Abstract. Black carbon (BC) contributes to Arctic warming, yet sources of Arctic BC and their geographic contributions remain uncertain. We interpret a series of recent airborne (NETCARE 2015; PAMARCMiP 2009 and 2011 campaigns) and ground-based measurements (at Alert, Barrow and Ny-Ålesund) from multiple methods (thermal, laser incandescence and light absorption) with the GEOS-Chem global chemical transport model and its adjoint to attribute the sources of Arctic BC. This is the first comparison with a chemical transport model of refractory BC (rBC) measurements at Alert. The springtime airborne measurements performed by the NETCARE campaign in 2015 and the PAMARCMiP campaigns in 2009 and 2011 offer BC vertical profiles extending to above 6 km across the Arctic and include profiles above Arctic ground monitoring stations. Our simulations with the addition of seasonally varying domestic heating and of gas flaring emissions are consistent with ground-based measurements of BC concentrations at Alert and Barrow in winter and spring (rRMSE < 13 %) and with airborne measurements of the BC vertical profile across the Arctic (rRMSE = 17 %) except for an underestimation in the middle troposphere (500-700 hPa).Sensitivity simulations suggest that anthropogenic emissions in eastern and southern Asia have the largest effect on the Arctic BC column burden both in spring (56 %) and annually (37 %), with the largest contribution in the middle troposphere (400-700 hPa). Anthropogenic emissions from northern Asia contribute considerable BC (27 % in spring and 43 % annually) to the lower troposphere (below 900 hPa). Biomass burning contributes 20 % to the Arctic BC column annually.At the Arctic surface, anthropogenic emissions from northern Asia (40-45 %) and eastern and southern Asia (20-40 %) are the largest BC contributors in winter and spring, followed by Europe (16-36 %). Biomass burning from North America is the most important contributor to all stations in summer, especially at Barrow.Our adjoint simulations indicate pronounced spatial heterogeneity in the contribution of emissions to the Arctic BC column concentrations, with noteworthy contributions from emissions in eastern China (15 %) and western Siberia (6.5 %). Although uncertain, gas flaring emissions from oilfields in western Siberia could have a striking impact (13 %) on Arctic BC loadings in January, comparable to the total influence of continental Europe and North America (6.5 % each in January). Emissions from as far as the Indo-Gangetic Plain could have a substantial influence (6.3 % annually) on Arctic BC as well.

Recent Global Burden of Disease (GBD) assessments estimated that outdoor fine-particulate matter (PM2.5) is a causal factor in over 5% of global premature deaths. PM2.5 is produced by a variety of direct and indirect, natural and anthropogenic processes that complicate PM2.5 management. This study develops a proof-of-concept method to quantify the effects on global premature mortality of changes to PM2.5 precursor emissions. Using the adjoint of the GEOS-Chem chemical transport model, we calculated sensitivities of global PM2.5-related premature mortality to emissions of precursor gases (SO2, NOx, NH3) and carbonaceous aerosols. We used a satellite-derived ground-level PM2.5 data set at approximately 10 × 10 km(2) resolution to better align the exposure with population density. We used exposure-response functions from the GBD project to relate mortality to exposure in the adjoint calculation. The response of global mortality to changes in local anthropogenic emissions varied spatially by several orders of magnitude. The largest reductions in mortality for a 1 kg km(-2) yr(-1) decrease in emissions were for ammonia and carbonaceous aerosols in Eastern Europe. The greatest reductions in mortality for a 10% decrease in emissions were found for secondary inorganic sources in East Asia. In general, a 10% decrease in SO2 emissions was the most effective source to control, but regional exceptions were found.

Abstract. Global modeling of atmospheric chemistry is a grand computational challenge because of the need to simulate large coupled systems of ∼100–1000 chemical species interacting with transport on all scales. Offline chemical transport models (CTMs), where the chemical continuity equations are solved using meteorological data as input, have usability advantages and are important vehicles for developing atmospheric chemistry knowledge that can then be transferred to Earth system models. However, they have generally not been designed to take advantage of massively parallel computing architectures. Here, we develop such a high-performance capability for GEOS-Chem (GCHP), a CTM driven by meteorological data from the NASA Goddard Earth Observation System (GEOS) and used by hundreds of research groups worldwide. GCHP is a grid-independent implementation of GEOS-Chem using the Earth System Modeling Framework (ESMF) that permits the same standard model to operate in a distributed-memory framework for massive parallelization. GCHP also allows GEOS-Chem to take advantage of the native GEOS cubed-sphere grid for greater accuracy and computational efficiency in simulating transport. GCHP enables GEOS-Chem simulations to be conducted with high computational scalability up to at least 500 cores, so that global simulations of stratosphere–troposphere oxidant–aerosol chemistry at C180 spatial resolution (∼0.5∘×0.625∘) or finer become routinely feasible.

