The impact of climate change and emissions control on future ozone levels: Implications for human health

Understanding the spatial and seasonal variation of the ground-level ozone in Southeast China with an interpretable machine learning and multi-source remote sensing

Ground-level ozone (O3) pollution poses significant threats to both human health and air quality. This study uses ground observations and satellite retrievals to explore the spatiotemporal characteristics of ground-level O3 in Zhejiang Province, China. We created data-driven machine learning models that include meteorological, geographical and atmospheric parameters from multi-source remote sensing products, achieving good performance (Pearson's r of 0.81) in explaining regional O3 dynamics. Analyses revealed the crucial roles of temperature, relative humidity, total column O3, and the distributions and interactions of precursor (volatile organic compounds and nitrogen oxides) in driving the varied O3 patterns observed in Zhejiang. Furthermore, the interpretable modeling quantified multifactor interactions that sustain high O3 levels in spring and autumn, suppress O3 levels in summer, and inhibit O3 formation in winter. This work demonstrates the value of a combined approach using satellite and machine learning as an effective novel tool for regional air quality assessment and control.

Kinetic and Thermodynamic Characteristics of Torrefied Acer palmatum

The goal of this research was to investigate the effects of torrefying temperature (220, 260, and 300 °C) on the physicochemical properties, kinetics, thermodynamic parameters, and reaction processes of Acer palmatum (AP) during the pyrolysis process. The kinetics of raw materials and torrefied biomass were studied by using three kinetic models, and the main function graph approach was employed to find the reaction mechanism. The torrefied biomass produced at temperatures of 220 °C (AP-220), 260 °C (AP-260), and 300 °C (AP-300) was thermogravimetrically analyzed at four different heating rates (5, 10, 15, and 20 °C/min). In comparison to the raw material, the average activation energy of torrefied biomass declined with increasing temperature, from 174.13 to 84.67 kJ/mol (FWO), 172.52 to 81.24 kJ/mol (KAS and DAEM). The volatile contents of AP and AP-220 are higher than those of AP-260 and AP-300, indicating that the random nucleation model occupies the central position. Compared with the raw biomass, the average Gibbs free energy (ΔG) of torrefied biomass increased from 157.97 to 195.38 kJ/mol. The mean enthalpy change (ΔH) during the torrefaction process is positive, while the mean entropy change (ΔS) of the torrefaction of biomass is negative, decreasing from 16.93 to -151.53 kJ/mol (FWO) and from 14.36 to -156.06 kJ/mol (KAS and DAEM). Overall, the findings provide a comprehensive understanding of the kinetics and improved features of torrefied biomass as a high-quality solid fuel.

Impact of spatial scales of control measures on the effectiveness of ozone pollution mitigation in eastern China

Ozone (O3) pollution is becoming the primary air pollution issue with the large decrease in fine particulate concentrations in eastern China. The development of widely recognized policies for controlling O3 pollution episodes is urgent. This study aims to provide actionable and comprehensive suggestions for O3 control policy development, with an emphasis on the precursor emission reductions. Here, we compared the impacts of different spatial scale reductions on a widespread O3 pollution episode in eastern China by a state-of-the-art regional air quality model. We find that region-scale joint control (in >30 cities) is much more effective than city-scale sporadic reduction in reducing O3 concentration. Sporadic controls only reduce the maximum daily 8-h average (MDA8) O3 by ∼1 μg/m3 in the controlled city, whereas regional controls lead to a MDA8 O3 decrease of ∼8 μg/m3 in the controlled region. In addition, the emission reduction effectiveness increased by 2.6 times from <5 cities to >30 cities. Continuous reductions have a cumulative effect on the decrease of MDA8 O3, showing the strongest effects within 24 h and diminishing after 48 h, which underscores the importance of reducing emissions 24 h prior to an episode. Moreover, the effect of control measures on MDA8 O3 varies spatially depending on the ratio of volatile organic compounds (VOCs) to nitrogen oxides (NOx) (VOCs/NOx). Both the reductions of VOC and NOx emissions have a positive effect on the decrease of MDA8 O3 in summer, but the effects of VOC reductions are 1.2 to 1.7 times higher than those of NOx reductions. The residential sector, due to its high VOCs/NOx emission ratio, exhibits the highest efficiency in the reduction of O3 concentrations. Our results highlight the importance of regional joint control and synergistic reduction of VOCs and NOx in eastern China.

