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Despite the significant progress in improving chemical transport models (CTMs), applications of these modeling endeavors are still subject to large and complex model uncertainty. The Model Inter-Comparison Study for Asia III (MICS-Asia III) has provided the opportunity to assess the capability and uncertainty of current CTMs in East Asian applications. In this study, we have evaluated the multi-model simulations of nitrogen dioxide (NO2), carbon monoxide (CO) and ammonia (NH3) over China under the framework of MICS-Asia III. A total of 13 modeling results, provided by several independent groups from different countries and regions, were used in this study. Most of these models used the same modeling domain with a horizontal resolution of 45 km and were driven by common emission inventories and meteorological inputs. New observations over the North China Plain (NCP) and Pearl River Delta (PRD) regions were also available in MICS-Asia III, allowing the model evaluations over highly industrialized regions. The evaluation results show that most models captured the monthly and spatial patterns of NO2 concentrations in the NCP region well, though NO2 levels were slightly underestimated. Relatively poor performance in NO2 simulations was found in the PRD region, with larger root-mean-square error and lower spatial correlation coefficients, which may be related to the coarse resolution or inappropriate spatial allocations of the emission inventories in the PRD region. All models significantly underpredicted CO concentrations in both the NCP and PRD regions, with annual mean concentrations that were 65.4 % and 61.4 % underestimated by the ensemble mean. Such large underestimations suggest that CO emissions might be underestimated in the current emission inventory. In contrast to the good skills for simulating the monthly variations in NO2 and CO concentrations, all models failed to reproduce the observed monthly variations in NH3 concentrations in the NCP region. Most models mismatched the observed peak in July and showed negative correlation coefficients with the observations, which may be closely related to the uncertainty in the monthly variations in NH3 emissions and the NH3 gas–aerosol partitioning. Finally, model intercomparisons have been conducted to quantify the impacts of model uncertainty on the simulations of these gases, which are shown to increase with the reactivity of species. Models contained more uncertainty in the NH3 simulations. This suggests that for some highly active and/or short-lived primary pollutants, like NH3, model uncertainty can also take a great part in the forecast uncertainty in addition to the emission uncertainty. Based on these results, some recommendations are made for future studies.

Climate change is anticipated to influence heat-related mortality in the future. However, estimates of excess mortality attributable to future heat waves are subject to large uncertainties and have not been projected under the latest greenhouse gas emission scenarios. We estimated future heat wave mortality in the eastern United States (approximately 1,700 counties) under two Representative Concentration Pathways (RCPs) and investigated sources of uncertainty. Using dynamically downscaled hourly temperature projections for 2057-2059, we projected heat wave days that were defined using four heat wave metrics and estimated the excess mortality attributable to them. We apportioned the sources of uncertainty in excess mortality estimates using a variance-decomposition method. Estimates suggest that excess mortality attributable to heat waves in the eastern United States would result in 200-7,807 deaths/year (mean 2,379 deaths/year) in 2057-2059. Average excess mortality projections under RCP4.5 and RCP8.5 scenarios were 1,403 and 3,556 deaths/year, respectively. Excess mortality would be relatively high in the southern states and eastern coastal areas (excluding Maine). The major sources of uncertainty were the relative risk estimates for mortality on heat wave versus non-heat wave days, the RCP scenarios, and the heat wave definitions. Mortality risks from future heat waves may be an order of magnitude higher than the mortality risks reported in 2002-2004, with thousands of heat wave-related deaths per year in the study area projected under the RCP8.5 scenario. Substantial spatial variability in county-level heat mortality estimates suggests that effective mitigation and adaptation measures should be developed based on spatially resolved data.

