Ozone modelling and mapping for risk assessment: An overview of different approaches for human and ecosystems health

Meteorological, chemical and biological evaluation of the coupled chemistry-climate WRF-Chem model from regional to urban scale. An impact-oriented application for human health

Extreme climatic conditions, like heat waves or cold spells, associated to high concentrations of air pollutants are responsible for a broad range of effects on human health. Consequently, in the recent years, the question on how urban and peri-urban forests may improve both air quality and surface climate conditions at city-scale is receiving growing attention by scientists and policymakers, with previous studies demonstrating how nature-based solutions (NBS) may contribute to reduce the risk of population to be exposed to high pollutant levels and heat stress, preventing, thus, premature mortality. In this study we present a new modeling framework designed to simulate air quality and meteorological conditions from regional to urban scale, allowing thus to assess the impacts of both air pollution and heat stress on human health at urban level. To assess the model reliability, we evaluated the model's performances in reproducing several relevant meteorological, chemical, and biological variables. Results show how our modeling system can reliably reproduce the main meteorological, chemical, and biological variables over our study areas, thus this tool can be used to estimate the impact of air pollution and heat stress on human health. As an example of application, we show how common heat stress and air pollutant indices used for human health protection change when computed from regional to urban scale for the cities of Florence (Italy) and Aix en Provence (France).

Estimation of plant pollution removal capacity based on intensive air quality measurements

This study investigated the role of present vegetation in improving air quality in Bucharest (Romania) by analyzing six years of air quality data (PM10 and NO2) from multiple monitoring stations. The target value for human health protection is regularly exceeded for PM10 and not for NO2 over time. Road traffic has substantially contributed (over 70%) to ambient PM10 and NO2 levels. The results showed high seasonal variations in pollutant concentrations, with a pronounced effect of vegetation in reducing PM10 and NO2 levels. Indeed, air quality improvements of 7% for PM10 and 25% for NO2 during the growing season were reported. By using Principal Component Analysis and pollution data subtraction methodology, we have disentangled the impact of vegetation on air pollution and observed distinct annual patterns, particularly higher differences in PM10 and NO2 concentrations during the warm season. Despite limitations such as a lack of full tree inventory for Bucharest and a limited number of monitoring stations, the study highlighted the efficiency of urban vegetation to mitigate air pollution.

Differential responses and mechanisms of monoterpene emissions from broad-leaved and coniferous species under elevated ozone scenarios

Although ozone (O3) pollution affects plant growth and monoterpene (MT) emissions, the responses of MT emission rates to elevated O3 and the related mechanisms are not entirely understood. To gain an insight into these effects and mechanisms, we evaluated physiological (leaf MT synthesis ability, including precursor availability and enzyme kinetics) and physicochemical limiting factors (e.g. leaf thickness of the lower and upper epidermis, palisade and spongy tissue, and size of resin ducts and stomatal aperture) affecting MT emissions simultaneously from two broad-leaved and two coniferous species after one growing season of field experiment. The effects of elevated O3 on MT emissions and the related mechanisms differed between plant functional types. Specifically, long-term moderate O3 exposure significantly reduced MT emissions in broad-leaved species, primarily attributed to a systematic decrease in MT synthesis ability, including reductions in all MT precursors, geranyl diphosphate content, and MT synthase protein levels. In contrast, the same O3 exposure significantly enhanced MT emissions in coniferous species. However, the change in MT emissions in coniferous species was not due to modifications in leaf MT synthesis ability but rather because of alterations in leaf anatomical structure characteristics, particularly the size of resin ducts and stomatal aperture. These findings provide an important understanding of the mechanisms driving MT emissions from different tree functional groups and can enlighten the estimation of MT emissions in the context of O3 pollution scenarios as well as the development of MT emission algorithms.

