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Ozone modelling and mapping for risk assessment: An overview of different approaches for human and ecosystems health
Abstract
Tropospheric ozone (O3) is one of the most concernedair pollutants dueto its widespread impacts on land vegetated ecosystems and human health. Ozone is also the third greenhouse gas for radiative forcing. Consequently, it should be carefully and continuously monitored to estimate its potential adverse impacts especially inthose regions where concentrations are high. Continuous large-scale O3 concentrations measurement is crucial but may be unfeasible because of economic and practical limitations; therefore, quantifying the real impact of O3over large areas is currently an open challenge. Thus, one of the final objectives of O3 modelling is to reproduce maps of continuous concentrations (both spatially and temporally) and risk assessment for human and ecosystem health. We here reviewedthe most relevant approaches used for O3 modelling and mapping starting from the simplest geo-statistical approaches andincreasing in complexity up to simulations embedded into the global/regional circulation models and pro and cons of each mode are highlighted. The analysis showed that a simpler approach (mostly statistical models) is suitable for mappingO3concentrationsat the local scale, where enough O3concentration data are available. The associated error in mapping can be reduced by using more complex methodologies, based on co-variables. The models available at the regional or global level are used depending on the needed resolution and the domain where they are applied to. Increasing the resolution corresponds to an increase in the prediction but only up to a certain limit. However, with any approach, the ensemble models should be preferred.
... The effects of elevation are also implicit in a Kriging interpolation model through spatial autocorrelation of the monitoring network. More advanced methods such as co-kriging or machine learning could also improve accuracy, but were outside of the scope of this study (De Marco et al., 2022). ...
... Additional exposure-response relationships on other native species would also improve estimation of risk. Machine learning techniques and co-kriging methods incorporating additional geographic data have also been employed for ecological risk assessments of ozone (De Marco et al., 2022) and either approach might improve estimations of risk at a finer scale. ...
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.
... Atmospheric chemical transport models (CTM) have been commonly applied to investigate the effect of changes of emissions and meteorological conditions on air pollutant concentrations (e.g., Lamarque et al., 2013;Young et al., 2013;De Marco et al., 2022). However, they require a lot of computational power and are subject to large uncertainties related to the missing or poorly parameterized physical and chemical processes, and also to the emission inventories, which, frequently, are inaccurate, incomplete or not updated (Liu et al., 2018). ...
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 PM2.5 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.
... In China, surface O 3 concentrations have risen tõ 50 ppb, exceeding both the Europe and USA levels [3,4]. These high O 3 levels have the potential to impair normal forest growth and productivity and represent a serious threat to the biodiversity and multifunctionality of terrestrial ecosystems [5][6][7][8]. N deposition, in contrast, can drive the enhanced growth of plants and improved forest-based carbon (C) sequestration [9,10]. However, prior evidence has been inconsistent with respect to whether the addition of N to soil can exacerbate (e.g., [11]), mitigate (e.g., [12]), or fail to impact (e.g., [13,14]) the negative effects that O 3 levels have on plant growth, physiological characteristics, and biomass production, or on the associated rhizosphere soil microbes associated with these plants. ...
Ground-level ozone (O3) can adversely impact tree productivity and the service functions of forest ecosystems. The deposition of atmospheric nitrogen (N) can enhance nutrient availability and mitigate the O3-mediated impairment of plant–soil–microbe systems. Interactions between plants and associated microbial communities are integral to the ability of these plants to resist environmental stressors, yet studies examining the impact of increased O3 and N levels, alone or in combination, on these phyllosphere bacterial communities have been lacking to date. Accordingly, this study was conducted to examine the impact of O3 (charcoal-filtered air vs. non-filtered ambient air + 40 ppb of O3), N addition (0, 50, and 100 kg N ha−1 year−1), and a combination of these treatments on the phyllosphere bacterial communities associated with Cathay poplars. Higher O3 levels were found to significantly reduce the relative abundance of Gammaproteobacteria phyla while increasing the relative abundance of the dominant Alphaproteobacteria and Betaproteobacteria, with these effects being independent of N levels. Consistently, while marked differences in the composition of phyllosphere bacterial communities were observed as a function of O3 treatment conditions, they were largely similar across N treatments. Higher O3 levels contributed to significant reductions in α diversity, including both observed OTUs and phylogenetic diversity, when no N or low levels of N were added. α diversity was not affected by the N addition irrespective of O3 levels. A significant correlation was observed between photosynthesis rates and both α diversity and phyllosphere bacterial community composition, indicating a close relationship between photosynthetic activity and this microbial community. Together, these data offer new ecological insights regarding O3-induced changes in the makeup of bacterial communities present on plant surfaces, providing a foundation for efforts to formulate novel management strategies aimed at adapting environmental stressors under conditions of O3 pollution and in N-enriched environments.
... O 3 is among the pollutants listed by the World Health Organization that has the strongest evidence for public health concern. Ground level O 3 is not directly emitted into the air, but it is formed through a photochemical reaction driven by hydroxyl radicals (OH), its precursors like nitrogen oxides (NOx) from traffic and industrial emissions, and volatile organic compounds (VOCs) in the presence of sunlight and heat [19,21,28,48,49,8,9]. High levels of O 3 pose detrimental effects to human health such as eye and nose irritation and lung function impairment [31,37]. ...
High levels of ground level ozone (O3) are associated with detrimental health concerns. Most of the studies only focused on daily average and daytime trends due to the presence of sunlight that initiates its formation. However, atmospheric chemical reactions occur all day, thus, nighttime concentrations should be given equal importance. In this study, geospatial-artificial intelligence (Geo-AI) which combined kriging, land use regression (LUR), machine learning, an ensemble learning, was applied to develop ensemble mixed spatial models (EMSMs) for daily, daytime, and nighttime periods. These models were used to estimate the long-term O3 spatio-temporal variations using a two-decade worth of in-situ measurements, meteorological parameters, geospatial predictors, and social and season-dependent factors. From the traditional LUR approach, the performance of EMSMs improved by 60% (daytime), 49% (nighttime), and 57% (daily). The resulting daily, daytime, and nighttime EMSMs had a high explanatory power with and adjusted R2 of 0.91, 0.91, and 0.88, respectively. Estimation maps were produced to examine the changes before and during the implementation of nationwide COVID-19 restrictions. These results provide accurate estimates and its diurnal variation that will support pollution control measure and epidemiological studies.
... Many factors contribute to disease emergence, including climate change, globalization and urbanization; most of these factors are caused by humans [23]. Anthropogenic activities are a major issue of air pollution due to the emission of harmful pollutants and sources of transmissible disease agents [5, 22-24, 43, 44, 73]. ...
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 PM 10 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 PM 10 (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 PM 10 (27.3%) and PM 2.5 (17.8%) were reduced compared to the 2015–2019 period.
... Ozone (O 3 ) is one of the most important pollutants in the atmosphere, high concentrations of which pose a serious threat to human health, ecosystems, and global climate change (Y. Liang et al., 2019;De Marco et al., 2022;Feng et al., 2022;Skeie et al., 2020). Many metropolitan areas in China, such as Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD), have been experiencing severe O 3 pollution in recent years (Gao et al., 2017;Lu et al., 2018). ...
Ozone (O3) has become a significant air pollutant in China in
recent years. O3 abatement is challenging due to the nonlinear response
of O3 to precursors nitrogen oxides (NOx) and volatile organic
compounds (VOCs). Photochemical indicators are widely used to estimate the
O3–NOx–VOC sensitivity, and this has important policy
implications. However, the effectiveness of the indicators has seldom been
evaluated. This study examined the applications of four indicators that
include the ratio of the production rates of H2O2 and HNO3
(PH2O2/PHNO3), HCHO/NO2, HCHO/NOy, and reactive nitrogen
(NOy) in the Yangtze River Delta (YRD) with localized thresholds. The
overall accuracy was high (>92 %) for all indicators and not
significantly reduced with different simulation periods or in different
locations of the region. By comparing with the O3 isopleths, it was
found that HCHO/NO2 and HCHO/NOy showed the most consistency,
whereas PH2O2/PHNO3 (NOy) tended to underestimate
(overestimate) the positive response of O3 to NOx. Additionally,
PH2O2/PHNO3 was less likely to attribute the O3 formation to
mixed sensitivity than the other indicators, and this demonstrated a
preference for a single-pollutant control strategy. This study also revealed
that the details in the methodology used to derive the threshold values
impacted the results, and this may produce uncertainties in the application
of photochemical indicators.
... The Tropospheric Ozone Assessment Report (TOAR), initiated by the International Global Atmospheric Chemistry Project, gathers surface O 3 measurements from monitoring stations worldwide . However, the spatial distribution of monitoring stations tends to be heterogeneous, and gaps within time series can be noted for suitable human health and ecological risk assessments (Araki et al., 2015;De Marco et al., 2022). For example, ground PM 2.5 measurements are missing for sites representing >50 % of the world's urban population (Apte et al., 2021). ...
Ground-level ozone (O3), fine particles (PM2.5), 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, PM2.5, and NO2 between 2000 and 2019. PM2.5, 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, PM2.5 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.
... Ozone (O3) is one of the most important pollutants in the atmosphere, high concentrations of which pose a serious threat to human health, ecosystems, and global climate change (Wang et al., 2020b;Liang et al., 2019;De Marco et al., 2022;Feng et 25 al., 2022;Skeie et al., 2020). Many metropolitan areas in China, such as Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and Pearl River Delta (PRD), have been experiencing severe O3 pollution in recent years (Gao et al., 2017;Lu et al., 2018). ...
