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Urban regions emit a large fraction of anthropogenic emissions of greenhouse gases (GHG) such as carbon dioxide (CO2) and methane (CH4) that contribute to modern-day climate change. As such, a growing number of urban policymakers and stakeholders are adopting emission reduction targets and implementing policies to reach those targets. Over the past two decades research teams have established urban GHG monitoring networks to determine how much, where, and why a particular city emits GHGs, and to track changes in emissions over time. Coordination among these efforts has been limited, restricting the scope of analyses and insights. Here we present a harmonized data set synthesizing urban GHG observations from cities with monitoring networks across North America that will facilitate cross-city analyses and address scientific questions that are difficult to address in isolation.

The purpose of this study is to determine whether urban greenhouse gas (GHG) fluxes can be quantified from tower-based mole fraction measurements using Monin–Obukhov similarity theory (MOST). Tower-based GHG mole fraction networks are used in many cities to quantify whole-city GHG emissions. Local-scale, micrometeorological flux estimates would complement whole-city estimates from atmospheric inversions. CO2 mole fraction and eddy-covariance flux data at an urban site in Indianapolis, Indiana, from October 2020 through January 2022 are analyzed. Using MOST flux–variance and flux–gradient relationships, CO2 fluxes were calculated using these mole fraction data and compared to the eddy-covariance fluxes. MOST-based fluxes were calculated using varying measurement heights and methods of estimating stability. The MOST flux–variance relationship method showed good temporal correlation with eddy-covariance fluxes at this site but overestimated flux magnitudes. Fluxes calculated using flux–gradient relationships showed lower temporal correlation with eddy-covariance fluxes but closer magnitudes to eddy-covariance fluxes. Measurement heights closer to ground level produce more precise flux estimates for both MOST-based methods. For flux–gradient methods, flux estimates are more accurate and precise when low-altitude measurements are combined with a large vertical separation between measurement heights. When stability estimates based on eddy-covariance flux measurements are replaced with stability estimates based on the weather station or net radiation data, the MOST-based fluxes still capture the temporal patterns measured via eddy covariance. Based on these results, MOST can be used to estimate the temporal patterns in local GHG fluxes at mole fraction tower sites, complementing the small number of eddy-covariance flux measurements available in urban settings. [ABSTRACT FROM AUTHOR]

ABSTRACT The severe storms research community lacks reliable, aboveground, thermodynamic observations (e.g., temperature, humidity, and pressure) in convective storms. These missing observations are crucial to understanding the behavior of both [...]

We quantify weekly methane emissions at 0.25 ∘ × 0.3125 ∘ (≈25 × 25 km 2) resolution from the Permian Basin, the largest oil production basin in the US, by inverse analysis of satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI) from May 2018 to October 2020. The mean oil and gas emission from the region (± standard deviation of weekly estimates) was 3.7 ± 0.9 Tg a -1 , higher than previous TROPOMI inversion estimates that may have used biased prior emissions or background assumptions. We find strong week-to-week variability in emissions superimposed on longer-term trends, and these are consistent with independent inferences of temporal emission variability from tower, aircraft, and multispectral satellite data. New well development and natural gas spot price were significant drivers of variability in emissions over our study period but the concurrent 50 % increase in oil and gas production was not. The methane intensity (methane emitted per unit of methane gas produced) averaged 4.6 % ± 1.3 % and steadily decreased from 5 %–6 % in 2018 to 3 %–4 % in 2020. While the decreasing trend suggests improvement in operator practices during the study period, methane emissions from the Permian Basin remained high, with methane intensity an order of magnitude above the industry target of <0.2 %. Our success in using TROPOMI satellite observations for weekly estimates of emissions from a major oil production basin shows promise for application to near-real-time monitoring in support of climate change mitigation efforts. [ABSTRACT FROM AUTHOR]

