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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.

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.

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.

Abstract The near-surface temperature in Mediterranean climate-type regions has increased overall similarly or more rapidly than the global mean rates. Although these regions have comparable climate characteristics and are located at similar latitudes, recent warming acceleration is most pronounced in the Mediterranean Basin. Here, we investigate the contributions of several climate drivers to regional warming anomalies. We consider greenhouse gases, aerosols, solar irradiance, land–atmosphere interactions, and natural climate variability modes. Our results highlight the dominant role of anthropogenic greenhouse gas radiative forcing in all Mediterranean climate-type regions, particularly those in the northern hemisphere. In the Mediterranean Basin, the recent warming acceleration is largely due to the combined effect of declining aerosols and a negative trend in near-surface soil moisture. While land-atmosphere feedbacks are also important in other locations (e.g., California and Southern Africa), this synergy is unique in the Mediterranean Basin. These two regional climate drivers have natural and anthropogenic components of equivalent importance. Such feedbacks are not fully resolved in the current regional climate projections.

Abstract Smoke 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.

Abstract Atmospheric ozone and oxygen protect the terrestrial biosphere against harmful ultraviolet (UV) radiation. Here, we model atmospheres of Earth-like planets hosted by stars with near-solar effective temperatures (5300 to 6300 K) and a broad range of metallicities covering known exoplanet host stars. We show that paradoxically, although metal-rich stars emit substantially less ultraviolet radiation than metal-poor stars, the surface of their planets is exposed to more intense ultraviolet radiation. For the stellar types considered, metallicity has a larger impact than stellar temperature. During the evolution of the universe, newly formed stars have progressively become more metal-rich, exposing organisms to increasingly intense ultraviolet radiation. Our findings imply that planets hosted by stars with low metallicity are the best targets to search for complex life on land.

Abstract Carbonyl sulfide (OCS or COS) is a ubiquitous trace gas and plays a role in forming stratospheric sulfate aerosol particles, thereby influencing climate. In this study, whole‐air samples containing OCS were collected onboard a passenger aircraft (IAGOS‐CARIBIC) from the upper troposphere/lowermost stratosphere (UT/LMS, 10–12 km) region and analyzed with CryoTrap–GC–AED system in the laboratory. Global OCS mixing ratios are presented and by using the OCS measurements in conjunction with other trace gases, an atmospheric OCS lifetime of 2.1 ± 1.3 years, and lowermost stratospheric OCS lifetime of 47 ± 16 years were determined. A total flux of 137 GgS a−1 of OCS from the troposphere into the stratosphere was estimated, and the stratospheric sink estimate yielded 55 ± 23 GgS a−1 of OCS. The 60% smaller sink can be interpreted as 82 GgS a−1 OCS which is transported back from the stratosphere into the troposphere.

Fine particulate aerosols sampled around the Arabian Peninsula predominantly originate from anthropogenic pollution and constitute one of the leading health risk factors in the region, according to shipborne sampling and numerical atmospheric chemistry modelling.

Long-term exposure to ambient ozone (O _3 ) is associated with excess respiratory mortality. Pollution emissions, demographic, and climate changes are expected to drive future ozone-related mortality. Here, we assess global mortality attributable to ozone according to an Intergovernmental Panel on Climate Change (IPCC) Shared Socioeconomic Pathway (SSP) scenario applied in Coupled Model Intercomparison Project Phase 6 (CMIP6) models, projecting a temperature increase of about 3.6 °C by the end of the century. We estimated ozone-related mortality on a global scale up to 2090 following the Global Burden of Disease (GBD) 2019 approach, using bias-corrected simulations from three CMIP6 Earth System Models (ESMs) under the SSP3-7.0 emissions scenario. Based on the three ESMs simulations, global ozone-related mortality by 2090 will amount to 2.79 M [95% CI 0.97 M–5.23 M] to 3.12 M [95% CI 1.11 M–5.75 M] per year, approximately ninefold that of the 327 K [95% CI 103 K–652 K] deaths per year in 2000. Climate change alone may lead to an increase of ozone-related mortality in 2090 between 42 K [95% CI −37 K–122 K] and 217 K [95% CI 68 K–367 K] per year. Population growth and ageing are associated with an increase in global ozone-related mortality by a factor of 5.34, while the increase by ozone trends alone ranges between factors of 1.48 and 1.7. Ambient ozone pollution under the high-emissions SSP3-7.0 scenario is projected to become a significant human health risk factor. Yet, optimizing living conditions and healthcare standards worldwide to the optimal ones today (application of minimum baseline mortality rates) will help mitigate the adverse consequences associated with population growth and ageing, and ozone increases caused by pollution emissions and climate change.

High levels of sulfur dioxide (SO2) due to human activities pose a serious air pollution issue in China, especially in urban agglomerations. However, limited research has investigated the impact of anthropogenic emissions on higher SO2 concentrations in urban regions compared to rural areas in China. Here, we analyzed the trends in SO2 concentrations from 1980 to 2021 in China using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) dataset. SO2 column concentrations from the Copernicus Atmosphere Monitoring Service (CAMS) and the Ozone Monitoring Instrument (OMI) during the years 2007–2021 were also examined for validation and comparison purposes. Eight representative areas, including four urban regions (Pearl River Delta [PRD], Beijing-Tianjin-Hebei [BTH], Yangtze River Delta [YRD], and Sichuan Basin [SCB]) and four rural regions (Northeast Region [NER], Mongolian Region [MR], West Region [WR], and Tibetan Plateau Region [TR]) were selected for the analysis. Overall, a significant but fluctuating increase in SO2 concentrations over China was observed during 1980–2021. During 1980–1997 and 2000–2010, there was an increase in SO2 concentration, while during 1997–2000 and 2010–2021, a decreasing trend was observed. The average increase in SO2 concentration was approximately 16 times higher in urban regions than in the rural background. We also found that SO2 dynamics were highly associated with expansion of urban areas, population density, and gross domestic product. Nonetheless, since 2007, SO2 concentrations have exhibited a downward trend, which is mainly attributed to the air pollution policies implemented by the Chinese government. Our findings highlight the need for further studies on the impact of SO2 on regional climate change in China.

