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Sheng H, Fan L, Chen M, Wang H, Huang H, Ye D. Identification of NO x emissions and source characteristics by TROPOMI observations - A case study in north-central Henan, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 931:172779. [PMID: 38679100 DOI: 10.1016/j.scitotenv.2024.172779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 04/07/2024] [Accepted: 04/23/2024] [Indexed: 05/01/2024]
Abstract
With the development of industries, air pollution in north-central Henan is becoming increasingly severe. The TROPOspheric Monitoring Instrument (TROPOMI) provides nitrogen dioxide (NO2) column densities with high spatial resolution. Based on TROPOMI, in this study, the nitrogen oxides (NOx) emissions in north-central Henan are derived and the emission hotspots are identified with the flux divergence method (FDM) from May to September 2021. The results indicate that Zhengzhou has the highest NOx emissions in north-central Henan. The most prominent hotspots are in Guancheng Huizu District (Zhengzhou) and Yindu District (Anyang), with emissions of 448.4 g/s and 300.3 g/s, respectively. The Gaussian Mixture Model (GMM) is applied to quantify the characteristics of emission hotspots, including the diameter, eccentricity, and tilt angle, among which the tilt angle provides a novel metric for identifying the spatial distribution of pollution sources. Furthermore, the results are compared with the CAMS global anthropogenic emissions (CAMS-GLOB-ANT) and Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC), and they are generally in good agreement. However, some point sources, such as power plants, may be missed by both inventories. It is also found that for emission hotspots near transportation hubs, CAMS-GLOB-ANT may not have fully considered the actual traffic flow, leading to an underestimation of transportation emissions. These findings provide key information for the accurate implementation of pollution prevention and control measures, as well as references for future optimization of emission inventories. Consequently, deriving NOx emissions from space, quantifying the characteristics of emission hotspots, and combining them with bottom-up inventories can provide valuable insights for targeted emission control.
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Affiliation(s)
- Huilin Sheng
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Liya Fan
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, Guangzhou 510006, China; Guangdong Provincial Engineering and Technology Research Centre for Environmental Risk Prevention and Emergency Disposal, Guangzhou 510006, China.
| | - Meifang Chen
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Huanpeng Wang
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Haomin Huang
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, Guangzhou 510006, China; Guangdong Provincial Engineering and Technology Research Centre for Environmental Risk Prevention and Emergency Disposal, Guangzhou 510006, China
| | - Daiqi Ye
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, Guangzhou 510006, China; Guangdong Provincial Engineering and Technology Research Centre for Environmental Risk Prevention and Emergency Disposal, Guangzhou 510006, China
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2
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Liu S, Valks P, Curci G, Chen Y, Shu L, Jin J, Sun S, Pu D, Li X, Li J, Zuo X, Fu W, Li Y, Zhang P, Yang X, Fu TM, Zhu L. Satellite NO 2 Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001-2018). ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:7891-7903. [PMID: 38602183 PMCID: PMC11080052 DOI: 10.1021/acs.est.3c02111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 03/28/2024] [Accepted: 03/29/2024] [Indexed: 04/12/2024]
Abstract
Tropospheric nitrogen dioxide (NO2) poses a serious threat to the environmental quality and public health. Satellite NO2 observations have been continuously used to monitor NO2 variations and improve model performances. However, the accuracy of satellite NO2 retrieval depends on the knowledge of aerosol optical properties, in particular for urban agglomerations accompanied by significant changes in aerosol characteristics. In this study, we investigate the impacts of aerosol composition on tropospheric NO2 retrieval for an 18 year global data set from Global Ozone Monitoring Experiment (GOME)-series satellite sensors. With a focus on cloud-free scenes dominated by the presence of aerosols, individual aerosol composition affects the uncertainties of tropospheric NO2 columns through impacts on the aerosol loading amount, relative vertical distribution of aerosol and NO2, aerosol absorption properties, and surface albedo determination. Among aerosol compositions, secondary inorganic aerosol mostly dominates the NO2 uncertainty by up to 43.5% in urban agglomerations, while organic aerosols contribute significantly to the NO2 uncertainty by -8.9 to 37.3% during biomass burning seasons. The possible contrary influences from different aerosol species highlight the importance and complexity of aerosol correction on tropospheric NO2 retrieval and indicate the need for a full picture of aerosol properties. This is of particular importance for interpreting seasonal variations or long-term trends of tropospheric NO2 columns as well as for mitigating ozone and fine particulate matter pollution.
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Affiliation(s)
- Song Liu
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- Collaborative
Innovation Center of Atmospheric Environment and Equipment Technology,
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution
Control (AEMPC), Nanjing University of Information
Science and Technology, Nanjing 210044, China
| | - Pieter Valks
- Institut
für Methodik der Fernerkundung (IMF), Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen 82234, Germany
| | - Gabriele Curci
- Department
of Physical and Chemical Sciences, University
of L’Aquila, L’Aquila 67100, Italy
- Center
of Excellence in Telesensing of Environment and Model Prediction of
Severe Events, University of L’Aquila, L’Aquila 67100, Italy
| | - Yuyang Chen
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Lei Shu
- School of
Geographical Sciences, Fujian Normal University, Fuzhou 350117, China
| | - Jianbing Jin
- Jiangsu
Key Laboratory of Atmospheric Environment Monitoring and Pollution
Control, Collaborative Innovation Center of Atmospheric Environment
and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Shuai Sun
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Dongchuan Pu
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xicheng Li
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Juan Li
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xiaoxing Zuo
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Weitao Fu
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Yali Li
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Peng Zhang
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xin Yang
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- Guangdong
Provincial Observation and Research Station for Coastal Atmosphere
and Climate of the Greater Bay Area, Shenzhen 518055, China
- Shenzhen
Key Laboratory of Precision Measurement and Early Warning Technology
for Urban Environmental Health Risks, School of Environmental Science
and Engineering, Southern University of
Science and Technology, Shenzhen 518055, China
| | - Tzung-May Fu
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- Guangdong
Provincial Observation and Research Station for Coastal Atmosphere
and Climate of the Greater Bay Area, Shenzhen 518055, China
- Shenzhen
Key Laboratory of Precision Measurement and Early Warning Technology
for Urban Environmental Health Risks, School of Environmental Science
and Engineering, Southern University of
Science and Technology, Shenzhen 518055, China
| | - Lei Zhu
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- Guangdong
Provincial Observation and Research Station for Coastal Atmosphere
and Climate of the Greater Bay Area, Shenzhen 518055, China
- Shenzhen
Key Laboratory of Precision Measurement and Early Warning Technology
for Urban Environmental Health Risks, School of Environmental Science
and Engineering, Southern University of
Science and Technology, Shenzhen 518055, China
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3
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Jin X, Fiore AM, Cohen RC. Space-Based Observations of Ozone Precursors within California Wildfire Plumes and the Impacts on Ozone-NO x-VOC Chemistry. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:14648-14660. [PMID: 37703172 DOI: 10.1021/acs.est.3c04411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
The frequency of wildfires in the western United States has escalated in recent decades. Here we examine the impacts of wildfires on ground-level ozone (O3) precursors and the O3-NOx-VOC chemistry from the source to downwind urban areas. We use satellite retrievals of nitrogen dioxide (NO2) and formaldehyde (HCHO, an indicator of VOC) from the Tropospheric Monitoring Instrument (TROPOMI) to track the evolution of O3 precursors from wildfires over California from 2018 to 2020. We improved these satellite retrievals by updating the a priori profiles and explicitly accounting for the effects of smoke aerosols. TROPOMI observations reveal that the extensive and intense fire smoke in 2020 led to an overall increase in statewide annual average HCHO and NO2 columns by 16% and 9%. The increase in the level of NO2 offsets the anthropogenic NOx emission reduction from the COVID-19 lockdown. The enhancement of NO2 within fire plumes is concentrated near the regions actively burning, whereas the enhancement of HCHO is far-reaching, extending from the source regions to urban areas downwind due to the secondary production of HCHO from longer-lived VOCs such as ethene. Consequently, a larger increase in NOx occurs in NOx-limited source regions, while a greater increase in HCHO occurs in VOC-limited urban areas, both contributing to more efficient O3 production.
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Affiliation(s)
- Xiaomeng Jin
- Department of Environmental Sciences, Rutgers, The State University of New Jersey, New Brunswick, New Jersey 08901, United States
| | - Arlene M Fiore
- Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Ronald C Cohen
- Department of Chemistry, University of California Berkeley, Berkeley, California 94720, United States
- Department of Earth and Planetary Sciences, University of California Berkeley, Berkeley, California 94720, United States
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4
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Patnaik K, Kesarkar AP, Rath S, Bhate JN, Panchal A, Chandrasekar A, Giri R. A 1-D model to retrieve the vertical profiles of minor atmospheric constituents for cloud microphysical modeling: I. Formulation and validation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 881:163360. [PMID: 37028675 DOI: 10.1016/j.scitotenv.2023.163360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 04/03/2023] [Accepted: 04/03/2023] [Indexed: 06/01/2023]
Abstract
Determining the number concentration of minor constituents in the atmosphere is very important as it determines the whole tropospheric chemistry process. These constituents may act as cloud condensation nuclei (CCN) and ice nuclei (IN), impacting heterogeneous nucleation inside the cloud. However, the estimations of the number concentration of CCN/IN in cloud microphysical parameters are associated with uncertainties. In the present work, a hybrid Monte Carlo Gear solver has been developed to retrieve profiles of CH4, N2O, and SO2. The idealized experiments have been carried out using this solver for retrieving vertical profiles of these constituents over four megacities, viz., Delhi, Mumbai, Chennai, and Kolkata. Community Long-term Infrared Microwave Coupled Atmospheric Product System (CLIMCAPS) dataset around 0800 UTC (2000UTC) has been used for initializing the number concentration of CH4, N2O, and SO2 for daytime (nighttime). The daytime (nighttime) retrieved profiles have been validated using 2000 UTC (next day 0800 UTC) CLIMCAPS products. ERA5 temperature dataset has been used to estimate the kinematic rate of reactions with 1000 perturbations determined using Maximum Likelihood Estimation (MLE). The retrieved profiles and CLIMCAPS products are in very good agreement, as evidenced by the percentage difference between them within the range of 1.3 × 10-5-60.8 % and the coefficient of determination mainly within the range between 81 and 97 %. However, during the passage of tropical cyclone and western disturbance, its value became as low as 27 and 65 % over Chennai and Kolkata, respectively. The enactment of synoptic scale systems such as western disturbances, tropical cyclone Amphan, and easterly waves caused disturbed weather over these megacities-the retrieved profiles during disturbed weather cause large deviations of vertical profiles of N2O. However, the profiles of CH4 and SO2 have less deviation. It is inferred that incorporating this methodology in the dynamical model will be useful to simulate the realistic vertical profiles of the minor constituents in the atmosphere.
