Abstract. The integration of satellite aerosol optical depth (AOD) and trace gas observations using data assimilation has the potential to improve our understanding of aerosol composition. This study evaluates these synergistic effects through combined constraints on total aerosols by AOD and on secondary aerosol formation by trace gases. The simultaneous data assimilation (DA) of NO2, SO2, CO, and HNO3 from OMI, TROPOMI, MOPITT, and MLS, together with AOD from MODIS and VIIRS, improved aerosol analyses in most cases compared to conventional DA runs that separately assimilate AOD or trace gases satellite observations. Validation against independent surface observations of sulfate, nitrate, and ammonium (SNA), and PM2.5 showed improved agreements by 6–98 % compared to the conventional DA runs and the control simulation without any data assimilation. Notably, the reduction in PM2.5 model biases exceeded that achieved by the conventional DA of AOD by 56 % in Northeast Asia. These improvements were achieved by reduced SO2 and soil dust emissions by 30 % and 60 % globally and increased NOx and carbonaceous aerosol emissions by 30 % and 15 %. The simultaneous DA provides even larger reductions in SNA and AOD biases by up to 25 % and 48 % respectively, when the current generation instruments (TROPOMI and VIIRS) is used, instead of the previous generation instruments (OMI and MODIS). This coupled aerosol and trace gas DA framework offers significant advantages for improving global aerosol composition analyses, informing policy decisions with co-benefits for air quality and climate, and optimizing the use of the current satellite observing network.

Abstract This study validates tropospheric NO2 vertical column density (TropNO2 VCD) data from the Geostationary Environment Monitoring Spectrometer (GEMS) version 3.0 and the Tropospheric Chemistry Reanalysis version 2 (TCR-2) against Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) and Tropospheric Monitoring Instrument (TROPOMI) data at three Japanese sites: Yokosuka (urban), Fukue (rural-remote), and Cape Hedo (remote). The GEMS v3.0 dataset showed markedly improved agreement with MAX-DOAS compared to v2.0, especially at Fukue and Cape Hedo remote islands, with significantly reduced normalized mean bias from 142–319% to 8–18%. GEMS v3.0 showed agreement with MAX-DOAS observations at Yokosuka (R = 0.75) and Fukue (R = 0.50). It performed particularly well in autumn and winter. There were positive biases in autumn at Yokosuka (NMB = 3.5%), but negative biases in the other seasons (NMB = −0.4% to −51.2%). The reanalysis TCR-2 and aggregated TROPOMI TropNO2 VCD data (both at 1 × 1° resolution) showed moderate to good correlation at all three sites (R = 0.72 at Yokosuka; R = 0.44 at Fukue; R = 0.57 at Cape Hedo). While the spatial resolution of TCR-2 (1.1 × 1.1°) precluded meaningful comparisons with MAX-DOAS at urban sites such as Yokosuka, TCR-2 exhibited lower biases than TROPOMI at Cape Hedo, which represents a background environment (NMB = 38% vs. 87%). GEMS v3.0 data effectively captured midday NO2 reductions at Cape Hedo, consistent with TCR-2 and MAX-DOAS, marking this as the first study to explore daytime NO2 decreases in remote regions using GEMS. NO2 loss pathways at Cape Hedo were examined using TCR-2 data and box-model simulations. NO2 levels from GEMS exhibited a decline between 10 AM and 3 PM in autumn, aligning with patterns from MAX-DOAS and TCR-2, with NO2 decay rates of 16 ± 10h from GEMS, 21 ± 5h from MAX-DOAS, and 22 ± 20h from TCR-2. The box-model NOx budget analysis revealed that the NO2 + OH reaction was the dominant pathway for NOx loss. The markedly improved agreement of GEMS v3.0 data with MAX-DOAS and TCR-2 data will allow potential exploration of the oxidizing capacity of the atmosphere over the clean marine regions, after further characterization of NOx chemistry.