Abstract Various environmental drivers influence life processes of insect vectors that transmit human disease. Life histories observed under experimental conditions can reveal such complex links; however, designing informative experiments for insects is challenging. Furthermore, inferences obtained under controlled conditions often extrapolate poorly to field conditions. Here, we introduce a pseudo-stage-structured population dynamics model to describe insect development as a renewal process with variable rates. The model permits representing realistic life stage durations under constant and variable environmental conditions. Using the model, we demonstrate how random environmental variations result in fluctuating development rates and affect stage duration. We apply the model to infer environmental dependencies from the life history observations of two common disease vectors, the southern (Culex quinquefasciatus) and northern (Culex pipiens) house mosquito. We identify photoperiod, in addition to temperature, as pivotal in regulating larva stage duration, and find that carefully timed life history observations under semi-field conditions accurately predict insect development throughout the year. The approach we describe augments existing methods of life table design and analysis, and contributes to the development of large-scale climate- and environment-driven population dynamics models for important disease vectors.

Most research on the air pollution-related health effects of decarbonization has focused on adults. We assess the potential health benefits that could be achieved in children and young people in a global sample of 16 cities through global decarbonization actions. We modelled annual average concentrations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) at 1x1 km resolution in the cities using a general circulation/atmospheric chemistry model assuming removal of all global combustion-related emissions from land transport, industries, domestic energy use and power generation. We modelled the impact on childhood asthma incidence and adverse birth outcomes (low birthweight, pre-term births) using published exposure–response relationships. Removal of combustion emissions was estimated to decrease annual average PM2.5 by between 2.9 μg/m3 (8.4%) in Freetown and 45.4 μg/m3 (63.7%) in Dhaka. For NO2, the range was from 0.3 ppb (7.9%) in Freetown to 18.8 ppb (92.3%) in Mexico City. Estimated reductions in asthma incidence ranged from close to zero in Freetown, Tamale and Harare to 149 cases per 100,000 population in Los Angeles. For pre-term birth, modelled impacts ranged from a reduction of 135 per 100,000 births in Dar es Salaam to 2,818 per 100,000 births in Bhubaneswar and, for low birthweight, from 75 per 100,000 births in Dar es Salaam to 2,951 per 100,000 births in Dhaka. The large variations chiefly reflect differences in the magnitudes of air pollution reductions and estimated underlying disease rates. Across the 16 cities, the reduction in childhood asthma incidence represents more than one-fifth of the current burden, and an almost 10% reduction in pre-term and low birthweight births. Decarbonization actions that remove combustion-related emissions contributing to ambient PM2.5 and NO2 would likely lead to substantial but geographically-varied reductions in childhood asthma and adverse birth outcomes, though there are uncertainties in causality and the precision of estimates.

Worldwide, up to 8.8 million excess deaths/year have been attributed to air pollution, mainly due to the exposure to fine particulate matter (PM). Traffic-related noise is an additional contributor to global mortality and morbidity. Both health risk factors substantially contribute to cardiovascular, metabolic and neuropsychiatric sequelae. Studies on the combined exposure are rare and urgently needed because of frequent co-occurrence of both risk factors in urban and industrial settings. To study the synergistic effects of PM and noise, we used an exposure system equipped with aerosol generator and loud-speakers, where C57BL/6 mice were acutely exposed for 3d to either ambient PM (NIST particles) and/or noise (aircraft landing and take-off events). The combination of both stressors caused endothelial dysfunction, increased blood pressure, oxidative stress and inflammation. An additive impairment of endothelial function was observed in isolated aortic rings and even more pronounced in cerebral and retinal arterioles. The increase in oxidative stress and inflammation markers together with RNA sequencing data indicate that noise particularly affects the brain and PM the lungs. The combination of both stressors has additive adverse effects on the cardiovascular system that are based on PM-induced systemic inflammation and noise-triggered stress hormone signaling. We demonstrate an additive upregulation of ACE-2 in the lung, suggesting that there may be an increased vulnerability to COVID-19 infection. The data warrant further mechanistic studies to characterize the propagation of primary target tissue damage (lung, brain) to remote organs such as aorta and heart by combined noise and PM exposure.

Visceral and cutaneous leishmaniases are important public health concerns in Cyprus. Although the diseases, historically prevalent on the island, were nearly eradicated by 1996, an increase in frequency and geographical spread has recently been recorded. Upward trends in leishmaniasis prevalence have largely been attributed to environmental changes that amplify the abundance and activity of its vector, the phlebotomine sand flies. Here, we performed an extensive field study across the island to map the sand fly fauna and compared the presence and distribution of the species found with historical records. We mapped the habitat preferences of Phlebotomus papatasi and P. tobbi, two medically important species, and predicted the seasonal abundance of P. papatasi at unprecedented spatiotemporal resolution using a climate-sensitive population dynamics model driven by high-resolution meteorological forecasting. Our compendium holds a record of 18 species and the locations of a subset, including those of potential public and veterinary health concern. We confirmed that P. papatasi is widespread, especially in densely urbanized areas, and predicted that its abundance uniformly peaks across the island at the end of summer. We identified potential hotspots of P. papatasi activity even after this peak. Our results form a foundation to inform public health planning and contribute to the development of effective, efficient, and environmentally sensitive strategies to control sand fly populations and prevent sand fly-borne diseases.