Wildfire emission inventories are usually applied with biome‐scale emission factors for atmospheric modeling. However, emission factors measured for different plant species vary substantially within the same biome. We apply the species‐specific emission factors and refine the Fire Emission Inventory‐northern Eurasia (FEI‐NE), and derive the wildfire black carbon emission inventory in northern Eurasia from 2002 to 2015. Our new inventory produces 61% more black carbon emissions than current estimates based on Global Fire Emission Database (GFED) and 33% less than FEI‐NE. Model simulations with different inventories are compared with ground‐based and satellite retrievals of aerosol absorption optical depth (AAOD). Compared with the Ozone Monitoring Instrument, the normalized root mean square deviation of AAOD over northern Eurasia is reduced from 1.0 under FEI‐NE to 0.95 through application of the new inventory. This study reveals the importance of applying sub‐biome‐scale emission factors for wildfire inventories development and revisiting emissions uncertainty in atmospheric modeling. Plain Language Summary A recent biomass burning emission inventory for black carbon in northern Eurasia was developed as FEI‐NE. We found that the emission factors applied for wildfires in northern Eurasia boreal forest and grassland were adopted from the prescribed fire measurements conducted in the United States for woody savannas and wetlands, respectively. By comparing with recently published local measurements in Siberia, we mapped the emission factors for plant species from the database published by U.S. Forest Service to biomass structures in northern Eurasia and rebuilt the FEI‐NE inventory as FEI‐NEsp. Modeling results obtained from GEOS‐Chem for 2011–2012 suggested that the simulation with FEI‐NEsp agreed better with ground‐based and satellite observations than FEI‐NE and GFEDv4.1s. Key Points Emission factors indexed by plant species are used to replace biome‐scale factors to update fire emission inventory over northern Eurasia Updated fire emission for black carbon over northern Eurasia is 33% lower than the original inventory FEI‐NE, but 61% higher than GFED Simulation with the new inventory shows better reproduced ground‐based and satellite retrievals of aerosol absorption optical depth

Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating wintertime haze events in the North China Plain region and evaluates the importance of aerosol radiative feedbacks. This paper discusses the estimates of aerosol radiative forcing, aerosol feedbacks, and possible causes for the differences among the participating models. Over the Beijing–Tianjin–Hebei (BTH) region, the ensemble mean of estimated aerosol direct radiative forcing (ADRF) at the top of atmosphere, inside the atmosphere, and at the surface are −1.1, 7.7, and −8.8 W m−2 during January 2010, respectively. Subdivisions of direct and indirect aerosol radiative forcing confirm the dominant role of direct forcing. During severe haze days (17–19 January 2010), the averaged reduction in near-surface temperature for the BTH region can reach 0.3–1.6 ∘C. The responses of wind speeds at 10 m (WS10) inferred from different models show consistent declines in eastern China. For the BTH region, aerosol–radiation feedback-induced daytime changes in PM2.5 concentrations during severe haze days range from 6.0 to 12.9 µg m−3 (<6 %). Sensitivity simulations indicate the important effect of aerosol mixing states on the estimates of ADRF and aerosol feedbacks. Besides, black carbon (BC) exhibits a large contribution to atmospheric heating and feedbacks although it accounts for a small share of mass concentration of PM2.5.

The increasingly unpredictable and extreme weather patterns under a warming climate underscore the urgency of accurate regional assessments of future drought risk. This study evaluates the projected drought evolution in the contiguous United States under the high-emission shared socioeconomic pathway 5–8.5 climate scenario for the coming decades. Using a multi-model ensemble of six Coupled Model Intercomparison Project Phase 6 global climate models combined with dynamical downscaling techniques, we analyzed near-term (2020–2039) and mid-term (2040–2059) drought patterns using the self-calibrating palmer drought severity index (ScPDSI), the standardized precipitation index (SPI-12), and the Standardized Precipitation-Evapotranspiration Index (SPEI-12). Results reveal a widespread increase in abnormally dry (D0) and moderate drought (D1) conditions, particularly in urban areas, while severe (D2), extreme (D3), and exceptional (D4) droughts are expected to become less common in many regions. Meanwhile, persistent and intensifying droughts are projected in the western and southwestern U.S., driven by long-term soil moisture deficits. The ScPDSI projects that 1.1 million urban residents will be affected by D0 conditions in 2050, while SPI-12 suggests a decrease in the total affected populations after 2040. ScPDSI indicates prolonged droughts in the West, and SPI-12 captures transient variability. Although the total drought-exposed population is expected to decrease, urban areas will continue to bear a greater burden, particularly for mild droughts (D0, D1). These findings highlight a shift toward more frequent mild droughts, fewer severe droughts, and persistent drying in the Southwest, emphasizing the need for region-specific adaptation strategies.