The complexity of ozone chemistry makes it difficult to quantify the extent to which different national ozone reduction scenarios affect the country that implemented the strategy, neighboring countries, and the world. To better understand ozone sensitivity to national/regional emission scenarios, the zero-out method was applied for the anthropogenic emission of ozone precursors, i.e., nitrogen oxides (NOx), in nine regions and three countries worldwide. In this study, ozone simulations were performed at a high global resolution of 56 km via the use of a nonhydrostatic icosahedral atmosphere model coupled with chemistry (NICAM-Chem). The model performance in predicting surface ozone was evaluated with ground-based measurements worldwide. The correlation was moderate to high, but both bias and uncertainty were high but remained within the ranges of values obtained from other global chemistry models. Experiments based on zero-out methods for assessing anthropogenic NOx emissions revealed that the domestic impacts of anthropogenic NOx emission reduction on ozone reduction were the largest in India (14 ppbv, regional and annual average) and China (11 ppbv, regional and annual average). The influence of anthropogenic NOx emission reduction in China on transboundary ozone concentrations was notable, with a reduction in ozone of 7 ppbv (regional and annual average) in Japan and even yielding ozone reductions in North America (1 ppbv, regional and annual average) and western Europe (1 ppbv, regional and annual average). Sensitivity experiments with a 20% reduction in anthropogenic NOx emissions were also conducted, and the results were generally consistent with those of previous studies. However, the results for a 20% reduction in anthropogenic NOx emissions partially differed from the results for a 100% reduction in anthropogenic NOx emissions because of the high nonlinearity of ozone chemistry. For example, in Japan, a 20% reduction in domestic NOx emissions resulted in a larger reduction in ozone levels than that obtained with a 20% reduction in Chinese NOx emissions. This indicates the inherent uncertainty resulting from experimental settings that assume a substantial reduction, such as a 100% decrease in the NOx flux. Understanding the impact of emission reduction in a given country on other countries is important for accelerating future international collaboration on ozone reduction for ensuring climate and human health.

Iodine chemistry exerts a nonnegligible influence on tropospheric ozone depletion over oceanic regions. The impact of iodine has been extensively studied using three-dimensional chemical transport models (CTMs). However, the factors governing the variability of iodine monoxide (IO) and ozone in the marine boundary layer (MBL) remain uncertain. This study examines the impact of fine-scale meteorological variability and ozone-independent iodine sources on the MBL IO and ozone concentrations over the Western Pacific Warm Pool (WPWP) through ship-borne observations and high-resolution CTMs during November–December 2014. The high (0.56 ^∘ )-resolution model demonstrates a negative correlation between IO and ozone at the observation locations ( r = - 0.45), which is more closely aligned with that derived from the ship-borne observation data ( r = - 0.70) than the coarse (2.8 ^∘ )-resolution model ( r = 0.08). Sensitivity analysis indicates that a contrast in the correlation between the 0.56 ^∘ and 2.8 ^∘ resolutions emerges from the interplay of fine-scale atmospheric transport and chemistry processes, rather than from fine-scale atmospheric transport solely or ozone-dependent oceanic iodine release. This interplay leads to a greater ozone loss mediated by the iodine cycle at 0.56 ^∘ resolution (by 0.56 ppbv day ^-1 ) compared to that at 2.8 ^∘ resolution (by 0.20 ppbv day ^-1 ), due to the reduced mixing with air outside the MBL over the WPWP at finer resolution. Furthermore, incorporating ozone-independent iodine sources such as photolysis of CH_2I_2 , CH_2IBr , and CH_2ICl enhances the IO-ozone anti-correlation coefficient (−0.50). These findings highlight the critical roles of interplay of the fine-scale atmospheric transport and chemistry processes and oceanic ozone-independent iodine sources in the co-variability of IO and ozone over the WPWP.

Atmospheric nitrogen deposition modulates carbon sequestration by terrestrial ecosystems via nitrogen-carbon interactions. The intertwined chemical and physical processes in nitrogen deposition and subsequent nitrogen-carbon interactions pose challenges for Earth system model (ESM) in quantifying them. Here, we combine 30-year nitrogen wet deposition measurements (1980-2014) with Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations to disentangle the nitrogen wet deposition variabilities across different scales. We show that observed decadal trends in nitrogen deposition can be reproduced by ESMs for the United States and Europe, but diverge in East Asia. Models generally fail to capture nitrogen deposition seasonality, with distinct driving factors of model errors for different nitrogen forms. The incorrect ammonia emission seasonality explains the bias in reduced nitrogen deposition, whereas precipitation scavenging and nitrogen oxides chemical oxidation collectively determine the seasonal bias of oxidized nitrogen deposition. Our results can facilitate the informed assessment of nitrogen-carbon-climate interactions under changing human activities.

