High Ozone Levels Research Articles

Insights into the variations of polycyclic aromatic hydrocarbons and their nitrated and oxygenated derivatives in urban airborne PM2.5

Polycyclic aromatic hydrocarbons (PAHs) can be transformed into more toxic species in the atmosphere, but field evidence for their transformation remains rare. Here, polycyclic aromatic compounds (PACs), including PAHs and their nitrated and oxygenated derivatives (NPAHs and OPAHs), in fine particulate matter (PM2.5) were measured in the seasons at multiple locations in a megacity (Guangzhou, China). Molecular diagnostic ratios (MDRs), meteorological factors, and atmospheric oxidant measurements were employed to understand the atmospheric behaviors of PM2.5-bound PACs. The results indicated that similarities/differences in the short-term variations of PAC concentrations between the locations depended on their sources and seasons. The temporal trends in MDRs were more distinct than those in concentrations among the locations. Meteorological factors affected PAC concentrations through a similar pathway (demodulating loadings on PM). Their influence on the ratios can be explained by compounds’ atmospheric half-life, vapor pressure, or particle-size distribution. Temperature was the most powerful factor for both the concentrations and MDRs. Relative humidity was minor, but its positive influence on the reaction to OH radicals was appreciable. The dependence on PM2.5 concentrations suggests that PM plays a more significant role in the sorption or formation of N/OPAHs than in their parent compounds. The OH radical-initiated reaction is the major formation mechanism of N/OPAHs throughout the year, but substantial reactions to NO3 radical in autumn were observed due to high ozone levels. Multiple linear regression revealed that parent PAHs, NO2, and/or O3 are significant contributing factors to the secondary formation of N/OPAHs. Partial least squares-discriminant analysis showed the distinguishing characteristics of summer and autumn PM2.5-bound PACs. This study provides field evidence for the gaseous and heterogeneous reactions of PAHs.

The influence of plant water stress on vegetation–atmosphere exchanges: implications for ozone modelling

Abstract. Evapotranspiration is important for Earth's water and energy cycles as it strongly affects air temperature, cloud cover, and precipitation. Leaf stomata are the conduit of transpiration, and their opening is sensitive to weather and climate conditions. This feedback can exacerbate heat waves and can play a role in their spatiotemporal propagation. Sustained high temperatures strongly favour high ozone levels, with significant negative impacts on air quality and thus on human health. Our study evaluates the process representation of evapotranspiration in the atmospheric chemistry–climate European Centre for Medium-Range Weather Forecasts – Hamburg(ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry model. Different water stress parameterizations are implemented in a stomatal model based on CO2 assimilation. The stress factors depend on either soil moisture or leaf water potential, which act on photosynthetic activity, and mesophyll and stomatal conductance. The new functionalities reduce the initial overestimation of evapotranspiration in the model globally by more than an order of magnitude, which is most important in the Southern Hemisphere. The intensity of simulated warm spells over continents is significantly improved. For ozone, we find that a realistic model representation of plant water stress suppresses uptake by vegetation and enhances photochemical production in the troposphere. These effects lead to an overall increase in simulated ground-level ozone, which is most pronounced in the Southern Hemisphere over the continents. More sophisticated land surface models with multi-layer soil schemes could address the uncertainties in representing plant dynamics representation due to too-shallow roots. In regions with low evaporative loss, the representation of precipitation remains the largest uncertainty.

