Over the past few decades, the tropospheric ozone precursor anthropogenic emissions – nitrogen oxides (NOx) and reactive carbon (RC) from northern mid-/high-latitude regions (e.g., North America, Europe) – have been decreasing, and those from (sub-)tropical regions (e.g., South Asia , the Middle East ) have been increasing, leading to an equatorward emission redistribution. In this study, we quantify the contributions of various sources of NOx and RC emissions to tropospheric ozone using a source attribution technique during the 2000–2018 period in a global chemistry transport model. We tag the ozone molecules with the source of their NOx or RC precursor emission in two separate simulations: NOx-tagged and RC-tagged. These tags include various natural (biogenic, biomass burning, lightning NOx and RC from methane oxidation) and regional anthropogenic precursor emission sources and influx from the stratosphere. We simulate ∼336 Tg O3 of tropospheric ozone burden (TOB) with an increasing trend of 0.91 Tg O3 yr−1 (0.28 % yr−1), largely contributed (and trend driven) by anthropogenic NOx emissions and methane oxidation. The ozone production efficiency of regional anthropogenic NOx emissions increases when emissions decrease (e.g., Europe, North America) and decreases when emissions increase (e.g., South Asia, Middle East, international shipping). Tropical regions, despite lower emissions, contribute more to TOB compared to emissions from higher latitudes, consistent with previous work, predominantly due to large convection (combined with intense sunlight and larger reaction rates) at the tropics, thereby lifting O3 and its precursor molecules into the free troposphere where ozone's lifetime is longer. We simulate a smaller relative contribution from tropical regions to the global mean surface ozone compared to their contribution to the TOB. The global population-weighted mean ozone is much larger compared to global mean surface ozone, mainly due to large anthropogenic emissions from densely populated regions – East Asia, South Asia and other tropical regions – and a substantial contribution from international ship NOx emissions. The increasing trends in anthropogenic precursor emissions from these regions are the main drivers of increasing global population-weighted mean ozone.

Surface ozone, with its long enough lifetime, can travel far from its precursor emissions, affecting human health, vegetation, and ecosystems on an intercontinental scale. Recent decades have seen significant shifts in ozone precursor emissions: reductions in North America and Europe, increases in Asia, and a steady global rise in methane. Observations from North America and Europe show declining ozone trends, a flattened seasonal cycle, a shift in peak ozone from summer to spring, and increasing wintertime levels. To explain these changes, we use TOAST 1.0, a novel ozone tagging technique implemented in the global atmospheric model CAM4-Chem which attributes ozone to its precursor emissions fully by NOx or VOC+CO+CH4 sources and perform multi-decadal model simulations for 2000–2018. Model-simulated maximum daily 8 h ozone (MDA8 O3) agrees well with rural observations from the TOAR-II database. Our analysis reveals that declining local NOx contributions to peak-season ozone (PSO) in North America and Europe are offset by rising contributions from natural NOx (due to increased O3 production), and foreign anthropogenic- and international shipping NOx due to increased emissions. Transported ozone dominates during spring. Methane is the largest VOC contributor to PSO, while natural NMVOCs become more important in summer. Contributions from anthropogenic NMVOCs remain smaller than those from anthropogenic NOx. Despite rising global methane levels, its contribution to PSO in North America and Europe has declined due to reductions in local NOx emissions. Our results highlight the evolving drivers of surface ozone and emphasize the need for coordinated global strategies that consider both regional emission trends and long-range pollutant transport.

We apply a statistical model, two machine learning models, and three chemical transport models to attribute the observed ozone increases over East and Southeast Asia (ESEA) to changes in anthropogenic emissions and climate. Despite variations in model capabilities and emission inventories, all chemical transport models agree that increases in anthropogenic emission are a primary driver of ozone increases in 1995–2019. The models attribute 53 %–59 % of the increase in tropospheric ozone burden over ESEA to changes in anthropogenic emissions, with emission within ESEA contributing by 66 %–77 %. South Asia has increasing contribution to ozone increases over ESEA. At the surface, the models attribute 69 %–75 % of the ozone increase in 1995–2019 to changes in anthropogenic emissions. Climate change also contributes substantially to the increase in summertime tropospheric (41 %–47 %) and surface ozone (25 %–31 %). We find that emission reductions in China since 2013 have led to contrasting responses in ozone levels in the troposphere (decrease) and at the surface (increase). From 2013 to 2019, the ensemble mean derived from multiple models estimate that 66 % and 56 % of the summertime surface ozone enhancement in the North China Plain and the Yangtze River Delta could be attributed to changes in anthropogenic emissions, respectively, with the remaining attributed to meteorological factors. In contrast, changes in anthropogenic emissions dominate summertime ozone increase in the Pearl River Delta and Sichuan Basin (91 %–95 %). Our study underscores the need for long-term observational data, improved emission inventories, and advanced modeling frameworks to better understand the mechanisms of ozone increases in ESEA.