Ozone (O3) has become a significant air pollutant in China in recent years. O3 abatement is challenging due to the nonlinear response of O3 to precursors nitrogen oxides (NOx) and volatile organic compounds (VOCs). Photochemical indicators are widely used to estimate the O3-NOx-VOC sensitivity, and this has important policy implications. However, the effectiveness of the indicators has seldom been evaluated. This study examines the applications of four indicators that include the ratio of the production rates of H2O2 and HNO3 (PH2O2 / PHNO3), HCHO / NO2, HCHO / NOy, and reactive nitrogen (NOy) in the Yangtze River Delta (YRD) with localized thresholds. The overall accuracy was high (> 92 %) for all indicators and not significantly reduced with different simulation periods or in different locations of the region. By comparing with the O3 isopleths, it was found that HCHO/NO2 and HCHO / NOy showed the most consistency, whereas PH2O2 / PHNO3 (NOy) tended to underestimate (overestimate) the positive response of O3 to NOx. Additionally, PH2O2 / PHNO3 was less likely to attribute the O3 formation to mixed sensitivity than the other indicators, and this demonstrated a preference for a single-pollutant control strategy. This study also revealed that the details in the methodology used to derive the threshold values impacted the results, and this may produce uncertainties in the application of photochemical indicators.
The aims of this study were to i) assess the relationship between COVID-19 cases with PM10 concentration and ii) investigation premature deaths due to cardiovascular (M-CVD) and respiratory (M-RD) diseases in three classification levels (PM10<50µg m⁻³ in normal days, 50–200 µg m⁻³ in dusty days, and >200 µg m⁻³ in MED storm), by using daily averages of PM10 concentrations. The number of M-CVD and M-RD were estimated by concentration-response model, per 10⁵ people during 2017 to 2021. The results showed that 187, 183, 163, 215, and 206 days were observed with the PM10 concentrations lower than 50 µg m⁻³ during 2017 to 2021, and 178, 180, 200, 150, and 149 days were subtotal with exceeding PM10 from the WHO guideline (50 µg m⁻³), respectively. A positive correlation (r²=0.33, p < 0.05) was found to be between the number of COVID-19 cases and PM10 mean concentrations (r = 0.589, p = 0.046). Our findings showed that the highest M-CVD and M-RD were among exposed people at dusty days (50 < PM10≤ 200 μg m⁻³) in 2019. The total M-CVD and M-RD from 2017 to 2021 were 11.78 and 12.2, 18.25 and 17.4, 22.29 and 23.78, 10.33 and 7.6, 10.37 and 9.95 per 10⁵ people, respectively which 31.48% of health effects were related to PM10 concentrations more than 200 μg m⁻³.
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.
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.
The aims of 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.
The main objectives of this study were to (i) assess variation within fine particles (PM2.5) and tropospheric ozone (O3) time series in Khorramabad (Iran) between 2019 (before) and 2020 (during COVID-19 pandemic); (ii) assess relationship between PM2.5 and O3, the PM2.5/O3 ratio, and energy consumption; and (iii) estimate the health effects of exposure to ambient PM2.5 and O3. From hourly PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 (−25.5%) and an increase of O3 concentration (+ 8.0%) in Khorramabad.
Stomatal O3 flux accumulated over the growing season (or phytotoxic ozone dose above a y threshold of uptake, PODy) is nowadays considered as the best biologically based metric to assess O3 injury to vegetation and establishing critical levels (CLs). So far, CLs have used biomass losses as forest-health indicator in experimental research. Ozone-induced biomass losses of adult forests, however, are difficult to assess. We stress a need to reconcile present CLs and dose-response functions to estimate O3-induced biomass losses. In fact, a clear discrepancy emerges when comparing CL exceedances calculated from WRF-Chem results and biomass losses estimated based on the presently available dose-response functions for different forest types. We synthesize recent evidence that visible foliar O3 injury (VFI) recorded annually in large-scale forest surveys may be used as forest-health indicator and coupled with active O3 monitoring in setting epidemiology-based CLs for forest protection. Bridging experimental and monitoring research is needed for validation and parameterization of field results and models, with the O3 free-air controlled exposure (FACE) facilities as a reliable experimental tool. In fact, VFI is well correlated to O3-induced biomass loss at O3 FACE experiments, and POD1 and O3 tolerance (when characterized as leaf mass per area (LMA) directly affect VFI under field conditions. POD1 shows a much stronger causality than the O3 exposure index AOT40 in affecting VFI. Accurate calculation of PODy at field sites is now possible, thanks to recent technological advances that support low-cost and reliable monitoring of PODy at forest sites and thus ensure long-term sustainability of such laborious monitoring. We summarise evidence that active O3 monitoring is a cost-effective approach for estimating PODy and its economic effects on forests, as the initial investment is compensated in few years by less travels to the field sites than passive O3 monitoring. These results respond to raising legislative interest into PODy, and support long-term sustainability of PODy monitoring at forest sites.
In response to the increasing need to better understand air pollution and climate change impacts, the international conference Air Pollution threats to Plant Ecosystems was held in Paphos, Cyprus, during 11-15 October 2021. The conference was an advanced version of the previous international conference on Ozone and Plant Ecosystems, which was held in Florence, Italy, during 21-24 May, 2018. The 2021 conference was hybrid, with either physical presence or online participation, organized by ARCHES-Conseils and co-organized by the Research Group “Air Pollution and Climate Change” of the International Union of Forest Research Organization(IUFRO 8.04.00), and the International Cooperative Program on Effects of Air Pollution on Natural Vegetation and Crops (ICP Vegetation). Based on the conference, this Editorial summarizes a Virtual Special Issue (VSI) published in Environmental Research. The papers collection is available at https://www.sciencedirect.com/journal/environmental-research/special-issue/102B9S3D59H.
Background
The paper presents an overview of air quality in the 27 member countries of the European Union (EU) and the United Kingdom (previous EU-28), from 2000 to 2017. We reviewed the progress made towards meeting the air quality standards established by the EU Ambient Air Quality Directives (European Council Directive 2008/50/EC) and the World Health Organization (WHO) Air Quality Guidelines by estimating the trends (Mann-Kendal test) in national emissions of main air pollutants, urban population exposure to air pollution, and in mortality related to exposure to ambient fine particles (PM 2.5 ) and tropospheric ozone (O 3 ).
Results
Despite significant reductions of emissions (e.g., sulfur oxides: ~ 80%, nitrogen oxides: ~ 46%, non-methane volatile organic compounds: ~ 44%, particulate matters with a diameter lower than 2.5 µm and 10 µm: ~ 30%), the EU-28 urban population was exposed to PM 2.5 and O 3 levels widely exceeding the WHO limit values for the protection of human health. Between 2000 and 2017, the annual PM 2.5 -related number of deaths decreased (- 4.85 per 10 ⁶ inhabitants) in line with a reduction of PM 2.5 levels observed at urban air quality monitoring stations. The rising O 3 levels became a major public health issue in the EU-28 cities where the annual O 3 -related number of premature deaths increased (+ 0.55 deaths per 10 ⁶ inhabitants).
Conclusions
To achieve the objectives of the Ambient Air Quality Directives and mitigate air pollution impacts, actions need to be urgently taken at all governance levels. In this context, greening and re‐naturing cities and the implementation of fresh air corridors can help meet air quality standards, but also answer to social needs, as recently highlighted by the COVID-19 lockdowns.
Although exposure to air pollution increases the risk of premature mortality and years of life lost (YLL), the effects of daily air quality improvement to the life expectancy of respiratory diseases remained unclear. We applied a generalized additive model (GAM) to assess the associations between daily PM2.5 exposure and YLL from respiratory diseases in 96 Chinese cities during 2013–2016. We further estimated the avoidable YLL, potential gains in life expectancy, and the attributable fraction by assuming daily PM2.5 concentration decrease to the air quality standards of China and World Health Organization. Regional and national results were generated by random-effects meta-analysis. A total of 861,494 total respiratory diseases and 586,962 chronic obstructive pulmonary disease (COPD) caused death from 96 Chinese cities were recorded during study period. Each 10 μg/m³ increase of PM2.5 in 3-day moving average (lag02) was associated with 0.16 (95% CI: 0.08, 0.24) years increment in life expectancy from total respiratory diseases. The highest effect was observed in Southwest region with 0.42 (95% CI: 0.22, 0.62) years increase in life expectancy. By attaining the WHO's Air Quality Guidelines, we estimated that an average of 782.09 (95% CI: 438.29, 1125.89) YLLs caused by total respiratory death in each city could be avoided, which corresponded to 1.15% (95% CI: 0.67%, 1.64%) of the overall YLLs, and 0.12 (95% CI: 0.07, 0.17) years increment in life expectancy. The results of COPD were generally consistent with total respiratory diseases. Our findings indicate that reduction in daily PM2.5 concentrations might lead to longer life expectancy from respiratory death.
Background - The paper presents an overview of air quality in the 27 member countries of the European Union (EU) and the United Kingdom (previous EU-28), from 2000 to 2017. We reviewed the progress made towards meeting the air quality standards established by the EU Ambient Air Quality Directives (Directive 2008/50/EC) and the World Health Organization (WHO) Air Quality Guidelines by estimating the trends (Mann-Kendal test) in national emissions of main air pollutants, urban population exposure to air pollution, and in mortality related to exposure to ambient fine particles (PM2.5) and tropospheric ozone (O3).
