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Ground-level PM2.5 data derived from satellites with machine learning are crucial for health and climate assessments. However, uncertainties persist due to the absence of spatially covered observations. To address this, we propose a novel testbed using nontraditional numerical simulations to evaluate PM2.5 estimation across the entire spatial domain. The testbed emulates the general machine-learning approach by training the model with grids corresponding to ground monitoring sites and subsequently testing its predictive accuracy for other locations. Our approach enables comprehensive evaluation of various machine-learning methods' performance in estimating PM2.5 across the spatial domain for the first time. Unexpected results are shown in the application in China, with larger absolute PM2.5 biases found in densely populated regions with abundant ground observations across all benchmark models due to the higher baseline concentration, though the relative error (approximately 20 %) is smaller compared to that in rural areas (over 50 %). The imbalance in training samples, mostly from urban areas with high emissions, is the main reason, leading to significant overestimation due to the lack of monitors in downwind areas where PM2.5 is transported from urban areas with varying vertical profiles. Our proposed testbed also provides an efficient strategy for optimizing model structure or training samples to enhance satellite-retrieval model performance. Integration of spatiotemporal features, especially with conventional neural network (CNN)-based deep-learning approaches like the residual neural network (ResNet) model, has successfully mitigated PM2.5 overestimation (by 5–30 µg m−3) and the corresponding exposure (by 3 million people ⋅ µg m−3) in the downwind area over 9 years (2013–2021) compared to the traditional approach. Furthermore, the incorporation of 600 strategically positioned ground monitoring sites identified through the testbed is essential for achieving a more balanced distribution of training samples, thereby ensuring precise PM2.5 estimation and facilitating the assessment of the associated impacts in China. In addition to presenting the retrieved surface PM2.5 concentrations in China from 2013 to 2021, this study provides a testbed dataset derived from physical modeling simulations which can serve to evaluate the performance of data-driven methodologies, such as machine learning, in estimating spatial PM2.5 concentrations for the community (Li et al., 2024a; https://doi.org/10.5281/zenodo.11122294).

This study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model–measurement comparisons presented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0–7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by −9.7 % for CH4, −21 % for CO, and −18 % for O3. Results for CH4 are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and minimum in the summer and O3 has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15 % of the model–location comparisons.

Global reactive nitrogen (N) deposition has more than tripled since 1860 and is expected to remain high due to food production and fossil fuel consumption. Global sulfur emissions have been decreasing worldwide over the last 30 years, but many regions are still experiencing unhealthily high levels of deposition. We update the 2010 global deposition budget for reactive nitrogen and sulfur components with new regional wet deposition measurements from Asia, improving the ensemble results of 11 global chemistry transport models from the second phase of the United Nations Economic Commission for Europe's Task Force on Hemispheric Transport of Air Pollution (HTAP II). The observationally adjusted global N deposition budget is 114.5 Tg N, representing a minor increase of 1 % from the model-only derived values, and the adjusted global sulfur deposition budget is 88.9 Tg S, representing a 6.5 % increase from the modeled values, using an interpolation distance of 2.5∘. Regionally, deposition adjustments can be up to ∼ 73 % for nitrogen and 112 % for sulfur. Our study demonstrates that a global measurement–model fusion approach can improve N and S deposition model estimates at a regional scale, with sufficient availability of observations; however, in large parts of the world, alternative approaches need to be explored. The analysis presented here represents a step forward toward the World Meteorological Organization's goal of global fusion products for accurately mapping harmful air pollution deposition.

As the third most important greenhouse gas (GHG) after carbon dioxide (CO2) and methane (CH4), tropospheric ozone (O3) is also an air pollutant causing damage to human health and ecosystems. This study brings together recent research on observations and modeling of tropospheric O3 in the Arctic, a rapidly warming and sensitive environment. At different locations in the Arctic, the observed surface O3 seasonal cycles are quite different. Coastal Arctic locations, for example, have a minimum in the springtime due to O3 depletion events resulting from surface bromine chemistry. In contrast, other Arctic locations have a maximum in the spring. The 12 state-of-the-art models used in this study lack the surface halogen chemistry needed to simulate coastal Arctic surface O3 depletion in the springtime; however, the multi-model median (MMM) has accurate seasonal cycles at non-coastal Arctic locations. There is a large amount of variability among models, which has been previously reported, and we show that there continues to be no convergence among models or improved accuracy in simulating tropospheric O3 and its precursor species. The MMM underestimates Arctic surface O3 by 5 % to 15 % depending on the location. The vertical distribution of tropospheric O3 is studied from recent ozonesonde measurements and the models. The models are highly variable, simulating free-tropospheric O3 within a range of ±50 % depending on the model and the altitude. The MMM performs best, within ±8 % for most locations and seasons. However, nearly all models overestimate O3 near the tropopause (∼300 hPa or ∼8 km), likely due to ongoing issues with underestimating the altitude of the tropopause and excessive downward transport of stratospheric O3 at high latitudes. For example, the MMM is biased high by about 20 % at Eureka. Observed and simulated O3 precursors (CO, NOx, and reservoir PAN) are evaluated throughout the troposphere. Models underestimate wintertime CO everywhere, likely due to a combination of underestimating CO emissions and possibly overestimating OH. Throughout the vertical profile (compared to aircraft measurements), the MMM underestimates both CO and NOx but overestimates PAN. Perhaps as a result of competing deficiencies, the MMM O3 matches the observed O3 reasonably well. Our findings suggest that despite model updates over the last decade, model results are as highly variable as ever and have not increased in accuracy for representing Arctic tropospheric O3.

Airborne dust is one of the most important natural aerosols; it has various environmental impacts on air quality, ocean fertilization, and the global climate change. Asian dust, representing one of the major dust sources in the world, has been widely studied due to its long-range transport capability. However, its transport to the Arctic has been less investigated. In this study, two typical transport routes were identified based on the recorded dust events in China during 2011–2015. Accordingly, two specific Asian dust long-range transport events were selected and compared, i.e., one observed at Barrow, Alaska (traveled mostly over lands within 6–7 d), and the other one observed at Alert, Canada (traveled mostly over oceans within 7–8 d). The transport routes of the two dust events had been cross-validated by using air mass trajectory modeling, meteorology reanalysis data, ground-based aerosol columnar and profiling observations, and spaceborne remote sensing. It was found that different transport routes to the Arctic had divergent effects on the evolution of aerosol properties, revealing different mixing extents between dust, anthropogenic particles, smoke, and sea salts. Based on the Snow, Ice, and Aerosol Radiative (SNICAR) model, the albedo simulation indicated that dust and elemental carbon together reduced the surface albedo by 0.35 % to 2.63 % compared to the pure snow condition. This study implied that the dust long-range transport from China to the Arctic was ubiquitous and may be a potential contributor to the Arctic regional climate.

While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO42-), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.

An accurate emission inventory is a crucial part of air pollution management and is essential for air quality modelling. One source in an emission inventory, an industrial source, has been known with high uncertainty in both location and magnitude in China. In this study, a new reallocation method based on blue-roof industrial buildings was developed to replace the conventional method of using population density for the Chinese emission development. The new method utilized the zoom level 14 satellite imagery (i.e. Google®) and processed it based on hue, saturation, and value (HSV) colour classification to derive new spatial surrogates for province-level reallocation, providing more realistic spatial patterns of industrial PM2.5 and NO2 emissions in China. The WRF-CMAQ-based PATH-2016 model system was then applied with the new processed industrial emission input in the MIX inventory to simulate air quality in the Greater Bay Area (GBA) area (formerly called Pearl River Delta, PRD). In the study, significant root mean square error (RMSE) improvement was observed in both summer and winter scenarios in 2015 when compared with the population-based approach. The average RMSE reductions (i.e. 75 stations) of PM2.5 and NO2 were found to be 11 µg m−3 and 3 ppb, respectively. Although the new method for allocating industrial sources did not perform as well as the point- and area-based industrial emissions obtained from the local bottom-up dataset, it still showed a large improvement over the existing population-based method. In conclusion, this research demonstrates that the blue-roof industrial allocation method can effectively identify scattered industrial sources in China and is capable of downscaling the industrial emissions from regional to local levels (i.e. 27 to 3 km resolution), overcoming the technical hurdle of ∼ 10 km resolution from the top-down or bottom-up emission approach under the unified framework of emission calculation.

