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We introduce NitroNet, a deep learning model for the prediction of tropospheric NO2 profiles from satellite column measurements. NitroNet is a neural network trained on synthetic NO2 profiles from the regional chemistry and transport model WRF-Chem, which was operated on a European domain for the month of May 2019. This WRF-Chem simulation was constrained by in situ and satellite measurements, which were used to optimize important simulation parameters (e.g. the boundary layer scheme). The NitroNet model receives NO2 vertical column densities (VCDs) from the TROPOspheric Monitoring Instrument (TROPOMI) and ancillary variables (meteorology, emissions, etc.) as input, from which it reproduces NO2 concentration profiles. Training of the neural network is conducted on a filtered dataset, meaning that NO2 profiles showing strong disagreement (>20 %) with colocated TROPOMI column measurements are discarded. We present a first evaluation of NitroNet over a variety of geographical and temporal domains (Europe, the US West Coast, India, and China) and different seasons. For this purpose, we validate the NO2 profiles predicted by NitroNet against satellite, in situ, and MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) measurements. The training data were previously validated against the same datasets. During summertime, NitroNet shows small biases and strong correlations with all three datasets: a bias of +6.7 % and R=0.95 for TROPOMI NO2 VCDs, a bias of −10.5 % and R=0.75 for AirBase surface concentrations, and a bias of −34.3 % to +99.6 % with R=0.83–0.99 for MAX-DOAS measurements. In comparison to TROPOMI satellite data, NitroNet even shows significantly lower errors and stronger correlation than a direct comparison with WRF-Chem numerical results. During wintertime considerable low biases arise because the summertime/late-spring training data are not fully representative of all atmospheric wintertime characteristics (e.g. longer NO2 lifetimes). Nonetheless, the wintertime performance of NitroNet is surprisingly good and comparable to that of classic regional chemistry and transport models. NitroNet can demonstrably be used outside the geographic and temporal domain of the training data with only slight performance reductions. What makes NitroNet unique when compared to similar existing deep learning models is the inclusion of synthetic model data, which offers important benefits: due to the lack of NO2 profile measurements, models trained on empirical datasets are limited to the prediction of surface concentrations learned from in situ measurements. NitroNet, however, can predict full tropospheric NO2 profiles. Furthermore, in situ measurements of NO2 are known to suffer from biases, often larger than +20 %, due to cross-sensitivities to photooxidants, which other models trained on empirical data inevitably reproduce.

Abstract Anthropogenic emissions alter atmospheric composition and therefore the climate, with implications for air pollution- and climate-related human health. Mortality attributable to air pollution and non-optimal temperature is a major concern, expected to shift under future climate change and socioeconomic scenarios. In this work, results from numerical simulations are used to assess future changes in mortality attributable to long-term exposure to both non-optimal temperature and air pollution simultaneously. Here we show that under a realistic scenario, end-of-century mortality could quadruple from present-day values to around 30 (95% confidence level:12-53) million people/year. While pollution-related mortality is projected to increase five-fold, temperature-related mortality will experience a seven-fold rise, making it a more important health risk factor than air pollution for at least 20% of the world’s population. These findings highlight the urgent need to implement stronger climate policies to prevent future loss of life, outweighing the benefits of air quality improvements alone.

The climate effects of atmospheric aerosol particles serving as cloud condensation nuclei (CCN) depend on chemical composition and hygroscopicity, which are highly variable on spatial and temporal scales. Here we present global CCN measurements, covering diverse environments from pristine to highly polluted conditions. We show that the effective aerosol hygroscopicity, κ, can be derived accurately from the fine aerosol mass fractions of organic particulate matter (ϵorg) and inorganic ions (ϵinorg) through a linear combination, κ = ϵorg ⋅ κorg + ϵinorg ⋅ κinorg. In spite of the chemical complexity of organic matter, its hygroscopicity is well captured and represented by a global average value of κorg = 0.12 ± 0.02 with κinorg = 0.63 ± 0.01 as the corresponding value for inorganic ions. By showing that the sensitivity of global climate forcing to changes in κorg and κinorg is small, we constrain a critically important aspect of global climate modelling.

