Abstract
Carbon monoxide (CO) is regarded as a useful tracer of biomass burning and anthropogenic pollution, so CO measurements can provide valuable information about the intensity of various anthropogenic activities. However, the emission estimates of CO based on inventories are associated with high uncertainties, especially in China. As CO is co-emitted with CO2 in the combustion of carbonaceous fuels, the relationship between CO and CO2 is often used to estimate regional CO emissions. Hefei is located in the area of eastern central China, which is one of the most industrialized regions in China, with severe regional air pollution. The enhancement slopes of ∆CO to ∆CO2 were calculated and compared from ground-based remote sensing observations, surface in-situ measurements, satellite and emission inventory data at the Hefei site during the period from September 2015 to August 2017. Both inventory based ratios of ΔCO to ΔCO2 are significantly larger than the ratios based on the observation data, including Fourier Transform Spectrometer (FTS) data, in-situ data, and satellite data. Further the CO emissions in the central China were estimated from the enhancement slopes of ∆CO/∆CO2 combined with the CO2 emission inventory. The CO emission estimated from the ground-based FTS observations and the Peking University (PKU) inventory based CO2 emission is about 10.96 ± 0.88 and 11.95 ± 0.71 Tg CO yr−1 during the 2015–2016 and the 2016–2017 period, respectively. The CO emission estimated from the ground-based FTS observations and the Emission Database for Global Atmospheric Research (EDGAR) inventory based CO2 emission is about 11.27 ± 0.91 and 12.35 ± 0.74 Tg CO yr−1, respectively. So the CO emissions estimated from the ground-based FTS data and the different inventory based CO2 emission show a good agreement. However, CO emissions derived from FTS data are substantially lower than those calculated directly from the inventories, i.e. there is a large difference between CO emissions derived from FTS and CO emissions directly derived from the two inventories. The phenomenon suggests that the emission inventories greatly overestimate the actual CO emission in the study area. This study estimates the regional CO emissions from ground-based remote sensing observations and investigates how much the difference is between the emissions from inventories and ground-based measurements.
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