Plumes from the boreal spring biomass burning (BB) in northern peninsular Southeast Asia (nPSEA) are lifted into the subtropical jet stream and transported and deposited across nPSEA, South China, Taiwan and even the western North Pacific Ocean. This paper as part of the Seven SouthEast Asian Studies (7-SEAS) project effort attempts to improve the chemical weather prediction capability of the Weather Research and Forecasting coupled with the Community Multiscale for Air Quality (WRF–CMAQ) model over a vast region, from the mountainous near-source burning sites at nPSEA to its downwind region. Several sensitivity analyses of plume rise are compared in the paper, and it is discovered that the initial vertical allocation profile of BB plumes and the plume rise module (PLMRIM) are the main reasons causing the inaccuracies of the WRF–CMAQ simulations. The smoldering emission from the Western Regional Air Partnership (WRAP) empirical algorithm included has improved the accuracies of PM10, O3 and CO at the source. The best performance at the downwind sites is achieved with the inline PLMRIM, which accounts for the atmospheric stratification at the mountainous source region with the FINN burning emission dataset. Such a setup greatly improves not only the BB aerosol concentration prediction over near-source and receptor ground-based measurement sites but also the aerosol vertical distribution and column aerosol optical depth of the BB aerosol along the transport route. The BB aerosols from nPSEA are carried by the subtropical westerlies in the free troposphere to the western North Pacific, while BB aerosol has been found to interact with the local pollutants in the Taiwan region through three conditions: (a) overpassing western Taiwan and entering the central mountain area, (b) mixing down to western Taiwan, (c) transport of local pollutants upwards and mixing with a BB plume on higher ground. The second condition, which involves the prevailing high-pressure system from Asian cold surge, is able to impact most of the population in Taiwan.

Black carbon (BC) emissions play an important role in regional climate change in the Arctic. It is necessary to pay attention to the impact of long-range transport from regions outside the Arctic as BC emissions from local sources in the Arctic were relatively small. The task force Hemispheric Transport of Air Pollution Phase 2 (HTAP2) set up a series of simulation scenarios to investigate the response of BC in a given region to different source regions. This study investigated the responses of Arctic BC concentrations and surface temperature to 20 % anthropogenic emission reductions from six regions in 2010 within the framework of HTAP2 based on ensemble modeling results. Emission reductions from East Asia (EAS) had the most (monthly contributions: 0.2–1.5 ng m−3) significant impact on the Arctic near-surface BC concentrations, while the monthly contributions from Europe (EUR), Middle East (MDE), North America (NAM), Russia–Belarus–Ukraine (RBU), and South Asia (SAS) were 0.2–1.0, 0.001–0.01, 0.1–0.3, 0.1–0.7, and 0.0–0.2 ng m−3, respectively. The responses of the vertical profiles of the Arctic BC to the six regions were found to be different due to multiple transport pathways. Emission reductions from NAM, RBU, EUR, and EAS mainly influenced the BC concentrations in the low troposphere of the Arctic, while most of the BC in the upper troposphere of the Arctic derived from SAS. The response of the Arctic BC to emission reductions in six source regions became less significant with the increase in the latitude. The benefit of BC emission reductions in terms of slowing down surface warming in the Arctic was evaluated by using absolute regional temperature change potential (ARTP). Compared to the response of global temperature to BC emission reductions, the response of Arctic temperature was substantially more sensitive, highlighting the need for curbing global BC emissions.

Asia has attracted research attention because it has the highest anthropogenic emissions in the world, and the Model Inter-Comparison Study for Asia (MICS-Asia) phase III was carried out to foster our understanding of the status of air quality over Asia. This study analyzed wet deposition in southeast Asian countries (Myanmar, Thailand, Lao People's Democratic Republic (PDR), Cambodia, Vietnam, the Philippines, Malaysia, and Indonesia) with the aim of providing insights into the seasonal variation of wet deposition. Southeast Asia was not fully considered in MICS-Asia phase II due to a lack of observational data; however, the analysis period of MICS-Asia III, namely the year 2010, is covered by ground observations of the Acid Deposition Monitoring Network in East Asia (EANET), and the coordinated simulation domain was extended to cover these observation sites. The analyzed species are wet depositions of S (sulfate aerosol, sulfur dioxide (SO2), and sulfuric acid (H2SO4)), N (nitrate aerosol, nitrogen monoxide (NO), nitrogen dioxide (NO2), and nitric acid (HNO3)), and A (ammonium aerosol and ammonia (NH3)). The wet deposition simulated with seven models driven by a unified meteorological model in MICS-Asia III was used with the ensemble approach, which effectively modulates the differences in performance among models. By comparison with EANET observations, although the seven models generally captured the wet depositions of S, N, and A, there were difficulties capturing these in some cases. Considering the model performance for ambient aerosol concentrations over southeast Asia, this failure of models is considered to be related to the difficulty in capturing the precipitation in southeast Asia, especially during the dry and wet seasons. Generally, meteorological fields overestimate the precipitation during the dry season, which leads to the overestimation of wet deposition during this season. To overcome this, a precipitation-adjusted approach that scaled the modeled precipitation to the observed value was applied, and it was demonstrated that the model performance was improved. Satellite measurements were also used to adjust for precipitation data, which adequately accounted for the spatiotemporal precipitation patterns, especially in the dry season. As the statistical scores were mostly improved by this adjustment, the estimation of wet deposition with precipitation adjustment was considered to be superior. To utilize satellite measurements, the spatial distribution of wet deposition was revised. Based on this revision, it was found that Vietnam, Malaysia, and Indonesia were upward corrected, and Myanmar, Thailand, Lao PDR, Cambodia, and the Philippines were downward-corrected; these corrections were up to ±40 %. The improved accuracy of precipitation amount was key to estimating wet deposition in this study. These results suggest that the precipitation-adjusted approach has the potential to obtain accurate estimates of wet deposition through the fusion of models and observations.

In order to identify the causes of overestimate of the surface-level O3 mixing ratio simulated by three regional chemical-transport models, NAQPMS v.3 (abbreviated as NAQM in this paper), CMAQ v.5.0.2, and CMAQ v.4.7.1, compared to the EANET observational data at a marine remote site at Oki in July 2010, analyses of hourly O3 mixing ratios and net ozone production were made in the context of MICS-Asia III. In addition to Oki, model-simulated and observational data for two other EANET marine sites, Hedo and Ogasawara, were also examined. Three factors, i.e., long-range transport from the continent, in situ photochemical formation, and dry deposition of O3 on seawater, have been identified as contributing to the overestimate by these regional models at Oki. The calculated O3 mixing ratios during long-range transport from the continent were much higher for all three models than those of the observation. In situ photochemical formation, demonstrated by a distinct diurnal variation which was not discerned in the observational data, was seen in the simulated data of all three models and ascribed to the virtual transport of NOx from the southern urban areas of the main island of Japan. The overestimate of the O3 mixing ratio in the background oceanic air mass has been discussed referring to dry deposition velocity (Vd) of O3 over oceanic water. Sensitivity analysis of the dry deposition velocity to the concentration of O3 was made for Oki in July. An increase in Vd from 0.0005 to 0.001 cm s−1 used in the standard runs for CMAQ by a factor of 10 decreases the O3 mixing ratio by more than 20 ppbv on an event basis in certain periods of time and by ca. 4.9 ppbv as a monthly mean in July. The dry deposition velocity of O3 in Bohai Bay and the Yellow Sea has been assumed to be comparable to that of the open ocean in all three models, which could have resulted in the overestimate of O3 mixing ratios in this area and also in the long-range transport of O3 from the continent to Oki. A higher value of dry deposition velocity in this marine area is expected considering the higher content of organics in the surface sea layer brought by rivers and atmospheric wet deposition. Empirical measurements of the mixing ratios and dry deposition flux of O3 in this area are highly recommended, since they would affect the simulated mixing ratios in the downwind region in the Pacific Rim region.

The outflow of the East Asian haze (EAH) has attracted much attention in recent years. For downstream areas, it is meaningful to understand the impact of crucial upstream sources and the process analysis during transport. This study evaluated the impact of PM2.5 from the three largest industrial regions on the Asian continent, namely the Bohai Rim industrial region (BRIR), Yangtze River Delta industrial region (YRDIR), and Pearl River Delta industrial region (PRDIR), in Taiwan and discussed the processes during transport with the help of air quality modeling. The simulation results revealed that the contributions of monthly average PM2.5 from BRIR and YRDIR were 0.7–1.1 and 1.2–1.9 µg m−3 (∼ 5 % and 7.5 % of the total concentration) in Taiwan, respectively, in January 2017. When the Asian anticyclone moved from the Asian continent to the western Pacific, e.g., on 9 January 2017, the contributions from BRIR and YRDIR to northern Taiwan could reach daily averages of 8 and 11 µg m−3. The transport of EAH from BRIR and YRDIR to low-latitude regions was horizontal advection (HADV), vertical advection (ZADV), and vertical diffusion (VDIF) over the Bohai Sea and East China Sea. Over the Taiwan Strait and the northern South China Sea, cloud processes (CLDS) were the major contribution to PM2.5 due to a high relative humidity environment. Along the transport from high-latitude regions to low-latitude regions, aerosol chemistry (AERO) and dry deposition (DDEP) were the major removal processes. When the EAH intruded into northern Taiwan, the major processes for the gains of PM2.5 in northern Taiwan were HADV and AERO. The stronger the EAH, the more the EAH could influence central and southern Taiwan. Although PRDIR is located downstream of Taiwan under northeasterly wind, the PM2.5 from PRDIR could be lifted upward above the boundary layer, allowing it to move eastwards. When the PM2.5 plume moved over Taiwan and was blocked by mountains, PM2.5 could be transported downward, via boundary layer mixing (VDIF), as it was further enhanced by the passing cold surge. In contrast, for the simulation of July 2017, the influence from the three industrial regions was almost negligible unless there was a special weather system, such as thermal lows which may have carried pollutants from PRDIR to Taiwan, but this occurrence was rare.

