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Tian X, Wang Z, Xie P, Xu J, Li A, Pan Y, Hu F, Hu Z, Chen M, Zheng J. A CNN-SVR model for NO 2 profile prediction based on MAX-DOAS observations: The influence of Chinese New Year overlapping the 2020 COVID-19 lockdown on vertical distributions of tropospheric NO 2 in Nanjing, China. J Environ Sci (China) 2024; 141:151-165. [PMID: 38408816 DOI: 10.1016/j.jes.2023.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 09/01/2023] [Accepted: 09/03/2023] [Indexed: 02/28/2024]
Abstract
In this study, a hybrid model, the convolutional neural network-support vector regression model, was adopted to achieve prediction of the NO2 profile in Nanjing from January 2019 to March 2021. Given the sudden decline in NO2 in February 2020, the contribution of the Coronavirus Disease-19 (COVID-19) lockdown, Chinese New Year (CNY), and meteorological conditions to the reduction of NO2 was evaluated. NO2 vertical column densities (VCDs) from January to March 2020 decreased by 59.05% and 32.81%, relative to the same period in 2019 and 2021, respectively. During the period of 2020 COVID-19, the average NO2 VCDs were 50.50% and 29.96% lower than those during the pre-lockdown and post-lockdown periods, respectively. The NO2 volume mixing ratios (VMRs) during the 2020 COVID-19 lockdown significantly decreased below 400 m. The NO2 VMRs under the different wind fields were significantly lower during the lockdown period than during the pre-lockdown period. This phenomenon could be attributed to the 2020 COVID-19 lockdown. The NO2 VMRs before and after the CNY were significantly lower in 2020 than in 2019 and 2021 in the same period, which further proves that the decrease in NO2 in February 2020 was attributed to the COVID-19 lockdown. Pollution source analysis of an NO2 pollution episode during the lockdown period showed that the polluted air mass in the Beijing-Tianjin-Hebei was transported southwards under the action of the north wind, and the subsequent unfavorable meteorological conditions (local wind speed of < 2.0 m/sec) resulted in the accumulation of pollutants.
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Affiliation(s)
- Xin Tian
- Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China; Key laboratory of Environmental Optical and Technology, Anhui Institute of optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Zijie Wang
- Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Pinhua Xie
- Key laboratory of Environmental Optical and Technology, Anhui Institute of optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China.
| | - Jin Xu
- Key laboratory of Environmental Optical and Technology, Anhui Institute of optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China.
| | - Ang Li
- Key laboratory of Environmental Optical and Technology, Anhui Institute of optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Yifeng Pan
- Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Feng Hu
- School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China
| | - Zhaokun Hu
- Key laboratory of Environmental Optical and Technology, Anhui Institute of optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Mingsheng Chen
- Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Jiangyi Zheng
- Key laboratory of Environmental Optical and Technology, Anhui Institute of optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
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Zheng X, Javed Z, Liu C, Tanvir A, Sandhu O, Liu H, Ji X, Xing C, Lin H, Du D. MAX-DOAS and in-situ measurements of aerosols and trace gases over Dongying, China: Insight into ozone formation sensitivity based on secondary HCHO. J Environ Sci (China) 2024; 135:656-668. [PMID: 37778836 DOI: 10.1016/j.jes.2022.09.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 08/31/2022] [Accepted: 09/12/2022] [Indexed: 10/03/2023]
Abstract
This study presents a comprehensive overview of the atmospheric pollutants including Sulfur dioxide (SO2), Nitrogen dioxide (NO2), Formaldehyde (HCHO), Particulate Matter PM; PM10: diameter ≤ 10 µm, and PM2.5: diameter ≤ 2.5 µm), and Ozone (O3), over Dongying (Shandong Province) from March-April 2018 and September-October 2019 by employing ground-based Multiple Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations along with the in-situ measurements attained by the national air quality monitoring platform. The concentrations of SO2 and NO2 were under the acceptable level, while both PM2.5, and PM10 were higher than the safe levels as prescribed by national and international air quality standards. The results depict that 21% of the total observation days were found to be complex polluted days (PM2.5 > 35 µg/m3 and O3 > 160 µg/m3). The secondary HCHO was used for accurate analysis of O3 sensitivity. A difference of 11.40% and 10% during March-April 2018 and September-October 2019 respectively in O3 sensitivity was found between HCHOtotal/NO2 and HCHOsec/NO2. The results indicate that primary HCHO have significant contribution in HCHO. O3 formation predominantly remained to be in VOC-limited and transitional regime during March-April 2018 and September-October 2019 in Dongying. These results imply that concurrent control of both NOx and VOCs would benefit in ozone reductions. Additionally, the criteria pollutants (PM, SO2, and NO2) depicted strong correlations with each other except for O3 for which weak correlation coefficient was obtained with all the species. This study will prove to be baseline for designing of air pollution control strategies.