Formaldehyde (HCHO), a precursor to tropospheric ozone, is an important tracer of volatile organic compounds (VOCs) in the atmosphere. Two years (2019-2020) of HCHO simulations obtained from the global chemistry transport model CHASER at a horizontal resolution of 2.8 degrees x 2.8 degrees have been evaluated using the Tropospheric Monitoring Instrument (TROPOMI) and multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations. In situ measurements from the Atmospheric Tomography Mission (ATom) in 2018 were used to evaluate the HCHO simulations for 2018. CHASER reproduced the TROPOMI-observed global HCHO spatial distribution with a spatial correlation (r) of 0.93 and a negative bias of 7 %. The model showed a good capability to reproduce the observed magnitude of the HCHO seasonality in different regions, including the background conditions. The discrepancies between the model and satellite in the Asian regions were related mainly to the underestimated and missing anthropogenic emission inventories. The maximum difference between two HCHO simulations based on two different nitrogen oxide (NOx) emission inventories was 20 %. TROPOMI's finer spatial resolution than that of the Ozone Monitoring Instrument (OMI) sensor reduced the global model-satellite root-mean-square error (RMSE) by 20 %. The OMI- and TROPOMI-observed seasonal variations in HCHO abundances were consistent. The simulated seasonality showed better agreement with TROPOMI in most regions. The simulated HCHO and isoprene profiles correlated strongly (R=0.81) with the ATom observations. However, CHASER overestimated HCHO mixing ratios over dense vegetation areas in South America and the remote Pacific region (background condition), mainly within the planetary boundary layer (< 2 km). The simulated seasonal variations in the HCHO columns showed good agreement (R>0.70) with the MAX-DOAS observations and agreed within the 1 sigma standard deviation of the observed values. However, the temporal correlation (R similar to 0.40) was moderate on a daily scale. CHASER underestimated the HCHO levels at all sites, and the peak occurrences in the observed and simulated HCHO seasonality differed. The coarseness of the model's resolution could potentially lead to such discrepancies. Sensitivity studies showed that anthropogenic emissions were the highest contributor (up to similar to 35 %) to the wintertime regional HCHO levels.

Ambient fine particulate matter (PM2.5) pollution is a leading health risk factor for children under- 5 years, especially in developing countries. South Asia is a PM2.5 hotspot, where climate change, a potential factor affecting PM2.5 pollution, adds a major challenge. However, limited evidence is available on under-5 mortality attributable to PM2.5 under different climate change scenarios. This study aimed to project under-5 mortality attributable to long-term exposure to ambient PM2.5 under seven air pollution and climate change mitigation scenarios in South Asia. We used a concentration-risk function obtained from a previous review to project under-5 mortality attributable to ambient PM2.5. With a theoretical minimum risk exposure level of 2.4 μg/m3, this risk function was linked to gridded annual PM2.5 concentrations from atmospheric modeling to project under-5 mortality from 2010 to 2049 under different climate change mitigation scenarios. The scenarios were developed from the Aim/Endues global model based on end-of-pipe (removing the emission of air pollutants at the source, EoP) and 2 °C target measures. Our results showed that, in 2010-2014, about 306.8 thousand under-5 deaths attributable to PM2.5 occurred in South Asia under the Reference (business as usual) scenario. The number of deaths was projected to increase in 2045-2049 by 36.6% under the same scenario and 7.7% under the scenario where EoP measures would be partially implemented by developing countries (EoPmid), and was projected to decrease under other scenarios, with the most significant decrease (81.2%) under the scenario where EoP measures would be fully enhanced by all countries along with the measures to achieve 2 °C target (EoPmaxCCSBLD) across South Asia. Country-specific projections of under-5 mortality varied by country. The current emission control strategy would not be sufficient to reduce the number of deaths in South Asia. Robust climate change mitigation and air pollution control policy implementation is required.

Climate change profoundly affects the timing of seasonal activities of organisms, known as phenology. The impact of climate change is not unidirectional; it is also influenced by plant phenology as plants modify atmospheric composition and climatic processes. One important aspect of this interaction is the emission of biogenic volatile organic compounds (BVOCs), which link the Earth's surface, atmosphere, and climate. BVOC emissions exhibit significant diurnal and seasonal variations and are therefore considered essential phenological traits. To understand the dynamic equilibrium arising from the interplay between plant phenology and climate, this review presents recent advances in comprehending the molecular mechanisms underpinning plant phenology and its interaction with climate. We provide an overview of studies investigating molecular phenology, genome-wide gene expression analyses conducted in natural environments, and how these studies revolutionize the concept of phenology, shifting it from observable traits to dynamic molecular responses driven by gene-environment interactions. We explain how this knowledge can be scaled up to encompass plant populations, regions, and even the globe by establishing connections between molecular phenology, changes in plant distribution, species composition, and climate.