Climate change and human activities have drastically altered the natural wildfire balance in the Western US and increased population health risks due to exposure to pollutants from fire smoke. Using dynamically downscaled climate model projections, we estimated additional asthma emergency room visits and hospitalizations due to exposure to smoke fine particulate matter (PM 2.5 ) in the Western US in the 2050s. Isolating the amount of PM 2.5 from wildfire smoke is both difficult to estimate and, thus, utilized by relatively few studies. In this study, we use a sophisticated modeling approach to estimate future increase in wildfire smoke exposure over the reference period (2003–2010) and subsequent health care burden due to asthma exacerbation. Average increases in smoke PM 2.5 during future fire season ranged from 0.05 to 9.5 µ g m −3 with the highest increases seen in Idaho, Montana, and Oregon. Using the Integrated Climate and Land-Use Scenarios (ICLUS) A2 scenario, we estimated the smoke-related asthma events could increase at a rate of 15.1 visits per 10 000 persons in the Western US, with the highest rates of increased asthma (25.7–41.9 per 10 000) in Idaho, Montana, Oregon, and Washington. Finally, we estimated healthcare costs of smoke-induced asthma exacerbation to be over $1.5 billion during a single future fire season. Here we show the potential future health impact of climate-induced wildfire activity, which may serve as a key tool in future climate change mitigation and adaptation planning.

In order to clarify the causes of variability among the model outputs for surface ozone in the Model Intercomparison Study Asia Phase III (MICS-Asia III), three regional models, CMAQ v.5.0.2, CMAQ v.4.7.1, and NAQPMS (abbreviated as NAQM in this paper), have been selected. Detailed analyses of monthly averaged diurnal variation have been performed for selected grids covering the metropolitan areas of Beijing and Tokyo and at a remote oceanic site, Oki. The chemical reaction mechanism, SAPRC99, used in the CMAQ models tended to give a higher net chemical ozone production than CBM-Z used in NAQM, agreeing with previous studies. Inclusion of the heterogeneous “renoxification” reaction of HNO3 (on soot surface)→NO+NO2 only in NAQM would give a higher NO concentration resulting in a better agreement with observational data for NO and nighttime O3 mixing ratios. In addition to chemical processes, the difference in the vertical transport of O3 was found to affect the simulated results significantly. Particularly, the increase in downward O3 flux from the upper layer to the surface after dawn was found to be substantially different among the models. Larger early morning vertical transport of O3 simulated by CMAQ 5.0.2 is thought to be the reason for higher daytime O3 in July in this model. All three models overestimated the daytime ozone by ca. 20 ppbv at the remote site Oki in July, where in situ photochemical activity is minimal.

Atmospheric nitrogen deposition in China has attracted public attention in recent years due to the increasing anthropogenic emission of reactive nitrogen (Nr) and its impacts on the terrestrial and aquatic ecosystems. However, limited long-term and multisite measurements have restrained the understanding of the mechanism of the Nr deposition and the chemical transport model (CTM) improvement. In this study, the performance of the simulated wet and dry deposition for different Nr species, i.e., particulate NO3- and NH4+, gaseous NOx, HNO3 and NH3 have been conducted using the framework of Model Inter-Comparison Study for Asia (MICS-Asia) phase III. A total of nine models, including five Weather Research and Forecasting models coupled with the Community Multiscale Air Quality (WRF-CMAQ) models, two self-developed regional models, a global model and a Regional Atmospheric Modeling System coupled with the Community Multiscale Air Quality (RAMS-CMAQ) model have been selected for the comparison. For wet deposition, observation data from 83 measurement sites from the East Asia Acid Deposition Monitoring Network (EANET), Chinese Ecosystem Research Network (CERN), China Agricultural University Deposition Network (CAUDN), National Acid Deposition Monitoring Network (NADMN) and Department of Ecological Environment (DEE) of China have been collected and normalized for comparison with model results. In general, most models show the consistent spatial and temporal variation of both oxidized N (Nox) and reduced N (Nrd) wet deposition in China, with the normalized mean error (NME) at around 50 %, which is lower than the value of 70 % based on EANET observation over Asia. Both the ratio of wet or dry deposition to the total inorganic N (TIN) deposition and the ratios of TIN to their emissions have shown consistent results with the Nationwide Nitrogen Deposition Monitoring Network (NNDMN) estimates. The performance of ensemble results (ENMs) was further assessed with satellite measurements. In different regions of China, the results show that the simulated Nox wet deposition was overestimated in northeastern China (NE) but underestimated in the south of China, namely southeastern (SE) and southwestern (SW) China, while the Nrd wet deposition was underestimated in all regions by all models. The deposition of Nox has larger uncertainties than the Nrd, especially in northern China (NC), indicating the chemical reaction process is one of the most important factors affecting the model performance. Compared to the critical load (CL) value, the Nr deposition in NC, SE and SW reached or exceeded reported CL values and resulted in serious ecological impacts. The control of Nrd in NC and SW and Nox in SE would be an effective mitigation measure for TIN deposition in these regions. The Nr deposition in the Tibetan Plateau (TP) with a high ratio of TIN ∕ emission (∼3.0), indicates a significant transmission from outside. Efforts to reduce these transmissions ought to be paramount due the climatic importance of the Tibetan region to the sensitive ecosystems throughout China.