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 compares the performance of 12 regional chemical transport models (CTMs) from the third phase of the Model Inter-Comparison Study for Asia (MICS-Asia III) on simulating the particulate matter (PM) over East Asia (EA) in 2010. The participating models include the Weather Research and Forecasting model coupled with Community Multiscale Air Quality (WRF-CMAQ; v4.7.1 and v5.0.2), the Regional Atmospheric Modeling System coupled with CMAQ (RAMS-CMAQ; v4.7.1 and v5.0.2), the Weather Research and Forecasting model coupled with chemistry (WRF-Chem; v3.6.1 and v3.7.1), Goddard Earth Observing System coupled with chemistry (GEOS-Chem), a non-hydrostatic model coupled with chemistry (NHM-Chem), the Nested Air Quality Prediction Modeling System (NAQPMS) and the NASA-Unified WRF (NU-WRF). This study investigates three model processes as the possible reasons for different model performances on PM. (1) Models perform very differently in the gas–particle conversion of sulfur (S) and oxidized nitrogen (N). The model differences in sulfur oxidation ratio (50 %) are of the same magnitude as that in SO42- concentrations. The gas–particle conversion is one of the main reasons for different model performances on fine mode PM. (2) Models without dust emission modules can perform well on PM10 at non-dust-affected sites but largely underestimate (up to 50 %) the PM10 concentrations at dust sites. The implementation of dust emission modules in the models has largely improved the model accuracies at dust sites (reduce model bias to −20 %). However, both the magnitude and distribution of dust pollution are not fully captured. (3) The amounts of modeled depositions vary among models by 75 %, 39 %, 21 % and 38 % for S wet, S dry, N wet and N dry depositions, respectively. Large inter-model differences are found in the washout ratios of wet deposition (at most 170 % in India) and dry deposition velocities (generally 0.3–2 cm s−1 differences over inland regions).

Serious urban ozone (O3) pollution was observed during the campaign of 2016 G20 summit in Hangzhou, China, while other pollutants had been significantly reduced by the short-term emission control measures. To understand the underlying mechanism, the Weather Research Forecast with Chemistry (WRF-Chem) model is used to investigate the spatial and temporal O3 variations in Hangzhou from 24 August to 6 September 2016. The model is first successfully evaluated and validated for local and regional meteorological and chemical parameters by using the ground and upper-air level observed data. High ozone concentrations, temporally during most of the daytime emission control period and spatially from the surface to the top of the planetary boundary layer, are captured in Hangzhou and even the whole Yangtze River Delta region. Various atmospheric processes are further analyzed to determine the influential factors of local ozone formation through the integrated process rate method. Interesting horizontal and vertical advection circulations of O3 are observed during several short periods, and the effects of these processes are nearly canceled out. As a result, ozone pollution is mainly attributed to the local photochemical reactions that are not obviously influenced by the emission reduction measures. The ratio of reduction of Volatile Organic Compounds (VOCs) to that of NOx is a critical parameter that needs to be carefully considered for future alleviation of ozone formation. In addition, the vertical diffusion from the upper-air background O3 also plays an important role in shaping the surface ozone concentration. These results provide insight into urban O3 formation in Hangzhou and support the Model Intercomparison Study Asia Phase III (MICS-Asia Phase III).

The Model Inter-Comparison Study for Asia (MICS-Asia) phase III was conducted to promote understanding of regional air quality and climate change in Asia, which have received growing attention due to the huge amount of anthropogenic emissions worldwide. This study provides an overview of acid deposition. Specifically, dry and wet deposition of the following species was analyzed: S (sulfate aerosol, sulfur dioxide (SO2), and sulfuric acid (H2SO4)), N (nitrate aerosol, nitrogen monoxide (NO), nitrogen dioxide (NO2), and nitric acid (HNO3)), and A (ammonium aerosol and ammonia (NH3)). The wet deposition simulated by a total of nine models was analyzed and evaluated using ground observation data from the Acid Deposition Monitoring Network in East Asia (EANET). In the phase III study, the number of observation sites was increased from 37 in the phase II study to 54, and southeast Asian countries were newly added. Additionally, whereas the analysis period was limited to representative months of each season in MICS-Asia phase II, the phase III study analyzed the full year of 2010. The scope of this overview mainly focuses on the annual accumulated deposition. In general, models can capture the observed wet deposition over Asia but underestimate the wet deposition of S and A, and show large differences in the wet deposition of N. Furthermore, the ratio of wet deposition to the total deposition (the sum of dry and wet deposition) was investigated in order to understand the role of important processes in the total deposition. The general dominance of wet deposition over Asia and attributions from dry deposition over land were consistently found in all models. Then, total deposition maps over 13 countries participating in EANET were produced, and the balance between deposition and anthropogenic emissions was calculated. Excesses of deposition, rather than of anthropogenic emissions, were found over Japan, northern Asia, and southeast Asia, indicating the possibility of long-range transport within and outside of Asia, as well as other emission sources. To improve the ability of models to capture the observed wet deposition, two approaches were attempted, namely, ensemble and precipitation adjustment. The ensemble approach was effective at modulating the differences in performance among models, and the precipitation-adjusted approach demonstrated that the model performance for precipitation played a key role in better simulating wet deposition. Finally, the lessons learned from the phase III study and future perspectives for phase IV are summarized.

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.

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 ( %). 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.

Spatiotemporal variations of ozone (O3) and nitrogen oxide (NOx) mixing ratios from 14 state-of-the-art chemical transport models (CTMs) are intercompared and evaluated with O3 observations in East Asia, within the framework of the Model Inter-Comparison Study for Asia Phase III (MICS-Asia III). This study was designed to evaluate the capabilities and uncertainties of current CTMs simulations for Asia and to provide multi-model estimates of pollutant distributions. These models were run by 14 independent groups working in China, Japan, South Korea, the United States and other countries/regions. Compared with the previous phase of MICS-Asia (MICS-Asia II), the evaluation with observations was extended from 4 months to 1 full year across China and the western Pacific Rim. In general, model performance levels for O3 varied widely by region and season. Most models captured the key patterns of monthly and diurnal variation of surface O3 and its precursors in the North China Plain and western Pacific Rim but failed to do so for the Pearl River Delta. A significant overestimation of surface O3 was evident from May to September/October and from January to May over the North China Plain, the western Pacific Rim and the Pearl River Delta. Comparisons drawn from observations show that the considerable diversity in O3 photochemical production partly contributed to this overestimation and to high levels of inter-model variability in O3 for North China. In terms of O3 soundings, the ensemble average of models reproduced the vertical structure for the western Pacific, but overestimated O3 levels to below 800 hPa in the summer. In the industrialized Pearl River Delta, the ensemble average presented an overestimation for the lower troposphere and an underestimation for the middle troposphere. The ensemble average of 13 models for O3 did not always exhibit superior performance compared with certain individual models in contrast with its superior value for Europe. This finding suggests that the spread of ensemble-model values does not represent all of the uncertainties of O3 or that most MICS-Asia III models missed key processes. This study improved the performance of modeling O3 in March at Japanese sites compared with MICS-Asia II. However, it overpredicted surface O3 concentrations for western Japan in July, which was not found by MICS-Asia II. Major challenges still remain with regard to identifying the sources of bias in surface O3 over East Asia in CTMs.