Estimates of biomass reductions of ozone sensitive herbaceous plants in California

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

Emission characteristics and inventory of volatile organic compounds from the Chinese cement industry based on field measurements

Volatile organic compounds (VOCs) are major precursors of ozone (O₃) and secondary organic aerosols (SOA), which degrade air quality and pose a serious risk to human health and ecological systems. Previous studies on the emission characteristics of VOCs have predominantly focused on petrochemical and solvent-using sources, while localized studies on the cement industry are scarce in China. Field measurements for four cement plants were carried out in this study to investigate the emission levels, source profiles, and secondary pollutant generation potential of 98 VOCs species emitted from rotary and shaft kilns in China. Furthermore, a species-differentiated VOCs emission inventory was compiled for the Chinese cement industry in 2019. The results demonstrated that the mass concentration of VOCs emitted from shaft kiln was more than 20-fold higher than that emitted from rotary kilns, and the alkanes was the dominant species (56%) in shaft kilns, while oxygenated VOCs (OVOCs) and halocarbons were the main species in rotary kilns. Moreover, alkenes & alkyne were the dominant contributors to ozone formation potential (OFP) in shaft kilns, whereas alkenes & alkyne and OVOCs were comparable and prominent contributors in rotary kilns. In contrast, secondary organic aerosol potential (SOAP) for the two types of kilns was dominated by aromatics. In 2019, approximately 18.18 kt VOCs were emitted from cement production and were found to be largely concentrated in the southeast and central provinces of China. Considering the influence on environmental conditions, high OFP-contributing species in cement kilns are suggested to be a priority in the pollution mitigation of O₃. This study provides a new, comprehensive, and reasonable cognition of the current VOCs emissions from both rotary and shaft kilns in China, which will aid in a better understanding of VOCs emission characteristics and guide future policy-making.

Mild allergic airways responses to an environmental mixture increase cardiovascular risk in rats

Recent epidemiological findings link asthma to adverse cardiovascular responses. Yet, the precise cardiovascular impacts of asthma have been challenging to disentangle from the potential cardiovascular effects caused by asthma medication. The purpose of this study was to determine the impacts of allergic airways disease alone on cardiovascular function in an experimental model. Female Wistar rats were intranasally sensitized and then challenged once per week for 5 weeks with saline vehicle or a mixture of environmental allergens (ragweed, house dust mite, and Aspergillus fumigatus). Ventilatory and cardiovascular function, measured using double-chamber plethysmography and implantable blood pressure (BP) telemetry and cardiovascular ultrasound, respectively, were assessed before sensitization and after single and final allergen challenge. Responses to a single 0.5 ppm ozone exposure and to the cardiac arrhythmogenic agent aconitine were also assessed after final challenge. A single allergen challenge in sensitized rats increased tidal volume and specific airways resistance in response to provocation with methacholine and increased bronchoalveolar lavage fluid (BALF) eosinophils, neutrophils, lymphocytes, cytokines interleukin (IL)-4, IL-5, IL-10, IL-1β, tumor necrosis factor-α, and keratinocyte chemoattract-growth-related oncogene characteristic of allergic airways responses. Lung responses after final allergen challenge in sensitized rats were diminished, although ozone exposure increased BALF IL-6, IL-13, IL-1 β, and interferon-γ and modified ventilatory responses only in the allergen group. Final allergen challenge also increased systolic and mean arterial BP, stroke volume, cardiac output, end-diastolic volume, sensitivity to aconitine-induced cardiac arrhythmia, and cardiac gene expression with lesser effects after a single challenge. These findings demonstrate that allergic airways responses may increase cardiovascular risk in part by altering BP and myocardial function and by causing cardiac electrical instability.

A Review of the Impact That Healthcare Risk Waste Treatment Technologies Have on the Environment

Health-Care Risk Waste (HCRW) treatment protects the environment and lives. HCRW is waste from patient diagnostics, immunization, surgery, and therapy. HCRW must be treated before disposal since it pollutes, spreads illnesses, and causes harm. However, waste treatment increases the healthcare sector's carbon footprint, making the healthcare sector a major contributor to anthropogenic climate change. This is because treating HCRW pollutes the environment and requires a lot of energy. Treating HCRW is crucial, but its risks are not well-studied. Unintentionally, treating HCRW leads to climate change. Due to frequent climate-related disasters, present climate-change mitigation strategies are insufficient. All sectors, including healthcare, must act to mitigate and prevent future harms. Healthcare can reduce its carbon footprint to help the environment. All contributing elements must be investigated because healthcare facilities contribute to climate change. We start by evaluating the environmental impact of different HCRW treatment technologies and suggesting strategies to make treatments more sustainable, cost-effective, and reliable to lower the carbon footprint.