Stand age diversity (and more than climate change) affects forests' resilience and stability, although unevenly

Stand age significantly influences the functioning of forest ecosystems by shaping structural and physiological plant traits, affecting water and carbon budgets. Forest age distribution is determined by the interplay of tree mortality and regeneration, influenced by both natural and anthropogenic disturbances. Unfortunately, human-driven alteration of tree age distribution presents an underexplored avenue for enhancing forest stability and resilience. In our study, we investigated how age impacts the stability and resilience of the forest carbon budget under both current and future climate conditions. We employed a state-of-the-science biogeochemical, biophysical, validated process-based model on historically managed forest stands, projecting their future as undisturbed systems, i.e., left at their natural evolution with no management interventions (i.e., forests are left to develop undisturbed). Such a model, forced by climate data from five Earth System Models under four representative climate scenarios and one baseline scenario to disentangle the effect of climate change, spanned several age classes as representative of the current European forests' context, for each stand. Our findings indicate that Net Primary Production (NPP) peaks in the young and middle-aged classes (16- to 50-year-old), aligning with longstanding ecological theories, regardless of the climate scenario. Under climate change, the beech forest exhibited an increase in NPP and maintained stability across all age classes, while resilience remained constant with rising atmospheric CO2 and temperatures. However, NPP declined under climate change scenarios for the Norway spruce and Scots pine sites. In these coniferous forests, stability and resilience were more influenced. These results underscore the necessity of accounting for age class diversity -lacking in most, if not all, the current Global Vegetation Models - for reliable and robust assessments of the impacts of climate change on future forests' stability and resilience capacity. We, therefore, advocate for customized management strategies that enhance the adaptability of forests to changing climatic conditions, taking into account the diverse responses of different species and age groups to climate.

Machine-learning-based corrections of CMIP6 historical surface ozone in China during 1950-2014

Due to a lack of long-term observations in China, reports on historical ozone concentration are severely limited. In this study, by combining observation, reanalysis and model simulation data, XGBoost machine learning algorithm is used to correct the surface ozone concentration from CMIP6 climate model, and the long-term and large-scale surface ozone concentration of China during 1950-2014 is obtained. The long-term evolutions and trends of ozone and meteorological effects on interannual ozone variations are further analyzed. The results reveal that CMIP6 historical simulations have a large underestimation in ozone concentrations and their trends. The XGB-derived ozone are closer to observations, with R2 value of 0.66 and 0.74 for daily and monthly retrievals, respectively. Both the concentrations and exceedances of ozone in most parts of China have shown increasing trends from 1950 to 2014. The daily mean ozone concentration without climate change effects is estimated to be 117 ppb in the year 1950 averaged over China. It indicates that the increase in anthropogenic emissions of China has a significant contribution to ozone enhancement between 1950 and 2014. The higher ozone growth rates of XGB retrievals than those from the model indicate a regional surface ozone penalty due to the warming climate. The relatively significant increment in ozone are estimated in the Central and Western China. Seasonally, the ozone enhancement is largest in spring, indicating a shift in seasonal variation of ozone. Given the uncertainty in simulating historical ozone by climate model, we show that machine learning approaches can provide improved assessment of evolution in surface ozone, along with valuable information to guide future model development and formulate future ozone pollution prevention and control policies.

Population exposure to multiple air pollutants and its compound episodes in Europe

Air pollution remains as a substantial health problem, particularly regarding the combined health risks arising from simultaneous exposure to multiple air pollutants. However, understanding these combined exposure events over long periods has been hindered by sparse and temporally inconsistent monitoring data. Here we analyze daily ambient PM2.5, PM10, NO2 and O3 concentrations at a 0.1-degree resolution during 2003-2019 across 1426 contiguous regions in 35 European countries, representing 543 million people. We find that PM10 levels decline by 2.72% annually, followed by NO2 (2.45%) and PM2.5 (1.72%). In contrast, O3 increase by 0.58% in southern Europe, leading to a surge in unclean air days. Despite air quality advances, 86.3% of Europeans experience at least one compound event day per year, especially for PM2.5-NO2 and PM2.5-O3. We highlight the improvements in air quality control but emphasize the need for targeted measures addressing specific pollutants and their compound events, particularly amidst rising temperatures.

