Abstract. Tropospheric trace gas and aerosol pollutants have adverse effects on health, environment and climate. In order to quantify and mitigate such effects, a wide range of processes leading to the formation and transport of pollutants must be considered, understood and represented in numerical models. Regional scale pollution episodes result from the combination of several factors: high emissions (from anthropogenic or natural sources), stagnant meteorological conditions, kinetics and efficiency of the chemistry and the deposition. All these processes are highly variable in time and space, and their relative contribution to the pollutants budgets can be quantified with chemistry-transport models. The CHIMERE chemistry-transport model is dedicated to regional atmospheric pollution event studies. Since it has now reached a certain level a maturity, the new stable version, CHIMERE 2013, is described to provide a reference model paper. The successive developments of the model are reviewed on the basis of published investigations that are referenced in order to discuss the scientific choices and to provide an overview of the main results.

Abstract. CHIMERE is a chemistry-transport model designed for regional atmospheric composition. It can be used at a variety of scales from local to continental domains. However, due to the model design and its historical use as a regional model, major limitations had remained, hampering its use at hemispheric scale, due to the coordinate system used for transport as well as to missing processes that are important in regions outside Europe. Most of these limitations have been removed in the CHIMERE-2017 version, allowing its use in any region of the world and at any scale, from the scale of a single urban area up to hemispheric scale, with or without polar regions included. Other important improvements have been made in the treatment of the physical processes affecting aerosols and the emissions of mineral dust. From a computational point of view, the parallelization strategy of the model has also been updated in order to improve model numerical performance and reduce the code complexity. The present article describes all these changes. Statistical scores for a model simulation over continental Europe are presented, and a simulation of the circumpolar transport of volcanic ash plume from the Puyehue volcanic eruption in June 2011 in Chile provides a test case for the new model version at hemispheric scale.

Black carbon (BC) is increasingly recognized as a significant air pollutant with harmful effects on human health, either in its own right or as a carrier of other chemicals. The adverse impact is of particular concern in those developing regions with high emissions and a growing population density. The results of recent studies indicate that BC emissions could be underestimated by a factor of 2-3 and this is particularly true for the hot-spot Asian region. Here we present a unique inventory at 10-km resolution based on a recently published global fuel consumption data product and updated emission factor measurements. The unique inventory is coupled to an Asia-nested (∼50 km) atmospheric model and used to calculate the global population exposure to BC with fully quantified uncertainty. Evaluating the modeled surface BC concentrations against observations reveals great improvement. The bias is reduced from −88% to −35% in Asia when the unique inventory and higher-resolution model replace a previous inventory combined with a coarse-resolution model. The bias can be further reduced to −12% by downscaling to 10 km using emission as a proxy. Our estimated global population-weighted BC exposure concentration constrained by observations is 2.14 μg·m −3 ; 130% higher than that obtained using less detailed inventories and low-resolution models.air pollution | climate change | model resolution | emission inventory

A persistent challenge for small-scale air quality modeling is the assessment of health impact and population exposure studies. Despite progress in computation and in the quality of model input (i.e., highresolution information on land use and emission patterns), the uncertainty associated with input parameters cannot be eliminated. The aim of this paper is to study different sources of uncertainty that affect model results as the resolution increases. Mesoscale chemistry transport simulations at different resolutions are used and modeled 0 3 concentrations are compared with surface measurements. The case study consists of CHIMERE model simulations over the city of Paris. It is shown that the principal source of noise in model results is the resolution of the input emission fluxes. The O 3 concentrations modeled with simulations forced by several horizontal resolutions of input emission data (from ⌬x ϭ 48 km to ⌬x ϭ 6 km) indicate that model results do not improve monotonously with resolution, but that after a certain point discrepancies become larger. Based on this result and as an alternative to the deterministic downscaling that resolves explicitly the finer scale (beyond the 1-km range), the authors propose a subgrid-scale approach that uses a statistical description of spatial scales finer than model resolution. As an example, the subgrid variability of modeled O 3 concentration has been quantified, when modeled dry deposition processes occur over subgrid surfaces (land use fractions). The implementation of this modified calculation gives access to subgrid fluxes and subgrid surface concentrations instead of the mean values provided by the commonly used model calculation.