A total of 14 chemical transport models (CTMs) participated in the first topic of the Model Inter-Comparison Study for Asia (MICS-Asia) phase III. These model results are compared with each other and an extensive set of measurements, aiming to evaluate the current CTMs' ability in simulating aerosol concentrations, to document the similarities and differences among model performance, and to reveal the characteristics of aerosol components in large cities over East Asia. In general, these CTMs can well reproduce the spatial–temporal distributions of aerosols in East Asia during the year 2010. The multi-model ensemble mean (MMEM) shows better performance than most single-model predictions, with correlation coefficients (between MMEM and measurements) ranging from 0.65 (nitrate, NO3-) to 0.83 (PM2.5). The concentrations of black carbon (BC), sulfate (SO42-), and PM10 are underestimated by MMEM, with normalized mean biases (NMBs) of −17.0 %, −19.1 %, and −32.6 %, respectively. Positive biases are simulated for NO3- (NMB = 4.9 %), ammonium (NH4+) (NMB = 14.0 %), and PM2.5 (NMB = 4.4 %). In comparison with the statistics calculated from MICS-Asia phase II, frequent updates of chemical mechanisms in CTMs during recent years make the intermodel variability of simulated aerosol concentrations smaller, and better performance can be found in reproducing the temporal variations of observations. However, a large variation (about a factor of 2) in the ratios of SNA (sulfate, nitrate, and ammonium) to PM2.5 is calculated among participant models. A more intense secondary formation of SO42- is simulated by Community Multi-scale Air Quality (CMAQ) models, because of the higher SOR (sulfur oxidation ratio) than other models (0.51 versus 0.39). The NOR (nitric oxidation ratio) calculated by all CTMs has larger values (∼0.20) than the observations, indicating that overmuch NO3- is simulated by current models. NH3-limited condition (the mole ratio of ammonium to sulfate and nitrate is smaller than 1) can be successfully reproduced by all participant models, which indicates that a small reduction in ammonia may improve the air quality. A large coefficient of variation (CV > 1.0) is calculated for simulated coarse particles, especially over arid and semi-arid regions, which means that current CTMs have difficulty producing similar dust emissions by using different dust schemes. According to the simulation results of MMEM in six large Asian cities, different air-pollution control plans should be taken due to their different major air pollutants in different seasons. The MICS-Asia project gives an opportunity to discuss the similarities and differences of simulation results among CTMs in East Asian applications. In order to acquire a better understanding of aerosol properties and their impacts, more experiments should be designed to reduce the diversities among air quality models.

Heavy haze usually occurs in winter in eastern China. To control the severe air pollution during the season, comprehensive regional joint-control strategies were implemented throughout a campaign. To evaluate the effectiveness of these strategies and to provide some insights into strengthening the regional joint-control mechanism, the influence of control measures on levels of air pollution was estimated with an integrated measurement-emission-modeling method. To determine the influence of meteorological conditions, and the control measures on the air quality, in a comprehensive study, the 2nd World Internet Conference was held during 16–18 December 2015 in Jiaxing City, Zhejiang province, in the Yangtze River Delta (YRD) region. We first analyzed the air quality changes during four meteorological regimes and then compared the air pollutant concentrations before, during, and after the regulation under static meteorological conditions. Next, we conducted modeling scenarios to quantify the effects caused due to the air pollution control measures. We found that total emissions of SO2, NOx, PM2.5, and volatile organic compounds (VOCs) in Jiaxing were reduced by 56 %, 58 %, 64 %, and 80 %, respectively, while total emission reductions of SO2, NOx, PM2.5, and VOCs over the YRD region are estimated to be 10 %, 9 %, 10 %, and 11 %, respectively. Modeling results suggest that during the campaign from 8 to 18 December, PM2.5 daily average concentrations decreased by 10 µg m−3 with an average decrease of 14.6 %. Our implemented optimization analysis compared with previous studies also reveals that local emission reductions play a key role in air quality improvement, although it shall be supplemented by regional linkage. In terms of regional joint control, implementing pollution channel control 48 h before the event is of most benefit in getting similar results. Therefore, it is recommended that a synergistic emission reduction plan between adjacent areas with local pollution emission reductions as the core part should be established and strengthened, and emission reduction plans for different types of pollution through a stronger regional linkage should be reserved.

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.

Haze has been severely affecting the densely populated areas in China recently. While many of the efforts have been devoted to investigating the impact of local anthropogenic emission, limited attention has been paid to the contribution from long-range transport. In this study, we apply simulations from six participating models supplied through the Task Force on Hemispheric Transport of Air Pollution phase 2 (HTAP2) exercise to investigate the long-range transport impact of Europe (EUR) and Russia–Belarus–Ukraine (RBU) on the surface air quality in eastern Asia (EAS), with special focus on their contributions during the haze episodes in China. The impact of 20 % anthropogenic emission perturbation from the source region is extrapolated by a factor of 5 to estimate the full impact. We find that the full impacts from EUR and RBU are 0.99 µg m−3 (3.1 %) and 1.32 µg m−3 (4.1 %) during haze episodes, while the annual averaged full impacts are only 0.35 µg m−3 (1.7 %) and 0.53 µg m−3 (2.6 %). By estimating the aerosol response within and above the planetary boundary layer (PBL), we find that long-range transport from EUR within the PBL contributes to 22–38 % of the total column density of aerosol response in EAS. Comparison with the HTAP phase 1 (HTAP1) assessment reveals that from 2000 to 2010, the long-range transport from Europe to eastern Asia has decreased significantly by a factor of 2–10 for surface aerosol mass concentration due to the simultaneous emission reduction in source regions and emission increase in the receptor region. We also find the long-range transport from the Europe and RBU regions increases the number of haze events in China by 0.15 % and 0.11 %, and the North China Plain and southeastern China has 1–3 extra haze days (

With the rising anthropogenic emissions from human activities, elevated concentrations of air pollutants have been detected in the hemispheric air flows in recent years, aggravating the regional air pollution and deposition issues. However, the regional contributions of hemispheric air flows to deposition have been given little attention in the literature. In this light, we assess the impact of hemispheric transport on sulfur (S) and nitrogen (N) deposition for six world regions: North America (NA), Europe (EU), South Asia (SA), East Asia (EA), Middle East (ME) and Russia (RU) in 2010, by using the multi-model ensemble results from the 2nd phase of the Task Force Hemispheric Transport of Air Pollution (HTAP II) with 20 % emission perturbation experiments. About 27 %–58 %, 26 %–46 % and 12 %–23 % of local S, NOx and NH3 emissions and oxidation products are transported and removed by deposition outside of the source regions annually, with seasonal variation of 5 % more in winter and 5 % less in summer. The 20 % emission reduction in the source regions could affect 1 %–10 % of deposition in foreign continental regions and 1 %–14 % in foreign coastal regions and the open ocean. Significant influences are found from NA to the North Atlantic Ocean (2 %–14 %), and from EA to the North Pacific Ocean (4 %–10 %) and to western NA (4 %–6 %) (20 % emission reduction). The impact on deposition caused by short-distance transport between neighboring regions (i.e., from EU to RU) occurs throughout the whole year (slightly stronger in winter), while the long-range transport (i.e., from EA to NA) mainly takes place in spring and fall, which is consistent with the seasonality found for hemispheric transport of air pollutants. Deposition in the emission-intensive regions such as US, SA and EA is dominated ( ∼ 80 %) by own-region emissions, while deposition in the low-emission-intensity regions such as RU is almost equally affected by foreign exported emissions (40 %–60 %) and own-region emissions. We also find that deposition of the coastal regions or the near-coastal open ocean is twice more sensitive to hemispheric transport than the non-coastal continental regions, especially for regions in the downwind direction of emission sources (i.e., west coast of NA). This study highlights the significant impacts of hemispheric transport of air pollution on the deposition in coastal regions, the open ocean and low-emission-intensity regions. Further research is proposed to improve the ecosystem and human health, with regards to the enhanced hemispheric air flows.

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.

Near-surface and vertical in situ measurements of atmospheric particles were conducted in Shanghai during 19–23 March 2010 to explore the transport and chemical evolution of dust particles in a super dust storm. An air quality model with optimized physical dust emission scheme and newly implemented dust chemistry was utilized to study the impact of dust chemistry on regional air quality. Two discontinuous dust periods were observed with one traveling over northern China (DS1) and the other passing over the coastal regions of eastern China (DS2). Stronger mixing extents between dust and anthropogenic emissions were found in DS2, reflected by the higher SO2 ∕ PM10 and NO2 ∕ PM10 ratios as well as typical pollution elemental species such as As, Cd, Pb, and Zn. As a result, the concentrations of SO42− and NO3− and the ratio of Ca2+ ∕ Ca were more elevated in DS2 than in DS1 but opposite for the [NH4+] ∕ [SO42−+NO3−] ratio, suggesting the heterogeneous reactions between calcites and acid gases were significantly promoted in DS2 due to the higher level of relative humidity and gaseous pollution precursors. Lidar observation showed a columnar effect on the vertical structure of particle optical properties in DS1 that dust dominantly accounted for ∼ 80–90 % of the total particle extinction from near the ground to ∼ 700 m. In contrast, the dust plumes in DS2 were restrained within lower altitudes while the extinction from spherical particles exhibited a maximum at a high altitude of ∼ 800 m. The model simulation reproduced relatively consistent results with observations that strong impacts of dust heterogeneous reactions on secondary aerosol formation occurred in areas where the anthropogenic emissions were intensive. Compared to the sulfate simulation, the nitrate formation on dust is suggested to be improved in the future modeling efforts.

