorology and land use types, in Guangdong-Hong Kong-Macao Greater Bay Area, China. J Environ Sci (China) 2020; 94:1-13. [PMID: 32563472 DOI: 10.1016/j.jes.2020.04.005] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 04/03/2020] [Accepted: 04/03/2020] [Indexed: 06/11/2023]
Abstract
Due to the influences of precursors emissions, meteorology, geography and other factors, ozone formation sensitivity (OFS) is generally spatially and temporally heterogeneous. This study characterized detailed spatial and temporal variations of OFS in Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2012 to 2016 based on OMI satellite data, and analyzed the relationships of OFS with precursors emissions, meteorology and land use types (LUTs). From 2012 to 2016, the OFS tended to be NOx-limited in GBA, with the value of FNR (HCHO/NO2) increasing from 2.04 to 2.22. According to the total annual emission statistics of precursors, NOx emissions decreased by 33.1% and VOCs emissions increased by 35.2% from 2012 to 2016, directly resulting in OFS tending to be NOx-limited. The Grey Relation Analysis results show that total column water (TCW), surface net solar radiation (SSR), air temperature at 2 m (T2) and surface pressure (SP) are the top four meteorological factors with the greatest influences on OFS. There are significant positive correlations between FNR and T2, SSR, TCW, and significant negative correlations between FNR and SP. In GBA, the OFS tends to be NOx-limited regime in wet season (higher T2, SSR, TCW and lower SP) and VOCs-limited regime in dry season (lower T2, SSR, TCW and higher SP). The FNR displays obvious gradient variations on different LUTs, with the highest in "Rural areas", second in "Suburban areas" and lowest in "Urban areas".
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Affiliation(s)
- Yuping Chen
- School of Environment and Energy, South China University of Technology (SCUT), Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, SCUT, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, SCUT, Guangzhou 510006, China.
| | - Hui Yan
- School of Environment and Energy, South China University of Technology (SCUT), Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, SCUT, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, SCUT, Guangzhou 510006, China
| | - Yijuan Yao
- School of Environment and Energy, South China University of Technology (SCUT), Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, SCUT, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, SCUT, Guangzhou 510006, China
| | - Chunling Zeng
- School of Environment and Energy, South China University of Technology (SCUT), Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, SCUT, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, SCUT, Guangzhou 510006, China
| | - Ping Gao
- School of Environment and Energy, South China University of Technology (SCUT), Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, SCUT, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, SCUT, Guangzhou 510006, China
| | - Liyue Zhuang
- School of Environment and Energy, South China University of Technology (SCUT), Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, SCUT, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, SCUT, Guangzhou 510006, China
| | - Liya Fan
- School of Environment and Energy, South China University of Technology (SCUT), Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, SCUT, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, SCUT, Guangzhou 510006, China.
| | - Daiqi Ye
- School of Environment and Energy, South China University of Technology (SCUT), Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, SCUT, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, SCUT, Guangzhou 510006, China
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Spatial and Temporal Distribution of PM2.5 Pollution over Northeastern Mexico: Application of MERRA-2 Reanalysis Datasets. REMOTE SENSING 2020. [DOI: 10.3390/rs12142286] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Aerosol and meteorological remote sensing data could be used to assess the distribution of urban and regional fine particulate matter (PM2.5), especially in locations where there are few or no ground-based observations, such as Latin America. The objective of this study is to evaluate the ability of Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRA-2) aerosol components to represent PM2.5 ground concentrations and to develop and validate an ensemble neural network (ENN) model that uses MERRA-2 aerosol and meteorology products to estimate the monthly average of PM2.5 ground concentrations in the Monterrey Metropolitan Area (MMA), which is the main urban area in Northeastern Mexico (NEM). The project involves the application of the ENN model to a regional domain that includes not only the MMA but also other municipalities in NEM in the period from January 2010 to December 2014. Aerosol optical depth (AOD), temperature, relative humidity, dust PM2.5, sea salt PM2.5, black carbon (BC), organic carbon (OC), and sulfate (SO42−) reanalysis data were identified as factors that significantly influenced PM2.5 concentrations. The ENN estimated a PM2.5 monthly mean of 25.62 μg m−3 during the entire period. The results of the comparison between the ENN and ground measurements were as follows: correlation coefficient R ~ 0.90; root mean square error = 1.81 μg m−3; mean absolute error = 1.31 μg m−3. Overall, the PM2.5 levels were higher in winter and spring. The highest PM2.5 levels were located in the MMA, which is the major source of air pollution throughout this area. The estimated data indicated that PM2.5 was not distributed uniformly throughout the region but varied both spatially and temporally. These results led to the conclusion that the magnitude of air pollution varies among seasons and regions, and it is correlated with meteorological factors. The methodology developed in this study could be used to identify new monitoring sites and address information gaps.