A bibliometric analysis of research on the health impacts of ozone air pollution

Ground-level ozone (O3) is one of the major air pollutants. A large body of literature has linked O3 air pollution to various adverse human health effects. The objective of this study is to attain a comprehensive and in-depth understanding of the progress and frontiers of research on O3 and human health. We used bibliometric methods to summarize publications on O3 air pollution and public health between 1990 and 2022 obtained from the Web of Science Core Collection database. VOSviewer and R software were used for bibliometric analysis and visualization. A total of 4501 relevant papers were included in the analysis. There has been a significant increase in the number of publications since 2013, with the USA being the major contributor, followed by China and England. Harvard University was the most prolific research institution, followed by the US Environmental Protection Agency and the University of North Carolina System. Professor Joel Schwartz was the most published author and has established a complex network of national and international collaborations. Co-occurrence analysis of keywords suggested evolving research hotspots, from toxicological studies to population-based epidemiological studies and from the respiratory system to the extra-pulmonary system. Research on O3 and its human health effects has progressed rapidly over the past few decades, but academic disparities still persist between developed and developing countries. There is an urgent need to strengthen international cooperation to address the public health challenges posed by rising O3 air pollution in the future.

Spatiotemporal patterns of surface ozone exposure inequality in China

Rising surface ozone (O3) levels in China are increasingly emphasizing the potential threats to public health, ecological balance, and economic sustainability. Using a 1 km × 1 km dataset of O3 concentrations, this research employs subpopulation demographic data combined with a population-weighted quality model. Its aim is to evaluate quantitatively the differences in O3 exposure among various subpopulations within China, both at a provincial and urban cluster level. Additionally, an exposure disparity indicator was devised to establish unambiguous exposure risks among significant urban agglomerations at varying O3 concentration levels. The findings reveal that as of 2018, the population-weighted average concentration of O3 for all subgroups has experienced a significant uptick, surpassing the average O3 concentration (118 μg/m3). Notably, the middle-aged demographic exhibited the highest O3 exposure level at 135.7 μg/m3, which is significantly elevated compared to other age brackets. Concurrently, there exists a prominent positive correlation between educational attainment and O3 exposure levels, with the medium-income bracket showing the greatest susceptibility to O3 exposure risks. From an industrial vantage point, the secondary sector demographic is the most adversely impacted by O3 exposure. In terms of urban-rural structure, urban groups in all regions had higher levels of exposure to O3 than rural areas, with North and East China having the most significant levels of exposure. These findings not only emphasize the intricate interplay between public health and environmental justice but further highlight the indispensability of segmented subgroup strategies in environmental health risk assessment. Moreover, this research furnishes invaluable scientific groundwork for crafting targeted public health interventions and sustainable air quality management policies.

Ozone spectroscopy in the terahertz range from first high-resolution Synchrotron SOLEIL experiments combined with far-infrared measurements and ab initio intensity calculations

Ozone is one of the important molecules in terms of the impact on the atmospheric chemistry, climate changes, bio- and eco-systems and human health. It has a strong absorption in the microwave, terahertz and far-infrared spectral ranges where a large part of the Earth's outgoing longwave radiation to space is located. In this work, the observations, and analyses of the ozone high-resolution spectra in the THz range recorded using the Synchrotron light source of the SOLEIL CNRS equipment are reported for the first time. Thanks to the exceptional brightness of the Synchrotron radiation and to the signal/noise ratio, it was possible to observe many more ozone transitions of the cold rotational band and the hot ν2-ν2 band in the range 0.9-6 THz compared to the previous works. In addition, we have carried out new measurements and assignments for the ν2 band. The simultaneous fit of the rotational band GS-GS, the hot band ν2-ν2 and the FIR ν2 band yielded an overall weighted standard deviation of 0.68 for 13,466 line positions within the experimental accuracy. This includes all previously available MW (with the best uncertainty 0.1 - 10 kHz), FIR data and the original SOLEIL measurements that provided experimental accuracy of 0.00005 - 0.0001 cm-1 for the best lines. Significant deviations in new experimental spectra compared to available spectroscopic databases were evidenced, particularly for the line positions and energy levels at high J, Ka rotational quantum numbers that are the most pronounced in the 4.5 - 6 THz range. Accurate ab initio calculations of line intensities combined with empirically fitted line positions were used to create new linelists that permit theoretical modelling of the transmittance in a good agreement with the Synchrotron spectra in the entire range of observations for various pressures and optical paths. The region near 100 cm-1 and above appears to be more sensitive to the temperature conditions that should be considered in atmospheric observation for the currently operational and future ground based and space missions.