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Affiliation(s)
- Xiaojun Zheng
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Zeeshan Javed
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Cheng Liu
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China; Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei 230026, China.
| | - Aimon Tanvir
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Osama Sandhu
- National Agromet Center, Pakistan Meteorological Department, Islamabad 44000, Pakistan
| | - Haoran Liu
- Institute of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Xiangguang Ji
- Institute of Physical Science and Information Technology, Anhui University, Hefei 230601, China; Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China
| | - Chengzhi Xing
- Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Hua Lin
- School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China
| | - Daolin Du
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China.
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Xu W, Zhou W, Li Z, Wang Q, Du A, You B, Qi L, Prévôt ASH, Cao J, Wang Z, Zhu J, Sun Y. Changes in primary and secondary aerosols during a controlled Chinese New Year. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 315:120408. [PMID: 36243190 PMCID: PMC9556005 DOI: 10.1016/j.envpol.2022.120408] [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: 03/14/2022] [Revised: 10/05/2022] [Accepted: 10/06/2022] [Indexed: 05/17/2023]
Abstract
Large reductions in anthropogenic emissions during the Chinese New Year (CNY) holiday in Beijing have been well reported. However, the changes during the CNY of 2021 are different because most people stayed in Beijing to control the spread of coronavirus disease (COVID-19). Here a high-resolution aerosol mass spectrometer (HR-AMS) was deployed for characterization of the changes in size-resolved aerosol composition and sources during the CNY. We found that the reductions in traffic-related NOx and fossil fuel-related organic aerosol (OA), and cooking OA (1.3-12.7%) during the CNY of 2021 were much smaller than those in previous CNY holidays of 2013, 2015, and 2020. In contrast, the mass concentrations of secondary aerosol species except nitrate showed ubiquitous increases (17.6-30.4%) during the CNY of 2021 mainly due to a 4-day severe haze episode. OA composition also changed substantially during the CNY of 2021. In particular, we observed a large increase by nearly a factor of 2 in oxidized primary OA likely from biomass burning, and a decrease of 50.1% in aqueous-phase secondary OA. A further analysis of the severe haze episode during the CNY illustrated a rapid transition of secondary formation from photochemical to aqueous-phase processing followed by a scavenging process, leading to significant changes in aerosol composition, size distributions, and oxidation degree of OA. A parameterization relationship between oxygen-to-carbon (O/C) and f44 (fraction of m/z 44 in OA) from a collocated capture vaporizer aerosol chemical speciation monitor (CV-ACSM) was developed, which has a significant implication for characterization of OA evolution and the impacts on hygroscopicity due to the rapidly increased deployments of CV-ACSM worldwide.
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Affiliation(s)
- Weiqi Xu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Wei Zhou
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Zhijie Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qingqing Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Aodong Du
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bo You
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lu Qi
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), Villigen 5232, Switzerland
| | - André S H Prévôt
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), Villigen 5232, Switzerland
| | - Junji Cao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Zifa Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jiang Zhu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
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Javed Z, Bilal M, Qiu Z, Li G, Sandhu O, Mehmood K, Wang Y, Ali MA, Liu C, Wang Y, Xue R, Du D, Zheng X. Spatiotemporal characterization of aerosols and trace gases over the Yangtze River Delta region, China: impact of trans-boundary pollution and meteorology. ENVIRONMENTAL SCIENCES EUROPE 2022; 34:86. [PMID: 36097441 PMCID: PMC9453706 DOI: 10.1186/s12302-022-00668-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 08/21/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND The spatiotemporal variation of observed trace gases (NO2, SO2, O3) and particulate matter (PM2.5, PM10) were investigated over cities of Yangtze River Delta (YRD) region including Nanjing, Hefei, Shanghai and Hangzhou. Furthermore, the characteristics of different pollution episodes, i.e., haze events (visibility < 7 km, relative humidity < 80%, and PM2.5 > 40 µg/m3) and complex pollution episodes (PM2.5 > 35 µg/m3 and O3 > 160 µg/m3) were studied over the cities of the YRD region. The impact of China clean air action plan on concentration of aerosols and trace gases is examined. The impacts of trans-boundary pollution and different meteorological conditions were also examined. RESULTS The highest annual mean concentrations of PM2.5, PM10, NO2 and O3 were found for 2019 over all the cities. The annual mean concentrations of PM2.5, PM10, and NO2 showed continuous declines from 2019 to 2021 due to emission control measures and implementation of the Clean Air Action plan over all the cities of the YRD region. The annual mean O3 levels showed a decline in 2020 over all the cities of YRD region, which is unprecedented since the beginning of the China's National environmental monitoring program since 2013. However, a slight increase in annual O3 was observed in 2021. The highest overall means of PM2.5, PM10, SO2, and NO2 were observed over Hefei, whereas the highest O3 levels were found in Nanjing. Despite the strict control measures, PM2.5 and PM10 concentrations exceeded the Grade-1 National Ambient Air Quality Standards (NAAQS) and WHO (World Health Organization) guidelines over all the cities of the YRD region. The number of haze days was higher in Hefei and Nanjing, whereas the complex pollution episodes or concurrent occurrence of O3 and PM2.5 pollution days were higher in Hangzhou and Shanghai.The in situ data for SO2 and NO2 showed strong correlation with Tropospheric Monitoring Instrument (TROPOMI) satellite data. CONCLUSIONS Despite the observed reductions in primary pollutants concentrations, the secondary pollutants formation is still a concern for major metropolises. The increase in temperature and lower relative humidity favors the accumulation of O3, while low temperature, low wind speeds and lower relative humidity favor the accumulation of primary pollutants. This study depicts different air pollution problems for different cities inside a region. Therefore, there is a dire need to continuous monitoring and analysis of air quality parameters and design city-specific policies and action plans to effectively deal with the metropolitan pollution. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1186/s12302-022-00668-2.
