Source Apportionment of Urban GHGs in Hong Kong from Regional Transportation Based on Diagnostic Ratio Method
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| Publicado en: | Sustainability vol. 17, no. 22 (2025), p. 10099-10120 |
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| Autor principal: | |
| Otros Autores: | , , , , , , |
| Publicado: |
MDPI AG
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| Resumen: | Quantifying the regional source of long-lived ozone precursors (especially GHGs) transported to Hong Kong is hampered by sparse observational data and computational limitations. This study introduces an observation-driven analytical framework that integrates a tracer ratio (ethylbenzene/m,p-xylene), wind–source–distance correlations to constrain transport corridors, and inventory mapping to determine the province- and sector-specific contributions, operationalized by identifying transport periods from observations, classifying sources with diagnostic ratios into five emission categories, deriving seasonal weighting factors via frequency normalization, mapping high-resolution inventory classes to these categories to restructure sectoral inventories, and combining normalized provincial spatial weights with the restructured inventories to quantify cross-boundary CO2 and CH4 emissions by sector and region. High-resolution measurements were conducted at the Cape D’Aguilar Supersite (CDSS), which showed dominant wintertime regional transport with mean concentrations of 435.29 ± 7.64 ppm (CO2) and 2083.45 ± 56.50 ppb (CH4). Thirteen transport periods were quantitatively analyzed, and province–sector contributions were estimated. The dominant provincial contributors were Guangdong (20.66%), followed by Jiangxi (18.36%) and Zhejiang (11.15%). Motor vehicles (70%), fuel combustion (15%), and solvent use (10%) were the primary contributing sectors. The framework enables province- and sector-specific attribution under stated assumptions and provides a tool for measuring cross-boundary mitigation and developing air quality and climate strategies in monsoon-affected coastal cities. |
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| ISSN: | 2071-1050 |
| DOI: | 10.3390/su172210099 |
| Fuente: | Publicly Available Content Database |