Meteorological station measurements are an important source of information for understanding the weather and its association with risk, and are vital in quantifying climate change. However, such data tend to lack spatial coverage and are often plagued with flaws such as erroneous outliers and missing values. Alternative meteorological data exist in the form of climate model output that have better spatial coverage, at the expense of bias. We propose a probabilistic framework to integrate temperature measurements with climate model (reanalysis) data, in a way that allows for biases and erroneous outliers, while enabling prediction at any spatial resolution. The approach is Bayesian which facilitates uncertainty quantification and simulation based inference, as illustrated by application to two countries from the Middle East and North Africa region, an important climate change hotspot. We demonstrate the use of the model in: identifying outliers, imputing missing values, non-linear bias correction, downscaling and aggregation to any given spatial configuration.

Climate models are fundamental tools for assessing historical climate conditions and projecting future ones. However, the results often differ systematically from observational data. The minimization of these differences is known as bias correction. The present study aims to correct the biases between observed daily precipitation values and the respective simulated ones from a EURO-CORDEX climate model. For this purpose, powerful statistical tools—generalized additive models (GAMs)—are used. GAMs are modified to adjust the simulated rainfall with the highest accuracy, and subsequently, they are evaluated by comparison with observational data. The method was applied to two eastern Mediterranean stations (Larissa in Greece and Larnaca in Cyprus) for the period 1981 to 2005. The results from both stations reveal that GAMs offer a valuable and accurate technique for the bias adjustment of daily precipitation.

Air pollution is an important environmental risk factor associated with increased morbidity and excess mortality. Fine particulate matter (PM2.5) is a complex mixture of both organic and inorganic compounds, depending on emissions sources and atmospheric chemistry. According to toxicological studies, there is strong evidence that anthropogenic carbonaceous aerosols, especially those emitted from combustion sources, are more hazardous to human health than other types of fine particles. In this study, we use WRF-Chem to simulate PM2.5 and the carbonaceous sub-components (black carbon and organics from anthropogenic sources) over Europe. The excess mortality attributed to long-term exposure to these particles is quantified using the MR-BRT (meta-Regression–Bayesian, regularized, trimmed) and the Global Exposure Mortality Model (GEMM) exposure–response functions to assess the public health outcomes. Differential toxicity of carbonaceous aerosols is assumed to account for their potentially more pronounced effect on excess mortality.

Abstract Global climate projections suggest a significant intensification of summer heat extremes in the Middle East and North Africa (MENA). To assess regional impacts, and underpin mitigation and adaptation measures, robust information is required from climate downscaling studies, which has been lacking for the region. Here, we project future hot spells by using the Heat Wave Magnitude Index and a comprehensive ensemble of regional climate projections for MENA. Our results, for a business-as-usual pathway, indicate that in the second half of this century unprecedented super- and ultra-extreme heatwave conditions will emerge. These events involve excessively high temperatures (up to 56 °C and higher) and will be of extended duration (several weeks), being potentially life-threatening for humans. By the end of the century, about half of the MENA population (approximately 600 million) could be exposed to annually recurring super- and ultra-extreme heatwaves. It is expected that the vast majority of the exposed population (>90%) will live in urban centers, who would need to cope with these societally disruptive weather conditions.

The Asian tiger mosquito, Aedes albopictus, is an important vector of arboviruses that cause diseases such as dengue, chikungunya, and zika. The vector is highly invasive and adapted to survive in temperate northern territories outside its native tropical and sub-tropical range. Climate and socio-economic change are expected to facilitate its range expansion and exacerbate the global vector-borne disease burden. To project shifts in the global habitat suitability of the vector, we developed an ensemble machine learning model, incorporating a combination of a Random Forest and XGBoost binary classifiers, trained with a global collection of vector surveillance data and an extensive set of climate and environmental constraints. We demonstrate the reliable performance and wide applicability of the ensemble model in comparison to the known global presence of the vector, and project that suitable habitats will expand globally, most significantly in the northern hemisphere, putting at least an additional billion people at risk of vector-borne diseases by the middle of the 21st century. We project several highly populated areas of the world will be suitable for Ae. albopictus populations, such as the northern parts of the USA, Europe, and India by the end of the century, which highlights the need for coordinated preventive surveillance efforts of potential entry points by local authorities and stakeholders.

Tick-borne diseases are among the challenges associated with warming climate. Many studies predict, and already note, expansion of ticks' habitats to the north, bringing previously non-endemic diseases, such as borreliosis and encephalitis, to the new areas. In addition, higher temperatures accelerate phases of ticks' development in areas where ticks have established populations. Earlier works have shown that meteorological parameters, such as temperature and humidity influence ticks' survival and define their areas of habitat. Here, we study the link between climatic parameters and tick-related hospital visits as well as borreliosis incidence rates focusing on European Russia. We have used yearly incidence rates of borreliosis spanning a period of 20 years (1997-2016) and weekly tick-related hospital visits spanning two years (2018-2019). We identify regions in Russia characterized by similar dynamics of incidence rates and dominating tick species. For each cluster, we find a set of climatic parameters that are significantly correlated with the incidence rates, though a linear regression approach using exclusively climatic parameters to incidence prediction was less than 50% effective. On a weekly timescale, we find correlations of different climatic parameters with hospital visits. Finally, we trained two long short-term memory neural network models to project the tick-related hospital visits until the end of the century, under the RCP8.5 climate scenario, and present our findings in the evolution of the tick season length for different regions in Russia. Our results show that the regions with an expected increase in both tick season length and borreliosis incidence rates are located in the southern forested areas of European Russia. Oppositely, our projections suggest no prolongation of the tick season length in the northern areas with already established tick population.