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Affiliation(s)
- Zeeshan Javed
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, 212013 China
| | - Muhammad Bilal
- School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Zhongfeng Qiu
- School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Guanlin Li
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, 212013 China
| | - Osama Sandhu
- National Agromet Center, Pakistan Meteorological Department, Islamabad, 44000 Pakistan
| | - Khalid Mehmood
- Key Laboratory of Meteorological Disaster, Ministry of Education [KLME]/Joint International Research Laboratory of Climate and Environment Change [ILCEC]/Collaborative Innovation Center On Forecast and Evaluation of Meteorological Disasters [CIC-FEMD]/CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Yu Wang
- School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Md. Arfan Ali
- School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Cheng Liu
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, 230026 China
- Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031 China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 China
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei, 230026 China
| | - Yuhang Wang
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332 USA
| | - Ruibin Xue
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention [LAP3], Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433 China
| | - Daolin Du
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, 212013 China
| | - Xiaojun Zheng
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, 212013 China
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Seasonal Investigation of MAX-DOAS and In Situ Measurements of Aerosols and Trace Gases over Suburban Site of Megacity Shanghai, China. REMOTE SENSING 2022. [DOI: 10.3390/rs14153676] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Shanghai has gained much attention in terms of air quality research owing to its importance to economic capital and its huge population. This study utilizes ground-based remote sensing instrument observations, namely by Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS), and in situ measurements from the national air quality monitoring platform for various atmospheric trace gases including Nitrogen dioxide (NO2), Sulfur dioxide (SO2), Ozone (O3), Formaldehyde (HCHO), and Particulate Matter (PM; PM10: diameter ≤ 10 µm, and PM2.5: diameter ≤ 2.5 µm) over Shanghai from June 2020 to May 2021. The results depict definite diurnal patterns and strong seasonality in HCHO, NO2, and SO2 concentrations with maximum concentrations during winter for NO2 and SO2 and in summer for HCHO. The impact of meteorology and biogenic emissions on pollutant concentrations was also studied. HCHO emissions are positively correlated with temperature, relative humidity, and the enhanced vegetation index (EVI), while both NO2 and SO2 depicted a negative correlation to all these parameters. The results from diurnal to seasonal cycles consistently suggest the mainly anthropogenic origin of NO2 and SO2, while the secondary formation from the photo-oxidation of volatile organic compounds (VOCs) and substantial contribution of biogenic emissions for HCHO. Further, the sensitivity of O3 formation to its precursor species (NOx and VOCs) was also determined by employing HCHO and NO2 as tracers. The sensitivity analysis depicted that O3 formation in Shanghai is predominantly VOC-limited except for summer, where a significant percentage of O3 formation lies in the transition regime. It is worth mentioning that seasonal variation of O3 is also categorized by maxima in summer. The interdependence of criteria pollutants (O3, SO2, NO2, and PM) was studied by employing the Pearson’s correlation coefficient, and the results suggested complex interdependence among the pollutant species in different seasons. Lastly, potential source contribution function (PSCF) analysis was performed to have an understanding of the contribution of different source areas towards atmospheric pollution. PSCF analysis indicated a strong contribution of local sources on Shanghai’s air quality compared to regional sources. This study will help policymakers and stakeholders understand the complex interactions among the atmospheric pollutants and provide a baseline for designing effective control strategies to combat air pollution in Shanghai.
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