Results - Despite significant reductions of emissions (e.g. sulfur oxides: ~80%, nitrogen oxides: ~46%, non-methane volatile organic compounds: ~44%, particulate matters with a diameter lower than 2.5µm and 10µm: ~30%), the EU-28 urban population was exposed to PM2.5 and O3 levels widely exceeding the WHO limit values for the protection of human health. Between 2000 and 2017, the annual PM2.5-related number of deaths decreased (- 4.85 per 106 inhabitants) in line with a reduction of PM2.5 levels observed at urban air quality monitoring stations. The rising O3 levels became a major public health issue in the EU-28 cities where the annual O3-related number of premature deaths increased (+ 0.55 deaths per 10⁶ inhabitants).
Conclusions - To achieve the objectives of the Ambient Air Quality Directives and mitigate air pollution impacts, actions need to be urgently taken at all governance levels. In this context, greening and re‐naturing cities can help meet air quality standards, but also answer to social needs, as recently highlighted by the COVID-19 lockdowns.
In this paper we integrated multiple types of predictor variables and three types of machine learners into a geographically weighted ensemble model to estimate daily maximum 8-hr O3 with high resolution over both space (at 1 km × 1 km grid cells covering the contiguous United States) and time (daily estimates between 2000 and 2016). We further quantify monthly model uncertainty for our 1 km × 1 km gridded domain. The results demonstrate high overall model performance, with an average cross-validated R2 (coefficient of determination) against observations of 0.90, and of 0.86 for annual averages. Overall, model performance of the three machine learning algorithms was quite similar. The overall model performance from the ensemble model outperformed those from any single algorithm. The East North Central region of the United States had the highest R2, 0.93, and performance was weakest for the western mountainous regions (R2 of 0.86) and New England (R2 of 0.87). For the cross-validation by season, our model had the best performance during summer, with an R2 of 0.88. This study can be useful for the environmental health community to more accurately estimate the health impacts of O3 over space and time, especially in health studies at intra-urban scale.
Elevated tropospheric ozone concentrations induce adverse effects in plants. We reviewed how ozone affects (i) the composition and diversity of plant communities by affecting key physiological traits; (ii) foliar chemistry and the emission of volatiles, thereby affecting plant-plant competition, plant-insect interactions, and the composition of insect communities; and (iii) plant-soil-microbe interactions and the composition of soil communities by disrupting plant litterfall and altering root exudation, soil enzymatic activities, decomposition, and nutrient cycling. The community composition of soil microbes is consequently changed, and alpha diversity is often reduced. The effects depend on the environment and vary across space and time. We suggest that Atlantic islands in the Northern Hemisphere, the Mediterranean Basin, equatorial Africa, Ethiopia, the Indian coastline, the Himalayan region, southern Asia, and Japan have high endemic richness at high ozone risk by 2100.
This is an open-access publication and can be downloaded at now cost: https://advances.sciencemag.org/content/6/33/eabc1176
Background
Spatial linear Land-Use Regression (LUR) is commonly used for long-term modeling of air pollution in support of exposure and epidemiological assessments. Machine Learning (ML) methods in conjunction with spatiotemporal modeling can provide more flexible exposure-relevant metrics and have been studied using different model structures. There is however a lack of comparisons of methods available within these two modeling frameworks, that can guide model/algorithm selection in air quality epidemiology.
Objective
The present study compares thirteen algorithms for spatial/spatiotemporal modeling applied for daily maxima of 8-hour running averages of ambient ozone concentrations at spatial resolutions corresponding to census tracts, to support estimation of annual ozone design values across the contiguous US. These algorithms were selected from nine representative categories and trained using predictors that included chemistry-transport model predictions, meteorological factors, land use and land cover, and stationary and mobile emissions.
Methods
To obtain the best predictive performance, model structures were optimized through a repeated coarse/fine grid search with expert knowledge. Six target-oriented validation strategies were used to prevent overfitting and avoid over-optimistic model evaluation results. In order to take full advantage of the power of different algorithms, we introduced tuning sample weights in spatiotemporal modeling to ensure predictive accuracy of peak concentrations, that is crucial for exposure assessments. In spatial modeling, four interpretation and visualization tools were introduced to explain predictions from different algorithms.
Results
Nonlinear ML methods achieved higher prediction accuracy than linear LUR, and the improvements were more significant for spatiotemporal modeling (nearly 10%-40% decrease of predicted RMSE). By tuning the sample weights, spatiotemporal models can predict concentrations used to calculate ozone design values that are comparable or even better than spatial models (nearly 30% decrease of cross-validated RMSE). We visualized the underlying nonlinear relationships, heterogeneous associations and complex interactions from the two best performing ML algorithms, i.e., Random Forest and Extreme Gradient Boosting, and found that the complex patterns were relatively less significant with respect to model accuracy for spatial modeling.
Conclusion
Machine Learning can provide estimates that are actually more interpretable and practical than linear regression to improve accuracy in modeling human exposures. A careful design of hyperparameter tuning and flexible data splitting and validations is crucial to obtain reliable and stable results. Desirable/successful nonlinear models are expected to capture similar nonlinear patterns and interactions using different ML algorithms.
Background
Ozone is one of the dominant air pollutants due to its impact on disease burden and increasing trend in concentration. However, evidence regarding short-term effect of ozone on years of life lost (YLL) is scarce.
Methods
A national time-series study was conducted in 48 large Chinese cities from 2013 to 2017. Generalized additive model coupled with random effects model were used to estimate national-average associations of ozone with YLL. Potential modifiers and additional life gain due to avoidable YLL under certain scenario were also evaluated.
Results
The average annual mean ozone concentration of these cities was 86.9 μg/m³. For 10 μg/m³ increase in 3-day moving average ozone concentration, we estimated 0.37% [95% confidence interval (CI): 0.29%, 0.46%] increase in YLL from nonaccidental causes, 0.38% (95% CI: 0.30%, 0.46%) increase in YLL from cardiovascular diseases, and 0.36% (95% CI: 0.16%, 0.56%) increase in YLL from respiratory diseases. Moreover, the associations were more evident in people with less education and in cities with lower carbon monoxide concentration or those located at north region with lower mean temperature. Finally, an estimated life of 0.055 (95% CI: 0.043, 0.068) years would be gained per deceased people if ozone concentration could fall to 100 μg/m³.
Conclusions
Our findings indicated robust associations between short-term exposure to ozone and YLL from nonaccidental causes and cardiopulmonary diseases. Relevant intervention design should take the heterogeneity of both individual- and city-level characteristics into account. Implementation of more stringent standard is beneficial for alleviating YLL caused by ozone.
Few large multicity studies have assessed acute effect of tropospheric ozone pollution on pneumonia risk. We aimed to examine the relation between day-to-day changes in ozone concentrations and hospital admissions for pneumonia in China. We conducted a national time-series study in 184 major Chinese cities from 2014 to 2017. City-specific relation between ozone concentrations and pneumonia admissions was evaluated using an over-dispersed generalized additive model. Random-effects meta-analysis was conducted to pool the city-specific estimates. Two-pollutant models were fitted to test the robustness of the relations. We also investigated potential effect modifiers. Overall, we observed increased admissions for pneumonia associated with ozone exposure. The national-average estimates per 10-μg/m3 increase in ozone were 0.14% (95% CI: 0.03%-0.25%) at lag 0 day in the whole year, 0.30% (95% CI: 0.17%-0.43%) at lag 0 day in the warm season, and 0.20% (95% CI: 0.05%-0.34%) at lag 1 day in the cool season. Two-pollutant models indicated that the ozone effects were not confounded by PM2.5, SO2, NO2 or CO. The association between ozone and pneumonia was stronger in the elderly. Ozone levels and gross domestic product per capita reduced the effects of ozone, and smoking enhanced the effects of ozone. In conclusion, we estimated an increase in daily pneumonia admissions associated with ozone exposure in China. As the first national study in China to report acute effect of ozone on pneumonia hospitalizations, our findings are incredibly meaningful in terms of both ozone pollution related policy development and pneumonia prevention.
At present, both tropospheric ozone (O3) and particulate matters (PM) are among the most threatening air pollutants for human health in cities. The air pollution effects over public health include increased risk of hospital admissions and mortality for respiratory and cardiovascular diseases even when air pollutant concentrations are below European and international standards. The aim of this study was to (i) estimate the burden of mortality and morbidity for cardiovascular and respiratory diseases attributed to PM2.5, PM10 and O3 in nine selected cities in France, Iran and Italy in 2015 and 2016 and to (ii) compare estimated burdens at current O3 and PM levels with pre-industrial levels. The selected Mediterranean cities are among the most affected by the air pollution in Europe, in particular by rising O3 while the selected Iranian cities rank as the most polluted by PM in the world. The software AirQ+ was used to estimate the short-term health effects, in terms of mortality and morbidity by using in situ air quality data, city-specific relative risk values and baseline incidence. Compared to pre-industrial levels, long-term exposures to ambient PM2.5, PM10 and O3 have substantially contributed to mortality and hospital admissions in selected cities: about 8200 deaths for non-accidental causes, 2400 deaths for cardiovascular diseases, 540 deaths for respiratory diseases, 220 deaths for chronic obstructive pulmonary diseases as well as 18,800 hospital admissions for cardiovascular diseases and 3400 for respiratory diseases were reported in 2015. The study supports the need of city-specific epidemiological data and urgent strategies to mitigate the health burden of air pollution.
