Seasonally Resolved Excess Urban Methane Emissions from the Baltimore/Washington, DC Metropolitan Region

Underestimation of Thermogenic Methane Emissions in New York City

Recent studies have shown that methane emissions are underestimated by inventories in many US urban areas. This has important implications for climate change mitigation policy at the city, state, and national levels. Uncertainty in both the spatial distribution and sectoral allocation of urban emissions can limit the ability of policy makers to develop appropriately focused emission reduction strategies. Top-down emission estimates based on atmospheric greenhouse gas measurements can help to improve inventories and inform policy decisions. This study presents a new high-resolution (0.02 × 0.02°) methane emission inventory for New York City and its surrounding area, constructed using the latest activity data, emission factors, and spatial proxies. The new high-resolution inventory estimates of methane emissions for the New York-Newark urban area are 1.3 times larger than those for the gridded Environmental Protection Agency inventory. We used aircraft mole fraction measurements from nine research flights to optimize the high-resolution inventory emissions within a Bayesian inversion. These sectorally optimized emissions show that the high-resolution inventory still significantly underestimates methane emissions within the New York-Newark urban area, primarily because it underestimates emissions from thermogenic sources (by a factor of 2.3). This suggests that there remains a gap in our process-based understanding of urban methane emissions.

Urban methane emission monitoring across North America using TROPOMI data: an analytical inversion approach

Monitoring methane emissions is crucial in mitigating climate change as it has a relatively short atmospheric lifetime of about 12 years and a significant radiative forcing impact. To measure the impact of methane-controlling policies and techniques, a deep understanding of methane emissions is of great importance. Remote sensing offers scalable approaches for monitoring methane emissions at various scales, from point-source high-resolution monitoring to regional and global estimates. The TROPOMI satellite instrument provides daily XCH4 data globally, offering the opportunity to monitor methane at a moderate spatial resolution with an acceptable level of sensitivity. To infer emissions from TROPOMI data, we used the prior emission estimates from global and national inventories and the GEOS-Chem chemical transport model to simulate atmospheric methane along with actual observations of TROPOMI. In this study, methane emissions from Toronto, Montreal, New York, Los Angeles, Houston, and Mexico City have been estimated using the analytical solution of Bayesian inversion using the cloud-based Integrated Methane Inversion (IMI) framework. Using the result from ensemble inversions, and city boundaries, the average total emissions were as follows: Toronto 230.52 Gg a-1, Montreal 111.54 Gg a-1, New York 144.38 Gg a-1, Los Angeles 207.03 Gg a-1, Houston 650.16 Gg a-1, and Mexico City 280.81 Gg a-1. The resulting gridded scale factors ranged from 0.22 to 6.2, implying methane prior emission underestimations in most of these cities. As such, this study underscores the key role of remote sensing in accurately assessing urban methane emissions, informing essential climate mitigation efforts.

Methane Emissions Show Recent Decline but Strong Seasonality in Two US Northeastern Cities

Urban methane emissions estimated using atmospheric observations have been found to exceed estimates derived by using traditional inventory methods in several northeastern US cities. In this work, we leveraged a nearly five-year record of observations from a dense tower network coupled with a newly developed high-resolution emissions map to quantify methane emission rates in Washington, DC, and Baltimore, Maryland. Annual emissions averaged over 2018-2021 were 80.1 [95% CI: 61.2, 98.9] Gg in the Washington, DC urban area and 47.4 [95% CI: 35.9, 58.5] Gg in the Baltimore urban area, with a decreasing trend of approximately 4-5% per year in both cities. We also find wintertime emissions 44% higher than summertime emissions, correlating with natural gas consumption. We further attribute a large fraction of total methane emissions to the natural gas sector using a least-squares regression on our spatially resolved estimates, supporting previous findings that natural gas systems emit the plurality of methane in both cities. This study contributes to the relatively sparse existing knowledge base of urban methane emissions sources and variability, adding to our understanding of how these emissions change in time and providing evidence to support efforts to mitigate natural gas emissions.

