A Gridded Inventory of Annual 2012-2018 U.S. Anthropogenic Methane Emissions.

Nationally reported greenhouse gas inventories are a core component of the Paris Agreement's transparency framework. Comparisons with emission estimates derived from atmospheric observations help identify improvements to reduce uncertainties and increase the confidence in reported values. To facilitate comparisons over the contiguous United States, we present a 0.1° × 0.1° gridded inventory of annual 2012-2018 anthropogenic methane emissions, allocated to 26 individual source categories, with scale-dependent error estimates. Our inventory is consistent with the U.S. Environmental Protection Agency (EPA) Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI), submitted to the United Nations in 2020. Total emissions and patterns (spatial/temporal) reflect the activity and emission factor data underlying the GHGI, including many updates relative to a previous gridded version of the GHGI that has been extensively compared with observations. These underlying data are not generally available in global gridded inventories, and comparison to EDGAR version 6 shows large spatial differences, particularly for the oil and gas sectors. We also find strong regional variability across all sources in annual 2012-2018 spatial trends, highlighting the importance of understanding regional- and facility-level activities. Our inventory represents the first time series of gridded GHGI methane emissions and enables robust comparisons of emissions and their trends with atmospheric observations.

Artificial Intelligence Approach for Estimating Dairy Methane Emissions.

California's dairy sector accounts for ∼50% of anthropogenic CH4 emissions in the state's greenhouse gas (GHG) emission inventory. Although California dairy facilities' location and herd size vary over time, atmospheric inverse modeling studies rely on decade-old facility-scale geospatial information. For the first time, we apply artificial intelligence (AI) to aerial imagery to estimate dairy CH4 emissions from California's San Joaquin Valley (SJV), a region with ∼90% of the state's dairy population. Using an AI method, we process 316,882 images to estimate the facility-scale herd size across the SJV. The AI approach predicts herd size that strongly (>95%) correlates with that made by human visual inspection, providing a low-cost alternative to the labor-intensive inventory development process. We estimate SJV's dairy enteric and manure CH4 emissions for 2018 to be 496-763 Gg/yr (mean = 624; 95% confidence) using the predicted herd size. We also apply our AI approach to estimate CH4 emission reduction from anaerobic digester deployment. We identify 162 large (90th percentile) farms and estimate a CH4 reduction potential of 83 Gg CH4/yr for these large facilities from anaerobic digester adoption. The results indicate that our AI approach can be applied to characterize the manure system (e.g., use of an anaerobic lagoon) and estimate GHG emissions for other sectors.

Assessment of Regional Methane Emission Inventories through Airborne Quantification in the San Francisco Bay Area.

This study derives methane emission rates from 92 airborne observations collected over 23 facilities including 5 refineries, 10 landfills, 4 wastewater treatment plants (POTWs), 2 composting operations, and 2 dairies in the San Francisco Bay Area. Emission rates are measured using an airborne mass-balance technique from a low-flying aircraft. Annual measurement-based sectorwide methane emissions are 19,000 ± 2300 Mg for refineries, 136,700 ± 25,900 Mg for landfills, 11,900 ± 1,500 Mg for POTWs, and 11,100 ± 3,400 Mg for composting. The average of measured emissions for each refinery ranges from 4 to 23 times larger than the corresponding emissions reported to regulatory agencies, while measurement-derived landfill and POTW estimates are approximately twice the current inventory estimates. Significant methane emissions at composting facilities indicate that a California mandate to divert organics from landfills to composting may not be an effective measure for mitigating methane emissions unless best management practices are instituted at composting facilities. Complementary evidence from airborne remote sensing imagery indicates atmospheric venting from refinery hydrogen plants, landfill working surfaces, composting stockpiles, etc., to be among the specific source types responsible for the observed discrepancies. This work highlights the value of multiple measurement approaches to accurately estimate facility-scale methane emissions and perform source attribution at subfacility scales to guide and verify effective mitigation policy and action.

An Estimate of Natural Gas Methane Emissions from California Homes.

We estimate postmeter methane (CH4) emissions from California's residential natural gas (NG) system using measurements and analysis from a sample of homes and appliances. Quiescent whole-house emissions (i.e., pipe leaks and pilot lights) were measured using a mass balance method in 75 California homes, while CH4 to CO2 emission ratios were measured for steady operation of individual combustion appliances and, separately, for transient operation of three tankless water heaters. Measured quiescent whole-house emissions are typically <1 g CH4/day, though they exhibit long-tailed gamma distributions containing values >10 g CH4/day. Most operating appliances yield undetectable CH4 to CO2 enhancements in steady operation (<0.01% of gas consumed), though storage water heaters and stovetops exhibit long-tailed gamma distributions containing high values (∼1-3% of gas consumed), and transients are observed for the tankless heaters. Extrapolating results to the state-level using Bayesian Markov chain Monte Carlo sampling combined with California housing statistics and gas use information suggests quiescent house leakage of 23.4 (13.7-45.6, at 95% confidence) Gg CH4, with pilot lights contributing ∼30%. Emissions from steady operation of appliances and their pilots are 13.3 (6.6-37.1) Gg CH4/yr, an order of magnitude larger than current inventory estimates, with transients likely increasing appliance emissions further. Together, emissions from residential NG are 35.7 (21.7-64.0) Gg CH4/yr, equivalent to ∼15% of California's NG CH4 emissions, suggesting leak repair, improvement of combustion appliances, and adoption of nonfossil energy heating sources can help California meet its 2050 climate goals.