We examined the association between average annual fine particulate matter (PM2.5) and ozone and first hospital admissions of Medicare participants for stroke, chronic obstructive pulmonary disease (COPD), pneumonia, myocardial infarction (MI), lung cancer, and heart failure (HF). Annual average PM2.5 and ozone levels were estimated using high-resolution spatio-temporal models. We fit a marginal structural Cox proportional hazards model, using stabilized inverse probability weights (IPWs) to account for the competing risk of death and confounding. Analyses were then repeated after restricting to exposure levels below the current U.S. standards. The results showed that PM2.5 was significantly associated with an increased hazard of admissions for all studied outcomes; the highest observed being a 6.1% (95% CI: 5.9%–6.2%) increase in the hazard of admissions with pneumonia for each μg/m3 increase in particulate levels. Ozone was also significantly associated with an increase in the risk of first hospital admissions of all outcomes. The hazard of pneumonia increased by 3.0% (95% CI: 2.9%–3.1%) for each ppb increase in the ozone level. Our results reveal a need to regulate long-term ozone exposure, and that associations persist below current PM2.5 standards. Keywords: Air pollution, Particulate matter, Ozone, Long-term exposure, Hospital admissions, Inverse probability weights
The interannual variability of the greenhouse gases methane (CH4) and tropospheric ozone (O3) is largely driven by natural variations in global emissions and meteorology. The El Niño–Southern Oscillation (ENSO) is known to influence fire occurrence, wetland emission and atmospheric circulation, affecting sources and sinks of CH4 and tropospheric O3, but there are still important uncertainties associated with the exact mechanism and magnitude of this effect. Here we use a modelling approach to investigate how fires and meteorology control the interannual variability of global carbon monoxide (CO), CH4 and O3 concentrations, particularly during large El Niño events. Using a three-dimensional chemical transport model (TOMCAT) coupled to a sophisticated aerosol microphysics scheme (GLOMAP) we simulate changes to CO, hydroxyl radical (OH) and O3 for the period 1997–2014. We then use an offline radiative transfer model to quantify the climate impact of changes to atmospheric composition as a result of specific drivers.
During the El Niño event of 1997–1998, there were increased emissions from biomass burning globally, causing global CO concentrations to increase by more than 40 %. This resulted in decreased global mass-weighted tropospheric OH concentrations of up to 9 % and a consequent 4 % increase in the CH4 atmospheric lifetime. The change in CH4 lifetime led to a 7.5 ppb yr⁻¹ increase in the global mean CH4 growth rate in 1998. Therefore, biomass burning emission of CO could account for 72 % of the total effect of fire emissions on CH4 growth rate in 1998.
Our simulations indicate that variations in fire emissions and meteorology associated with El Niño have opposing impacts on tropospheric O3 burden. El Niño-related changes in atmospheric transport and humidity decrease global tropospheric O3 concentrations leading to a −0.03 W m⁻² change in the O3 radiative effect (RE). However, enhanced fire emission of precursors such as nitrogen oxides (NOx) and CO increase O3 and lead to an O3 RE of 0.03 W m⁻². While globally the two mechanisms nearly cancel out, causing only a small change in global mean O3 RE, the regional changes are large – up to −0.33 W m⁻² with potentially important consequences for atmospheric heating and dynamics.
Aerosol properties and their climatic feedbacks are characterized by high uncertainty in both global and regional model simulations. We explore sources of uncertainty in the representation of aerosol properties using an ensemble of simulations performed at 24 km resolution with WRF‐Chem over eastern North America. The sensitivity of aerosol optical depth (AOD) and near‐surface fine particle concentrations (PM2.5) to planetary boundary layer (PBL) and aerosol schemes (modal with secondary organic aerosol (SOA) versus sectional but excluding SOA), as well as different emission inventories (National Emission Inventory (NEI) 2005 versus 2011) is examined. We quantify the spread among ensemble members with respect to the model setup and compute statistical metrics to identify the run configuration that exhibits greatest fidelity relative to observations of aerosol and meteorological properties. Use of the Modal Aerosol Dynamics Model for Europe/Secondary Organic Aerosol Model scheme leads to highest agreement with MODIS clear‐sky AOD observations particularly when the 2005 NEI is used (with either PBL scheme). These members exhibit small negative mean fractional bias over the simulation domain (<2%), and relatively high spatial correlation in summertime mean monthly AOD (>0.5). The aerosol scheme and NEI dominate the ensemble spread in AOD. Near‐surface PM2.5 is also dependent on PBL scheme and is best reproduced in runs adopting a sectional approach and emissions for 2011. Thus, WRF‐Chem configuration associated with highest agreement with AOD observations is not the same as for PM2.5, possibly reflecting the importance of columnar water vapor in dictating AOD.
In this study, we used eight sites from across Europe to investigate the implications of a future climate (2 °C warmer and 20% drier) and a changing ozone profile (increased background concentrations and reduced peaks) on stomatal ozone fluxes of three widely occurring plant species. A changing ozone profile with small increases in background ozone concentrations over the course of a growing season could have significant impacts on the annual accumulated stomatal ozone uptake, even if peak concentrations of ozone are reduced. Predicted increases in stomatal ozone uptake showed a strong relationship with latitude and were larger at sites from northern and mid-Europe than those from southern Europe. At the sites from central and northern regions of Europe, including the UK and Sweden, climatic conditions were highly conducive to stomatal ozone uptake by vegetation during the summer months and therefore an increase in daily mean ozone concentration of 3–16% during this time of year (from increased background concentrations, reduced peaks) would have a large impact on stomatal ozone uptake. In contrast, during spring and autumn, the climatic conditions can limit ozone uptake for many species. Although small increases in ozone concentration during these seasons could cause a modest increase in ozone uptake, for those species that are active at low temperatures, a 2 °C increase in temperature would increase stomatal ozone uptake even in the absence of further increases in ozone concentration. Predicted changes in climate could alter ozone uptake even with no change in ozone profile. For some southern regions of Europe, where temperatures are close to or above optimum for stomatal opening, an increase in temperature of 2 °C could limit stomatal ozone uptake by enhancing stomatal closure during the summer months, whereas during the spring, when many plants are actively growing, a small increase in temperature would increase stomatal ozone uptake.
This study is based on model results from TF HTAP (Task Force on Hemispheric Transport of Air Pollution) phase II, in which a set of source receptor model experiments have been defined, reducing global (and regional) anthropogenic emissions by 20% in different source regions throughout the globe, with the main focus on the year 2010. All the participating models use the same set of anthropogenic emissions. Comparisons of model results to measurements are shown for selected European surface sites and for ozone sondes, but the main focus here is on the contributions to European ozone levels from different world regions, and how and why these contributions differ depending on the model. We investigate the origins by use of a novel stepwise approach, combining simple tracer calculations and calculations of CO and O3. To highlight the differences, we analyse the vertical transects of the midlatitude effects from the 20% emission reductions.
The spread in the model results increases from the simple CO tracer to CO and then to ozone as the complexity of the physical and chemical processes involved increase. As a result of non-linear ozone chemistry, the contributions from non-European relative to European sources are larger for ozone compared to the CO and the CO tracer. For annually averaged ozone the contributions from the rest of the world is larger than the effects from European emissions alone, with the largest contributions from North America and eastern Asia. There are also considerable contributions from other nearby regions to the east and from international shipping. The calculated contributions to European annual average ozone from other major source regions relative to all contributions from all major sources (RAIR – Relative Annual Intercontinental Response) have increased from 43% in HTAP1 to 82% in HTAP2. This increase is mainly caused by a better definition of Europe, with increased emissions outside of Europe relative to those in Europe, and by including a nearby non-European source for external-to-Europe regions. European contributions to ozone metrics reflecting human health and ecosystem damage, which mostly accumulated in the summer months, are larger than for annual ozone. Whereas ozone from European sources peaks in the summer months, the largest contributions from non-European sources are mostly calculated for the spring months, when ozone production over the polluted continents starts to increase, while at the same time the lifetime of ozone in the free troposphere is relatively long. At the surface, contributions from non-European sources are of similar magnitude for all European subregions considered, defined as TF HTAP receptor regions (north-western, south-western, eastern and south-eastern Europe).
The objective of the study is to investigate short and long-term mortality due to exposure of the inhabitants of Ahvaz, Iran to ambient O3. The study employed the World Health Organisation Regional Office for Europe’s (WHO/Europe) AirQ+ modeling system to estimate total mortality (TM), cardiovascular mortality (CM), and respiratory mortality (RM) using relative risks (RR) and baseline incidences (BI). The AirQ+ model estimates risks of 2.08% (95% CI: 1.39-2.76) for TM, 2.78% (95% CI: 0-4.13) for CM, and 5.48% (95% CI: 2.76 -8.14) for RM in 2015 for increase in O3 concentration above 10 µg m-3. These estimates were high compared to 2016 estimates where the risks were 0.72 % (95% CI: 0.48-0.96) for TM, 0.96% (95% CI: 0-1.44) for CM and 1.92% (95% CI: 0.96-2.87) for RM. The long-term risks for RM were 1.53 (95% CI: 0.77-2.28) and 0.14 (95% CI: 0.07-0.2) for 2015 and 2016, respectively. The estimated health effects from O3 exposures in Ahvaz were low compared to other studies in Iran and across the world. Introduction of electric and hybrid cars with good urban planning could further reduce the health impacts of O3 exposure in Ahvaz, Iran.
This study was conducted to quantify, by an approach proposed by the World Health
Organization (WHO), the daily hospital admissions for chronic obstructive pulmonary disease
(COPD) related to an exposure to particulate matter (PM10) and oxidants such as ozone (O3),
sulfur dioxide (SO2) and nitrogen dioxide (NO2) in a heavily-polluted city in Iran. For the health
impact assessment, in terms of COPD, the current published relative risk (RR) and baseline
incidence (BI) values, suggested by the WHO, and the 1-hour O3 concentrations and daily
PM10, NO2, and SO2 concentrations were compiled. The results showed that 5.9%, 4.1%, 1.2%
and 1.9% of the COPD daily hospitalizations in 2011 and 6.6%, 1.9%, 2.3% and 2.1% in 2012
were attributed to PM10, O3, SO2, and NO2 concentrations exceeding 10 µg/m3
, respectively.
