A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): An application of the Community Emissions Data System (CEDS)

Abstract

Abstract. Global anthropogenic emission inventories remain vital for understanding the fate and transport of atmospheric pollution, as well as the resulting impacts on the environment, human health, and society. Rapid changes in today’s society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel-type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx, CO, SO2, NH3, NMVOCs, BC, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture, energy generation, industrial processes, transportation (on-road and non-road), residential, commercial, and other sectors (RCO), waste, solvent use, and international-shipping) and four fuel categories (total coal, solid biofuel, and the sum of liquid fuels and natural gas combustion, plus remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes global gridded (0.5°×0.5°) emission fluxes with monthly time resolution for each compound, sector, and fuel-type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default calibration procedure, and modifications to the final procedures for emissions gridding and aggregation to retain sector and fuel-specific information. Relative to the previous CEDS data released for CMIP6 (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to-date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel-types across multiple source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors, as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), as well as emissions from waste. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture serving as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories, including uncertainties in the underlying activity data and sector- and region-specific emission factors. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS. The CEDSGBD-MAPS emission inventory dataset (both annual country-total and global gridded files) is publicly available and registered under: https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020).

Factors controlling marine aerosol size distributions and their climate effects over the Northwest Atlantic Ocean region

“…These findings are in agreement with previous observational-based studies for the North Atlantic region (e.g. Sanchez et al, 2018;Zheng et al, 2020) We calculated the aerosol direct (DRE) and cloud-albedo indirect (AIE) radiative effects over the North Atlantic attributed to four key factors controlling MBL aerosols. The cooling effects were about a factor of 10 larger for the AIEs than the respective DREs.…”

“…Primary particles are emitted with a lognormal distribution (Lee et al, 2013). The most recent CEDS emissions dataset extends to the year 2017, as described in McDuffie et al (2020). In this work, monthly CEDS emission totals for each compound are spatially gridded by source sector, according to the 0.1° ´ 0.1° gridded EDGAR v4.2 emissions inventory (EC-JRC/PBL, 2012) and population, as described in Hoesly et al (2018).…”

US COVID‐19 Shutdown Demonstrates Importance of Background NO2 in Inferring NOx Emissions From Satellite NO2 Observations

“…However, this is not captured by GEOS‐Chem, which underestimates the free tropospheric NO 2 over the contiguous US (Silvern et al., 2019; Travis et al., 2016). Anthropogenic NO x emissions over the past decade have increased in South Asia and the Middle East, but this would be offset by a decrease of emissions in East Asia (McDuffie et al., 2020) and the net effect would be simulated by GEOS‐Chem. Aircraft emissions have been increasing but their contributions to the NO 2 column remain relatively small (Shah et al., 2021).…”

Source sector and fuel contributions to ambient PM2.5 and attributable mortality across multiple spatial scales

“…Sources include direct emissions such as forest fires and agricultural waste burning 2,3 , windblown mineral dust from arid regions 4 , and inefficient fuel combustion 5 , as well as secondary emissions from atmospheric chemical reactions between primary gas-phase pollutant precursors. These precursors are emitted from both combustion and non-combustion processes that include residential energy use, on-and off-road vehicles, energy generation, solvent use, industrial processes, and agricultural fertilizer application 6 . Once emitted, the chemical production of PM 2.5 mass in the atmosphere is highly nonlinear 7,8 .…”

“…In today's rapidly changing society, the accuracy and policy relevance of such global studies is contingent on (1) the availability of contemporary and detailed emission inventories, (2) scientifically rigorous chemical transport models, (3) global fine resolution PM 2.5 exposure estimates, and (4) disease-specific concentration-response functions (CRFs) derived from contemporary air pollution epidemiologic studies. First, emission datasets that capture recent trends are particularly important in highly polluted regions, such as China, India, and Africa, that have experienced large and rapid changes in PM 2.5 precursor emissions in the last decade 6,41,42 . Disaggregation of these emissions across multiple sectors, fuel types, and regions also increases their policy relevance, as detailed source contribution studies can quantify the health benefits from specific and achievable strategies such as transitions away from coal use for energy generation or solid biofuel for residential cooking and heating.…”