Abstract Many insects utilise optical information in linearly polarised light for navigation, with the degree of linear polarisation (DoLP) determining whether the ‘visibility’ of such optical information is available to them. However, changes in degree of linear polarisation in response to increased atmospheric levels of fine particulate matter (PM2.5) are poorly understood. We present analyses based on both ground-based monitoring and particulate matter modelling, establishing a quantitative relationship between PM2.5 mass concentration and the DoLP. We apply this relationship to a global PM2.5 projection for 2050 and estimate the increase in number and spatial extent of low visibility days for honeybees. We find an increase by up to 20% in the geographical extent of low visibility days in 2050, with an augmented frequency of low visibility days across an area exceeding 0.75 million km2 in India and 2 million km2 in China. More frequent and widespread low visibility conditions can reduce the ability of insects to navigate, especially in hotspot regions.

Abstract During summer, ammonia emissions in Southeast Asia influence air pollution and cloud formation. Convective transport by the South Asian monsoon carries these pollutant air masses into the upper troposphere and lower stratosphere (UTLS), where they accumulate under anticyclonic flow conditions. This air mass accumulation is thought to contribute to particle formation and the development of the Asian Tropopause Aerosol Layer (ATAL). Despite the known influence of ammonia and particulate ammonium on air pollution, a comprehensive understanding of the ATAL is lacking. In this modelling study, the influence of ammonia on particle formation is assessed with emphasis on the ATAL. We use the EMAC chemistry-climate model, incorporating new particle formation parameterisations derived from experiments at the CERN CLOUD chamber. Our diurnal cycle analysis confirms that new particle formation mainly occurs during daylight, with a 10-fold enhancement in rate. This increase is prominent in the South Asian monsoon UTLS, where deep convection introduces high ammonia levels from the boundary layer, compared to a baseline scenario without ammonia. Our model simulations reveal that this ammonia-driven particle formation and growth contributes to an increase of up to 80% in cloud condensation nuclei (CCN) concentrations at cloud-forming heights in the South Asian monsoon region. We find that ammonia profoundly influences the aerosol mass and composition in the ATAL through particle growth, as indicated by an order of magnitude increase in nitrate levels linked to ammonia emissions. However, the effect of ammonia-driven new particle formation on aerosol mass in the ATAL is relatively small. Ammonia emissions enhance the regional aerosol optical depth (AOD) for shortwave solar radiation by up to 70%. We conclude that ammonia has a pronounced effect on the ATAL development, composition, the regional AOD, and CCN concentrations.

We present the coupling of the Jena Scheme for Biosphere–Atmosphere Coupling in Hamburg version 4 (JSBACHv4) to the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. With JSBACH, the soil water bucket model in EMAC is replaced by a diffusive hydrological transport model for soil water that includes water storage and infiltration in five soil layers, preventing soil from drying too rapidly and reducing biases in soil temperature and moisture. A three-layer soil scheme is implemented, and phase changes in water in the soil are considered. The leaf area index (LAI) climatology in EMAC has been substituted with a phenology module calculating the LAI. Multiple land cover types are included to provide a state-dependent surface albedo, which accounts for the absorption of solar radiation by vegetation. Plant net primary productivity, leaf area index and surface roughness are calculated according to the plant functional types. This paper provides a detailed evaluation of the new coupled model based on observations and reanalysis data, including ERA5/ERA5-Land datasets, Global Precipitation Climatology Project (GPCP) data and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. Land surface temperature (LST), terrestrial water storage (TWS), surface albedo (α), net top-of-atmosphere radiation flux (RadTOA), precipitation (precip), leaf area index (LAI), fraction of absorbed photosynthetic active radiation (FAPAR) and gross primary productivity (GPP) are evaluated in particular. The strongest correlation (r) between reanalysis data and the newly coupled model is found for LST (r=0.985, with an average global bias of −1.546 K), α (r=0.947, with an average global bias of −0.015) and RadTOA (r=0.907, with an average global bias of 3.56 W m−2). Precipitation exhibits a correlation with the GPCP dataset of 0.523 and an average global bias of 0.042 mm d−1. The LAI optimisation yields a correlation of 0.637 with observations and a global mean deviation of −0.212. FAPAR and GPP exemplify two of the many additional variables made available through JSBACH in EMAC. FAPAR and observations show a correlation of 0.663, with an average global difference of −0.223, while the correlation for GPP and observations is 0.564 and the average global difference is −0.001 kg carbon km−1. Benefiting from the numerous added features within the simulated land system, the representation of soil moisture is improved, which is critical for vegetation modelling. This improvement can be attributed to a general increase in soil moisture and water storage in deeper soil layers and a closer alignment of simulated TWS with observations, mitigating the previously widespread problem of soil drought. We show that the numerous newly added components strongly improve the land surface, e.g. soil moisture, TWS and LAI, while surface parameters, such as LST, surface albedo or RadTOA, which were mostly prescribed according to climatologies, remain similar. The coupling of JSBACH brings EMAC a step closer towards a holistic comprehensive Earth system model and extends its versatility.

