Melissa Payer Sulprizio
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Melissa Payer Sulprizio has a total of 122 co-authors. Here are the top co-authors by number of shared publications:
- Daniel J. Varon
Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, Cambridge, Massachusetts, 02139, United States
7 shared publications Daniel J. Jacob
Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA USA
6 shared publications- James D. East
Harvard University, School of Engineering and Applied Sciences, Cambridge, MA, 02138, USA
5 shared publications - John Worden
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
5 shared publications - Nicholas Balasus
John A. Paulson School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, 02134, United States
5 shared publications - Robert M. Yantosca
School of Engineering and Applied Sciences Harvard University Cambridge MA USA
4 shared publications
Latest Publications
- Top Cited PapersOpen Access
- 10 April 2026
- Published by American Association for the Advancement of Science (AAAS) in Science Advances
- Vol. 12 (15) , eadz9007
Attributing 2019–2024 methane growth using TROPOMI satellite observations
Atmospheric methane concentrations increased at a rate of 0.7% year −1 over 2019–2024, but the causes are unclear. We conducted an analytical inversion of bias-corrected TROPOspheric Monitoring Instrument (TROPOMI) satellite observations to quantify 2019–2024 annual mean methane emissions and hemispheric OH concentrations. We find that the methane rise from 2019 to 2024 reflects an approach to steady state between 2019 sources and sinks (59% of the rise), augmented by increasing emissions (25%) and decreasing OH concentrations (16%). Global emissions increased from 571 teragrams (Tg) per year in 2019 to 601 Tg per year in 2021 and back to 575 Tg per year in 2024. 2019–2024 emission decreases from oil/gas and rice were offset by increases from livestock and waste. East Africa and South America were most responsible for the 2019–2024 increase in emissions. The weaker methane rise over 2022–2024 was driven mostly by increasing OH concentrations rather than decreasing emissions.
- 10 April 2026
- Published by American Association for the Advancement of Science (AAAS) in Science Advances
- Vol. 12 (15) , eadz9007
Top Cited PapersOpen AccessAttributing 2019–2024 methane growth using TROPOMI satellite observations
Atmospheric methane concentrations increased at a rate of 0.7% year −1 over 2019–2024, but the causes are unclear. We conducted an analytical inversion of bias-corrected TROPOspheric Monitoring Instrument (TROPOMI) satellite observations to quantify 2019–2024 annual mean methane emissions and hemispheric OH concentrations. We find that the methane rise from 2019 to 2024 reflects an approach to steady state between 2019 sources and sinks (59% of the rise), augmented by increasing emissions (25%) and decreasing OH concentrations (16%). Global emissions increased from 571 teragrams (Tg) per year in 2019 to 601 Tg per year in 2021 and back to 575 Tg per year in 2024. 2019–2024 emission decreases from oil/gas and rice were offset by increases from livestock and waste. East Africa and South America were most responsible for the 2019–2024 increase in emissions. The weaker methane rise over 2022–2024 was driven mostly by increasing OH concentrations rather than decreasing emissions.
- Top Cited PapersOpen Access
- 27 March 2026
- Published by American Association for the Advancement of Science (AAAS) in Science Advances
- Vol. 12 (13) , eadz9308
Quantifying urban and landfill methane emissions in the United States using TROPOMI satellite data
Urban areas are major sources of population-driven methane with high potential for mitigation, but emission quantification and sectoral attribution remain uncertain. Using satellite observations and a high-resolution (12 kilometers by 12 kilometers) atmospheric inversion framework, we find that emissions from 12 major US urban areas are 80% higher than the US Environmental Protection Agency Greenhouse Gas Inventory (EPA GHGI), with up to four times higher emissions in Houston but 32 to 37% lower emissions in Los Angeles and Cincinnati. Landfills are the principal cause of inventory underestimates, with city-level management practices driving large variations in per capita emissions. Examination of individual landfills with gas collection systems shows gas collection efficiencies averaging 38% (range: 5 to 90%), much lower than their reported average of 70% (range: 40 to 87%). An exception is Los Angeles, where we find landfill gas collection averaging 85%, suggesting large urban methane mitigation potential through improved landfill management.