Short-term exposure to ozone and economic burden of premature mortality in Italy: A nationwide observation study

Italy is among the countries with the highest ozone concentration in Europe. However, the mortality burden of ozone and related economic loss has not been fully characterized. This study aimed to estimate the ozone-mortality association in Italy and evaluate attributable mortality burden and related economic loss in 2015-2019. We collected daily all-cause mortality data stratified by age and sex from 2015 to 2019 in 107 provinces of Italy. A two-stage time-series framework was applied to estimate the association between daily maximum eight-hour average ozone and mortality as well as economic loss. An overall increase in the risk of mortality (RR=1.0043, 95% CI: 1.0029, 1.0057) was associated with every 10 µg/m³ increase in ozone. Generally, a total of 70,060 deaths and $65 billion economic loss were attributed to ozone exposure, corresponding to 3.11% of mortality and about 0.5% of the national GDP during the study period, respectively. The highest ozone-related mortality burden (30,910 deaths) and economic loss ($29.24 billion) were observed in the hot season. This nationwide study suggested considerable mortality burden and economic loss were associated with exposure to ozone. More actions and policies should be proposed to reduce ozone levels and help the public protect their health.

Analysis of the Effect of Catalytic Additives in the Agricultural Waste Combustion Process

This paper presents the research results of the effect of using calcium oxide and potassium permanganate on the combustion of pellets from wheat bran and beet pulp. The measurements were performed in the technical laboratory of the Centre of Energy Utilization of Non-Traditional Energy Sources in Ostrava. The research examined the effect of the use of chemical substances on the amount of air pollutants from biomass thermal conversion in a low-power boiler and the process temperature. First, we performed technical and elementary analyses of agricultural waste. The raw material was then comminuted, mixed with a selected additive, pelletized, and finally burned in a low-power boiler. The additive was added in three proportions: 1:20, 1:10, and 1:6.67 (i.e., 15%) relative to the fuel weight. The combustion process efficiency was measured using a flue gas analyzer and three thermocouples attached to the data recorder. From the measurement results, we were able to determine the percentage reduction of pollutant emissions into the atmosphere (CO, NOx, and SO2) due to the use of additives. Because emission standards are becoming increasingly stringent and fuel and energy prices are rising, the results presented in this article may be useful to agri-food processing plants that want to manage these materials thermally.

Low- and Medium-Cost Sensors for Tropospheric Ozone Monitoring—Results of an Evaluation Study in Wrocław, Poland

The paper presents the results of a 1.5-year evaluation study of low- and medium-cost ozone sensors. The tests covered electrochemical sensors: SensoriC O3 3E 1 (City Technology) and semiconductor gas sensors: SM50 OZU (Aeroqual), SP3-61-00 (FIS) and MQ131 (Winsen). Three copies of each sensor were enclosed in a measurement box and placed near the reference analyser (MLU 400). In the case of SensoriC O3 3E 1 sensors, the R2 values for the 1-h data were above 0.90 for the first 9 months of deployment, but a performance deterioration was observed in the subsequent months (R2 ≈ 0.6), due to sensor ageing processes. High linear relationships were observed for the SM50 devices (R2 > 0.94), but some periodic data offsets were reported, making regular checking and recalibration necessary. Power-law functions were used in the case of SP3-61-00 (R2 = 0.6–0.7) and MQ131 (R2 = 0.4–0.7). Improvements in the fittings were observed for models that included temperature and relative humidity data. In the case of SP3-61-00, the R2 values increased to above 0.82, while for MQ131 they increased to above 0.86. The study also showed that the measurement uncertainty of tested sensors meets the EU Directive 2008/50/EC requirements for indicative measurements and, in some cases, even for fixed measurements.