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Affiliation(s)
- Kavita Patnaik
- National Atmospheric Research Laboratory, Gadanki, Tirupati, Andhra Pradesh 517112, India; Indian Institute of Space Science and Technology, Valiamala, Kerala 695547, India
| | - Amit P Kesarkar
- National Atmospheric Research Laboratory, Gadanki, Tirupati, Andhra Pradesh 517112, India.
| | - Subhrajit Rath
- National Atmospheric Research Laboratory, Gadanki, Tirupati, Andhra Pradesh 517112, India; Indian Institute of Space Science and Technology, Valiamala, Kerala 695547, India
| | - Jyoti N Bhate
- National Atmospheric Research Laboratory, Gadanki, Tirupati, Andhra Pradesh 517112, India
| | - Abhishek Panchal
- National Atmospheric Research Laboratory, Gadanki, Tirupati, Andhra Pradesh 517112, India
| | | | - Ramakumar Giri
- India Meteorological Department, Mausam Bhavan, Lodhi Road, New Delhi, India
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5
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Chan KL, Xu J, Slijkhuis S, Valks P, Loyola D. TROPOspheric Monitoring Instrument observations of total column water vapour: Algorithm and validation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 821:153232. [PMID: 35090926 DOI: 10.1016/j.scitotenv.2022.153232] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 12/29/2021] [Accepted: 01/13/2022] [Indexed: 06/14/2023]
Abstract
In this paper, we present the total column water vapour (TCWV) retrieval for the TROPOspheric Monitoring Instrument (TROPOMI) observations in the visible blue spectral band. The TROPOMI TCWV algorithm is being optimized and validated in the framework of the Sentinel 5 Precursor Product Algorithm Laboratory (S5P-PAL) project from the European Space Agency (ESA). The retrieval was first developed to retrieve TCWV from the Global Ozone Monitoring Experiment 2 (GOME-2). We have optimized the settings of the retrieval to adapt it for TROPOMI observations. The TROPOMI TCWV algorithm follows the typical two step approach, using spectral fit retrieval of slant columns, and conversion of the slant columns to vertical columns using air mass factors (AMFs). An iterative optimization algorithm is developed to dynamically find the optimal a priori water vapour profile for the AMF calculation. Further optimizations on the spectral retrieval, air mass factor calculations as well as a new surface albedo retrieval approach are implemented. The TCWV retrieval algorithm is applied to TROPOMI observations from May 2018 to May 2021. The results are validated by comparing them to ERA5 reanalysis data, GOME-2, MODerate resolution Imaging Spectroradiometer (MODIS) and Special Sensor Microwave Imager Sounder (SSMIS) satellite observations. TCWV derived from TROPOMI observations agree well with the other data sets with Pearson correlation coefficient (R) ranging from 0.96 to 0.99. The mean bias between TROPOMI and ERA5 data is -1.24 kg m-2 for measurements over land and 0.73 kg m-2 for measurements over water. The comparison to MODIS observations show similar results with small dry bias of 1.51,kg m-2 for measurements over land and a small wet bias of 1.25 kg m-2 for measurements over water. Slightly larger dry bias of 1.98 kg m-2 for measurements over land and 1.74 kg m-2 for measurements over water are found when compared to GOME-2 obserations. Compared to SSMIS data over water, TROPOMI observations are bias low by 3.25 kg m-2. The small discrepancies found between TROPOMI and reference data sets are related to the differences in measurement technique, measurement time, surface albedo issue, as well as cloud and aerosol contamination. This study demonstrates that the algorithm can provide stable and consistent results on a global scale and can be applied to generate operational TCWV products from TROPOMI and the forthcoming Copernicus missions Sentinel-4 and Sentinel-5. We have also demonstrated the capability of retrieving fine scale water vapour structures in a case study over the Amazon. This indicates that the TROPOMI data set is also useful for local and regional climate studies.
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Affiliation(s)
- Ka Lok Chan
- Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany; Rutherford Appleton Laboratory Space, Harwell Oxford, United Kingdom.
| | - Jian Xu
- Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany; National Space Science Center, Chinese Academy of Sciences, Beijing, China
| | - Sander Slijkhuis
- Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
| | - Pieter Valks
- Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
| | - Diego Loyola
- Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
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6
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Impact of Drought on Isoprene Fluxes Assessed Using Field Data, Satellite-Based GLEAM Soil Moisture and HCHO Observations from OMI. REMOTE SENSING 2022. [DOI: 10.3390/rs14092021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Biogenic volatile organic compounds (BVOCs), primarily emitted by terrestrial vegetation, are highly reactive and have large effects on the oxidizing potential of the troposphere, air quality and climate. In terms of global emissions, isoprene is the most important BVOC. Droughts bring about changes in the surface emission of biogenic hydrocarbons mainly because plants suffer water stress. Past studies report that the current parameterization in the state-of-the-art Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1, which is a function of the soil water content and the permanent wilting point, fails at representing the strong reduction in isoprene emissions observed in field measurements conducted during a severe drought. Since the current algorithm was originally developed based on potted plants, in this study, we update the parameterization in the light of recent ecosystem-scale measurements of isoprene conducted during natural droughts in the central U.S. at the Missouri Ozarks AmeriFlux (MOFLUX) site. The updated parameterization results in stronger reductions in isoprene emissions. Evaluation using satellite formaldehyde (HCHO), a proxy for BVOC emissions, and a chemical-transport model, shows that the adjusted parameterization provides a better agreement between the modelled and observed HCHO temporal variability at local and regional scales in 2011–2012, even if it worsens the model agreement in a global, long-term evaluation. We discuss the limitations of the current parameterization, a function of highly uncertain soil properties such as porosity.
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Souri AH, Chance K, Bak J, Nowlan CR, Abad GG, Jung Y, Wong DC, Mao J, Liu X. Unraveling pathways of elevated ozone induced by the 2020 lockdown in Europe by an observationally constrained regional model using TROPOMI. ATMOSPHERIC CHEMISTRY AND PHYSICS 2021; 21:1-19. [PMID: 34987561 PMCID: PMC8721815 DOI: 10.5194/acp-21-18227-2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Questions about how emissions are changing during the COVID-19 lockdown periods cannot be answered by observations of atmospheric trace gas concentrations alone, in part due to simultaneous changes in atmospheric transport, emissions, dynamics, photochemistry, and chemical feedback. A chemical transport model simulation benefiting from a multi-species inversion framework using well-characterized observations should differentiate those influences enabling to closely examine changes in emissions. Accordingly, we jointly constrain NO x and VOC emissions using well-characterized TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO2 columns during the months of March, April, and May 2020 (lockdown) and 2019 (baseline). We observe a noticeable decline in the magnitude of NO x emissions in March 2020 (14 %-31 %) in several major cities including Paris, London, Madrid, and Milan, expanding further to Rome, Brussels, Frankfurt, Warsaw, Belgrade, Kyiv, and Moscow (34 %-51 %) in April. However, NO x emissions remain at somewhat similar values or even higher in some portions of the UK, Poland, and Moscow in March 2020 compared to the baseline, possibly due to the timeline of restrictions. Comparisons against surface monitoring stations indicate that the constrained model underrepresents the reduction in surface NO2. This underrepresentation correlates with the TROPOMI frequency impacted by cloudiness. During the month of April, when ample TROPOMI samples are present, the surface NO2 reductions occurring in polluted areas are described fairly well by the model (model: -21 ± 17 %, observation: -29 ± 21 %). The observational constraint on VOC emissions is found to be generally weak except for lower latitudes. Results support an increase in surface ozone during the lockdown. In April, the constrained model features a reasonable agreement with maximum daily 8 h average (MDA8) ozone changes observed at the surface (r = 0.43), specifically over central Europe where ozone enhancements prevail (model: +3.73 ± 3.94 %, + 1.79 ppbv, observation: +7.35 ± 11.27 %, +3.76 ppbv). The model suggests that physical processes (dry deposition, advection, and diffusion) decrease MDA8 surface ozone in the same month on average by -4.83 ppbv, while ozone production rates dampened by largely negative J NO 2 [ NO 2 ] - k NO + O 3 [ NO ] [ O 3 ] become less negative, leading ozone to increase by +5.89 ppbv. Experiments involving fixed anthropogenic emissions suggest that meteorology contributes to 42 % enhancement in MDA8 surface ozone over the same region with the remaining part (58 %) coming from changes in anthropogenic emissions. Results illustrate the capability of satellite data of major ozone precursors to help atmospheric models capture ozone changes induced by abrupt emission anomalies.
