[1] We use a global chemical transport model (GEOS-Chem) to interpret aircraft curtain observations of black carbon (BC) aerosol over the Pacific from 85°N to 67°S during the 2009-2011 HIAPER (High-Performance Instrumented Airborne Platform for Environmental Research) Pole-to-Pole Observations (HIPPO) campaigns. Observed concentrations are very low, implying much more efficient scavenging than is usually implemented in models. Our simulation with a global source of 6.5 Tg a À1 and mean tropospheric lifetime of 4.2 days (versus 6.8 ± 1.8 days for the Aerosol Comparisons between Observations and Models (AeroCom) models) successfully simulates BC concentrations in source regions and continental outflow and captures the principal features of the HIPPO data but is still higher by a factor of 2 (1.48 for column loads) over the Pacific. It underestimates BC absorbing aerosol optical depths (AAODs) from the Aerosol Robotic Network by 32% on a global basis. Only 8.7% of global BC loading in GEOS-Chem is above 5 km, versus 21 ± 11% for the AeroCom models, with important implications for radiative forcing estimates. Our simulation yields a global BC burden of 77 Gg, a global mean BC AAOD of 0.0017, and a top-of-atmosphere direct radiative forcing (TOA DRF) of 0.19 W m À2 , with a range of 0.17-0.31 W m À2 based on uncertainties in the BC atmospheric distribution. Our TOA DRF is lower than previous estimates (0.27 ± 0.06 W m À2 in AeroCom, 0.65-0.9 W m À2 in more recent studies). We argue that these previous estimates are biased high because of excessive BC concentrations over the oceans and in the free troposphere.

Fertilized soils have large potential for production of soil nitrogen oxide (NOx=NO+NO2), however these emissions are difficult to predict in high-temperature environments. Understanding these emissions may improve air quality modelling as NOx contributes to formation of tropospheric ozone (O3), a powerful air pollutant. Here we identify the environmental and management factors that regulate soil NOx emissions in a high-temperature agricultural region of California. We also investigate whether soil NOx emissions are capable of influencing regional air quality. We report some of the highest soil NOx emissions ever observed. Emissions vary nonlinearly with fertilization, temperature and soil moisture. We find that a regional air chemistry model often underestimates soil NOx emissions and NOx at the surface and in the troposphere. Adjusting the model to match NOx observations leads to elevated tropospheric O3. Our results suggest management can greatly reduce soil NOx emissions, thereby improving air quality.

Abstract. Aerosols from biomass burning (BB) emissions are poorly constrained in global and regional models, resulting in a high level of uncertainty in understanding their impacts. In this study, we compared six BB aerosol emission datasets for 2008 globally as well as in 14 regions. The six BB emission datasets are (1) GFED3.1 (Global Fire Emissions Database version 3.1), (2) GFED4s (GFED version 4 with small fires), (3) FINN1.5 (FIre INventory from NCAR version 1.5), (4) GFAS1.2 (Global Fire Assimilation System version 1.2), (5) FEER1.0 (Fire Energetics and Emissions Research version 1.0), and (6) QFED2.4 (Quick Fire Emissions Dataset version 2.4). The global total emission amounts from these six BB emission datasets differed by a factor of 3.8, ranging from 13.76 to 51.93 Tg for organic carbon and from 1.65 to 5.54 Tg for black carbon. In most of the regions, QFED2.4 and FEER1.0, which are based on satellite observations of fire radiative power (FRP) and constrained by aerosol optical depth (AOD) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), yielded higher BB aerosol emissions than the rest by a factor of 2–4. By comparison, the BB aerosol emissions estimated from GFED4s and GFED3.1, which are based on satellite burned-area data, without AOD constraints, were at the low end of the range. In order to examine the sensitivity of model-simulated AOD to the different BB emission datasets, we ingested these six BB emission datasets separately into the same global model, the NASA Goddard Earth Observing System (GEOS) model, and compared the simulated AOD with observed AOD from the AErosol RObotic NETwork (AERONET) and the Multiangle Imaging SpectroRadiometer (MISR) in the 14 regions during 2008. In Southern Hemisphere Africa (SHAF) and South America (SHSA), where aerosols tend to be clearly dominated by smoke in September, the simulated AOD values were underestimated in almost all experiments compared to MISR, except for the QFED2.4 run in SHSA. The model-simulated AOD values based on FEER1.0 and QFED2.4 were the closest to the corresponding AERONET data, being, respectively, about 73 % and 100 % of the AERONET observed AOD at Alta Floresta in SHSA and about 49 % and 46 % at Mongu in SHAF. The simulated AOD based on the other four BB emission datasets accounted for only ∼50 % of the AERONET AOD at Alta Floresta and ∼20 % at Mongu. Overall, during the biomass burning peak seasons, at most of the selected AERONET sites in each region, the AOD values simulated with QFED2.4 were the highest and closest to AERONET and MISR observations, followed closely by FEER1.0. However, the QFED2.4 run tends to overestimate AOD in the region of SHSA, and the QFED2.4 BB emission dataset is tuned with the GEOS model. In contrast, the FEER1.0 BB emission dataset is derived in a more model-independent fashion and is more physically based since its emission coefficients are independently derived at each grid box. Therefore, we recommend the FEER1.0 BB emission dataset for aerosol-focused hindcast experiments in the two biomass-burning-dominated regions in the Southern Hemisphere, SHAF, and SHSA (as well as in other regions but with lower confidence). The differences between these six BB emission datasets are attributable to the approaches and input data used to derive BB emissions, such as whether AOD from satellite observations is used as a constraint, whether the approaches to parameterize the fire activities are based on burned area, FRP, or active fire count, and which set of emission factors is chosen.

