Atmospheric emissions and air quality impacts of natural gas production from shale formations

textNatural gas is at the core of the energy supply and security debates; new extraction technologies, such as horizontal drilling and hydraulic fracturing, have expanded natural gas production. As with any energy system, however, natural gas has an environmental footprint and this thesis examines the air quality impacts of natural gas production. Greenhouse gas (GHG), criteria pollutant, and toxic emissions from natural gas production have been subject to a great amount of uncertainty, largely due to limited measurements of emission rates from key sources. This thesis reports direct and indirect measurements of emissions, assessing the spatial and temporal distributions of emissions, as well as the role of very high emitting wells and high emitting sources in determining national emissions. Direct measurements are used to identify, characterize and classify the most important sources of continuous and episodic emissions, and to analyze mitigation opportunities. Methods are proposed and demonstrated for reconciling these direct measurements of emissions from sources with measurements of ambient concentrations. Collectively, the direct source measurements, and analyses of ambient air pollutant measurements in natural gas production regions reported in this work improve the estimation, characterization, and methods for monitoring air quality implications of shale gas production.Chemical Engineerin

Satellites Detect Abatable Super-Emissions in One of the World¿s Largest Methane Hotspot Regions

[EN] Reduction of fossil fuel-related methane emissions has been identified as an essential means for climate change mitigation, but emission source identification remains elusive for most oil and gas production basins in the world. We combine three complementary satellite data sets to survey single methane emission sources on the west coast of Turkmenistan, one of the largest methane hotspots in the world. We found 29 different emitters, with emission rates >1800 kg/h, active in the 2017¿2020 time period, although older satellite data show that this type of emission has been occurring for decades. We find that all sources are linked to extraction fields mainly dedicated to crude oil production, where 24 of them are inactive flares venting gas. The analysis of time series suggests a causal relationship between the decrease in flaring and the increase in venting. At the regional level, 2020 shows a substantial increase in the number of methane plume detections concerning previous years. Our results suggest that these large venting point sources represent a key mitigation opportunity as they emanate from human-controlled facilities, and that new satellite methods promise a revolution in the detection and monitoring of methane point emissions worldwide.The authors thank the team that realized the TROPOMI instrument and its data products, consisting of the partnership between Airbus Defense and Space Netherlands, KNMI, SRON, and TNO, commissioned by NSO and ESA. Sentinel-5 Precursor is part of the EU Copernicus program, Copernicus (modified) Sentinel-5P data (2018-2020) have been used. We thank the Sentinel Hub service for providing the EO Browser service. Thanks to the Environmental Defense Fund (EDF) for providing data about the O&G fields of the study area, and the Carbon Limits group for contributing to the verification of the emission sources. We thank the Italian Space Agency for the PRISMA data used in this work. Dr. Yongguang Zhang from the University of Nanjing is also thanked for his support to get access to ZY1 AHSI data, and Dr. Javier Gorrono from Universitat Politecnica de Valencia for his assistance in the uncertainty estimations. Authors Itziar Irakulis-Loitxate and Luis Guanter received funding from ESA Contract 4000134929.Irakulis-Loitxate, I.; Guanter-Palomar, LM.; Joannes D. Maasakkers; Daniel Zavala-Araiza; Ilse Aben (2022). Satellites Detect Abatable Super-Emissions in One of the World¿s Largest Methane Hotspot Regions. Environmental Science & Technology (Online). 56(4):2143-2152. https://doi.org/10.1021/acs.est.1c048732143215256

Quantification of methane emission rate from oil and gas wells in Romania using ground-based measurement techniques

