scholarly journals Top-down estimate of methane emissions in California using a mesoscale inverse modeling technique: The San Joaquin Valley

2017 ◽  
Vol 122 (6) ◽  
pp. 3686-3699 ◽  
Author(s):  
Yu Yan Cui ◽  
Jerome Brioude ◽  
Wayne M. Angevine ◽  
Jeff Peischl ◽  
Stuart A. McKeen ◽  
...  
Keyword(s):  
Inverse Modeling ◽  
Methane Emissions ◽  
San Joaquin Valley ◽  
Modeling Technique ◽  
Top Down

scholarly journals Top-down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin

2015 ◽  
Vol 120 (13) ◽  
pp. 6698-6711 ◽  
Author(s):  
Yu Yan Cui ◽  
Jerome Brioude ◽  
Stuart A. McKeen ◽  
Wayne M. Angevine ◽  
Si-Wan Kim ◽  
...  
Keyword(s):  
Inverse Modeling ◽  
Methane Emissions ◽  
South Coast ◽  
Modeling Technique ◽  
The South ◽  
Top Down ◽  
South Coast Air Basin

scholarly journals Emissions of organic carbon and methane from petroleum and dairy operations in California's San Joaquin Valley

2013 ◽  
Vol 13 (10) ◽  
pp. 28225-28278 ◽  
Author(s):  
D. R. Gentner ◽  
T. B. Ford ◽  
A. Guha ◽  
K. Boulanger ◽  
J. Brioude ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Organic Carbon ◽  
Gas Phase ◽  
Organic Compounds ◽  
Methane Emissions ◽  
San Joaquin Valley ◽  
Motor Vehicles ◽  
Meteorological Model ◽  
Wide Range ◽  
Petroleum Extraction

Abstract. Petroleum and dairy operations are prominent sources of gas-phase organic compounds in California's San Joaquin Valley. Ground site measurements in Bakersfield and aircraft measurements of reactive gas-phase organic compounds were made in this region as part of the CalNex (California Research at the Nexus of Air Quality and Climate Change) project to determine the sources contributing to regional gas-phase organic carbon emissions. Using a combination of near-source and downwind data, we assess the composition and magnitude of emissions from these prominent sources that are relatively understudied compared to motor vehicles We also developed a statistical modeling method with the FLEXPART-WRF transport and meteorological model using ground-based data to assess the spatial distribution of emissions in the San Joaquin Valley. We present evidence for large sources of paraffinic hydrocarbons from petroleum extraction/processing operations and oxygenated compounds from dairy (and other cattle) operations. In addition to the small straight-chain alkanes typically associated with petroleum operations, we observed a wide range of branched and cyclic alkanes that have limited previous in situ measurements or characterization in emissions from petroleum operations. Observed dairy emissions were dominated by ethanol, methanol, and acetic acid, and methane. Dairy operations were responsible for the vast majority of methane emissions in the San Joaquin Valley; observations of methane were well-correlated with non-vehicular ethanol, and multiple assessments of the spatial distribution of emissions in the San Joaquin Valley highlight the dominance of dairy operations for methane emissions. The good agreement of the observed petroleum operations source profile with the measured composition of non-methane hydrocarbons in unrefined natural gas associated with crude oil suggests a fugitive emissions pathway during petroleum extraction, storage, or processing with negligible coincident methane emissions Aircraft observations of emission hotspots from operations at oil wells and dairies are consistent with the statistical source footprint determined via transport modeling and ground-based data. At Bakersfield, petroleum and dairy operations each comprised 22–23% of anthropogenic non-methane organic carbon and were each responsible for ~12% of potential precursors to ozone, but their direct impacts as potential SOA precursors were estimated to be minor. A comparison with the California Air Resources Board emission inventory supports the current relative emission rates of reactive organic gases from these sources in the region.

scholarly journals Variability and quasi-decadal changes in the methane budget over the period 2000–2012

2017 ◽  
Author(s):  
Marielle Saunois ◽  
Philippe Bousquet ◽  
Benjamin Poulter ◽  
Anna Peregon ◽  
Philippe Ciais ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Methane Emissions ◽  
Data Driven ◽  
Atmospheric Methane ◽  
Top Down ◽  
Bottom Up ◽  
Ch4 Emissions ◽  
Ensemble Mean ◽  
The Mean ◽  
The Tropics

Abstract. Following the recent Global Carbon project (GCP) synthesis of the decadal methane (CH4) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling frameworks) and bottom-up models, inventories, and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seems to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the EDGARv4.2 inventory, which should be revised to smaller values in a near future. Though the sectorial partitioning of six individual top-down studies out of eight are not consistent with the observed change in atmospheric 13CH4, the partitioning derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that, the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. Besides, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. The methane loss (in particular through OH oxidation) has not been investigated in detail in this study, although it may play a significant role in the recent atmospheric methane changes.

scholarly journals Inverse modeling of black carbon emissions over China using ensemble data assimilation

2016 ◽  
Vol 16 (2) ◽  
pp. 989-1002 ◽  
Author(s):  
P. Wang ◽  
H. Wang ◽  
Y. Q. Wang ◽  
X. Y. Zhang ◽  
S. L. Gong ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Black Carbon ◽  
Atmospheric Chemistry ◽  
Inverse Modeling ◽  
Optimal Interpolation ◽  
Top Down ◽  
Bottom Up ◽  
Error Matrix ◽  
Ensemble Data Assimilation ◽  
Ensemble Data

