Regional Chemistry-climate Model Research Articles

Ozone source attribution in polluted European areas during summer 2017 as simulated with MECO(n)

Abstract. Emissions of land transport and anthropogenic non-traffic emissions (e.g. industry, households and power generation) are significant sources of nitrogen oxides, carbon monoxide and volatile organic compounds (VOCs). These emissions are important precursors of tropospheric ozone and affect air quality. The contribution of the emission sectors to ozone cannot be measured directly but can only be calculated using sophisticated atmospheric chemistry models. For this study we apply the MECO(n) model system (MESSy-fied ECHAM and COSMO models nested n times) equipped with a source attribution method to investigate the contribution of various sources to ground-level ozone in Europe. Compared to previous source apportionment studies for Europe, for the first time we apply a combined NOx–VOC tagging implemented in an online nested global–regional chemistry–climate model to achieve a finer resolution over central Europe (12 km) but concurrently incorporating the effect of long-range transport. We distinguish 10 different source sectors and 4 geographical source regions, analysing especially the contribution from the land transport sector. Our analysis focuses on large ozone events during summer in four different regions, two major polluted regions (Po Valley and Benelux) and two more remote regions (Iberian Peninsula and Ireland). The analysis concentrates on results for summer 2017, during which measurement campaign EMeRGe took place. Measurement data from this campaign are used for model evaluation. Our analysis shows that European land transport emissions contribute largely (42 % and 44 %, respectively) to ground-level NOy mixing ratios over Benelux and the Po Valley. Due to the overall lower ozone production efficiency over Benelux compared to the Po Valley, however, the contributions to ground-level ozone are larger in the Po Valley (12 %) compared to Benelux (8 %). In line with previous publications using different source apportionment methods, our results underline the large importance of long-range transport of ozone, especially from North America (Benelux, Ireland), but also from Africa (Iberian Peninsula), and provide additional information about the sectoral contribution not available before. Our analysis shows that the contributions of European emissions from land transport and anthropogenic non-traffic sectors strongly increase with increasing values of MDA8 (daily maximum 8 h average) ozone over the Po Valley and in the Benelux region. Accordingly, these two sectors drive large MDA8 values in these regions. Inter-comparisons of results for 2018 and with a coarser model resolution (50 instead of 12 km) show that these results are robust with respect to inter-annual variability and model resolution. Comparing our results with results from other source attribution methods we find that the contributions to ozone from individual sectors, which have large NOx but rather low VOC emissions, are estimated to be lower, if their emissions of NOx and VOCs are regarded concurrently.

Seasonal characteristics of emission, distribution, and radiative effect of marine organic aerosols over the western Pacific Ocean: an investigation with a coupled regional climate aerosol model

Abstract. Organic aerosols from marine sources over the western Pacific Ocean of East Asia were investigated using an online coupled regional chemistry–climate model RIEMS-Chem for the entire year 2014. Model evaluation against a wide variety of observations from research cruises and in situ measurements demonstrated a good skill of the model in simulating temporal variation and spatial distribution of particulate matter with aerodynamic diameter less than 2.5 and 10 µm (PM2.5 and PM10), black carbon (BC), organic carbon (OC), sodium, and aerosol optical depth (AOD) in the marine atmosphere. The inclusion of marine organic aerosols improved model performance on OC concentration by reducing model biases of up to 20 %. The regional and annual mean near-surface marine organic aerosol (MOA) concentration was estimated to be 0.27 µg m−3, with the maximum in spring and the minimum in winter, and contributed 26 % of the total organic aerosol concentration on average over the western Pacific. Marine primary organic aerosol (MPOA) accounted for the majority of marine organic aerosol (MOA) mass, and the MPOA concentration exhibited the maximum in autumn and the minimum in summer, whereas marine secondary organic aerosol (MSOA) was approximately 1–2 orders of magnitude lower than MPOA, having a distinct summer maximum and a winter minimum. MOA induced a direct radiative effect (DREMOA) of −0.27 W m−2 and an indirect radiative effect (IREMOA) of −0.66 W m−2 at the top of the atmosphere (TOA) in terms of annual and oceanic average over the western Pacific, with the highest seasonal mean IREMOA up to −0.94 W m−2 in spring. IREMOA was stronger than, but in a similar magnitude to, the IRE due to sea salt aerosol on average, and it was approximately 9 % of the IRE due to anthropogenic aerosols in terms of annual mean over the western Pacific. This ratio increased to 19 % in the northern parts of the western Pacific in autumn. This study reveals an important role of MOA in perturbing cloud properties and shortwave radiation fluxes in the western Pacific of East Asia.