Chronic exposure to fine particulate matter (PM2.5) poses a major global health risk, commonly assessed by assuming equivalent toxicity for different PM2.5 constituents. We used a data-informed global atmospheric model and recent exposure–response functions to calculate the health burden of ambient PM2.5 from ten source categories. We estimate 4.23 (95% confidence interval 3.0–6.14) million excess deaths annually from the exposure to ambient PM2.5. We distinguished contributions and major sources of black carbon (BC), primary organic aerosols (POA) and anthropogenic secondary organic aerosols (aSOA). These components make up to ∼20% of the total PM2.5 in South and East Asia and East Africa. We find that domestic energy use by the burning of solid biofuels is the largest contributor to ambient BC, POA and aSOA globally. Epidemiological and toxicological studies indicate that these compounds may be relatively more hazardous than other PM2.5 compounds such as soluble salts, related to their high potential to inflict oxidative stress. We performed sensitivity analyses by considering these species to be more harmful compared to other compounds in PM2.5, as suggested by their oxidative potential using a range of potential relative risks. These analyses show that domestic energy use emerges as the leading cause of excess mortality attributable to ambient PM2.5, notably in Asia and Africa. We acknowledge the uncertainties inherent in our assumed enhanced toxicity of the anthropogenic organic and BC aerosol components, which suggest the need to better understand the mechanisms and magnitude of the associated health risks and the consequences for regulatory policies. However our assessment of the importance of emissions from domestic energy use as a cause of premature mortality is robust to a range of assumptions about the magnitude of the excess risk.

Global warming is anticipated to intensify the hydrological cycle. However, this is neither expected to be globally uniform nor is the relationship between temperature increase and rainfall intensities expected to be linear. The objective of this study is to assess changes in annual rainfall extremes, total annual precipitation, and their relationship in the larger Mediterranean region. We use an up-to-date ensemble of 33 regional climate simulations from the EURO-CORDEX initiative at 0.11° resolution. We analyse the significance of trends for 1951–2000 and 2001–2100 under a ‘business-as-usual’ pathway (RCP8.5). Our future projections indicate a strong north/south Mediterranean gradient, with significant, decreasing trends in the magnitude of daily precipitation extremes in the south and the Maghreb region (up to −10 mm/decade) and less profound, increasing trends in the north. Despite the contrasting future trends, the 50-year daily precipitation extremes are projected to strongly increase (up to 100%) throughout the region. The 100-year extremes, derived with traditional extreme value approaches from the 1951–2000 simulations, underestimate the magnitude of these extreme events in the 2001–2100 projections by 30% for the drier areas of the Mediterranean (200–500 mm average annual rainfall) and by up to 20–30% for the wetter parts of the region. These 100-year extremes can occur at any time in any Mediterranean location. The contribution of the wettest day per year to the annual total precipitation is expected to increase (5–30%) throughout the region. The projected increase in extremes and the strong reductions in mean annual precipitation in the drier, southern and eastern Mediterranean will amplify the challenges for water resource management.

Both exposure to higher levels of polluted air and physical inactivity are crucial risk factors for the development and progression of major noncommunicable diseases and, in particular, of cardiovascular disease. In this context, the World Health Organization estimated 4.2 and 3.2 million global deaths per year in response to ambient air pollution and insufficient physical activity, respectively. While regular physical activity is well known to improve general health, it may also increase the uptake and deposit of air pollutants in the lungs/airways and circulation, due to increased breathing frequency and minute ventilation, thus increasing the risk of cardiovascular disease. Thus, determining the tradeoff between the health benefits of physical activity and the potential harmful effects of increased exposure to air pollution during physical activity has important public health consequences. In the present comprehensive review, we analyzed evidence from human and animal studies on the combined effects of physical activity and air pollution on cardiovascular and other health outcomes. We further report on pathophysiological mechanisms underlying air pollution exposure, as well as the protective effects of physical activity with a focus on oxidative stress and inflammation. Lastly, we provide mitigation strategies and practical recommendations for physical activity in areas with polluted air.

The Unmanned Systems Research Laboratory (USRL) of the Cyprus Institute is a new mobile exploratory platform of the EU Research Infrastructure Aerosol, Clouds and Trace Gases Research InfraStructure (ACTRIS). USRL offers exclusive Unmanned Aerial Vehicle (UAV)-sensor solutions that can be deployed anywhere in Europe and beyond, e.g., during intensive field campaigns through a transnational access scheme in compliance with the drone regulation set by the European Union Aviation Safety Agency (EASA) for the research, innovation, and training. UAV sensor systems play a growing role in the portfolio of Earth observation systems. They can provide cost-effective, spatial in-situ atmospheric observations which are complementary to stationary observation networks. They also have strong potential for calibrating and validating remote-sensing sensors and retrieval algorithms, mapping close-to-the-ground emission point sources and dispersion plumes, and evaluating the performance of atmospheric models. They can provide unique information relevant to the short- and long-range transport of gas and aerosol pollutants, radiative forcing, cloud properties, emission factors and a variety of atmospheric parameters. Since its establishment in 2015, USRL is participating in major international research projects dedicated to (1) the better understanding of aerosol-cloud interactions, (2) the profiling of aerosol optical properties in different atmospheric environments, (3) the vertical distribution of air pollutants in and above the planetary boundary layer, (4) the validation of Aeolus satellite dust products by utilizing novel UAV-balloon-sensor systems, and (5) the chemical characterization of ship and stack emissions. A comprehensive overview of the new UAV-sensor systems developed by USRL and their field deployments is presented here. This paper aims to illustrate the strong scientific potential of UAV-borne measurements in the atmospheric sciences and the need for their integration in Earth observation networks.