Comparison of Selected Technologies to Improve the Quality of Exhaust Gases from Landfill Gas Combustion

This paper presents the results of research on exhaust gases from landfill gas combustion. The measurements were carried out in a reclaimed landfill in Kiełcz (a passive degassing system based on gas flare). The research concerned the effects of selected exhaust gas purification technologies (platinum catalyzer on a ceramic carrier, molecular sieve, copper(II) oxide) for the quality of exhaust gases, and their particulate matter content. This paper aims to indicate which catalytic systems are most suitable for this gas type and their most efficient positioning in the flue gas duct. Due to increasingly stringent emission standards, the outcomes presented in this article could be helpful for landfill owners who wish to avoid paying fines for not complying with applicable limits. The measurements were carried out using a flue gas analyser, a particulate matter analyser fitted with a probe, and four thermocouples connected with the data recorder. The research outcomes determined the percentage reduction of pollutant emissions into the atmosphere (CO, NOx, and particulate matter) using catalysts. The potential benefits of using catalysts in landfill gas combustion systems due to their operating temperature ranges are discussed.

Global trade network and CH4 emission outsourcing

The intensifying globalization contributes to the anthropogenic methane (CH₄) emissions outsourcing, a strong greenhouse gas and harmful air pollutant, through the increasingly complex global trade network. However, the CH₄ flow patterns embodied in global traded goods and services have not been interpreted from the perspective of a complex network. In this paper, we integrate global CH₄ emission inventory from the EDGAR (the Emission Database for Global Atmospheric Research) databases, global multi-regional input-output model from the GTAP database, and complex network analysis to reveal the structural characteristics of the global CH₄ flow network (GCFN). In the GCFN, more than one quarter of the global anthropogenic CH₄ emissions in 2014 are associated with international trade. The top 20 economies contribute to about 70% of the total embodied CH₄ emission flows. The GCFNs mainly consist of tripartite patterns centered on China, the USA and Russia. Some emerging countries, such as Thailand and Brazil, also exhibit dominated positions in different kinds of GCFNs. Moreover, the core-periphery structure of the GCFN confirms the existence of a few hub economies associated with a large amount of CH₄ emissions. The results emphasize the multinational cooperation on global CH₄ emission mitigation, and well-focused mitigation policies should be implemented on some key economies.

Mimicking atmospheric photochemical modelling with a deep neural network

Fast and accurate prediction of ambient ozone (O₃) formed from atmospheric photochemical processes is crucial for designing effective O₃ pollution control strategies in the context of climate change. The chemical transport model (CTM) is the fundamental tool for O₃ prediction and policy design, however, existing CTM-based approaches are computationally expensive, and resource burdens limit their usage and effectiveness in air quality management. Here we proposed a novel method (noted as DeepCTM) that using deep learning to mimic CTM simulations to improve the computational efficiency of photochemical modeling. The well-trained DeepCTM successfully reproduces CTM-simulated O₃ concentration using input features of precursor emissions, meteorological factors, and initial conditions. The advantage of the DeepCTM is its high efficiency in identifying the dominant contributors to O₃ formation and quantifying the O₃ response to variations in emissions and meteorology. The emission-meteorology-concentration linkages implied by the DeepCTM are consistent with known mechanisms of atmospheric chemistry, indicating that the DeepCTM is also scientifically reasonable. The DeepCTM application in China suggests that O₃ concentrations are strongly influenced by the initialized O₃ concentration, as well as emission and meteorological factors during daytime when O₃ is formed photochemically. The variation of meteorological factors such as short-wave radiation can also significantly modulate the O₃ chemistry. The DeepCTM developed in this study exhibits great potential for efficiently representing the complex atmospheric system and can provide policymakers with urgently needed information for designing effective control strategies to mitigate O₃ pollution.

A machine learning model to estimate ground-level ozone concentrations in California using TROPOMI data and high-resolution meteorology

Estimating ground-level ozone concentrations is crucial to study the adverse health effects of ozone exposure and better understand the impacts of ground-level ozone on biodiversity and vegetation. However, few studies have attempted to use satellite retrieved ozone as an indicator given their low sensitivity in the boundary layer. Using the Troposphere Monitoring Instrument (TROPOMI)'s total ozone column together with the ozone profile information retrieved by the Ozone Monitoring Instrument (OMI), as TROPOMI ozone profile product has not been released, we developed a machine learning model to estimate daily maximum 8-hour average ground-level ozone concentration at 10 km spatial resolution in California. In addition to satellite parameters, we included meteorological fields from the High-Resolution Rapid Refresh (HRRR) system at 3 km resolution and land-use information as predictors. Our model achieved an overall 10-fold cross-validation (CV) R² of 0.84 with root mean square error (RMSE) of 0.0059 ppm, indicating a good agreement between model predictions and observations. Model predictions showed that the suburb of Los Angeles Metropolitan area had the highest ozone levels, while the Bay Area and the Pacific coast had the lowest. High ozone levels are also seen in Southern California and along the east side of the Central Valley. TROPOMI data improved the estimate of extreme values when compared to a similar model without it. Our study demonstrates the feasibility and value of using TROPOMI data in the spatiotemporal characterization of ground-level ozone concentration.

