Spatiotemporal Variability of Methane Emissions at Oil and Natural Gas Operations in the Eagle Ford Basin.

Methane emissions from oil and gas facilities can exhibit operation-dependent temporal variability; however, this variability has yet to be fully characterized. A field campaign was conducted in June 2014 in the Eagle Ford basin, Texas, to examine spatiotemporal variability of methane emissions using four methods. Clusters of methane-emitting sources were estimated from 14 aerial surveys of two ("East" or "West") 35 × 35 km grids, two aircraft-based mass balance methods measured emissions repeatedly at five gathering facilities and three flares, and emitting equipment source-types were identified via helicopter-based infrared camera at 13 production and gathering facilities. Significant daily variability was observed in the location, number (East: 44 ± 20% relative standard deviation (RSD), N = 7; West: 37 ± 30% RSD, N = 7), and emission rates (36% of repeat measurements deviate from mean emissions by at least ±50%) of clusters of emitting sources. Emission rates of high emitters varied from 150-250 to 880-1470 kg/h and regional aggregate emissions of large sources (>15 kg/h) varied up to a factor of ∼3 between surveys. The aircraft-based mass balance results revealed comparable variability. Equipment source-type changed between surveys and alterations in operational-mode significantly influenced emissions. Results indicate that understanding temporal emission variability will promote improved mitigation strategies and additional analysis is needed to fully characterize its causes.

Assessing the Methane Emissions from Natural Gas-Fired Power Plants and Oil Refineries.

Presently, there is high uncertainty in estimates of methane (CH4) emissions from natural gas-fired power plants (NGPP) and oil refineries, two major end users of natural gas. Therefore, we measured CH4 and CO2 emissions at three NGPPs and three refineries using an aircraft-based mass balance technique. Average CH4 emission rates (NGPPs: 140 ± 70 kg/h; refineries: 580 ± 220 kg/h, 95% CL) were larger than facility-reported estimates by factors of 21-120 (NGPPs) and 11-90 (refineries). At NGPPs, the percentage of unburned CH4 emitted from stacks (0.01-0.08%) was much lower than respective facility-scale losses (0.09-0.34%), and CH4 emissions from both NGPPs and refineries were more strongly correlated with enhanced H2O concentrations (R2avg = 0.65) than with CO2 (R2avg = 0.21), suggesting noncombustion-related equipment as potential CH4 sources. Additionally, calculated throughput-based emission factors (EF) derived from the NGPP measurements made in this study were, on average, a factor of 4.4 (stacks) and 37 (facility-scale) larger than industry-used EFs. Subsequently, throughput-based EFs for both the NGPPs and refineries were used to estimate total U.S. emissions from these facility-types. Results indicate that NGPPs and oil refineries may be large sources of CH4 emissions and could contribute significantly (0.61 ± 0.18 Tg CH4/yr, 95% CL) to U.S. emissions.

Direct and Indirect Measurements and Modeling of Methane Emissions in Indianapolis, Indiana.

This paper describes process-based estimation of CH4 emissions from sources in Indianapolis, IN and compares these with atmospheric inferences of whole city emissions. Emissions from the natural gas distribution system were estimated from measurements at metering and regulating stations and from pipeline leaks. Tracer methods and inverse plume modeling were used to estimate emissions from the major landfill and wastewater treatment plant. These direct source measurements informed the compilation of a methane emission inventory for the city equal to 29 Gg/yr (5% to 95% confidence limits, 15 to 54 Gg/yr). Emission estimates for the whole city based on an aircraft mass balance method and from inverse modeling of CH4 tower observations were 41 ± 12 Gg/yr and 81 ± 11 Gg/yr, respectively. Footprint modeling using 11 days of ethane/methane tower data indicated that landfills, wastewater treatment, wetlands, and other biological sources contribute 48% while natural gas usage and other fossil fuel sources contribute 52% of the city total. With the biogenic CH4 emissions omitted, the top-down estimates are 3.5-6.9 times the nonbiogenic city inventory. Mobile mapping of CH4 concentrations showed low level enhancement of CH4 throughout the city reflecting diffuse natural gas leakage and downstream usage as possible sources for the missing residual in the inventory.

IL-22 regulation of functional gene expression in salivary gland cells.

TH17 cells and their associated signature cytokines, IL-17 and IL-22, are highly elevated in primary Sjögren's syndrome (pSjS). The levels of IL-22 present in sera showed significant correlations with many disease parameters, specifically hyposalivation, anti-SSB, anti-SSA/SSB, hypergammaglobulinemia and rheumatoid factor. The present study aims to examine the biological function of IL-22 on human salivary glands. To accomplish the goal, microarray analysis using the HumanHT-12 v4 Expression BeadChip was utilized to determine the biological function of IL-22. Differential expression analyses were conducted using the LIMMA package from the Bioconductor project. MTT assay, flow cytometry and Western blotting were used to identify the function of IL-22 on human salivary gland cells. Results indicate an extensive effect of IL-22 on many major molecular functions including activation of antimicrobial genes and downregulation of immune-associated pathways. Functional studies performed in-vitro using human salivary gland cells treated with IL-22 indicated a direct effect of IL-22 on cell cycling, specifically reducing cellular proliferation at the G2-M phase by activation of STAT3. These results suggest the important role of IL-22 in the salivary gland function. The present study suggests that IL-22 might be involved in regulating inflammation and controlling the cell proliferation in SjS.