Tropospheric ozone (trop-O3) is a major pollutant at the surface and an important greenhouse gas at upper layers of troposphere. Major sources of trop-O3 are: transport from the stratosphere; and photochemical production within the troposphere involving reactions of ozone precursors: oxides of nitrogen (NO and NO2, collectively NOx) and reactive carbon species (RC), including methane. In the past few decades, there have been several clean air measures taken by developed countries that have led to decreasing emissions from NH high latitude regions. However, the emissions from developing countries situated in the tropical and mid-latitude regions have been increasing, resulting in an overall equatorward shift in emissions. Zhang et al. 2016 find that this equatorward redistribution of ozone precursor emission is the dominant factor that has led to increase in global tropospheric ozone burden (TOB), due to larger convection of ozone and it’s precursors at the tropics from surface to the free troposphere where ozone lifetime is longer. While several previous studies perform sensitivity simulations to understand the impact of changing precursor emissions on TOB trends, we use a source attribution technique (known as tagging/labelling) to quantify the absolute and relative contribution of various emission sectors to the global TOB. We perform simulation using CESM 1.2.2- CAM4-Chem are performed for a global study of trop-O3 source attribution (summarized in Butler et al. 2018) for the 2000-2018 period. Here, we modify the default chemical mechanism to output the ozone and its tags attributed to the source region/sector of its emitted precursors. For example, an NO molecule originating from biogenic source would be called NO_BIO, and all the other chemical species emanating from NO_BIO (NO2, NO3, O3 etc.) will hold the tag “BIO”. Two simulations are performed for tagging trop-O3 with its NOx and RC precursor emission sources separately. We specify separate tag identities for emissions from anthropogenic, biogenic, biomass burning, and aircraft sources. Additional tags are specified for lightning NOx in the NOx-tagged simulation, and for methane in the VOC-tagged simulation. Here, all surface-based anthropogenic emissions hold tags representing the geographical location (Europe, North America, East Asia, South Asia, Middle East etc.) at which the emissions occur. Using these “tagged” simulations, we address the following questions: What is the contribution of precursor emissions from various regions/sectors to the global TOB and its trend? How does the ozone production efficiency of ozone precursor emissions respond to the trends in these precursor emissions during the 2000-2018 period? How do contributions of different ozone precursors to the TOB contrast with their contribution to the trends in lower and upper tropospheric ozone, area-weighted mean surface O3 and population weighted O3? The design of our simulations and several prominent results will be presented in our PICO. Zhang et al. 2016: Tropospheric ozone change from 1980 to 2010 dominated by equatorward redistribution of emissions. Butler et al. 2018: TOAST 1.0: Tropospheric Ozone Attribution of Sources with Tagging for CESM 1.2.2

Fine and ultrafine ambient particulate matter (PM) has major health and climate impacts.Chemical composition of PM is required for better estimation of these impacts but is considerably expensive to measure as compared to the measurement of only the total PM mass concentrations.We discuss the theoretical possibility of indirect estimation of PM chemical composition by analysing the temporal variation of, relatively inexpensively measured, total PM mass concentrations.We highlight the peculiarities of the temporal characteristics of primary versus secondary aerosols which can become the basis for a machine learning-assisted estimation of chemical fractions at a given time if PM mass concentration time-series of preceding few hours is supplied as input.We also analyse a publicly available chemical composition dataset to show the inter-relationships between different chemical components which can further assist machine learning algorithms to optimise the chemical fraction estimates.

