Articles | Volume 21, issue 17
https://doi.org/10.5194/acp-21-13311-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-13311-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Sep 2021
Research article |
| 08 Sep 2021
| 08 Sep 2021
A satellite-data-driven framework to rapidly quantify air-basin-scale NOx emissions and its application to the Po Valley during the COVID-19 pandemic
Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, NY, USA
Research and Education in Energy, Environment and Water Institute, University at Buffalo, Buffalo, NY, USA
Lingbo Li
Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, NY, USA
Shruti Jagini
Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, NY, USA
Department of Earth and Environment, Boston University, Boston, MA, USA
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Christopher Chan Miller, Sébastien Roche, Jonas Wilzweski, Xiong Liu, Kelly V. Chance, Bingkun Luo, Kang Sun, Jonathan E. Franklin, Joshua S. Benmergui, Maya Nasr, David J. Miller, Sean Crowell, Nathan Leisso, Eleanor Walker, Ritesh Gautam, Nicholas LoFaso, Sasha Ayvazov, David Wells, Carlos Cervantes, Christopher Hairfield, and Steven Wofsy
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This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Reducing oil and gas methane emissions is among the fastest ways to slow near-term climate change, and satellites offer a transparent means of verifying progress. MethaneSAT fills a gap between existing instruments, which either measure methane accurately but at coarse scales, or detect large leaks at fine resolution without the accuracy to account for all sources. We present the first measurements and show they meet the accuracy requirements for regional emissions mapping at the 2–4 km2 scale.
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Atmos. Meas. Tech., 17, 4109–4120, https://doi.org/10.5194/amt-17-4109-2024, https://doi.org/10.5194/amt-17-4109-2024, 2024
Short summary
Short summary
Using data collected from three levels of a 62 m tower, we found that both the temperature variances and sensible heat flux obtained from sonic anemometers are consistently lower, by a few percent, compared to those from fine-wire thermocouples.
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Atmos. Chem. Phys., 24, 7793–7813, https://doi.org/10.5194/acp-24-7793-2024, https://doi.org/10.5194/acp-24-7793-2024, 2024
Short summary
Short summary
In contrast with past work showing that the reduction of emissions was the dominant factor for the nationwide increase of surface O3 during the lockdown in China, this study finds that the variation in meteorology (temperature and other parameters) plays a more important role. This result is obtained through sensitivity simulations using a chemical transport model constrained by satellite (TROPOMI) data and calibrated with surface observations.
Eamon K. Conway, Amir H. Souri, Joshua Benmergui, Kang Sun, Xiong Liu, Carly Staebell, Christopher Chan Miller, Jonathan Franklin, Jenna Samra, Jonas Wilzewski, Sebastien Roche, Bingkun Luo, Apisada Chulakadabba, Maryann Sargent, Jacob Hohl, Bruce Daube, Iouli Gordon, Kelly Chance, and Steven Wofsy
Atmos. Meas. Tech., 17, 1347–1362, https://doi.org/10.5194/amt-17-1347-2024, https://doi.org/10.5194/amt-17-1347-2024, 2024
Short summary
Short summary
The work presented here describes the processes required to convert raw sensor data for the MethaneAIR instrument to geometrically calibrated data. Each algorithm is described in detail. MethaneAIR is the airborne simulator for MethaneSAT, a new satellite under development by MethaneSAT LLC, a subsidiary of the EDF. MethaneSAT's goals are to precisely map over 80 % of the production sources of methane emissions from oil and gas fields across the globe to a high degree of accuracy.
Karen E. Cady-Pereira, Xuehui Guo, Rui Wang, April B. Leytem, Chase Calkins, Elizabeth Berry, Kang Sun, Markus Müller, Armin Wisthaler, Vivienne H. Payne, Mark W. Shephard, Mark A. Zondlo, and Valentin Kantchev
Atmos. Meas. Tech., 17, 15–36, https://doi.org/10.5194/amt-17-15-2024, https://doi.org/10.5194/amt-17-15-2024, 2024
Short summary
Short summary
Ammonia is a significant precursor of PM2.5 particles and thus contributes to poor air quality in many regions. Furthermore, ammonia concentrations are rising due to the increase of large-scale, intensive agricultural activities. Here we evaluate satellite measurements of ammonia against aircraft and surface network data, and show that there are differences in magnitude, but the satellite data are spatially and temporally well correlated with the in situ data.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
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Short summary
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We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
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Ammonia (NH3) is a key precursor for fine particulate matter (PM2.5) and a primary form of reactive nitrogen, yet it has sparse ground measurements. We perform the first comprehensive comparison between ground observations and satellite retrievals in the US, demonstrating that satellite NH3 data can help fill spatial gaps in the current ground monitoring networks. Trend analyses using both datasets highlight increasing NH3 trends across the US, including the NH3 hotspots and urban areas.
