scholarly journals Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations

2020 ◽  
Vol 12 (3) ◽  
pp. 375 ◽  
Author(s):  
Rajesh Janardanan ◽  
Shamil Maksyutov ◽  
Aki Tsuruta ◽  
Fenjuan Wang ◽  
Yogesh K. Tiwari ◽  
...  
Keyword(s):  
United States ◽  
High Resolution ◽  
The United States ◽  
Methane Emissions ◽  
Inverse Model ◽  
Anthropogenic Emissions ◽  
Observation Data ◽  
Scale Analysis ◽  
Uncertainty Range ◽  
Natural Emissions

We employed a global high-resolution inverse model to optimize the CH4 emission using Greenhouse gas Observing Satellite (GOSAT) and surface observation data for a period from 2011–2017 for the two main source categories of anthropogenic and natural emissions. We used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission and scaled them by country to match the national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using the Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimated a global total anthropogenic and natural methane emissions of 340.9 Tg CH4 yr−1 and 232.5 Tg CH4 yr−1, respectively. Country-scale analysis of the estimated anthropogenic emissions showed that all the top-emitting countries showed differences with their respective inventories to be within the uncertainty range of the inventories, confirming that the posterior anthropogenic emissions did not deviate from nationally reported values. Large countries, such as China, Russia, and the United States, had the mean estimated emission of 45.7 ± 8.6, 31.9 ± 7.8, and 29.8 ± 7.8 Tg CH4 yr−1, respectively. For natural wetland emissions, we estimated large emissions for Brazil (39.8 ± 12.4 Tg CH4 yr−1), the United States (25.9 ± 8.3 Tg CH4 yr−1), Russia (13.2 ± 9.3 Tg CH4 yr−1), India (12.3 ± 6.4 Tg CH4 yr−1), and Canada (12.2 ± 5.1 Tg CH4 yr−1). In both emission categories, the major emitting countries all had the model corrections to emissions within the uncertainty range of inventories. The advantages of the approach used in this study were: (1) use of high-resolution transport, useful for simulations near emission hotspots, (2) prior anthropogenic emissions adjusted to the UNFCCC reports, (3) combining surface and satellite observations, which improves the estimation of both natural and anthropogenic methane emissions over spatial scale of countries.

Country scale analysis of natural and anthropogenic methane emissions with a high-resolution inverse model using GOSAT and ground-based observations

2020 ◽  
Author(s):  
Rajesh Janardanan ◽  
Shamil Maksyutov ◽  
Aki Tsuruta ◽  
Fenjuan Wang ◽  
Yogesh Tiwari ◽  
...  
Keyword(s):  
United States ◽  
High Resolution ◽  
The United States ◽  
Methane Emissions ◽  
Inverse Model ◽  
Anthropogenic Emissions ◽  
Observation Data ◽  
Scale Analysis ◽  
Uncertainty Range ◽  
Natural Emissions