This study indicates that air quality and the high air pollutant levels have an effect on COPD
morbidity. Air pollution is associated with visits to emergency services and hospital
admissions. A lower relative risk can be achieved if some stringent control strategies for
reducing air pollutants or precursors emissions are implemented.
This study examined the health impacts of O3
in Ahvaz (Iran). Ozone data were obtained from the
Iranian Environmental Protection Agency and the
time series were analyzed while the health endpoints from O3 exposure were calculated using the
Air Q model. The time series analysis showed that
air pollutants levels were associated with five steps
delay of O3 and zero step delay of moving average
ARMA (5, 0). The results of Air Q model revealed
cumulative cases of cardiovascular mortality and
myocardial infarction related to surface O3. The
number of cases attributable to O3 exposure for
cardiovascular mortality and myocardial infarction
were estimated at 182 and 51 people per year, respectively. The finding of this study showed that,
the distribution of O3 data has a correlated structure
over time. Ground-level O3 was found to be positively correlated with an increased risk of cardiovascular mortality and acute myocardial infarction
in Ahvaz.
Three online coupled chemical transport model simulations were analyzed for three summer months of 2015 in Poland. One of them was run with default emission inventory, the other two with NOx and VOC emissions reduced by 30%, respectively. Obtained ozone concentrations were evaluated with data from air quality measurement stations and ozone sensitivity to precursor emissions was estimated by ozone concentration differences between simulations and with the use of indicator ratios. They were calculated based on modeled mixing ratios of ozone, total reactive nitrogen and its components, nitric acid and hydrogen peroxide. The results show that the model overestimates ozone concentrations with the largest errors in the morning and evening, which is primarily related to the way vertical mixing is resolved by the model. Better model performance for ozone is achieved in rural than urban environment, as PBL and mixing mechanisms play more significant role in urban areas. Modeled ozone shows mixed sensitivity to precursor concentrations, similarly to other European regions, but indicator ratios have different values than are found in literature, particularly H2O2/HNO3 is larger than in southern Europe. However, indicator ratios often differ between locations and transition values need to be established individually for a given region.
The impact of ground-level ozone (O3) on vegetation is
largely under-investigated at the global scale despite large
areas worldwide that are exposed to high surface O3 levels. To explore future potential impacts of O3 on vegetation, we compared
historical and projected surface O3 concentrations simulated by six global atmospheric chemistry transport models on the
basis of three representative concentration pathways emission scenarios (i.e. RCP2.6, 4.5, 8.5). To assess changes in the potential
surface O3 threat to vegetation at the global scale, we used the AOT40 metric. Results point out a significant exceedance of
AOT40 in comparison with the recommendations of UNECE for the protection of vegetation. In fact, many areas of the Northern
Hemisphere show that AOT40-based critical levels will be exceeded by a factor of at least 10 under RCP8.5. Changes in surface
O3 by 2100 worldwide range from about +4–5 ppb in the RCP8.5 scenario to reductions of about 2–10 ppb in the
most optimistic scenario, RCP2.6. The risk of O3 injury for vegetation, through the potential O3 impact on
photosynthetic assimilation, decreased by 61 and 47 % under RCP2.6 and RCP4.5, respectively, and increased by 70 % under
RCP8.5. Key biodiversity areas in southern and northern Asia, central Africa and North America were identified as being at risk from
high O3 concentrations.
Health impact assessments are useful for governmental authorities and decision-makers to determine the need for action and address potential public health problems arising from exposure to air pollution. The present study was conducted to assess the short-term health impacts of ambient air pollution in Tehran using the AirQ 2.2.3 model for March 2013–March 2016. Hourly concentrations of PM10, PM2.5, O3, NO2 and SO2 were acquired from the Department of Environment (DOE) and Tehran Air Quality Control Company (TAQCC). Air pollution data was validated according to the USEPA criteria, and only valid monitoring stations for each of the three years were entered to the AirQ 2.2.3 model. The pollutant concentrations were lower in the March 2015 March 2016 period compared to the previous years. The three-year average (± standard deviation) of PM10 and PM2.5 concentrations were 80.21 (± 34.21) and 39.17 (± 17.26) µg m–3, respectively. The three-year averages (± standard deviation) for ozone (O3), nitrogen dioxide (NO2), and sulphur dioxide (SO2) were 54.88 (± 24.15), 103.97 (± 25.88) and 39.84 (± 11.17) µg m–3, respectively. The total estimated number of deaths attributed to PM10, PM2.5, O3, NO2 and SO2 over these three years were 4192, 4336, 1363, 2830, and 1216, respectively. The health impacts attributed to all pollutants except for PM10 were estimated to decrease in 2016, compared to the prior years. However, the air quality in Tehran still poses significant risks to public health. In conclusion, urgent efforts are needed such as mandating the replacing of old and poorly functioning vehicles from the roadways in order to reduce the health burden that air pollution is currently imposing on this city.
Ozone fields simulated for the first phase of the Chemistry-Climate Model
Initiative (CCMI-1) will be used as forcing data in the 6th Coupled Model
Intercomparison Project. Here we assess, using reference and sensitivity
simulations produced for CCMI-1, the suitability of CCMI-1 model results for
this process, investigating the degree of consistency amongst models
regarding their responses to variations in individual forcings. We consider
the influences of methane, nitrous oxide, a combination of chlorinated or
brominated ozone-depleting substances, and a combination of carbon dioxide
and other greenhouse gases. We find varying degrees of consistency in the
models' responses in ozone to these individual forcings, including some
considerable disagreement. In particular, the response of total-column ozone
to these forcings is less consistent across the multi-model ensemble than
profile comparisons. We analyse how stratospheric age of air, a commonly
used diagnostic of stratospheric transport, responds to the forcings. For
this diagnostic we find some salient differences in model behaviour, which may
explain some of the findings for ozone. The findings imply that the ozone
fields derived from CCMI-1 are subject to considerable uncertainties
regarding the impacts of these anthropogenic forcings. We offer some
thoughts on how to best approach the problem of generating a consensus ozone
database from a multi-model ensemble such as CCMI-1.
This work presents the evaluation of the WRF-Chem model applied for a
European domain over the year 2008 and employing two different chemical
modules. Airbase European station data and E-OBS database are used for
validation of the simulated meteorological conditions as well as
concentrations of NO2, SO2 and ozone. In both experiments,
underestimation of the amplitude of temperature daily cycle (by about
1 °C) and precipitation overestimation (by about 25 %) were found,
with possible impact on chemistry processes due to increased removal via wet
deposition. The modelled ozone concentrations match the observations quite
well, while the simulated concentrations of other gases show highly negative
bias.
Ozone is a highly reactive, oxidative gas associated with adverse health outcome, including mortality and morbidity. Data from monitoring sites worldwide show levels of ozone often exceeding EU legislation threshold and the more restrictive WHO guidelines for the protection of human health. Well-established evidence has been produced for short-term effects, especially on respiratory and cardiovascular systems, associated to ozone exposure. Less conclusive is the evidence for long-term effects, reporting suggestive associations with respiratory mortality, new-onset asthma in children and increased respiratory symptom effects in asthmatics. The growing epidemiological evidence and the increasing availability of routinely collected data on air pollutant concentrations and health statistics allow to produce robust estimates in health impact assessment routine. Most recent estimates indicate that in 2013 in EU-28, 16,000 premature deaths, equivalent to 192,000 years of life lost, are attributable to ozone exposure. Italy shows very high health impact estimates among EU countries, reporting 3380 premature deaths and 61 years of life lost (per 100,000 inhabitants) attributable to ozone exposure.
Background:
Exposure to ambient air pollution increases morbidity and mortality, and is a leading contributor to global disease burden. We explored spatial and temporal trends in mortality and burden of disease attributable to ambient air pollution from 1990 to 2015 at global, regional, and country levels.
Methods:
We estimated global population-weighted mean concentrations of particle mass with aerodynamic diameter less than 2·5 μm (PM2·5) and ozone at an approximate 11 km × 11 km resolution with satellite-based estimates, chemical transport models, and ground-level measurements. Using integrated exposure-response functions for each cause of death, we estimated the relative risk of mortality from ischaemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, lung cancer, and lower respiratory infections from epidemiological studies using non-linear exposure-response functions spanning the global range of exposure.
Findings:
Ambient PM2·5 was the fifth-ranking mortality risk factor in 2015. Exposure to PM2·5 caused 4·2 million (95% uncertainty interval [UI] 3·7 million to 4·8 million) deaths and 103·1 million (90·8 million 115·1 million) disability-adjusted life-years (DALYs) in 2015, representing 7·6% of total global deaths and 4·2% of global DALYs, 59% of these in east and south Asia. Deaths attributable to ambient PM2·5 increased from 3·5 million (95% UI 3·0 million to 4·0 million) in 1990 to 4·2 million (3·7 million to 4·8 million) in 2015. Exposure to ozone caused an additional 254 000 (95% UI 97 000-422 000) deaths and a loss of 4·1 million (1·6 million to 6·8 million) DALYs from chronic obstructive pulmonary disease in 2015.