Comprehensive analysis of long-term trends, meteorological influences, and ozone formation sensitivity in the Jakarta Greater Area

Jakarta Greater Area (JGA) has encountered recurrent challenges of air pollution, notably, high ozone levels. We investigate the trends of surface ozone (O3) changes from the air quality monitoring stations and resolve the contribution of meteorological drivers in urban Jakarta (2010–2019) and rural Bogor sites (2017–2019) using stepwise Multi Linear Regression. During 10 years of measurement, 41% of 1-h O3 concentrations exceeded Indonesia’ s national threshold in Jakarta. In Bogor, 0.1% surpassed the threshold during 3 years of available data records. The monthly average of maximum daily 8-h average (MDA8) O3 anomalies exhibited a downward trend at Jakarta sites while increasing at the rural site of Bogor. Meteorological and anthropogenic drivers contribute 30% and 70%, respectively, to the interannual O3 anomalies in Jakarta. Ozone formation sensitivity with satellite demonstrates that a slight decrease in NO2 and an increase in HCHO contributed to declining O3 in Jakarta with 10 years average of HCHO to NO2 ratio (FNR) of 3.7. Conversely, O3 increases in rural areas with a higher FNR of 4.4, likely due to the contribution from the natural emission of O3 precursors and the influence of meteorological factors that magnify the concentration.

A spatial analysis of ozone and PM2.5 distribution for assessing design factors of healthy buildings

Indoor air quality (IAQ) represents one of the significant challenges in healthy building design, with thermal comfort and daylighting being primary design objectives. This study aims to demonstrate the potential of energy-independent building infrastructure as a passive design solution to mitigate the impact of outdoor air pollution. This paper presents experimental and numerical investigations to establish the relationship between design factors (e.g., building orientation, geometry, and window opening location) and the spatial distribution of ozone and fine particulate matter (PM2.5) in residential houses. Our case study involves experimentally validated computational fluid dynamics (CFD) simulations for typical rowhouse archetypes in one of the United States' most polluted cities. Our findings indicate that higher ozone levels are observed on upper floors, posing a significant exposure risk at a breathing zone height of 1.7 m. In contrast, PM2.5 levels are most concerning at a height of 1 m, directly impacting children's health. Alarmingly, future trends of ozone pollution suggest that these risks could be almost three times higher compared to current conditions. Given the distinctive diurnal patterns of outdoor air pollution, the study also finds that the strategic placement of windows for nighttime air flushing, specifically in the upper two-thirds of the building, can improve IAQ. Our analysis of the spatial placement of the air purifier reveals that the optimal location is at the middle center of the windward wall. Our work underscores the potential of building design features in mitigating pollution exposure in indoor environments, emphasizing the importance of architectural solutions in public health.

Comprehensive Assessment of Environmental Factors Influencing Crop Yields: Ozone, CO2, And Aerosols

The research explored how air pollution, particularly high ozone levels, negatively impacts sensitive crops like wheat, rice, and soybeans, posing significant threats to global food security. It emphasized the long-overlooked destructive effects of ozone and emphasized the immediate need for strategies to counter these impacts amid climate change. Furthermore, the study examined the crucial role of increased carbon dioxide (CO2) levels on C4 crops, essential for global food security and biofuel production. Contrary to expectations, it challenged the belief that C4 crops inherently benefit from elevated CO2 levels in terms of enhanced photosynthesis. The study urged more experiments under changing climate conditions to refine predictions regarding crop yields. It emphasized the importance of focusing on ozone reduction, understanding how C4 crops respond to increased CO2, and assessing aerosol effects on specific crops. These insights aim to inform policies and strategies that can safeguard food security amidst rapid global economic growth and the challenges posed by climate changet.

Urban Air Pollution by Laser Photoacoustic Spectroscopy and Simplified Numerical Modeling of Gas Pollution in Urban Canyon