<p>Here, we present the results of a global high-resolution inversion study of methane emissions and their analysis for the large emitting countries. We employ a global high-resolution inverse model to optimize CH<sub>4</sub> emissions using Greenhouse gas Observing Satellite (GOSAT) and surface observation data over the 2011-2017 period for the two main source categories of anthropogenic and natural emissions. As prior emissions, we used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission, scaled by country to match the national emissions reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimate a global total anthropogenic and natural methane emissions of 340.9 Tg CH<sub>4</sub> yr<sup>-1</sup> and 232.5 Tg CH<sub>4</sub> yr<sup>-1</sup>, respectively. This agrees with recent Global Carbon Project (GCP) estimates of 357 and 215 Tg CH<sub>4</sub> yr<sup>-1</sup>, respectively. Country-scale analysis of the estimated anthropogenic emissions shows that for all the top-emitting countries, differences with their respective nationally reported inventories are within the uncertainty range of the inventories. Large emitting countries such as China, Russia and the United States have mean estimated anthropogenic emission of 45.7±8.6, 31.9±7.8 and 29.8±7.8 Tg CH<sub>4</sub> yr<sup>-1 </sup>respectively. For natural emissions, we estimate large emissions for Brazil (39.8±12.4 Tg CH<sub>4</sub> yr<sup>-1</sup>), the United States (25.9±8.3 Tg CH<sub>4</sub> yr<sup>-1</sup>), Russia (13.2±9.3 Tg CH<sub>4</sub> yr<sup>-1</sup>), India (12.3±6.4 Tg CH<sub>4</sub> yr<sup>-1</sup>), and Canada (12.2±5.1 Tg CH<sub>4</sub> yr<sup>-1</sup>). In both emission categories, natural and anthropogenic, the major emitting countries all had model corrections to their emissions that were within the uncertainty range of the inventories and the inverse model uncertainty. As a special case, we evaluate anthropogenic emissions estimated for India (24.2±5.3 Tg yr<sup>-1</sup>) with aircraft observation data over urban regions over India. On average, the optimized profiles showed a better match with the observations compared to the prior profile confirming improved estimates by the model for India.</p>

scholarly journals Methane emissions in the United States, Canada, and Mexico: Evaluation of national methane emission inventories and sectoral trends by inverse analysis of in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) atmospheric observations

2021 ◽  
Author(s):  
Xiao Lu ◽  
Daniel J. Jacob ◽  
Haolin Wang ◽  
Joannes D. Maasakkers ◽  
Yuzhong Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
United States ◽  
Inverse Analysis ◽  
The United States ◽  
Methane Emissions ◽  
Anthropogenic Emissions ◽  
Emission Inventories ◽  
South Central ◽  
The Us

Abstract. We quantify methane emissions and their 2010–2017 trends by sector in the contiguous United States (CONUS), Canada, and Mexico by inverse analysis of in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) atmospheric methane observations. The inversion uses as prior estimate the national anthropogenic emission inventories for the three countries reported by the US Environmental Protection Agency (EPA), Environment and Climate Change Canada (ECCC), and the Instituto Nacional de Ecologia y Cambio Climatico (INECC) in Mexico to the United Nations Framework Convention on Climate Change (UNFCCC), and thus serves as an evaluation of these inventories in terms of their magnitudes and trends. Emissions are optimized with a Gaussian mixture model (GMM) at 0.5° × 0.625° resolution and for individual years. Optimization is done analytically using log-normal error forms. This yields closed-form statistics of error estimates and information content on the posterior (optimized) estimates, allows better representation of the high tail of the emission distribution, and enables construction of a large ensemble of inverse solutions using different observations and assumptions. We find that GOSAT and in situ observations are largely consistent and complementary in the optimization of methane emissions for North America. Mean 2010–2017 anthropogenic emissions from our base GOSAT + in situ inversion, with ranges from the inversion ensemble, are 36.9 (32.5–37.8) Tg a−1 for CONUS, 5.3 (3.6–5.7) Tg a−1 for Canada, and 6.0 (4.7–6.1) Tg a−1 for Mexico. These are higher than the most recent reported national inventories of 26.0 Tg a−1 for the US (EPA), 4.0 Tg a−1 for Canada (ECCC), and 5.0 Tg a−1 for Mexico (INECC). The correction in all three countries is largely driven by a factor of 2 underestimate in emissions from the oil sector with major contributions from the south-central US, western Canada, and southeast Mexico. Total CONUS anthropogenic emissions in our inversion peak in 2014, in contrast to the EPA report of a steady decreasing trend over 2010–2017. This reflects combined effects of increases in emissions from the oil and landfill sectors, decrease from the gas, and flat emissions from the livestock and coal sectors. We find decreasing trends in Canadian and Mexican anthropogenic methane emissions over the 2010–2017 period, mainly driven by oil and gas emissions. Our best estimates of mean 2010–2017 wetland emissions are 8.4 (6.4–10.6) Tg a−1 for CONUS, 9.9 (7.8–12.0) Tg a−1 for Canada, and 0.6 (0.4–0.6) Tg a−1 for Mexico. Wetland emissions in CONUS show an increasing trend of 2.6 (1.7–3.8) % a−1 over 2010–2017 correlated with precipitation.