Interpretation:
Ambient air pollution contributed substantially to the global burden of disease in 2015, which increased over the past 25 years, due to population ageing, changes in non-communicable disease rates, and increasing air pollution in low-income and middle-income countries. Modest reductions in burden will occur in the most polluted countries unless PM2·5 values are decreased substantially, but there is potential for substantial health benefits from exposure reduction.
Funding:
Bill & Melinda Gates Foundation and Health Effects Institute.
Fine particles i.e., with an aerodynamic diameter lower than 2.5 μm (PM2.5) have potentially the most significant effects on human health compared to other air pollutants. The main objectives of this study were to i) investigate the temporal variations of ambient PM2.5 in Marseille (Southern France), where air pollution is again a major public health issue, and ii) estimate their short-term health effects and annual trend (Mann-Kendall test) over a 10-year period from 2010 to 2019. In Marseille, the main sources of PM2.5 could be related to road traffic, industrial complexes, and oil refineries surrounded the city.. The number of premature deaths and hospital admissions attributable to ambient PM2.5 exposure for non-accidental causes, cardiovascular and respiratory diseases were estimated by using in-situ air quality data, city-specific relative risk values and baseline incidence. Despite significant reduction of PM2.5 (- 0.80 μg m⁻³ year⁻¹), Marseille citizens were exposed to PM2.5 levels exceeding the World Health Organization (WHO) Air Quality Guideline for human health protection (10 μg m⁻³) during entire study period. Exposure to ambient PM2.5 substantially contributed to mortality and hospital admissions: 871 deaths for non-accidental causes, 515 deaths for cardiovascular diseases, 47 deaths for respiratory diseases, as well as 1034 hospital admissions for cardiovascular diseases and 834 for respiratory diseases were reported between 2010 and 2019. Compliance with WHO annual limit values can result in substantial socio-economic benefits by preventing premature deaths and hospital admissions. For instance, based on the value of a statistical life and average cost of a hospital admission, the associated benefit for healthcare would have been €131 million in 2019. Between 2010 and 2019, the number of PM2.5-related non-accidental deaths decreased by 1.15 per 10⁵ inhabitants annually. Compared to 2010-2019, the restrictive measures associated to COVID-19 pandemic led to a reduction in PM2.5 of 11% in Marseille, with 2.6 PM2.5-related deaths averted in 2020.
Estimates of ground-level ozone concentrations are necessary to determine the human health burden of ozone. To support the Global Burden of Disease Study, we produce yearly fine resolution global surface ozone estimates from 1990 to 2017 through a data fusion of observations and models. As ozone observations are sparse in many populated regions, we use a novel combination of the M3Fusion and Bayesian Maximum Entropy (BME) methods. With M3Fusion, we create a multimodel composite by bias-correcting and weighting nine global atmospheric chemistry models based on their ability to predict observations (8834 sites globally) in each region and year. BME is then used to integrate observations, such that estimates match observations at each monitoring site with the observational influence decreasing smoothly across space and time until the output matches the multimodel composite. After estimating at 0.5° resolution using BME, we add fine spatial detail from an additional model, yielding estimates at 0.1° resolution. Observed ozone is predicted more accurately (R2 = 0.81 at the test point, 0.63 at 0.1°, and 0.62 at 0.5°) than the multimodel mean (R2 = 0.28 at 0.5°). Global ozone exposure is estimated to be increasing, driven by highly populated regions of Asia and Africa, despite decreases in the United States and Russia.
Tropospheric ozone (O3) pollution is a major air quality issue for human health, vegetation, and climate worldwide. Through an extensive literature review, this paper reports robust short-term O3 trends over the last three decades and provides insights on the effect of regional emission control policies on O3 levels. Since the 1990s, anthropogenic O3 precursor emissions have decreased in North America and Europe, while Eastern Asian emissions slightly decreased recently. A reduction in O3 mean concentrations was observed in rural areas (on average 0.23 ppb year⁻¹) in North America and Europe since the 1990s, while slight decreases were recently reported in East Asia. Most studies have reported significant increases in urban areas worldwide (on average + 0.31 ppb year⁻¹) and at regional background stations (on average + 0.15 ppb year⁻¹) since the 1990s. The increase in urban O3 concentrations can be attributed to decreased local NOx emissions, due to, e.g., vehicle emission controls, resulting in lower O3 titration by NO. The global background O3 increase can be driven by the net impacts of climate change, such as an increase in stratospheric O3 inputs, higher CH4 emissions, changing lightning NOx emissions, and weakened NO titration.
Most cities in China are experiencing severe air pollution due to rapid economic development and accelerated industrialization. Exposure to various air pollutants has been related to acute exacerbations of chronic obstructive pulmonary disease (AECOPD). However, less is known about the spatial association between air pollution and AECOPD hospitalizations in the Yangtze River delta (YRD) economic and industrial region. Jinhua city is located in the YRD region of East China, in the middle of Zhejiang province. For the first time, 1563 AECOPD hospitalization cases in Jinhua during 2019 were enrolled in our analysis. The spatial distribution of six pollutants (SO2, CO, PM10, PM2.5, O3, NO2) and the population temporal-spatial specific air pollutant exposure levels were estimated using the ordinary Kriging model through geographic information system (GIS). Global Moran’s I was used to explore the spatial association between ambient air pollutants and AECOPD hospitalizations. The Z-scores of residential SO2, CO, PM10, PM2.5, O3, and NO2 levels were 31.88, 42.95, 45.90, 32.29, 52.18, and 34.59, respectively. The concentrations of six monitored pollutants and AECOPD hospitalizations showed statistically significant spatial clustering. A generalized linear model (GLM) using a Poisson distribution with the log-link function was used to construct a core model. After adjusting for potential confounders in the model, residential SO2, NO2 and O3 concentrations were significantly associated with increased AECOPD hospitalizations.
The representation of air quality and meteorology over Asia remains challenging for chemical transport models
as a result of the complex interactions between the East Asian monsoons and the large uncertainty (in space and
time) of the high anthropogenic emissions levels over the region. High spatial resolution models allow resolving
small-scale features induced by the complex topography of this region. In this study, the Weather Research and
Forecasting model with Chemistry (WRF-Chem) was used to simulate the spatial and seasonal variability of main
physical and chemical variables over Asia for the year 2015 at 8-km horizontal resolution to enable resolving
small-scale features induced by the region complex topography. The simulated atmospheric composition was
evaluated against satellite retrievals (MOPITT, IASI + GOME2, MODIS and OMI) in addition to ground-based
observations in China for the year 2015, while the meteorological variables were evaluated by several
observational-based datasets (ERA5, CRU, MODIS, MTE). Results showed low to moderate seasonal biases for
major meteorological variables, i.e. air temperature, relative humidity, precipitation, latent heat, sensible heat
and snow cover fraction. Overall, WRF-Chem reproduced well the spatial and seasonal variability of lowermost
tropospheric ozone content, total column carbon monoxide and aerosol optical depth, while large discrepancies
were found for tropospheric nitrogen dioxide content, mainly during the warm season. In consistency with
previous studies, the different biases between model-simulated and satellite-retrieved values can be mainly
attributed to i) the large uncertainties in anthropogenic and natural nitrogen oxides emission estimates, as well
as dust and sea salt emissions in the case of aerosol optical depth, and ii) some coarse parameterizations used to
reproduce main small-scale features (e.g. meteorology, chemical processes, dry deposition to vegetation).
Compared to ground-based observations, the WRF-Chem model reproduced well the mean annual cycle of
surface nitrogen dioxide, ozone and fine particles concentrations in all seasons across China. Our results suggest
that WRF-Chem provides reliable spatio-temporal patterns for most of the meteorological and chemical variables,
adding thus confidence to its applicability in the context of air pollution risk assessment to human and ecosystems health.
Studying weekend-weekday variation in ground-level ozone (O3) allows one to better understand O3 formation conditions, with a potential for developing effective strategies for O3 control. Reducing inappropriately the O3 precursors emissions can either produce no reduction or increase surface O3 concentrations. This paper analyzes the weekend-weekday differences of O3 at 300 rural and 808 urban background stations worldwide from 2005 to 2014, in order to investigate the O3 weekend effect over time and assess the effectiveness of the precursors emissions control policies for reducing O3 levels. Data were analyzed with the non-parametric Mann-Kendall test and Theil-Sen estimator. Rural sites typically did not experience a weekend-weekday effect. In all urban stations, the mean O3 concentration on the weekend was 12% higher than on weekdays. Between 2005 and 2014, the annual mean of daily O3 concentrations increased at 74% of urban sites worldwide (+0.41 ppb year-1) and decreased in the United Kingdom (- 0.18 ppb year-1). Over this time period, emissions of O3 precursors declined significantly. However, a greater decline in nitrogen oxides (NOx) emissions caused an increase in Volatile Organic Compounds (VOCs) to NOx ratios leading to O3 formation. In France, South Korea and the United Kingdom, most urban stations showed a significant upward trend (+1.15% per year) for O3 weekend effect. Conversely, in Canada, Germany, Japan, Italy and the United States, the O3 weekend effect showed a significant downward trend (- 0.26% per year). Further or inappropriate control of anthropogenic emissions in Canada, Southern Europe, Japan, South Korea and the United States might result in increased daily O3 levels in urban areas.