Este estudo teve como objetivo corrigir algumas lacunas, ainda existentes, no processo de aferição da rugosidade do assento do rolamento em tampas para motores elétricos, utilizando uma das metodologias mais assertivas atualmente, o Seis Sigma. A pesquisa focou a análise da robustez da medição do componente, a verificação da frequência de sua inspeção e a identificação dos fatores que poderiam influenciar a sua variação. Para isso utilizou-se ferramentas associadas ao Seis Sigma, buscando realizar um mapa de processo coerente, uma matriz de decisão que considerasse os principais fatores de variação e, posteriormente, uma árvore de processos robusta para permitir análises corretas. Com o estudo, garantiu-se que os componentes estavam chegando para os clientes finais com a devida qualidade designada no projeto inicial e eliminou-se a incerteza em relação ao método com o qual essa aferição era realizada, melhorando a assertividade das medições e tornando o processo mais confiável para os clientes e auditores externos.

Abstract Geological evidence indicates that a supernova within 100 parsecs of Earth occurs around once per million years. Such nearby supernovas can produce an intense gamma-ray burst and a 100-fold increase of cosmic rays, lasting several centuries. We find that the effect of a short burst of gamma rays is small since they are strongly attenuated before reaching the lower stratosphere. Intense cosmic radiation affects stratospheric ozone but, due to compensating effects in catalytic chemical cycles, ozone depletion is moderate and comparable to that from current anthropogenic emissions. This also holds for the low-oxygen atmosphere during early evolution of terrestrial life. We estimate the increase in aerosol and clouds from a 100-fold increase of cosmic rays exerts a radiative forcing comparable in magnitude but opposite in sign to current anthropogenic climate forcing. We conclude that Earth’s atmosphere is effective at shielding the biosphere from nearby supernovae.

Direct exposure to household fine particulate air pollution (HAP) associated with inefficient combustion of fuels (wood, charcoal, coal, crop residues, kerosene, etc.) for cooking, space-heating, and lighting is estimated to result in 2.3 (1.6-3.1) million premature yearly deaths globally. HAP emitted indoors escapes outdoors and is a leading source of outdoor ambient fine particulate air pollution (AAP) in low- and middle-income countries, often being a larger contributor than well-recognized sources including road transport, industry, coal-fired power plants, brick kilns, and construction dust. We review published scientific studies that model the contribution of HAP to AAP at global and major sub-regional scales. We describe strengths and limitations of the current state of knowledge on HAPs contribution to AAP and the related impact on public health and provide recommendations to improve these estimates. We find that HAP is a dominant source of ambient fine particulate matter (PM2.5) globally - regardless of variations in model types, configurations, and emission inventories used - that contributes approximately 20 % of total global PM2.5 exposure. There are large regional variations: in South Asia, HAP contributes ∼ 30 % of ambient PM2.5, while in high-income North America the fraction is ∼ 7 %. The median estimate indicates that the household contribution to ambient air pollution results in a substantial premature mortality burden globally of about 0.77(0.54-1) million excess deaths, in addition to the 2.3 (1.6-3.1) million deaths from direct HAP exposure. Coordinated global action is required to avert this burden.

AbstractSmoke from vegetation fires affects air quality, atmospheric cycling, and the climate in the Amazon rain forest. A major unknown has remained the quantity of long-range transported smoke from Africa in relation to local and regional fire emissions. Here we quantify the abundance, seasonality, and properties of African smoke in central Amazonia. We show that it accounts for ~ 60% of the black carbon concentrations during the wet season and ~ 30% during the dry season. The African smoke influences aerosol-radiation interactions across the entire Amazon, with the strongest impact on the vulnerable eastern basin, a hot spot of climate and land use change. Our findings further suggest that the direct influence of African smoke has been historically relevant for soil fertilization, the carbon and water cycles, and, thus, the development of the Amazon forest ecosystem, even in the pre-industrial era.

