High-resolution air quality models (AQMs) are critical for real-time air quality forecasting and exposure assessment, although their computational costs increase cubically with resolution. Quantifying model sensitivity to resolution is therefore crucial for developing effective forecasting systems. This study conducts a systematic model intercomparison of three widely used AQMs (CAMx, CMAQ, NAQPMS) under identical input conditions at 45, 15, and 5 km resolutions to forecast PM2.5 and O3 in the North China Plain during 2021. Results indicate distinct, model-dependent responses to grid refinement. NAQPMS achieves the optimal PM2.5 forecasting performance at 5 km, with improvements in nearly all evaluated statistics. CMAQ excels in O3 prediction at 5 km resolution, with RMSE reducing 6.48 mu g/m3 relative to the coarsest grids. We also found that terrain complexity significantly influences these resolution-dependent biases, leading to a substantial 19.51% reduction in NMB in the CAMx PM2.5 simulation over mountain areas. Moreover, the evaluation of 10-day forecasting accuracy suggests that a high-resolution setting is recommended for NAQPMS and CMAQ, whereas a coarser resolution is sufficient for CAMx. These findings underscore that optimizing real-time forecasting strategies requires a critical investigation of inter-model physicochemical discrepancies rather than universally pursuing higher resolution.

Abstract Accurate simulation of regional carbon dioxide (CO 2 ) concentrations is critical for urban carbon monitoring, inverse modeling and mitigation. However, large uncertainties persist due to differences in anthropogenic emission inventories in China. Focusing on Jiangsu Province in the Yangtze River Delta, where the mean inter‐inventory spread in annual city‐level total emissions exceeds 60% and spatial discrepancies are substantial, we assessed how six widely used inventories affect modeled CO 2 fields. Using a 3‐km WRF‐Chem‐VPRM framework, we performed simulations for July and December 2022. To isolate the impact of inventory‐related uncertainties, we designed sensitivity experiments that separately perturbed inventory selection, emission magnitude, spatial distribution, and temporal and vertical allocation used in the inventory‐to‐model matching. All experiments were driven by identical meteorological conditions to ensure comparability. Model outputs showed good consistency with meteorological observations, CarbonTracker near‐surface CO 2 , and OCO‐2 XCO 2 ( R ≈ 0.83), while also capturing physically reasonable near‐surface diurnal behavior. Inventory selection led to a nighttime urban domain‐averaged standard deviation of 8.2 ppm. Sensitivity results indicated that spatial allocation differences contributed more to modeled CO 2 variability than total emission magnitude. Under stable boundary‐layer conditions, vertical allocation emerged as a key uncertainty source, producing 25–50 ppm differences in surface CO 2 . These results demonstrate that inventory‐to‐model matching, especially vertical allocation, can exceed the impact of inventory selection for high‐resolution urban CO 2 simulations under stable nighttime conditions. This study provides a quantitative basis for diagnosing inventory‐induced variability and supports the development of fine‐resolution, vertically resolved inventories for robust urban CO 2 modeling and future inversion efforts.

Abstract. Simulations from Model Inter-Comparison Study for Asia (MICS-Asia) phase III generally underestimate regional nitrogen wet deposition, mainly because aerosol below-cloud scavenging processes are oversimplified or ignored in models. To address the problem, most existing studies adopt empirical corrections rather than optimizing physical mechanisms. This study develops an improved physically-based below-cloud wet scavenging parameterization scheme, which is implemented into the Nested Air Quality Prediction Model System (NAQPMS) for comparative simulations over East Asia in 2014. On the basis of conventional collision mechanisms, this scheme further incorporates three additional key mechanisms, including thermophoresis, diffusiophoresis and electrostatic interaction. The results show that the new scheme not only well captures the observed aerosols below-cloud scavenging coefficients, but also enables refined characterization of separate in-cloud and below-cloud wet deposition processes. Pronounced simulation improvements are found in heavily polluted regions including Beijing-Tianjin-Hebei region, Northeast China and Yangtze River Delta, while slight overestimation appears at several sites in Korea and Japan. Furthermore, the new scheme effectively elevates the contribution of below-cloud scavenging, especially for reduced nitrogen, achieving good agreement with observations in Beijing. Accurate simulations in both the in-cloud and below-cloud processes facilitate the reliable assessments of long-range transport and near-surface deposition fluxes of pollutants. This study demonstrates the necessity of fully resolving physically based wet scavenging mechanisms for high-precision nitrogen deposition modeling, which further advances our understanding of regional pollutant transport and the global nitrogen cycle.