- 27 March 2026
- Published by American Association for the Advancement of Science (AAAS) in Science Advances
- Vol. 12 (13) , eadz9308
Top Cited PapersOpen AccessQuantifying urban and landfill methane emissions in the United States using TROPOMI satellite data
Urban areas are major sources of population-driven methane with high potential for mitigation, but emission quantification and sectoral attribution remain uncertain. Using satellite observations and a high-resolution (12 kilometers by 12 kilometers) atmospheric inversion framework, we find that emissions from 12 major US urban areas are 80% higher than the US Environmental Protection Agency Greenhouse Gas Inventory (EPA GHGI), with up to four times higher emissions in Houston but 32 to 37% lower emissions in Los Angeles and Cincinnati. Landfills are the principal cause of inventory underestimates, with city-level management practices driving large variations in per capita emissions. Examination of individual landfills with gas collection systems shows gas collection efficiencies averaging 38% (range: 5 to 90%), much lower than their reported average of 70% (range: 40 to 87%). An exception is Los Angeles, where we find landfill gas collection averaging 85%, suggesting large urban methane mitigation potential through improved landfill management.
- Open Access
- 11 December 2025
- Published by Springer Nature in Nature Communications
- Vol. 16 (1) , 11004
Worldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates
Meeting climate policy goals to reduce methane emissions under the Paris Agreement and the Global Methane Pledge requires nations to set targets and quantify reductions. Individual countries report emissions by sector to the United Nations Framework Convention on Climate Change (UNFCCC) but there are large uncertainties. Here we optimize 2023 national emissions at up to 25 km grid resolution for 161 countries with a globally consistent open-source framework for inverse analysis of Tropospheric Monitoring Instrument (TROPOMI) satellite observations, using UNFCCC reports for prior estimates together with point source information from GHGSat and other satellites. We find global anthropogenic emissions to be 15% higher than UNFCCC reporting (32% for oil-gas), with national emissions more than 50% higher than reporting for a quarter of the countries. Oil-gas emission intensities vary by two orders of magnitude between countries. Sub-Saharan Africa has the highest livestock emission intensity of any region. Hydroelectric reservoirs, generally not included in UNFCCC reporting, contribute 6% of anthropogenic emissions globally. The framework allows updates for subsequent years, enabling monitoring of emission trends and support for improved reporting.
- 11 December 2025
- Published by Springer Nature in Nature Communications
- Vol. 16 (1) , 11004
Open AccessWorldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates
Meeting climate policy goals to reduce methane emissions under the Paris Agreement and the Global Methane Pledge requires nations to set targets and quantify reductions. Individual countries report emissions by sector to the United Nations Framework Convention on Climate Change (UNFCCC) but there are large uncertainties. Here we optimize 2023 national emissions at up to 25 km grid resolution for 161 countries with a globally consistent open-source framework for inverse analysis of Tropospheric Monitoring Instrument (TROPOMI) satellite observations, using UNFCCC reports for prior estimates together with point source information from GHGSat and other satellites. We find global anthropogenic emissions to be 15% higher than UNFCCC reporting (32% for oil-gas), with national emissions more than 50% higher than reporting for a quarter of the countries. Oil-gas emission intensities vary by two orders of magnitude between countries. Sub-Saharan Africa has the highest livestock emission intensity of any region. Hydroelectric reservoirs, generally not included in UNFCCC reporting, contribute 6% of anthropogenic emissions globally. The framework allows updates for subsequent years, enabling monitoring of emission trends and support for improved reporting.
- Open Access
- 14 October 2024
- Published by American Geophysical Union (AGU) in Journal of Advances in Modeling Earth Systems
- Vol. 16 (10)
Toward Fine Horizontal Resolution Global Simulations of Aerosol Sectional Microphysics: Advances Enabled by GCHP‐TOMAS
Global modeling of aerosol‐particle number and size is important for understanding aerosol effects on Earth's climate and air quality. Fine‐resolution global models are desirable for representing nonlinear aerosol‐microphysical processes, their nonlinear interactions with dynamics and chemistry, and spatial heterogeneity. However, aerosol‐microphysical simulations are computationally demanding, which can limit the achievable global horizontal resolution. Here, we present the first coupling of the TwO‐Moment Aerosol Sectional (TOMAS) microphysics scheme with the High‐Performance configuration of the GEOS‐Chem model of atmospheric composition (GCHP), a coupling termed GCHP‐TOMAS. GCHP's architecture allows massively parallel GCHP‐TOMAS simulations including on the cloud, using hundreds of computing cores, faster runtimes, more memory, and finer global horizontal resolution (e.g., 25 km × 25 km, 7.8 × 105 model columns) versus the previous single‐node capability of GEOS‐Chem‐TOMAS (tens of cores, 200 km × 250 km, 1.3 × 104 model columns). GCHP‐TOMAS runtimes have near‐ideal scalability with computing‐core number. Simulated global‐mean number concentrations increase (dominated by free‐tropospheric over‐ocean sub‐10‐nm‐diameter particles) toward finer GCHP‐TOMAS horizontal resolution. Increasing the horizontal resolution from 200 km × 200–50 km × 50 km increases the global monthly mean free‐tropospheric total particle number by 18.5%, and over‐ocean sub‐10‐nm‐diameter particles by 39.8% at 4‐km altitude. With a cascade of contributing factors, free‐tropospheric particle‐precursor concentrations increase (32.6% at 4‐km altitude) with resolution, promoting new‐particle formation and growth that outweigh coagulation changes. These nonlinear effects have the potential to revise current understanding of processes controlling global aerosol number and aerosol impacts on Earth's climate and air quality.