The ROMEO campaign (ROmanian Methane Emissions from Oil and gas) focused on measurements of methane (CH4) emission rates from oil and natural gas (O&G) production in Romania. The campaign took place in October 2019 and covered the southern part of Romania around the cities Bucharest, Ploiesti, Pitesti, and Craiova. This study presents emission rates calculated from mobile in situ measurement of CH4 and wind measurements using the Other Test Method 33a from U.S. Environmental Protection Agency and the Gaussian Plume Method. These methods were used to determine emission rates from 112 O&G well sites and other production-related facilities. Estimated mean CH4 emission rate with a 95% confidence interval equals 0.49 [0.35, 0.71] kg CH4 h-1 per site; 10% of all quantified sites account for 56% of the estimated emission rates. In addition, more than 1,000 O&G sites were visited for a qualitative “screening” (CH4 detection without quantification). Analysis of the screening data shows that 65% of the sites emitted methane at detectable rates. The CH4 emission rates obtained during the ROMEO campaign are comparable to the methane emission rates in study carried out in other Romanian regions

Methane Emissions from Process Equipment at Natural Gas Production Sites in the United States: Liquid Unloadings

Methane emissions from liquid unloadings were measured at 107 wells in natural gas production regions throughout the United States. Liquid unloadings clear wells of accumulated liquids to increase production, employing a variety of liquid lifting mechanisms. In this work, wells with and without plunger lifts were sampled. Most wells without plunger lifts unload less than 10 times per year with emissions averaging 21 000–35 000 scf methane (0.4–0.7 Mg) per event (95% confidence limits of 10 000–50 000 scf/event). For wells with plunger lifts, emissions averaged 1000–10 000 scf methane (0.02–0.2 Mg) per event (95% confidence limits of 500–12 000 scf/event). Some wells with plunger lifts are automatically triggered and unload thousands of times per year and these wells account for the majority of the emissions from all wells with liquid unloadings. If the data collected in this work are assumed to be representative of national populations, the data suggest that the central estimate of emissions from unloadings (270 Gg/yr, 95% confidence range of 190–400 Gg) are within a few percent of the emissions estimated in the EPA 2012 Greenhouse Gas National Emission Inventory (released in 2014), with emissions dominated by wells with high frequencies of unloadings

Short-term methane emissions from two dairy farms in California estimated by different measurement techniques and US Environmental Protection Agency inventory methodology: A case study

Atmospheric top-down measurements have attributed up to twice the methane (CH4) emissions of bottom-up (BU) inventories to dairy production. We explored this discrepancy by estimating CH4 emissions of two dairy facilities in California with U.S. Environmental Protection Agency (USEPA) methodology, which is used for BU inventories, and three independent measurement techniques: 1) open-path measurements with inverse dispersion modeling (hereafter “open-path”); 2) vehicle measurements with tracer flux ratio method; and 3) aircraft measurements with closed-path method. All three techniques estimated whole farm CH4 emissions during one week in the summer of 2016. In addition, open-path also estimated whole farm CH4 emissions during two months in the winter of 2017. The objectives of the present study were: 1) to compare the different techniques to measure whole farm CH4 emissions from dairies, 2) to estimate CH4 emissions from animal housing and liquid manure storage, and compare them to USEPA inventory estimates, and 3) to compare CH4 emissions between the two dairies. Whole farm CH4 estimates were similar among measurement techniques. No seasonality was detected for CH4 emissions from animal housing, but CH4 emissions from liquid manure storage were three to six times greater during the summer than during the winter. Open-path estimates for liquid manure storage emissions were similar to monthly USEPA estimates during the summer but not during the winter, and neither open-path estimates from summer nor winter were similar to the annual USEPA estimate. Thus, CH4 emissions need to be measured throughout the year to evaluate annual inventories. Methane yields from housing and liquid manure storage were used to compare emissions between the farms. While CH4 yields from animal housing were similar (on average 20.9 g CH4/kg dry matter intake), CH4 yields from liquid manure storage at one dairy were 1.7 and 3.5 times greater than at the other dairy during summer (234 vs. 137 g CH4/kg volatile solids [VS]) and winter (78 vs. 22 g CH4/kg VS), respectively. This greater CH4 yield was attributed to the greater proportion of manure stored in liquid form, which suggests that the promotion of manure management practices that reduce the amount of manure solids stored in liquid form, such as manure separators, could significantly reduce CH4 emissions from dairies. These results demonstrate that multiple techniques for monitoring emissions on these farms were comparable