Objectives: Percutaneous Vocal Fold Lateralization (PVFL) consists of external fixation with non-absorbable percutaneous suture of the vocal fold in a lateral position, under direct glottic visualization. The objective of this study is to determine the effectiveness of PVFL in a university pediatric hospital, as well as to describe the potential risks and complications of the surgery. Methods: Retrospective cohort study, with data collected from electronic medical records. The study was approved by the Research Ethics Committee of the institution. Surgeries were performed with the modified Lichentenberg technique and data, and outcomes were analyzed. Results: Six patients with Bilateral Vocal Fold Paralysis who underwent Percutaneous Vocal Fold Lateralization were evaluated. Three patients were male. The age at diagnosis ranged from 2 to 132 days (mean 10.5 days). The reason for investigating the upper airway was the presence of increased work of breathing and stridor. Five patients had a favorable clinical evolution, with spontaneous ventilation in room air and absence of stridor or ventilatory effort, without the need for tracheostomy. Surgical results in this series corroborate the findings of other similar cohorts, which showed Percutaneous Vocal Fold Lateralization as a safe and effective procedure in avoiding tracheostomy or allowing decannulation in children with Bilateral Vocal Fold Paralysis. Conclusions: PVFL seems to be a safe and effective procedure, but it has morbidity, due to immediate, and probably late, non-serious complications. Studies with a larger number of patients, with longer follow-up and using a controlled and randomized clinical design are needed to establish the role of PVFL in the treatment of BVFP in newborns and infants. Levels of evidence: Level 4 (step 4).

Carbon cycling in the Amazon fundamentally depends on the functioning of ecosystems and atmospheric dynamics, which are highly intricate. Few studies have hitherto investigated or measured the radiative effects of aerosols on the Amazon and Cerrado. This study examines the effects of atmospheric aerosols on solar radiation and their effects on net ecosystem exchange (NEE) in an area of semideciduous tropical forest in the north of Mato Grosso. Our results show that for a relative irradiance (f) 1.10–0.67, a decrease in incident solar radiation is associated with a reduction in the NEE. However, an average increase of 25 %–110 % in NEE was observed when pollution levels and aerosol optical depth (AOD) were above ≈ 1.25 and f < 0.5. The increase NEE was attributed to the increase of up to 60 % in the diffuse fraction of photosynthetically active radiation. The change in AOD and f was mainly attributable to biomass burning organic aerosols from fires. Important influences on vapor pressure deficit (VPD) as well as air temperature (Tair) and canopy (LCT), induced by the interaction between solar radiation and high aerosol load in the observation area, were also noticed. On average, a cooling of about 3–4 ∘C was observed for Tair and LCT, and a decrease of up to 2–3 hPa was observed for VPD. Given the long-distance transport of aerosols emitted by burning biomass, significant changes in atmospheric optical properties and irradiance will impact the CO2 flux of semideciduous forests distributed in the region.

Studies of atmospheric trace gases in remote, pristine environments are critical for assessing the accuracy of climate models and advancing our understanding of natural processes and global changes. We investigated the surface ozone (O3) variability over East Antarctica during the austral summer of 2015–2017 by combining surface and balloon-borne measurements at the Indian station Bharati (69.4∘ S, 76.2∘ E, ∼ 35 m above mean sea level) with EMAC (ECHAM5/MESSy Atmospheric Chemistry) atmospheric chemistry–climate model simulations. The model reproduced the observed surface O3 level (18.8 ± 2.3 nmol mol−1) with negligible bias and captured much of the variability (R = 0.5). Model-simulated tropospheric O3 profiles were in reasonable agreement with balloon-borne measurements (mean bias: 2–12 nmol mol−1). Our analysis of a stratospheric tracer in the model showed that about 41 %–51 % of surface O3 over the entire Antarctic region was of stratospheric origin. Events of enhanced O3 (∼ 4–10 nmol mol−1) were investigated by combining O3 vertical profiles and air mass back trajectories, which revealed the rapid descent of O3-rich air towards the surface. The photochemical loss of O3 through its photolysis (followed by H2O + O(1D)) and reaction with hydroperoxyl radicals (O3 + HO2) dominated over production from precursor gases (NO + HO2 and NO + CH3O2) resulting in overall net O3 loss during the austral summer. Interestingly, the east coastal region, including the Bharati station, tends to act as a stronger chemical sink of O3 (∼ 190 pmol mol−1 d−1) than adjacent land and ocean regions (by ∼ 100 pmol mol−1 d−1). This is attributed to reverse latitudinal gradients between H2O and O(1D), whereby O3 loss through photolysis (H2O + O(1D)) reaches a maximum over the east coast. Further, the net photochemical loss at the surface is counterbalanced by downward O3 fluxes, maintaining the observed O3 levels. The O3 diurnal variability of ∼ 1.5 nmol mol−1 was a manifestation of combined effects of mesoscale wind changes and up- and downdrafts, in addition to the net photochemical loss. The study provides valuable insights into the intertwined dynamical and chemical processes governing the O3 levels and variability over East Antarctica.