The Beijing–Tianjin–Hebei (BTH) region has been suffering from the most severe fine-particle (PM2. 5) pollution in China, which causes serious health damage and economic loss. Quantifying the source contributions to PM2. 5 concentrations has been a challenging task because of the complicated nonlinear relationships between PM2. 5 concentrations and emissions of multiple pollutants from multiple spatial regions and economic sectors. In this study, we use the extended response surface modeling (ERSM) technique to investigate the nonlinear response of PM2. 5 concentrations to emissions of multiple pollutants from different regions and sectors over the BTH region, based on over 1000 simulations by a chemical transport model (CTM). The ERSM-predicted PM2. 5 concentrations agree well with independent CTM simulations, with correlation coefficients larger than 0.99 and mean normalized errors less than 1 %. Using the ERSM technique, we find that, among all air pollutants, primary inorganic PM2. 5 makes the largest contribution (24–36 %) to PM2. 5 concentrations. The contribution of primary inorganic PM2. 5 emissions is especially high in heavily polluted winter and is dominated by the industry as well as residential and commercial sectors, which should be prioritized in PM2. 5 control strategies. The total contributions of all precursors (nitrogen oxides, NOx; sulfur dioxides, SO2; ammonia, NH3; non-methane volatile organic compounds, NMVOCs; intermediate-volatility organic compounds, IVOCs; primary organic aerosol, POA) to PM2. 5 concentrations range between 31 and 48 %. Among these precursors, PM2. 5 concentrations are primarily sensitive to the emissions of NH3, NMVOC + IVOC, and POA. The sensitivities increase substantially for NH3 and NOx and decrease slightly for POA and NMVOC + IVOC with the increase in the emission reduction ratio, which illustrates the nonlinear relationships between precursor emissions and PM2. 5 concentrations. The contributions of primary inorganic PM2. 5 emissions to PM2. 5 concentrations are dominated by local emission sources, which account for over 75 % of the total primary inorganic PM2. 5 contributions. For precursors, however, emissions from other regions could play similar roles to local emission sources in the summer and over the northern part of BTH. The source contribution features for various types of heavy-pollution episodes are distinctly different from each other and from the monthly mean results, illustrating that control strategies should be differentiated based on the major contributing sources during different types of episodes.

The Community Multiscale Air Quality (CMAQ) model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust. The default parameterization of initial threshold friction velocity constants are revised to correct the double counting of the impact of soil moisture in CMAQ by the reanalysis of field experiment data; source-dependent speciation profiles for dust emission are derived based on local measurements for the Gobi and Taklamakan deserts in East Asia; and dust heterogeneous chemistry is also implemented. The improved dust module in the CMAQ is applied over East Asia for March and April from 2006 to 2010. The model evaluation result shows that the simulation bias of PM10 and aerosol optical depth (AOD) is reduced, respectively, from −55.42 and −31.97 % by the original CMAQ to −16.05 and −22.1 % by the revised CMAQ. Comparison with observations at the nearby Gobi stations of Duolun and Yulin indicates that applying a source-dependent profile helps reduce simulation bias for trace metals. Implementing heterogeneous chemistry also results in better agreement with observations for sulfur dioxide (SO2), sulfate (SO42−), nitric acid (HNO3), nitrous oxides (NOx), and nitrate (NO3−). The investigation of a severe dust storm episode from 19 to 21 March 2010 suggests that the revised CMAQ is capable of capturing the spatial distribution and temporal variation of dust. The model evaluation also indicates potential uncertainty within the excessive soil moisture used by meteorological simulation. The mass contribution of fine-mode particles in dust emission may be underestimated by 50 %. The revised CMAQ model provides a useful tool for future studies to investigate the emission, transport, and impact of wind-blown dust over East Asia and elsewhere.

Data intensive simulations are often limited by their I/O (input/output) performance, and "novel" techniques need to be developed in order to overcome this limitation. The software package pnetCDF (parallel network Common Data Form), which works with parallel file systems, was developed to address this issue by providing parallel I/O capability. This study examines the performance of an application-level data aggregation approach which performs data aggregation along either row or column dimension of MPI (Message Passing Interface) processes on a spatially decomposed domain, and then applies the pnetCDF parallel I/O paradigm. The test was done with three different domain sizes which represent small, moderately large, and large data domains, using a small-scale Community Multiscale Air Quality model (CMAQ) mock-up code. The examination includes comparing I/O performance with traditional serial I/O technique, straight application of pnetCDF, and the data aggregation along row and column dimension before applying pnetCDF. After the comparison, "optimal" I/O configurations of this application-level data aggregation approach were quantified. Data aggregation along the row dimension (pnetCDFcr) works better than along the column dimension (pnetCDFcc) although it may perform slightly worse than the straight pnetCDF method with a small number of processors. When the number of processors becomes larger, pnetCDFcr outperforms pnetCDF significantly. If the number of processors keeps increasing, pnetCDF reaches a point where the performance is even worse than the serial I/O technique. This new technique has also been tested for a real application where it performs two times better than the straight pnetCDF paradigm.

An innovative extended response surface modeling technique (ERSM v1.0) is developed to characterize the nonlinear response of fine particles (PM2.5) to large and simultaneous changes of multiple precursor emissions from multiple regions and sectors. The ERSM technique is developed based on the conventional response surface modeling (RSM) technique; it first quantifies the relationship between PM2.5 concentrations and the emissions of gaseous precursors from each single region using the conventional RSM technique, and then assesses the effects of inter-regional transport of PM2.5 and its gaseous precursors on PM2.5 concentrations in the target region. We apply this novel technique with a widely used regional chemical transport model (CTM) over the Yangtze River delta (YRD) region of China, and evaluate the response of PM2.5 and its inorganic components to the emissions of 36 pollutant–region–sector combinations. The predicted PM2.5 concentrations agree well with independent CTM simulations; the correlation coefficients are larger than 0.98 and 0.99, and the mean normalized errors (MNEs) are less than 1 and 2% for January and August, respectively. It is also demonstrated that the ERSM technique could reproduce fairly well the response of PM2.5 to continuous changes of precursor emission levels between zero and 150%. Employing this new technique, we identify the major sources contributing to PM2.5 and its inorganic components in the YRD region. The nonlinearity in the response of PM2.5 to emission changes is characterized and the underlying chemical processes are illustrated.

Dynamical downscaling was applied in this study to link the global climate-chemistry model Community Atmosphere Model (CAM-Chem) with the regional models Weather Research and Forecasting (WRF) Model and Community Multi-scale Air Quality (CMAQ). Two representative concentration pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) were used to evaluate the climate impact on ozone concentrations in the 2050s. From the CAM-Chem global simulation results, ozone concentrations in the lower to mid-troposphere (surface to ~300 hPa), from mid- to high latitudes in the Northern Hemisphere, decreases by the end of the 2050s (2057–2059) in RCP 4.5 compared to present (2001–2004), with the largest decrease of 4–10 ppbv occurring in the summer and the fall; and an increase as high as 10 ppbv in RCP 8.5 resulting from the increased methane emissions. From the regional model CMAQ simulation results, under the RCP 4.5 scenario (2057–2059), in the summer when photochemical reactions are the most active, the large ozone precursor emissions reduction leads to the greatest decrease of downscaled surface ozone concentrations compared to present (2001–2004), ranging from 6 to 10 ppbv. However, a few major cities show ozone increases of 3 to 7 ppbv due to weakened NO titration. Under the RCP 8.5 scenario, in winter, downscaled ozone concentrations increase across nearly the entire continental US in winter, ranging from 3 to 10 ppbv due to increased methane emissions. More intense heat waves are projected to occur by the end of the 2050s in RCP 8.5, leading to a 0.3 ppbv to 2.0 ppbv increase (statistically significant except in the Southeast) of the mean maximum daily 8 h daily average (MDA8) ozone in nine climate regions in the US. Moreover, the upper 95% limit of MDA8 increase reaches 0.4 ppbv to 1.5 ppbv in RCP 4.5 and 0.6 ppbv to 3.2 ppbv in RCP 8.5. The magnitude differences of increase between RCP 4.5 and 8.5 also reflect that the increase of methane emissions may favor or strengthen the effect of heat waves.