High nitrous oxide fluxes from rice indicate the need to manage water for both long- and short-term climate impacts

Global rice cultivation is estimated to account for 2.5% of current anthropogenic warming because of emissions of methane (CH4), a short-lived greenhouse gas. This estimate assumes a widespread prevalence of continuous flooding of most rice fields and hence does not include emissions of nitrous oxide (N2O), a long-lived greenhouse gas. Based on the belief that minimizing CH4 from rice cultivation is always climate beneficial, current mitigation policies promote increased use of intermittent flooding. However, results from five intermittently flooded rice farms across three agroecological regions in India indicate that N2O emissions per hectare can be three times higher (33 kg-N2O⋅ha−1⋅season−1) than the maximum previously reported. Correlations between N2O emissions and management parameters suggest that N2O emissions from rice across the Indian subcontinent might be 30–45 times higher under intensified use of intermittent flooding than under continuous flooding. Our data further indicate that comanagement of water with inorganic nitrogen and/or organic matter inputs can decrease climate impacts caused by greenhouse gas emissions up to 90% and nitrogen management might not be central to N2O reduction. An understanding of climate benefits/drawbacks over time of different flooding regimes because of differences in N2O and CH4 emissions can help select the most climate-friendly water management regimes for a given area. Region-specific studies of rice farming practices that map flooding regimes and measure effects of multiple comanaged variables on N2O and CH4 emissions are necessary to determine and minimize the climate impacts of rice cultivation over both the short term and long term

Night-time lights: A global, long term look at links to socio-economic trends

We use a parallelized spatial analytics platform to process the twenty-one year totality of the longest-running time series of night-time lights data—the Defense Meteorological Satellite Program (DMSP) dataset—surpassing the narrower scope of prior studies to assess changes in area lit of countries globally. Doing so allows a retrospective look at the global, long-term relationships between night-time lights and a series of socio-economic indicators. We find the strongest correlations with electricity consumption, CO2 emissions, and GDP, followed by population, CH4 emissions, N2O emissions, poverty (inverse) and F-gas emissions. Relating area lit to electricity consumption shows that while a basic linear model provides a good statistical fit, regional and temporal trends are found to have a significant impact

Comparisons of Airborne Measurements and Inventory Estimates of Methane Emissions in the Alberta Upstream Oil and Gas Sector

Airborne measurements of methane emissions from oil and gas infrastructure were completed over two regions of Alberta, Canada. These top-down measurements were directly compared with region-specific bottom-up inventories that utilized current industry-reported flaring and venting volumes (reported data) and quantitative estimates of unreported venting and fugitive sources. For the 50 × 50 km measurement region near Red Deer, characterized by natural gas and light oil production, measured methane fluxes were more than 17 times greater than that derived from directly reported data but consistent with our region-specific bottom-up inventory-based estimate. For the 60 × 60 km measurement region near Lloydminster, characterized by significant cold heavy oil production with sand (CHOPS), airborne measured methane fluxes were five times greater than directly reported emissions from venting and flaring and four times greater than our region-specific bottom up inventory-based estimate. Extended across Alberta, our results suggest that reported venting emissions in Alberta should be 2.5 ± 0.5 times higher, and total methane emissions from the upstream oil and gas sector (excluding mined oil sands) are likely at least 25−50% greater than current government estimates. Successful mitigation efforts in the Red Deer region will need to focus on the \u3e90% of methane emissions currently unmeasured or unreported

Correlation between area lit and a collection of socio-economic indicators.

<p>The matrix above shows links between logarithms of Area Lit, GDP, Electric Power Consumption, Population, CO₂ Emissions, N₂O Emissions, CH₄ Emissions, F-gas Emissions, and non-log Poverty Headcount Ratio, respectively. Numbers on the top-right side of the matrix denote Pearson’s <b><i>r</i></b> values (font size <b><i>∝</i></b> value), and stars represent significance level (***, <b><i>p</i> < 0.05</b>).</p