O3 Concentration Levels Research Articles

Spatiotemporal patterns of surface ozone exposure inequality in China.

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

Evaluation of different machine learning approaches for predicting high concentration episodes of ground-level ozone: A case study in Catalonia, Spain

Ground-level ozone (O3) is a pollutant with a great impact on human health and the environment. As a secondary air contaminant of photochemical origin, those areas with greater exposure to solar radiation, such as Spain and other Mediterranean countries, are considerably affected. With the aggravation of O3 pollution, it is important to provide reliable forecasting tools to help stakeholders implement more effective policies to mitigate the negative impact associated with this problem. In this regard, Machine Learning-based models have emerged in recent years, since they are able to identify complex relationships between ozone levels and relevant variables. However, their application to capture the most extreme events remains difficult. In this work, different ML approaches for predicting daily maximum 8-h average ozone (O3,MDA8) were compared, investigating their ability to forecast the highest concentration levels recorded. Two variants of the Random Forest algorithm (regression and classification) were applied to a specific area of Catalonia, Spain, with a special interest due to the high number of episodes of exceedance of O3 concentration levels. The predictive models were built with a 1 day time horizon, using datasets from 2002 to 2020. The variables used as inputs were other air pollutants concentrations and meteorological processes, monitored the day before to the target day to be predicted, and time information. Although results showed reasonable overall performances, low accuracy was achieved when forecasting the highest episodes of O3,MDA8. To improve the capacity of the models in predicting high-O3,MDA8 concentration levels, a methodology was proposed to fine-tuning the original predictions of the ML models according to a classification metric, G-Mean, which allows adjusting the balance between the correct predictions of different classes. Using the Sensitivity and Specificity metrics, the classical approaches were compared with the original ones proposed in the present study. The results obtained, for all the cases analysed, showed a mean increase in Sensitivity of 0.28, associated with a greater number of True Positives (correct predictions of high O3-episodes). On the other hand, the average Specificity value decreased, due to the appearance of a greater number of False Positives, although this reduction was only 0.05. The proposed criteria showed promising results, better balancing classification metrics and increasing the ratio of correct predictions linked to the higher ranges of O3.

Ozone enrichment and drought stress have more negative effects on invasive leguminous woody species than co-occurring native species

Ozone (O3) enrichment and drought stress are common phenomenon of global climate change. However, it remains unknown to what extent these factors might affect leguminous woody plant species invasion. In an open-top chamber (OTC) experiment, we grew four congeneric pairs of invasive and native woody plant species under two levels of O3 concentrations (ambient vs. elevated) and water conditions (dry vs. wet). We studied the effects of O3 enrichment and drought stress on the biomass, biomass allocation and leaf number of these four pairs of invasive vs. native woody species that are common in temperate forests. The results showed that O3 enrichment and drought stress alone reduced the total biomass of invasive woody species significantly greater than those of co-occurring native species. Moreover, O3 enrichment reduced the root biomass allocation of invasive species significantly more than that of native species. Under elevated O3 environments, the ratio of damaged leaves to total leaves for invasive species was 22.6% and 33.9%, and for native species was 13.9% and 24.4%, under dry and wet conditions, respectively. Results suggested that negative effects of O3 enrichment on plants was alleviated under drought conditions, and such negative effects on invasions of woody plant species were both detected from biomass allocation and visible foliar injury perspectives. Our study demonstrated that elevated O3 and drought stress have stronger adverse effects on invasive woody species than that co-occurring native species. The invasive woody plant species may be facilitated for invasion to the areas with lower O3 concentration or higher precipitation.

Assessment of meteorological and air quality drivers of elevated ambient ozone in Beijing via machine learning approach.

Over the past few years, surface ozone (O3) pollution has dominated China's air pollution as particulate matter has decreased. In Beijing, the annual average concentrations of ground-level O3 from 2015 to 2020 regularly increased from 57.32 to 62.72μg/m3, showing a change of almost 9.4%, with a 1.6% per year increase. The meteorological factors are the primary influencer of elevated O3 levels; however, their importance and heterogeneity of variables remain rarely understood. In this study, we used 13 meteorological factors and 6 air quality (AQ) parameters to estimate their influencing score using the random forest (RF) algorithm to explain and predict ambient O3. Among the meteorological variables and overall, both land surface temperature and temperature at 2m from the surface emerged as the most influential factors, while NO2 stood out as the highest influencing factor from the AQ parameters. Indeed, it is crucial and imperative to reduce the temperature caused by climate change in order to effectively control ambient O3 levels in Beijing. Overall, meteorological factors alone exhibited a higher coefficient of determination (R2) value of 0.80, compared with AQ variables of 0.58, for the post-lockdown period. In addition, we calculated the number of days O3 concentration levels exceeded the WHO standard and newly proposed peak-season maximum daily 8-h average (MDA8) O3 guideline for Beijing. The exceedance number of days from the WHO standard of MDA8 ambient O3 was observed to be the highest in June, and each studied year crossed peak season guidelines by almost 2 times margin. This study demonstrates the contributions of meteorological variables and AQ parameters in surging ambient O3 and highlights the importance of future research toward devising an optimum strategy to combat growing O3 pollution in urban areas.