Abstract Exposure to fine particulate matter (PM2.5) is associated with an increased risk of morbidity and mortality. In Europe, residential fuel combustion and road transport emissions contribute significantly to PM2.5. Toxicological studies indicate that PM2.5 from these sources is relatively more hazardous, owing to its high content of black and organic carbon. Here, we study the contribution of the emissions from these sectors to long-term exposure and excess mortality in Europe. We quantified the impact of anthropogenic carbonaceous aerosols on excess mortality and performed a sensitivity analysis assuming that they are twice as toxic as inorganic particles. We find that total PM2.5 from residential combustion leads to 72,000 (95% confidence interval: 48,000–99,000) excess deaths per year, with about 40% attributed to carbonaceous aerosols. Similarly, road transport leads to about 35,000 (CI 23,000–47,000) excess deaths per year, with 6000 (CI 4000–9000) due to carbonaceous particles. Assuming that carbonaceous aerosols are twice as toxic as other PM2.5 components, they contribute 80% and 37%, respectively, to residential fuel combustion and road transport-related deaths. We uncover robust national variations in the contribution of each sector to excess mortality and emphasize the importance of country-specific emission reduction policies based on national characteristics and sectoral shares.

Abstract Terrestrial vegetation emits vast amounts of monoterpenes into the atmosphere, influencing ecological interactions and atmospheric chemistry. Global emissions are simulated as a function of temperature with a fixed exponential relationship (β coefficient) across forest ecosystems and environmental conditions. We applied meta-analysis algorithms on 40 years of published monoterpene emission data and show that relationship between emissions and temperature is more sensitive and intricate than previously thought. Considering the entire dataset, a higher temperature sensitivity (β = 0.13 ± 0.01 °C−1) is derived but with a linear increase with the reported coefficients of determination (R2), indicating that co-occurring environmental factors modify the temperature sensitivity of the emissions that is primarily related to the specific plant functional type (PFT). Implementing a PFT-dependent β in a biogenic emission model, coupled with a chemistry – climate model, demonstrated that atmospheric processes are exceptionally dependent on monoterpene emissions which are subject to amplified variations under rising temperatures.

We present WRF-Chem simulations over central Europe with a spatial resolution of 3 km × 3 km and focus on nitrogen dioxide (NO2). A regional emission inventory issued by the German Environmental Agency, with a spatial resolution of 1 km × 1 km, is used as input. We demonstrate by comparison of five different model setups that significant improvements in model accuracy can be achieved by choosing the appropriate boundary layer scheme, increasing vertical mixing strength, and/or tuning the temporal modulation of the emission data (“temporal profiles”) driving the model. The model setup with improved vertical mixing is shown to produce the best results. Simulated NO2 surface concentrations are compared to measurements from a total of 275 in situ measurement stations in Germany, where the model was able to reproduce average noontime NO2 concentrations with a bias of ca. −3 % and R=0.74. The best agreement is achieved when correcting for the presumed NOy cross sensitivity of the molybdenum-based in situ measurements by computing an NOy correction factor from modelled peroxyacetyl nitrate (PAN) and nitric acid (HNO3) mixing ratios. A comparison between modelled NO2 vertical column densities (VCDs) and satellite observations from TROPOMI (TROPOspheric Monitoring Instrument) is conducted with averaging kernels taken into account. Simulations and satellite observations are shown to agree with a bias of +5.5 % and R=0.87 for monthly means. Lastly, simulated NO2 concentration profiles are compared to noontime NO2 profiles obtained from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements at five locations in Europe. For stations within Germany, average biases of −25.3 % to +12.0 % were obtained. Outside of Germany, where lower-resolution emission data were used, biases of up to +50.7 % were observed. Overall, the study demonstrates the high sensitivity of modelled NO2 to the mixing processes in the boundary layer and the diurnal distribution of emissions.