Global lockdown measures to prevent the spread of the coronavirus disease 2019 (COVID-19) led to air pollutant emission reductions. While the COVID-19 lockdown impacts on both trace gas and total particulate pollutants have been widely investigated, secondary aerosol formation from trace gases remains unclear. To that end, we quantify the COVID-19 lockdown impacts on NOx and SO2 emissions and sulfate-nitrate-ammonium aerosols using multiconstituent satellite data assimilation and model simulations. We find that anthropogenic emissions over major polluted regions were reduced by 19 to 25% for NOx and 14 to 20% for SO2 during April 2020. These emission reductions led to 8 to 21% decreases in sulfate and nitrate aerosols over highly polluted areas, corresponding to >34% of the observed aerosol optical depth declines and a global aerosol radiative forcing of +0.14 watts per square meter relative to business-as-usual scenario. These results point to the critical importance of secondary aerosol pollutants in quantifying climate impacts of future mitigation measures.

Estimates of ground-level ozone concentrations have been improved through data fusion of observations and atmospheric chemistry models. Our previous global ozone estimates for the Global Burden of Disease study corrected for bias uniformly across continents and then corrected near monitoring stations using the Bayesian Maximum Entropy (BME) framework for data fusion. Here, we use the Regionalized Air Quality Model Performance (RAMP) framework to correct model bias over a much larger spatial range than BME can, accounting for the spatial inhomogeneity of bias and nonlinearity as a function of modeled ozone. RAMP bias correction is applied to a composite of 9 global chemistry-climate models, based on the nearest set of monitors. These estimates are then fused with observations using BME, which matches observations at measurement stations, with the influence of observations declining with distance in space and time. We create global ozone maps for each year from 1990 to 2017 at fine spatial resolution. RAMP is shown to create unrealistic discontinuities due to the spatial clustering of ozone monitors, which we overcome by applying a weighting for RAMP based on the number of monitors nearby. Incorporating RAMP before BME has little effect on model performance near stations, but strongly increases R2 by 0.15 at locations farther from stations, shown through a checkerboard cross-validation. Corrections to estimates differ based on location in space and time, confirming heterogeneity. We quantify the likelihood of exceeding selected ozone levels, finding that parts of the Middle East, India, and China are most likely to exceed 55 parts per billion (ppb) in 2017. About 96% of the global population was exposed to ozone levels above the World Health Organization guideline of 60 µg m−3 (30 ppb) in 2017. Our annual fine-resolution ozone estimates may be useful for several applications including epidemiology and assessments of impacts on health, agriculture, and ecosystems.

Abstract. Nitrous acid (HONO) is an important atmospheric gas given its contribution to the cycles of NOx and HOx, but its role in global atmospheric photochemistry is not fully understood. This study, for the first time, implemented three pathways of HONO formation in the chemistry-climate model CHASER (MIROC-ESM) to explore three physical phenomena: gas-phase kinetic reactions (GRs), direct emission (EM), and heterogeneous reactions on cloud/aerosol particles (HRs). We evaluated the simulations by the atmospheric measurements from the OMI (Ozone Monitoring Instrument), EANET (Acid Deposition Monitoring Network in eastern Asia) / EMEP (European Monitoring and Evaluation Programme) ground-based stationary observations, observations from the ship R/V Mirai, and aircraft-based measurements by ATom1 (atmospheric tomography) and EMeRGe-Asia-2018 (Effect of Megacities on the Transport and Transformation of Pollutants on the Regional to Global scales). We showed that the inclusion of the HONO chemistry in the modeling process reduces the model bias against the measurements for PM2.5, NO3−/HNO3, NO2, OH, O3, and CO, especially in the lower troposphere and the North Pacific (NP) region. We found that the retrieved global abundance of tropospheric HONO was 1.4 TgN. Of the three source pathways, HRs and EM contributed 63 % and 26 % to the net HONO production, respectively. We also observed that, reactions on the aerosol surfaces contributed larger amounts of HONO (51 %) than those on the cloud surfaces (12 %). The model exhibited significant negative biases for daytime HONO in the Asian off-coast region, compared with the airborne measurements by EMeRGe-Asia-2018, indicating the existence of unknown daytime HONO sources. Strengthening of aerosol uptake of NO2 near-surface and in the middle troposphere, cloud uptake, and direct HONO emission are all potential yet-unknown HONO sources. We also found that the simulated HONO abundance and its impact on NOx-O3 chemistry are sensitive to the yield of the heterogeneous conversion of NO2 to HONO (vs. HNO3). Inclusion of HONO reduces global tropospheric NOx (NO + NO2) levels by 20.4 %, thereby weakening the tropospheric oxidizing capacity, which in turn, increases CH4 lifetime (13 %) and CO abundance (8 %). HRs on the surfaces of cloud particles, which have been neglected in previous modeling studies, are the main drivers of these impacts. This effect is particularly salient for the substantial reductions of levels of OH (40–67 %) and O3 (30–45 %) in the NP region during summer given the significant reduction of NOx level (50–95 %). In contrast, HRs on aerosol surfaces in China (Beijing) enhance OH and O3 winter mean levels by 600–1700 % and 10–33 %, respectively, with regards to their minima in winter. Overall, our findings suggest that a global model that does not consider HONO heterogeneous mechanisms (especially HRs on cloud particle surfaces) may erroneously predict the effect of HONO in remote areas and polluted regions.