Natural and anthropogenic methane emissions in West Siberia estimated using a wetland inventory, GOSAT and a regional tower network

2020 ◽  
Author(s):  
Shamil Maksyutov ◽  
Motoki Sasakawa ◽  
Rajesh Janardanan ◽  
Fenjuan Wang ◽  
Aki Tsuruta ◽  
...  
Keyword(s):  
High Resolution ◽  
West Siberia ◽  
Methane Emissions ◽  
Inverse Model ◽  
Anthropogenic Emissions ◽  
Taiga Zone ◽  
Tracer Transport ◽  
Bottom Up ◽  
Near Surface

&lt;p&gt;West Siberia contributes a large fraction of Russian methane emissions, with both natural emissions from peatlands and anthropogenic emissions by oil and gas industries. To quantify anthropogenic emissions with atmospheric observations and inventories, we must better understand the natural wetland emissions.&amp;#160; We combine high-resolution wetland mapping based on Landsat data for whole West Siberian lowland with a database of in situ flux measurements to derive bottom-up wetland emission estimates. We use a global high-resolution methane flux inversion based on a Lagrangian-Eulerian coupled tracer transport model to estimate methane emissions in West Siberia using atmospheric methane data collected at the Siberian GHG monitoring network JR-STATION, ZOTTO, data by the global in situ network and GOSAT satellite observations. High-resolution prior fluxes were prepared for anthropogenic emissions (EDGAR), biomass burning (GFAS), and wetlands (VISIT). A global high-resolution wetland emission dataset was constructed using 0.5-degree monthly emission data simulated by the VISIT model and wetland area fraction map by the Global Lake and Wetlands Database (GLWD). We estimate biweekly flux corrections to prior flux fields for 2010 to 2015. The inverse model optimizes corrections to two categories of fluxes: anthropogenic and natural (wetlands). Based on fitting the model simulations to the observations, the inverse model provides upward corrections to West Siberian anthropogenic emissions in winter and wetland emissions in summer. The use of high-resolution atmospheric transport in the flux inversion, when compared to low-resolution transport modeling, enables a better fit to observations in winter, when anthropogenic emissions dominate variability of the near-surface methane concentration. We estimate 15% higher anthropogenic emissions than EDGAR v.4.3.2 inventory for whole Russia, with most of the correction attributed to West Siberia and the European part of Russia. Comparison of the inversion estimates with the bottom-up wetland emission inventory for West Siberia suggests a need to adjust the wetland emissions to match observed north-south gradient of emissions with higher emissions in the southern taiga zone.&lt;/p&gt;

scholarly journals Methane emissions in the United States, Canada, and Mexico: evaluation of national methane emission inventories and 2010–2017 sectoral trends by inverse analysis of in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) atmospheric observations

2022 ◽  
Vol 22 (1) ◽  
pp. 395-418
Author(s):  
Xiao Lu ◽  
Daniel J. Jacob ◽  
Haolin Wang ◽  
Joannes D. Maasakkers ◽  
Yuzhong Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
United States ◽  
Inverse Analysis ◽  
The United States ◽  
Methane Emissions ◽  
Anthropogenic Emissions ◽  
Emission Inventories ◽  
South Central ◽  
The Us