The direct and indirect radiative effects of sea salt aerosols over the western Pacific using an online-coupled regional chemistry-climate model with a developed sea salt emission scheme

The direct and indirect radiative effects of sea salt aerosols (SSA) over the western Pacific Ocean of East Asia for the year 2014 are investigated by using an online-coupled regional chemistry-climate model (RIEMS-Chem) with a developed sea salt emission scheme (G03SSTRH) by considering the effects of sea surface temperature (SST) and relative humidity (RH) on sea salt generation. Model comparison with observations at coastal and island sites demonstrates the G03SSTRH scheme apparently improve model simulation for sea salt concentration, with the overall model-observation bias for PM10 concentration reduced from 29% to 16% and more evident improvement at northern sites of the western Pacific. It is noteworthy that compared to the experiment with the old SSA emission scheme (G03), the G03SSTRH experiment substantially alters the spatial distribution of mass concentration and radiative effects of sea salt, shifting the maximum value center from the ocean northeast of Japan to the southern parts of the western Pacific with the maximum value increasing to some extent. SSA exerts a negative radiative effect at the top of atmosphere (TOA), in which direct radiative effect (DRESSA) dominates over indirect radiative effect (IRESSA) in the western Pacific. The oceanic and annual mean DRESSA, IRESSA, and total radiative effect (TRESSA) are estimated to be −1.22 W/m2, −0.46 W/m2, and −1.65 W/m2, respectively, from the G03SSTRH experiment, which are 16%, 5%, and 12% stronger than those from the G03 experiment, and the seasonal mean DRESSA in G03SSTRH are approximately 45% and 32% higher than those in G03 in summer and autumn. Distinct seasonality of SSA radiative effects is revealed in the G03SSTRH experiment, showing stronger DRESSA and IRESSA in summer and autumn than those in spring and winter, in marked contrast to the little seasonality in the G03 experiment. This study provides a comprehensive regional estimation of radiative effects induced by SSA and reveals the significant effect of different SSA emission schemes on both mass concentration, radiative effects and seasonal variation of SSA over the western Pacific.

Impact of urbanization on fine particulate matter concentrations over central Europe