Secondary organic aerosols (SOA) are important for climate and aerosol quality, but the phase state is unclear. Here, the authors show that SOA is liquid in tropical and polar air, semi-solid in the mid-latitudes, solid over dry lands and in a glassy solid phase state in the middle and upper troposphere.

This study assessed the aerosol climatology over Iran, based on the monthly data of aerosol optical depth (AOD) derived from the reanalysis-based Modern Era Retrospective Analysis for Research and Applications (MERRA-2) and the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS). In addition, sea level pressure, wind speed, temperature, relative humidity, precipitation, and soil moisture from the ERA5 reanalysis dataset were applied to investigate the climate-related effects on temporal AOD changes. Our analysis identified positive and negative AOD trends during 2000–2010 and 2010–2018, respectively, which are likely linked to aeolian dust changes. The dust-driven AOD trends were supported by changes in the Ångström exponent (AE) and fine mode fraction (FMF) of aerosols over Iran. During the early period (2000–2010), results of AOD-meteorology correlation analyses suggest reduced soil moisture, leading to increased dust emissions, whereas our results suggest that during the later period (2010–2018) an increase of soil moisture led to decreased AOD levels. Soil moisture appears to be a key factor in dust mobilization in the region, notably in southwestern Iran, being influenced by adjacent mineral dust sources. These phenomena were affected by large-scale sea level pressure transformations and the associated meteorology in the preceding winter seasons. Using a multiple linear regression model, AOD variability was linked to various meteorological factors in different regions. Our results suggest that climatic variations strongly affect the dust cycle, with a strong dependence on wintertime conditions in the region.

Pediatric asthma incidence has been associated with exposure to nitrogen dioxide (NO _2 ) in ambient air. NO _2 is predominantly emitted through fossil fuel use in land transportation, power generation and the burning of solid biofuels in households. We simulated NO _2 with a global atmospheric chemistry model, combined with a land use regression model, to estimate NO _2 exposure in all countries worldwide. The global asthma incidence among children and adolescents attributable to NO _2 was estimated by deriving an exposure-response function from a meta-analysis which included epidemiological studies from multiple countries, baseline incidence rates from the Global Burden of Disease and gridded population data. The sectoral contribution to pediatric asthma from NO _2 exposure (NO _2 -related asthma incidence: NINC) was estimated for different source categories to provide guidance to mitigation policies. We estimate 3.52 (2.1–6.0) million NINC per year globally, being about 14% of the total asthma incidence cases among children and adolescents. We find that emissions from land transportation are the leading contributor to NINC globally (∼44%), followed by the domestic burning of solid fuels (∼10.3%) and power generation from fossil fuels (∼8.7%). Biogenic emissions which are not anthropogenically induced may contribute ∼14% to the total NINC. Our results show large regional differences in source contributions, as the domestic burning of solid fuels is a main contributor to NINC in India and Nepal (∼25%), while emissions from shipping are the leading source in Scandinavian countries (∼40%), for example. While only 5% of all children and adolescents live in areas where NO _2 exceeds the WHO annual guideline of 21.25 ppb (40 μ g m ^−3 ) for NO _2 , about 90% of the NINC is found in regions that meet the WHO guideline, related to the uneven distribution of children and adolescents in the population. This suggests the need for stricter policies to reduce NO _2 exposure, and revisiting the current WHO guideline to reduce the health risks of children and adolescents.

We studied the contribution of coal-fired power plant (CPP) emissions (SO _2 and NO x ) to air pollution levels and annual excess mortality by cardiovascular and respiratory diseases in Europe, based on fine particulate matter (PM2.5) concentrations computed with a regional atmospheric chemistry-transport model. The health burden of European CPP emission-induced PM2.5, estimated with the Global Exposure Mortality Model, amounts to at least 16 800 (CI95 14 800–18 700) excess deaths per year over the European domain. We identified an underestimation of the emissions magnitude and correcting for it doubles CPP-attributed annual excess mortality to 33 900 (CI95 33 000–37 600) per year. Due to the non-linearity of exposure-responses, especially at relatively low concentrations, these estimates represent lower limits of possible health benefits for the EU-28 states. CPP emission phase-out would avoid 18 400 (CI95 16 000–20 500) excess deaths annually assuming background PM2.5 levels of 10 μ g m ^−3 , 25 500 (CI95 22 600–28 200) per year if pollution levels from other sources are reduced by 50% in parallel, and 105 900 (CI95 89 900–121 700) deaths by drastically reducing anthropogenic pollution from other sources to 2.4 μ g m ^−3 that represents the threshold for health impacts. Depending on the emission scenario, large health gains can be achieved from the phase-out of CPP emissions, which calls for coordinated air pollution control strategies at the European level.