Abstract. This study, performed under the umbrella of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP), responds to the need of the global and regional atmospheric modelling community of having a mosaic emission inventory of air pollutants that conforms to specific requirements: global coverage, long time series, spatially distributed emissions with high time resolution, and a high sectoral resolution. The mosaic approach of integrating official regional emission inventories based on locally reported data, with a global inventory based on a globally consistent methodology, allows modellers to perform simulations of a high scientific quality while also ensuring that the results remain relevant to policymakers. HTAP_v3, an ad-hoc global mosaic of anthropogenic inventories, has been developed by integrating official inventories over specific areas (North America, Europe, Asia including Japan and Korea) with the independent Emissions Database for Global Atmospheric Research (EDGAR) inventory for the remaining world regions. The results are spatially and temporally distributed emissions of SO2, NOx, CO, NMVOC, NH3, PM10, PM2.5, Black Carbon (BC), and Organic Carbon (OC), with a spatial resolution of 0.1 x 0.1 degree and time intervals of months and years covering the period 2000–2018 (DOI 10.5281/zenodo.7516361, https://edgar.jrc.ec.europa.eu/dataset_htap_v3). The emissions are further disaggregated to 16 anthropogenic emitting sectors. This paper describes the methodology applied to develop such an emission mosaic, reports on source allocation, differences among existing inventories, and best practices for the mosaic compilation. One of the key strengths of the HTAP_v3 emission mosaic is its temporal coverage, enabling the analysis of emission trends over the past two decades. The development of a global emission mosaic over such long time series represents a unique product for global air quality modelling and for better-informed policy making, reflecting the community effort expended by the TF-HTAP to disentangle the complexity of transboundary transport of air pollution.

Abstract. This study, performed under the umbrella of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP), responds to the global and regional atmospheric modelling community's need of a mosaic emission inventory of air pollutants that conforms to specific requirements: global coverage, long time series, spatially distributed emissions with high time resolution, and a high sectoral resolution. The mosaic approach of integrating official regional emission inventories based on locally reported data, with a global inventory based on a globally consistent methodology, allows modellers to perform simulations of high scientific quality while also ensuring that the results remain relevant to policymakers. HTAP_v3, an ad hoc global mosaic of anthropogenic inventories, has been developed by integrating official inventories over specific areas (North America, Europe, Asia including Japan and South Korea) with the independent Emissions Database for Global Atmospheric Research (EDGAR) inventory for the remaining world regions. The results are spatially and temporally distributed emissions of SO2, NOx, CO, non-methane volatile organic compounds (NMVOCs), NH3, PM10, PM2.5, black carbon (BC), and organic carbon (OC), with a spatial resolution of 0.1∘ × 0.1∘ and time intervals of months and years, covering the period 2000–2018 (https://doi.org/10.5281/zenodo.7516361, Crippa, 2023, https://edgar.jrc.ec.europa.eu/dataset_htap_v3, last access: June 2023). The emissions are further disaggregated into 16 anthropogenic emitting sectors. This paper describes the methodology applied to develop such an emission mosaic, reports on source allocation, differences among existing inventories, and best practices for the mosaic compilation. One of the key strengths of the HTAP_v3 emission mosaic is its temporal coverage, enabling the analysis of emission trends over the past 2 decades. The development of a global emission mosaic over such long time series represents a unique product for global air quality modelling and for better-informed policymaking, reflecting the community effort expended by the TF-HTAP to disentangle the complexity of transboundary transport of air pollution.

Cities in the global south face dire climate impacts. It is in socioeconomically marginalized urban communities of the global south that the effects of climate change are felt most deeply. Santiago de Chile, a major mid-latitude Andean city of 7.7 million inhabitants, is already undergoing the so-called “climate penalty” as rising temperatures worsen the effects of endemic ground-level ozone pollution. As many cities in the global south, Santiago is highly segregated along socioeconomic lines, which offers an opportunity for studying the effects of concurrent heatwaves and ozone episodes on distinct zones of affluence and deprivation. Here, we combine existing datasets of social indicators and climate-sensitive health risks with weather and air quality observations to study the response to compound heat-ozone extremes of different socioeconomic strata. Attributable to spatial variations in the ground-level ozone burden (heavier for wealthy communities), we found that the mortality response to extreme heat (and the associated further ozone pollution) is stronger in affluent dwellers, regardless of comorbidities and lack of access to health care affecting disadvantaged population. These unexpected findings underline the need of a site-specific hazard assessment and a community-based risk management.

Fine particulate matter (PM2.5) and ground-level ozone (O3) pose a significant risk to human health. The World Health Organization (WHO) has recently revised healthy thresholds for both pollutants. The formation and evolution of PM2.5 and O3 are however governed by complex physical and multiphase chemical processes, and therefore, it is extremely challenging to mitigate both pollutants simultaneously. Here, we review mechanisms and discuss the science-informed pathways for effective and simultaneous mitigation of PM2.5 and O3. Global warming has led to a general increase in biogenic emissions, which can enhance the formation of O3 and secondary organic aerosols. Reductions in anthropogenic emissions during the COVID-19 lockdown reduced PM2.5; however, O3 was enhanced in several polluted regions. This was attributed to more intense sunlight due to low aerosol loading and non-linear response of O3 to NOx. Such contrasting physical and chemical interactions hinder the formulation of a clear roadmap for clean air over such regions. Atmospheric chemistry including the role of biogenic emissions, aerosol-radiation interactions, boundary layer, and regional-scale transport are the key aspects that need to be carefully considered in the formulation of mitigation pathways. Therefore, a thorough understanding of the chemical effects of the emission reductions, changes in photolytic rates and boundary layer due to perturbation of solar radiation, and the effect of meteorological/seasonal changes are needed on a regional basis. Statistical emulators and machine learning approaches can aid the cumbersome process of multi-sector multi-species source attribution.

