A sectoral model for territorial emission inventory in a low income country - a case study from Madagascar

A territorial Emission Inventory combined with Economic Weightage to quantify regional pollutant emissions in low-income countries is presented. The study covers the 5 regions of Fianarantsoa city in Madagascar and is analyzing the dominant sectors of activities and pollutant concentrations for BC, PM 10 , PM 2.5 , CO 2 , CO, and NO x . Ground based surveys are used to assess regional emission related activities. The findings corresponding to residential, hotels and restaurant, open waste burning and transport sectors reveal high levels of total pollutant emissions that is 88.98 T/y of PM, 3.5 T/y of BC, 1375.6 T/y of CO, 158.2 T/y of NO x and 7614 T/y of CO 2 . The emission estimation combined with economic weightage reveals that despite the residential sector being the primary emitter, hotels and restaurants disproportionately influence emissions and hotspot zones, highlighting the significance of economic activity on emissions. The study highlights significant gaps between regional results from our study when compared to global datasets available in literature, revealing NO x emissions of 158.2 T/y, 6-63 times higher than EDGAR (2.5-25 T/y), alongside BC, PM, CO (2-36 times high), and CO 2 (2-8 times high). This study identifies sectoral hotspots and regional emission drivers often overlooked by global top-down inventories. This study highlights a territorial approach that enhances sectoral emission quantification, considering fuel types, sectoral contributions, and economic weightage. • A sectorial model for developing a territorial Emission Inventory in low-income countries combined with Economic Weightage to quantify pollutant emissions in Madagascar. • Detail Quantification and analysis of annual regional emissions across major sectors and fuel types. • Residential, hotels and restaurants, open waste burning, and transport sectors reveal high pollutant emissions: 88.98 T/y PM, 3.5 T/y BC, 1375.6 T/y CO, 158.2 T/y NOx, and 7614 T/y CO 2 . • Reveals disproportionate emission impacts by identifying economic-driven hotspots overlooked in global datasets. • Study highlights significant discrepancies between regional emissions and global datasets.