Abstract. Emissions inventories of black carbon (BC), which are traditionally constructed using a bottom-up approach based on activity data and emissions factors, are considered to contain a large level of uncertainty. In this paper, an ensemble optimal interpolation (EnOI) data assimilation technique is used to investigate the possibility of optimally recovering the spatially resolved emissions bias of BC. An inverse modeling system for emissions is established for an atmospheric chemistry aerosol model and two key problems related to ensemble data assimilation in the top-down emissions estimation are discussed: (1) how to obtain reasonable ensembles of prior emissions and (2) establishing a scheme to localize the background-error matrix. An experiment involving 1-year-long simulation cycle with EnOI inversion of BC emissions is performed for 2008. The bias of the BC emissions intensity in China at each grid point is corrected by this inverse system. The inverse emission over China in January is 240.1 Gg, and annual emission is about 2539.3 Gg, which is about 1.8 times of bottom-up emission inventory. The results show that, even though only monthly mean BC measurements are employed to inverse the emissions, the accuracy of the daily model simulation improves. Using top-down emissions, the average root mean square error of simulated daily BC is decreased by nearly 30 %. These results are valuable and promising for a better understanding of aerosol emissions and distributions, as well as aerosol forecasting.

scholarly journals Emissions of organic carbon and methane from petroleum and dairy operations in California's San Joaquin Valley

2014 ◽  
Vol 14 (10) ◽  
pp. 4955-4978 ◽  
Author(s):  
D. R. Gentner ◽  
T. B. Ford ◽  
A. Guha ◽  
K. Boulanger ◽  
J. Brioude ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Air Quality ◽  
Organic Carbon ◽  
Gas Phase ◽  
Organic Compounds ◽  
Methane Emissions ◽  
Modeling Method ◽  
San Joaquin Valley ◽  
Source Profiles ◽  
Source Profile

Abstract. Petroleum and dairy operations are prominent sources of gas-phase organic compounds in California's San Joaquin Valley. It is essential to understand the emissions and air quality impacts of these relatively understudied sources, especially for oil/gas operations in light of increasing US production. Ground site measurements in Bakersfield and regional aircraft measurements of reactive gas-phase organic compounds and methane were part of the CalNex (California Research at the Nexus of Air Quality and Climate Change) project to determine the sources contributing to regional gas-phase organic carbon emissions. Using a combination of near-source and downwind data, we assess the composition and magnitude of emissions, and provide average source profiles. To examine the spatial distribution of emissions in the San Joaquin Valley, we developed a statistical modeling method using ground-based data and the FLEXPART-WRF transport and meteorological model. We present evidence for large sources of paraffinic hydrocarbons from petroleum operations and oxygenated compounds from dairy (and other cattle) operations. In addition to the small straight-chain alkanes typically associated with petroleum operations, we observed a wide range of branched and cyclic alkanes, most of which have limited previous in situ measurements or characterization in petroleum operation emissions. Observed dairy emissions were dominated by ethanol, methanol, acetic acid, and methane. Dairy operations were responsible for the vast majority of methane emissions in the San Joaquin Valley; observations of methane were well correlated with non-vehicular ethanol, and multiple assessments of the spatial distribution of emissions in the San Joaquin Valley highlight the dominance of dairy operations for methane emissions. The petroleum operations source profile was developed using the composition of non-methane hydrocarbons in unrefined natural gas associated with crude oil. The observed source profile is consistent with fugitive emissions of condensate during storage or processing of associated gas following extraction and methane separation. Aircraft observations of concentration hotspots near oil wells and dairies are consistent with the statistical source footprint determined via our FLEXPART-WRF-based modeling method and ground-based data. We quantitatively compared our observations at Bakersfield to the California Air Resources Board emission inventory and find consistency for relative emission rates of reactive organic gases between the aforementioned sources and motor vehicles in the region. We estimate that petroleum and dairy operations each comprised 22% of anthropogenic non-methane organic carbon at Bakersfield and were each responsible for 8–13% of potential precursors to ozone. Yet, their direct impacts as potential secondary organic aerosol (SOA) precursors were estimated to be minor for the source profiles observed in the San Joaquin Valley.

scholarly journals Trends and inter-annual variability of methane emissions derived from 1979-1993 global CTM simulations

2003 ◽  
Vol 3 (1) ◽  
pp. 73-88 ◽  
Author(s):  
F. Dentener ◽  
M. van Weele ◽  
M. Krol ◽  
S. Houweling ◽  
P. van Velthoven
Keyword(s):  
Transport Model ◽  
Meteorological Data ◽  
Stratospheric Ozone ◽  
Methane Emissions ◽  
Anthropogenic Emission ◽  
Top Down ◽  
Bottom Up ◽  
Annual Variability ◽  
The Difference ◽  
Ozone Precursor

Abstract. The trend and interannual variability of methane sources are derived from multi-annual simulations of tropospheric photochemistry using a 3-D global chemistry-transport model. Our semi-inverse analysis uses the fifteen years (1979--1993) re-analysis of ECMWF meteorological data and annually varying emissions including photo-chemistry, in conjunction with observed CH4 concentration distributions and trends derived from the NOAA-CMDL surface stations. Dividing the world in four zonal regions (45--90 N, 0--45 N, 0--45 S, 45--90 S) we find good agreement in each region between (top-down) calculated emission trends from model simulations and (bottom-up) estimated anthropogenic emission trends based on the EDGAR global anthropogenic emission database, which amounts for the period 1979--1993 2.7 Tg CH4 yr-1. Also the top-down determined total global methane emission compares well with the total of the bottom-up estimates. We use the difference between the bottom-up and top-down determined emission trends to calculate residual emissions. These residual emissions represent the inter-annual variability of the methane emissions. Simulations have been performed in which the year-to-year meteorology, the emissions of ozone precursor gases, and the stratospheric ozone column distribution are either varied, or kept constant. In studies of methane trends it is most important to include the trends and variability of the oxidant fields. The analyses reveals that the variability of the emissions is of the order of 8Tg CH4 yr-1, and likely related to wetland emissions and/or biomass burning.

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