Black carbon (BC) contributes to global warming by absorbing sunlight. However, the size of this contribution, namely, the direct radiative forcing (RF), ranges from +0.1 to +1.0 W m À2 , largely due to differences between bottom-up and observation-based estimates. Current global models systematically underestimate BC radiation absorption relative to observations, which is often attributed to the underestimation of BC emissions. Several studies that adjusted emissions to correct biases of global aerosol models resulted in a revised upward estimate of the BC RF. However, the BC RF was never optimized against observations in a rigorous mathematical manner. Here we simulated the absorption of solar radiation by BC from all sources at the 10 km resolution by combining a highly disaggregated emission inventory with a nested aerosol climate model and a downscaling method. As a result, the normalized mean bias in BC radiation absorption was reduced from À51% to À24% in Asia and from À57% to À50% elsewhere. We applied a Bayesian method that makes the best account of all model, representativeness and observational uncertainties to estimate the BC RF and its uncertainty. Using the new emission inventory and high-resolution model reduces uncertainty in BC RF from À101%/+152% to À70%/+71% over Asia and from À83%/+108% to À64%/+68% over other continental regions. Finally we derived an observationally constrained BC RF of 0.61 Wm À2 (0.16 to 1.40 as 90% confidence) as our best estimate. Our estimate implies that reduction in BC emissions would contribute to slow down global warming, but the contribution could be less than previously thought. tions of aerosol absorption optical depth (AAOD) from the ground-based remote sensing Aerosol Robotic Network (AERONET) [Koch et al., 2009;Bond et al., 2013], leading to ad hoc adjustments in the so-called observation-based or top-down method. Previous studies chose to adjust the BC emissions upward to correct the low bias of global models, resulting in a larger revised BC RF [Sato et al., 2003;Chung et al., 2005Chung et al., , 2012Ramanathan and Carmichael, 2008;Bond et al., 2013], in the range 0.6-1.0 W m À2 . This would make BC a WANG ET AL.RADIATIVE FORCING OF BLACK CARBON 5948

Abstract. Ozone and PM 2.5 concentrations over the city of Paris are modeled with the CHIMERE air-quality model at 4 km × 4 km horizontal resolution for two future emission scenarios. A high-resolution (1 km × 1 km) emission projection until 2020 for the greater Paris region is developed by local experts (AIRPARIF) and is further extended to year 2050 based on regional-scale emission projections developed by the Global Energy Assessment. Model evaluation is performed based on a 10-year control simulation. Ozone is in very good agreement with measurements while PM 2.5 is underestimated by 20 % over the urban area mainly due to a large wet bias in wintertime precipitation. A significant increase of maximum ozone relative to present-day levels over Paris is modeled under the "business-as-usual" scenario (+7 ppb) while a more optimistic "mitigation" scenario leads to a moderate ozone decrease (−3.5 ppb) in year 2050. These results are substantially different to previous regionalscale projections where 2050 ozone is found to decrease under both future scenarios. A sensitivity analysis showed that this difference is due to the fact that ozone formation over Paris at the current urban-scale study is driven by volatile organic compound (VOC)-limited chemistry, whereas at the regional-scale ozone formation occurs under NO x -sensitive conditions. This explains why the sharp NO x reductions implemented in the future scenarios have a different effect on ozone projections at different scales. In rural areas, projections at both scales yield similar results showing that the longer timescale processes of emission transport and ozone formation are less sensitive to model resolution. PM 2.5 concentrations decrease by 78 % and 89 % under business-asusual and mitigation scenarios, respectively, compared to the present-day period. The reduction is much more prominent over the urban part of the domain due to the effective reductions of road transport and residential emissions resulting in the smoothing of the large urban increment modeled in the control simulation.

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Multi-scale HIAs can illustrate the difference in direct consequences of costly mitigation policies and provide results that may help decision-makers choose between different policy alternatives at different scales.