The mining industry in Brazil, despite contributing to economic growth, is one of the human activities that negatively impacts the environment. This situation can be contextualized in discussions of several curricular chemistry topics. One way in which science, technology, society, and environmental issues can be discussed in classes is through case studies. This article reports on three interrupted case studies, based on research articles, which were developed and implemented in a Scientific Communication Course offered to first-year undergraduate Chemistry students at the University of São Paulo, Brazil. During two sessions of this course, students, divided in groups, developed hypotheses, chose sampling points and equipment for instrumental analyses, and evaluated data provided in the case studies. Results from a Descending Hierarchical Classification Analysis of oral presentations, performed on "IRAMUTEQ" software, and from a quiz containing 11 true or false statements (response rate of 79%) provide evidence for the effectiveness of the case studies for conceptual understanding of different topics in chemistry, such as heavy metals, sediments, and principles of instrumental chemical analysis, and for the development of communication and oral presentation skills.

The Covid-19 pandemic has affected the travel behavior of commuters, with soft modes emerging as reliable options for short-distance trips. This research focuses on evaluating the bike-friendliness of Venice, Italy, a unique city for its morphological and mobility characteristics. When considering daily commuting between the mainland and the historic city center in the lagoon, the bicycle is not an adopted solution. Yet, the recent construction of a bicycle and pedestrian path that runs alongside the main bridge between the mainland and historical city could alleviate the pressure on public transport and the use of cars, especially in peak hours. This contribution evaluates the potential for using bicycles to reach the historic center of Venice from the mainland, and the appropriateness of the infrastructural equipment. The quantitative analysis examines the current supply and demand in absolute values and in terms of modal share. Projecting the number of actual users under different scenarios until 2030, in accordance with the Venice Sustainable Urban Mobility Plan and other relevant plans, the inadequate provision of parking areas for bikes emerges as an unsolved issue. A revision of the mobility layout is thus required if bicycles are expected to be a competitive alternative solution.

Elevated concentrations of particulate matter (PM) significantly deteriorate the air quality; however, the contributions from regional versus remote anthropogenic sources have remained uncertain over the western Indian region. In this regard, we have performed high-resolution regional modeling (WRF-Chem v3.9.1) to quantify the contribution of regional versus trans-regional anthropogenic sources to PM2.5 (fine PM) and PM2.5-10 (coarse PM) concentrations in contrasting seasons. Seasonal variability in spatial mean Aerosol Optical Depth (AOD) derived from the WRF-Chem model (0.21–0.42) agreed reasonably with MERRA-2 reanalysis (0.29–0.54) and MODIS satellite (0.23–0.51) over western India. Variability in surface PM2.5 and PM10 concentrations were also reproduced as per the benchmarks (|Fractional Bias| ≤ 60% and |Fractional Error| ≤ 75%) at most of the stations in this region. Results from sensitivity simulations reveal the dominant contribution of both regional and trans-regional anthropogenic sources to PM2.5 concentrations over western India in winter and post-monsoon, when PM2.5 concentrations are generally high. On the other hand, contribution from background levels (due to domain-wide natural emissions, fire emissions and pollutant transport from beyond domain boundaries) is highest during pre-monsoon and monsoon with a significant contribution of mineral dust especially to PM2.5-10 (coarse PM). Analysis of PM spatial distribution at ∼900hpa pressure level reveals greater relative contributions of trans-regional emissions and background levels compared to that near the surface. Our study highlights key roles of trans-regional anthropogenic emissions and mineral dust, besides the local and regional emissions, in air pollution over western India. The quantitative analyses presented here would be useful for designing measures to minimize health and environmental impacts in line with the objectives of the National Clean Air Programme (NCAP) in India.

Tropospheric chlorine chemistry can strongly impact the atmospheric oxidation capacity and composition, especially in urban environments. To account for these reactions, the gas- and aqueous-phase Cl chemistry of the community atmospheric chemistry box model Chemistry As A Boxmodel Application/Module Efficiently Calculating the Chemistry of the Atmosphere (CAABA/MECCA) has been extended. In particular, an explicit mechanism for ClNO2 formation following N2O5 uptake to aerosols has been developed. The updated model has been applied to two urban environments with different concentrations of NOx (NO + NO2): New Delhi (India) and Leicester (United Kingdom). The model shows a sharp build-up of Cl at sunrise through Cl2 photolysis in both the urban environments. Besides Cl2 photolysis, ClO+NO reaction and photolysis of ClNO2 and ClONO are also prominent sources of Cl in Leicester. High-NOx conditions in Delhi tend to suppress the nighttime build-up of N2O5 due to titration of O3 and thus lead to lower ClNO2, in contrast to Leicester. Major loss of ClNO2 is through its uptake on chloride, producing Cl2, which consequently leads to the formation of Cl through photolysis. The reactivities of Cl and OH are much higher in Delhi; however, the Cl/OH reactivity ratio is up to ≈ 9 times greater in Leicester. The contribution of Cl to the atmospheric oxidation capacity is significant and even exceeds (by ≈ 2.9 times) that of OH during the morning hours in Leicester. Sensitivity simulations suggest that the additional consumption of volatile organic compounds (VOCs) due to active gas- and aqueous-phase chlorine chemistry enhances OH, HO2, and RO2 near sunrise. The simulation results of the updated model have important implications for future studies on atmospheric chemistry and urban air quality.

