Espacialização das emissões de gases de efeito estufa no setor energético de Londrina (PR)

Abstract

The increase in greenhouse gas (GHG) emissions intensifies global warming and the occurrence of extreme weather events, representing one of the primary contemporary environmental challenges. In this context, urban areas play a central role, accounting for a significant portion of global emissions. Municipal-scale emission inventories are fundamental tools for supporting public policies and mitigation strategies. Thus, this study aimed to inventory and spatialize the emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) from the energy sector in the municipality of Londrina (Paraná state), considering the base year of 2018. The methodology followed the Intergovernmental Panel on Climate Change (IPCC) guidelines using bottom-up methods according to data availability and the specificities of each subsector. The analyzed subsectors included transformation industry, road transportation, air transportation, and commercial food establishments (CFE). Emission spatialization was performed using Geographic Information Systems (GIS) to identify areas with the highest concentrations of emissions. Additionally, a semi-qualitative uncertainty analysis was conducted based on the Data Attribute Rating System (DARS). Total emissions from the energy sector amounted to 999,429 t CO2e/year, dominated by road transportation at 725,898 t CO2e/year due to the extensive use of fossil fuels, particularly diesel and gasoline. The industrial energy subsector emitted 255,412 t CO2e/year, highlighting the combustion of diesel oil and firewood. Aviation transportation presented emissions of 9,368 t CO2e/year associated with the aircraft Landing and Take-Off (LTO) cycles due to the use of main engines and auxiliary power units, while CFEs contributed 8,751 t CO2e/year, primarily through the use of firewood, liquefied petroleum gas (LPG), and charcoal. The spatial analysis revealed a concentration of industrial emissions in specific areas of the municipality and the distribution of vehicle emissions along the urban road network, with higher intensity on high-flow routes. These results demonstrate the importance of spatialization as a support tool for urban management and climate planning. However, this representation is subject to uncertainties associated with the quality and resolution of input data, especially in road transport, where spatialization depends on proxies such as traffic intensity and road classification, in addition to the use of generic emission factors. While these limitations may influence the precision of the spatial distribution, they do not compromise the identification of general urban-scale patterns. It is concluded that the energy sector represents a substantial source of GHG emissions in the city of Londrina, making the adoption of public policies focused on energy transition, transport efficiency, and the use of cleaner fuels. This work contributes to the improvement of local climate governance, offering technical support for urban and climate planning.