Three field campaigns were conducted before, during, and after the 2010 World Expo in Shanghai, aiming to understand the response of secondary aerosol components to both control measures and human activities. In spring, PM2.5 (particulate matter) averaged 34.5 ± 20.9 μg m−3 with a severe pollution episode influenced by a floating dust originating from northwestern China on 26–28 April, right before the opening of the expo. With the approaching expo a significant increasing trend of SNA (SO42−, NO3−, and NH4+) concentrations was observed from 22 April to 2 May, attributed to the enhanced human activities. Nitrate had the most significant daily increasing rate of 1.1 μg m−3d−1 due to enhanced vehicle emission. In summer, two intensive pollution episodes were found to be a mixed pollution of SNA with biomass burning due to loose control of post-harvest straw burning. In the autumn phase of the expo, before the closing of the expo (20–30 October), the air quality over Shanghai was much better than ever before. However, the air quality rapidly plummeted as soon as the expo was announced closed. SNA increased 3–6 fold to be 42.1 and 68.2 μg m−3 on 31 October and 1 November, respectively, as compared to 20–30 October. Of which, nitrate increased most ~5–8 fold, indicating the serious impact from enhanced vehicle emission. Compared to the spring and summer of 2009, NO3− increased 12–15% while SO42− showed reductions of 15–30%. Continuous desulfurization of SO2 emission from power plants in recent years was responsible for the lowered SO42−, while increased traffic emission from the tremendous number of expo visitors was the major contributor to the increased NO3−. Compared to the autumn of 2009, all the ion components increased in 2010, owing to the lifting of emission control measures after the expo. SO42− was found least increased while NO3− and Ca2+ had tremendous increases of 150 and 320%, respectively. The anthropogenic Ca as a tracer from construction dust increased from 2.88 ± 1.85 μg m−3 during the expo to 6.98 ± 3.19 μg m−3 during the post-expo period, attributed to the resumption of construction works after the expo. The lack of successive control measures with the loose regulations after the expo were responsible for this jump of the bad quality. The ratio of NO3−/SO42− in PM2.5 over Shanghai had a significant increasing trend from ~0.3 in the early 2000s to more than 1.0 in 2010, indicating the increasing role of mobile sources. Reducing NOx emission will be China's priority in the future in order to improve the air quality over the megacities. In addition, lowering mineral aerosol components (e.g., Ca2+) was also demonstrated to be beneficial for alleviating air pollution in China. This study demonstrated that stringent emission control measures aiming at mega-events in China could achieve positive benefits on improving the air quality in a short term. However, persistent efforts of curbing the anthropogenic emission remain a long way to go in the future.

The Chinese Spring Festival is one of the most important traditional festivals in China. The peak transport in the Spring Festival season (spring travel rush) provides a unique opportunity for investigating the impact of human activity on air quality in the Chinese megacities. Emission sources are varied and fluctuate greatly before, during and after the Festival. Increased vehicular emissions during the "spring travel rush" before the 2009 Festival resulted in high level pollutants of NOx (270 μg m−3), CO (2572 μg m−3), black carbon (BC) (8.5 μg m−3) and extremely low single scattering albedo of 0.76 in Shanghai, indicating strong, fresh combustion. Organics contributed most to PM2.5, followed by NO3−, NH4+, and SO42−. During the Chinese Lunar New Year's Eve and Day, widespread usage of fireworks caused heavy pollution of extremely high aerosol concentration, scattering coefficient, SO2, and NOx. Due to the "spring travel rush" after the festival, anthropogenic emissions gradually climbed and mirrored corresponding increases in the aerosol components and gaseous pollutants. Secondary inorganic aerosol (SO42−, NO3−, and NH4+) accounted for a dominant fraction of 74% in PM2.5 due to an increase in human activity. There was a greater demand for energy as vast numbers of people using public transportation or driving their own vehicles returned home after the Festival. Factories and constructions sites were operating again. The potential source contribution function (PSCF) analysis illustrated the possible source areas for air pollutants of Shanghai. The effects of regional and long-range transport were both revealed. Five major sources, i.e. natural sources, vehicular emissions, burning of fireworks, industrial and metallurgical emissions, and coal burning were identified using the principle component analysis. The average visibility during the whole study period was less than 6 km. It had been estimated that 50% of the total light extinction was due to the high water vapor in the atmosphere. This study demonstrates that organic aerosol was the largest contributor to aerosol extinction at 47%, followed by sulfate ammonium, nitrate ammonium, and EC at 22%, 14%, and 12%, respectively. Our results indicated the dominant role of traffic-related aerosol species (i.e. organic aerosol, nitrate and EC) on the formation of air pollution, and suggested the importance of controlling vehicle numbers and emissions in mega-cities of China as its population and economy continue to grow.

A high O3 episode was detected in urban Shanghai, a typical city in the Yangtze River Delta (YRD) region in August 2010. The CMAQ integrated process rate method is applied to account for the contribution of different atmospheric processes during the high pollution episode. The analysis shows that the maximum concentration of ozone occurs due to transport phenomena, including vertical diffusion and horizontal advective transport. Gas-phase chemistry producing O3 mainly occurs at the height of 300–1500 m, causing a strong vertical O3 transport from upper levels to the surface layer. The gas-phase chemistry is an important sink for O3 in the surface layer, coupled with dry deposition. Cloud processes may contribute slightly to the increase of O3 due to convective clouds or to the decrease of O3 due to scavenging. The horizontal diffusion and heterogeneous chemistry contributions are negligible during the whole episode. Modeling results show that the O3 pollution characteristics among the different cities in the YRD region have both similarities and differences. During the buildup period, the O3 starts to appear in the city regions of the YRD and is then transported to the surrounding areas under the prevailing wind conditions. The O3 production from photochemical reaction in Shanghai and the surrounding area is most significant, due to the high emission intensity in the large city; this ozone is then transported out to sea by the westerly wind flow, and later diffuses to rural areas like Chongming island, Wuxi and even to Nanjing. The O3 concentrations start to decrease in the cities after sunset, due to titration of the NO emissions, but ozone can still be transported and maintain a significant concentration in rural areas and even regions outside the YRD region, where the NO emissions are very small.

To evaluate the impact of biomass burning from Southeast Asia to East Asia, this study conducted numerical simulations during NASA's 2006 Biomass-burning Aerosols in South-East Asia: Smoke Impact Assessment (BASE-ASIA). Two typical episode periods (27–28 March and 13–14 April) were examined. Two emission inventories, FLAMBE and GFED, were used in the simulations. The influences during two episodes in the source region (Southeast Asia) contributed to the surface CO, O3 and PM2.5 concentrations as high as 400 ppbv, 20 ppbv and 80 μg m−3, respectively. The perturbations with and without biomass burning of the above three species during the intense episodes were in the range of 10 to 60%, 10 to 20% and 30 to 70%, respectively. The impact due to long-range transport could spread over the southeastern parts of East Asia and could reach about 160 to 360 ppbv, 8 to 18 ppbv and 8 to 64 μg m−3 on CO, O3 and PM2.5, respectively; the percentage impact could reach 20 to 50% on CO, 10 to 30% on O3, and as high as 70% on PM2.5. In March, the impact of biomass burning mainly concentrated in Southeast Asia and southern China, while in April the impact becomes slightly broader and even could go up to the Yangtze River Delta region. Two cross-sections at 15° N and 20° N were used to compare the vertical flux of biomass burning. In the source region (Southeast Asia), CO, O3 and PM2.5 concentrations had a strong upward transport from surface to high altitudes. The eastward transport becomes strong from 2 to 8 km in the free troposphere. The subsidence process during the long-range transport contributed 60 to 70%, 20 to 50%, and 80% on CO, O3 and PM2.5, respectively to surface in the downwind area. The study reveals the significant impact of Southeastern Asia biomass burning on the air quality in both local and downwind areas, particularly during biomass burning episodes. This modeling study might provide constraints of lower limit. An additional study is underway for an active biomass burning year to obtain an upper limit and climate effects.

An intensive aerosol and gases campaign was performed at Shanghai in the Yangtze River Delta region over Eastern China from late March to early June 2009. This study provided a complementary picture of typical haze types and the formation mechanisms in megacities over China by using a synergy of ground-based monitoring, satellite and lidar observations. During the whole study period, several extreme low visibility periods were observed with distinct characteristics, and three typical haze types were identified, i.e. secondary inorganic pollution, dust, and biomass burning. Sulfate, nitrate and ammonium accounted for a major part of PM2.5 mass during the secondary inorganic pollution, and the good correlation between SO2/NOx/CO and PM2.5 indicated that coal burning and vehicle emission were the major sources. Large-scale regions with high AOD (aerosol optical depths) and low Ångström exponent were detected by remote-sensing observation during the dust pollution episode, and this episode corresponded to coarse particles rich in mineral components such as Al and Ca contributing 76.8% to TSP. The relatively low Ca/Al ratio of 0.75 along with the air mass backward trajectory analysis suggested the dust source was from Gobi Desert. Typical tracers for biomass burning from satellite observation (column CO and HCHO) and from ground measurement (CO, particulate K+, OC, and EC) were greatly enhanced during the biomass burning pollution episode. The exclusive linear correlation between CO and PM2.5 corroborated that organic aerosol dominated aerosol chemistry during biomass burning, and the high concentration and enrichment degree of arsenic (As) could be also partly derived from biomass burning. Aerosol optical profile observed by lidar demonstrated that aerosol was mainly constrained below the boundary layer and comprised of spheric aerosol (depolarization ratio