Ozone (O3) is a natural component of the atmosphere. It occurs in the stratosphere, where it protects biota against ultraviolet radiation, but also in the lower troposphere, where it can directly harm biota. Because of its i) high toxicological potential for biota, ii) high reactivity and molecular instability, and iii) difficult differentiation from other reactive oxygen species, O3 challenges scientists in a continuing effort to develop methods for its monitoring. We present here the operation principles of the most used techniques, along with some new technological developments for atmospheric O3 monitoring, with emphasis upon near surface. Huge amounts of scientific data have been produced thanks to progresses in O3 monitoring technologies. However, it remains a challenge to further develop reliable methods with rapid response and high sensitivity to ambient O3, which will also be free from the disadvantages of the current technologies. The link is: https://doi.org/10.1016/j.coesh.2020.07.004
According to the epidemiological surveys, ambient air pollution has directly related to mortality and different diseases such as cardiovascular and respiratory defects. Among the atmospheric contaminants, criteria air ones (NO2, O3, PM2.5/10, SO2) demonstrated that have particular importance in the community disease. The overall goal of this paper was to study the impact of criteria air contaminants on the health of the inhabitants of Shiraz city, Iran. To accomplish this, the AirQ2.2.3 software was applied. The results of the study revealed that the annual average NO2, SO2, PM2.5, PM10, and O3 concentrations are 39.98, 27.6, 14.35, 46.16, and 120.03 μg/m³ in 2016 and 30.27, 23.97, 16.45, 51.65, and 52.58 μg/m³ in 2017. The total International Classification of Diseases (ICD), cardiovascular, and respiratory mortalities caused by air contaminants in Shiraz was predicted as 911, 628, and 182 cases in 2016, and 346, 370, and 82 cases in 2017, respectively. Sulfur dioxide (SO2) had the greatest rate of total mortality with the attributable equivalent of 4.3% in 2016, but this value has been decreased to 0.42% in 2017. The findings of this research revealed that air contamination has caused problems in Shiraz city according to the predicted results. The findings of this work provide useful data for regional and national health policymakers, who should take decisions to develop strategies for control air contaminants and estimate the cost-effectiveness of interventions.
Because ozone is a highly reactive trace gas, estimates of its contribution to climate forcing must rely on global chemistry-transport models. These models employ many uncertain input parameters representing the sources and sinks for tropospheric ozone. Ten thousand quasi-randomly Monte Carlo sampled model runs employing a zonally-averaged global ozone model were completed and the output uncertainties were estimated in the burdens and turnovers of methane, carbon monoxide and ozone, together with the uncertainties in the ozone seasonal cycles. Multiple regression was then used to attribute the uncertainty in each output metric to each of the 183 uncertain input parameters which represented emission source sectors, chemical and photochemical rate coefficients, dry deposition velocities and biases in temperature and water vapour concentrations. We have tentatively identified sixteen chemical and photochemical rate coefficients, eight emission source sectors, ozone dry deposition and biases in temperature and water vapour as contributing most to the uncertainties in our chosen output metrics. Ten out of the sixteen chemical processes turned out to be the most important processes in the fast, photochemical balance of the troposphere. Emissions from NOx, methane, carbon monoxide and isoprene had the potential to contribute in a major way to model output uncertainties. There are, however, many limitations to our study, not the least being our use of a two-dimensional (altitude-latitude) ozone model. We have not been able to resolve the apparent conflicts between our model and the observations of ozone seasonal cycles and these must await a more rigorous treatment of tropospheric ozone sources and sinks before they can be resolved.
Ozone (O3) in the troposphere, an air pollutant with phytotoxicity, is considered as a driver of global warming, because it reduces plant carbon fixation. Recently, a process-based plant growth model has been used in evaluating the O3 impacts on plants (Schauberger et al., 2019). To make the evaluation more rigorous, we developed a plant growth model and clarified the key factors driving O3-induced change in the whole-plant carbon fixation amount (Cfix). Fagus crenata seedlings were exposed to three O3 levels (charcoal-filtered air or 1.0- or 1.5-folds ambient [O3]) with three soil fertilization levels (non-, low-, or high-fertilized), i.e., a total of nine treatments. The Cfix was reduced in non- and low-fertilized treatments but was unaffected in high-fertilized treatment by O3 fumigation. Our plant growth model could simulate Cfix accurately (<10% error) by considering the impacts of O3 on plant leaf area and photosynthetic capacities, including maximum velocities of carboxylation and electron transport (Vcmax and Jmax, respectively), and the initial slope and convexity of the curve of the electron transport velocity response to photosynthetic photon flux density (φ and θ, respectively). Furthermore, the model revealed that changes in Vcmax and Jmax, φ and θ, or leaf area, caused by 1.5-folds the ambient [O3] fumigation resulted in the following Cfix changes: -1.6, -5.8, or -16.4% in non-fertilized seedlings, -4.1, -4.4, or -9.3% in low-fertilized seedlings, and -4.6, -7.6, or +5.8% in high-fertilized seedlings. Therefore, photosynthetic capacities (particularly φ and θ) and leaf area are important factors influencing the impact of O3 on Cfix of F. crenata seedlings grown under various fertilization levels. Further, the impacts of O3 and soil nutrient on these photosynthetic capacities and plant leaf area should be considered to predict O3-induced changes in carbon fixation by forest tree species using the process-based plant growth model.
The purpose of this study was to assess the impact to human health of air pollutants, through the integration of different technics: data statistics (spatial and temporal trends), population attributable fraction using AIRQ+ model developed by the WHO, and burden of disease using Disability-Adjusted Life Years (DALYs). The levels of SO2, NO, NO2, O3, H2S, benzene, PM10, PM2.5, CO, benzo(a)pyrene and metals, obtained between 2005 and 2017 from the air quality monitoring network across Camp de Tarragona County, were temporally and spatially determined. Health impacts were evaluated using the AIRQ+ model. Finally, the burden of disease was assessed through the calculation of Years of Lost life (YLL) and Years Lost due to Disability (YLD). In general terms, air quality was good according to European quality standards, but it did not fulfil the WHO guidelines, especially for O3, PM10 and PM2.5. Several decreasing (NO, NO2, SO2, PM10 and benzene) and an increasing (O3) temporal trend were found. Correlation between unemployment rate and air pollutant levels was found, pointing that the economic crisis (2008-2014) was a factor influencing the air pollutant levels. Reduction of air pollutant levels (PM2.5) to WHO guidelines in the Camp de Tarragona County would decrease the adult mortality between 23 and 297 cases per year, which means between 0.5 and 7% of all mortality in the area. In this County, for lung cancer, ischemic heart disease, stroke, and chronic obstructive pulmonary disease due to levels of PM2.5 above the WHO threshold limits, DAYLs were 240 years. This means around 80 DALYs for 100,000 persons every year -between 2005 and 2017. Population attributable fraction (PAF) and burden of disease (DALYs) methodologies are suitable tools for regional and national policymakers, who must take decisions to prevent and to control air pollution and to analyse the cost-effectiveness of interventions.
China's economic growth has significantly increased emissions of tropospheric ozone (O 3) precursors, resulting in increased regional O 3 pollution. We analyzed data from > 1400 monitoring stations and estimated the exposure of population and vegetation (crops and forests) to O 3 pollution across China in 2015. Based on WHO metrics for human health protection, the current O 3 level leads to +0.9% premature mortality (59,844 additional cases a year) with 96% of populated areas showing O 3-induced premature death. For vegetation, O 3 reduces annual forest tree biomass growth by 11-13% and yield of rice and wheat by 8% and 6%, respectively, relative to conditions below the respective AOT40 critical levels (CL). These CLs are exceeded over 98%, 75% and 83% of the areas of forests, rice and wheat, respectively. Using O 3 exposure-response functions, we evaluated the costs of O 3-induced losses in rice (7.
Data from experiments where field-grown wheat was exposed to ozone were collated in order to compare the effects in Europe, Asia and North America using dose-response regression. In addition to grain yield, average grain mass and harvest index were included to reflect the influence of ozone on the crop growth pattern. In order to include as many experiments as possible, daytime average ozone concentration was used as the ozone exposure index, but AOT40, estimated from average ozone concentrations, was also used to compare the performance of the two exposure metrics. The response to ozone differed significantly between the continents only for grain yield when using AOT40 as the exposure index. North American wheat was less sensitive than European and Asian that responded similarly. The variation in responses across all three continents was smallest for harvest index, followed by grain mass and grain yield. The highly consistent effect on harvest index shows that not only effects on biomass accumulation, but also on the partitioning of biomass, are important for the ozone-induced grain yield loss in wheat. The average duration of daily ozone exposure was longer in European experiments compared to North American and Asian. It cannot be excluded that this contributed to the indicated higher ozone sensitivity in European wheat in relation to North American. The main conclusions from this study are that on the average the response of wheat to ozone was lower for the older North American experiments and that the ozone response of the growth pattern reflected by grain mass and harvest index did not differ between continents.
Ozone pollution can severely diminish crop yields. Its damaging effects depend, apart from ozone concentration, on crop, cultivar, water status, temperature and CO2 concentration. Previous studies estimating global yield loss from ozone pollution did not consider all of these co-factors and climate change impact studies on crop yields typically ignore ozone pollution. Here we introduce an ozone damage module for the widely used process-based crop model LPJmL. The implementation describes ozone uptake through stomata, internal detoxification and short- and long-term effects on productivity and phenology, dynamically accounting for all listed co-factors. Using this enhanced model we estimate historical global yield losses from ozone pollution for wheat and soybeans. We divide wheat into “Western” and “Asian” to account for higher ozone sensitivities in Asian types. We apply daily ozone concentrations obtained from six chemistry-transport models provided by the ACCMIP and HTAP2 projects.
Our implementation of ozone damage follows expected dynamics, for example damage amplification under irrigation. The model is able to reproduce results from chamber and field studies. Historical ozone-induced losses between 2008 and 2010 vary between countries, and we estimate these between 2 and 10% of ozone-free yields for soybeans, between 0 and 27% for Western wheat and 4 and 39% for Asian wheat.