We investigate the contributions of local and regional emission sources to air pollution in Beijing to inform the design of short-term emission control strategies for mitigating major pollution episodes. We use a well-evaluated version of the WRF-Chem model at 3 km horizontal resolution to determine the daily accumulation of pollution over Beijing from local and regional sources in October 2014 under a range of meteorological conditions. Considering feasible emission reductions across residential, transport, power, and industrial sectors, we find that 1 d controls on local emissions have an immediate effect on PM2.5 (particulate matter with diameter less than 2.5 µm) concentrations on the same day but can have lingering effects as much as 5 d later under stagnant conditions. One-day controls in surrounding provinces have the greatest effect in Beijing on the day following the controls but may have negligible effects under northwesterly winds when local emissions dominate. To explore the contribution of different emission sectors and regions, we perform simulations with each source removed in turn. We find that residential and industrial sectors from neighbouring provinces dominate PM2.5 levels in Beijing during major pollution episodes but that local residential emissions and industrial or residential emissions from more distant provinces can also contribute significantly during some episodes. We then perform a structured set of perturbed emission simulations to allow us to build statistical emulators that represent the relationships between emission sources and air pollution in Beijing over the period. We use these computationally fast emulators to determine the sensitivity of PM2.5 concentrations to different emission sources and the interactions between them, including for secondary PM, and to create pollutant response surfaces for daily average PM2.5 concentrations in Beijing. We use these surfaces to identify the short-term emission controls needed to meet the national air quality target of daily average PM2.5 less than 75 µg m−3 for pollution episodes of different intensities. We find that for heavily polluted days with daily mean PM2.5 higher than 225 µg m−3, even emission reductions of 90 % across all sectors over Beijing and surrounding provinces may be insufficient to meet the national air quality standards. These results highlight the regional nature of PM pollution and the challenges of tackling it during major pollution episodes.

Fine particulate matter (PM2.5, aerodynamic diameter ≤2.5 µm) impacts the climate, reduces visibility and severely influences human health. The Indo-Gangetic Plain (IGP), home to about one-seventh of the world’s total population and a hotspot of aerosol loading, observes strong enhancements in the PM2.5 concentrations towards winter. We performed high-resolution (12 km × 12 km) atmospheric chemical transport modeling (WRF-Chem) for the post-monsoon to winter transition to unravel the underlying dynamics and influences of regional emissions over the region. Model, capturing the observed variations to an extent, reveals that the spatial distribution of PM2.5 having patches of enhanced concentrations (≥100 µgm−3) during post-monsoon, evolves dramatically into a widespread enhancement across the IGP region during winter. A sensitivity simulation, supported by satellite observations of fires, shows that biomass-burning emissions over the northwest IGP play a crucial role during post-monsoon. Whereas, in contrast, towards winter, a large-scale decline in the air temperature, significantly shallower atmospheric boundary layer, and weaker winds lead to stagnant conditions (ventilation coefficient lower by a factor of ~4) thereby confining the anthropogenic influences closer to the surface. Such changes in the controlling processes from post-monsoon to winter transition profoundly affect the composition of the fine aerosols over the IGP region. The study highlights the need to critically consider the distinct meteorological processes of west-to-east IGP and changes in dominant sources from post-monsoon to winter in the formulation of future pollution mitigation policies.