Abstract. Rural-to-urban transformation (RUT) is the process of turning a rural or natural land surface into an urban one, which brings about important modifications in the surface, causing well-known effects like the urban heat island (UHI), reduced wind speeds, and increased boundary layer heights. Moreover, with concentrated human activities, RUT introduces new emission sources which greatly perturb local and regional air pollution. Particulate matter (PM) is one of the key pollutants responsible for the deterioration of urban air quality and is still a major issue in European cities, with frequent exceedances of limit values. Here we introduce a regional chemistry–climate model (regional climate model RegCM coupled offline to chemistry transport model CAMx) study which quantifies how the process of RUT modified the PM concentrations over central Europe including the underlying controlling mechanisms that contribute to the final PM pollution. Apart from the two most studied ones, (i) urban emissions and (ii) urban canopy meteorological forcing (UCMF; i.e. the impact of modified meteorological conditions on air quality), we also analyse two less studied contributors to RUT's impact on air quality: (iii) the impact of modified dry-deposition velocities (DVs) due to urbanized land use and (iv) the impact of modified biogenic emissions due to urbanization-induced vegetation modifications and changes in meteorological conditions which affect these emissions. To calculate the magnitude of each of these RUT contributors, we perform a cascade of simulations, whereby each contributor is added one by one to the reference state, while focus is given on PM2.5 (particulate matter with diameter less then 2.5 µm). Its primary and secondary components, namely primary elemental carbon (PEC), sulfates (PSO4), nitrates (PNO3), ammonium (PNH4), and secondary organic aerosol (SOA), are analysed too. The validation using surface measurements showed a systematic negative bias for the total PM2.5, which is probably caused by underestimated organic aerosol and partly by the negative bias in sulfates and elemental carbon. For ammonium and nitrates, the underestimation is limited to the warm season, while for winter, the model tends to overestimate their concentrations. However, in each case, the annual cycle is reasonably captured. We evaluated the RUT impact on PM2.5 over a sample of 19 central European cities and found that the total impact of urbanization is about 2–3 and 1–1.5 µg m−3 in winter and summer, respectively. This is mainly driven by the impact of emissions alone causing a slightly higher impact (1.5–3.5 and 1.2–2 µg m−3 in winter and summer), while the effect of UCMF was a decrease at about 0.2–0.5 µg m−3 (in both seasons), which was mainly controlled by enhanced vertical eddy diffusion, while increases were modelled over rural areas. The transformation of rural land use into an urban one caused an increase in dry-deposition velocities by around 30 %–50 %, which alone resulted in a decrease in PM2.5 by 0.1–0.25 µg m−3 in both seasons. Finally, the impact of biogenic emission modifications due to modified land use and meteorological conditions caused a decrease in summer PM2.5 of about 0.1 µg m−3, while the winter effects were negligible. The total impact of urbanization on aerosol components is modelled to be (values indicate winter and summer averages) 0.4 and 0.3 µg m−3 for PEC, 0.05 and 0.02 µg m−3 for PSO4, 0.1 and 0.08 µg m−3 for PNO3, 0.04 and 0.03 µg m−3 for PNH4, and 0 and 0.05 µg m−3 for SOA. The main contributor of each of these components was the impact of emissions, which was usually larger than the total impact due to the fact that UCMF was counteracted with a decrease. For each aerosol component, the impact of modified DV was a clear decrease in concentration, and finally, the modifications of biogenic emissions impacted SOA predominantly, causing a summer decrease, while a very small secondary effect of secondary inorganic aerosol was modelled too (they increased). In summary, we showed that when analysing the impact of urbanization on PM pollution, apart from the impact of emissions and the urban canopy meteorological forcing, one also has to consider the effect of modified land use and its impact on dry deposition. These were shown to be important in both seasons. For the effect of modified biogenic emissions, our calculations showed that they act on PM2.5 predominantly through SOA modifications, which only turned out to be important during summer.

Achieving Brazil's Deforestation Target Will Reduce Fire and Deliver Air Quality and Public Health Benefits.

Climate, deforestation, and forest fires are closely coupled in the Amazon, but models of fire that include these interactions are lacking. We trained machine learning models on temperature, rainfall, deforestation, land-use, and fire data to show that spatial and temporal patterns of fire in the Amazon are strongly modified by deforestation. We find that fire count across the Brazilian Amazon increases by 0.44 percentage points for each percentage point increase in deforestation rate. We used the model to predict that the increased deforestation rate in the Brazilian Amazon from 2013 to 2020 caused a 42% increase in fire counts in 2020. We predict that if Brazil had achieved the deforestation target under the National Policy on Climate Change, there would have been 32% fewer fire counts across the Brazilian Amazon in 2020. Using a regional chemistry-climate model and exposure-response associations, we estimate that the improved air quality due to reduced smoke emission under this scenario would have resulted in 2,300 fewer deaths due to reduced exposure to fine particulate matter. Our analysis demonstrates the air quality and public health benefits that would accrue from reducing deforestation in the Brazilian Amazon.