- 14 October 2024
- Published by American Geophysical Union (AGU) in Journal of Advances in Modeling Earth Systems
- Vol. 16 (10)
Open AccessToward Fine Horizontal Resolution Global Simulations of Aerosol Sectional Microphysics: Advances Enabled by GCHP‐TOMAS
Global modeling of aerosol‐particle number and size is important for understanding aerosol effects on Earth's climate and air quality. Fine‐resolution global models are desirable for representing nonlinear aerosol‐microphysical processes, their nonlinear interactions with dynamics and chemistry, and spatial heterogeneity. However, aerosol‐microphysical simulations are computationally demanding, which can limit the achievable global horizontal resolution. Here, we present the first coupling of the TwO‐Moment Aerosol Sectional (TOMAS) microphysics scheme with the High‐Performance configuration of the GEOS‐Chem model of atmospheric composition (GCHP), a coupling termed GCHP‐TOMAS. GCHP's architecture allows massively parallel GCHP‐TOMAS simulations including on the cloud, using hundreds of computing cores, faster runtimes, more memory, and finer global horizontal resolution (e.g., 25 km × 25 km, 7.8 × 105 model columns) versus the previous single‐node capability of GEOS‐Chem‐TOMAS (tens of cores, 200 km × 250 km, 1.3 × 104 model columns). GCHP‐TOMAS runtimes have near‐ideal scalability with computing‐core number. Simulated global‐mean number concentrations increase (dominated by free‐tropospheric over‐ocean sub‐10‐nm‐diameter particles) toward finer GCHP‐TOMAS horizontal resolution. Increasing the horizontal resolution from 200 km × 200–50 km × 50 km increases the global monthly mean free‐tropospheric total particle number by 18.5%, and over‐ocean sub‐10‐nm‐diameter particles by 39.8% at 4‐km altitude. With a cascade of contributing factors, free‐tropospheric particle‐precursor concentrations increase (32.6% at 4‐km altitude) with resolution, promoting new‐particle formation and growth that outweigh coagulation changes. These nonlinear effects have the potential to revise current understanding of processes controlling global aerosol number and aerosol impacts on Earth's climate and air quality.
- Top Cited PapersOpen Access
- 15 May 2024
- Published by American Geophysical Union (AGU) in Geophysical Research Letters
- Vol. 51 (10)
Interpreting the Seasonality of Atmospheric Methane
Surface and satellite observations of atmospheric methane show smooth seasonal behavior in the Southern Hemisphere driven by loss from the hydroxyl (OH) radical. However, observations in the Northern Hemisphere show a sharp mid‐summer increase that is asymmetric with the Southern Hemisphere and not captured by the default configuration of the GEOS‐Chem chemical transport model. Using an ensemble of 22 OH model estimates and 24 wetland emission inventories in GEOS‐Chem, we show that the magnitude, latitudinal distribution, and seasonality of Northern Hemisphere wetland emissions are critical for reproducing the observed seasonality of methane in that hemisphere, with the interhemispheric OH ratio playing a lesser role. Reproducing the observed seasonality requires a wetland emission inventory with ∼80 Tg a−1 poleward of 10°N including significant emissions in South Asia, and an August peak in boreal emissions persisting into autumn. In our 24‐member wetland emission ensemble, only the LPJ‐wsl MERRA‐2 inventory has these attributes.
- 15 May 2024
- Published by American Geophysical Union (AGU) in Geophysical Research Letters
- Vol. 51 (10)
Top Cited PapersOpen AccessInterpreting the Seasonality of Atmospheric Methane
Surface and satellite observations of atmospheric methane show smooth seasonal behavior in the Southern Hemisphere driven by loss from the hydroxyl (OH) radical. However, observations in the Northern Hemisphere show a sharp mid‐summer increase that is asymmetric with the Southern Hemisphere and not captured by the default configuration of the GEOS‐Chem chemical transport model. Using an ensemble of 22 OH model estimates and 24 wetland emission inventories in GEOS‐Chem, we show that the magnitude, latitudinal distribution, and seasonality of Northern Hemisphere wetland emissions are critical for reproducing the observed seasonality of methane in that hemisphere, with the interhemispheric OH ratio playing a lesser role. Reproducing the observed seasonality requires a wetland emission inventory with ∼80 Tg a−1 poleward of 10°N including significant emissions in South Asia, and an August peak in boreal emissions persisting into autumn. In our 24‐member wetland emission ensemble, only the LPJ‐wsl MERRA‐2 inventory has these attributes.