Aircraft-Based Measurements of Point Source Methane Emissions in the Barnett Shale Basin.

We report measurements of methane (CH4) emission rates observed at eight different high-emitting point sources in the Barnett Shale, Texas, using aircraft-based methods performed as part of the Barnett Coordinated Campaign. We quantified CH4 emission rates from four gas processing plants, one compressor station, and three landfills during five flights conducted in October 2013. Results are compared to other aircraft- and surface-based measurements of the same facilities, and to estimates based on a national study of gathering and processing facilities emissions and 2013 annual average emissions reported to the U.S. EPA Greenhouse Gas Reporting Program (GHGRP). For the eight sources, CH4 emission measurements from the aircraft-based mass balance approach were a factor of 3.2-5.8 greater than the GHGRP-based estimates. Summed emissions totaled 7022 ± 2000 kg hr(-1), roughly 9% of the entire basin-wide CH4 emissions estimated from regional mass balance flights during the campaign. Emission measurements from five natural gas management facilities were 1.2-4.6 times larger than emissions based on the national study. Results from this study were used to represent "super-emitters" in a newly formulated Barnett Shale Inventory, demonstrating the importance of targeted sampling of "super-emitters" that may be missed by random sampling of a subset of the total.

Aircraft-Based Estimate of Total Methane Emissions from the Barnett Shale Region.

We present estimates of regional methane (CH4) emissions from oil and natural gas operations in the Barnett Shale, Texas, using airborne atmospheric measurements. Using a mass balance approach on eight different flight days in March and October 2013, the total CH4 emissions for the region are estimated to be 76 ± 13 × 10(3) kg hr(-1) (equivalent to 0.66 ± 0.11 Tg CH4 yr(-1); 95% confidence interval (CI)). We estimate that 60 ± 11 × 10(3) kg CH4 hr(-1) (95% CI) are emitted by natural gas and oil operations, including production, processing, and distribution in the urban areas of Dallas and Fort Worth. This estimate agrees with the U.S. Environmental Protection Agency (EPA) estimate for nationwide CH4 emissions from the natural gas sector when scaled by natural gas production, but it is higher than emissions reported by the EDGAR inventory or by industry to EPA's Greenhouse Gas Reporting Program. This study is the first to show consistency between mass balance results on so many different days and in two different seasons, enabling better quantification of the related uncertainty. The Barnett is one of the largest production basins in the United States, with 8% of total U.S. natural gas production, and thus, our results represent a crucial step toward determining the greenhouse gas footprint of U.S. onshore natural gas production.

Constructing a Spatially Resolved Methane Emission Inventory for the Barnett Shale Region.

Methane emissions from the oil and gas industry (O&G) and other sources in the Barnett Shale region were estimated by constructing a spatially resolved emission inventory. Eighteen source categories were estimated using multiple data sets, including new empirical measurements at regional O&G sites and a national study of gathering and processing facilities. Spatially referenced activity data were compiled from federal and state databases and combined with O&G facility emission factors calculated using Monte Carlo simulations that account for high emission sites representing the very upper portion, or fat-tail, in the observed emissions distributions. Total methane emissions in the 25-county Barnett Shale region in October 2013 were estimated to be 72,300 (63,400-82,400) kg CH4 h(-1). O&G emissions were estimated to be 46,200 (40,000-54,100) kg CH4 h(-1) with 19% of emissions from fat-tail sites representing less than 2% of sites. Our estimate of O&G emissions in the Barnett Shale region was higher than alternative inventories based on the United States Environmental Protection Agency (EPA) Greenhouse Gas Inventory, EPA Greenhouse Gas Reporting Program, and Emissions Database for Global Atmospheric Research by factors of 1.5, 2.7, and 4.3, respectively. Gathering compressor stations, which accounted for 40% of O&G emissions in our inventory, had the largest difference from emission estimates based on EPA data sources. Our inventory's higher O&G emission estimate was due primarily to its more comprehensive activity factors and inclusion of emissions from fat-tail sites.

Current concepts: mouse models of Sjögren's syndrome.

Sjögren's syndrome (SjS) is a complex chronic autoimmune disease of unknown etiology which primarily targets the exocrine glands, resulting in eventual loss of secretory function. The disease can present as either primary SjS or secondary SjS, the latter of which occurs concomitantly with another autoimmune disease such as rheumatoid arthritis, systemic lupus erythematosus, scleroderma, or primary biliary cirrhosis. Current advancements in therapeutic prevention and treatment for SjS are impeded by lack of understanding in the pathophysiological and clinical progression of the disease. Development of appropriate mouse models for both primary and secondary SjS is needed in order to advance knowledge of this disease. This paper details important features, advantages, and pitfalls of current animal models of SjS, including spontaneous, transgenic, knockout, immunization, and transplantation chimera mouse models, and emphasizes the need for a better model in representing the human SjS phenotype.