With rapid urbanization and industrialization, atmospheric pollution has emerged as a significant environmental challenge in Romania. Employing a laser photoacoustic spectroscopy detector, researchers analyzed ethylene, benzene, and toluene simultaneously across three distinct environmental settings in the country's southern region. This investigation spanned from March to August 2021, covering both spring and summer seasons. Measurements were taken at a breathing height of 1.5 meters above ground level. The highest concentrations of ethylene (116.82 ± 82.37 ppb), benzene (1.13 ± 0.32 ppb), and toluene (5.48 ± 3.27 ppb) were recorded at measurement point P1, situated within the city amidst residential buildings during the summer season. Additionally, the highest ozone levels (154.75 ± 68.02 ppb) were observed at point P3, located in an industrial area, during the summer. The behavior of gas concentrations is influenced by meteorological factors such as temperature, wind speed, and direction. The high toluene/benzene ratio suggests that traffic and industrial emissions are the primary sources of these pollutants. Notably, benzene and ozone concentrations exceeded prescribed limit values based on the measurements. Concurrently, a numerical model was employed to assess the impact of greenery on mitigating pollution in urban canyons. Specifically, the study focused on how wind velocity affects the dispersion of benzene pollutants in a street canyon. This study's governing equations utilized for air pollutant flow were the Reynolds-averaged Navier–Stokes (RANS) equations for compressible turbulent flow and moisture transport in air, implemented through Comsol software.

A machine learning approach to downscale EMEP4UK: analysis of UK ozone variability and trends

Abstract. High-resolution modelling of surface ozone is an essential step in the quantification of the impacts on health and ecosystems from historic and future concentrations. It also provides a principled way in which to extend analysis beyond measurement locations. Often, such modelling uses relatively coarse-resolution chemistry transport models (CTMs), which exhibit biases when compared to measurements. EMEP4UK is a CTM that is used extensively to inform UK air quality policy, including the effects on ozone from mitigation of its precursors. Our evaluation of EMEP4UK for the years 2001–2018 finds a high bias in reproducing daily maximum 8 h average ozone (MDA8), due in part to the coarse spatial resolution. We present a machine learning downscaling methodology to downscale EMEP4UK ozone output from a 5×5 km to 1×1 km resolution using a gradient-boosted tree. By addressing the high bias present in EMEP4UK, the downscaled surface better represents the measured data, with a 128 % improvement in R2 and 37 % reduction in RMSE. Our analysis of the downscaled surface shows a decreasing trend in annual and March–August mean MDA8 ozone for all regions of the UK between 2001–2018, differing from increasing measurement trends in some regions. We find the proportion of the UK which fails the government objective to have at most 10 exceedances of 100 µg m−3 per annum is 27 % (2014–2018 average), compared to 99 % from the unadjusted EMEP4UK model. A statistically significant trend in this proportion of −2.19 % yr−1 is found from the downscaled surface only, highlighting the importance of bias correction in the assessment of policy metrics. Finally, we use the downscaling approach to examine the sensitivity of UK surface ozone to reductions in UK terrestrial NOx (i.e. NO + NO2) emissions on a 1×1 km surface. Moderate NOx emission reductions with respect to present day (20 % or 40 %) increase both average and high-level ozone concentrations in large portions of the UK, whereas larger NOx reductions (80 %) cause a similarly widespread decrease in high-level ozone. In all three scenarios, very urban areas (i.e. major cities) are the most affected by increasing concentrations of ozone, emphasizing the broader air quality challenges of NOx control.

Characteristics and Source Apportionment of Volatile Organic Compounds in an Industrial Area at the Zhejiang–Shanghai Boundary, China

As “fuel” for atmospheric photochemical reactions, volatile organic compounds (VOCs) play a key role in the secondary generation of ozone (O3) and fine particulate matter (PM2.5, an aerodynamic diameter ≤ 2.5 μm). To determine the characteristics of VOCs in a high-level ozone period, comprehensive monitoring of O3 and its precursors (VOCs and NOx) was continuously conducted in an industrial area in Shanghai from 18 August to 30 September 2021. During the observation period, the average concentration of VOCs was 47.33 ppb, and alkanes (19.64 ppb) accounted for the highest proportion of TVOCs, followed by oxygenated volatile organic compounds (OVOCs) (13.61 ppb), alkenes (6.92 ppb), aromatics (4.65 ppb), halogenated hydrocarbons (1.60 ppb), and alkynes (0.91 ppb). Alkenes were the predominant components that contributed to the ozone formation potential (OFP), while aromatics such as xylene, toluene, and ethylbenzene contributed the most to the secondary organic aerosol production potential (SOAFP). During the study period, O3, NOx, and VOCs showed significant diurnal variations. Industrial processes were the main source of VOCs, and the second largest source of VOCs was vehicle exhaust. While the largest contribution to OFP was from vehicle exhaust, the second largest contribution was from liquid petroleum gas (LPG). High potential source contribution function (PSCF) values were observed in western and southeastern areas near the sampling sites. The results of a health risk evaluation showed that the Hazard Index was less than 1 and there was no non-carcinogenic risk, but 1,3-butadiene, benzene, chloroform, 1,2-dibromoethane, and carbon tetrachloride pose a potential carcinogenic risk to the population.