Formaldehyde (HCHO), a precursor to tropospheric ozone, is an important tracer of volatile organic compounds (VOCs) in the atmosphere. Two years of HCHO simulations obtained from the global chemistry transport model CHASER at horizontal resolution of 2.8° × 2.8° have been evaluated using observations from the Tropospheric Ozone Monitoring Experiment (TROPOMI), Atmospheric Tomography Mission (ATom), and multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations. CHASER reproduced the observed global HCHO spatial distribution with spatial correlation (r) of 0.93 and negative bias of 7%. The model showed good capability for reproducing the observed magnitude of the HCHO seasonality in different regions, including the background conditions. The discrepancies between the model and satellite in the Asian regions were related mainly to the underestimated and missing anthropogenic emission inventories. TROPOMI’s finer spatial resolution than that of the Ozone monitoring Experiment (OMI) sensor reduced the global model–satellite root-mean-square-error (RMSE) by 20%. The OMI and TROPOMI observed seasonal variations in HCHO abundances were consistent. However, the simulated seasonality showed better agreement with TROPOMI in most regions. The simulated HCHO and isoprene profiles correlated (R = 0.81) strongly with the ATom observations. CHASER overestimated HCHO mixing ratios over dense vegetation areas in South America and the remote Pacific (background condition) regions, mainly within the planetary boundary layer (<2 km). The simulated temporal (daily and diurnal) variations in the HCHO mixing ratio showed good congruence with the MAX-DOAS observations and agreed within the 1-sigma standard deviation of the observed values.