Abstract. We quantify methane emissions and their 2010–2017 trends by sector in the contiguous United States (CONUS), Canada, and Mexico by inverse analysis of in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) atmospheric methane observations. The inversion uses as a prior estimate the national anthropogenic emission inventories for the three countries reported by the US Environmental Protection Agency (EPA), Environment and Climate Change Canada (ECCC), and the Instituto Nacional de Ecología y Cambio Climático (INECC) in Mexico to the United Nations Framework Convention on Climate Change (UNFCCC) and thus serves as an evaluation of these inventories in terms of their magnitudes and trends. Emissions are optimized with a Gaussian mixture model (GMM) at 0.5∘×0.625∘ resolution and for individual years. Optimization is done analytically using lognormal error forms. This yields closed-form statistics of error covariances and information content on the posterior (optimized) estimates, allows better representation of the high tail of the emission distribution, and enables construction of a large ensemble of inverse solutions using different observations and assumptions. We find that GOSAT and in situ observations are largely consistent and complementary in the optimization of methane emissions for North America. Mean 2010–2017 anthropogenic emissions from our base GOSAT + in situ inversion, with ranges from the inversion ensemble, are 36.9 (32.5–37.8) Tg a−1 for CONUS, 5.3 (3.6–5.7) Tg a−1 for Canada, and 6.0 (4.7–6.1) Tg a−1 for Mexico. These are higher than the most recent reported national inventories of 26.0 Tg a−1 for the US (EPA), 4.0 Tg a−1 for Canada (ECCC), and 5.0 Tg a−1 for Mexico (INECC). The correction in all three countries is largely driven by a factor of 2 underestimate in emissions from the oil sector with major contributions from the south-central US, western Canada, and southeastern Mexico. Total CONUS anthropogenic emissions in our inversion peak in 2014, in contrast to the EPA report of a steady decreasing trend over 2010–2017. This reflects offsetting effects of increasing emissions from the oil and landfill sectors, decreasing emissions from the gas sector, and flat emissions from the livestock and coal sectors. We find decreasing trends in Canadian and Mexican anthropogenic methane emissions over the 2010–2017 period, mainly driven by oil and gas emissions. Our best estimates of mean 2010–2017 wetland emissions are 8.4 (6.4–10.6) Tg a−1 for CONUS, 9.9 (7.8–12.0) Tg a−1 for Canada, and 0.6 (0.4–0.6) Tg a−1 for Mexico. Wetland emissions in CONUS show an increasing trend of +2.6 (+1.7 to +3.8)% a−1 over 2010–2017 correlated with precipitation.

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

2014 ◽  
Vol 49 (1) ◽  
pp. 641-648 ◽  
Author(s):  
David T. Allen ◽  
David W. Sullivan ◽  
Daniel Zavala-Araiza ◽  
Adam P. Pacsi ◽  
Matthew Harrison ◽  
...  
Keyword(s):  
United States ◽  
Natural Gas ◽  
The United States ◽  
Methane Emissions ◽  
Gas Production ◽  
Process Equipment ◽  
Natural Gas Production

scholarly journals Evaluation of high-resolution simulations of daily-scale temperature and precipitation over the United States

2009 ◽  
Vol 33 (7-8) ◽  
pp. 1131-1147 ◽  
Author(s):  
Megan D. Walker ◽  
Noah S. Diffenbaugh
Keyword(s):  
United States ◽  
High Resolution ◽  
The United States ◽  
Temperature And Precipitation ◽  
Scale Temperature ◽  
Daily Scale

scholarly journals The extensive episode of derecho-producing convective systems in the United States during May and June 1998: A multi-scale analysis and review

2007 ◽  
Vol 14 (3) ◽  
pp. 227-244 ◽  
Author(s):  
Walker S. Ashley ◽  
Thomas L. Mote ◽  
Mace L. Bentley
Keyword(s):  
United States ◽  
The United States ◽  
Scale Analysis ◽  
Convective Systems ◽  
Multi Scale ◽  
Multi Scale Analysis

scholarly journals Exploring the nature of air quality over southwestern Ontario: main findings from the Border Air Quality and Meteorology Study