How does pollen production of allergenic species differ between urban and rural environments?

Pollen production is one plant characteristic that is considered to be altered by changes in environmental conditions. In this study, we investigated pollen production of the three anemophilous species Betula pendula, Plantago lanceolata, and Dactylis glomerata along an urbanization gradient in Ingolstadt, Germany. We compared pollen production with the potential influencing factors urbanization, air temperature, and the air pollutants nitrogen dioxide (NO2) and ozone (O3). While we measured air temperature in the field, we computed concentration levels of NO2 and O3 from a land use regression model. The results showed that average pollen production (in million pollen grains) was 1.2 ± 1.0 per catkin of Betula pendula, 5.0 ± 2.4 per inflorescence of Plantago lanceolata, and 0.7 ± 0.5 per spikelet of Dactylis glomerata. Pollen production was higher in rural compared to urban locations on average for B. pendula (+ 73%) and P. lanceolata (+ 31%), while the opposite was the case for D. glomerata (- 14%). We found that there was substantial heterogeneity across the three species with respect to the association of pollen production and environmental influences. Pollen production decreased for all species with increasing temperature and urbanization, while for increasing pollutant concentrations, decreases were observed for B. pendula, P. lanceolata, and increases for D. glomerata. Additionally, pollen production was found to be highly variable across species and within species-even at small spatial distances. Experiments should be conducted to further explore plant responses to altering environmental conditions.

Impacts of Meteorological Parameters on Tropospheric Ozone Concentrations in Çanakkale

Meteorological factors have a significant impact on the formation and transport of tropospheric ozone. In addition to the meteorological factors, solar radiation and associated chemical reactions, topography, and pollution sources also affect the ozone concentration levels (O3). In this study, the influences of the meteorological factors (temperature, wind speed, relative humidity, solar radiation) on O3 were investigated for Çanakkale throughout the 2014-2018 period. It was found that O3 concentration levels in summer season are linked with the high humidity and, especially high temperature. The statistical analysis indicated that O3 concentrations at Çan district (SE Çanakkale) were positively correlated with temperature during summer and autumn seasons (r=0.53). Similarly, a statistically significant positive correlation was found at Lapseki station of Çanakkale during autumn (r=0.48), spring (r=0.41), and summer months (r=0.40), respectively. On the other hand, relative humidity (RH) displayed negative correlations with O3 at Çan and Lapseki stations. In addition, negative correlation was observed between nitrogen oxides (NOX) and O3 values measured at Lapseki station. The main important factors affecting ozone concentration levels in Çanakkale were found as local meteorological conditions and long-range transportation of pollutants from anthropogenic sources (e.g. vehicle, industrial emissions, volatile organic compounds (VOCs) emitted from solvents and industry).

Impact of drought conditions on air pollution over Turkey

AbstractAs a natural disaster, drought affects many sectors such as agriculture and hydrology, as well as having an effect on air quality. In terms of air pollution, drought can reduce wet scavenging of pollutants and change their chemical production/loss and lifetime. This study investigates the relationship between drought events and air pollutants in Turkey. As a drought indicator, the Standardized Precipitation‐Evapotranspiration Index (SPEI)‐1 monthly values for dry (SPEI < −0.99), normal (−0.99 < SPEI < 0.99) and wet (SPEI < 0.99) conditions were used to investigate the changes in PM10, PM2.5, O3 concentration levels. Monthly mean PM10 values of 80 stations for the period 2010–2018, PM2.5 and O3 values of 10 and 12 stations, respectively, were used for the analysis throughout the 2014–2018 period. According to the results, while frequency occurrence of normal conditions decreased in the last period (2010–2018) when compared to the first (1901–2009), drought conditions have significantly increased in each region of Turkey in the last decade. Highest increase in drought events occurred in the inner/southern parts of Turkey. In dry events, while PM10 levels of the stations show above‐normal values, highest regional increase in PM10 was found in the Central Anatolia (CAR), Mediterranean (MeR), Aegean (AR) and Marmara (MR) regions of the country. In fall, high daily temperatures and cloudless days in CAR and MeR regions are seen under deep surface low over continental Europe and surface high over Caspian Sea, which result in severe dryness events and associated high PM10 values in the air quality stations. On the other hand, as a consequence of the expanding Asiatic monsoon low to the eastern part of Turkey, significant amount of moisture is transferred from the Eastern Mediterranean Sea surface to the CAR and MeR regions by southerly flows (wetness SPEI conditions in fall) and cause to appear below‐normal PM10 values in the southern stations.