The North China Plain (NCP) faced severe summer ozone pollution in 2023, exacerbating risks to public health and crop yield. Accurate county-level ozone source attribution is essential for precise air quality management, yet conventional city-scale source modeling often overlooks heterogeneity in intra-urban contributions. Here, the Nested Air Quality Prediction Modeling System (NAQPMS), coupled with an online tracer-tagging module, was employed to quantify ozone sources and crop impacts, successfully reproducing spatiotemporal ozone variations across the NCP. The results showed that regional transport dominated summer ozone formation; emissions within 200 km contributed 43%-49% to the site-averaged maximum daily 8-h average (MDA8) O3, rising to 77%-91% at the 800 km scale. Local priority control zones shifted substantially when evaluated against site-average, site-maximum, and maximum population-weighted metrics. Notably, Beijing's maximum noontime ozone peaks (MNP) differ distinctly from MDA8 O3: local emissions contribute 44% to MNP versus 26% to MDA8 O3, whereas 200-500 km transport dominates MNP in Zhengzhou and 500-800 km transport in Shijiazhuang, reflecting intensified midday photochemistry and precursor transport. Furthermore, AOT40-based assessments estimate 21% relative maize yield losses (RYL) across the NCP, primarily attributable to regional transport. In Beijing, local emissions contribute 22% to maize RYL, with urban sources accounting for 26% of local emission-induced RYL. These findings underscore the need for coordinated regional controls to curb long-range ozone transport alongside localized precision interventions, providing a scientific basis for integrated air quality and agricultural management.

Brown carbon (BrC), a subset of light-absorbing organic aerosols, contributes significantly to global warming not only by absorbing atmospheric radiation but also by accelerating snowmelt in the cryosphere through reducing surface albedo. However, accurately quantifying its global distribution and absorption remains challenging for numerical models, stemming from its complex composition, variable optical properties, and dynamic atmospheric transformations. This study developed an absorptivity basis set module for BrC (ABS-BrC) simulation, which categorizes BrC into four classes based on light-absorbing ability and accounts for chemical aging processes to better represent the variability in BrC absorption. Global simulations using ABS-BrC reveal notable disparities between source contributions to BrC concentrations and their associated absorption aerosol optical depth (AAOD). While secondary formation dominates global BrC concentrations (45.8%), its contribution to AAOD is disproportionately small (16.6%). In contrast, wildfire-sourced BrC, despite contributing less than a third of the total concentration, is responsible for the majority (54.2%) of global BrC AAOD. Notably, dark BrC (d-BrC), a strongly absorbing and water-insoluble subset, contributes 30-64% to global BrC AAOD. Its contribution is particularly critical in the Arctic during JJA and SON, where it accounts for 67% of BrC absorption, highlighting its critical role in polar warming. Implementing the ABS-BrC module in Earth system models is recommended for a more accurate assessment of BrC's radiative impact on the atmosphere and cryosphere.

