An exploratory approach to estimate point emission sources

• Published in: Atmospheric environment (1994) Vol. 312; p. 120026
• Main Authors: Lopes, D., Graça, D., Rafael, S., Rosa, M., Relvas, H., Ferreira, J., Reis, J., Lopes, M.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2023
• Subjects: Air quality modelling; Big data; Critical air pollutants; Emission inventory; High-resolution; Emission inventory; Critical air pollutants; High-resolution; Big data; Air quality modelling
• ISSN: 1352-2310; 1873-2844
• DOI: 10.1016/j.atmosenv.2023.120026

The current atmospheric emission inventories do not fully meet the spatial and temporal resolution requirements of air quality modelling applications. Considering Portugal as a case study and focusing on combustion point emission sources (i.e., public power, refineries, manufacturers, and construction activities), this work proposes a methodological approach and dataset to estimate anthropogenic emissions suitable for different spatial scales (from regional to local). The obtained results were similar to the annual values reported by the Portuguese Environment Agency with the maximum emissions being estimated for manufacturing and construction activities. No significant differences were recorded between the temporal profiles developed in this and previous studies. However, the country-specific proxies from the developed database allowed us to better represent the temporal and spatial patterns of the Portuguese atmospheric emissions. The combination of the BigAir database with a comprehensive and standardized approach could help policymakers define mitigation and/or plan measures to reduce emissions from point sources, support countries worldwide (with a lack of data) to develop high-resolution emission inventories, and improve the current global and European inventories. •A point emission source inventory was developed.•Manufactures and construction activities were the main emission sources.•Country-specific proxies improved the temporal variation of the emissions.•Improvement of the spatial allocation of emission sources.•Scalability and replicability of the developed approach in other case studies.