Assessing the effect of COVID-19 pandemic on air quality change and human health outcomes in a capital city, southwestern Iran

The aimsof this study were to assess the spatial variation of PM2.5, NO2, and O3 between 2019 (before) and 2020 (during COVID-19 pandemic); and calculation the health outcomes of exposure to these pollutants. The daily PM2.5, NO2, and O3 concentrations were applied to assess health effects by relative risk, and baseline incidence. The annual PM2.5 and NO2 mean concentrations exceeded the WHO guideline values, while O3 did not exceed. The restrictive measures associated to COVID-19 led to reduction at the annual means of PM2.5 and NO2 by -25.5% and -23.1%, respectively, while the annual mean of O3 increased by +7.9%. The number of M-CVD and M-RD (-25.6%, -26.1%) related to PM2.5 exposure, and HA-COPD and HA-RD >65 years old (-21% and -3.84%) related to NO2 exposure were reduced in 2020, and O3 exposure-related M-CVD (+30.1%) and HA-RD >65 years old (+23.4%) increased compared to the previous year 2019.

Effect of ozone stress on crop productivity: A threat to food security

Tropospheric ozone (O3), the most important phytotoxic air pollutant, can deteriorate crop quality and productivity. Notably, satellite and ground-level observations-based multimodel simulations demonstrate that the present and future predicted O3 exposures could threaten food security. Hence, the present study aims at reviewing the phytotoxicity caused by O3 pollution, which threatens the food security. The present review encompasses three major aspects; wherein the past and prevailing O3 concentrations in various regions were compiled at first, followed by discussing the physiological, biochemical and yield responses of economically important crop species, and considering the potential of O3 protectants to alleviate O3-induced phytotoxicity. Finally, the empirical data reported in the literature were quantitatively analysed to show that O3 causes detrimental effect on physiological traits, photosynthetic pigments, growth and yield attributes. The review on prevailing O3 concentrations over various regions, where economically important crop are grown, and their negative impact would support policy makers to implement air pollution regulations and the scientific community to develop countermeasures against O3 phytotoxicity for maintaining food security.

Analysis of severe ozone-related human health and weather influence over China in 2019 based on a high-resolution dataset

Ozone pollution in 2019 in China is particularly severe posing a tremendous threat to the health of Chinese inhabitants. In this study, we constructed a more reliable and accurate 1-km gridded dataset for 2019 with as many sites as possible using the inverse distance weight interpolation method to analyze spatiotemporal ozone pollution characteristics and health burden attributed to ozone exposure from the perspective of different diseases and weather influence. The accuracy of this new dataset is higher than other public datasets, with the coefficient of determination of 0.84 and root-mean-square error of 8.77 ppb through the validation of 300 external sites which were never used for establishing retrieval methods by the datasets mentioned-above. The averaged MDA8 (the daily maximum 8 h average) ozone concentrations over China was 43.5 ppb, and during April-July, 83.9% of total grids occurred peak-month ozone concentrations. Overall, the highest averaged exceedance days (60 days) and population-weighted ozone concentrations (55.0 ppb) both concentrated in central-eastern China including 9 provinces (only 11.4% of the national territory); meanwhile, all-cause premature deaths attributable to ozone exposure reached up to 142,000 (54.9% of national total deaths) with higher deaths for cardiovascular and respiratory, and the provincial per capita premature mortality was 0.27~0.44‰. The six most polluted weather types in the central-eastern China are in order as follows: westerly (SW and W), cyclonic, northerly, and southerly (NW, N, and S) types, which accounts for approximately 73.2% of health burden attributed to daily ozone exposure and poses the greatest public health risk with mean daily premature deaths ranging from 466 to 610. Our findings could provide an effective support for regional ozone pollution control and public health management in China.