Distinct spatiotemporal variation patterns of surface ozone in China due to diverse influential factors

A better knowledge of surface ozone variations and the relevant influential factors is of great significance for controlling frequent ozone pollution events. In this study, we first examined the primary variation patterns of surface ozone in space and time across China via a clustering analysis on the basis of daily maximum 8h average surface ozone (MDA8) between 2015 and 2018. Statistical models were then established between MDA8 and a set of influential factors to pinpoint dominant factors contributing to regional MDA8 variations. The clustering results revealed four typical variation patterns of MDA8 in China given distinct pollution levels, seasonality, and long-term trends. Statistical modeling results indicated that the seasonal variability of MDA8 was closely associated with UV radiation and meteorological factors like boundary layer height, temperature and relative humidity. In contrast, the long-term trends of MDA8 were largely linked to ozone precursors and meteorological variables including temperature, relative humidity, and total cloud cover. Moreover, the phenomenal increasing trends of MDA8 in North China were found to be statistically associated with the depletion of nitrogen dioxide (NO₂) and carbon monoxide (CO). Specifically, substantial increases in volatile organic compounds (VOCs) along with depletions in NO₂ and CO significantly boosted the photochemical ozone formation chain process in a VOC-limited regime like the North China plain. Overall, the inferred linkage in this study provides evidence and clues to help control increasing ozone pollution events in North China.

On the association between high outdoor thermo-hygrometric comfort index and severe ground-level ozone: A first investigation

According to the European Environment Agency, the year 2015 was the warmest on record to that point, with a series of heat waves from May to September resulted in high levels of tropospheric ozone. The implications of such a year on the human well-being and health are therefore of multiple nature and can be quantified referring to the exceedances of the corresponding thresholds. This work focused on the analysis of the May-September period of 2015 in the city of Milan (Italy) in terms of Mediterranean Outdoor Comfort Index (MOCI) and ozone concentrations, recorded by monitoring stations and modeled through the Weather Research and Forecasting model. Main findings show that thermo-hygrometric stress events (periods of at least six consecutive days characterized by daily maximum values of the MOCI higher than 0.5) are characterized by daily ozone higher than the guideline level of the World Health Organization (equal to 100 μgm^-3). This means that thermo-hygrometric stress conditions are added up to poor air quality conditions, with severe risks for human health. Moreover, a daily MOCI-daily ozone correlation coefficient equal to 0.6 was found for the whole period. The degree of correspondence between ozone events (defined according to the European Air Quality Directive) and MOCI events was also investigated pointing out that 86% and 95% of days during ozone events are correctly predicted by events of recorded and modeled MOCI respectively, with a corresponding false alarm rate of 3% and 9%.

Revealing the modulation of boundary conditions and governing processes on ozone formation over northern China in June 2017

In this study, ozonesonde data were used to evaluate the impact of different boundary conditions on the vertical distribution of ozone over urban Beijing. The comparison shows that the clean and static boundary conditions, referred to as PROFILE, apparently underestimate the ozone concentration over the upper troposphere and stratosphere, whereas the global chemical transport model (CTM) provides much more reasonable performance. Further investigation reveals that the boundary conditions exert larger impacts over areas with high altitudes and close distances to boundaries, such as the Tibetan Plateau, while they yield weak impacts on regions relatively far from the boundary, such as the North China Plain (NCP). Process analysis was conducted to investigate the modulation of physical and chemical processes on ozone formation in June 2017, illustrating that during the daytime of the high-O₃ period, the photochemical reactions within the planetary boundary layer (PBL) almost become the only source favorable to ozone accumulation. Motivated by this phenomenon, we constructed a linear regression and found that the maximum daily 8-hr ozone (MDA8) ozone concentration was highly correlated with the surface ozone change rate and chemical reactions in the PBL during the pollution period, with MDA8 ozone exceeding 70 ppbv over NCP. Based on this relationship as well as the design of numerical experiments, we propose a strategy of dynamic emission control. Firstly, the emission reduction during the peak ozone formation period may weaken the fast chemical reactions in the PBL and subsequent surface ozone concentration. Secondly, emission reduction one or two days prior to an episode might achieve larger ozone reduction through the accumulation effect. Lastly, emission control outside of the NCP may surpass the local impact under favorable meteorological conditions. Therefore, the efficacy of dynamic emission control was striking when both the accumulation and transport effect were taken into consideration.