Lightning can cause natural hazards that result in human and animal injuries and fatalities, infrastructure destruction, and wildfire ignition. Lightning-produced NOx (LNOx), a major NOx (NOx=NO+NO2) source, plays a vital role in atmospheric chemistry and global climate. The Earth has experienced marked global warming and changes in aerosol and aerosol precursor emissions (AeroPEs) since the 1960s. Investigating long-term historical (1960–2014) lightning and LNOx trends can provide important indicators for all lightning-related phenomena and for LNOx effects on atmospheric chemistry and global climate. Understanding how global warming and changes in AeroPEs influence historical lightning and LNOx trends can be helpful in providing a scientific basis for assessing future lightning and LNOx trends. Moreover, global lightning activities' responses to large volcanic eruptions such as the 1991 Pinatubo eruption are not well elucidated and are worth exploring. This study employed the widely used cloud top height lightning scheme (CTH scheme) and the newly developed ice-based ECMWF-McCAUL lightning scheme to investigate historical (1960–2014) lightning and LNOx trends and variations as well as their influencing factors (global warming, increases in AeroPEs, and the Pinatubo eruption) in the framework of the CHASER (MIROC) chemistry–climate model. The results of the sensitivity experiments indicate that both lightning schemes simulated almost flat global mean lightning flash rate anomaly trends during 1960–2014 in CHASER (the Mann–Kendall trend test (significance inferred as 5 %) shows no trend for the ECMWF-McCAUL scheme, but a 0.03 % yr−1 significant increasing trend is detected for the CTH scheme). Moreover, both lightning schemes suggest that past global warming enhances historical trends for global mean lightning density and global LNOx emissions in a positive direction (around 0.03 % yr−1 or 3 % K−1). However, past increases in AeroPEs exert an opposite effect on the lightning and LNOx trends (−0.07 % to −0.04 % yr−1 for lightning and −0.08 % to −0.03 % yr−1 for LNOx) when one considers only the aerosol radiative effects in the cumulus convection scheme. Additionally, effects of past global warming and increases in AeroPEs in lightning trends were found to be heterogeneous across different regions when analyzing lightning trends on the global map. Lastly, this paper is the first of study results suggesting that global lightning activities were markedly suppressed during the first year after the Pinatubo eruption as shown in both lightning schemes (global lightning activities decreased by as much as 18.10 % as simulated by the ECMWF-McCAUL scheme). Based on the simulated suppressed lightning activities after the Pinatubo eruption, the findings also indicate that global LNOx emissions decreased after the 2- to 3-year Pinatubo eruption (1.99 %–8.47 % for the annual percentage reduction). Model intercomparisons of lightning flash rate trends and variations between our study (CHASER) and other Coupled Model Intercomparison Project Phase 6 (CMIP6) models indicate great uncertainties in historical (1960–2014) global lightning trend simulations. Such uncertainties must be investigated further.

The Summary for Policymakers of the Working Group I of the 6th assessment report of the Intergovernmental Panel for Climate Change (IPCC) contained a diagram of the contribution of the global mean change in surface air temperature from the preindustrial to the present climate by the composition of the short-lived climate forces (SLCFs) including aerosols. However, it was estimated by a two-layer energy budget emulator with effective radiative forcing obtained from a model inter comparison project, AerChemMIP. Although the effects of total anthropogenic aerosols have been included in the past, present, and future simulations by climate models, it is essential to estimate and analyze climate change by composition of SLCFs using coupled atmosphere-ocean models in the next step. For example, the amount of temperature change varies significantly with CO2 concentration even when the reduced amount of anthropogenic SO2 emissions and then the instantaneous radiative forcing are the same (Takemura, 2020, doi:10.1038/s41598-020-78805-1). In this study, sensitivity experiments to reduce anthropogenic emissions of SO2, organic matter, and black carbon to zero for each of the 12 regions of the world are simulated using a coupled atmosphere-ocean aerosol model MIROC-SPRINTARS and the results are analyzed in comparison with the experiment under standard emissions. Similar experiments are conducted for biomass burning aerosols from several regions. In the simulations, well-mixed greenhouse gas concentrations are set in two patterns, 2015 and 2060 for SSP3-7.0. The same set of simulations using an atmospheric general circulation model with prescribed sea surface temperature and sea ice are conducted for calculating the effective radiative forcing and rapid adjustment due to each anthropogenic aerosol. This set of experiments also aims to generate scientific knowledge to explore the optimal path for emission reductions of SLCFs and use it in policy making. The project S-20 of the Ministry of the Environment of Japan is also conducting experiments to reduce emissions of SLCFs other than aerosols, as well as experiments to reduce SLCFs emissions using a global cloud-resolving model NICAM. Conducting similar experiments with other climate models and comparing them will enable us to better understand the climate impact of SLCFs with uncertainty.

This study gives a systematic comparison of the Tropospheric Monitoring Instrument (TROPOMI) version 1.2 and Ozone Monitoring Instrument (OMI) QA4ECV tropospheric NO2 column through global chemical data assimilation (DA) integration for the period April–May 2018. DA performance is controlled by measurement sensitivities, retrieval errors, and coverage. The smaller mean relative observation errors by 16 % in TROPOMI than OMI over 60∘ N–60∘ S during April–May 2018 led to larger reductions in the global root-mean-square error (RMSE) against the assimilated NO2 measurements in TROPOMI DA (by 54 %) than in OMI DA (by 38 %). Agreements against the independent surface, aircraft-campaign, and ozonesonde observation data were also improved by TROPOMI DA compared to the control model simulation (by 12 %–84 % for NO2 and by 7 %–40 % for ozone), which were more obvious than those by OMI DA for many cases (by 2 %–70 % for NO2 and by 1 %–22 % for ozone) due to better capturing spatial and temporal variability by TROPOMI DA. The estimated global total NOx emissions were 15 % lower in TROPOMI DA, with 2 %–23 % smaller regional total emissions, in line with the observed negative bias of the TROPOMI version 1.2 product compared to the OMI QA4ECV product. TROPOMI DA can provide city-scale emission estimates, which were within 10 % differences with other high-resolution analyses for several limited areas, while providing a globally consistent analysis. These results demonstrate that TROPOMI DA improves global analyses of NO2 and ozone, which would also benefit studies on detailed spatial and temporal variations in ozone and nitrate aerosols and the evaluation of bottom-up NOx emission inventories.