Surface ozone risk to human health and vegetation in tropical region: The case of Thailand

Tropospheric ozone (O3) is a threat to vegetation and human health over the world, in particular in Asia. Knowledge on O3 impacts on tropical ecosystems is still very limited. An O3 risk assessment to crops, forests, and people from 25 monitoring stations across the tropical and subtropical Thailand during 2005-2018 showed that 44% of sites exceeded the critical levels (CLs) of SOMO35 (i.e., the annual Sum Of daily maximum 8-h Means Over 35 ppb) for human health protection. The concentration-based AOT40 CL (i.e., sum of the hourly exceedances above 40 ppb for daylight hours during the assumed growing season) was exceeded at 52% and 48% of the sites where the main crops rice and maize are present, respectively, and at 88% and 12% of the sites where evergreen or deciduous forests are present, respectively. The flux-based metric PODY (i.e., Phytotoxic Ozone Dose above a threshold Y of uptake) was calculated and was found to exceed the CLs at 1.0%, 1.5%, 20.0%, 1.5%, 0% and 68.0% of the sites where early rice, late rice, early maize, late maize, evergreen forests, and deciduous forests can grow, respectively. Trend analysis indicated that AOT40 increased over the study period (+5.9% year-1), while POD1 decreased (- 5.3% year-1), suggesting that the role of climate change in affecting the environmental factors that control stomatal uptake cannot be neglected. These results contribute novel knowledge on O3 threat to human health, forest productivity, and food security in tropical and subtropical areas.

Machine learning model to predict vehicle electrification impacts on urban air quality and related human health effects

Air pollution is a prevailing environmental problem in cities worldwide. The future vehicle electrification (VE), which in Europe will be importantly fostered by the ban of thermal engines from 2035, is expected to have an important effect on urban air quality. Machine learning models represent an optimal tool for predicting changes in air pollutants concentrations in the context of future VE. For the city of Valencia (Spain), a XGBoost (eXtreme Gradient Boosting package) model was used in combination with SHAP (SHapley Additive exPlanations) analysis, both to investigate the importance of different factors explaining air pollution concentrations and predicting the effect of different levels of VE. The model was trained with 5 years of data including the COVID-19 lockdown period in 2020, in which mobility was strongly reduced resulting in unprecedent changes in air pollution concentrations. The interannual meteorological variability of 10 years was also considered in the analyses. For a 70% VE, the model predicted: 1) improvements in nitrogen dioxide pollution (-34% to -55% change in annual mean concentrations, for the different air quality stations), 2) a very limited effect on particulate matter concentrations (-1 to -4% change in annual means of PM_2.5 and PM₁₀), 3) heterogeneous responses in ground-level ozone concentrations (-2% to +12% change in the annual means of the daily maximum 8-h average concentrations). Even at a high VE increase of 70%, the 2021 World Health Organization Air Quality Guidelines will be exceeded for all pollutants in some stations. VE has a potentially important impact in terms of reducing NO₂-associated premature mortality, but complementary strategies for reducing traffic and controlling all different air pollution sources should also be implemented to protect human health.

Assessment of rice yield and economic losses caused by ground-level O3 exposure in the Mekong delta region, Vietnam