2013 ◽  
Vol 13 (20) ◽  
pp. 10461-10482 ◽  
Author(s):  
J. R. Brook ◽  
P. A. Makar ◽  
D. M. L. Sills ◽  
K. L. Hayden ◽  
R. McLaren
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Great Lakes ◽  
The United States ◽  
Urban Heat Islands ◽  
Anthropogenic Emissions ◽  
Lake Breeze ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Quality Model

Abstract. This paper serves as an overview and discusses the main findings from the Border Air Quality and Meteorology Study (BAQS-Met) in southwestern Ontario in 2007. This region is dominated by the Great Lakes, shares borders with the United States and consistently experiences the highest ozone (O3) and fine particulate matter concentrations in Canada. The purpose of BAQS-Met was to improve our understanding of how lake-driven meteorology impacts air quality in the region, and to improve models used for forecasting and policy scenarios. Results show that lake breeze occurrence frequencies and inland penetration distances were significantly greater than realized in the past. Due to their effect on local meteorology, the lakes were found to enhance secondary O3 and aerosol formation such that local anthropogenic emissions have their impact closer to the populated source areas than would otherwise occur in the absence of the lakes. Substantial spatial heterogeneity in O3 was observed with local peaks typically 30 ppb above the regional values. Sulfate and secondary organic aerosol (SOA) enhancements were also linked to local emissions being transported in the lake breeze circulations. This study included the first detailed evaluation of regional applications of a high-resolution (2.5 km grid) air quality model in the Great Lakes region. The model showed that maxima in secondary pollutants occur in areas of convergence, in localized updrafts and in distinct pockets over the lake surfaces. These effects are caused by lake circulations interacting with the synoptic flow, with each other or with circulations induced by urban heat islands. Biogenic and anthropogenic emissions were both shown to play a role in the formation of SOA in the region. Detailed particle measurements and multivariate receptor models reveal that while individual particles are internally mixed, they often exist within more complex external mixtures. This makes it difficult to predict aerosol optical properties and further highlights the challenges facing aerosol modelling. The BAQS-Met study has led to a better understanding of the value of high-resolution (2.5 km) modelling for air quality and meteorological predictions and has led to several model improvements.

scholarly journals Non-targeted Screening of Commercial CBD Products in the United States Reveals Common Contamination and Adulteration

2020 ◽  
Author(s):  
Ben Orsburn
Keyword(s):  
United States ◽  
Mass Spectrometry ◽  
High Resolution ◽  
The United States ◽  
Mass Spectrometry Data ◽  
Accurate Mass ◽  
Targeted Screening ◽  
Accurate Mass Spectrometry ◽  
High Concentrations ◽  
High Resolution Accurate Mass

AbstractThe production of hemp and products derived from these plants that contain zero to trace amounts of the psychoactive cannabinoid tetrahydrocannabidiol (THC) is a rapidly growing new market in the United States. The most common products today contain relatively high concentrations of the compound cannabidiol (CBD). Recent studies have investigated commercial CBD products using targeted assays and have found varying degrees of misrepresentation and contamination of these products. To expand on previous studies, we demonstrate the application of non-targeted screening by high resolution accurate mass spectrometry to more comprehensively identify potential adulterants and contaminants. We find evidence to support previous conclusions that CBD products are commonly misrepresented in terms of cannabinoid concentrations present. Specifically, we observe a wide variation in relative THC concentrations across the product tested, with some products containing 10-fold more relative signal than others. In addition, we find that several products appear to be purposely adulterated with over the counter drugs such as caffeine and melatonin. We also observe multiple small molecule contaminants that are typically linked to improper production or packaging methods in food or pharmaceutical production. Finally, we present high resolution accurate mass spectrometry data and tandem MS/MS fragments supporting the presence of trace amounts of fluorofentanyl in a single mail order CBD product. We conclude that the CBD industry would benefit from more robust testing regulations and that the cannabis testing industry, in general, would benefit from the use of non-targeted screening technologies.

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