Numerical models are being used for the simulation of recent climate conditions as well as future projections. Due to the complexity of the Earth’s climate system and processes occurring at sub-grid scales, model results often diverge from the observed values. Different methods have been developed to minimize such biases. In the present study, the recently introduced “triangular irregular networks (TIN)-Copula” method was used for the bias correction of modelled monthly total and extreme precipitation in Cyprus. The method was applied to a 15-year historical period and two future periods of the same duration. Precipitation time-series were derived from a 12-km resolution EURO-CORDEX regional climate simulation. The results show that the TIN-Copula method significantly reduces the positive biases between the model results and observations during the historical period of 1986–2000, for both total and extreme precipitation (>80%). However, the level of improvement differs temporally and spatially. For future periods, the model tends to project significantly higher total precipitation rates prior to bias correction, while for extremes the differences are smaller. The adjustments slightly affect the overall climate change signal, which tends to be enhanced after bias correction, especially for total precipitation and for the autumn period.

The objective of this analysis is to provide an up-to-date observation-based assessment of the evolution of temperature extremes in the Middle East–North Africa (MENA) region and evaluate the performance of global climate model simulations of the past four decades. A list of indices of temperature extremes, based on absolute level, threshold, percentile and duration is used, as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). We use daily near-surface air temperature (Tmax and Tmin) to derive the indices of extremes for the period 1980–2018 from: (i) re-analyses (ERA-Interim, MERRA-2) and gridded observational data (Berkeley Earth) and (ii) 18 CMIP5 model results combining historical (1950–2005) and scenario runs (2006–2018 under RCP 2.6, RCP 4.5 and RCP 8.5). The CMIP5 results show domain-wide strong, statistically significant warming, while the observation based ones are more spatially variable. The CMIP5 models capture the climatology of the hottest areas in the western parts of northern Africa and the Gulf region with the thewarmest day (TXx) > 46 °C and warmest night (TNx) > 33 °C. For these indices, the observed trends are about 0.3–0.4 °C/decade while they are 0.1–0.2 °C/decade stronger in the CMIP5 results. Overall, the modeled climate warming up to 2018, as reflected in the indices of temperature extremes is confirmed by re-analysis and observational data.

Exposure to ambient air pollution is a well-established determinant of health and disease. The Lancet Commission on pollution and health concludes that air pollution is the leading environmental cause of global disease and premature death. Indeed, there is a growing body of evidence that links air pollution not only to adverse cardiorespiratory effects but also to increased risk of cerebrovascular and neuropsychiatric disorders. Despite being a relatively new area of investigation, overall, there is mounting recent evidence showing that exposure to multiple air pollutants, in particular to fine particles, may affect the central nervous system (CNS) and brain health, thereby contributing to increased risk of stroke, dementia, Parkinson’s disease, cognitive dysfunction, neurodevelopmental disorders, depression and other related conditions. The underlying molecular mechanisms of susceptibility and disease remain largely elusive. However, emerging evidence suggests inflammation and oxidative stress to be crucial factors in the pathogenesis of air pollution-induced disorders, driven by the enhanced production of proinflammatory mediators and reactive oxygen species in response to exposure to various air pollutants. From a public health perspective, mitigation measures are urgent to reduce the burden of disease and premature mortality from ambient air pollution.

The Asian tropopause aerosol layer (ATAL) is characterized by enhanced aerosol concentrations in the Asian summer monsoon anticyclone in the upper troposphere and lower stratosphere at 13–18 km altitude. A growing body of evidence suggests that the aerosol enhancement is closely connected with deep convection during the monsoon. However, the origin of the aerosols is under debate, and the key factors that determine the ATAL variability remain poorly understood. We investigated the formation and dissipation mechanisms of the ATAL and the inter-annual variation from a dynamical viewpoint using satellite observations and meteorological reanalysis data from 2012 to 2018. We identified the northern Bay of Bengal and adjacent land area, where air pollution from the Indian subcontinent converges, as the major convection source area of aerosols to the ATAL. The spatial extent of the ATAL, represented by the mean attenuated scattering ratio from satellite measurements, appears to be related to a secondary circulation driven by the stratospheric quasi-biennial oscillation. The aerosols are not homogeneously distributed within the ATAL, and descending motion in the western part is found to play an important role in dissipation of the layer. These findings elucidate the ATAL dynamics and associated regional and global air pollution transports.

Exposure to ambient air pollution is a major global health risk factor. Using recently updated hazard ratio functions, we estimate that the global premature mortality burden attributable to ambient PM _2.5 and O _3 exposure increased by about 30% and 17%, respectively, from 2000 to 2015. We analyzed these trends in terms of tradeoffs between changes in baseline mortality, population size, age distribution and exposure. Global population growth alone increased the mortality burden by about 29% and 42% among adults and children, respectively. On the other hand, decreasing baseline mortality during the same period lowered the burden by about 18% and 55% among adults and children, respectively. In high-income countries, aging of the population contributed to increasing premature mortality, while in low-income countries, in Central and West Africa for example, the growing youth population reduced premature mortality. Our results show that improved air quality generally does not keep up with the increasing air pollution-associated disease burden in middle- and high-income countries. We conclude that improvements in health care that reduce baseline mortality along with air pollution mitigation strategies are needed to maximize benefits, and counter the growth and aging of the global population.