Elliptic Cylinder Airborne Sampling and Geostatistical Mass Balance Approach for Quantifying Local Greenhouse Gas Emissions.

In this study, we explore observational, experimental, methodological, and practical aspects of the flux quantification of greenhouse gases from local point sources by using in situ airborne observations, and suggest a series of conceptual changes to improve flux estimates. We address the major sources of uncertainty reported in previous studies by modifying (1) the shape of the typical flight path, (2) the modeling of covariance and anisotropy, and (3) the type of interpolation tools used. We show that a cylindrical flight profile offers considerable advantages compared to traditional profiles collected as curtains, although this new approach brings with it the need for a more comprehensive subsequent analysis. The proposed flight pattern design does not require prior knowledge of wind direction and allows for the derivation of an ad hoc empirical correction factor to partially alleviate errors resulting from interpolation and measurement inaccuracies. The modified approach is applied to a use-case for quantifying CH4 emission from an oil field south of San Ardo, CA, and compared to a bottom-up CH4 emission estimate.

Regulation of interleukin-11 expression in ovulatory follicles of the rat ovary.

The aim of the present study was to examine the regulation of interleukin (IL)-11 expression, as well as the role of IL-11, during ovulation in gonadotropin-primed immature rats. Injection of equine chorionic gonadotropin (eCG), followed by human CG (hCG) to induce superovulation stimulated expression of the Il11 gene in theca cells within 6h, as revealed by northern blot and in situ hybridisation analyses. Real-time reverse transcription-polymerase chain reaction analysis showed that the IL-11 receptor, α subunit gene was expressed in granulosa and theca cells and that injection of hCG had no effect on its expression. IL-11 protein expression was stimulated in theca cells by hCG. LH-stimulated increases in Il11 mRNA levels in cultured preovulatory follicles were inhibited by protein kinase A and mitogen-activated protein kinase kinase inhibitors. Toll-like receptor (TLR) 2 and TLR4 were detected in preovulatory follicles, and the TLR4 ligand lipopolysaccharide, but not the TLR2 ligand Pam3Cys, increased Il11 mRNA levels in theca cells, but not in granulosa cells. Treatment of preovulatory follicles with IL-11 stimulated progesterone production and steroidogenic acute regulatory protein (Star) gene expression. Together, these results indicate that IL-11 in theca cells is stimulated by mitogen-activated protein kinase signalling and TLR4 activation, and increases progesterone production during ovulation.

Gridded National Inventory of U.S. Methane Emissions.

We present a gridded inventory of US anthropogenic methane emissions with 0.1° × 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 US Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) for 2012. The EPA inventory is available only as national totals for different source types. We use a wide range of databases at the state, county, local, and point source level to disaggregate the inventory and allocate the spatial and temporal distribution of emissions for individual source types. Results show large differences with the EDGAR v4.2 global gridded inventory commonly used as a priori estimate in inversions of atmospheric methane observations. We derive grid-dependent error statistics for individual source types from comparison with the Environmental Defense Fund (EDF) regional inventory for Northeast Texas. These error statistics are independently verified by comparison with the California Greenhouse Gas Emissions Measurement (CALGEM) grid-resolved emission inventory. Our gridded, time-resolved inventory provides an improved basis for inversion of atmospheric methane observations to estimate US methane emissions and interpret the results in terms of the underlying processes.

Spatially explicit methane emissions from petroleum production and the natural gas system in California.

We present a new, spatially resolved inventory of methane (CH4) emissions based on US-EPA emission factors and publically available activity data for 2010 California petroleum production and natural gas production, processing, transmission, and distribution. Compared to official California bottom-up inventories, our initial estimates are 3 to 7 times higher for the petroleum and natural gas production sectors but similar for the natural gas transmission and distribution sectors. Evidence from published "top-down" atmospheric measurement campaigns within Southern California supports our initial emission estimates from production and processing but indicates emission estimates from transmission and distribution are low by a factor of approximately 2. To provide emission maps with more accurate total emissions we scale the spatially resolved inventory by sector-specific results from a Southern California aircraft measurement campaign to all of California. Assuming uncertainties are determined by the uncertainties estimated in the top-down study, our estimated state total CH4 emissions are 541 ± 144 Gg yr(-1) (as compared with 210.7 Gg yr(-1) in California's current official inventory), where the majority of our reported uncertainty is derived from transmission and distribution. We note uncertainties relative to the mean for a given region are likely larger than that for the State total, emphasizing the need for additional measurements in undersampled regions.