A new classification approach to enhance future VOCs emission policies: Taking solvent-consuming industry as an example

Volatile organic compounds (VOCs) has consistently been linked to ozone (O₃) and secondary organic aerosol (SOA) formation, and ongoing emission policies are primarily focusing on total VOCs without addressing the association between regulation measures and secondary pollution characteristic. For enhancing VOCs emission policy, we investigated potential formation of O₃ and SOA based on analyses of node-specific VOCs concentration and species distribution in solvent-consuming industry. Although aromatics were found to contribute most to O₃ and SOA formation averagely (2.57 ± 2.14 g O₃/g VOCs, 1.91 ± 1.67 g SOA/g VOCs), however, large disparity concerning emission and secondary pollution profile were identified among different emission nodes which demonstrated that regulation policy should be formulated based on comprehensive pollution characteristic. Therefore, emission nodes were classified into four clusters through data normalization, formatting and classification process, including aromatics dominated (7 emission nodes), aromatics-alkene dominated (4 emission nodes), aromatics-alcohols dominated (4 emission nodes) and alcohols dominated (4 emission nodes). And different dominating VOCs species were further obtained in each cluster. Subsequently, focusing regulation measures of reducing O₃ and SOA for different emission source clusters were proposed to guide pollution prevention and enhance future VOCs emission policies.

How will air quality effects on human health, crops and ecosystems change in the future?

Future air quality will be driven by changes in air pollutant emissions, but also changes in climate. Here, we review the recent literature on future air quality scenarios and projected changes in effects on human health, crops and ecosystems. While there is overlap in the scenarios and models used for future projections of air quality and climate effects on human health and crops, similar efforts have not been widely conducted for ecosystems. Few studies have conducted joint assessments across more than one sector. Improvements in future air quality effects on human health are seen in emission reduction scenarios that are more ambitious than current legislation. Larger impacts result from changing particulate matter (PM) abundances than ozone burdens. Future global health burdens are dominated by changes in the Asian region. Expected future reductions in ozone outside of Asia will allow for increased crop production. Reductions in PM, although associated with much higher uncertainty, could offset some of this benefit. The responses of ecosystems to air pollution and climate change are long-term, complex, and interactive, and vary widely across biomes and over space and time. Air quality and climate policy should be linked or at least considered holistically, and managed as a multi-media problem. This article is part of a discussion meeting issue 'Air quality, past present and future'.

An Ensemble Learning Approach for Estimating High Spatiotemporal Resolution of Ground-Level Ozone in the Contiguous United States

In this paper, we integrated multiple types of predictor variables and three types of machine learners (neural network, random forest, and gradient boosting) into a geographically weighted ensemble model to estimate the daily maximum 8 h 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 0.86 for annual averages. Overall, the 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 an intra-urban scale.

An Ensemble Learning Approach for Estimating High Spatiotemporal Resolution of Ground-Level Ozone in the Contiguous United States

In this paper, we integrated multiple types of predictor variables and three types of machine learners (neural network, random forest, and gradient boosting) into a geographically weighted ensemble model to estimate the daily maximum 8 h 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 0.86 for annual averages. Overall, the 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 an intra-urban scale.

Impact of weather changes on air quality and related mortality in Spain over a 25 year period [1993-2017]