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Affiliation(s)
- Amir H. Souri
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
| | - Kelly Chance
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
| | - Juseon Bak
- Institute of Environmental Studies, Pusan National University, Busan, South Korea
| | - Caroline R. Nowlan
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
| | - Gonzalo González Abad
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
| | - Yeonjin Jung
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
| | - David C. Wong
- US Environmental Protection Agency, Center for Environmental Measurement & Modeling, Research Triangle Park, NC, USA
| | - Jingqiu Mao
- Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA
- Department of Chemistry and Biochemistry, University of Alaska Fairbanks, Fairbanks, AK, USA
| | - Xiong Liu
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
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8
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Qu Z, Jacob DJ, Silvern RF, Shah V, Campbell PC, Valin LC, Murray LT. US COVID-19 Shutdown Demonstrates Importance of Background NO 2 in Inferring NO x Emissions From Satellite NO 2 Observations. GEOPHYSICAL RESEARCH LETTERS 2021; 48:e2021GL092783. [PMID: 34149109 PMCID: PMC8206743 DOI: 10.1029/2021gl092783] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 04/14/2021] [Accepted: 04/24/2021] [Indexed: 05/08/2023]
Abstract
Satellite nitrogen dioxide (NO2) measurements are used extensively to infer nitrogen oxide emissions and their trends, but interpretation can be complicated by background contributions to the NO2 column sensed from space. We use the step decrease of US anthropogenic emissions from the COVID-19 shutdown to compare the responses of NO2 concentrations observed at surface network sites and from satellites (Ozone Monitoring Instrument [OMI], Tropospheric Ozone Monitoring Instrument [TROPOMI]). After correcting for differences in meteorology, surface NO2 measurements for 2020 show decreases of 20% in March-April and 10% in May-August compared to 2019. The satellites show much weaker responses in March-June and no decrease in July-August, consistent with a large background contribution to the NO2 column. Inspection of the long-term OMI trend over remote US regions shows a rising summertime NO2 background from 2010 to 2019 potentially attributable to wildfires.
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Affiliation(s)
- Zhen Qu
- School of Engineering and Applied ScienceHarvard UniversityCambridgeMAUSA
| | - Daniel J. Jacob
- School of Engineering and Applied ScienceHarvard UniversityCambridgeMAUSA
| | - Rachel F. Silvern
- Department of Earth and Planetary SciencesHarvard UniversityCambridgeMAUSA
- Now at The National Academies of Sciences, Engineering, and MedicineWashingtonDCUSA
| | - Viral Shah
- School of Engineering and Applied ScienceHarvard UniversityCambridgeMAUSA
| | - Patrick C. Campbell
- Center for Spatial Information Science and Systems/Cooperative Institute for Satellite Earth System StudiesGeorge Mason UniversityFairfaxVAUSA
- Office of Air and Radiation, Air Resources LaboratoryNational Oceanic and Atmospheric AdministrationCollege ParkMDUSA
| | - Lukas C. Valin
- Office of Research and DevelopmentUnited States Environmental Protection Agency, Triangle Research ParkDurhamNCUSA
| | - Lee T. Murray
- Department of Earth and Environmental SciencesUniversity of RochesterRochesterNYUSA
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9
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Goldberg DL, Anenberg SC, Kerr GH, Mohegh A, Lu Z, Streets DG. TROPOMI NO 2 in the United States: A Detailed Look at the Annual Averages, Weekly Cycles, Effects of Temperature, and Correlation With Surface NO 2 Concentrations. EARTH'S FUTURE 2021; 9:e2020EF001665. [PMID: 33869651 PMCID: PMC8047911 DOI: 10.1029/2020ef001665] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 01/10/2021] [Accepted: 02/10/2021] [Indexed: 05/27/2023]
Abstract
Observing the spatial heterogeneities of NO2 air pollution is an important first step in quantifying NOX emissions and exposures. This study investigates the capabilities of the Tropospheric Monitoring Instrument (TROPOMI) in observing the spatial and temporal patterns of NO2 pollution in the continental United States. The unprecedented sensitivity of the sensor can differentiate the fine-scale spatial heterogeneities in urban areas, such as emissions related to airport/shipping operations and high traffic, and the relatively small emission sources in rural areas, such as power plants and mining operations. We then examine NO2 columns by day-of-the-week and find that Saturday and Sunday concentrations are 16% and 24% lower respectively, than during weekdays. We also analyze the correlation of daily maximum 2-m temperatures and NO2 column amounts and find that NO2 is larger on the hottest days (>32°C) as compared to warm days (26°C-32°C), which is in contrast to a general decrease in NO2 with increasing temperature at moderate temperatures. Finally, we demonstrate that a linear regression fit of 2019 annual TROPOMI NO2 data to annual surface-level concentrations yields relatively strong correlation (R 2 = 0.66). These new developments make TROPOMI NO2 satellite data advantageous for policymakers and public health officials, who request information at high spatial resolution and short timescales, in order to assess, devise, and evaluate regulations.
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Affiliation(s)
- Daniel L. Goldberg
- Department of Environmental and Occupational HealthGeorge Washington UniversityWashingtonDCUSA
- Energy Systems DivisionArgonne National LaboratoryArgonneILUSA
| | - Susan C. Anenberg
- Department of Environmental and Occupational HealthGeorge Washington UniversityWashingtonDCUSA
| | - Gaige Hunter Kerr
- Department of Environmental and Occupational HealthGeorge Washington UniversityWashingtonDCUSA
| | - Arash Mohegh
- Department of Environmental and Occupational HealthGeorge Washington UniversityWashingtonDCUSA
| | - Zifeng Lu
- Energy Systems DivisionArgonne National LaboratoryArgonneILUSA
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10
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Wu S, Huang B, Wang J, He L, Wang Z, Yan Z, Lao X, Zhang F, Liu R, Du Z. Spatiotemporal mapping and assessment of daily ground NO 2 concentrations in China using high-resolution TROPOMI retrievals. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 273:116456. [PMID: 33477063 DOI: 10.1016/j.envpol.2021.116456] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 01/04/2021] [Accepted: 01/05/2021] [Indexed: 05/21/2023]
Abstract
Nitrogen dioxide (NO2) is an important air pollutant that causes direct harms to the environment and human health. Ground NO2 mapping with high spatiotemporal resolution is critical for fine-scale air pollution and environmental health research. We thus developed a spatiotemporal regression kriging model to map daily high-resolution (3-km) ground NO2 concentrations in China using the Tropospheric Monitoring Instrument (TROPOMI) satellite retrievals and geographical covariates. This model combined geographically and temporally weighted regression with spatiotemporal kriging and achieved robust prediction performance with sample-based and site-based cross-validation R2 values of 0.84 and 0.79. The annual mean and standard deviation of ground NO2 concentrations from June 1, 2018 to May 31, 2019 were predicted to be 15.05 ± 7.82 μg/m3, with that in 0.6% of China's area (10% of the population) exceeding the annual air quality standard (40 μg/m3). The ground NO2 concentrations during the coronavirus disease (COVID-19) period (January and February in 2020) was 14% lower than that during the same period in 2019 and the mean population exposure to ground NO2 was reduced by 25%. This study was the first to use TROPOMI retrievals to map fine-scale daily ground NO2 concentrations across all of China. This was also an early application to use the satellite-estimated ground NO2 data to quantify the impact of the COVID-19 pandemic on the air pollution and population exposures. These newly satellite-derived ground NO2 data with high spatiotemporal resolution have value in advancing environmental and health research in China.
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Affiliation(s)
- Sensen Wu
- School of Earth Sciences, Zhejiang University, Hangzhou, 310027, China; Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, 310028, China; Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong
| | - Bo Huang
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong; Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.
| | - Jionghua Wang
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong
| | - Lijie He
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong
| | - Zhongyi Wang
- School of Earth Sciences, Zhejiang University, Hangzhou, 310027, China
| | - Zhen Yan
- Center of Agricultural and Rural Development, School of Public Affairs, Zhejiang University, Hangzhou, 310058, China
| | - Xiangqian Lao
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, NT, Hong Kong
| | - Feng Zhang
- School of Earth Sciences, Zhejiang University, Hangzhou, 310027, China; Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, 310028, China
| | - Renyi Liu
- School of Earth Sciences, Zhejiang University, Hangzhou, 310027, China; Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, 310028, China
| | - Zhenhong Du
- School of Earth Sciences, Zhejiang University, Hangzhou, 310027, China; Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, 310028, China
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11
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Choi S, Lamsal LN, Follette-Cook M, Joiner J, Krotkov NA, Swartz WH, Pickering KE, Loughner CP, Appel W, Pfister G, Saide PE, Cohen RC, Weinheimer AJ, Herman JR. Assessment of NO 2 observations during DISCOVER-AQ and KORUS-AQ field campaigns. ATMOSPHERIC MEASUREMENT TECHNIQUES 2020; 13:10.5194/amt-13-2523-2020. [PMID: 32670429 PMCID: PMC7362396 DOI: 10.5194/amt-13-2523-2020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
NASA's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011-2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea-United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori profiles) but mostly to OMI's large footprint (> 312 km2).