Residential solid fuel use contributes to degraded indoor and ambient air quality and may affect global surface temperature. However, the potential for national-scale cookstove intervention programs to mitigate the latter issues is not yet well known, owing to the spatial heterogeneity of aerosol emissions and impacts, along with coemitted species. Here we use a combination of atmospheric modeling, remote sensing, and adjoint sensitivity analysis to individually evaluate consequences of a 20-y linear phase-out of cookstove emissions in each country with greater than 5% of the population using solid fuel for cooking. Emissions reductions in China, India, and Ethiopia contribute to the largest global surface temperature change in 2050 [combined impact of −37 mK (11 mK to −85 mK)], whereas interventions in countries less commonly targeted for cookstove mitigation such as Azerbaijan, Ukraine, and Kazakhstan have the largest per cookstove climate benefits. Abatement in China, India, and Bangladesh contributes to the largest reduction of premature deaths from ambient air pollution, preventing 198,000 (102,000-204,000) of the 260,000 (137,000-268,000) global annual avoided deaths in 2050, whereas again emissions in Ukraine and Azerbaijan have the largest per cookstove impacts, along with Romania. Global cookstove emissions abatement results in an average surface temperature cooling of −77 mK (20 mK to −278 mK) in 2050, which increases to −118 mK (−11 mK to −335 mK) by 2100 due to delayed CO 2 response. Health impacts owing to changes in ambient particulate matter with an aerodynamic diameter of 2.5 µm or less (PM 2.5 ) amount to ∼22.5 million premature deaths prevented between 2000 and 2100.aerosols | climate | human health | cookstoves | atmospheric modeling G lobally over 3 billion people presently use solid fuel for meal preparation (1). The extent of this activity and the associated air quality pollutant emissions have led to numerous cookstove intervention studies and programs, such as the Global Alliance for Clean Cookstoves work to implement 60 million clean cookstoves by 2017 (cleancookstoves.org/about/news/11-20-2014-market-enabling-roadmap-phase-2-2015-2017.html). A primary goal of these efforts is to improve indoor air quality, estimated to cause ∼4.3 million premature deaths annually, along with enhancing livelihood of woman and children via reprieval from fuel collection and other solid fuel cookingrelated tasks (2).The magnitude of the emissions of aerosols, aerosol precursors, and greenhouse gases from solid fuel use has also motivated studies of the impact of these emissions on climate and ambient air quality. An estimated 370,000-500,000 global premature deaths in adults occur annually owing to ambient exposure to fine particulate matter associated with residential cookstoves (3-5), and there are as many as 1.0 million global annual premature deaths of adults and children under the age of 5 y from combined residential and commercial energy generation (which includes solid fuel use for cooking) (6). Thi...

We evaluate two inverse modeling methods by conducting inversion experiments using the GEOS‐Chem chemical transport model and its adjoint. We simulate synthetic NH3 column density as observed by the Cross‐track Infrared Sounder over North America to test the ability of the iterative finite difference mass balance (IFDMB) and the four‐dimensional variational assimilation (4D‐Var) methods to recover known NH3 emissions. Comparing to the more rigorous 4D‐Var method, the IFDMB approach requires 3–4 times lower computational cost and yields similar or smaller errors (12–17% vs 17–26%) in the top‐down inventories at 2° × 2.5° resolution. These errors in IFDMB‐derived emission estimates are amplified (53–62%) if compared to the assumed true emissions at 0.25° × 0.3125° resolution. When directly conducting inversions at 0.25° × 0.3125°, the IFDMB consistently exhibits larger errors (44–69% vs 30–45%) than the 4D‐Var approach. Analysis of simulated differences in NH3 columns and in NH3 emissions suggests stronger misalignments at the finer resolution, since the local column is more strongly influenced by spatial smearing from neighboring grids. Adjoint calculations indicate that the number of adjacent grids needed to account for most (>65%) of the emission contributions to the local columnar NH3 abundance over an NH3 source site increases from ~1 at 2° × 2.5° to ~10 at 0.25° × 0.3125°, leading to increased errors especially in IFDMB. Applying inversion results at 2° × 2.5° to update the a priori emissions at 0.25° × 0.3125° could improve the accuracy of IFDMB inversions and reduce the computational cost of 4D‐Var.