- Open Access
- 2 February 2024
- Published by Wiley
Interpreting the seasonality of atmospheric methane
Surface and satellite observations of atmospheric methane show smooth seasonal behavior in the Southern Hemisphere driven by loss from the hydroxyl (OH) radical. However, observations in the Northern Hemisphere show a sharp mid-summer increase that is asymmetric with the Southern Hemisphere and not captured by the default configuration of the GEOS-Chem chemical transport model. Using an ensemble of 22 OH model estimates and 24 wetland emission inventories in GEOS-Chem, we show that the magnitude, latitudinal distribution, and seasonality of Northern Hemisphere wetland emissions are critical for reproducing the observed seasonality of methane in that hemisphere, with the interhemispheric OH ratio playing a lesser role. Reproducing the observed seasonality requires a wetland emission inventory with ~80 Tg a-1 poleward of 10°N including significant emissions in South Asia, and an August peak in boreal emissions persisting into autumn. In our 24-member wetland emission ensemble, only the LPJ-wsl MERRA-2 inventory has these attributes.
- 2 February 2024
- Published by Wiley
Open AccessInterpreting the seasonality of atmospheric methane
Surface and satellite observations of atmospheric methane show smooth seasonal behavior in the Southern Hemisphere driven by loss from the hydroxyl (OH) radical. However, observations in the Northern Hemisphere show a sharp mid-summer increase that is asymmetric with the Southern Hemisphere and not captured by the default configuration of the GEOS-Chem chemical transport model. Using an ensemble of 22 OH model estimates and 24 wetland emission inventories in GEOS-Chem, we show that the magnitude, latitudinal distribution, and seasonality of Northern Hemisphere wetland emissions are critical for reproducing the observed seasonality of methane in that hemisphere, with the interhemispheric OH ratio playing a lesser role. Reproducing the observed seasonality requires a wetland emission inventory with ~80 Tg a-1 poleward of 10°N including significant emissions in South Asia, and an August peak in boreal emissions persisting into autumn. In our 24-member wetland emission ensemble, only the LPJ-wsl MERRA-2 inventory has these attributes.
- Open Access
- 24 August 2022
- Published by American Geophysical Union (AGU) in Journal of Geophysical Research: Biogeosciences
- Vol. 127 (8)
Estimating Drivers and Pathways for Hydroelectric Reservoir Methane Emissions Using a New Mechanistic Model
Hydroelectric reservoirs can emit significant quantities of methane, particularly through degassing at turbine outlets. Improved understanding of processes affecting hydroelectric reservoir CH4 emissions is thus important as the world economy transitions to renewable forms of energy production. Here we develop and evaluate a new mechanistic model of CH4 emissions: ResME ([Res]ervoir [M]ethane [E]missions), which estimates carbon inputs and methanogenesis to predict CH4 release via ebullition and diffusion, plant emissions, and downstream emissions. ResME results demonstrate that the relative importance of allochthonous and autochthonous carbon input to methane emissions varies by latitude, with allochthonous carbon contributions typically being higher in tropical reservoirs. Results also demonstrate that total reservoir emissions are highly dependent on turbine intake depths, which are not typically reported. Potential maximum degassing emissions from existing hydroelectric reservoirs are estimated as 11 ± 4 Tg C/yr, if all reservoirs had deep turbine intakes and stratified for 5 months per year. In comparison, the estimated diffusive, ebullitive, and plant CH4 emissions are estimated to be 2.8 ± 0.2 Tg C/yr (where the true uncertainty is much higher than the model standard error). Future work should focus on improving estimates of reservoir carbon inputs and decomposition rates, as well as surveying turbine intake depths. Satellite measurements from missions such as TROPOMI may also help constrain hydropower methane emissions.