Environmental Refuges during Summertime Heat and Elevated Ozone Levels: A Preliminary Case Study of an Urban “Cool Zone” Building

The combination of extreme heat waves and ozone pollution is a major health hazard for urban populations in the summertime, particularly for the most sensitive groups such as children, the elderly, the unsheltered, and those with pre-existing health conditions. The “Cool Zone Program”, operated by the Salt Lake County Aging and Adult Services, identifies areas in the county and Salt Lake City facilities where members of the public can escape the summer heat, hydrate, and learn about available programs. We measured indoor and outdoor temperature and ozone for a pilot study at a designated Cool Zone location during the 22 August–6 September 2019 period and found that the building provided substantial heat relief and protection from more than 75% of the outdoor ozone. We observed a nearly 35 min delay for the outdoor ozone to be reflected on the indoor readings, providing an action window for ventilation scheduling changes to protect against the highest ozone levels during the day. Our findings show that it is critical to re-think and formulate action plans to protect vulnerable populations from excessive heat and pollution events during the summer.

The Evolutions and Large‐Scale Mechanisms of Summer Stratospheric Ozone Intrusion Across Global Hotspots

AbstractStratospheric ozone intrusions can have a significant impact on regional near‐surface ozone levels. Especially in summer, intrusions can contribute to extreme ozone events because of preexisting high ozone levels near the surface and cause serious health issues. Considering the increasing trend of surface ozone level, an understanding of stratospheric ozone intrusion is necessary. From a 19‐year Whole Atmosphere Community Climate Model, version 6 simulation and a stratospheric origin ozone tracer, we identify the global hotspots of stratospheric intrusions based on extreme tracer concentrations near the surface: North America, Africa, the Mediterranean, and the Middle East. We investigate the common underlying large‐scale mechanisms of the stratospheric intrusions over the identified hotspots from the lower stratosphere to the lower troposphere. From the trajectory analysis, we find that the upper‐level jet drives isentropic mixing near the jet axis and initiates stratospheric ozone intrusion. Subsequently, climatological descent at the lower troposphere brings the ozone down to the surface, which explains the spatial preference of summertime stratospheric intrusion events.

The Combined Effects of High Temperatures and Ozone Pollution on Medical Emergency Calls - Jinan City, Shandong Province, China, 2013-2019.

Studies have extensively documented the separate and independent effects of extreme temperature and ozone on morbidity and mortality associated with respiratory and circulatory diseases. The study revealed a significant association between elevated temperature, ozone pollution, and the combined effect of high temperature and ozone pollution with an increased risk of all-cause medical emergency calls (MECs) and MECs specifically related to neurological diseases. Interventional measures should be implemented to mitigate exposure to high temperatures and ozone levels. Specifically, during the warm season, it is crucial for relevant authorities to focus on disseminating scientific information regarding the health impacts of elevated temperatures and ozone pollution. Additionally, timely public health advisories should be issued to alert the public effectively.

