M. Rosa’s scientific contributions

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Publications (2)


Enhancing multi-mode transport emission inventories: Combining open-source data with traditional approaches
  • Article

September 2024

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28 Reads

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1 Citation

Urban Climate

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M. Rosa

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Fig. 1. The general methodology used to estimate the atmospheric emissions using the BigAir approach.
Fig. 2. The geographical location of the public power plants (blue triangles), refineries (orange squares), and manufacturers (grey circles) in Portugal's mainland, Madeira Islands, and Azores islands.
Fig. 3. Annual atmospheric emissions by activity (public power, refineries, manufacturers, and construction) estimated by the BigAir approach and APA for the year 2020.
Fig. 4. The BigAir approach's emissions share (in percentage) of atmospheric pollutants (PM 10 , PM 2.5 , NOx, CO, SOx, NH 3 , NMVOC, and CH 4 ) for public power, refineries, manufacturing, and construction, by fuel: biomass, diesel oil, hard coal, natural gas, and others.
Fig. 7. Annual spatial distribution of PM 10 emissions (kton) in the Porto region with a horizontal spatial resolution of 0.005 • × 0.005 • (left panel, BigAir approach), 0.01 • × 0.01 • (middle panel, BigAir approach), and 0.1 • × 0.05 • (right panel, CAMS-REG approach).

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An exploratory approach to estimate point emission sources
  • Article
  • Full-text available

August 2023

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56 Reads

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2 Citations

Atmospheric Environment

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.

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Citations (1)


... By comparing the emission's spatial distribution represented in Fig. 7 and Table 1, it is very clear that the Residential, Commercial and Services, and the Industrial activity sectors are the main contributors to NO x and PM 10 emissions in the region, as changes to these sectors are the most visible in the three scenarios, allowing for an almost direct comparison with the design of the scenarios in Fig. 2. This is especially true for the Industrial sector, which has the highest emission values, for both pollutants (Lopes et al., 2023). For all three scenarios, the road transport activity sector (S7) is also evident, mostly for NO x , where the contribution to the total emissions is higher. ...

Reference:

Assessing the impact of different urban morphology scenarios on air pollutant emissions distribution
An exploratory approach to estimate point emission sources

Atmospheric Environment