Spatially Resolved Emission Factors to Reduce Uncertainties in Air Pollutant Emission Estimates from the Residential Sector

Abstract

The residential sector is a major source of air pollutant emission inventory uncertainties. A nationwide field emission measurement campaign was conducted in rural China to evaluate the variabilities of realistic emission factors (EFs) from indoor solid fuel combustion. For a total of 1313 burning events, the overall average EFs (±standard deviation) of PM2.5 were 8.93 ± 6.95 and 7.33 ± 9.01 g/kg for biomass and coals, respectively, and 89.3 ± 51.2 and 114 ± 87 g/kg for CO. Higher EFs were found from burning of uncompressed straws, while lower EFs were found from processed biomass pellets, coal briquettes, and relatively clean anthracite coals. Modified combustion efficiency was found to be the most significant factor associated with variations in CO EFs, whereas for PM2.5, fuel and stove differences determined its variations. Weak correlations between PM2.5 and CO indicated high uncertainties in using CO as a surrogate for PM2.5. EFs accurately fit log-normal distributions, and obvious spatial heterogeneity was observed attributed to different fuel–stove combinations across the country. Emission estimation variabilities, which are determined by the interquartile ranges divided by the median values, were notably reduced when spatially resolved EFs were adopted in the inventory.

Mass Absorption Efficiency of Black Carbon from Residential Solid Fuel Combustion and Its Association with Carbonaceous Fractions

“…During 2018−2019, a national-scale residential combustion emission measurement campaign was conducted in rural China. 19 All emission measurements were uncontrolled tests where residents performed their normal daily cooking/heating activities with the fuels and stoves of their choice, igniting and managing fires as they did in their daily lives. Emissions were sampled using a compact measurement system.…”

“…29 All emission samples were previously reported for PM 2.5 and CO EFs. 19 Given the labor cost and time needed in laboratory carbon content analysis, a subtotal of 163 samples were analyzed for the optical properties and the association with carbonaceous fractions. These 163 samples covered 16 different fuel−stove combinations that are typical in the real world.…”

Quantitative Sustainable Design (QSD) for the Prioritization of Research, Development, and Deployment of Technologies: A Tutorial and Review

“…To facilitate spatial analysis, geospatial data that link locality-specific contextual parameters with location information are collected, and they can be further combined with temporal information to reveal the evolution of attributes over time. 302 These geospatial data may include physical information (e.g., geological properties, 285,303,304 distances, 305,306 existing infrastructure 93 ), policies, 304 cultural preferences, 291 and any other contextual parameters that could serve as QSD inputs (e.g., energy and water unit impacts, 307,308 costs and impact characterization factors 309 ). As contextual parameters can be particularly important for the human health and social dimensions of sustainability that are highly site-specific, measures should be taken to ensure the representativeness of these values (e.g., use high stakeholder input and influence methods discussed in Section 4.4).…”

Toward Clean Residential Energy: Challenges and Priorities in Research

“…Emissions of air pollutants depend on both fuel consumption and emission factors (EFs). The EFs of incomplete combustion products, such as BC, organic carbon (OC), and polycyclic aromatic hydrocarbons, are particularly high for residential solid fuels. − Therefore, although the residential sector accounts for a relatively small fraction of the total energy consumption, its contribution to total pollutant emissions is much higher in many developing countries. , For example, with only 7.5% of total energy use, this sector accounted for 27% of the total emissions of primary PM 2.5 in China . The EFs for residential emissions are often associated with relatively high variations and uncertainties due to the diversity of stoves, fuels, and measurement methods.…”