Our study highlights the threat of ozone pollution for global crop production and improves over previous studies by considering co-factors of ozone damage. Uncertainties of our study include the extrapolation from rather few point observations to the globe, possible biases in ozone data, omission of sub-daily fluctuations in ozone concentration or stomatal conductance and the averaging of different cultivars across regions. We suggest performing further field-scale experimental studies of ozone effects on crops, as these are currently rare but would be particularly helpful to evaluate models and to estimate large-scale effects of ozone.
We calculate ozone radiative forcing (RF) and stratospheric temperature adjustments for the period 1850-2014 using the newly available CMIP6 ozone dataset. The CMIP6 total ozone RF (1850s-2000s) is 0.28±0.17 Wm−2 (which is 80% higher than our CMIP5 estimation), and 0.30±0.17 Wm−2 out to the present day (2014). The total ozone RF grows rapidly until the 1970s, slows towards the 2000s, and shows a renewed growth thereafter. Since the 1990s the shortwave RF exceeds the longwave RF. Global stratospheric ozone RF is positive between 1930 and 1970 and then turns negative, but remains positive in the Northern Hemisphere throughout. Derived stratospheric temperature changes show a localized cooling in the sub-tropical lower stratosphere due to tropospheric ozone increases, and cooling in the upper stratosphere due to ozone depletion by more than 1K already prior to the satellite era (1980), and by more than 2K out to the present day (2014).
Iranian western cities, including Hamadan, have been experiencing Middle East Dust Storms (MEDS) phenomenon problems in recent years, so the air quality is getting worse every year in these cities. The aim of this study was to evaluate the human health impacts of criteria air pollutants including PM10, PM2.5, NO2, SO2, CO and O3 on the citizens of Hamadan using AirQ model software 2.2.3. Considering the determined baseline incidence (BI) and relative risk (RR) rate, the attributable proportion (AP) of deaths due to cardiovascular and respiratory mortality attributed to PM2.5, PM10, O3, NO2, and CO pollutants was estimated to be 4.42%, 3.37%, 1.75%, 1.74% and 0.92% (95% CI) of the total mortality and the excess death cases were respectively estimated to be 131.9, 100.4, 52.1, 51.9 and 27.3 persons. In addition, cardiovascular mortality brings more contribution than respiratory mortality in total death number. The results of our study also showed that PM2.5 poses the greatest health effects on the citizens. Analyzing the average seasonal concentrations of studied pollutants (PM10, PM2.5, and NO2) and the mean seasonal temperature values revealed a positive linear correlation. Significant negative correlations were observed between the studied pollutants (PM10, PM2.5 and NO2) and relative humidity, and between PM and wind speed. This study, therefore, provides additional data in decision-makings for the development of strategies for reduction of ambient air pollution which will result in improvements of air quality.
We processed hourly ozone (O3) concentrations collected in 2015 and in 2016 by a network of 1497 stations across China, with the main aim of assessing the risk that present ambient O3 exposure is posing to Chinese forests. Our results indicate that the values of the metrics AOT40 (the accumulated hourly O3 concentrations above 40 ppb during daylight hours) recommended as European Union standard, and W126 (the sum of weighted hourly concentrations from 8:00 to 20:00) recommended as USA standard for forest protection, exceeded the critical levels (5 ppm h across 6 months for AOT40 and 7-21 ppm h over 3 months for W126) on average by 5.1 and 1.2 times, respectively. N100 showed on average 65 annual exceedances of 100 ppb as hourly value. The 12-h and 24-h averages showed a small difference, suggesting high concentrations also at night. Risk was higher for the northern temperate climate than for the southern tropical and sub-tropical climates, and overall for the northern regions than for the southern regions. Higher risk occurred in the non-urban areas than in the urban areas in northern, south-west and north-west China, whereas risk was higher at urban areas in eastern and southern China. The overall results of this first nationwide assessment suggest a significant risk for forests over the entire China and warrant for urgent measures for controlling O3 precursor emissions and establishing standards of protection.
Stratospheric intrusions have been the interest of decades of research for their ability to bring stratospheric ozone (O3) into the troposphere with the potential to enhance surface O3 concentrations. However, these intrusions have been misrepresented in models and reanalyses until recently, as the features of a stratospheric intrusion are best identified in horizontal resolutions of 50 km or smaller. NASA's Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) reanalysis is a publicly-available high-resolution dataset (∼50 km) with assimilated O3 that characterizes O3 on the same spatiotemporal resolution as the meteorology. We demonstrate the science capabilities of the MERRA-2 reanalysis when applied to the evaluation of stratospheric intrusions that impact surface air quality. This is demonstrated through a case study analysis of stratospheric intrusion-influenced O3 exceedences in spring 2012 in Colorado, using a combination of observations, the MERRA-2 reanalysis and Goddard Earth Observing System Model, Version 5 (GEOS-5) simulations.
We modelled the effects of past and expected future changes in climate (temperature, precipitation), CO2 concentration, nitrogen deposition (N) and ozone (O3) exposure (phytotoxic ozone dose, POD) on carbon (C) sequestration by European forest ecosystems for the period 1900–2050. Tree C sequestration was assessed by using empirical response functions, while soil C sequestration was simulated with the process-based model VSD, combined with the RothC model. We evaluated two empirical growth responses to N deposition (linear and non-linear) and two O3 exposure relationships (linear function with total biomass or net annual increment). We further investigated an ‘interactive model’ with interactions between drivers and a ‘multiplicative model’, in which the combined effect is the product of individual drivers. A single deposition and climate scenario was used for the period 1900–2050. Contrary to expectations, growth observations at European level for the period 1950–2010 compared better with predictions by the multiplicative model than with the interactive model. This coincides with the fact that carbon responses in kg C ha− 1 yr− 1 per unit change in drivers, i.e. per °C, ppm CO2, kg N ha− 1 yr− 1 and mmol m− 2 yr− 1 POD, are more in line with literature data when using the multiplicative model. Compared to 1900, the estimated European average total C sequestration in both forests and forest soils between 1950 and 2000 increased by 21% in the interactive model and by 41% in the multiplicative model, but observed changes were even higher. This growth increase is expected to decline between 2000 and 2050. The simulated changes between 1950 and 2000 were mainly due to the increase in both N deposition and CO2, while the predicted increases between 2000 and 2050 were mainly caused by the increase in CO2 and temperature, and to lesser extent a decrease in POD, counteracted by reduced N deposition.
The performance of a modeling system consisting of WRF model v3.4.1 and CMAQ model v4.7.1 for forecasting fine particle concentrations were evaluated using measurement data at the surface. Twenty-four hour averages of PM2.5 and its major components at Bulgwang (located in the northwest of Seoul) during the period February 2012 through January 2013 were compared with predicted concentrations as well as hourly averages of inorganic ions measured at Yongin (located to the southeast of Seoul) in spring 2012. The mean fractional bias (MFB) of –0.37 for PM2.5 at Bulgwang fell just outside the goal of –0.3, the level of accuracy that the best model can be achieved. Negative values of MFB, especially in winter, along with the correlation coefficient of 0.61 between measured and predicted concentrations showed that the model performance at Bulgwang was closer to that for Europe than that for North America. However, underestimation of SO42– and overestimation of NO3– were similarly observed at Bulgwang as in the United States. Although diurnal variations in the measured values showed distinctive features at Yongin according to the classified patterns, most variations in the predicted values typically showed a peak early in the morning followed by an increase at night.
We present an overview of state-of-the-art chemistry-climate and -transport models that are used within the Chemistry Climate Model Initiative (CCMI). CCMI aims to conduct a detailed evaluation of participating models using process-oriented diagnostics derived from observations in order to gain confidence in the models’ projections of the stratospheric ozone layer, air quality, where applicable global climate change, and the interactions between them. Interpretation of these diagnostics requires detailed knowledge of the radiative, chemical, dynamical, and physical processes incorporated in the models. Also an understanding of the degree to which CCMI recommendations for simulations have been followed is necessary to understand model response to anthropogenic and natural forcing and also to explain inter-model differences. This becomes even more important given the ongoing development and the ever-growing complexity of these models. This paper also provides an overview of the available CCMI simulations with the aim to inform CCMI data users.
Millions of people die every year from diseases caused by exposure to outdoor air pollution. Some studies have estimated premature mortality related to local sources of air pollution but local air quality can also be affected by atmospheric transport of pollution from distant sources. International trade is contributing to the globalization of emission and pollution as a result of the production of goods (and their associated emissions) in one region for consumption in another region. The effects of international trade on air pollutant emissions, air quality and health have been investigated regionally, but a combined, global assessment of the health impacts related to international trade and the transport of atmospheric air pollution is lacking. Here we combine four global models to estimate premature mortality caused by fine particulate matter (PM_(2.5)) pollution as a result of atmospheric transport and the production and consumption of goods and services in different world regions. We find that, of the 3.45 million premature deaths related to PM_(2.5) pollution in 2007 worldwide, about 12 per cent (411,100 deaths) were related to air pollutants emitted in a region of the world other than that in which the death occurred, and about 22 per cent (762,400 deaths) were associated with goods and services produced in one region for consumption in another. For example, PM_(2.5) pollution produced in China in 2007 is linked to more than 64,800 premature deaths in regions other than China, including more than 3,100 premature deaths in western Europe and the USA; on the other hand, consumption in western Europe and the USA is linked to more than 108,600 premature deaths in China. Our results reveal that the transboundary health impacts of PM_(2.5) pollution associated with international trade are greater than those associated with long-distance atmospheric pollutant transport.