Abstract

This study presents the first high-resolution national inventory of anthropogenic emissions for Chile (Inventario Nacional de Emisiones Antropogenicas, INEMA). Emissions for the vehicular, industrial, energy, mining and residential sectors are estimated for the period 2015-2017 and spatially distributed onto a high-resolution grid (approximately 1km x 1 km). The pollutants included are CO2, NOx, SO2, CO, VOCs (volatile organic compounds), NH3 and particulate matter (PM10 and PM2.5) for all sectors. CH4 and black carbon are included for transport and residential sources, while arsenic, benzene, mercury, lead, toluene, and polychlorinated dibenzo-p-dioxins and furan (PCDD/F) are estimated for energy, mining and industrial sources. New activity data and emissions factors are compiled to estimate emissions, which are subsequently spatially distributed using census data and Chile's road network information. The estimated annual average total national emissions of PM10 and PM2.5 during the study period are 191 and 173kt a(-1) (kilotons per year), respectively. The residential sector is responsible for over 90% of these emissions. This sector also emits 81% and 87% of total CO and VOC, respectively. On the other hand, the energy and industry sectors contribute significantly to NH3, SO2 and CO2 emissions, while the transport sector dominates NOx and CO2 emissions, and the mining sector dominates SO2 emissions. In general, emissions of anthropogenic air pollutants and CO2 in northern Chile are dominated by mining activities as well as thermoelectric power plants, while in central Chile the dominant sources are transport and residential emissions. The latter also mostly dominates emissions in southern Chile, which has a much colder climate. Preliminary analysis revealed the dominant role of the emission factors in the final emission uncertainty. Nevertheless, uncertainty in activity data also contributes as suggested by the difference in CO2 emissions between INEMA and EDGAR (Emission Database for Global Atmospheric Research). A comparison between these two inventories also revealed considerable differences for all pollutants in terms of magnitude and sectoral contribution, especially for the residential sector. EDGAR presents larger emissions for most of the pollutants except for CH4 and PM2.5. The differences between both inventories can partly be explained by the use of different emission factors, in particular for the residential sector, where emission factors incorporate information on firewood and local operation conditions. Although both inventories use similar emission factors, differences in CO2 emissions between both inventories indicate biases in the quantification of the activity. This inventory (available at https://doi.org/10.5281/zenodo.4784286, Alamos et al., 2021) will support the design of policies that seek to mitigate climate change and improve air quality by providing policymakers, stakeholders and scientists with qualified scientific spatially explicit emission information.