Abstract. The rapid development of Graphics Processing Units (GPUs) has established new computational paradigms for enhancing air quality modeling efficiency. In this study, the heterogeneous-compute interface for portability (HIP) was implemented to parallel computing of the piecewise parabolic method (PPM) advection solver (HADVPPM) on China’s domestic GPU-like accelerators (GPU-like), resulting in a GPU-accelerated version denoted as GPU-HADVPPM4HIP V1.0. Computational performance was enhanced through three strategic optimizations: reducing the central processing unit (CPU) and GPU (CPU-GPU) data transfer frequency, thread-block coordinated indexing, and the Message Passing Interface (MPI) and HIP (“MPI+HIP”) hybrid parallelization across heterogeneous computing clusters. Following validation of the GPU-HADVPPM4HIP V1.0 program’s offline computational consistency and the pollutant simulation performance of the Emission and atmospheric Processes Integrated and Coupled Community version 1.6.0 (EPICC-Model V1.6.0) on the Earth System Numerical Simulation Facility (EarthLab), comprehensive performance testing was conducted. Offline benchmark results demonstrated that GPU-HADVPPM4HIP V1.0 achieved a maximum speedup of 556.5x on a GPU-like using the compiler optimization option compared to the Fortran HADVPPM baseline compiled option for a data size of 108. Integrating GPU-HADVPPM4HIP V1.0 into EPICC-Model V1.6.0 yielded three distinct versions: the initial HIP-based version (HIP-Ori), a version optimized for CPU and GPU communication frequency (HIP‑Opt1), and a further-optimized version employing a thread‑block coordinated indexing strategy (HIP‑Opt2). Compared to the HIP‑Ori version, HIP‑Opt1 achieved a model‑level computational efficiency improvement of 17.0x. Building upon HIP‑Opt1, HIP‑Opt2 delivered an additional 1.5x enhancement in computational efficiency. At the module level, including CPU and GPU data transfer overhead, the GPU implementation improves computational efficiency of the advection module by 39.3 %; when communication cost is excluded, the advection module attains a 20.5× acceleration relative to its CPU counterpart. This coupling establishes a foundational framework for adapting air quality models to GPU-like architectures and identifies critical optimization pathways. Moreover, the methodology provides essential technical support for achieving full-model GPU implementation of the EPICC-Model, addressing both current computational constraints and future demands for high-resolution air quality simulations.

China’s atmospheric environment modeling has advanced rapidly in response to intensifying air pollution challenges, emerging scientific needs, and growing international engagement. This review synthesizes advances across the historical evolution of model systems, key innovations in mechanisms and technologies, and emerging strategic directions. We trace the development from early offline models to fully coupled meteorology–chemistry systems, culminating in high-resolution, multi-pollutant platforms increasingly integrated with artificial intelligence. These models have improved the representation of key processes such as heterogeneous chemistry, secondary aerosol formation, and ozone photochemistry, and have enhanced forecasting capacity through ensemble approaches, data assimilation, and decision-support applications. However, significant challenges remain, including the incomplete simulation of multiphase and feedback processes under compound extremes, limited computational scalability for high-resolution and ensemble use, and fragmented integration of multi-source observations. To address these challenges, this review highlights four priorities: (1) incorporate machine learning into mechanistic modeling; (2) advance open-source and internationally aligned platforms; (3) develop flexible numerical schemes for multi-scale coupling; (4) embed atmospheric chemistry into Earth system models. China’s experience illustrates not only a national transformation from model adaptation to innovation but also provides transferable insights for the global modeling community.

Underlying surface conditions significantly affect the formation and transport of dust storms. Their impact on dust emission is straightforward, but the limiting effect on transport remains unclear. In this study, a machine learning surface classification framework was developed to quantify changes in dust source underlying surfaces between 2001 and 2023, and sensitivity simulations using WRF-Chem were conducted to isolate the impacts of surface changes under identical meteorological conditions. The results show that the bare land area of the major dust sources in East Asia decreased by 19.7% in 2023 compared with 2001. This decrease reduced the surface albedo by 0.021 and led to an increase in sensible heat flux by 3.33 W m-2, enhancing atmospheric convergence and strengthening cold high-pressure near dust sources in a dust storm event on March 19-23, 2023. The intensified high-pressure circulation initially promoted stronger uplift and horizontal transport near source regions but ultimately suppressed eastward long-range transport, which led to a 5.3 degrees westward shift of the eastern boundary of high dust concentrations.