Fine particulate matter (PM2.5) and surface ozone (O3) are major air pollutants in megacities such as Delhi, but the design of suitable mitigation strategies is challenging. Some strategies for reducing PM2.5 may have the notable side effect of increasing O3. Here, we demonstrate a numerical framework for investigating the impacts of mitigation strategies on both PM2.5 and O3 in Delhi. We use Gaussian process emulation to generate a computationally efficient surrogate for a regional air quality model (WRF-Chem). This allows us to perform global sensitivity analysis to identify the major sources of air pollution and to generate emission-sector-based pollutant response surfaces to inform mitigation policy development. Based on more than 100 000 emulation runs during the pre-monsoon period (peak O3 season), our global sensitivity analysis shows that local traffic emissions from the Delhi city region and regional transport of pollution emitted from the National Capital Region (NCR) surrounding Delhi are dominant factors influencing PM2.5 and O3 in Delhi. They together govern the O3 peak and PM2.5 concentration during daytime. Regional transport contributes about 80% of the PM2.5 variation during the night. Reducing traffic emissions in Delhi alone (e.g. by 50 %) would reduce PM2.5 by 15 %–20 % but lead to a 20 %–25 % increase in O3. However, we show that reducing NCR regional emissions by 25 %–30 % at the same time would further reduce PM2.5 by 5 %–10 % in Delhi and avoid the O3 increase. This study provides scientific evidence to support the need for joint coordination of controls on local and regional scales to achieve effective reduction in PM2.5 whilst minimising the risk of O3 increase in Delhi.

Dry deposition is a major sink for tropospheric ozone; nevertheless, studies on its effects on ozone distribution are very limited over the rapidly developing South Asian region. We performed numerical simulations using the regional model WRF-Chem (Weather Research and Forecasting Model coupled with chemistry) to investigate the effect of dry deposition on surface ozone over this region by switching dry deposition ON-OFF in the model. Dry deposition of ozone is found to reduce ozone mixing ratios by up to ∼ 40% over the Indo-Gangetic Plain (IGP) and parts of western and central India. Additional enhancements (by up to ∼ 5 ppbv) in ozone are simulated when dry deposition for all gaseous species is switched off. We find a significant contrast on the effects of dry deposition from station to station as well as on the diurnal timescales over this region. The enhancements in ozone, caused by the absence of dry deposition, are lower over urban stations during nighttime, as compared to the rural and high-altitude stations. Significant enhancements in ozone levels in the absence of dry deposition over the mostly agrarian IGP underpin the importance of dry deposition particularly in the vegetated areas. The South Asian ecosystem is seen to act as an important sink of surface ozone via the dry deposition. The analyses partially fill a gap in the studies of dry deposition over the South Asian region, where this sink is anticipated to get perturbed following the changes in land use and land cover.

We explore the impacts of short-term emission controls on haze events in Beijing in October–November 2014 using high-resolution Weather Research and Forecasting model with Chemistry (WRF-Chem) simulations. The model reproduces surface temperature and relative humidity profiles over the period well and captures the observed variations in key atmospheric pollutants. We highlight the sensitivity of simulated pollutant levels to meteorological variables and model resolution and in particular to treatment of turbulent mixing in the planetary boundary layer. We note that simulating particle composition in the region remains a challenge, and we overpredict NH4 and NO3 at the expense of SO4. We find that the emission controls implemented for the Asia-Pacific Economic Cooperation (APEC) summit period made a relatively small contribution to improved air quality (20 %–26 %), highlighting the important role played by favourable meteorological conditions over this period. We demonstrate that the same controls applied under less favourable meteorological conditions would have been insufficient in reducing pollutant levels to meet the required standards. Continued application of these controls over the 6-week period considered would only have reduced the number of haze days when daily mean fine particulate matter exceeds 75 µg m−3 from 15 to 13 d (days). Our study highlights the limitations of current emission controls and the need for more stringent measures over a wider region during meteorologically stagnant weather.

The spatial distribution of trace gases exhibit large spatial heterogeneity over the Indian region with an elevated pollution loading over densely populated Gangetic Plains (IGP). The contending role and importance of anthropogenic emissions and meteorology in deciding the trace gases level and distribution over Indian region, however, is poorly investigated. In this paper, we use an online regional chemistry transport model (WRF/Chem) to simulate the spatial distribution of trace gases over Indian region during one representative month of only three meteorological seasons namely winter, spring/summer and monsoon. The base simulation, using anthropogenic emissions from SEAC(4)RS inventory, is used to simulate the general meteorological conditions and the realistic spatial distribution of trace gases. A sensitivity simulation is conducted after removing the spatial heterogeneity in the anthropogenic emissions, i.e., with spatially uniform emissions to decouple the role of anthropogenic emissions and meteorology and their role in controlling the distribution of trace gases over India. The concentration levels of Ozone, CO, SO2 and NO2 were found to be lower over IGP when the emissions are uniform over India. A comparison of the base run with the sensitivity run highlights that meteorology plays a dominant role in controlling the spatial distribution of relatively longer-lived species like CO and secondary species like Ozone while short-lived species like NOX and SO2 are predominantly controlled by the spatial variability in anthropogenic emissions over the Indian region.