The Lower Mekong Delta region (LMD) accounts for 90% of Vietnam's rice exports; however, the air quality in the LMD is remarkably reduced by ground-level ozone (O₃) pollution. This study aimed to quantify the relative yield and economic value losses in rice-growing crop seasons affected by ground-level O₃ concentrations across the LMD. The results of this study can serve as a basis for extensive assessments for the following years and support environmental managers to propose control measures of O₃ precursor emissions (NO_x and VOCs) from man-made sectors, as well as build protective solutions for rice farming in LMD. Two ground-level O₃ exposure metrics of M7 and AOT40 reflecting ground-level O₃ pollution impacts, combined with the model of exposure-relative yield relationship (or surface O₃-crop models), were used to assess losses of crop production (CPL) and economic cost losses (ECL) caused by rice crop yield reductions. For the M7 metric of ground-level O₃ exposure, the average value was 14.746 ppbV, with levels ranging from 13.959 ppbV to 15.502 ppbV, and the affected area was spread across 1309.39 thousand hectares. The AOT40 exposure metric reached an average value of 11.490 ppbV, with a range of 0.000-31.665 ppbV. The highest exposure level was 17.503-31.653 ppbV, covering an area of 747.01 thousand hectares. The total CPL of the three rice crops over the LMD was 9593.52 tonnes (accounting for 0.039% of the total value of rice production in the region), with a total corresponding EPL of 62.405 billion VND (equivalent to 2761.01 thousand USD). The results are considered a baseline study to serve as a basis for extensive assessments for the following years and support for the environmental managers to propose control measures of O₃ precursor emissions (NO_x and VOCs) from man-made sectors as well as build protective solutions in rice farming in LMD shortly.

Estimates of biomass reductions of ozone sensitive herbaceous plants in California

Exposure to tropospheric ozone pollution impairs photosynthesis and growth in plants and this can have consequences for ecosystems. However, exposure-response research in the United States (U.S.) has historically focused on trees and crops, and less attention has been given to non-crop herbaceous species. We combined U.S. Environmental Protection Agency ozone monitoring data from the entirety of 2016 with published exposure-response relationships from controlled exposure experiments for twenty herbaceous plant species occurring in California. The U.S. Department of Agriculture PLANTS database was used to identify county-level occurrence data of these plant species. A kriged ozone exposure surface for 2016 was generated using data from monitoring stations in California and surrounding states, using Accumulated Ozone exposure over a Threshold of 40 ppb (AOT40) as an exposure metric. County-wide ozone exposure estimations were then combined with published exposure response functions for focal plants, and maps were created to estimate ozone-induced growth losses in the counties where the plants occur. Plant species had estimated annual growth losses from <1 % to >20 % based on exposure levels and sensitivity. Of the 20 species, 17 had predicted biomass loss >5 % in at least one county, emphasizing the vulnerability of herbaceous species at recent ozone concentrations. Butte, Nevada, Plumas, San Luis Obispo, and Shasta Counties, an area of about 31,652 km2, had the highest number of species (6) with >10 % estimated biomass loss, the loss threshold for European critical levels. White clover (Trifolium repens L.) was one of the most affected species with more than an estimated 10 % annual estimated growth loss over 59 % of the state. Overall, these estimated growth losses demonstrate potential for shifts in plant communities and negative effects on ecosystems. This study addresses critical policy needs for risk assessments on herbaceous species in a single year of ozone exposure.

Increases in ozone-related mortality in China over 2013-2030 attributed to historical ozone deterioration and future population aging

We systematically examine historical and future changes in premature respiratory mortalities attributable to ozone (O₃) exposure (O₃-mortality) in China and identify the leading cause of respective change for the first time. The historical assessment for 2013-2019 is based on gridded O₃ concentrations generated by a multi-source-data-fusion algorithm; the future prediction for 2019-2030 uses gridded O₃ concentrations projected by four Coupled Model Intercomparison Project Phase 6 (CMIP6) models under three Shared Socioeconomic Pathways (SSP) scenarios. During 2013-2019, national annual O₃-mortality is 176.3 thousand (95%CI: 123.5-224.0 thousand) averaged over 2013-2019 with an increasing trend of 14.1 thousand yr^-1 (95%CI: 10.2-17.4 thousand yr^-1); sensitivity experiments show that the O₃-mortality varies at a rate of +12.7 (95%CI: 9.2-15.6), +5.8 (95%CI: 4.0-7.4), +1.0 (95%CI: 0.7-1.2), -5.4 (95%CI: -6.9 to -3.7) thousand yr^-1, owing to changes in O₃ concentration, population age structure, population size, mortality rate for respiratory disease, respectively. The deterioration of O₃ air quality, shown as significant increase in O₃ concentration, is identified as the primary factor which contributes 90.1 % of 2013-2019 O₃-mortality rise. Compared with O₃-mortality estimated in this study, the widely-used O₃-mortality assessment method based on urban-site-dominant O₃ measurements generates close national O₃-mortality but overestimates (underestimates) provincial O₃-mortality in coastal (central) provinces. From 2019 to 2030, national O₃-mortality is projected to increase by 50.4-103.7 thousand under different SSP scenarios. The change in age structure (i.e. population aging) alone will result in significant O₃-mortality rises of 137.9-160.5 thousand. Compared with 2013-2019 rapid O₃ increase (+2.5 μg m^-3 yr^-1 at national level), O₃ concentrations are projected to increase at a lower rate (+0.4 μg m^-3 yr^-1 in SSP5-8.5) or even decrease (-0.7 μg m^-3 yr^-1 in SSP1-2.6) from 2019 to 2030. Therefore, population aging, in place of O₃ air quality deterioration, will become the leading cause of future O₃-mortality rises during the coming decade.