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Affiliation(s)
- Sungyeon Choi
- NASA Goddard Space Flight Center, Greenbelt, MD 20771,
USA
- Science Systems and Applications, Inc., Lanham, MD 20706,
USA
| | - Lok N. Lamsal
- NASA Goddard Space Flight Center, Greenbelt, MD 20771,
USA
- Universities Space Research Association, Columbia, MD
21046, USA
| | - Melanie Follette-Cook
- NASA Goddard Space Flight Center, Greenbelt, MD 20771,
USA
- Goddard Earth Sciences Technology and Research, Morgan
State University, Baltimore, MD 20251, USA
| | - Joanna Joiner
- NASA Goddard Space Flight Center, Greenbelt, MD 20771,
USA
| | | | - William H. Swartz
- Johns Hopkins University, Applied Physics Laboratory,
Laurel, MD 20723, USA
| | - Kenneth E. Pickering
- NASA Goddard Space Flight Center, Greenbelt, MD 20771,
USA
- Department of Atmospheric and Oceanic Science, University
of Maryland, College Park, MD 20742, USA
| | | | - Wyat Appel
- Environmental Protection Agency, Research Triangle Park, NC
27709, USA
| | - Gabriele Pfister
- National Center for Atmospheric Research, Boulder, CO
80301, USA
| | - Pablo E. Saide
- Department of Atmospheric and Oceanic Sciences, and
Institute of the Environment and Sustainability, University of California, Los
Angeles, CA 90095, USA
| | - Ronald C. Cohen
- Department of Chemistry and Department of Earth and
Planetary Science, University of California, Berkeley, CA 94720, USA
| | | | - Jay R. Herman
- NASA Goddard Space Flight Center, Greenbelt, MD 20771,
USA
- Joint Center for Earth Systems Technology, University of
Maryland Baltimore County, Baltimore, MD 21250, USA
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12
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Di Q, Amini H, Shi L, Kloog I, Silvern R, Kelly J, Sabath MB, Choirat C, Koutrakis P, Lyapustin A, Wang Y, Mickley LJ, Schwartz J. Assessing NO 2 Concentration and Model Uncertainty with High Spatiotemporal Resolution across the Contiguous United States Using Ensemble Model Averaging. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:1372-1384. [PMID: 31851499 PMCID: PMC7065654 DOI: 10.1021/acs.est.9b03358] [Citation(s) in RCA: 129] [Impact Index Per Article: 32.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
NO2 is a combustion byproduct that has been associated with multiple adverse health outcomes. To assess NO2 levels with high accuracy, we propose the use of an ensemble model to integrate multiple machine learning algorithms, including neural network, random forest, and gradient boosting, with a variety of predictor variables, including chemical transport models. This NO2 model covers the entire contiguous U.S. with daily predictions on 1-km-level grid cells from 2000 to 2016. The ensemble produced a cross-validated R2 of 0.788 overall, a spatial R2 of 0.844, and a temporal R2 of 0.729. The relationship between daily monitored and predicted NO2 is almost linear. We also estimated the associated monthly uncertainty level for the predictions and address-specific NO2 levels. This NO2 estimation has a very high spatiotemporal resolution and allows the examination of the health effects of NO2 in unmonitored areas. We found the highest NO2 levels along highways and in cities. We also observed that nationwide NO2 levels declined in early years and stagnated after 2007, in contrast to the trend at monitoring sites in urban areas, where the decline continued. Our research indicates that the integration of different predictor variables and fitting algorithms can achieve an improved air pollution modeling framework.
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Affiliation(s)
- Qian Di
- Research Center for Public Health, Tsinghua University, Beijing, China, 100084
- Department of Environmental Health, Harvard T.H. Chan School of Public Heath, Boston, Massachusetts, United States, 02215
- Corresponding author: Qian Di ()
| | - Heresh Amini
- Department of Environmental Health, Harvard T.H. Chan School of Public Heath, Boston, Massachusetts, United States, 02215
| | - Liuhua Shi
- Department of Environmental Health, Harvard T.H. Chan School of Public Heath, Boston, Massachusetts, United States, 02215
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States, 30322
| | - Itai Kloog
- Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Beer Sheva, Israel, P.O.Box 653
| | - Rachel Silvern
- Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts, United States, 02138
| | - James Kelly
- U.S. Environmental Protection Agency, Office of Air Quality Planning & Standards, Research Triangle Park, North Carolina, United States, 27711
| | - M. Benjamin Sabath
- Department of Biostatistics, Harvard T.H. Chan School of Public Heath, Boston, Massachusetts, United States, 02115
| | - Christine Choirat
- Department of Biostatistics, Harvard T.H. Chan School of Public Heath, Boston, Massachusetts, United States, 02115
| | - Petros Koutrakis
- Department of Environmental Health, Harvard T.H. Chan School of Public Heath, Boston, Massachusetts, United States, 02215
| | - Alexei Lyapustin
- NASA Goddard Space Flight Center, Greenbelt, Maryland, United States, 20771
| | - Yujie Wang
- University of Maryland, Baltimore County, Baltimore, Maryland, United States, 21250
| | - Loretta J. Mickley
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge Massachusetts, United States, 02138
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Heath, Boston, Massachusetts, United States, 02215
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13
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NO2 Retrieval from the Environmental Trace Gases Monitoring Instrument (EMI): Preliminary Results and Intercomparison with OMI and TROPOMI. REMOTE SENSING 2019. [DOI: 10.3390/rs11243017] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Onboard the Chinese GaoFen-5 (GF5) satellite, the Environmental trace gases Monitoring Instrument (EMI) is a nadir-viewing wide-field spectrometer that was launched on May 9, 2018. EMI measures the back-scattered earthshine solar radiance in the ultraviolet and visible spectral range. By using the differential optical absorption spectrometry (DOAS) method and the EMI measurements in the VIS1 band (405–465 nm), we performed retrievals of NO2. Some first retrieval results of NO2 from EMI and a comparison with OMI and TROPOMI products are presented in this paper. The monthly mean total vertical column densities (VCD) of NO2 show similar spatial distributions to OMI and TROPOMI (r > 0.88) and their difference is less than 27%. A comparison of the daily total VCD shows that EMI could detect the NO2 patterns in good agreement with OMI (r = 0.93) and TROPOMI (r = 0.95). However, the slant column density (SCD) uncertainty (0.79 × 1015 molec cm−2) of the current EMI algorithm is relatively larger than OMI. The daily variation pattern of NO2 from EMI in Beijing in January 2019 is consistent with TROPOMI (r = 0.96). The spatial distribution correlation of the tropospheric NO2 VCD of EMI with OMI and TROPOMI is 0.88 and 0.89, respectively, but shows an overestimate compared to OMI (15%) and TROPOMI (23%), respectively. This study demonstrates the capability of using EMI for global NO2 monitoring.
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14
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Goldberg DL, Lu Z, Streets DG, de Foy B, Griffin D, McLinden CA, Lamsal LN, Krotkov NA, Eskes H. Enhanced Capabilities of TROPOMI NO 2: Estimating NO X from North American Cities and Power Plants. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:12594-12601. [PMID: 31601103 DOI: 10.1021/acs.est.9b04488] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
The TROPOspheric Monitoring Instrument (TROPOMI) is used to derive top-down NOX emissions for two large power plants and three megacities in North America. We first re-process the vertical column NO2 with an improved air mass factor to correct for a known systematic low bias in the operational retrieval near urban centers. For the two power plants, top-down NOX emissions agree to within 10% of the emissions reported by the power plants. We then derive top-down NOX emissions rates for New York City, Chicago, and Toronto, and compare them to projected bottom-up emissions inventories. In this analysis of 2018 NOX emissions, we find a +22% overestimate for New York City, a -21% underestimate in Toronto, and good agreement in Chicago in the projected bottom-up inventories when compared to the top-down emissions. Top-down NOX emissions also capture intraseasonal variability, such as the weekday versus weekend effect (emissions are +45% larger on weekdays versus weekends in Chicago). Finally, we demonstrate the enhanced capabilities of TROPOMI, which allow us to derive a NOX emissions rate for Chicago using a single overpass on July 7, 2018. The large signal-to-noise ratio of TROPOMI is well-suited for estimating NOX emissions from relatively small sources and for sub-seasonal timeframes.
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Affiliation(s)
- Daniel L Goldberg
- Energy Systems Division , Argonne National Laboratory , Lemont , Illinois 60439 , United States
- Consortium for Advanced Science and Engineering , University of Chicago , Chicago , Illinois 60637 , United States
- Department of Environmental and Occupational Health , George Washington University , Washington , DC 20052 , United States
| | - Zifeng Lu
- Energy Systems Division , Argonne National Laboratory , Lemont , Illinois 60439 , United States
- Consortium for Advanced Science and Engineering , University of Chicago , Chicago , Illinois 60637 , United States
| | - David G Streets
- Energy Systems Division , Argonne National Laboratory , Lemont , Illinois 60439 , United States
- Consortium for Advanced Science and Engineering , University of Chicago , Chicago , Illinois 60637 , United States
| | - Benjamin de Foy
- Department of Earth and Atmospheric Sciences , Saint Louis University , St. Louis , Missouri 63108 , United States
| | - Debora Griffin
- Air Quality Research Division , Environment and Climate Change Canada , Toronto , Ontario M3H 5T4 , Canada
| | - Chris A McLinden
- Air Quality Research Division , Environment and Climate Change Canada , Toronto , Ontario M3H 5T4 , Canada
| | - Lok N Lamsal
- University Space Research Association, Goddard Earth Sciences Technology and Research (GESTAR) , Columbia , Maryland 21046 , United States
- NASA Goddard Space Flight Center , Greenbelt , Maryland 20770 , United States
| | - Nickolay A Krotkov
- NASA Goddard Space Flight Center , Greenbelt , Maryland 20770 , United States
| | - Henk Eskes
- Royal Netherlands Meteorological Institute (KNMI) , De Bilt 3730 AE , The Netherlands
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15
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Temporal Analysis of OMI-Observed Tropospheric NO2 Columns over East Asia during 2006–2015. ATMOSPHERE 2019. [DOI: 10.3390/atmos10110658] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The study analyzed temporal variations of Ozone Monitoring Instrument (OMI)-observed NO2 columns, interregional correlation, and comparison between NO2 columns and NOx emissions during the period from 2006 to 2015. Regarding the trend of the NO2 columns, the linear lines were classified into four groups: (1) ‘upward and downward’ over six defined geographic regions in central-east Asia; (2) ‘downward’ over Guangzhou, Japan, and Taiwan; (3) ‘stagnant’ over South Korea; and (4) ‘upward’ over North Korea, Mongolia, Qinghai, and Northwestern Pacific ocean. In particular, the levels of NO2 columns in 2015 returned to those in 2006 over most of the polluted regions in China. Quantitatively, their relative changes in 2015 compared to 2006 were approximately 10%. From the interregional correlation analysis, it was found that unlike positive relationships between the polluted areas, the different variations of monthly NO2 columns led to negative relationships in Mongolia and Qinghai. Regarding the comparison between NO2 columns and NOx emission, the NOx emissions from the Copernicus Atmosphere Monitoring Service (CAMS) and Clean Air Policy Support System (CAPSS) inventories did not follow the year-to-year variations of NO2 columns over the polluted regions. In addition, the weekly effect was only clearly shown in South Korea, Japan, and Taiwan, indicating that the amounts of NOx emissions are significantly contributed to by the transportation sector.