The formation of nitrogen oxides (NOx) associated with lightning activities (hereinafter designated as LNOx) is a major source of NOx. In fact, it is regarded as the dominant NOx source in the middle to upper troposphere. Therefore, improving the prediction accuracy of lightning and LNOx in chemical climate models is crucially important. This study implemented three new lightning schemes with the CHASER (MIROC) global chemical transport and climate model. The first lightning scheme is based on upward cloud ice flux (ICEFLUX scheme). The second one (the original ECMWF scheme), also adopted in the European Centre for Medium-Range Weather Forecasts (ECMWF) forecasting system, calculates lightning flash rates as a function of QR (a quantity intended to represent the charging rate of collisions between graupel and other types of hydrometeors inside the charge separation region), convective available potential energy (CAPE), and convective cloud-base height. For the original ECMWF scheme, by tuning the equations and adjustment factors for land and ocean, a new lightning scheme called the ECMWF-McCAUL scheme was also tested in CHASER. The ECMWF-McCAUL scheme calculates lightning flash rates as a function of CAPE and column precipitating ice. In the original version of CHASER (MIROC), lightning is initially parameterized with the widely used cloud-top height scheme (CTH scheme). Model evaluations with lightning observations conducted using the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) indicate that both the ICEFLUX and ECMWF schemes simulate the spatial distribution of lightning more accurately on a global scale than the CTH scheme does. The ECMWF-McCAUL scheme showed the highest prediction accuracy for the global distribution of lightning. Evaluation by atmospheric tomography (ATom) aircraft observations (NO) and tropospheric monitoring instrument (TROPOMI) satellite observations (NO2) shows that the newly implemented lightning schemes partially facilitated the reduction of model biases (NO and NO2), typically within the regions where LNOx is the major source of NOx, when compared to using the CTH scheme. Although the newly implemented lightning schemes have a minor effect on the tropospheric mean oxidation capacity compared to the CTH scheme, they led to marked changes in oxidation capacity in different regions of the troposphere. Historical trend analyses of flash and surface temperatures predicted using CHASER (2001–2020) show that lightning schemes predicted increasing trends of lightning or no significant trends, except for one case of the ICEFLUX scheme, which predicted a decreasing trend of lightning. The global lightning rates of increase during 2001–2020 predicted by the CTH scheme were 17.69 % ∘C−1 and 2.50 % ∘C−1, respectively, with and without meteorological nudging. The un-nudged runs also included the short-term surface warming but without the application of meteorological nudging. Furthermore, the ECMWF schemes predicted a larger increasing trend of lightning flash rates under the short-term surface warming by a factor of 4 (ECMWF-McCAUL scheme) and 5 (original ECMWF scheme) compared to the CTH scheme without nudging. In conclusion, the three new lightning schemes improved global lightning prediction in the CHASER model. However, further research is needed to assess the reproducibility of trends of lightning over longer periods.

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.

Efforts to stem the transmission of coronavirus disease 2019 (COVID-19) led to rapid, global ancillary reductions in air pollutant emissions. Here, we quantify the impact on tropospheric ozone using a multiconstituent chemical data assimilation system. Anthropogenic NO x emissions dropped by at least 15% globally and 18 to 25% regionally in April and May 2020, which decreased free tropospheric ozone by up to 5 parts per billion, consistent with independent satellite observations. The global total tropospheric ozone burden declined by 6TgO3 (∼2%) in May and June 2020, largely due to emission reductions in Asia and the Americas that were amplified by regionally high ozone production efficiencies (up to 4 TgO3/TgN). Our results show that COVID-19 mitigation left a global atmospheric imprint that altered atmospheric oxidative capacity and climate radiative forcing, providing a test of the efficacy of NO x emissions controls for co-benefiting air quality and climate.