This study uses multi-model ensemble results of 11 models from the second phase of Task Force Hemispheric Transport of Air Pollution (HTAP II) to calculate the global sulfur (S) and nitrogen (N) deposition in 2010. Modeled wet deposition is evaluated with observation networks in North America, Europe and East Asia. The modeled results agree well with observations, with 76–83 % of stations being predicted within ±50 % of observations. The models underestimate SO42-, NO3- and NH4+ wet depositions in some European and East Asian stations but overestimate NO3- wet deposition in the eastern United States. Intercomparison with previous projects (PhotoComp, ACCMIP and HTAP I) shows that HTPA II has considerably improved the estimation of deposition at European and East Asian stations. Modeled dry deposition is generally higher than the “inferential” data calculated by observed concentration and modeled velocity in North America, but the inferential data have high uncertainty, too. The global S deposition is 84 Tg(S) in 2010, with 49 % in continental regions and 51 % in the ocean (19 % of which coastal). The global N deposition consists of 59 Tg(N) oxidized nitrogen (NOy) deposition and 64 Tg(N) reduced nitrogen (NHx) deposition in 2010. About 65 % of N is deposited in continental regions, and 35 % in the ocean (15 % of which coastal). The estimated outflow of pollution from land to ocean is about 4 Tg(S) for S deposition and 18 Tg(N) for N deposition. Comparing our results to the results in 2001 from HTAP I, we find that the global distributions of S and N deposition have changed considerably during the last 10 years. The global S deposition decreases 2 Tg(S) (3 %) from 2001 to 2010, with significant decreases in Europe (5 Tg(S) and 55 %), North America (3 Tg(S) and 29 %) and Russia (2 Tg(S) and 26 %), and increases in South Asia (2 Tg(S) and 42 %) and the Middle East (1 Tg(S) and 44 %). The global N deposition increases by 7 Tg(N) (6 %), mainly contributed by South Asia (5 Tg(N) and 39 %), East Asia (4 Tg(N) and 21 %) and Southeast Asia (2 Tg(N) and 21 %). The NHx deposition increases with no control policy on NH3 emission in North America. On the other hand, NOy deposition has started to dominate in East Asia (especially China) due to boosted NOx emission.

Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative and microphysical feedbacks. A comprehensive overview of the MICS-Asia III Topic 3 study design, including descriptions of participating models and model inputs, the experimental designs, and results of model evaluation, are presented. Six modeling groups from China, Korea and the United States submitted results from seven applications of online coupled chemistry–meteorology models. Results are compared to meteorology and air quality measurements, including data from the Campaign on Atmospheric Aerosol Research Network of China (CARE-China) and the Acid Deposition Monitoring Network in East Asia (EANET). The correlation coefficients between the multi-model ensemble mean and the CARE-China observed near-surface air pollutants range from 0.51 to 0.94 (0.51 for ozone and 0.94 for PM2.5) for January 2010. However, large discrepancies exist between simulated aerosol chemical compositions from different models. The coefficient of variation (SD divided by the mean) can reach above 1.3 for sulfate in Beijing and above 1.6 for nitrate and organic aerosols in coastal regions, indicating that these compositions are less consistent from different models. During clean periods, simulated aerosol optical depths (AODs) from different models are similar, but peak values differ during severe haze events, which can be explained by the differences in simulated inorganic aerosol concentrations and the hygroscopic growth efficiency (affected by varied relative humidity). These differences in composition and AOD suggest that future models can be improved by including new heterogeneous or aqueous pathways for sulfate and nitrate formation under hazy conditions, a secondary organic aerosol (SOA) formation chemical mechanism with new volatile organic compound (VOCs) precursors, yield data and approaches, and a more detailed evaluation of the dependence of aerosol optical properties on size distribution and mixing state. It was also found that using the ensemble mean of the models produced the best prediction skill. While this has been shown for other conditions (for example, the prediction of high-ozone events in the US (McKeen et al., 2005)), this is to our knowledge the first time it has been shown for heavy haze events.