Chantelle R. Lonsdale and Kang Sun
Atmos. Chem. Phys., 23, 8727–8748, https://doi.org/10.5194/acp-23-8727-2023, https://doi.org/10.5194/acp-23-8727-2023, 2023
Short summary
Short summary
The COVID-19 pandemic, which was caused by the SARS-CoV-2 virus, emerged in 2019, and its still evolving variants have resulted in unprecedented shifts in human activities and anthropogenic emissions into the Earth's atmosphere. We present monthly nitrogen oxide emissions over three major continents from May 2018 to January 2023 to capture variations before and after the COVID-19 pandemic. We focus on a diverse collection of 54 cities to quantify the post-COVID-19 perturbations.
Huiqun Wang, Gonzalo González Abad, Chris Chan Miller, Hyeong-Ahn Kwon, Caroline R. Nowlan, Zolal Ayazpour, Heesung Chong, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Kang Sun, Robert Spurr, and Robert J. Hargreaves
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-66, https://doi.org/10.5194/amt-2023-66, 2023
Preprint withdrawn
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A pipeline for retrieving Total Column Water Vapor from satellite blue spectra is developed. New constraints are considered. Water-leaving radiance is important over the oceans. Results agree with reference datasets well under clear conditions. Due to high sensitivity to clouds, strict data filtering criteria are required. All-sky retrievals can be corrected using machine learning. GPS stations’ representation errors follow a power law relationship with grid resolutions.
Zolal Ayazpour, Shiqi Tao, Dan Li, Amy Jo Scarino, Ralph E. Kuehn, and Kang Sun
Atmos. Meas. Tech., 16, 563–580, https://doi.org/10.5194/amt-16-563-2023, https://doi.org/10.5194/amt-16-563-2023, 2023
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Accurate knowledge of the planetary boundary layer height (PBLH) is essential to study air pollution. However, PBLH observations are sparse in space and time, and PBLHs used in atmospheric models are often inaccurate. Using PBLH observations from the Aircraft Meteorological DAta Relay (AMDAR), we present a machine learning framework to produce a spatially complete PBLH product over the contiguous US that shows a better agreement with reference PBLH observations than commonly used PBLH products.
Kang Sun, Mahdi Yousefi, Christopher Chan Miller, Kelly Chance, Gonzalo González Abad, Iouli E. Gordon, Xiong Liu, Ewan O'Sullivan, Christopher E. Sioris, and Steven C. Wofsy
Atmos. Meas. Tech., 15, 3721–3745, https://doi.org/10.5194/amt-15-3721-2022, https://doi.org/10.5194/amt-15-3721-2022, 2022
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This study of upper atmospheric airglow from oxygen is motivated by the need to measure oxygen simultaneously with methane and CO2 in satellite remote sensing. We provide an accurate understanding of the spatial, temporal, and spectral distribution of airglow emissions, which will help in the satellite remote sensing of greenhouse gases and constraining the chemical and physical processes in the upper atmosphere.
Amir H. Souri, Kelly Chance, Kang Sun, Xiong Liu, and Matthew S. Johnson
Atmos. Meas. Tech., 15, 41–59, https://doi.org/10.5194/amt-15-41-2022, https://doi.org/10.5194/amt-15-41-2022, 2022
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The central component of satellite and model validation is pointwise measurements. A point is an element of space, whereas satellite (model) pixels represent an averaged area. These two datasets are inherently different. We leveraged some geostatistical tools to transform discrete points to gridded data with quantified uncertainty, comparable to satellite footprint (and response functions). This in part alleviated some complications concerning point–pixel comparisons.
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Short summary
We bridge the gap between satellite column observations and emissions by accounting for the dynamic lifetime of pollutants due to wind dispersion and the chemical lifetime due to chemical reactions. Applying it to the Po Valley air basin, we derive the monthly emissions of nitrogen oxides using satellite nitrogen dioxide observations. We further quantify the COVID-19-driven decline of emissions and estimate a 22 % decrease in nitrogen oxide emissions due to the pandemic in 2020.
We bridge the gap between satellite column observations and emissions by accounting for the...
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