Observation of CH4 and other Non-CO2 Green House Gas Emissions from California

Abstract

PrefaceThe California Energy Commission's Public Interest Energy Research (PIER) Program supports public interest energy research and development that will help improve the quality of life in California by bringing environmentally safe, affordable, and reliable energy services and products to the marketplace.The PIER Program conducts public interest research, development, and demonstration (RD&D) projects to benefit California.The PIER Program strives to conduct the most promising public interest energy research by partnering with RD&D entities, including individuals, businesses, utilities, and public or private research institutions.• PIER funding efforts are focused on the following RD&D program areas:• Buildings End Use Energy Efficiency AbstractIn 2006, California passed the landmark assembly bill AB-32 to reduce California's emissions of greenhouse gases (GHGs) that contribute to global climate change. AB-32 commits California to reduce total GHG emissions to 1990 levels by 2020, a reduction of 25 percent from current levels. To verify that GHG emission reductions are actually taking place, it will be necessary to measure emissions. We describe atmospheric inverse model estimates of GHG emissions obtained from the California Greenhouse Gas Emissions Measurement (CALGEM) project. In collaboration with NOAA, we are measuring the dominant long-lived GHGs at two tall-towers in central California. Here, we present estimates of CH4 emissions obtained by statistical comparison of measured and predicted atmospheric mixing ratios. The predicted mixing ratios are calculated using spatially resolved a priori CH4 emissions and surface footprints, that provide a proportional relationship between the surface emissions and the mixing ratio signal at tower locations. The footprints are computed using the Weather Research and Forecast (WRF) coupled to the Stochastic Time-Inverted Lagrangian Transport (STILT) model. Integral to the inverse estimates, we perform a quantitative analysis of errors in atmospheric transport and other factors to provide quantitative uncertainties in estimated emissions. Regressions of modeled and measured mixing ratios suggest that total CH4 emissions are within 25% of the inventory estimates. A Bayesian source sector analysis obtains posterior scaling factors for CH4 emissions, indicating that emissions from several of the sources (e.g., landfills, natural gas use, petroleum production, crops, and wetlands) are roughly consistent with inventory estimates, but livestock emissions are significantly higher than the inventory. A Bayesian "region" analysis is used to identify spatial variations in CH4 emissions from 13 sub-regions within California. Although, only regions near the tower are significantly constrained by the tower measurements, CH4 emissions from the south Central Valley appear to be underestimated in a manner consistent with the under-prediction of livestock emissions. Finally, we describe a pseudo-experiment using predicted CH4 signals to explore the uncertainty reductions that might...

Seasonal variation of CH4 emissions from central California

“…As described above, it appears that the different emissions models combined with the time varying footprints produce posterior emission sums that (1) peak in different regions and seasons and (2) contain anticorrelations among regions which limit unique spatial attribution of emissions. This type of anticorrelation in posterior emission estimates for different regions has been reported in the inversion results of Bergamaschi et al [2005], and suggests that a network of measurement stations will be required to accurately resolve the spatial distributions of CH 4 emissions over the state of California [ Fischer et al , 2009].…”

Pollutant transport among California regions

“…[15] Measurements of CO and other trace gases are conducted as part of the California Greenhouse Gas Emissions Measurement (CALGEM) project continuously at three levels (31, 91, and 483 m agl) on a tall tower (121.4911 W, 38.2650 N, 0 m above sea level (asl)) near Walnut Grove, California (WGC) in the Sacramento river delta [Fischer et al, 2009;Jeong et al, 2012]. Figure 6 shows the time series of measured CO (at 31 m agl) and simulated CO tracer at WGC.…”

Climate Change Governance in India: Mapping the Role of the Cities

“…This is problematic because, while it will mitigate the longterm effects of climate change, it will have little effect on the emissions already emitted in previous decades as a result of the continued use of fossil fuels. Since 1751, the world has emitted over 1.5 trillion tonnes of CO 2 , and these emissions are responsible for nearly all of the warming (Ritchie and Roser, 2020).…”