Large Air Quality and Public Health Impacts due to Amazonian Deforestation Fires in 2019.

Air pollution from Amazon fires has adverse impacts on human health. The number of fires in the Amazon has increased in recent years, but whether this increase was driven by deforestation or climate has not been assessed. We analyzed relationships between fire, deforestation, and climate for the period 2003 to 2019 among selected states across the Brazilian Legal Amazon (BLA). A statistical model including deforestation, precipitation and temperature explained ∼80% of the variability in dry season fire count across states when totaled across the BLA, with positive relationships between fire count and deforestation. We estimate that the increase in deforestation since 2012 increased the dry season fire count in 2019 by 39%. Using a regional chemistry‐climate model combined with exposure‐response associations, we estimate this increase in fire resulted in 3,400 (95UI: 3,300–3,550) additional deaths in 2019 due to increased exposure to particulate air pollution. If deforestation in 2019 had increased to the maximum recorded during 2003–2019, the number of active fire counts would have increased by an additional factor of 2 resulting in 7,900 (95UI: 7,600–8,200) additional premature deaths. Our analysis demonstrates the strong benefits of reduced deforestation on air quality and public health across the Amazon.

Attributing ozone and its precursors to land transport emissions in Europe and Germany

Abstract. Land transport is an important emission source of nitrogen oxides, carbon monoxide, and volatile organic compounds. The emissions of nitrogen oxides affect air quality directly. Further, all of these emissions serve as a precursor for the formation of tropospheric ozone, thus leading to an indirect influence on air quality. In addition, ozone is radiatively active and its increase leads to a positive radiative forcing. Due to the strong non-linearity of the ozone chemistry, the contribution of emission sources to ozone cannot be calculated or measured directly. Instead, atmospheric chemistry models equipped with specific source attribution methods (e.g. tagging methods) are required. In this study we investigate the contribution of land transport emissions to ozone and ozone precursors using the MECO(n) model system (MESSy-fied ECHAM and COSMO models nested n times). This model system couples a global and a regional chemistry climate model and is equipped with a tagging diagnostic. We investigate the combined effect of long-range-transported ozone and ozone which is produced by European emissions by applying the tagging diagnostic simultaneously and consistently on the global and regional scale. We performed two simulations each covering 3 years with different anthropogenic emission inventories for Europe. We applied two regional refinements, i.e. one refinement covering Europe (50 km resolution) and one covering Germany (12 km resolution). The diagnosed absolute contributions of land transport emissions to reactive nitrogen (NOy) near ground level are in the range of 5 to 10 nmol mol−1. This corresponds to relative contributions of 50 % to 70 %. The largest absolute contributions appear around Paris, southern England, Moscow, the Po Valley, and western Germany. The absolute contributions to carbon monoxide range from 30 nmol mol−1 to more than 75 nmol mol−1 near emission hot-spots such as Paris or Moscow. The ozone which is attributed to land transport emissions shows a strong seasonal cycle with absolute contributions of 3 nmol mol−1 during winter and 5 to 10 nmol mol−1 during summer. This corresponds to relative contributions of 8 % to 10 % during winter and up to 16 % during summer. The largest values during summer are confined to the Po Valley, while the contributions in western Europe range from 12 % to 14 %. Only during summer are the ozone contributions slightly influenced by the anthropogenic emission inventory, but these differences are smaller than the range of the seasonal cycle of the contribution to land transport emissions. This cycle is caused by a complex interplay of seasonal cycles of other emissions (e.g. biogenic) and seasonal variations of the ozone regimes. In addition, our results suggest that during events with large ozone values the ozone contributions of land transport and biogenic emissions increase strongly. Here, the contribution of land transport emissions peaks up to 28 %. Hence, our model results suggest that land transport emissions are an important contributor during periods with large ozone values.

Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53)

Abstract. Methane is the second most important greenhouse gas in terms of anthropogenic radiative forcing. Since pre-industrial times, the globally averaged dry mole fraction of methane in the atmosphere has increased considerably. Emissions from coal mining are one of the primary anthropogenic methane sources. However, our knowledge about different sources and sinks of methane is still subject to great uncertainties. Comprehensive measurement campaigns and reliable chemistry–climate models, are required to fully understand the global methane budget and to further develop future climate mitigation strategies. The CoMet 1.0 campaign (May to June 2018) combined airborne in situ, as well as passive and active remote sensing measurements to quantify the emissions from coal mining in the Upper Silesian Coal Basin (USCB, Poland). Roughly 502 kt of methane is emitted from the ventilation shafts per year. In order to help with the flight planning during the campaigns, we performed 6 d forecasts using the online coupled, three-time nested global and regional chemistry–climate model MECO(n). We applied three-nested COSMO/MESSy instances going down to a spatial resolution of 2.8 km over the USCB. The nested global–regional model system allows for the separation of local emission contributions from fluctuations in the background methane. Here, we introduce the forecast set-up and assess the impact of the model's spatial resolution on the simulation of methane plumes from the ventilation shafts. Uncertainties in simulated methane mixing ratios are estimated by comparing different airborne measurements to the simulations. Results show that MECO(3) is able to simulate the observed methane plumes and the large-scale patterns (including vertically integrated values) reasonably well. Furthermore, we obtain reasonable forecast results up to forecast day four.

Are contributions of emissions to ozone a matter of scale? – a study using MECO(n) (MESSy v2.50)

Abstract. Anthropogenic and natural emissions influence the tropospheric ozone budget, thereby affecting air quality and climate. To study the influence of different emission sources on the ozone budget, often source apportionment studies with a tagged tracer approach are performed. Studies investigating air quality issues usually rely on regional models with a fine spatial resolution, while studies focusing on climate-related questions often use coarsely resolved global models. It is well known that simulated ozone mixing ratios depend on the resolution of the model and the resolution of the emission inventory. Whether the contributions simulated using source apportionment approaches also depend on the model resolution, however, is still unclear. Therefore, this study attempts for the first time to analyse the impact of the model, the model resolution, and the emission inventory resolution on simulated ozone contributions using a diagnostic tagging method. The differences in the ozone contributions caused by these factors are compared with differences that arise from the usage of different emission inventories. To do so, we apply the MECO(n) (MESSy-fied ECHAM and COSMO models nested n times) model system which couples online a global chemistry-climate model with a regional chemistry-climate model equipped with a tagging scheme for source apportionment. The results of the global model (at 300 km horizontal resolution) are compared with the results of the regional model at 50 km (Europe) and 12 km (Germany) resolutions. Besides model-specific differences and biases that are discussed in detail, our results have important implications for other modelling studies and modellers applying source apportionment methods. First, contributions from anthropogenic emissions averaged over the continental scale are quite robust with respect to the model, model resolution, and emission inventory resolution. Second, differences on the regional scale caused by different models and model resolutions can be quite large, and regional models are indispensable for source apportionment studies on the subcontinental scale. Third, contributions from stratospheric ozone transported to the surface differ strongly between the models, mainly caused by differences in the efficiency of the vertical mixing. As stratospheric ozone plays an important role for ground level ozone, but the models show large differences in the amount of downward transported ozone, source apportionment methods should account for this source explicitly to better understand inter-model differences.

Air quality simulations for London using a coupled regional-to-local modelling system