Trends in urban air pollution over the last two decades: A global perspective

Ground-level ozone (O₃), fine particles (PM_2.5), and nitrogen dioxide (NO₂) are the most harmful urban air pollutants regarding human health effects. Here, we aimed at assessing trends in concurrent exposure of global urban population to O₃, PM_2.5, and NO₂ between 2000 and 2019. PM_2.5, NO₂, and O₃ mean concentrations and summertime mean of the daily maximum 8-h values (O₃ MDA8) were analyzed (Mann-Kendall test) using data from a global reanalysis, covering 13,160 urban areas, and a ground-based monitoring network (Tropospheric Ozone Assessment Report), collating surface O₃ observations at nearly 10,000 stations worldwide. At global scale, PM_2.5 exposures declined slightly from 2000 to 2019 (on average, - 0.2 % year^-1), with 65 % of cities showing rising levels. Improvements were observed in the Eastern US, Europe, Southeast China, and Japan, while the Middle East, sub-Saharan Africa, and South Asia experienced increases. The annual NO₂ mean concentrations increased globally at 71 % of cities (on average, +0.4 % year^-1), with improvements in North America and Europe, and increases in exposures in sub-Saharan Africa, Middle East, and South Asia regions, in line with socioeconomic development. Global exposure of urban population to O₃ increased (on average, +0.8 % year^-1 at 89 % of stations), due to lower O₃ titration by NO. The summertime O₃ MDA8 rose at 74 % of cities worldwide (on average, +0.6 % year^-1), while a decline was observed in North America, Northern Europe, and Southeast China, due to the reduction in precursor emissions. The highest O₃ MDA8 increases (>3 % year^-1) occurred in Equatorial Africa, South Korea, and India. To reach air quality standards and mitigate outdoor air pollution effects, actions are urgently needed at all governance levels. More air quality monitors should be installed in cities, particularly in Africa, for improving risk and exposure assessments, concurrently with implementation of effective emission control policies that will consider regional socioeconomic imbalances.

Ambient PM2.5 and O3 pollution and health impacts in Iranian megacity

The main objectives of this study were to (i) assess variation within fine particles (PM_2.5) and tropospheric ozone (O₃) time series in Khorramabad (Iran) between 2019 (before) and 2020 (during COVID-19 pandemic); (ii) assess relationship between PM_2.5 and O₃, the PM_2.5/O₃ ratio, and energy consumption; and (iii) estimate the health effects of exposure to ambient PM_2.5 and O₃. From hourly PM_2.5 and O₃ concentrations, we applied both linear-log and integrated exposure-response functions, city-specific relative risk, and baseline incidence values to estimate the health effects over time. A significant correlation was found between PM_2.5 and O₃ (r =-0.46 in 2019, r =-0.55 in 2020, p < 0.05). The number of premature deaths for all non-accidental causes (27.5 and 24.6), ischemic heart disease (7.3 and 6.3), chronic obstructive pulmonary disease (17 and 19.2), and lung cancer (9.2 and 6.25) attributed to ambient PM_2.5 exposure and for respiratory diseases (4.7 and 5.4) for exposure to O₃ above 10 µg m^-3 for people older than 30-year-old were obtained in 2019 and 2020. The number of years of life lost declined by 11.6% in 2020 and exposure to PM_2.5 reduced the life expectancy by 0.58 and 0.45 years, respectively in 2019 and 2020. Compared to 2019, the restrictive measures associated to COVID-19 pandemic led to reduction in PM_2.5 (-25.5%) and an increase of O₃ concentration (+ 8.0%) in Khorramabad.