Impacts of anthropogenic emissions and meteorology on spring ozone differences in San Antonio, Texas between 2017 and 2021

San Antonio has been designated as ozone nonattainment under the current National Ambient Air Quality Standards (NAAQS). Ozone events in the city typically occur in two peaks, characterized by a pronounced spring peak followed by a late summer peak. Despite higher ozone levels, the spring peak has received less attention than the summer peak. To address this research gap, we used the Weather Research and Forecasting (WRF)-driven GEOS-Chem (WRF-GC) model to simulate San Antonio's ozone changes in the spring month of May from 2017 to 2021 and quantified the respective contributions from changes in anthropogenic emissions and meteorology. In addition to modeling, observations from the San Antonio Field Studies (SAFS), the Texas Commission on Environmental Quality (TCEQ) Continuous Ambient Monitoring Stations (CAMS), and the spaceborne TROPOspheric Monitoring Instrument (TROPOMI) are used to examine and validate changes in ozone and precursors. Results show that the simulated daytime mean surface ozone in May 2021 is 3.8 ± 0.6 ppbv lower than in May 2017, which is slightly less than the observed average differences of −5.3 ppbv at CAMS sites. The model predicted that the anthropogenic emission-induced changes contribute to a 1.4 ± 0.5 ppbv reduction in daytime ozone levels, while the meteorology-induced changes account for a 2.4 ± 0.6 ppbv reduction over 2017–2021. This suggests that meteorology plays a relatively more important role than anthropogenic emissions in explaining the spring ozone differences between the two years. We additionally identified (1) reduced NO2 and HCHO concentrations as chemical reasons, and (2) lower temperature, higher humidity, increased wind speed, and a stronger Bermuda High as meteorological reasons for lower ozone levels in 2021 compared to 2017. The quantification of the different roles of meteorology and ozone precursor concentrations helps understand the cause and variation of ozone changes in San Antonio over recent years.

Ozone Pollution and Acute Exacerbation of Asthma in Residents of China: An Ecological Study.

The evidence for a causal relationship between high-level ozone (O3) exposure and acute exacerbation of asthma among adults is limited, and the conclusions are less definitive. Here we collected the daily data on asthma cases, O3 exposure, and meteorological factors from 2010 to 2016 in Shijiazhuang, China. We investigated the risk of asthma exacerbation associated with high-level ozone exposure using a polynomial distributed lag model (PDLM). Using a generalized additive model (GAM), we estimated the interactive effects between O3 and other pollutants as well as meteorological factors on asthma exacerbation. A total of 7270 patients with asthma were enrolled from 22 governmental hospitals in 13 counties. Each 10 μg/m3 increase in O3 concentration on the exacerbation of asthma was associated with a 1.92% (95% CI = 0.80-3.03%) higher risk of asthma exacerbation on day lag 7. The cumulative risk of O3 on asthma exacerbation increased by 18.9% (95% CI = 12.8-25.4%) on the 14th day. High consecutive levels of O3 increase the risk of asthma exacerbation, and the interactive effect of O3 and sulfur dioxide (SO2) appears before the exacerbation onset. These findings suggested that O3 should be an important risk factor for asthma exacerbation, and health benefits in reducing asthma exacerbation risk would be gained with continued efforts to improve the air quality in China.

Short-term impact of extreme temperatures, relative humidity and air pollution on emergency hospital admissions due to kidney disease and kidney-related conditions in the Greater Madrid area (Spain)