Summary: Background: WHO estimates that, in 2015, nearly 1 million children younger than 5 years died from lower respiratory tract infections (LRIs). Ambient air pollution has a major impact on mortality from LRIs, especially in combination with undernutrition and inadequate health care. We aimed to estimate mortality due to ambient air pollution in 2015, particularly in children younger than 5 years, to investigate to what extent exposure to this risk factor affects life expectancy in different parts of the world. Methods: Applying results from a recent atmospheric chemistry-general circulation model and health statistics from the WHO Global Health Observatory, combined in integrated exposure-response functions, we updated our estimates of mortality from ambient (outdoor) air pollution. We estimated excess deaths attributable to air pollution by disease category and age group, particularly those due to ambient air pollution-induced LRIs (AAP-LRIs) in childhood. Estimates are presented as excess mortality attributable to ambient air pollution and years of life lost (YLLs). To study recent developments, we calculated our estimates for the years 2010 and 2015. Findings: Overall, 4·55 million deaths (95% CI 3·41 million to 5·56 million) were attributable to air pollution in 2015, of which 727 000 deaths (573 000–865 000) were due to AAP-LRIs. We estimated that AAP-LRIs caused about 237 000 (192 000–277 000) excess child deaths in 2015. Although childhood AAP-LRIs contributed about 5% of air pollution-attributable deaths worldwide, they accounted for 18% of losses in life expectancy, equivalent to 21·5 million (17 million to 25 million) of the total 122 million YLLs due to ambient air pollution in 2015. The mortality rate from ambient air pollution was highest in Asia, whereas the per capita YLLs were highest in Africa. We estimated that in sub-Saharan Africa, ambient air pollution reduces the average life expectancy of children by 4–5 years. In Asia, all-age mortality increased by about 10% between 2010 and 2015, whereas childhood mortality from AAP-LRIs declined by nearly 30% in the same period. Interpretation: Most child deaths due to AAP-LRIs occur in low-income countries in Africa and Asia. A three-pronged strategy is needed to reduce the health effects of ambient air pollution in children: aggressive reduction of air pollution levels, improvements in nutrition, and enhanced treatment of air pollution-related health outcomes. Funding: None.

We estimate the contamination risks from the atmospheric dispersion of radionuclides released by severe nuclear power plant accidents using the ECHAM/Modular Earth Submodel System (MESSy) atmospheric chemistry (EMAC) atmospheric chemistry-general circulation model at high resolution (50 km). We present an overview of global risks and also a case study of nuclear power plants that are currently under construction, planned and proposed in the Eastern Mediterranean and Middle East, a region prone to earthquakes. We implemented continuous emissions from each location, making the simplifying assumption that all potential accidents release the same amount of radioactivity. We simulated atmospheric transport and decay, focusing on 137Cs and 131I as proxies for particulate and gaseous radionuclides, respectively. We present risk maps for potential surface layer concentrations, deposition and doses to humans from the inhalation exposure of 131I. The estimated risks exhibit seasonal variability, with the highest surface level concentrations of gaseous radionuclides in the Northern Hemisphere during winter.

Chikungunya is a viral disease transmitted to humans primarily via the bites of infected Aedes mosquitoes. The virus caused a major epidemic in the Indian Ocean in 2004, affecting millions of inhabitants, while cases have also been observed in Europe since 2007. We developed a stochastic spatiotemporal model of Aedes albopictus-borne chikungunya transmission based on our recently developed environmentally-driven vector population dynamics model. We designed an integrated modelling framework incorporating large-scale gridded climate datasets to investigate disease outbreaks on Reunion Island and in Italy. We performed Bayesian parameter inference on the surveillance data, and investigated the validity and applicability of the underlying biological assumptions. The model successfully represents the outbreak and measures of containment in Italy, suggesting wider applicability in Europe. In its current configuration, the model implies two different viral strains, thus two different outbreaks, for the two-stage Reunion Island epidemic. Characterisation of the posterior distributions indicates a possible relationship between the second larger outbreak on Reunion Island and the Italian outbreak. The model suggests that vector control measures, with different modes of operation, are most effective when applied in combination: adult vector intervention has a high impact but is short-lived, larval intervention has a low impact but is long-lasting, and quarantining infected territories, if applied strictly, is effective in preventing large epidemics. We present a novel approach in analysing chikungunya outbreaks globally using a single environmentally-driven mathematical model. Our study represents a significant step towards developing a globally applicable Ae. albopictus-borne chikungunya transmission model, and introduces a guideline for extending such models to other vector-borne diseases.

The study of water balance is considered here as a way to assess the performance of regional climate models and examine model uncertainty and as an approach to understanding regional hydrology, especially interactions between atmospheric and hydrological processes. We studied the atmospheric and terrestrial water balance over the Eastern Nile Basin (ENB) region using the weather research and forecasting (WRF) model. The model performance in simulating precipitation and surface air temperature is assessed by comparing the model output with the data from the Global Precipitation Climatology Center dataset for precipitation and from the University of Delaware for temperature. The results show that the simulated and observed values correlate well. In terms of water balance, the study region was found to be a sink for moisture, where the atmospheric convergence is negative during most of the time. Most of the precipitation originates from moisture fluxes from outside the domain, and the contribution of local evapotranspiration to precipitation is limited, with small values for the moisture recycling ratios year-round. The atmospheric moisture content does not show significant monthly or annual variation. The results indicate that the terrestrial water storage varies seasonally, with negative fluxes during most of the year, except June, July, and August, when most of the precipitation occurs.