A simple method to measure methane emissions from indoor gas leaks

From wellhead to burner tip, each component of the natural gas process chain has come under increased scrutiny for the presence and magnitude of methane leaks, because of the large global warming potential of methane. Top-down measures of methane emissions in urban areas are significantly greater than bottom-up estimates. Recent research suggests this disparity might in part be explained by gas leaks from one of the least understood parts of the process chain: behind the gas meter in homes and buildings. However, little research has been performed in this area and few methods and data sets exist to measure or estimate them. We develop and test a simple and widely deployable closed chamber method that can be used for quantifying indoor methane emissions with an order-of-magnitude precision which allows for screening of indoor large volume ("super-emitting") leaks. We also perform test applications of the method finding indoor leaks in 90% of the 20 Greater Boston buildings studied and indoor methane emissions between 0.02-0.51 ft3 CH4 day-1 (0.4-10.3 g CH4 day-1) with a mean of 0.14 ft3 CH4 day-1 (2.8 g CH4 day-1). Our method provides a relatively simple way to scale up indoor methane emissions data collection. Increased data may reduce uncertainty in bottom-up inventories, and can be used to find super-emitting indoor emissions which may better explain the disparity between top-down and bottom-up post-meter emissions estimates.

Decadal decrease in Los Angeles methane emissions is much smaller than bottom-up estimates

Methane, a powerful greenhouse gas, has a short atmospheric lifetime ( ~ 12 years), so that emissions reductions will have a rapid impact on climate forcing. In megacities such as Los Angeles (LA), natural gas (NG) leakage is the primary atmospheric methane source. The magnitudes and trends of fugitive NG emissions are largely unknown and need to be quantified to verify compliance with emission reduction targets. Here we use atmospheric remote sensing data to show that, in contrast to the observed global increase in methane emissions, LA area emissions decreased during 2011-2020 at a mean rate of (-1.57 ± 0.41) %/yr. However, the NG utility calculations indicate a much larger negative emissions trend of -5.8 %/yr. The large difference between top-down and bottom-up trends reflects the uncertainties in estimating the achieved emissions reductions. Actions taken in LA can be a blueprint for COP28 and future efforts to reduce methane emissions.

Laboratory and field evaluation of a low-cost methane sensor and key environmental factors for sensor calibration

Low-cost sensors enable finer-scale spatiotemporal measurements within the existing methane (CH4) monitoring infrastructure and could help cities mitigate CH4 emissions to meet their climate goals. While initial studies of low-cost CH4 sensors have shown potential for effective CH4 measurement at ambient concentrations, sensor deployment remains limited due to questions about interferences and calibration across environments and seasons. This study evaluates sensor performance across seasons with specific attention paid to the sensor's understudied carbon monoxide (CO) interferences and environmental dependencies through long-term ambient co-location in an urban environment. The sensor was first evaluated in a laboratory using chamber calibration and co-location experiments, and then in the field through two 8 week co-locations with a reference CH4 instrument. In the laboratory, the sensor was sensitive to CH4 concentrations below ambient background concentrations. Different sensor units responded similarly to changing CH4, CO, temperature, and humidity conditions but required individual calibrations to account for differences in sensor response factors. When deployed in-field, co-located with a reference instrument near Baltimore, MD, the sensor captured diurnal trends in hourly CH4 concentration after corrections for temperature, absolute humidity, CO concentration, and hour of day. Variable performance was observed across seasons with the sensor performing well (R 2 = 0.65; percent bias 3.12%; RMSE 0.10 ppm) in the winter validation period and less accurately (R 2 = 0.12; percent bias 3.01%; RMSE 0.08 ppm) in the summer validation period where there was less dynamic range in CH4 concentrations. The results highlight the utility of sensor deployment in more variable ambient CH4 conditions and demonstrate the importance of accounting for temperature and humidity dependencies as well as co-located CO concentrations with low-cost CH4 measurements. We show this can be addressed via Multiple Linear Regression (MLR) models accounting for key covariates to enable urban measurements in areas with CH4 enhancement. Together with individualized calibration prior to deployment, the sensor shows promise for use in low-cost sensor networks and represents a valuable supplement to existing monitoring strategies to identify CH4 hotspots.