We quantify weekly methane emissions at 0.25°×0.3125° (≈25×25 km²) resolution from the Permian Basin, the largest oil production basin in the United States, by inverse analysis of satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI) from May 2018 to October 2020. The mean oil and gas emission from the region (± standard deviation of weekly estimates) was 3.7 ± 0.9 Tg a-1, higher than previous TROPOMI inversion estimates that may have used too-low prior emissions or biased background assumptions. We find strong week-to-week variability in emissions superimposed on longer-term trends, and these are consistent with independent inferences of temporal emission variability from tower, aircraft, and multispectral satellite data. New well development and local natural gas spot price were significant drivers of variability in emissions over our study period, but the concurrent 50 % increase in oil and gas production was not. The methane intensity (methane emitted per unit of methane gas produced) averaged 4.6 % ± 1.3 % and steadily decreased over the period from 5–6 % in 2018 to 3–4 % in 2020. While the decreasing trend suggests improvement in operator practices during the study period, methane emissions from the Permian Basin remained high, with methane intensity an order of magnitude above recent industry targets of <0.2 %. Our success in using TROPOMI satellite observations for weekly estimates of emissions from a major oil production basin shows promise for application to near-real-time monitoring in support of climate change mitigation efforts. [ABSTRACT FROM AUTHOR]

Methane emissions associated with the production, transport, and use of oil and natural gas increase the climatic impacts of energy use; however, little is known about how emissions vary temporally and with commodity prices. We present airborne and ground-based data, supported by satellite observations, to measure weekly to monthly changes in total methane emissions in the United States' Permian Basin during a period of volatile oil prices associated with the COVID-19 pandemic. As oil prices declined from ~$ 60 to $ 20 per barrel, emissions changed concurrently from 3.4 % to 1.5 % of gas production; as prices partially recovered, emissions increased back to near initial values. Concurrently, total oil and natural gas production only declined by a maximum of ~10 % from the peak values seen in the months prior to the crash. Activity data indicate that a rapid decline in well development and subsequent effects on associated gas flaring and midstream infrastructure throughput are the likely drivers of temporary emission reductions. Our results, along with past satellite observations, suggest that under more typical price conditions, the Permian Basin is in a state of overcapacity in which rapidly growing natural gas production exceeds midstream capacity and leads to high methane emissions. [ABSTRACT FROM AUTHOR]

As natural gas extraction and use continues to increase, the need to quantify emissions of methane (CH4), a powerful greenhouse gas, has grown. Large discrepancies in Indianapolis CH4 emissions have been observed when comparing inventory, aircraft mass-balance, and tower inverse modeling estimates. Four years of continuous CH4 mole fraction observations from a network of nine tower-based cavity ring-down spectrometers measuring atmospheric CH4 mole fractions at 39 to 136 m above ground as part of the Indianapolis Flux Experiment (INFLUX) are utilized to investigate four possible reasons for the abovementioned inconsistencies: (1) differences in definition of the city domain, (2) a highly temporally variable and spatially non-uniform CH4 background, (3) temporal variability in CH4 emissions, and (4) the presence of unknown CH4 sources. Reducing the Indianapolis urban domain size to be consistent with the inventory domain size decreases the CH4 emission estimation of the inverse modeling methodology by about 35 % and thereby lessens the discrepancy by bringing total city flux within an error range of one of the inventories. Nevertheless, the inverse modeling estimate still remains about 40 % higher than the inventory value. Hourly urban background CH4 mole fractions are shown to be heterogeneous and temporally variable. Statistically significant, long-term biases in background mole fractions of 2–5 ppb are found from single point observations from most wind directions. Random errors in single point background mole fractions observed for a few hours are 20–30 ppb, but decrease substantially when data are averaged over multiple days. Boundary layer budget estimates suggest that Indianapolis CH4 emissions did not change significantly when comparing 2014 to 2016. However, it appears that CH4 emissions may follow a diurnal cycle with daytime emissions (12–16 LST) approximately twice as large as nighttime emissions (20–5 LST). The strongest CH4 source in Indianapolis is the South Side Landfill. Other point sources, perhaps leaks from the natural gas distribution system, are localized and transient, and do not appear to be a consistently large source of CH4 emissions in Indianapolis. Long-term averaging, spatially-extensive upwind mole fraction observations, mesoscale atmospheric modeling of the regional emissions environment, and careful treatment of the times of day and areal representation of emission estimates is recommended for precise and accurate quantification of urban CH4 emissions. [ABSTRACT FROM AUTHOR]