Emissions of biogenic volatile organic compounds (BVOCs) from the terrestrial biosphere play a significant role in major atmospheric processes. BVOCs are highly reactive compounds that influence the atmosphere's oxidation capacity and also serve as precursors for the formation of aerosols that influence global radiation budgets. Emissions depend on the response of vegetation to atmospheric conditions (primarily temperature and light), as well as other stresses, e.g. from droughts and herbivory. The El Niño–Southern Oscillation (ENSO) is a naturally occurring cycle arising from anomalies in the sea surface temperature (SST) in the tropical Pacific. ENSO perturbs the natural seasonality of weather systems on both global and regional scales and is considered the most significant driver of climate variability. Several studies have evaluated the sensitivity of BVOC fluxes during ENSO events using historical transient simulations. While this approach employs realistic scenarios, it is difficult to assess the impact of ENSO alone given the multiple types of climate forcing, e.g. from anthropogenic emissions of CO2 and aerosol. In this study, a global atmospheric chemistry–climate model with enabled interactive vegetation was used to conduct two sets of simulations: (1) isolated ENSO event simulations, in which a single ENSO event is used to perturb otherwise baseline conditions, and (2) sustained ENSO simulations, in which the same ENSO conditions are reproduced for an extended period of time. From the isolated ENSO events, we present global and regional BVOC emission changes resulting from the immediate response of vegetation to atmospheric states. More focus is given to the sustained ENSO simulations, which have the benefit of reducing the internal variability for more robust statistics when linking atmospheric and vegetation variables with BVOC flux anomalies. Additionally, these simulations explore long-term changes in the biosphere with potential shifts in vegetation in this possible climate mode, accounting for the prospect of increased intensity and frequency of ENSO with climate change. Our results show that strong El Niño events increase global isoprene emission fluxes by 2.9 % and that one single ENSO event perturbs the Earth system so markedly that BVOC emission fluxes do not return to baseline emissions within several years after the event. We show that persistent ENSO conditions shift the vegetation to a new quasi-equilibrium state, leading to an amplification of BVOC emission changes with up to a 19 % increase in isoprene fluxes over the Amazon. We provide evidence that BVOC-induced changes in plant phenology, such as the leaf area index (LAI), have a significant influence on BVOC emissions in the sustained ENSO climate mode.

Plants emit biogenic volatile organic compounds (BVOCs) in response to changes in environmental conditions (e.g. temperature, radiation, soil moisture). In the large family of BVOCs, isoprene is by far the strongest emitted compound and plays an important role in ozone chemistry, thus affecting both air quality and climate. In turn, climate change may alter isoprene emissions by increasing temperature as well as the occurrence and intensity of severe water stresses that alter plant functioning. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) provides different parameterizations to account for the impact of water stress on isoprene emissions, which essentially reduces emissions in response to the effect of soil moisture deficit on plant productivity. By applying the regional climate–chemistry model RegCM4chem coupled to the Community Land Model CLM4.5 and MEGAN2.1, we thus performed sensitivity simulations to assess the effects of water stress on isoprene emissions and near-surface ozone levels over the Euro-Mediterranean region and across the drier and wetter summers over the 1992–2016 period using two different parameterizations of the impact of water stress implemented in the MEGAN model. Over the Euro-Mediterranean region and across the simulated summers, water stress reduces isoprene emissions on average by nearly 6 %. However, during the warmest and driest selected summers (e.g. 2003, 2010, 2015) and over large isoprene-source areas (e.g. the Balkans), decreases in isoprene emissions range from −20 % to −60 % and co-occur with negative anomalies in precipitation, soil moisture and plant productivity. Sustained decreases in isoprene emissions also occur after prolonged or repeated dry anomalies, as observed for the summers of 2010 and 2012. Although the decrease in isoprene emissions due to water stress may be important, it only reduces near-surface ozone levels by a few percent due to a dominant VOC-limited regime over southern Europe and the Mediterranean Basin. Overall, over the selected analysis region, compared to the old MEGAN parameterization, the new one leads to localized and 25 %–50 % smaller decreases in isoprene emissions and 3 %–8 % smaller reductions in near-surface ozone levels.