Abstract Trace gas measurements from whole air samples collected weekly into glass flasks at background monitoring sites within the NOAA Global Greenhouse Gas Reference Network program (with most of the sites also being World Meteorological Organization (WMO) Global Atmospheric Watch (GAW) stations) were used to investigate the variability-lifetime relationship for site characterization and to estimate regional and seasonal OH concentrations. Chemical species considered include the atmospheric trace gases CO, H2, and CH4, as well as the non-methane hydrocarbons (NMHC) ethane (C2H6), propane (C3H8), i-butane (i-C4H10), and n-butane (n-C4H10). The correlation between atmospheric variability and lifetime was applied on a global scale spanning 42 sites with observations covering a period of 5 years. More than 50,000 individual flask measurement results were included in this analysis, making this the most extensive study of the variability-lifetime relationship to date. Regression variables calculated from the variability-lifetime relationship were used to assess the “remoteness” of sampling sites and to estimate the effect of local pollution on the measured distribution of atmospheric trace gases. It was found that this relationship yields reasonable results for description of the site remoteness and local pollution influences. Comparisons of seasonal calculated OH concentrations ([OH]) from the variability-lifetime relationships with six direct station measurements yielded variable agreement, with deviations ranging from ∼20% to a factor of ∼2–3 for locations where [OH] monitoring results had been reported. [OH] calculated from the variability-lifetime relationships was also compared to outputs from a global atmospheric model. Resutls were highly variable, with approximately half of the sites yielding agreement to within a factor of 2–3, while others showed deviations of up to an order of magnitude, especially during winter.

The Asian tiger mosquito, Aedes albopictus, is a highly invasive vector species. It is a proven vector of dengue and chikungunya viruses, with the potential to host a further 24 arboviruses. It has recently expanded its geographical range, threatening many countries in the Middle East, Mediterranean, Europe and North America. Here, we investigate the theoretical limitations of its range expansion by developing an environmentally-driven mathematical model of its population dynamics. We focus on the temperate strain of Ae. albopictus and compile a comprehensive literature-based database of physiological parameters. As a novel approach, we link its population dynamics to globally-available environmental datasets by performing inference on all parameters. We adopt a Bayesian approach using experimental data as prior knowledge and the surveillance dataset of Emilia-Romagna, Italy, as evidence. The model accounts for temperature, precipitation, human population density and photoperiod as the main environmental drivers, and, in addition, incorporates the mechanism of diapause and a simple breeding site model. The model demonstrates high predictive skill over the reference region and beyond, confirming most of the current reports of vector presence in Europe. One of the main hypotheses derived from the model is the survival of Ae. albopictus populations through harsh winter conditions. The model, constrained by the environmental datasets, requires that either diapausing eggs or adult vectors have increased cold resistance. The model also suggests that temperature and photoperiod control diapause initiation and termination differentially. We demonstrate that it is possible to account for unobserved properties and constraints, such as differences between laboratory and field conditions, to derive reliable inferences on the environmental dependence of Ae. albopictus populations.

In this study, we investigated the effects of grid and spectral nudging in regional hydroclimatic simulations over the Eastern Mediterranean climate change hot-spot. We performed year-long simulations for the hydrological year October 2001⁻September 2002 using the Weather Research and Forecasting (WRF) model at 12-km resolution, driven by the ERA-Interim reanalyses. Six grid and three spectral nudging options were tested using a number of model configurations. Due to the large uncertainty of regional observations, we compared the model with various satellite- and station-based meteorological datasets. The effect of nudging was tested for mean weather conditions and precipitation characteristics and extremes. For certain parts of the study domain, WRF was found to reproduce both aspects of rainfall over the Eastern Mediterranean reasonably well. Our findings highlighted that, for the WRF modeling system, nudging is critical for the simulation of rainfall; however, the application of interior constraint methods was found to have different impacts on various locations and climatic regimes. For the hyperarid parts of the domain, nudging did not improve the simulation of precipitation amounts (about 20% additional drying was introduced), while it added much value for the wetter rainfall regimes of the Eastern Mediterranean (corrections of about 30%). Improvements in the simulated precipitation were mostly introduced by spectral nudging; however, this option required significant computational resources. For these ERA-Interim-driven simulations, grid nudging that involves specific humidity within the planetary boundary layer is not recommended for the simulation of precipitation since it introduces dry biases up to 75⁻80%.

The assessment of health impacts associated with airborne particulate matter smaller than 2.5 μ m in diameter (PM _2.5 ) relies on aerosol concentrations derived either from monitoring networks, satellite observations, numerical models, or a combination thereof. When global chemistry-transport models are used for estimating PM _2.5 , their relatively coarse resolution has been implied to lead to underestimation of health impacts in densely populated and industrialized areas. In this study the role of spatial resolution and of vertical layering of a regional air quality model, used to compute PM _2.5 impacts on public health and mortality, is investigated. We utilize grid spacings of 100 km and 20 km to calculate annual mean PM _2.5 concentrations over Europe, which are in turn applied to the estimation of premature mortality by cardiovascular and respiratory diseases. Using model results at a 100 km grid resolution yields about 535 000 annual premature deaths over the extended European domain (242 000 within the EU-28), while numbers approximately 2.4% higher are derived by using the 20 km resolution. Using the surface (i.e. lowest) layer of the model for PM _2.5 yields about 0.6% higher mortality rates compared with PM _2.5 averaged over the first 200 m above ground. Further, the calculation of relative risks (RR) from PM _2.5 , using 0.1 μ g m ^−3 size resolution bins compared to the commonly used 1 μ g m ^−3 , is associated with ±0.8% uncertainty in estimated deaths. We conclude that model uncertainties contribute a small part of the overall uncertainty expressed by the 95% confidence intervals, which are of the order of ±30%, mostly related to the RR calculations based on epidemiological data.