Abstract

Black carbon (BC) aerosol negatively affects air quality and contributes to climate warming globally. However, little is known about the relative contributions of different source control measures to BC reduction owing to the lack of powerful source-diagnostic tools. We combine the fingerprints of dual-carbon isotope using an optimized Bayesian Markov chain Monte Carlo (MCMC) scheme and for the first time to study the key sources of BC in megacity Guangzhou of the Pearl River Delta (PRD) region, China in 2018 autumn season. The MCMC model-derived source apportionment of BC shows that the dominant contributor is petroleum combustion (39%), followed by coal combustion (34%) and biomass burning (27%). It should be noted that the BC source pattern is highly sensitive to the variations of air masses transported with an enhanced contribution of fossil source from the eastern area, suggesting the important impact of regional atmospheric transportation on the BC source profile in the PRD region. Also, we further found that fossil fuel combustion BC contributed 84% to the total BC reduction during 2013–2018. The response of PM2.5 concentration to the 14C-derived BC source apportionment is successfully fitted (r = 0.90) and the results predicted that it would take ∼6 years to reach the WHO PM2.5 guideline value (10 μg m−3) for the PRD region if the emission control measures keep same as they are at present. Taken together, our findings suggest that dual-carbon isotope is a powerful tool in constraining the source apportionment of BC for the evaluations of air pollution control and carbon emission measures.

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