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16
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Chatzidiakou L, Krause A, Popoola OAM, Di Antonio A, Kellaway M, Han Y, Squires FA, Wang T, Zhang H, Wang Q, Fan Y, Chen S, Hu M, Quint JK, Barratt B, Kelly FJ, Zhu T, Jones RL. Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments. ATMOSPHERIC MEASUREMENT TECHNIQUES 2019; 12:4643-4657. [PMID: 31534556 PMCID: PMC6751078 DOI: 10.5194/amt-12-1-2019] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The inaccurate quantification of personal exposure to air pollution introduces error and bias in health estimations, severely limiting causal inference in epidemiological research worldwide. Rapid advancements in affordable, miniaturised air pollution sensor technologies offer the potential to address this limitation by capturing the high variability of personal exposure during daily life in large-scale studies with unprecedented spatial and temporal resolution. However, concerns remain regarding the suitability of novel sensing technologies for scientific and policy purposes. In this paper we characterise the performance of a portable personal air quality monitor (PAM) that integrates multiple miniaturised sensors for nitrogen oxides (NO x ), carbon monoxide (CO), ozone (O3) and particulate matter (PM) measurements along with temperature, relative humidity, acceleration, noise and GPS sensors. Overall, the air pollution sensors showed high reproducibility (meanR ¯ 2 = 0.93, min-max: 0.80-1.00) and excellent agreement with standard instrumentation (meanR ¯ 2 = 0.82, min-max: 0.54-0.99) in outdoor, indoor and commuting microenvironments across seasons and different geographical settings. An important outcome of this study is that the error of the PAM is significantly smaller than the error introduced when estimating personal exposure based on sparsely distributed outdoor fixed monitoring stations. Hence, novel sensing technologies such as the ones demonstrated here can revolutionise health studies by providing highly resolved reliable exposure metrics at a large scale to investigate the underlying mechanisms of the effects of air pollution on health.
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Affiliation(s)
- Lia Chatzidiakou
- Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
| | - Anika Krause
- Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
| | | | - Andrea Di Antonio
- Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
| | | | - Yiqun Han
- MRC-PHE Centre for Environment & Health, Imperial College London and King’s College London, London, W2 1PG, UK
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- Department of Analytical, Environmental and Forensic Sciences, King’s College London, London, SE1 9NH, UK
| | | | - Teng Wang
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- The Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing, 100871, China
| | - Hanbin Zhang
- MRC-PHE Centre for Environment & Health, Imperial College London and King’s College London, London, W2 1PG, UK
- Department of Analytical, Environmental and Forensic Sciences, King’s College London, London, SE1 9NH, UK
- NIHR Health Protection Research Unit in Health Impact of Environmental Hazards, King’s College London, London, SE1 9NH, UK
| | - Qi Wang
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- The Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing, 100871, China
| | - Yunfei Fan
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- The Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing, 100871, China
| | - Shiyi Chen
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Min Hu
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- The Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing, 100871, China
| | - Jennifer K. Quint
- National Heart and Lung Institute, Imperial College London, SW3 6LR, UK
| | - Benjamin Barratt
- MRC-PHE Centre for Environment & Health, Imperial College London and King’s College London, London, W2 1PG, UK
- Department of Analytical, Environmental and Forensic Sciences, King’s College London, London, SE1 9NH, UK
- NIHR Health Protection Research Unit in Health Impact of Environmental Hazards, King’s College London, London, SE1 9NH, UK
| | - Frank J. Kelly
- MRC-PHE Centre for Environment & Health, Imperial College London and King’s College London, London, W2 1PG, UK
- Department of Analytical, Environmental and Forensic Sciences, King’s College London, London, SE1 9NH, UK
- NIHR Health Protection Research Unit in Health Impact of Environmental Hazards, King’s College London, London, SE1 9NH, UK
| | - Tong Zhu
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- The Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing, 100871, China
| | - Roderic L. Jones
- Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
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17
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Griffin D, McLinden CA, Boersma F, Bourassa A, Dammers E, Degenstein D, Eskes H, Fehr L, Fioletov V, Hayden K, Kharol SK, Li SM, Makar P, Martin RV, Mihele C, Mittermeier RL, Krotkov N, Sneep M, Lamsal LN, Ter Linden M, van Geffen J, Veefkind P, Wolde M, Zhao X. High resolution mapping of nitrogen dioxide with TROPOMI: First results and validation over the Canadian oil sands. GEOPHYSICAL RESEARCH LETTERS 2019; 46:1049-1060. [PMID: 33867596 PMCID: PMC8051066 DOI: 10.1029/2018gl081095] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Accepted: 12/22/2018] [Indexed: 05/20/2023]
Abstract
UNLABELLED TROPOMI, on-board the Sentinel-5 Precursor satellite is a nadir-viewing spectrometer measuring reflected sunlight in the ultraviolet, visible, near-infrared, and shortwave infrared spectral range. From these spectra several important air quality and climate-related atmospheric constituents are retrieved at an unprecedented high spatial resolution, including nitrogen dioxide (NO2). We present the first retrievals of TROPOMI NO2 over the Canadian Oil Sands, contrasting them with observations from the OMI satellite instrument, and demonstrate its ability to resolve individual plumes and highlight its potential for deriving emissions from individual mining facilities. Further, the first TROPOMI NO2 validation is presented, consisting of aircraft and surface in-situ NO2 observations, as well as ground-based remote-sensing measurements between March and May 2018. Our comparisons show that the TROPOMI NO2 vertical column densities are highly correlated with the aircraft and surface in-situ NO2 observations, and the ground-based remote-sensing measurements with a low bias (15-30 %) over the Canadian Oil Sands. PLAIN LANGUAGE SUMMARY Nitrogen dioxide (NO2) is a pollutant that is linked to respiratory health issues and has negative environmental impacts such as soil and water acidification. Near the surface the most significant sources of NO2 are fossil fuel combustion and biomass burning. With a recently launched satellite instrument (TROPOspheric Monitoring Instrument; TROPOMI) NO2 can be measured with an unprecedented combination of accuracy, spatial coverage, and resolution. This work presents the first TROPOMI NO2 measurements near the Canadian Oil Sands and shows that these measurements have an outstanding ability to detect NO2 on a very high horizontal resolution that is unprecedented for satellite NO2 observations. Further, these satellite measurements are in excellent agreement with aircraft and ground-based measurements.
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Affiliation(s)
- Debora Griffin
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
| | - Chris A McLinden
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
| | - Folkert Boersma
- Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
- Wageningen University, Environmental Sciences Group, Wageningen, The Netherlands
| | - Adam Bourassa
- Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Enrico Dammers
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
| | - Doug Degenstein
- Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Henk Eskes
- Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
| | - Lukas Fehr
- Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Vitali Fioletov
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
| | - Katherine Hayden
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
| | - Shailesh K Kharol
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
| | - Shao-Meng Li
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
| | - Paul Makar
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
| | - Randall V Martin
- Dalhousie University, Department of Physics and Atmospheric Science, Halifax, Nova Scotia, Canada
| | - Cristian Mihele
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
| | - Richard L Mittermeier
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
| | - Nickolay Krotkov
- Laboratory for atmospheric chemistry and dynamics, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Maarten Sneep
- Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
| | - Lok N Lamsal
- Laboratory for atmospheric chemistry and dynamics, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Goddard Earth Sciences Technology and Research, Universities Space Research Association, Columbia, MD, USA
| | - Mark Ter Linden
- Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
- Science and Technology (S&T), Delft, Netherlands
| | - Jos van Geffen
- Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
| | - Pepijn Veefkind
- Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
- Delft University of Technology, Delft, The Netherlands
| | - Mengistu Wolde
- National Research Council Canada, Flight Research Laboratory, Ottawa, K1A 0R6, Canada
| | - Xiaoyi Zhao
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
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18
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Zhang X, Zhang W, Lu X, Liu X, Chen D, Liu L, Huang X. Long-term trends in NO 2 columns related to economic developments and air quality policies from 1997 to 2016 in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 639:146-155. [PMID: 29783115 DOI: 10.1016/j.scitotenv.2018.04.435] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 04/08/2018] [Accepted: 04/28/2018] [Indexed: 05/08/2023]
Abstract
This study detected the long-term trends in NO2 concentrations in China from 1997 to 2016 based on the NO2 columns from GOME, SCIAMACHY, and GOME-2A. Both differences in the time-overlapped NO2 columns from GOME vs. SCIAMACHAY and SCIAMACHAY vs. GOME-2A showed seasonal variations, and the annual NO2 columns from GOME were 0.9% higher than those from SCIAMACHY, which exceeded that from GOME-2A by 14%. The long-term trends of the NO2 columns on a provincial scale could be simulated by cubic models (0.60 < R2 < 0.96, p < 0.05) and presented three shapes: first decreasing then increasing and decreasing again; first decreasing then increasing; and continuously decreasing. The peak years of NO2 columns in 17 provinces occurred in 2011 and 2012. These trends in NO2 columns were determined by the economic developments and enacted air quality policies in nearly all the provinces except for Xizang and Qinghai Provinces, where the trends were determined by natural NOx emission sources. In detail, the panel data analysis showed that the simulated model had fixed effects, and the thermal power generation, consumption of diesel oil in agriculture, passenger traffic by highways, and freight traffic by highways significantly increased NO2, while the air quality policies in the 12th five-year plan decreased NO2 columns from 1997 to 2016. The benefits to decreasing NO2 columns from the air quality policies issued in the 10th and 11th five-year plans were offset by the quickly increasing economies.