Climate change is a major public health concern. In addition to its direct impacts on temperature patterns and extreme weather events, climate change affects public health indirectly through its influence on air quality. Pollution trends are not only affected by emissions changes but also by weather changes. In this paper we analyze air quality trends in Spain of important air pollutants (C₆H₆, CO, NO₂, NO_x, O₃, PM₁₀, PM_2.5, and SO₂) recorded during the last 25 years, from 1993 to 2017. We found substantial reductions in ambient concentration levels for all the pollutants studied except for O₃. To assess the influence of recent weather changes on air quality trends we applied generalized additive models (GAMs) using nonparametric smoothing; with and without adjusting for weather parameters including temperature, wind speed, humidity and precipitation frequency. The difference of annual slopes estimated by the models without and with adjusting for these meteorological variables represents the impact of weather changes on pollutant trends, i.e. the 'weather penalty'. The analyses were seasonally and geographically stratified to account for temporal and regional differences across Spain. The results were meta-analyzed to estimate weather penalties on ambient concentration trends at a national level as well as the impact on mortality for the most relevant pollutants. We found significant penalties for most pollutants, implying that air quality would have improved even more during our study period if weather conditions had remained constant. The largest weather influences were found for PM₁₀, with seasonal penalties up to 22 μg⋅m^-3 accumulated over the 25-year period in some regions. The national meta-analysis shows penalties of 0.060 μg⋅m^-3 per year (95% Confidence Interval, CI: 0.004, 0.116) in cold months and 0.127 μg⋅m^-3 per year (95% CI: 0.089, 0.164) in warm months. Penalties of this magnitude would correspond to 129 annual deaths (95% CI: 25, 233), i.e. approximately 3200 deaths over the 25-year period in Spain. According to our results, the health benefits of recent emission abatements for this pollutant in Spain would have been up to 10% greater if weather conditions had remained constant during the last 25 years.

Hands-on Tutorial on a Modeling Framework for Projections of Climate Change Impacts on Health

Supplemental Digital Content is available in the text.

Reliable estimates of future health impacts due to climate change are needed to inform and contribute to the design of efficient adaptation and mitigation strategies. However, projecting health burdens associated to specific environmental stressors is a challenging task because of the complex risk patterns and inherent uncertainty of future climate scenarios. These assessments involve multidisciplinary knowledge, requiring expertise in epidemiology, statistics, and climate science, among other subjects. Here, we present a methodologic framework to estimate future health impacts under climate change scenarios based on a defined set of assumptions and advanced statistical techniques developed in time-series analysis in environmental epidemiology. The proposed methodology is illustrated through a step-by-step hands-on tutorial structured in well-defined sections that cover the main methodological steps and essential elements. Each section provides a thorough description of each step, along with a discussion on available analytical options and the rationale on the choices made in the proposed framework. The illustration is complemented with a practical example of study using real-world data and a series of R scripts included as Supplementary Digital Content; http://links.lww.com/EDE/B504, which facilitates its replication and extension on other environmental stressors, outcomes, study settings, and projection scenarios. Users should critically assess the potential modeling alternatives and modify the framework and R code to adapt them to their research on health impact projections.

Aging Exacerbates Neuroinflammatory Outcomes Induced by Acute Ozone Exposure

The role of environmental stressors, particularly exposure to air pollution, in the development of neurodegenerative disease remains underappreciated. We examined the neurological effects of acute ozone (O3) exposure in aged mice, where increased blood-brain barrier (BBB) permeability may confer vulnerability to neuroinflammatory outcomes. C57BL/6 male mice, aged 8-10 weeks or 12-18 months were exposed to either filtered air or 1.0 ppm O3 for 4 h; animals received a single IP injection of sodium fluorescein (FSCN) 20 h postexposure. One-hour post-FSCN injection, animals were transcardially perfused for immunohistochemical analysis of BBB permeability. β-amyloid protein expression was assessed via ELISA. Flow cytometric characterization of infiltrating immune cells, including neutrophils, macrophages, and microglia populations was performed 20 h post-O3 exposure. Flow cytometry analysis of brains revealed increased microglia "activation" and presentation of CD11b, F4/80, and MHCII in aged animals relative to younger ones; these age-induced differences were potentiated by acute O3 exposure. Cortical and limbic regions in aged brains had increased reactive microgliosis and β-amyloid protein expression after O3 insult. The aged cerebellum was particularly vulnerable to acute O3 exposure with increased populations of infiltrating neutrophils, peripheral macrophages/monocytes, and Ly6C+ inflammatory monocytes after insult, which were not significantly increased in the young cerebellum. O3 exposure increased the penetration of FSCN beyond the BBB, the infiltration of peripheral immune cells, and reactive gliosis of microglia. Thus, the aged BBB is vulnerable to insult and becomes highly penetrable in response to O3 exposure, leading to greater neuroinflammatory outcomes.