While some studies report a possible association between heat waves and kidney disease and kidney-related conditions, there still is no consistent scientific consensus on the matter or on the role played by other variables, such as air pollution and relative humidity.Ecological retrospective time series study 01-01-2013 to 31-12-2018). Dependent variables: daily emergency hospitalisations due to kidney disease (KD), acute kidney injury (AKI), lithiasis (L), dysnatraemia (DY) and hypovolaemia (HPV). Independent variables: maximum and minimum daily temperature (Tmax, Tmin, °C), and daily relative humidity (RH, %). Other variables were also calculated, such as the daily temperature for risk of kidney disease (Theat, °C) and low daily hazardous relative humidity (HRH%).As variables of air pollution, we used the daily mean concentrations of PM10, PM2.5, NO2 and O3 in μg/m3. Based on these, we then calculated their daily excesses over World Health Organisation (WHO) guideline levels (hPM10, hPM2.5, hNO2 and hO3 respectively). Poisson family generalised linear models (GLMs) (link = log) were used to calculate relative risks (RRs), and attributable risks and attributable admissions. In the models, we controlled for the covariates included: seasonalities, trend, autoregressive component, day of the week, month and year.A statistically significant association was found between Theat and all the dependent variables analysed. The greatest AKI disease burden was attributable to Theat (2.2 % (1.7, 2.6) of attributable hospital admissions), followed by hNO2 (1.7 % (0.9, 3.4)) and HRH (0.8 (0.6, 1.1)). In the case of hypovolaemia and dysnatraemia, the greatest disease burden again corresponded to Theat, with 6.9 % (6.2, 7.6) and 5.7 (4.8, 6.6) of attributable hospital admissions respectively.Episodes of extreme heat exacerbate daily emergency hospital admissions due to kidney disease and kidney-related conditions; and attributable risks are likewise seen for low relative humidity and high ozone levels.

Correlation between air temperature and surface ozone in their extreme ranges in the greater Tokyo region

High-level ozone (O3) events observed around major urban regions in the middle latitudes are correlated with high temperatures (T-O3 correlation). Therefore, the effects of global warming on the future O3 levels are a matter of concern. The T-O3 correlation is caused by various physicochemical and meteorological processes, the importance of which can differ by region. This statistical analysis focused on the correlation in the extremely high ranges, because the lower ranges would only act as noise in elucidating the conditions at which high temperatures and high levels of O3 occur. This methodology was applied to the greater Tokyo region after 2001, where severe O3 events frequently occurred when the sea breeze system developed in summer. To select sample days for the analysis, this study set up twofold filtering: (1) a large threshold for midday sunshine duration and (2) a typical variation pattern to roughly judge sea breeze days, mostly essential weather pattern for high-level O3 events in the region. The most notable result was a decrease in O3 corresponding to the reduction in non-methane hydrocarbons (NMHC) from Period I (2001–2007) to Period III (2017–2019). As the NMHC rank reduced, the linear regression line for the T-O3 correlation shifted downward, but its slope (ppb/°C) remained around 10, except that temporary spikes in O3 levels and temperatures occurred at moderate NMHC levels. From an urban meteorological perspective, the wind speed in the mature stage of the sea breeze is the major factor behind the T-O3 correlation.

Response of PM2.5 and O3 to Emission Reductions in Nanjing Based on Random Forest Algorithm

