科研之友
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摘要
Development of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of the national strategies in China. Although at the leading position of China, air quality in the GBA is still far worse than those in other renowned bay areas in the world, e.g. San Francisco, New York and Tokyo. To formulate refined PM2.5 prevention and control strategies in GBA, it is essential to identify PM2.5 emission sources in different cities of GBA, and to quantitatively characterize local and non-local contributions and their spatio-temporal variations. In this study, based on the first-ever regionally integrated PM2.5 speciation dataset simultaneously collected at fifteen stations across the GBA in the entire year of 2015, we developed a novel approach by combining Positive Matrix Factorization source apportionment with an optimized backward trajectory analysis, in an aim to quantify local and non-local contributions to PM2.5. Local and non-local contributions were further quantified in different air-sheds during different seasons, which provides important implications for city-level dynamic control of PM2.5 over the GBA. In 2015, nine source factors were identified, including vehicle exhaust, residual oil, aged sea salt, crustal soil, secondary sulfate, secondary nitrate, trace metals, biomass burning and fresh sea salt. Secondary sulfate was the largest contributor to PM2.5, followed by vehicle exhaust. Non-local contributions accounted for 51%~72% at different sites, suggesting PM2.5 over the GBA were mainly transported from outside. Significant differences in local and non-local relative contributions existed between inland and coastal areas, which was largely driven by emission and meteorological conditions. We also highlighted that GBA was in a single air-shed for more than half of time in 2015 and split into two air-sheds for 43% of time. Seasonal analysis revealed that in the two-air-shed pattern, non-local sources contributed 68%~72% over coastal stations which formed a separated air-shed in autumn and winter. In comparison, for the inland stations which formed a separated air-shed in spring, local contribution was predominant (94%). Based on the quantitative identification of local and non-local contributions and their seasonal and spatial variations, this study provides scientific guidance in formulating dynamic and region-specific PM2.5 control measures over the GBA.
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