Abstract. A coupled regional-to-local modelling system comprising a regional chemistry–climate model with 5 km horizontal resolution (EMEP4UK) and an urban dispersion and chemistry model with explicit road source emissions (ADMS-Urban) has been used to simulate air quality in 2012 across London. The study makes use of emission factors for NOx and NO2 and non-exhaust emission rates of PM10 and PM2.5 which have been adjusted compared to standard factors to reflect real-world emissions, with increases in total emissions of around 30 % for these species. The performance of the coupled model and each of the two component models is assessed against measurements from background and near-road sites in London using a range of metrics concerning annual averages, high hourly average concentrations and diurnal cycles. The regional model shows good performance compared to measurements for background sites for these metrics, but under-predicts concentrations of all pollutants except O3 at near-road sites due to the low resolution of input emissions and calculations. The coupled model shows good performance at both background and near-road sites, which is broadly comparable with that of the urban model that uses measured concentrations as regional background, except for PM2.5 where the under-prediction of the regional model causes the coupled model to also under-predict concentrations. Using the coupled model, it is estimated that 13 % of the area of London exceeded the EU limit value of 40 µg m−3 for annual average NO2 in 2012, whilst areas of exceedances of the annual average limit values of 40 and 25 µg m−3 for PM10 and PM2.5 respectively were negligible.

The on-line coupled atmospheric chemistry model system MECO(n) – Part 5: Expanding the Multi-Model-Driver (MMD v2.0) for 2-way data exchange including data interpolation via GRID (v1.0)

Abstract. As part of the Modular Earth Submodel System (MESSy), the Multi-Model-Driver (MMD v1.0) was developed to couple online the regional Consortium for Small-scale Modeling (COSMO) model into a driving model, which can be either the regional COSMO model or the global European Centre Hamburg general circulation model (ECHAM) (see Part 2 of the model documentation). The coupled system is called MECO(n), i.e., MESSy-fied ECHAM and COSMO models nested n times. In this article, which is part of the model documentation of the MECO(n) system, the second generation of MMD is introduced. MMD comprises the message-passing infrastructure required for the parallel execution (multiple programme multiple data, MPMD) of different models and the communication of the individual model instances, i.e. between the driving and the driven models. Initially, the MMD library was developed for a one-way coupling between the global chemistry–climate ECHAM/MESSy atmospheric chemistry (EMAC) model and an arbitrary number of (optionally cascaded) instances of the regional chemistry–climate model COSMO/MESSy. Thus, MMD (v1.0) provided only functions for unidirectional data transfer, i.e. from the larger-scale to the smaller-scale models.Soon, extended applications requiring data transfer from the small-scale model back to the larger-scale model became of interest. For instance, the original fields of the larger-scale model can directly be compared to the upscaled small-scale fields to analyse the improvements gained through the small-scale calculations, after the results are upscaled. Moreover, the fields originating from the two different models might be fed into the same diagnostic tool, e.g. the online calculation of the radiative forcing calculated consistently with the same radiation scheme. Last but not least, enabling the two-way data transfer between two models is the first important step on the way to a fully dynamical and chemical two-way coupling of the various model instances.In MMD (v1.0), interpolation between the base model grids is performed via the COSMO preprocessing tool INT2LM, which was implemented into the MMD submodel for online interpolation, specifically for mapping onto the rotated COSMO grid. A more flexible algorithm is required for the backward mapping. Thus, MMD (v2.0) uses the new MESSy submodel GRID for the generalised definition of arbitrary grids and for the transformation of data between them.In this article, we explain the basics of the MMD expansion and the newly developed generic MESSy submodel GRID (v1.0) and show some examples of the abovementioned applications.

Enhanced surface ozone during the heat wave of 2013 in Yangtze River Delta region, China