PM2.5 and TSP samples were collected at the summit of Mountain Tai (MT) (1534 m a.s.l.) in spring 2006/2007 and summer 2006 to investigate the characteristics of aerosols over central eastern China. For comparison, aerosol samples were also collected at Tazhong, Urumqi, and Tianchi in Xinjiang in northwestern China, Duolun and Yulin in northern China, and two urban sites in the megacities, Beijing and Shanghai, in 2007. Daily mass concentrations of TSP and PM2.5 ranged from 39.6–287.6 μg m−3 and 17.2–235.7 μg m−3 respectively at the summit of MT. Averaged concentrations of PM2.5 showed a pronounced seasonal variation with higher concentration in summer than spring. 17 water-soluble ions (SO42−, NO3−, Cl−, F−, PO43−, NO2−, CH3COO−, CH2C2O42−, C2H4C2O42−, HCOO−, MSA, C2O42−, NH4+, Ca2+, K+, Mg2+, Na+), and 19 elements of all samples were measured. SO42−, NO3−, and NH4+ were the major water-soluble species in PM2.5, accounting for 61.50 % and 72.65 % of the total measured ions in spring and summer, respectively. The average ratio of PM2.5/TSP was 0.37(2006) and 0.49(2007) in spring, while up to 0.91 in summer, suggesting that aerosol particles were primarily comprised of fine particles in summer and of considerable coarse particles in spring. Crustal elements (e.g., Ca, Mg, Al, Fe, etc.) showed higher concentration in spring than summer, while most of the pollution species (SO42−, NO3−, K+, NO2−, NH4+, Cl−, organic acids, Pb, Zn, Cd, and Cr) from local/regional anthropogenic emissions or secondary formation presented higher concentration in summer. The ratio of Ca/Al suggested the impact of Asian dust from the western deserts on the air quality in this region. The high concentration of K+ in PM2.5 (4.41 μg m−3) and its good correlation with black carbon (r = 0.90) and oxalic acid (r = 0.87) suggested the severe pollution from biomass burning, which was proved to be a main source of fine particles over central eastern China in summer. The contribution of biomass burning to the fine particle at MT accounted for 7.56 % in spring and 36.71 % in summer, and even reached to 81.58 % on a day. As and Pb were two of the most enriched elements. The long-range transport of aerosols spread the heavy pollution from coal-mining/coal-ash to everywhere over China. Anthropogenic air-pollution was evidently rather severe at MT, though it has been declared by UNESCO to be a World Heritage site.

Simulations of present and future average regional ozone and PM2.5 concentrations over the United States were performed to investigate the potential impacts of global climate change and emissions on regional air quality using CMAQ. Various emissions and climate conditions with different biogenic emissions and domain resolutions were implemented to study the sensitivity of future air quality trends from the impacts of changing biogenic emissions. A comparison of GEOS-Chem and CMAQ was performed to investigate the effect of downscaling on the prediction of future air quality trends. For ozone, the impacts of global climate change are relatively smaller when compared to the impacts of anticipated future emissions reduction, except for the Northeast area, where increasing biogenic emissions due to climate change have stronger positive effects (increases) to the regional ozone air quality. The combination effect from both climate change and emission reductions leads to approximately a 10 % or 5 ppbv decrease of the maximum daily average eight-hour ozone (MDA8) over the Eastern United States. For PM2.5, the impacts of global climate change have shown insignificant effect, where as the impacts of anticipated future emissions reduction account for the majority of overall PM2.5 reductions. The annual average 24-h PM2.5 of the future-year condition was found to be about 40 % lower than the one from the present-year condition, of which 60 % of its overall reductions are contributed to by the decrease of SO4 and NO3 particulate matters. Changing the biogenic emissions model increases the MDA8 ozone by about 5–10 % or 3–5 ppbv in the Northeast area. Conversely, it reduces the annual average PM2.5 by 5 % or 1.0 μg m−3 in the Southeast region.

Regional trans-boundary air pollution has become an important issue in the field of air pollution modeling. This paper presents the results of the implementation of the MM5-CMAQ modeling system in the Yangtze River Delta (YRD) for the months of January and July of 2004. The meteorological parameters are obtained by using the MM5 model. A new regional emission inventory with spatial and temporal allocations based on local statistical data has been developed to provide input emissions data to the MM5-CMAQ modeling system. The pollutant concentrations obtained from the MM5-CMAQ modeling system have been compared with observational data from the national air pollution monitoring network. It is found that air quality in winter in the YRD is generally worse than in summer, due mainly to unfavorable meteorological dispersion conditions. In winter, the pollution transport from Northern China to the YRD reinforces the pollution caused by large local emissions. The monthly average concentration of SO2 in the YRD is 0.026 ± 0.011 mg m−3 in January and 0.017 ± 0.009 mg m−3 in July. Monthly average concentrations of NO2 in the YRD in January and July are 0.021 ± 0.009 mg m−3, and 0.014 ± 0.008 mg m−3, respectively. The monthly average concentration of PM10 in the YRD is 0.080 ± 0.028 mg m−3 in January and 0.025 ± 0.015 mg m−3 in July. Visibility is also a problem, with average deciview values of 26.4 ± 2.95 dcv in winter and 17.6 ± 3.3 dcv in summer. The ozone concentration in the downtown area of a city like Zhoushan can be very high, with the highest simulated value reaching 0.24 mg m−3. In January, the monthly average concentration of O3 in the YRD is 0.052 ± 0.011 mg m−3, and 0.054 ± 0.008 mg m−3 in July. Our results show that ozone and haze have become extremely important issues in the regional air quality. Thus, regional air pollution control is urgently needed to improve air quality in the YRD.

Recently, downscaling global atmospheric model outputs (GCTM) for the USEPA Community Multiscale Air Quality (CMAQ) Initial (IC) and Boundary Conditions (BC) have become practical because of the rapid growth of computational technologies that allow global simulations to be completed within a reasonable time. The traditional method of generating IC/BC by profile data has lost its advocates due to the weakness of the limited horizontal and vertical variations found on the gridded boundary layers. Theoretically, high quality GCTM IC/BC should yield a better result in CMAQ. Unfortunately, several researchers have found that the outputs from GCTM IC/BC are not necessarily better than profile IC/BC due to the excessive transport of O3 aloft in GCTM IC/BC. In this paper, we intend to investigate the effects of using profile IC/BC and global atmospheric model data. In addition, we are suggesting a novel approach to resolve the existing issue in downscaling. In the study, we utilized the GEOS-Chem model outputs to generate time-varied and layer-varied IC/BC for year 2002 with the implementation of tropopause determining algorithm in the downscaling process (i.e., based on chemical (O3) tropopause definition). The comparison between the implemented tropopause approach and the profile IC/BC approach is performed to demonstrate improvement of considering tropopause. It is observed that without using tropopause information in the downscaling process, unrealistic O3 concentrations are created at the upper layers of IC/BC. This phenomenon has caused over-prediction of surface O3 in CMAQ. In addition, the amount of over-prediction is greatly affected by temperature and latitudinal location of the study domain. With the implementation of the algorithm, we have successfully resolved the incompatibility issues in the vertical layer structure between global and regional chemistry models to yield better surface O3 predictions than profile IC/BC for both summer and winter conditions. At the same time, it improved the vertical O3 distribution of CMAQ outputs. It is strongly recommended that the tropopause information should be incorporated into any two-way coupled global and regional models, where the tropospheric regional model is used, to solve the vertical incompatibility that exists between global and regional models. We have discovered that the previously published paper was not the latest version of the manuscript we intended to use. Some corrections made during the second ACPD reviewing process were not incorporated in the text. As a result, the figure numbers (i.e., figure number below the graph) were not referenced correctly in the manuscript. Therefore, we have decided to re-publish this paper as a corrigendum.

Recently, downscaling global atmospheric model outputs (GCTM) for the USEPA Community Multiscale Air Quality (CMAQ) Initial (IC) and Boundary Conditions (BC) have become practical because of the rapid growth of computational technologies that allow global simulations to be completed within a reasonable time. The traditional method of generating IC/BC by profile data has lost its advocates due to the weakness of the limited horizontal and vertical variations found on the gridded boundary layers. Theoretically, high quality GCTM IC/BC should yield a better result in CMAQ. Unfortunately, several researchers have found that the outputs from GCTM IC/BC are not necessarily better than profile IC/BC due to the excessive transport of O3 aloft in GCTM IC/BC. In this paper, we intend to investigate the effects of using profile IC/BC and global atmospheric model data. In addition, we are suggesting a novel approach to resolve the existing issue in downscaling. In the study, we utilized the GEOS-Chem model outputs to generate time-varied and layer-varied IC/BC for year 2002 with the implementation of tropopause determining algorithm in the downscaling process (i.e., based on chemical (O3) tropopause definition). The comparison between the implemented tropopause approach and the profile IC/BC approach is performed to demonstrate improvement of considering tropopause. It is observed that without using tropopause information in the downscaling process, unrealistic O3 concentrations are created at the upper layers of IC/BC. This phenomenon has caused over-prediction of surface O3 in CMAQ. In addition, the amount of over-prediction is greatly affected by temperature and latitudinal location of the study domain. With the implementation of the algorithm, we have successfully resolved the incompatibility issues in the vertical layer structure between global and regional chemistry models to yield better surface O3 predictions than profile IC/BC for both summer and winter conditions. At the same time, it improved the vertical O3 distribution of CMAQ outputs. It is strongly recommended that the tropopause information should be incorporated into any two-way coupled global and regional models, where the tropospheric regional model is used, to solve the vertical incompatibility that exists between global and regional models.