Accurately simulating the spatiotemporal distribution of global atmospheric CO2 remains challenging yet essential for reducing uncertainties in carbon source-sink inversions, quantifying the climate effects of heterogeneous CO2 fields, and supporting the development of CO2 observation networks. In this study, we simulated global atmospheric CO2 concentrations (2010–2019) at a horizontal spatial resolution of 1° × 1° using the Aerosol and Atmospheric Chemistry Model of the Institute of Atmospheric Physics (IAP-AACM) without data assimilation, with initial fields and flux data from the CarbonTracker CT2022 (CT2022) reanalysis product. The simulations were comprehensively evaluated against CT2022 and observations from ground-based (NOAA GML), airborne (ObsPack), and satellite (OCO-2) platforms. The results indicate that across all evaluated surface stations, CT2022 exhibits poorer overall statistical performance (R = 0.69, RMSE = 5.37 ppm, MB = 2.05 ppm) primarily due to noticeable overestimations at unassimilated ground stations, while IAP-AACM maintains robust performance across the surface network (R = 0.84, RMSE = 2.62 ppm, MB = 0.28 ppm). Vertically, airborne observations across eight global campaigns confirm that IAP-AACM accurately reproduces the vertical distribution of CO2, maintaining strong correlations (R = 0.72–1.00) and performance comparable to the CT2022 reanalysis (R = 0.86–1.00). In terms of total column CO2 concentrations (XCO2), IAP-AACM exhibits strong agreement with satellite retrievals annually (R = 0.97, RMSE = 1.08 ppm, MB = 0.26 ppm), with seasonal metrics remaining consistently robust across all four seasons (R = 0.96–0.97, RMSE = 0.98–1.20 ppm, MB = 0.13–0.37 ppm), demonstrating large-scale transport fidelity on par with the CT2022 reanalysis. Finally, across representative ObsPack land sites, unassimilated IAP-AACM achieves a high median correlation (R = 0.97), low error (RMSE = 2.01 ppm), and low mean bias (MB = −0.45 ppm), closely approaching the assimilated CT2022 reanalysis product (R = 0.98, RMSE = 1.40 ppm, MB = −0.07 ppm). Further analysis indicates that the optimized IAP-AACM exhibits robust performance under stable boundary layer conditions, where the revised diffusion scheme produces higher vertical diffusion coefficients that help mitigate excessive near-surface CO2 accumulation during nighttime. Overall, the optimized IAP-AACM effectively simulates the spatiotemporal distribution of global atmospheric CO2, serving as a reliable tool to support advanced research.

The effective density (ρeff) is a key parameter of black carbon-containing (BCc) particles and is related to their morphologies, deposition processes, and optical properties. In this study, a tandem system was established and used to determine the ρeff of ambient BCc particles. The results showed that the ρeff distribution of ambient BCc particles exhibited a bimodal pattern with a left peak located at 0.69 g cm−3 and a right peak at 1.45 g cm−3. The average ρeff of BCc particles over the entire observation period was 1.38 g cm−3. The ρeff of BCc particles showed a clear diurnal pattern with a relatively stable distribution at night and large variations during the daytime. The ρeff value was demonstrated to be a good indicator of BCc particle morphology. BCc particles became more regular with increasing ρeff related to the increasing coating thickness. More coating led to morphological restructuring of BCc particles. The restructuring could be more efficient under high relative humidity conditions. The observed data were further used in a dry deposition scheme, and it was found that the dry deposition velocity of fresh emitted BCc could be largely influenced by its irregular shape. This study reveals the presence of a significant amount of low-density/irregularly shaped black carbon in the environment with rapid morphological changes occurring during the daytime and highlights the need to consider morphological influences in future research on the physicochemical properties of BCc.

The isotopic composition of atmospheric species provides fundamental insights into their sources, sinks, and chemical processes. Conventional end-member mixing models, however, cannot capture progressive isotopic evolution in open systems where mixing and reaction proceed simultaneously. This limitation hinders a comprehensive understanding of the isotope effect and its atmospheric applications. Here, we develop an isotope-enabled chemical transport model (CTM) that tracks four sulfur isotopologues (32SO2, 34SO2, 32SO42−, 34SO42−) through emissions, transport, chemistry, and deposition. An iterative time-splitting method reduces the numerical bias from applying the Rayleigh equation in the open atmosphere. The model reproduces the 34S enrichment of sulfate relative to SO2 and captures the spatial and seasonal patterns of the sulfur isotope effect across eastern China (simulated Δδ34S_SO42− / SO2=6.11 ‰ ±1.85 ‰; observed =3.43 ‰ ±1.11 ‰). Further, the agreement between simulated (with δ34S_SO2=0 ‰ emission assumption) and observed sulfate isotopic compositions, combined with the documented higher δ34S values of coal at 1 ‰–10 ‰ across eastern China, implies a systematic 34S depletion in emitted SO2 relative to fuels. This highlights the importance of considering isotopic fractionation during combustion, flue gas desulfurization and chemical processes for accurate source apportionment. The isotope-enabled model provides a new approach for constraining the sulfur budget.