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Ouyang Y, Yin Z, Li Y, Fan E, Zhang L. Associations among air pollutants, grass pollens, and daily number of grass pollen allergen-positive patients: a longitudinal study from 2012 to 2016. Int Forum Allergy Rhinol 2019; 9:1297-1303. [PMID: 31513736 DOI: 10.1002/alr.22389] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 05/30/2019] [Accepted: 07/04/2019] [Indexed: 12/31/2022]
Abstract
BACKGROUND Grass pollen is the most prevalent sensitizing aeroallergen to cause respiratory allergies in northern China. Air pollutants have a substantial effect on respiratory health and some pollens. This study aimed to investigate relationships among airborne grass pollen, air pollutants and allergic diseases, in order to determine their effects on patients with grass pollen allergies in Beijing, China, during the period from 2013 to 2016. METHODS Data regarding autumnal grass pollens and air pollutants measured in Beijing from 2012 to 2016 were obtained from local governmental agencies. Patient data regarding specific immunoglobulin E (IgE) analyses from 2013 to 2016 were obtained from the Department of Allergy in Beijing Tongren Hospital. Spearman's rank correlation analysis was used to assess associations between the daily number of grass pollen allergen-positive patients and the following parameters: 3 clinically-relevant grass pollen genera (Artemisia, Humulus, and Chenopodium) and inhalable pollutants. RESULTS Correlation analysis indicated that the daily number of grass pollen-positive patients was significantly associated with the peak period of grass pollens, as well as pollutants SO2 and NOx. Moreover, concentrations of air pollutants (eg, ozone, oxides of nitrogen [NOx ], and SO2 ) were consistently and significantly associated with concentrations of grass pollens; particulate matter 2.5 µm in diameter was negatively associated with Artemisia and Chenopodium pollens. CONCLUSION Grass pollens exhibited substantial impact on allergic disease morbidity. Air pollutants impacted allergic disease and grass pollen. Thus, public health and clinical approaches to anticipate and reduce allergic disease morbidity from pollen and pollutants are needed.
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Affiliation(s)
- Yuhui Ouyang
- Department of Otolaryngology-Head and Neck Surgery and Department of Allergy, Beijing Tongren Hospital, Affiliated to the Capital University of Medical Science, Beijing, China.,Beijing Key Laboratory of Nasal Diseases, Beijing Institute of Otolaryngology, Beijing, China
| | - Zhaoyin Yin
- Beijing Weather Information Service, Beijing, China
| | - Ying Li
- Beijing Key Laboratory of Nasal Diseases, Beijing Institute of Otolaryngology, Beijing, China
| | - Erzhong Fan
- Beijing Key Laboratory of Nasal Diseases, Beijing Institute of Otolaryngology, Beijing, China
| | - Luo Zhang
- Department of Otolaryngology-Head and Neck Surgery and Department of Allergy, Beijing Tongren Hospital, Affiliated to the Capital University of Medical Science, Beijing, China.,Beijing Key Laboratory of Nasal Diseases, Beijing Institute of Otolaryngology, Beijing, China
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Increasing Weekend Effect in Ground-Level O3 in Metropolitan Areas of Mexico during 1988–2016. SUSTAINABILITY 2018. [DOI: 10.3390/su10093330] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Here, we present an assessment of long-term trends in the O3 weekend effect (WE) occurrences and spread within the Mexico City (MCMA), Guadalajara (GMA), and Monterrey (MMA) metropolitan areas, which are the three largest metropolitan areas (MAs) of Mexico and concentrate around 33% of the total population in the country. Daytime averages and peak differences in O3 concentrations from weekdays to weekends were used as a proxy of WE occurrence. All MAs exhibited the occurrence of WE in all years at least in one monitoring site. Substantial differences in O3 daytime averages and peaks from weekdays to weekends have decreased over time in all MAs, and since 1998 and 2013 for the MCMA and GMA, respectively, higher O3 levels during weekends are typical during most of the year. The largest variations in the O3 WE were observed at downwind and urban core sites of the MCMA and GMA. Significant increasing trends (p < 0.05) in the O3 WE magnitude were observed for Sundays at all sites within the MCMA, with trends in annual averages ranging between 0.33 and 1.29 ppb O3 yr−1. Within the GMA, for Sundays, fewer sites exhibited increasing trends in the WE occurrence and at lower growth rates (0.32 and 0.48 ppb yr−1, p < 0.1) than within the MCMA, while within the MMA no apparent trends were observed in marked contrast with the MCMA and GMA. Our findings suggest that policies implemented have been successful in controlling weekday ground-level O3 within the MCMA and GMA, but further actions must be introduced to control the increases in the O3 WE magnitude and spread.
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