Abstract
Abstract. Biomass burning and urbanization are both significant sources of CO emissions and atmospheric loadings in the real environment. The sources of CO are due to incomplete combustion, on one hand of biomass from agriculture or forest clearing, and on the other hand from coal, oil, gas, and other similar materials. However, the spatial and temporal underlying properties and patterns are quite different between these two types of source regions, with urban regions having a relatively constant source of CO emissions, with only short term concentration fluctuations due to local meteorology. On the other hand, in biomass burning regions, the emissions themselves tend to be highly concentrated over a short burning period, and very low otherwise. We hence present a new technique to classify and quantify biomass burning regions and urban regions based on an objective analysis of the CO total column measurements from the MOPITT satellite. By using all of the data from 2000–2016, in connection with averages and standard deviation cutoffs, we successfully determine these regions. By performing a sensitivity analysis, in connection with additional ground-based measurements, we determine that the ideal cutoffs for the mean column loading and standard deviation of the column loading 28 × 1017 mol/cm2 and 6 × 1017 mol/cm2 respectively. These results are capable of representing known urban regions and biomass burning regions well throughout China, Southeast Asia, and South Asia, specifically including Beijing, Hebei, Shandong, Jiangsu, Anhui, Hunan, Guangdong, and Bangkok on one hand, and Northeastern India, Myanmar, Laos, Northern Thailand, and Vietnam on the other hand. A detailed analysis of the time series over the different classified regions show that while the urban areas have a much higher annual value, and a relatively long peak time, that their maximum is never as high as the peaks in the biomass burning regions, and that these peaks in the biomass burning regions are extremely short in duration, although they occur annually or bi-annually. Finally, we have not been able to obtain a statistically relevant decreasing trend, as others have found, making CO possibly an interesting species for future studies.
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