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Affiliation(s)
- Xiuying Zhang
- International Institute for Earth System Science, Nanjing University, Nanjing 210023, China.
| | - Wuting Zhang
- International Institute for Earth System Science, Nanjing University, Nanjing 210023, China; Jiangsu Centre for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
| | - Xuehe Lu
- International Institute for Earth System Science, Nanjing University, Nanjing 210023, China.
| | - Xuejun Liu
- College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Dongmei Chen
- Department of Geography and Planning, Queen's University, Kingston, ON K7L 3N6, Canada
| | - Lei Liu
- International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Xianjin Huang
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China.
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Cooper MJ, Martin RV, Lyapustin AI, McLinden CA. Assessing snow extent data sets over North America to inform and improve trace gas retrievals from solar backscatter. ATMOSPHERIC MEASUREMENT TECHNIQUES 2018; 11:2983-2994. [PMID: 30450131 PMCID: PMC6235450 DOI: 10.5194/amt-11-2983-2018] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
Accurate representation of surface reflectivity is essential to tropospheric trace gas retrievals from solar backscatter observations. Surface snow cover presents a significant challenge due to its variability and thus snow-covered scenes are often omitted from retrieval data sets; however, the high reflectance of snow is potentially advantageous for trace gas retrievals. We first examine the implications of surface snow on retrievals from the upcoming TEMPO geostationary instrument for North America. We use a radiative transfer model to examine how an increase in surface reflectivity due to snow cover changes the sensitivity of satellite retrievals to NO2 in the lower troposphere. We find that a substantial fraction (>50%) of the TEMPO field of regard can be snow covered in January, and that the average sensitivity to the tropospheric NO2 column substantially increases (doubles) when the surface is snow covered. We then evaluate seven existing satellite-derived or reanalysis snow extent products against ground station observations over North America to assess their capability of informing surface conditions for TEMPO retrievals. The Interactive Multisensor Snow and Ice Mapping System (IMS) had the best agreement with ground observations (accuracy of 93%, precision of 87%, recall of 83%). Multiangle Implementation of Atmospheric Correction (MAIAC) retrievals of MODIS-observed radiances had high precision (90% for Aqua and Terra), but underestimated the presence of snow (recall of 74% for Aqua, 75% for Terra). MAIAC generally outperforms the standard MODIS products (precision of 51%, recall of 43% for Aqua; precision of 69%, recall of 45% for Terra). The Near-real-time Ice and Snow Extent (NISE) product had good precision (83%) but missed a significant number of snow-covered pixels (recall of 45%). The Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis Data set had strong performance metrics (accuracy of 91%, precision of 79%, recall of 82%). We use the F score, which balances precision and recall, to determine overall product performance (F = 85%, 82(82)%, 81%, 58%, 46(54)% for IMS, MAIAC Aqua(Terra), CMC, NISE, MODIS Aqua(Terra) respectively) for providing snow cover information for TEMPO retrievals from solar backscatter observations. We find that using IMS to identify snow cover and enable inclusion of snow-covered scenes in clear-sky conditions across North America in January can increase both the number of observations by a factor of 2.1 and the average sensitivity to the tropospheric NO2 column by a factor of 2.7.
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Affiliation(s)
- Matthew J Cooper
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Randall V Martin
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada
- Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts, USA
| | | | - Chris A McLinden
- Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
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20
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Estimation of Surface NO2 Volume Mixing Ratio in Four Metropolitan Cities in Korea Using Multiple Regression Models with OMI and AIRS Data. REMOTE SENSING 2017. [DOI: 10.3390/rs9060627] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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21
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Ground-Level NO2 Concentrations over China Inferred from the Satellite OMI and CMAQ Model Simulations. REMOTE SENSING 2017. [DOI: 10.3390/rs9060519] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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22
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Zoogman P, Liu X, Suleiman RM, Pennington WF, Flittner DE, Al-Saadi JA, Hilton BB, Nicks DK, Newchurch MJ, Carr JL, Janz SJ, Andraschko MR, Arola A, Baker BD, Canova BP, Chan Miller C, Cohen RC, Davis JE, Dussault ME, Edwards DP, Fishman J, Ghulam A, González Abad G, Grutter M, Herman JR, Houck J, Jacob DJ, Joiner J, Kerridge BJ, Kim J, Krotkov NA, Lamsal L, Li C, Lindfors A, Martin RV, McElroy CT, McLinden C, Natraj V, Neil DO, Nowlan CR, O'Sullivan EJ, Palmer PI, Pierce RB, Pippin MR, Saiz-Lopez A, Spurr RJD, Szykman JJ, Torres O, Veefkind JP, Veihelmann B, Wang H, Wang J, Chance K. Tropospheric Emissions: Monitoring of Pollution (TEMPO). JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER 2017; 186:17-39. [PMID: 32817995 PMCID: PMC7430511 DOI: 10.1016/j.jqsrt.2016.05.008] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
TEMPO was selected in 2012 by NASA as the first Earth Venture Instrument, for launch between 2018 and 2021. It will measure atmospheric pollution for greater North America from space using ultraviolet and visible spectroscopy. TEMPO observes from Mexico City, Cuba, and the Bahamas to the Canadian oil sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution (~2.1 km N/S×4.4 km E/W at 36.5°N, 100°W). TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry, as well as contributing to carbon cycle knowledge. Measurements are made hourly from geostationary (GEO) orbit, to capture the high variability present in the diurnal cycle of emissions and chemistry that are unobservable from current low-Earth orbit (LEO) satellites that measure once per day. The small product spatial footprint resolves pollution sources at sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies. TEMPO takes advantage of a commercial GEO host spacecraft to provide a modest cost mission that measures the spectra required to retrieve ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), formaldehyde (H2CO), glyoxal (C2H2O2), bromine monoxide (BrO), IO (iodine monoxide),water vapor, aerosols, cloud parameters, ultraviolet radiation, and foliage properties. TEMPO thus measures the major elements, directly or by proxy, in the tropospheric O3 chemistry cycle. Multi-spectral observations provide sensitivity to O3 in the lowermost troposphere, substantially reducing uncertainty in air quality predictions. TEMPO quantifies and tracks the evolution of aerosol loading. It provides these near-real-time air quality products that will be made publicly available. TEMPO will launch at a prime time to be the North American component of the global geostationary constellation of pollution monitoring together with the European Sentinel-4 (S4) and Korean Geostationary Environment Monitoring Spectrometer (GEMS) instruments.
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Affiliation(s)
- P Zoogman
- Harvard-Smithsonian Center for Astrophysics
| | - X Liu
- Harvard-Smithsonian Center for Astrophysics
| | | | | | | | | | | | | | | | | | - S J Janz
- NASA Goddard Space Flight Center
| | | | - A Arola
- Finnish Meteorological Institute
| | | | | | | | - R C Cohen
- University of California at Berkeley
| | - J E Davis
- Harvard-Smithsonian Center for Astrophysics
| | | | | | | | | | | | - M Grutter
- Universidad Nacional Autónoma de México
| | - J R Herman
- University of Maryland, Baltimore County
| | - J Houck
- Harvard-Smithsonian Center for Astrophysics
| | | | - J Joiner
- NASA Goddard Space Flight Center
| | | | | | | | - L Lamsal
- NASA Goddard Space Flight Center
- GESTAR, University Space Research Association
| | - C Li
- NASA Goddard Space Flight Center
- University of Maryland, Baltimore County
| | | | - R V Martin
- Harvard-Smithsonian Center for Astrophysics
- Dalhousie University
| | | | | | | | | | - C R Nowlan
- Harvard-Smithsonian Center for Astrophysics
| | | | | | - R B Pierce
- National Oceanic and Atmospheric Administration
| | | | - A Saiz-Lopez
- Instituto de Química Física Rocasolano, CSIC, Spain
| | | | | | - O Torres
- NASA Goddard Space Flight Center
| | | | | | - H Wang
- Harvard-Smithsonian Center for Astrophysics
| | | | - K Chance
- Harvard-Smithsonian Center for Astrophysics
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Wang B, Chen Z. High-resolution satellite-based analysis of ground-level PM2.5 for the city of Montreal. THE SCIENCE OF THE TOTAL ENVIRONMENT 2016; 541:1059-1069. [PMID: 26473708 DOI: 10.1016/j.scitotenv.2015.10.024] [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: 07/19/2015] [Revised: 09/21/2015] [Accepted: 10/06/2015] [Indexed: 06/05/2023]
Abstract
Satellite remote sensing offers the opportunity to determine the spatial distribution of aerosol properties and could fill the gap of ground-level observations. Various algorithms have recently been developed in order to retrieve the aerosol optical depth (AOD) at continental scales. However, they are, to some extent, subject to coarse spatial resolutions which are not appropriate for intraurban scales as usually needed in health studies. This paper presents an improved AOD retrieval algorithm for satellite instrument MODIS at 1-km resolution for intraurban scales. The MODIS-retrieved AODs are used to derive the ground-level PM2.5 concentrations using the aerosol vertical profiles and local scale factors obtained from the GEOS-Chem model simulation. The developed method has been applied to retrieve the AODs and to evaluate the ground-level PM2.5 over the city of Montreal, Canada for 2009 on daily, monthly and annual scales. The daily and monthly results are compared with the monitoring values with correlations R(2) ranging from 0.86 to 0.93. Especially, the annual mean PM2.5 concentrations are in good agreement with the measurement values at all monitoring stations (r=0.96, slope=1.0132 ± 0.0025, intercept=0.5739 ± 0.0013). This illustrates that the developed AOD retrieval algorithm can be used to retrieve AODs at a higher spatial resolution than previous studies to further derive the regional full coverage PM2.5 results at finer spatial and temporal scales. The study results are useful in health risk assessment across this region.