A new global dataset of annually averaged ultrafine particle (UFP) concentrations at the Earth's surface for the years 2015–2017 has been developed through numerical simulations using the ECHAM/MESSy Atmospheric Chemistry model (EMAC). We present total and size-resolved concentrations along with their interannual variability. Size distributions of emitted particles from the contributing source sectors have been derived based on literature reports. The model results of UFP concentrations are evaluated using particle size distribution and particle number concentration measurements from available datasets and the literature. While we obtain reasonable agreement between the model results and observations (logarithmic-scale correlation of r=0.76 for non-remote, polluted regions), the highest values of observed, street-level UFP concentrations are systematically underestimated, whereas in rural environments close to urban areas the model generally overestimates observed UFP concentrations. As the relatively coarse global model does not resolve concentration gradients in urban centres and industrial UFP hotspots, high-resolution data of anthropogenic emissions are used to account for such differences in each model grid box, obtaining UFP concentrations with unprecedented 0.1∘×0.1∘ horizontal resolution at the Earth's surface. This observation-guided downscaling further improves the agreement with observations, leading to an increase in the logarithmic-scale correlation between observed and simulated UFP concentrations to r=0.84 in polluted environments (and 0.95 in all regions), a decrease in the root mean squared logarithmic error (from 0.57 to 0.43), and removal of discrepancies associated with air quality and population density gradients within the model grid boxes. The model results are made publicly available for studies on public health and other impacts of atmospheric UFPs, as well as for intercomparison with other regional and global models and datasets.

Ozone is an important contributor to the radiative energy budget of the upper troposphere (UT). Therefore, observing and understanding the processes contributing to ozone production are important for monitoring the progression of climate change. Nitrogen oxides (NOx ≡ NO + NO2) and volatile organic compounds (VOCs) are two main tropospheric precursors to ozone formation. Depending on their abundances, ozone production can be sensitive to changes in either of these two precursors. Here, we focus on processes contributing to ozone chemistry in the upper tropical troposphere between 30∘ S and 30∘ N latitude, where changes in ozone have a relatively large impact on anthropogenic radiative forcing. Based on modeled trace gas mixing ratios and meteorological parameters simulated by the ECHAM5/MESSy2 Atmospheric Chemistry (EMAC) general circulation model, we analyze a variety of commonly applied metrics including ozone production rates (P(O3)), the formaldehyde (HCHO) to NO2 ratio and the share of methyl peroxy radicals (CH3O2) forming HCHO (α(CH3O2)) for their ability to describe the chemical regime. We show that the distribution of trace gases in the tropical UT is strongly influenced by the varying locations of deep convection throughout the year, and we observe peak values for NOx and P(O3) over the continental areas of South America and Africa where lightning is frequent. We find that P(O3) and its response to NO is unsuitable for determining the dominant regime in the upper troposphere. Instead, α(CH3O2) and the HCHO/NO2 ratio in combination with ambient NO levels perform well as metrics to indicate whether NOx or VOC sensitivity is prevalent. We show that effectively only the knowledge of the availability of NO and HO2 is required to adequately represent O3 precursors and its sensitivity towards them. A sensitivity study with halving, doubling and excluding lightning NOx demonstrates that lightning and its distribution in the tropics are the major determinants of the chemical regimes and ozone formation in the upper tropical troposphere.

Abstract The climate effects of atmospheric aerosol particles serving as cloud condensation nuclei (CCN) depend on chemical composition and hygroscopicity, which are highly variable on spatial and temporal scales. Here we present global CCN measurements, covering diverse environments from pristine to highly polluted conditions. We show that the effective aerosol hygroscopicity, κ, can be derived accurately from the fine aerosol mass fractions of organic particulate matter (ϵ org) and inorganic ions (ϵ inorg) through a linear combination, κ = ϵ org ⋅ κ org + ϵ inorg ⋅ κ inorg. In spite of the chemical complexity of organic matter, its hygroscopicity is well captured and represented by a global average value of κ org = 0.12 ± 0.02 with κ inorg = 0.63 ± 0.01 as the corresponding value for inorganic ions. By showing that the sensitivity of global climate forcing to changes in κ org and κ inorg is small, we constrain a critically important aspect of global climate modelling.