Atmospheric Oxidation Capacity (AOC) quantifies the ability of atmosphere to oxidize primary species. It plays a crucial role in initiating atmospheric chemical processes and impacts the formation of secondary pollutants, such as ozone (O₃) and secondary aerosols. AOC is fundamentally determined by the concentrations and reactivity of atmospheric oxidants, including O₃, hydroxyl radicals (OH), and nitrate radicals (NO₃). Due to the inherent challenges in direct measurement, AOC is typically inferred through numerical modeling. However, the chemical mechanisms implemented in commonly used 3-D chemical transport models (CTMs) often simplify organic species, leading to underestimations of radical concentrations and AOC.The Mechanism for Air pollution compleX version 1.0 (MAX1) describing detailed tropospheric chemical processes has been therefore developed to improve the simulation of radicals. MAX1 contains 940 reactions including photolysis, gaseous reactions and heterogeneous reactions of 300 species, which is adequate for both box model and CTM applications. Detailed chemical processes of chlorine chemistry, chemistry of Criegee radicals and heterogeneous uptake of HO2 and N2O5 have been implemented and updated. With this level of explicitness, MAX1 can support investigations on the quantification of secondary pollutant productions and the chemical behavior of the crucial intermedia such as organic peroxy radicals. MAX1 has been validated in box model and regional models. Simulations of MAX1 well captured the variation of O₃ in all cases tested. Meanwhile, significant improvement was made on predictions of radicals compared to other mechanisms, especially under the low NOx environment.

Black carbon has an important effect on global climate change. Uncertainty surrounding the absorption property of BC-containing aerosols still exists. In this study, the optical property of PM2.5 in Beijing in November 2018 was investigated using Mie theory based on observed and simulated PM2.5. The results showed that the absorption coefficient under uniform internal mixing is the highest, followed by core-shell mixing and calculation for external mixing is the lowest. The calculated BC absorption at 630 nm under a mixed mixing state (fraction of internal mixing constraint by observation) was reasonably close to the measured mean value. The simulations of the NAQPMS reproduced the temporal distribution of PM2.5 and its components in Beijing well. Under the same mixing state, the absorption coefficient can be highly impacted by the simulation of PM2.5 components. The aging process of BC can be reproduced by advanced microphysical module (APM) in NAQPMS. Then the fraction of aged BC can be used as a proxy for internal mixing proportion, and the absorption coefficient was reasonably reproduced. This study will provide a reference for the three-dimensional model simulation of black carbon aerosol radiation effect.

Photolysis and gas-phase reaction schemes (PHS and GRS, respectively) are two modules that significantly influence the modeling performance of tropospheric ozone in chemical transport models (CTMs). Quantifying the impacts of updating both PHS and GRS on simulated ozone has significant implications for effectively improving the modeling performance of CTMs, which has not been previously studied. In this study, based on the architecture of multi-option scientific modules in the Emission and atmospheric Processes Integrated and Coupled Community (EPICC)-Model, two PHSs (a highly parameterized approach (EXPR) and a streamlined version of the TUV model (STUV)) and two GRSs (CBMZ and CB6r5) were developed to assess their impacts on simulated tropospheric ozone concentrations in the North China Plain during winter and summer. Compared to the cbmzEXPR scheme, the cb6r5STUV scheme showed a significant improvement in ozone simulation performance in both winter and summer, with the normalized mean bias of the maximum daily 8-h average ozone improving from -0.24 to -0.10 in winter and from 0.11 to -0.01 in summer. These improvements were attributed to better representation of photolysis rates by STUV, along with a more detailed description of gas-phase reactions by CB6r5 with distinct seasonal effects. In winter, updates of the GRS dominated the total improvement, with a contribution of 2.29 ppb (91 %) to daytime ozone changes. In summer, updates of the PHS played a dominant role, contributing -6.58 ppb (66 %) to daytime ozone changes. This study highlights the importance of simultaneously updating the PHS and GRS in CTMs to achieve better ozone simulation performance.