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Affiliation(s)
- Baozhen Wang
- Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Quebec H3G 1M8, Canada
| | - Zhi Chen
- Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Quebec H3G 1M8, Canada.
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24
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Travis KR, Jacob DJ, Fisher JA, Kim PS, Marais EA, Zhu L, Yu K, Miller CC, Yantosca RM, Sulprizio MP, Thompson AM, Wennberg PO, Crounse JD, St Clair JM, Cohen RC, Laughner JL, Dibb JE, Hall SR, Ullmann K, Wolfe GM, Pollack IB, Peischl J, Neuman JA, Zhou X. Why do Models Overestimate Surface Ozone in the Southeastern United States? ATMOSPHERIC CHEMISTRY AND PHYSICS 2016; 16:13561-13577. [PMID: 29619045 PMCID: PMC5880041 DOI: 10.5194/acp-16-13561-2016] [Citation(s) in RCA: 105] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NOx ≡ NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC4RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25°×0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NOx from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC4RS observations of NOx and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Our results indicate that NEI NOx emissions from mobile and industrial sources must be reduced by 30-60%, dependent on the assumption of the contribution by soil NOx emissions. Upper tropospheric NO2 from lightning makes a large contribution to satellite observations of tropospheric NO2 that must be accounted for when using these data to estimate surface NOx emissions. We find that only half of isoprene oxidation proceeds by the high-NOx pathway to produce ozone; this fraction is only moderately sensitive to changes in NOx emissions because isoprene and NOx emissions are spatially segregated. GEOS-Chem with reduced NOx emissions provides an unbiased simulation of ozone observations from the aircraft, and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NOx oxidation products. However, the model is still biased high by 8±13 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer.
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Affiliation(s)
- Katherine R. Travis
- Department of Earth and Planetary Sciences and School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
| | - Daniel J. Jacob
- Department of Earth and Planetary Sciences and School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
- Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
| | - Jenny A. Fisher
- Centre for Atmospheric Chemistry, School of Chemistry, University of Wollongong, Wollongong, NSW, Australia
- School of Earth and Environmental Sciences, University of Wollongong, Wollongong, NSW, Australia
| | - Patrick S. Kim
- Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
| | - Eloise A. Marais
- Department of Earth and Planetary Sciences and School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
| | - Lei Zhu
- Department of Earth and Planetary Sciences and School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
| | - Karen Yu
- Department of Earth and Planetary Sciences and School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
| | - Christopher C. Miller
- Department of Earth and Planetary Sciences and School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
| | - Robert M. Yantosca
- Department of Earth and Planetary Sciences and School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
| | - Melissa P. Sulprizio
- Department of Earth and Planetary Sciences and School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
| | | | - Paul O. Wennberg
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
- Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA
| | - John D. Crounse
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
| | - Jason M. St Clair
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
| | - Ronald C. Cohen
- Department of Chemistry, University of California, Berkeley, CA, USA
| | | | - Jack E. Dibb
- Earth System Research Center, University of New Hampshire, Durham, NH, USA
| | - Samuel R. Hall
- Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, CO, USA
| | - Kirk Ullmann
- Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, CO, USA
| | - Glenn M. Wolfe
- Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Joint Center for Earth Systems Technology, University of Maryland Baltimore County, Baltimore, MD, USA
| | - Illana B. Pollack
- Atmospheric Science Department, Colorado State University, Fort Collins, Colorado, USA
| | - Jeff Peischl
- University of Colorado, Cooperative Institute for Research in Environmental Sciences, Boulder, CO, USA
- NOAA, Division of Chemical Science, Earth Systems Research Lab, Boulder, CO USA
| | - Jonathan A. Neuman
- University of Colorado, Cooperative Institute for Research in Environmental Sciences, Boulder, CO, USA
- NOAA, Division of Chemical Science, Earth Systems Research Lab, Boulder, CO USA
| | - Xianliang Zhou
- Department of Environmental Health and Toxicology, School of Public Health, State University of New York at Albany, Albany, New York, USA
- Wadsworth Center, New York State Department of Health, Albany, New York, USA
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25
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Kim NK, Kim YP, Morino Y, Kurokawa JI, Ohara T. Verification of NOx emission inventories over North Korea. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2014; 195:236-244. [PMID: 25074425 DOI: 10.1016/j.envpol.2014.06.034] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2014] [Revised: 06/24/2014] [Accepted: 06/28/2014] [Indexed: 06/03/2023]
Abstract
In this study, the top-down NOx emissions estimated from satellite observations of NO2 vertical column densities over North Korea from 1996 to 2009 were analyzed. Also, a bottom-up NOx emission inventory from REAS 1.1 from 1980 to 2005 was analyzed with several statistics. REAS 1.1 was in good agreement with the top-down approach for both trend and amount. The characteristics of NOx emissions in North Korea were quite different from other developed countries including South Korea. In North Korea, emissions from industry sector was the highest followed by transportation sector in the 1980s. However, after 1990, the NOx emissions from other sector, mainly agriculture, became the 2nd highest. Also, no emission centers such as urban areas or industrial areas were distinctively observed. Finally, the monthly NOx emissions were high during the warm season.
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Affiliation(s)
- Na Kyung Kim
- Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
| | - Yong Pyo Kim
- Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Republic of Korea.
| | - Yu Morino
- National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan
| | - Jun-ichi Kurokawa
- Atmospheric Research Department, Asia Center for Air Pollution Research, Niigata, Japan
| | - Toshimasa Ohara
- National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan.
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Huanhuan Y, Liangfu C, Lin S, Jinhua T, Chao Y. SO2columns over China: Temporal and spatial variations using OMI and GOME-2 observations. ACTA ACUST UNITED AC 2014. [DOI: 10.1088/1755-1315/17/1/012027] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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27
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Wang B, Chen Z. An intercomparison of satellite-derived ground-level NO₂ concentrations with GMSMB modeling results and in-situ measurements--a North American study. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2013; 181:172-181. [PMID: 23867698 DOI: 10.1016/j.envpol.2013.06.037] [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: 01/07/2013] [Revised: 06/19/2013] [Accepted: 06/20/2013] [Indexed: 06/02/2023]
Abstract
This paper investigates the biases associated with the ground-level nitrogen dioxide (NO2) concentrations derived from the satellite Ozone Monitoring Instrument (OMI) NO2 data through comparisons with the modeling and the monitoring results for the state of California in 2008. The seasonal and annual average ground-level NO2 concentrations are both analyzed from the OMI using the local NO2 profile obtained from the GEOS-Chem simulation. The OMI-derived ground-level NO2 concentrations are then compared with the NO2 concentrations predicted by a GIS-Based Multi-Source and Multi-Box model (GMSMB) and the in-situ measurements, correlation coefficients among the three sets of results are all above 0.84 with an average slope of 0.81 ± 0.04. Particularly, various biases associated with the three data sets have been analyzed, and the OMI-derived NO2 concentrations and the GMSMB modeling results have been proven to be essential for assessing regional air pollutant exposure risks with the aid of the extensive remote sensing database.
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Affiliation(s)
- Baozhen Wang
- Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Quebec H3G 1M8, Canada
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28
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Yuan T, Remer LA, Bian H, Ziemke JR, Albrecht R, Pickering KE, Oreopoulos L, Goodman SJ, Yu H, Allen DJ. Aerosol indirect effect on tropospheric ozone via lightning. ACTA ACUST UNITED AC 2012. [DOI: 10.1029/2012jd017723] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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29
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Barkley MP, Kurosu TP, Chance K, De Smedt I, Van Roozendael M, Arneth A, Hagberg D, Guenther A. Assessing sources of uncertainty in formaldehyde air mass factors over tropical South America: Implications for top-down isoprene emission estimates. ACTA ACUST UNITED AC 2012. [DOI: 10.1029/2011jd016827] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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30
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Muntaseer Billah Ibn Azkar MA, Chatani S, Sudo K. Simulation of urban and regional air pollution in Bangladesh. ACTA ACUST UNITED AC 2012. [DOI: 10.1029/2011jd016509] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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31
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Prasad AK, Singh RP, Kafatos M. Influence of coal-based thermal power plants on the spatial-temporal variability of tropospheric NO2 column over India. ENVIRONMENTAL MONITORING AND ASSESSMENT 2012; 184:1891-1907. [PMID: 21573858 DOI: 10.1007/s10661-011-2087-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2010] [Accepted: 04/14/2011] [Indexed: 05/30/2023]
Abstract
The oxides of nitrogen--NO(x) (NO and NO(2))--are an important constituent of the troposphere. The availability of relatively higher spatial (0.25° grid) and temporal (daily) resolution data from ozone monitoring instrument (OMI) onboard Aura helps us to better differentiate between the point sources such as thermal power plants from large cities and rural areas compared to previous sensors. The annual and seasonal (summer and winter) distributions shows very high mean tropospheric NO(2) in specific pockets over India especially over the Indo-Gangetic plains (up to 14.2 × 10(15) molecules/cm(2)). These pockets correspond with the known locations of major thermal power plants. The tropospheric NO(2) over India show a large seasonal variability that is also observed in the ground NO(2) data. The multiple regression analysis show that the influence of a unit of power plant (in gigawatts) over tropospheric NO(2) (×10(15) molecules/cm(2)) is around ten times compared to a unit of population (in millions) over India. The OMI data show that the NO(2) increases by 0.794 ± 0.12 (×10(15) molecules/cm(2); annual) per GW compared to a previous estimate of 0.014 (×10(15) molecules/cm(2)) over India. The increase of tropospheric NO(2) per gigawatt is found to be 1.088 ± 0.18, 0.898 ± 0.14, and 0.395 ± 0.13 (×10(15) molecules/cm(2)) during winter, summer, and monsoon seasons, respectively. The strong seasonal variation is attributed to the enhancement or suppression of NO(2) due to various controlling factors which is discussed here. The recent increasing trend (2005-2007) over rural thermal power plants pockets like Agori and Korba is due to recent large capacity additions in these regions.