A new inventory of air pollutant emissions in Asia in the year 2006 is developed to support the Intercontinental Chemical Transport Experiment-Phase B (INTEX-B) funded by the National Aeronautics and Space Administration (NASA). Emissions are estimated for all major anthropogenic sources, excluding biomass burning. We estimate total Asian anthropogenic emissions in the year 2006 as follows: 47.1 Tg SO2, 36.7 Tg NOx, 298.2 Tg CO, 54.6 Tg NMVOC, 29.2 Tg PM10, 22.2 Tg PM2.5, 2.97 Tg BC, and 6.57 Tg OC. We emphasize emissions from China because they dominate the Asia pollutant outflow to the Pacific and the increase of emissions from China since 2000 is of great concern. We have implemented a series of improved methodologies to gain a better understanding of emissions from China, including a detailed technology-based approach, a dynamic methodology representing rapid technology renewal, critical examination of energy statistics, and a new scheme of NMVOC speciation for model-ready emissions. We estimate China's anthropogenic emissions in the year 2006 to be as follows: 31.0 Tg SO2, 20.8 Tg NOx, 166.9 Tg CO, 23.2 Tg NMVOC, 18.2 Tg PM10, 13.3 Tg PM2.5, 1.8 Tg BC, and 3.2 Tg OC. We have also estimated 2001 emissions for China using the same methodology and found that all species show an increasing trend during 2001–2006: 36% increase for SO2, 55% for NOx, 18% for CO, 29% for VOC, 13% for PM10, and 14% for PM2.5, BC, and OC. Emissions are gridded at a resolution of 30 min×30 min and can be accessed at our web site (http://mic.greenresource.cn/intex-b2006).

Abstract The change in global mean surface temperature is a crucial and broadly used indicator of the evolution of climate change. Any decadal scale changes in warming rate are however obfuscated by internal variability. Here we show that the surface temperature increase through the recent La Nina influenced years (2022) is consistent with the 50-year trend of 0.18 °C/decade. We use an Earth System Model based tool to filter out modulations to the warming rate by sea-surface temperature patterns and find consistent warming rates in four major global temperature data series. However, we also find clear indications, in all observational series, of a step-up in warming rate since around 1990. CMIP6 models generally do not capture this observed combination of long-term warming rate and recent increase.

While the Intergovernmental Panel on Climate Change (IPCC) physical science reports usually assess a handful of future scenarios, the Working Group III contribution on climate mitigation to the IPCC's Sixth Assessment Report (AR6 WGIII) assesses hundreds to thousands of future emissions scenarios. A key task in WGIII is to assess the global mean temperature outcomes of these scenarios in a consistent manner, given the challenge that the emissions scenarios from different integrated assessment models (IAMs) come with different sectoral and gas-to-gas coverage and cannot all be assessed consistently by complex Earth system models. In this work, we describe the “climate-assessment” workflow and its methods, including infilling of missing emissions and emissions harmonisation as applied to 1202 mitigation scenarios in AR6 WGIII. We evaluate the global mean temperature projections and effective radiative forcing (ERF) characteristics of climate emulators FaIRv1.6.2 and MAGICCv7.5.3 and use the CICERO simple climate model (CICERO-SCM) for sensitivity analysis. We discuss the implied overshoot severity of the mitigation pathways using overshoot degree years and look at emissions and temperature characteristics of scenarios compatible with one possible interpretation of the Paris Agreement. We find that the lowest class of emissions scenarios that limit global warming to “1.5 ∘C (with a probability of greater than 50 %) with no or limited overshoot” includes 97 scenarios for MAGICCv7.5.3 and 203 for FaIRv1.6.2. For the MAGICCv7.5.3 results, “limited overshoot” typically implies exceedance of median temperature projections of up to about 0.1 ∘C for up to a few decades before returning to below 1.5 ∘C by or before the year 2100. For more than half of the scenarios in this category that comply with three criteria for being “Paris-compatible”, including net-zero or net-negative greenhouse gas (GHG) emissions, median temperatures decline by about 0.3–0.4 ∘C after peaking at 1.5–1.6 ∘C in 2035–2055. We compare the methods applied in AR6 with the methods used for SR1.5 and discuss their implications. This article also introduces a “climate-assessment” Python package which allows for fully reproducing the IPCC AR6 WGIII temperature assessment. This work provides a community tool for assessing the temperature outcomes of emissions pathways and provides a basis for further work such as extending the workflow to include downscaling of climate characteristics to a regional level and calculating impacts.

The pattern of sea surface temperatures affects global mean temperatures from year to year. By filtering out parts of this natural variability, researchers show that they can more rapidly detect the influence of mitigation of CO2 emissions on the climate

Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

Strong mitigation of anthropogenic emissions is necessary, but it is not clear how fast these efforts would lead to temperature changes. Here, the authors find that there is a substantial delay between reductions of emissions and a detectable change in surface temperature for a number of climate forcers.

We calculate the absolute regional temperature change potential (ARTP) of various short-lived climate forcers (SLCFs) based on detailed radiative forcing (RF) calculations from four different models. The temperature response has been estimated for four latitude bands (90–28° S, 28° S–28° N, 28–60° N, and 60–90° N). The regional pattern in climate response not only depends on the relationship between RF and surface temperature, but also on where and when emissions occurred and atmospheric transport, chemistry, interaction with clouds, and deposition. We present four emissions cases covering Europe, East Asia, the global shipping sector, and the entire globe. Our study is the first to estimate ARTP values for emissions during Northern Hemisphere summer (May–October) and winter season (November–April). The species studied are aerosols and aerosol precursors (black carbon, organic carbon, SO2, NH3), ozone precursors (NOx, CO, volatile organic compound), and methane (CH4). For the response to BC in the Arctic, we take into account the vertical structure of the RF in the atmosphere, and an enhanced climate efficacy for BC deposition on snow. Of all SLCFs, BC is the most sensitive to where and when the emissions occur, as well as giving the largest difference in response between the latitude bands. The temperature response in the Arctic per unit BC emission is almost four times larger and more than two times larger than the global average for Northern Hemisphere winter emissions for Europe and East Asia, respectively. The latitudinal breakdown likely gives a better estimate of the global temperature response as it accounts for varying efficacies with latitude. An annual pulse of non-methane SLCF emissions globally (representative of 2008) lead to a global cooling. In contrast, winter emissions in Europe and East Asia give a net warming in the Arctic due to significant warming from BC deposition on snow.

This study examines the impacts of emissions from aviation in six source regions on global and regional temperatures. We consider the NOx-induced impacts on ozone and methane, aerosols and contrail-cirrus formation and calculate the global and regional emission metrics global warming potential (GWP), global temperature change potential (GTP) and absolute regional temperature change potential (ARTP). The GWPs and GTPs vary by a factor of 2–4 between source regions. We find the highest aviation aerosol metric values for South Asian emissions, while contrail-cirrus metrics are higher for Europe and North America, where contrail formation is prevalent, and South America plus Africa, where the optical depth is large once contrails form. The ARTP illustrate important differences in the latitudinal patterns of radiative forcing (RF) and temperature response: the temperature response in a given latitude band can be considerably stronger than suggested by the RF in that band, also emphasizing the importance of large-scale circulation impacts. To place our metrics in context, we quantify temperature change in four broad latitude bands following 1 year of emissions from present-day aviation, including CO2. Aviation over North America and Europe causes the largest net warming impact in all latitude bands, reflecting the higher air traffic activity in these regions. Contrail cirrus gives the largest warming contribution in the short term, but remain important at about 15 % of the CO2 impact in several regions even after 100 years. Our results also illustrate both the short- and long-term impacts of CO2: while CO2 becomes dominant on longer timescales, it also gives a notable warming contribution already 20 years after the emission. Our emission metrics can be further used to estimate regional temperature change under alternative aviation emission scenarios. A first evaluation of the ARTP in the context of aviation suggests that further work to account for vertical sensitivities in the relationship between RF and temperature response would be valuable for further use of the concept.