Emissions from residential combustion considering end-uses and spatial constraints: Part I, methods and spatial distribution. (January 2016)

• Record Type: Journal Article
• Authors: Winijkul, Ekbordin; Fierce, Laura; Bond, Tami C.
• Is Part Of: Atmospheric environment. Volume 125:Part A(2016)
• Page Start: 126
• Page End: 139
• Publication Date: 2016-01
• Subjects: Residential combustion -- Traditional biofuel -- Emission inventories -- Geographic information systems -- Cookstoves -- Household end-use; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2015.10.013
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: This study describes a framework to attribute national-level atmospheric emissions in the year 2010 from the residential sector, one of the largest energy-related sources of aerosol emissions. We place special emphasis on end-uses, dividing usage into cooking, heating, lighting, and others. This study covers regions where solid biomass fuel provides more than 50% of total residential energy: Latin America, Africa, and Asia (5.2 billion people in 2010). Using nightlight data and population density, we classify five land types: urban, electrified rural with forest access, electrified rural without forest access, non-electrified rural with forest access, and non-electrified rural without forest access. We then apportion national-level residential fuel consumption among all land-types and end-uses, and assign end-use technologies to each combination. The resulting calculation gives spatially-distributed emissions of particulate matter, black carbon, organic carbon, nitrogen oxides, methane, non-methane hydrocarbons, carbon monoxide, and carbon dioxide. Within this study region, about 13% of the energy is consumed in urban areas, and 45% in non-urban land near forests. About half the energy is consumed in land without access to electricity. Cooking accounts for 54% of the consumption, heating for 9%, and lighting only 2%, with unidentified uses making up the remainder. Because biofuel use is assumed to occur preferentially where wood is accessible and electricity is not, our method shifts emissions to land types without electrification, compared with previous methods. The framework developed here is an important first step in acknowledging the role of household needs and local constraints in choosing energy provision. Although data and relationships described here need further development, this structure offers a more physically-based understanding of residential energy choices and, ultimately, opportunities for emission reduction. Graphical abstract: Highlights: New method to distribute fuel consumption and emissions from household energy. Population density, forest boundaries, and nightlights used to classify land types. Cooking accounts for over half of fuel consumption. Method predicts higher emissions in areas near forests and without electricity.