Estimating Top-down Emissions (2011-2014) of CH4 and CO2 From Los Angeles by an FTS Atop Mount Wilson

Megacities, such as Los Angeles, emit significant amount of anthropogenic greenhouse gases (GHGs). As the world's population in urban regions is expected to increase from over 50% now to 70% by 2050, monitoring the temporal trends of urban GHG emissions are necessary to verify regulation policy. Since megacities tend to have large spatially and temporally varying GHG emission characteristics, it is important to perform measurements which provide continuous spatio-temporal coverage of the domain. In this study, we demonstrate the ability to track major greenhouse gases, methane (CH4) and carbon dioxide (CO2) using ground-based remote sensing technique from Mount Wilson. Since 2010, in Los Angeles, a Fourier Transform Spectrometer (FTS) has been deployed on Mount Wilson to measure CO2, CH4, carbon monoxide (CO), the combustion tracer, and other tracer gases using reflected sunlight in the near-infrared spectral regions. Combining the unique vista from Mount Wilson and high-precision measurements from the FTS, the slant column abundances of these trace gases above and within the urban dome of Los Angeles are acquired. Within the urban dome, continuous daytime temporal and spatial measurements are recorded for 28 reflection points which are strategically located across the basin. Here we analyze the path-averaged dry air mixing ratios XCH4, XCO2 and XCO acquired by the FTS during a three-year period from 2011 to 2014. Using tracer-to-tracer correlation analysis, we investigate the ratios of XCH4:XCO2, XCH4:XCO and XCO:XCO2 in excess of the background values. Significant spatio-temporal variability in all three ratios is observed across the Los Angeles megacity during this measurement period. We then derive the top-down estimates of basin total CH4 and CO2 emissions between 2011 and 2014 using the existing bottom-up emission database of CO2and CO, and compare our estimates to the emissions reported by the state government and previous studies. Copyright 2014. California Institute of Technology. Government sponsorship acknowledged.