Interactive effects of changing stratospheric ozone and climate on tropospheric composition and air quality, and the consequences for human and ecosystem health

The composition of the air we breathe is determined by emissions, weather, and photochemical transformations induced by solar UV radiation. Photochemical reactions of many emitted chemical compounds can generate important (secondary) pollutants including ground-level ozone (O₃) and some particulate matter, known to be detrimental to human health and ecosystems. Poor air quality is the major environmental cause of premature deaths globally, and even a small decrease in air quality can translate into a large increase in the number of deaths. In many regions of the globe, changes in emissions of pollutants have caused significant changes in air quality. Short-term variability in the weather as well as long-term climatic trends can affect ground-level pollution through several mechanisms. These include large-scale changes in the transport of O₃ from the stratosphere to the troposphere, winds, clouds, and patterns of precipitation. Long-term trends in UV radiation, particularly related to the depletion and recovery of stratospheric ozone, are also expected to result in changes in air quality as well as the self-cleaning capacity of the global atmosphere. The increased use of substitutes for ozone-depleting substances, in response to the Montreal Protocol, does not currently pose a significant risk to the environment. This includes both the direct emissions of substitutes during use and their atmospheric degradation products (e.g. trifluoroacetic acid, TFA).

Effect of Health-Related Uncertainty and Natural Variability on Health Impacts and Cobenefits of Climate Policy

Climate policy can mitigate health risks attributed to intensifying air pollution under climate change. However, few studies quantify risks of illness and death, examine their contribution to climate policy benefits, or assess their robustness in light of natural climate variability. We employ an integrated modeling framework of the economy, climate, air quality, and human health to quantify the effect of natural variability on U.S. air pollution impacts under future climate and two global policies (2 and 2.5 °C stabilization scenarios) using 150 year ensemble simulations for each scenario in 2050 and 2100. Climate change yields annual premature deaths related to fine particulate matter and ozone (95CI: 25 000-120 000), heart attacks (900-9400), and lost work days (3.6M-4.9M) in 2100. It raises air pollution health risks by 20%, while policies avert these outcomes by 40-50% in 2050 and 70-88% in 2100. Natural variability introduces "climate noise", yielding some annual estimates with negative cobenefits, and others that reach 100% of annual policy costs. This "noise" is three times the magnitude of uncertainty (95CI) in health and economic responses in 2050. Averaging five annual simulations reduces this factor to two, which is still substantially larger than health-related uncertainty. This study quantifies the potential for inaccuracy in climate impacts projected using too few annual simulations.

Human exposure to ozone in school and office indoor environments

BACKGROUND

Although it is recognized that ozone causes acute and chronic health effects and that even trace amounts of ozone are potentially deleterious to human health, information about global and local exposures to ozone in different indoor environments is limited. To synthesize the existing knowledge, this review analyzes the magnitude of and the trends in global and local exposure to ozone in schools and offices and the factors controlling the exposures.

METHODS

In conducting the literature review, Web of Science, SCOPUS, Google Scholar, and PubMed were searched using 38 search terms and their combinations to identify manuscripts, reports, and directives published between 1973 and 2018. The search was then extended to the reference lists of relevant articles.

RESULTS

The calculated median concentration of ozone both in school (8.50 μg/m³) and office (9.04 μg/m³) settings was well below the WHO guideline value of 100 μg/m³ as a maximum 8 h mean concentration. However, a large range of average concentrations of ozone was reported, from 0.8-114 μg/m³ and from 0 to 96.8 μg/m³ for school and office environments, respectively, indicating situations where the WHO values are exceeded. Outdoor ozone penetrating into the indoor environment is the main source of indoor ozone, with median I/O ratios of 0.21 and 0.29 in school and office environments, respectively. The absence of major indoor ozone sources and ozone sinks, including gas-phase reactions and deposition, are the reasons for lower indoor than outdoor ozone concentrations. However, there are indoor sources of ozone that are of significance in certain indoor environments, including printers, photocopiers, and many other devices and appliances designed for indoor use (e.g., air cleaners), that release ozone either intentionally or unintentionally. Due to significantly elevated outdoor ozone concentrations during summer, summer indoor concentrations are typically elevated. In addition, the age of a building and various housing aspects (carpeting, air conditioning, window fans, and window openings) have been significantly associated with indoor ozone levels.

CONCLUSIONS

The existing means for reducing ozone and ozone reaction products in school and office settings are as follows: 1) reduce penetration of outdoor ozone indoors by filtering ozone from the supply air; 2) limit the use of printers, photocopiers, and other devices and appliances that emit ozone indoors; 3) limit gas-phase reactions by limiting the use of materials and products (e.g. cleaning chemicals) the emissions of which react with ozone.