High levels of fine particulate matter (PM2.5) and ozone (O3) in ambient air affect climate change and also endanger human health and ecosystems. Air pollution in Nanjing has been improving since the implementation of the "Air Pollution Prevention and Control Action Plan" in 2013. However, Nanjing still faces PM2.5 and O3 pollution. Evaluating the response of pollutant concentrations to the reductions in precursor emissions is helpful to obtain effective strategies of emission reduction to improve pollution levels. The sensitive simulations of emission perturbation in atmospheric chemistry models directly demonstrate the response of pollution to the reductions in emissions. Nevertheless, these sensitive simulations are limited in computing time and resources. The random forest algorithm was trained by using the simulation results of the atmospheric chemical transport model (GEOS-Chem) in 2015. The changes in daily PM2.5 and daily maximum eight-hour O3 (MDA8 O3) concentrations in Nanjing in 2019 were efficiently predicted under different reduction scenarios of anthropogenic emissions. The simulations showed that the seasonal average of ρ(PM2.5) in Nanjing would decrease by 2-4 μg·m-3 with the reduction in anthropogenic emissions of 10% in 2019 in China. In the case of controlling only local emissions in Nanjing, the concentrations of PM2.5 in Nanjing decreased significantly without local anthropogenic emissions. Additionally, the simulations showed that the annual average of ρ(PM2.5) in Nanjing could be lower than the national secondary limit (35 μg·m-3) when the anthropogenic emission reduction in China was higher than 20% in 2019. For ozone, the equal proportional emission reductions in nitrogen oxides (NOx) and volatile organic pollutants (VOCs) of O3 precursors in China likely led to the increase in seasonal average concentrations of O3 in Nanjing. For the proportional reduction of anthropogenic emissions by 10%-50% in China, the seasonal average of ρ(MDA8 O3) in Nanjing in 2019 would increase by 1-3 μg·m-3 in spring, 1-4 μg·m-3 in autumn, and 3-11 μg·m-3 in winter, respectively, compared with that in the base simulation. With the reduction in anthropogenic NOx emission by 10% and VOCs by 20%, the seasonal average of ρ(MDA8 O3) in Nanjing would decrease by 3-6 μg·m-3. On this basis, further increasing the proportion (30%) of VOCs emission reduction could reduce the annual average of ρ(MDA8 O3) in Nanjing by 7 μg·m-3. However, the annual average of ρ(MDA8 O3) of Nanjing in 2019 increased by 1 μg·m-3, with the local emission reduction of NOx by 10% and VOCs by 30%. Therefore, this showed that the key to alleviate ozone pollution in Nanjing is a reasonable control ratio of ozone precursor emissions and the implementation of regional joint prevention and control. In order to effectively reduce the O3 pollution in Nanjing, the emission reduction ratio of NOx and VOCs in China should be less than 1:2. The response of pollutant concentrations to reductions in precursor emissions were efficiently obtained by the random forest algorithm and GEOS-Chem model. The simulations would provide the scientific basis for the emission control strategy to alleviate air pollution.

Influence of biomass burning on ozone levels in the Megalopolis of Central Mexico during the COVID-19 lockdown

The massive reductions in anthropogenic emissions resulting from the COVID-19 lockdown provided a unique opportunity to evaluate the effect of mitigation measures aiming to abate air pollution. In Mexico, the total lockdown period took place during the dry-hot season when biomass burning activity is enhanced. Here, we investigate the role of biomass burning emissions on regional ozone levels in the Megalopolis of Central Mexico. The studied period covers the lockdown phases 2 and 3, and the first month of the New Normal.We applied a factor separation technique and process analysis to estimate the pure and synergistic contributions of emission reductions under lockdown and that from biomass burning to daily ozone maximum concentrations in 7 metropolitan areas of different states in the Megalopolis. The results revealed that biomass burning plumes likely masked the effect of massive reductions from mobile emissions, impacted the PBL development during phase 3 and favored transition and mixed NOx-limited and VOC-limited regional regimes. This contributed to increased ozone production in the middle to lower PBL by changing the regional background levels which potentially could bias high ozone production efficiency estimations.Given the Megalopolis contribution to economic and societal development at national scale, our study suggests that ozone mitigation measures during the dry-hot season targeting mainly mobile emissions will likely be offset by biomass burning plumes. A regional and synergic policy aiming to control biomass burning would help to reduce the occurrence of high ozone levels in Central Mexico with the co-benefit of tackling short-lived climate pollutants.

A comprehensive approach combining positive matrix factorization modeling, meteorology, and machine learning for source apportionment of surface ozone precursors: Underlying factors contributing to ozone formation in Houston, Texas