Temporal variation and grade categorization of methane emission from LNG fueling stations

Natural gas is increasingly seen as the fossil fuel of choice for China as it transitions to renewable sources. The significant development of China's LNG vehicle application and fueling stations and the urgency of climate changes make it particularly important to quantify methane emission from LNG stations, where the data are extremely rare. We carried out a pilot study on direct measurement and quantitative analysis of methane emission from five LNG fueling stations located in Shandong, China following the standard stationary EPA OTM 33A method. The measured methane emission of these five stations vary from 0.01 to 8.76 kg/h. The loss rates vary from 0.004 to 0.257%. We demonstrated that the emission from LNG stations consist of continuous and intermittent contents. The intermittent emission shows a strong temporal variation. If a station is only monitored for 20 min, it may either under-estimate or over-estimate the total emission. Both the distribution of emission events and total emission rates among different stations are highly skewed. We found that these LNG fueling station emission can be categorized into 3 grades, as low, medium and high, corresponding to emission rates below 0.1 kg/h; between 0.1 and 1 kg/h and above 1 kg/h, which can be characterized by the measured average methane concentration enhancement.

Home is Where the Pipeline Ends: Characterization of Volatile Organic Compounds Present in Natural Gas at the Point of the Residential End User

The presence of volatile organic compounds (VOCs) in unprocessed natural gas (NG) is well documented; however, the degree to which VOCs are present in NG at the point of end use is largely uncharacterized. We collected 234 whole NG samples across 69 unique residential locations across the Greater Boston metropolitan area, Massachusetts. NG samples were measured for methane (CH₄), ethane (C₂H₆), and nonmethane VOC (NMVOC) content (including tentatively identified compounds) using commercially available USEPA analytical methods. Results revealed 296 unique NMVOC constituents in end use NG, of which 21 (or approximately 7%) were designated as hazardous air pollutants. Benzene (bootstrapped mean = 164 ppbv; SD = 16; 95% CI: 134-196) was detected in 95% of samples along with hexane (98% detection), toluene (94%), heptane (94%), and cyclohexane (89%), contributing to a mean total concentration of NMVOCs in distribution-grade NG of 6.0 ppmv (95% CI: 5.5-6.6). While total VOCs exhibited significant spatial variability, over twice as much temporal variability was observed, with a wintertime NG benzene concentration nearly eight-fold greater than summertime. By using previous NG leakage data, we estimated that 120-356 kg/yr of annual NG benzene emissions throughout Greater Boston are not currently accounted for in emissions inventories, along with an unaccounted-for indoor portion. NG-odorant content (tert-butyl mercaptan and isopropyl mercaptan) was used to estimate that a mean NG-CH₄ concentration of 21.3 ppmv (95% CI: 16.7-25.9) could persist undetected in ambient air given known odor detection thresholds. This implies that indoor NG leakage may be an underappreciated source of both CH₄ and associated VOCs.

Estimating the methane emissions and energy potential from Trichy and Thanjavur dumpsite by LandGEM model

One major factor, contributing to the emission of greenhouse gas in the environment, is generation of hazardous gases in municipal landfills. Due to these potential negative impacts, it is obligatory to estimate the amount and type of landfill gasses to design and build a gas collecting system. Landfill gas emissions are governed by the type of waste, its biodegradability, its methane emission potential, the degree of separation, and other miscellaneous factors. LandGEM model was used to predict the amount of gases produced in the landfills of Trichy (Ariyamangalam) and Thanjavur (Srinivasapuram). According to the results, the largest amount of landfill gas emissions would be in 1993 for Trichy (Ariyamangalam) landfill and in 2027 for Thanjavur (Srinivasapuram) landfill. The total amount of produced gas, methane, and carbon dioxide would be 16.2E + 10, 8.2E + 10, and 16.2 + 10 cubic meters per year in 1993 for Trichy and 13E + 6, 5E + 6 and 13E + 6 cubic meters per year in 2027 for Thanjavur.