- 24 August 2022
- Published by American Geophysical Union (AGU) in Journal of Geophysical Research: Biogeosciences
- Vol. 127 (8)
Open AccessEstimating Drivers and Pathways for Hydroelectric Reservoir Methane Emissions Using a New Mechanistic Model
Hydroelectric reservoirs can emit significant quantities of methane, particularly through degassing at turbine outlets. Improved understanding of processes affecting hydroelectric reservoir CH4 emissions is thus important as the world economy transitions to renewable forms of energy production. Here we develop and evaluate a new mechanistic model of CH4 emissions: ResME ([Res]ervoir [M]ethane [E]missions), which estimates carbon inputs and methanogenesis to predict CH4 release via ebullition and diffusion, plant emissions, and downstream emissions. ResME results demonstrate that the relative importance of allochthonous and autochthonous carbon input to methane emissions varies by latitude, with allochthonous carbon contributions typically being higher in tropical reservoirs. Results also demonstrate that total reservoir emissions are highly dependent on turbine intake depths, which are not typically reported. Potential maximum degassing emissions from existing hydroelectric reservoirs are estimated as 11 ± 4 Tg C/yr, if all reservoirs had deep turbine intakes and stratified for 5 months per year. In comparison, the estimated diffusive, ebullitive, and plant CH4 emissions are estimated to be 2.8 ± 0.2 Tg C/yr (where the true uncertainty is much higher than the model standard error). Future work should focus on improving estimates of reservoir carbon inputs and decomposition rates, as well as surveying turbine intake depths. Satellite measurements from missions such as TROPOMI may also help constrain hydropower methane emissions.
- Open Access
- 22 June 2022
- Published by American Geophysical Union (AGU) in Journal of Advances in Modeling Earth Systems
- Vol. 14 (6)
An Online‐Learned Neural Network Chemical Solver for Stable Long‐Term Global Simulations of Atmospheric Chemistry
A major computational barrier in global modeling of atmospheric chemistry is the numerical integration of the coupled kinetic equations describing the chemical mechanism. Machine‐learned (ML) solvers can offer order of magnitude speedup relative to conventional implicit solvers but past implementations have suffered from fast error growth and only run for short simulation times (x under remote conditions where chemical aging leads to error accumulation. These regional biases remain a major limitation for practical application, and ML emulation would be more difficult in a more complex mechanism.
- 22 June 2022
- Published by American Geophysical Union (AGU) in Journal of Advances in Modeling Earth Systems
- Vol. 14 (6)
Open AccessAn Online‐Learned Neural Network Chemical Solver for Stable Long‐Term Global Simulations of Atmospheric Chemistry
A major computational barrier in global modeling of atmospheric chemistry is the numerical integration of the coupled kinetic equations describing the chemical mechanism. Machine‐learned (ML) solvers can offer order of magnitude speedup relative to conventional implicit solvers but past implementations have suffered from fast error growth and only run for short simulation times (x under remote conditions where chemical aging leads to error accumulation. These regional biases remain a major limitation for practical application, and ML emulation would be more difficult in a more complex mechanism.
- Top Cited PapersOpen Access
- 2 July 2021
- Published by American Association for the Advancement of Science (AAAS) in Science Advances
- Vol. 7 (27) , eabf4507
Satellite-based survey of extreme methane emissions in the Permian basin
Industrial emissions play a major role in the global methane budget. The Permian basin is thought to be responsible for almost half of the methane emissions from all U.S. oil- and gas-producing regions, but little is known about individual contributors, a prerequisite for mitigation. We use a new class of satellite measurements acquired during several days in 2019 and 2020 to perform the first regional-scale and high-resolution survey of methane sources in the Permian. We find an unexpectedly large number of extreme point sources (37 plumes with emission rates >500 kg hour−1), which account for a range between 31 and 53% of the estimated emissions in the sampled area. Our analysis reveals that new facilities are major emitters in the area, often due to inefficient flaring operations (20% of detections). These results put current practices into question and are relevant to guide emission reduction efforts.
- 2 July 2021
- Published by American Association for the Advancement of Science (AAAS) in Science Advances
- Vol. 7 (27) , eabf4507
Top Cited PapersOpen AccessSatellite-based survey of extreme methane emissions in the Permian basin
Industrial emissions play a major role in the global methane budget. The Permian basin is thought to be responsible for almost half of the methane emissions from all U.S. oil- and gas-producing regions, but little is known about individual contributors, a prerequisite for mitigation. We use a new class of satellite measurements acquired during several days in 2019 and 2020 to perform the first regional-scale and high-resolution survey of methane sources in the Permian. We find an unexpectedly large number of extreme point sources (37 plumes with emission rates >500 kg hour−1), which account for a range between 31 and 53% of the estimated emissions in the sampled area. Our analysis reveals that new facilities are major emitters in the area, often due to inefficient flaring operations (20% of detections). These results put current practices into question and are relevant to guide emission reduction efforts.