A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models.

In 2022, wind generation accounted for ~10% of total electricity generation in the United States. As wind energy accounts for a greater portion of total energy, understanding geographic and temporal variation in wind generation is key to many planning, operational, and research questions. However, in-situ observations of wind speed are expensive to make and rarely shared publicly. Meteorological models are commonly used to estimate wind speeds, but vary in quality and are often challenging to access and interpret. The Plant-Level US multi-model WIND and generation (PLUSWIND) data repository helps to address these challenges. PLUSWIND provides wind speeds and estimated generation on an hourly basis at almost all wind plants across the contiguous United States from 2018-2021. The repository contains wind speeds and generation based on three different meteorological models: ERA5, MERRA2, and HRRR. Data are publicly accessible in simple csv files. Modeled generation is compared to regional and plant records, which highlights model biases and errors and how they differ by model, across regions, and across time frames.

On the sources of methane to the Los Angeles atmosphere.

We use historical and new atmospheric trace gas observations to refine the estimated source of methane (CH(4)) emitted into California's South Coast Air Basin (the larger Los Angeles metropolitan region). Referenced to the California Air Resources Board (CARB) CO emissions inventory, total CH(4) emissions are 0.44 ± 0.15 Tg each year. To investigate the possible contribution of fossil fuel emissions, we use ambient air observations of methane (CH(4)), ethane (C(2)H(6)), and carbon monoxide (CO), together with measured C(2)H(6) to CH(4) enhancement ratios in the Los Angeles natural gas supply. The observed atmospheric C(2)H(6) to CH(4) ratio during the ARCTAS (2008) and CalNex (2010) aircraft campaigns is similar to the ratio of these gases in the natural gas supplied to the basin during both these campaigns. Thus, at the upper limit (assuming that the only major source of atmospheric C(2)H(6) is fugitive emissions from the natural gas infrastructure) these data are consistent with the attribution of most (0.39 ± 0.15 Tg yr(-1)) of the excess CH(4) in the basin to uncombusted losses from the natural gas system (approximately 2.5-6% of natural gas delivered to basin customers). However, there are other sources of C(2)H(6) in the region. In particular, emissions of C(2)H(6) (and CH(4)) from natural gas seeps as well as those associated with petroleum production, both of which are poorly known, will reduce the inferred contribution of the natural gas infrastructure to the total CH(4) emissions, potentially significantly. This study highlights both the value and challenges associated with the use of ethane as a tracer for fugitive emissions from the natural gas production and distribution system.

Evaluation of Serious Adverse Event Reporting Forms for Clinical Trials: A Comparative Korean Study.

Safety surveillance, using appropriately consistent review criteria, could improve human participants' well-being in clinical trials. To establish a globally consistent framework, the quality of the current content for review by institutional review boards (IRBs), as mandatory oversight entities, requires evaluation. This study collected and analyzed forms reporting serious adverse events (SAEs) to IRBs/ Research Ethics Committees(RECs) to compare them with the well-structured form presented in the literature using completeness and accuracy scores. We found sub-optimal completeness and accuracy scores when compared with perfect scores (p < .05). Less than half of the retrieved forms had queries on causality assessment (≤43.1%). Thus, contents of SAE forms require improvement for IRB oversight and, further, there is a need to develop a well-structured form that could improve international consistency.

Atmospheric observation-based estimation of fossil fuel CO2 emissions from regions of central and southern California.

Combustion of fossil fuel is the dominant source of greenhouse gas emissions to the atmosphere in California. Here, we describe radiocarbon (14CO2) measurements and atmospheric inverse modeling to estimate fossil fuel CO2 (ffCO2) emissions for 2009-2012 from a site in central California, and for June 2013-May 2014 from two sites in southern California. A priori predicted ffCO2 mixing ratios are computed based on regional atmospheric transport model (WRF-STILT) footprints and an hourly ffCO2 prior emission map (Vulcan 2.2). Regional inversions using observations from the central California site suggest that emissions from the San Francisco Bay Area (SFBA) are higher in winter and lower in summer. Taking all years together, the average of a total of fifteen 3-month inversions from 2009 to 2012 suggests ffCO2 emissions from SFBA were within 6 ±â€¯35% of the a priori estimate for that region, where posterior emission uncertainties are reported as 95% confidence intervals. Results for four 3-month inversions using measurements in Los Angeles South Coast Air Basin (SoCAB) during June 2013-May 2014 suggest that emissions in SoCAB are within 13 ±â€¯28% of the a priori estimate for that region, with marginal detection of any seasonality. While emissions from the SFBA and SoCAB urban regions (containing ~50% of prior emissions from California) are constrained by the observations, emissions from the remaining regions are less constrained, suggesting that additional observations will be valuable to more accurately estimate total ffCO2 emissions from California as a whole.