Ozone concentrations in Houston, Texas, are among the highest in the United States, posing significant risks to human health. This study aimed to evaluate the impact of various emissions sources and meteorological factors on ozone formation in Houston from 2017 to 2021 using a comprehensive PMF-SHAP approach. First, we distinguished the unique sources of VOCs in each area and identified differences in the local chemistry that affect ozone production. At the urban station, the primary sources were n_decane, biogenic/industrial/fuel evaporation, oil and gas flaring/production, industrial emissions/evaporation, and ethylene/propylene/aromatics. At the industrial site, the main sources were industrial emissions/evaporation, fuel evaporation, vehicle-related sources, oil and gas flaring/production, biogenic, aromatic, and ethylene and propylene. And then, we performed SHAP analysis to determine the importance and impact of each emissions factor and meteorological variables. Shortwave radiation (SHAP values are ∼5.74 and ∼6.3 for Milby Park and Lynchburg, respectively) and humidity (∼4.87 and ∼4.71, respectively) were the most important variables for both sites. For the urban station, the most important emissions sources were n_decane (∼2.96), industrial emissions/evaporation (∼1.89), and ethylene/propylene/aromatics (∼1.57), while for the industrial site, they were oil and gas flaring/production (∼1.38), ethylene/propylene (∼1.26), and industrial emissions/evaporation (∼0.95). NOx had a negative impact on ozone production at the urban station due to the NOx-rich chemical regime, whereas NOx had positive impacts at the industrial site. The study's findings suggest that the PMF-SHAP approach is efficient, inexpensive, and can be applied to other similar applications to identify factors contributing to ozone-exceedance events. The study's results can be used to develop more effective air quality management strategies for Houston and other cities with high levels of ozone.

Spatiotemporal characteristics of ozone and the formation sensitivity over the Fenwei Plain

High surface ozone (O3) levels affect human and environmental health. The Fenwei Plain (FWP), one of the critical regions for China's “Blue Sky Protection Campaign”, has reported severe O3 pollution. This study investigates the spatiotemporal properties and the causes of O3 pollution over the FWP using high-resolution data from the TROPOspheric Monitoring Instrument (TROPOMI) from 2019 to 2021. This study characterizes spatial and temporal variations in O3 concentration by linking O3 columns and surface monitoring using a trained deep forest machine learning model. O3 concentrations in summer were 2–3 times higher than those found in winter due to higher temperatures and greater solar irradiation. The spatial distributions of O3 correlate with the solar radiation showing decreased trends from the northeastern to the southwestern FWP, with the highest O3 values in Shanxi Province and the lowest in Shaanxi Province. For urban areas, croplands and grasslands, the O3 photochemistry in summer is NOx-limited or in the transitional regime, while it is VOC-limited in winter and other seasons. Reducing NOx emissions would be effective for decreasing O3 levels in summer, while VOC reductions are necessary for winter. The annual cycle in vegetated areas included both NOx-limited and transitional regimes, indicating the importance of NOx controls to protect ecosystems. The O3 response to limiting precursors shown here is of importance for optimizing control strategies and is illustrated by emission changes during the 2020 COVID-19 outbreak.

Hourly ozone level prediction based on the characterization of its periodic behavior via deep learning

Surface ozone has become one of the most important air pollutants in recent years, posing a huge threaten to human health. The accurate prediction of ozone pollution, especially when ozone concentration exceeds permissible standard, has become an important research topic in the field of air quality management, where data-driven methods are widely used. Among these methods, the long short-term memory neural network (LSTM) has received significant attention in ozone forecasting for its ability in modeling long-term time dependence. However, from the time series perspective, short-term nonstationary characteristics resulted from periodic trends of ozone data have not been sufficiently considered by LSTM. To address this issue, we propose a novel deep learning-based prediction method named multi-order difference embedded LSTM (MDELSTM). Through statistical analysis of ozone time series, a multi-order difference strategy is employed to extract the periodic information. By embedding it into LSTM layers, a brand-new deep learning prediction model with the ability to extract both long-term stationary information and short-term periodic information is constructed for ozone forecasting. The proposed method is verified through the Los Angeles air quality dataset between 2013 and 2017. The prediction accuracy of ozone concentration over the next hour is improved compared to other state-or-the-art methods in terms of mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). To further illustrate the ability of the proposed method in predicting high-level ozone concentration, new evaluation indicators oriented on situations where the ozone concentration exceeds permissible standard are proposed. The results demonstrate its application prospect in hourly ozone pollution prediction and prevention.