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Affiliation(s)
- Anup K Prasad
- School of Earth and Environmental Sciences, Schmid College of Science, Chapman University, Orange, CA 92866, USA.
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32
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Pyle JA, Warwick NJ, Harris NRP, Abas MR, Archibald AT, Ashfold MJ, Ashworth K, Barkley MP, Carver GD, Chance K, Dorsey JR, Fowler D, Gonzi S, Gostlow B, Hewitt CN, Kurosu TP, Lee JD, Langford SB, Mills G, Moller S, MacKenzie AR, Manning AJ, Misztal P, Nadzir MSM, Nemitz E, Newton HM, O'Brien LM, Ong S, Oram D, Palmer PI, Peng LK, Phang SM, Pike R, Pugh TAM, Rahman NA, Robinson AD, Sentian J, Samah AA, Skiba U, Ung HE, Yong SE, Young PJ. The impact of local surface changes in Borneo on atmospheric composition at wider spatial scales: coastal processes, land-use change and air quality. Philos Trans R Soc Lond B Biol Sci 2012; 366:3210-24. [PMID: 22006963 DOI: 10.1098/rstb.2011.0060] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
We present results from the OP3 campaign in Sabah during 2008 that allow us to study the impact of local emission changes over Borneo on atmospheric composition at the regional and wider scale. OP3 constituent data provide an important constraint on model performance. Treatment of boundary layer processes is highlighted as an important area of model uncertainty. Model studies of land-use change confirm earlier work, indicating that further changes to intensive oil palm agriculture in South East Asia, and the tropics in general, could have important impacts on air quality, with the biggest factor being the concomitant changes in NO(x) emissions. With the model scenarios used here, local increases in ozone of around 50 per cent could occur. We also report measurements of short-lived brominated compounds around Sabah suggesting that oceanic (and, especially, coastal) emission sources dominate locally. The concentration of bromine in short-lived halocarbons measured at the surface during OP3 amounted to about 7 ppt, setting an upper limit on the amount of these species that can reach the lower stratosphere.
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Affiliation(s)
- J A Pyle
- National Centre for Atmospheric Science, NCAS, UK.
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Nowlan CR, Liu X, Chance K, Cai Z, Kurosu TP, Lee C, Martin RV. Retrievals of sulfur dioxide from the Global Ozone Monitoring Experiment 2 (GOME-2) using an optimal estimation approach: Algorithm and initial validation. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2011jd015808] [Citation(s) in RCA: 67] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Haqq-Misra J, Kasting JF, Lee S. Availability of O(2) and H(2)O(2) on pre-photosynthetic Earth. ASTROBIOLOGY 2011; 11:293-302. [PMID: 21545266 PMCID: PMC3097080 DOI: 10.1089/ast.2010.0572] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Old arguments that free O(2) must have been available at Earth's surface prior to the origin of photosynthesis have been revived by a new study that shows that aerobic respiration can occur at dissolved oxygen concentrations much lower than had previously been thought, perhaps as low as 0.05 nM, which corresponds to a partial pressure for O(2) of about 4 × 10(-8) bar. We used numerical models to study whether such O(2) concentrations might have been provided by atmospheric photochemistry. Results show that disproportionation of H(2)O(2) near the surface might have yielded enough O(2) to satisfy this constraint. Alternatively, poleward transport of O(2) from the equatorial stratosphere into the polar night region, followed by downward transport in the polar vortex, may have brought O(2) directly to the surface. Thus, our calculations indicate that this "early respiration" hypothesis might be physically reasonable.
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Affiliation(s)
- Jacob Haqq-Misra
- Department of Meteorology, The Pennsylvania State University, University Park, PA 16802, USA.
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Dirksen RJ, Boersma KF, Eskes HJ, Ionov DV, Bucsela EJ, Levelt PF, Kelder HM. Evaluation of stratospheric NO2retrieved from the Ozone Monitoring Instrument: Intercomparison, diurnal cycle, and trending. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2010jd014943] [Citation(s) in RCA: 81] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Bucsela EJ, Pickering KE, Huntemann TL, Cohen RC, Perring A, Gleason JF, Blakeslee RJ, Albrecht RI, Holzworth R, Cipriani JP, Vargas-Navarro D, Mora-Segura I, Pacheco-Hernández A, Laporte-Molina S. Lightning-generated NOxseen by the Ozone Monitoring Instrument during NASA's Tropical Composition, Cloud and Climate Coupling Experiment (TC4). ACTA ACUST UNITED AC 2010. [DOI: 10.1029/2009jd013118] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Rivera C, Mellqvist J, Samuelsson J, Lefer B, Alvarez S, Patel MR. Quantification of NO2and SO2emissions from the Houston Ship Channel and Texas City industrial areas during the 2006 Texas Air Quality Study. ACTA ACUST UNITED AC 2010. [DOI: 10.1029/2009jd012675] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Lamsal LN, Martin RV, van Donkelaar A, Celarier EA, Bucsela EJ, Boersma KF, Dirksen R, Luo C, Wang Y. Indirect validation of tropospheric nitrogen dioxide retrieved from the OMI satellite instrument: Insight into the seasonal variation of nitrogen oxides at northern midlatitudes. ACTA ACUST UNITED AC 2010. [DOI: 10.1029/2009jd013351] [Citation(s) in RCA: 183] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Hains JC, Boersma KF, Kroon M, Dirksen RJ, Cohen RC, Perring AE, Bucsela E, Volten H, Swart DPJ, Richter A, Wittrock F, Schoenhardt A, Wagner T, Ibrahim OW, van Roozendael M, Pinardi G, Gleason JF, Veefkind JP, Levelt P. Testing and improving OMI DOMINO tropospheric NO2using observations from the DANDELIONS and INTEX-B validation campaigns. ACTA ACUST UNITED AC 2010. [DOI: 10.1029/2009jd012399] [Citation(s) in RCA: 89] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Lee C, Martin RV, van Donkelaar A, O'Byrne G, Krotkov N, Richter A, Huey LG, Holloway JS. Retrieval of vertical columns of sulfur dioxide from SCIAMACHY and OMI: Air mass factor algorithm development, validation, and error analysis. ACTA ACUST UNITED AC 2009. [DOI: 10.1029/2009jd012123] [Citation(s) in RCA: 94] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Kaynak B, Hu Y, Martin RV, Sioris CE, Russell AG. Comparison of weekly cycle of NO2satellite retrievals and NOxemission inventories for the continental United States. ACTA ACUST UNITED AC 2009. [DOI: 10.1029/2008jd010714] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Choi Y, Wang Y, Zeng T, Cunnold D, Yang ES, Martin R, Chance K, Thouret V, Edgerton E. Springtime transitions of NO2, CO, and O3over North America: Model evaluation and analysis. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2007jd009632] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Ghude SD, Fadnavis S, Beig G, Polade SD, van der A RJ. Detection of surface emission hot spots, trends, and seasonal cycle from satellite-retrieved NO2over India. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2007jd009615] [Citation(s) in RCA: 117] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Barkley MP, Palmer PI, Kuhn U, Kesselmeier J, Chance K, Kurosu TP, Martin RV, Helmig D, Guenther A. Net ecosystem fluxes of isoprene over tropical South America inferred from Global Ozone Monitoring Experiment (GOME) observations of HCHO columns. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2008jd009863] [Citation(s) in RCA: 88] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Kleipool QL, Dobber MR, de Haan JF, Levelt PF. Earth surface reflectance climatology from 3 years of OMI data. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2008jd010290] [Citation(s) in RCA: 216] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Lamsal LN, Martin RV, van Donkelaar A, Steinbacher M, Celarier EA, Bucsela E, Dunlea EJ, Pinto JP. Ground-level nitrogen dioxide concentrations inferred from the satellite-borne Ozone Monitoring Instrument. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2007jd009235] [Citation(s) in RCA: 247] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Wagner T, Beirle S, Deutschmann T, Eigemeier E, Frankenberg C, Grzegorski M, Liu C, Marbach T, Platt U, Penning de Vries M. Monitoring of atmospheric trace gases, clouds, aerosols and surface properties from UV/vis/NIR satellite instruments. ACTA ACUST UNITED AC 2008. [DOI: 10.1088/1464-4258/10/10/104019] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Kramer LJ, Leigh RJ, Remedios JJ, Monks PS. Comparison of OMI and ground-based in situ and MAX-DOAS measurements of tropospheric nitrogen dioxide in an urban area. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2007jd009168] [Citation(s) in RCA: 63] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Bucsela EJ, Perring AE, Cohen RC, Boersma KF, Celarier EA, Gleason JF, Wenig MO, Bertram TH, Wooldridge PJ, Dirksen R, Veefkind JP. Comparison of tropospheric NO2from in situ aircraft measurements with near-real-time and standard product data from OMI. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2007jd008838] [Citation(s) in RCA: 109] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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van der A RJ, Eskes HJ, Boersma KF, van Noije TPC, Van Roozendael M, De Smedt I, Peters DHMU, Meijer EW. Trends, seasonal variability and dominant NOxsource derived from a ten year record of NO2measured from space. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2007jd009021] [Citation(s) in RCA: 288] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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