The mixing state and aging characteristics of black carbon (BC) aerosols are the key factors in calculating their optical properties and quantifying their impacts on radiation balance and global climate change. Considerable uncertainty still exists in the absorption properties of BC-containing aerosols and the absorption enhancement (Eabs) due to the lensing effect. It is crucial to reasonably represent the mixing of BC with other aerosol components to reduce this uncertainty. In this study, the absorption properties of PM2.5 were investigated based on the Nested Air Quality Prediction Modeling System (NAQPMS) with different assumptions of the aerosol mixing state. The absorption coefficient (babs) is the highest under the assumption of uniform internal mixing, lower under core–shell mixing, and the lowest under external mixing. The result under core–shell mixing is closest to the observations. The aging process and coating thickness were well reproduced by an advanced particle microphysics (APM) module in NAQPMS. Following this, the fraction of embedded BC and secondary component coating on aerosols was used to constrain the mixing state. Eabs at 880 nm over the Beijing–Tianjin–Hebei region was 2.0–2.5 under core–shell mixing. When the fraction of coated BC and the coating layer are resolved, Eabs_880 – caused by the lensing effect – decreases by 30 %–43 % to 1.2–1.7, which is close to the range reported in previous studies. This study highlights the importance of representing the microphysical processes governing the mixing state and aging of BC and provides a reference for quantifying their radiative effects.

Abstract. The rapid development of Graphics Processing Units (GPUs) has established new computational paradigms for enhancing air quality modeling efficiency. In this study, the heterogeneous-compute interface for portability (HIP) was implemented to parallel computing of the piecewise parabolic method (PPM) advection solver (HADVPPM) on China’s domestic GPU-like accelerators (GPU-HADVPPM4HIP V1.0). Computational performance was enhanced through three strategic optimizations: reducing the central processing unit (CPU) and GPU (CPU-GPU) data transfer frequency, thread-block coordinated indexing, and the Message Passing Interface and HIP (“MPI+HIP”) hybrid parallelization across heterogeneous computing clusters. Following validation of the GPU-HADVPPM4HIP V1.0 program’s offline computational consistency and the pollutant simulation performance of the Emission and atmospheric Processes Integrated and Coupled Community version 1.0 (EPICC-Model V1.0) on the Earth System Numerical Simulation Facility (EarthLab), comprehensive performance testing was conducted. Offline benchmark results demonstrated that GPU-HADVPPM4HIP V1.0 achieved a maximum speedup of 556.5x on a domestic GPU-like accelerator with compiler optimization. Integration of GPU-HADVPPM4HIP V1.0 into EPICC-Model V1.0, combined with optimized CPU-GPU communication frequency and thread-block coordinated indexing strategies, yielded model-level computational efficiency improvements of 17.0x and 1.5x, respectively. At the module level, GPU-HADVPPM4HIP V1.0 exhibited a 39.3 % computational efficiency gain when accounting for CPU-GPU data transfer overhead, which escalated to 20.5x acceleration when excluding communication costs. This coupling establishes a foundational framework for adapting air quality models to China’s domestic GPU-like architectures and identifies critical optimization pathways. Moreover, the methodology provides essential technical support for achieving full-model GPU implementation of the EPICC-Model, addressing both current computational constraints and future demands for high-resolution air quality simulations.

Heatwaves pose a growing threat to human health and livelihoods, yet a comprehensive analysis of daytime and nighttime events across Africa remains lacking. This study provides a Pan-African analysis of observed and projected heatwaves, using percentile-based thresholds and multi-model climate projections. We find a significant increasing trend in heatwaves over recent decades, with a key novel finding: nighttime events are increasing more rapidly (6.23 days per decade) than daytime events (3.98 days per decade). Spatially, North Africa endures the most intense and prolonged heatwaves, while Southern Africa experiences the highest event frequency. This trend is projected to continue throughout the 21st century, with scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) indicating a continued intensification and a persistent amplification of nighttime over daytime heatwaves. Under the high-emission scenario (SSP5-8.5), the continent is projected to experience an increase of 35–103 additional nighttime heatwave days in the near-future (2030–2060) and 110–118 days in the far-future (2070–2100), compared to an increase of (21–75 days and 82–113 days) for daytime heatwaves, respectively. Consequently, our findings consistently demonstrate that nighttime heatwaves are becoming and will continue to be more frequent, intense, and longer-lasting than daytime heatwaves. Therefore, these results underscore the urgent need for policymakers to develop integrated, multi-faceted adaptation and mitigation strategies that specifically address the distinct risks of nighttime heat in Africa.