Increased tropospheric ozone levels as a public health issue during COVID-19 lockdown and estimation the related pulmonary diseases

The aims of this study were to i) investigate the variation of tropospheric ozone (O₃) levels during the COVID-19 lockdown; ii) determine the relationships between O₃ concentrations with the number of COVID-19 cases; and iii) estimate the O₃-related health effects in Southwestern Iran (Khorramabad) over the time period 2019-2021. The hourly O₃ data were collected from ground monitoring stations, as well as retrieved from Sentinel-5 satellite data for showing the changes in O₃ levels pre, during, and after lockdown period. The concentration-response function model was applied using relative risk (RR) values and baseline incidence (BI) to assess the O₃-related health effects. Compared to 2019, the annual O₃ mean concentrations increased by 12.2% in 2020 and declined by 3.9% in 2021. The spatiotemporal changes showed a significant O₃ increase during COVID-19 lockdown, and a negative correlation between O₃ levels and the number of COVID-19 cases was found (r = - 0.59, p < 0.05). In 2020, the number of hospital admissions for cardiovascular diseases increased by 4.0 per 10⁵ cases, the mortality for respiratory diseases increased by 0.7 per 10⁵ cases, and the long-term mortality for respiratory diseases increased by 0.9 per 10⁵ cases. Policy decisions are now required to reduce the surface O₃ concentrations and O₃-related health effects in Iran.

COVID-19 Outbreak Related to PM10, PM2.5, Air Temperature and Relative Humidity in Ahvaz, Iran

In this study, we assessed several points related to the incidence of COVID-19 between March 2020 and March 2021 in the Petroleum Hospital of Ahvaz (Iran) by analyzing COVID-19 data from patients referred to the hospital. We found that 57.5% of infected referrals were male, 61.7% of deaths by COVID-19 occurred in subjects over 65 years of age, and only 2.4% of deaths occurred in younger subjects (< 30 years old). Analysis showed that mean PM₁₀ and PM_2.5 concentrations were correlated to the incidence of COVID-19 (r = 0.547, P < 0.05, and r = 0.609, P < 0.05, respectively) and positive chest CT scans (r = 0.597, P < 0.05, and r = 0.541, P < 0.05 respectively). We observed that a high daily air temperature (30–51 °C) and a high relative humidity (60–97%) led to a significant reduction in the daily incidence of COVID-19. The highest number of positive chest CT scans were obtained in June 2020 and March 2021 for daily air temperature ranging from 38 °C and 49 °C and 11 °C and 15 °C, respectively. A negative correlation was detected between COVID-19 cases and air temperature (r =  − 0.320, P < 0.05) and relative humidity (r =  − 0.384, P < 0.05). In Ahvaz, a daily air temperature of 10–28 °C and relative humidity of 19–40% are suitable for the spread of coronavirus. The highest correlation with the number of COVID-19 cases was found at lag3 (r = 0.42) and at lag0 with a positive chest CT scan (r = 0.56). For air temperature and relative humidity, the highest correlations were found at day 0 (lag0). During lockdown (22 March to 21 April 2020), a reduction was observed for PM₁₀ (29.6%), PM_2.5 (36.9%) and the Air Quality Index (33.3%) when compared to the previous month. During the pandemic period (2020–2021), the annual mean concentrations of PM₁₀ (27.3%) and PM_2.5 (17.8%) were reduced compared to the 2015–2019 period.