Majority of US urban natural gas emissions unaccounted for in inventories

Across many cities, estimates of methane emissions from natural gas (NG) distribution and end use based on atmospheric measurements have generally been more than double bottom-up estimates. We present a top-down study of NG methane emissions from the Boston urban region spanning 8 y (2012 to 2020) to assess total emissions, their seasonality, and trends. We used methane and ethane observations from five sites in and around Boston, combined with a high-resolution transport model, to calculate methane emissions of 76 ± 18 Gg/yr, with 49 ± 9 Gg/yr attributed to NG losses. We found no significant trend in the NG loss rate over 8 y, despite efforts from the city and state to increase the rate of repairing NG pipeline leaks. We estimate that 2.5 ± 0.5% of the gas entering the urban region is lost, approximately three times higher than bottom-up estimates. We saw a strong correlation between top-down NG emissions and NG consumed on a seasonal basis. This suggests that consumption-driven losses, such as in transmission or end-use, may be a large component of emissions that is missing from inventories, and require future policy action. We also compared top-down NG emission estimates from six US cities, all of which indicate significant missing sources in bottom-up inventories. Across these cities, we estimate NG losses from distribution and end use amount to 20 to 36% of all losses from the US NG supply chain, with a total loss rate of 3.3 to 4.7% of NG from well pad to urban consumer, notably larger than the current Environmental Protection Agency estimate of 1.4% [R. A. Alvarez et al., Science 361, 186-188 (2018)].

Biogenic link to the recent increase in atmospheric methane over India

Methane (CH₄) is a prominent Greenhouse Gas (GHG) and its global atmospheric concentration has increased significantly since the year 2007. Anthropogenic CH₄ emissions are projected to be 9390 million metric tonnes by 2020. Here, we present the long-term changes in atmospheric methane over India and suggest possible alternatives to reduce soil emissions from paddy fields. The increase in atmospheric CH₄ concentrations from 2009 to 2020 in India is significant, about 0.0765 ppm/decade. The Indo-Gangetic Plains, Peninsular India and Central India show about 0.075, 0.076 and 0.074 ppm/decade, respectively, in 2009-2020. Seasonal variations in CH₄ emissions depend mostly on agricultural activities and meteorology, and contribution during the agricultural intensive period of Kharif-Rabi (i.e., June-December) is substantial in this regard. The primary reason for agricultural soil emissions is the application of chemical fertilizers to improve crop yield. However, for rice farming, soil amendments involving stable forms of carbon can reduce GHG emissions and improve soil carbon status. High crop production in pot culture experiment resulted in lower potential yield-scaled GHG emissions in rice with biochar supplement. The human impact of global warming induced by agricultural activities could be reduced by using biochar as a natural solution.

Urban Emissions of Nitrogen Oxides, Carbon Monoxide, and Methane Determined from Ground-Based Measurements in Philadelphia

Nitrogen oxides (NO_X) and methane impact air quality through the promotion of ozone formation, and methane is also a strong greenhouse gas. Despite the importance of these pollutants, emissions in urban areas are poorly quantified. We present measurements of NO_X, CH₄, CO, and CO₂ made at Drexel University in Philadelphia along with NO_X and CO observations at two roadside monitors. Because CO₂ concentrations in the winter result almost entirely from combustion with negligible influence from photosynthesis and respiration, we are able to infer fleet-averaged fuel-based emission factors (EFs) for NO_X and CO, similar in some ways to how EFs are determined from tunnel studies. Comparison of the inferred NO_X and CO fuel-based EF to the National Emissions Inventory (NEI) suggests errors in NEI emissions of either NO_X, CO, or both. From the measurements of CH₄ and CO₂, which are not emitted by the same sources, we infer the ratio of CH₄ emissions (from leaks in the natural gas infrastructure) to CO₂ emissions (from fossil fuel combustion) in Philadelphia. Comparison of the CH₄/CO₂ emission ratios to emission inventories from the Environmental Protection Agency suggests underestimates in CH₄ emissions by almost a factor of 4. These results demonstrate the need for the addition of long-term observations of CH₄ and CO₂ to existing monitoring networks in urban areas to better constrain emissions and complement existing measurements of NO_X and CO.

Greenhouse gas observations from the Northeast Corridor tower network

We present the organization, structure, instrumentation, and measurements of the Northeast Corridor greenhouse gas observation network. This network of tower-based in situ carbon dioxide and methane observation stations was established in 2015 with the goal of quantifying emissions of these gases in urban areas in the northeastern United States. A specific focus of the network is the cities of Baltimore, MD, and Washington, DC, USA, with a high density of observation stations in these two urban areas. Additional observation stations are scattered throughout the northeastern US, established to complement other existing urban and regional networks and to investigate emissions throughout this complex region with a high population density and multiple metropolitan areas. Data described in this paper are archived at the National Institute of Standards and Technology and can be found at https://doi.org/10.18434/M32126 (Karion et al., 2019).