Arctic observations show large decreases in the concentrations of sulfate and black carbon (BC) aerosols since the early 1980s. These near‐term climate‐forcing pollutants perturb the radiative balance of the atmosphere and may have played an important role in recent Arctic warming. We use the GEOS‐Chem global chemical transport model to construct a 3‐D representation of Arctic aerosols that is generally consistent with observations and their trends from 1980 to 2010. Observations at Arctic surface sites show significant decreases in sulfate and BC mass concentrations of 2–3% per year. We find that anthropogenic aerosols yield a negative forcing over the Arctic, with an average 2005–2010 Arctic shortwave radiative forcing (RF) of −0.19 ± 0.05 W m−2 at the top of atmosphere (TOA). Anthropogenic sulfate in our study yields more strongly negative forcings over the Arctic troposphere in spring (−1.17 ± 0.10 W m−2) than previously reported. From 1980 to 2010, TOA negative RF by Arctic aerosol declined, from −0.67 ± 0.06 W m−2 to −0.19 ± 0.05 W m−2, yielding a net TOA RF of +0.48 ± 0.06 W m−2. The net positive RF is due almost entirely to decreases in anthropogenic sulfate loading over the Arctic. We estimate that 1980–2010 trends in aerosol‐radiation interactions over the Arctic and Northern Hemisphere midlatitudes have contributed a net warming at the Arctic surface of +0.27 ± 0.04 K, roughly one quarter of the observed warming. Our study does not consider BC emissions from gas flaring nor the regional climate response to aerosol‐cloud interactions or BC deposition on snow.

Smoke particles can be injected by pyrocumulonimbus (pyroCb) in the upper troposphere and lower stratosphere, but their effects on the radiative budget of the planet remain elusive. Here, by focusing on the record‐setting Pacific Northwest pyroCb event of August 2017, we show with satellite‐based estimates of pyroCb emissions and injection heights in a chemical transport model (GEOS‐Chem) that pyroCb smoke particles can result in radiative forcing of ∼0.02 W/m2 at the top of the atmosphere averaged globally in the 2 months following the event and up to 0.9 K/day heating in the Arctic upper troposphere and lower stratosphere. The modeled aerosol distributions agree with observations from satellites (Earth Polychromatic Imaging Camera [EPIC], Cloud‐Aerosol Transport System [CATS], and Cloud‐Aerosol Lidar with Orthogonal Polarization [CALIOP]), showing the hemispheric transport of pyroCb smoke aerosols with a lifetime of 5 months. Hence, warming by pyroCb aerosols can have similar temporal duration but opposite sign to the well‐documented cooling of volcanic aerosols and be significant for climate prediction.

[1] Severe smog episodes over China in January 2013 received worldwide attention. This air pollution was distinguished by heavy loadings of fine particulate matter and SO 2 . To characterize these episodes, we employed the Ozone Mapping and Profiler Suite, Nadir Mapper (OMPS NM), an ultraviolet (UV) spectrometer flying on the Suomi National Polar-orbiting Partnership (SNPP) spacecraft since October 2011. We developed an advanced algorithm to quantify SO 2 in the lower troposphere and achieved highquality retrievals from OMPS NM, which are characterized by high precision, 0.2 Dobson Units (DU; 1 DU = 2.69 10 16 molecules/cm 2 ) for instantaneous field of view SO 2 data and low biases (within˙0.2 DU). Here we report SO 2 retrievals and UV aerosol index data for these pollution events. The SO 2 columns and the areas covered by high pollutant concentrations are quantified; the results reveal for the first time the full extent (an area of 10 6 km 2 containing up to 60 kt of SO 2 ) of these episodes.