Under the background of global warming, occurrence of heat waves has increased in most part of Europe, Asia and Australia along with enhanced ozone level. In this paper, observational air temperature and surface ozone in the Yangtze River Delta (YRD) region of China during summer of 2013, and the regional chemistry-climate model (RegCM-CHEM4) were applied to explore the relationship between heat wave and elevated ground-level ozone. Observations indicated that YRD experienced severe heat waves with maximum temperature up to 41.1°C, 6.1°C higher than the definition of heat wave in China, and can last for as long as 27days. Maximum ozone reached 160.5ppb, exceeding the national air quality standard (secondary level) as 74.7ppb. Moreover, ozone was found to increase at a rate of 4–5ppbK−1 within the temperature range of 28–38°C, but decrease by a rate of −1.3~−1.7ppbK−1 under extremely high temperature. A typical heat wave case (HW: 24/7–31/7) and non-heat wave case (NHW: 5/6–12/6) were selected to investigate the mechanism between heavy ozone and heat waves. It was found that chemical reactions play the most important role in ozone formation during HW days, which result in 12ppb ozone enhancement compared to NHW days. Chemical formation of ozone can be influenced by several factors. During heat waves, a more stagnant condition, controlled by anti-cyclone with sink airflow, led to less water vapor in YRD from south and contributed to less cloud cover, which favored a strong solar radiation environment and ozone significantly increasing. High temperature also slightly promote the effect of vertical turbulence and horizontal advection, which beneficial to ozone remove, but the magnitude is much smaller than chemical effect. Our study suggests that the chemical reaction will potentially lead to substantial elevated ozone in a warmer climate, which should be taken into account in future ozone related issues.

An advanced scheme for wet scavenging and liquid-phase chemistry in a regional online-coupled chemistry transport model

Abstract. Clouds are reaction chambers for atmospheric trace gases and aerosols, and the associated precipitation is a major sink for atmospheric constituents. The regional chemistry-climate model COSMO-ART has been lacking a description of wet scavenging of gases and aqueous-phase chemistry. In this work we present a coupling of COSMO-ART with a wet scavenging and aqueous-phase chemistry scheme. The coupling is made consistent with the cloud microphysics scheme of the underlying meteorological model COSMO. While the choice of the aqueous-chemistry mechanism is flexible, the effects of a simple sulfur oxidation scheme are shown in the application of the coupled system in this work. We give details explaining the coupling and extensions made, then present results from idealized flow-over-hill experiments in a 2-D model setup and finally results from a full 3-D simulation. Comparison against measurement data shows that the scheme efficiently reduces SO2 trace gas concentrations by 0.3 ppbv (−30%) on average, while leaving O3 and NOx unchanged. PM10 aerosol mass was increased by 10% on average. While total PM2.5 changes only little, chemical composition is improved notably. Overestimations of nitrate aerosols are reduced by typically 0.5–1 μg m−3 (up to −2 μg m−3 in the Po Valley) while sulfate mass is increased by 1–1.5 μg m−3 on average (up to 2.5 μg m−3 in Eastern Europe). The effect of cloud processing of aerosols on its size distribution, i.e. a shift towards larger diameters, is observed. Compared against wet deposition measurements the system tends to underestimate the total wet deposited mass for the simulated case study.

Indirect vs. Direct Effects of Anthropogenic Sulfate on the Climate of East Asia as Simulated with a Regional Coupled Climate-Chemistry/Aerosol Model

We intercompare a series of multi-year simulations with a coupled regionalchemistry-climate model for east Asia to assess the relative importance ofdirect and indirect (Type I) effects of anthropogenic sulfate on the climateof the region. Both direct and indirect aerosol effects induce a negativeradiative forcing that results in a cooling of the surface and in a decrease of precipitation. Under present day sulfur emissions,the direct aerosol effects prevail during the cold season, while the indirecteffects dominate in the warm season (when cloudiness is maximum over the region). When both the direct and indirect effects are included, the surface cooling varies in the range of –0.1 to over –1 K throughout the region and extended areas ofstatistically significant cooling are found in all seasons except winter.The indirect effects largely dominate in inhibiting precipitation, especiallyduring the summer. When doubling the sulfur emissions, the direct effects aresubstantially strengthened, while the indirect effects are only marginally affected. This indicates that the indirect effects over the region might be asymptotically approaching their maximum efficiency. Overall, the indirect effects appear necessary to explain theobserved temperature record over some regions of China, at least in the warm season.A number of uncertainties need to be addressed, such as due to Type IIindirect effects, modeling of the relationship between aerosol concentration and cloud optical properties, and contribution of aerosols other than anthropogenic sulfate.