Abstract. The online-coupled Weather Research and Forecasting model with Chemistry (WRF-Chem) is used to simulate the direct and semi-direct radiative impacts of smoke particles over the Southeast Asian Maritime Continent (MC, 10° S–10° N, 90–150° E) during October 2006 when a significant El Niño event caused the highest biomass burning activity since 1997. With the use of an OC (organic carbon) / BC (black carbon) ratio of 10 in the smoke emission inventory, the baseline simulation shows that the clouds can reverse the negative smoke forcing in cloud-free conditions to a positive value. The net absorption of the atmosphere is largely enhanced when smoke resides above a cloud. This led to a warming effect at the top of the atmosphere (TOA) with a domain and monthly average forcing value of ~ 20 W m−2 over the islands of Borneo and Sumatra. Smoke-induced monthly average daytime heating (0.3 K) is largely confined above the low-level clouds, and results in a local convergence over the smoke source region. This heating-induced convergence transports more smoke particles above the planetary boundary layer height (PBLH), hence rendering a positive effect. This positive effect contrasts with a decrease in the cloud fraction resulting from the combined effects of smoke heating within the cloud layer and the more stable boundary layer; the latter can be considered as a negative effect in which a decrease of the cloud fraction weakens the heating by smoke particles above the clouds. During the nighttime, the elevated smoke layer lying above the clouds in the daytime is decoupled from the boundary layer, and the enhanced downdraft and shallower boundary layer lead to the accumulation of smoke particles near the surface. Because of monthly smoke radiative extinction, the amount of solar input at the surface is reduced by as much as 60 W m−2, which leads to a decrease in sensible heat, latent heat, 2 m air temperature, and PBLH by a maximum of 20 W m−2, 20 W m−2, 1 K, and 120 m, respectively. During daytime, the cloud changes over continents mostly occur over the islands of Sumatra and Borneo where the low-level cloud fraction decreases more than 10%. However, the change of local wind, including sea breeze, induced by the smoke direct radiative effect leads to more convergence over the Karimata Strait and the south coastal area of Kalimantan during both daytime and nighttime; consequently, the cloud fraction there is increased up to 20%. The sensitivities with different OC / BC ratios show the importance of the smoke single-scattering albedo for the smoke semi-direct effects. Lastly, a conceptual model is used to summarize the responses of clouds, smoke, temperature, and water vapor fields to the coupling of smoke direct effect below and above clouds over the Southeast Asian Maritime Continent.

An ensemble approach is used to examine the sensitivity of smoke loading and smoke direct radiative effect in the atmosphere to uncertainties in smoke emission estimates. Seven different fire emission inventories are applied independently to WRF-Chem model (v3.5) with the same model configuration (excluding dust and other emission sources) over the northern sub-Saharan African (NSSA) biomass-burning region. Results for November and February 2010 are analyzed, respectively representing the start and end of the biomass burning season in the study region. For February 2010, estimates of total smoke emission vary by a factor of 12, but only differences by factors of 7 or less are found in the simulated regional (15°W-42°E, 13°S-17°N) and monthly averages of column PM 2.5 loading, surface PM 2.5 concentration, aerosol optical depth (AOD), smoke radiative forcing at the top-of-atmosphere and at the surface, and air temperature at 2 m and at 700 hPa. The smaller differences in these simulated variables may reflect the atmospheric diffusion and deposition effects to dampen the large difference in smoke emissions that are highly concentrated in areas much smaller than the regional domain of the Environmental Research Letters Environ.study. Indeed, at the local scale, large differences (up to a factor of 33) persist in simulated smoke-related variables and radiative effects including semi-direct effect. Similar results are also found for November 2010, despite differences in meteorology and fire activity. Hence, biomass burning emission uncertainties have a large influence on the reliability of model simulations of atmospheric aerosol loading, transport, and radiative impacts, and this influence is largest at local and hourly-to-daily scales. Accurate quantification of smoke effects on regional climate and air quality requires further reduction of emission uncertainties, particularly for regions of high fire concentrations such as NSSA.