Effect of Future Climate Change on Stratosphere-to-Troposphere-Exchange Driven Ozone in the Northern Hemisphere.

Future estimates of atmospheric pollutant concentrations serve as critical information for policy makers to formulate current policy indicators to achieve future targets. Tropospheric burden of O3 is modulated not only by anthropogenic and natural precursor emissions, but also by the downward transport of O3 associated with stratosphere to troposphere exchange (STE). Hence changes in the estimates of STE and its contributions are key to understand the nature and intensity of future ground level O3 concentrations. The difference in simulated O3 mixing ratios with and without the O3-Potential Vorticity (PV) parameterization scheme is used to represent the model estimated influence of STE on tropospheric O3 distributions. Though STE contributions remain constant in Northern hemisphere as a whole, regional differences exist with Europe (EUR) registering increased STE contribution in both spring and winter while Eastern China (ECH) reporting increased contribution in spring in 2050 (RCP8.5) as compared to 2015. Importance of climate change can be deduced from the fact that ECH and EUR recorded increased STE contribution to O3 in RCP8.5 compared to RCP4.5. Comparison of STE and non-STE meteorological process contributions to O3 due to climate change revealed that contributions of non-STE processes were highest in summer while STE contributions were highest in winter. EUR reported highest STE contribution while ECH reported highest non-STE contribution. None of the 3 regions show consistent low STE contribution due to future climate change (< 50%) in all seasons indicating the significance of STE to ground level O3.

Impacts of COVID-19 Lockdown on Traffic Flow, Active Travel and Gaseous Pollutant Concentrations; Implications for Future Emissions Control Measures in Oxford, UK

The COVID-19 lockdown provided a unique opportunity to test the impacts of changes in travel patterns on air quality and the environment. Therefore, this study provides insights into the impacts of COVID-19 emergency public health “lockdown” measures upon traffic flow, active travel and gaseous pollutant concentrations (NO, NO2 and O3) in Oxford city centre during 2020 using time-series analysis and linear regression methods. Comparisons of traffic counts indicated pronounced changes in traffic volume associated with national lockdown periods. Car volume reduced by 77.5% (statistically significant) during the first national lockdown, with lesser changes in goods vehicles and public transport (bus) activity during the second lockdown. Cycle flow reduced substantively during the first lockdown only. These changes resulted in a reduction in nitric oxide (NO) and nitrogen dioxide (NO2) concentrations of 75.1% and 47.4%, respectively, at roadside, and 71.8% and 34.1% at urban background during the first lockdown period. In contrast ozone (O3) concentrations increased at the urban background site by 22.3% during the first lockdown period, with no significant changes in gaseous concentrations during the second lockdown at either roadside or urban background location. The diurnal pattern of peak mean NO and NO2 concentrations reduced in magnitude and was shifted approximately 2 h earlier in the morning and 2 h later in the evening (roadside) and 3 h earlier in the morning and 3 h later in the evening (urban background). Our findings provide an example of how gaseous air quality in urban environments could respond to future urban traffic restrictions, suggesting benefits from reductions in peak and daily NO2 exposures may be offset by health harms arising from increases in ground level O3 concentrations in the summer months.

Assessment of Indoor Air Pollutants Exposure in Hair Salons of Lahore

Abstract Hairdressing activities release indoor air pollutants which are hazardous for human health. The present study was, therefore, conducted to determine indoor air pollutants exposure in hair salons of Lahore. The study period was from August to September 2019. Four hair salons were selected for sampling the indoor air pollutants during working hours and before it. Total working employees, working area, clients per day and ventilation facilities were noted on a designed proforma. The parameters of indoor air pollutants included volatile organic compounds (VOCs), coarse particulate matter (PM10), ozone (O3), carbon dioxide (CO2), relative humidity (RH%) and temperature (°C). PM10 was monitored through DustTrak aerosol monitors (model 8520, TSI Inc.). Similarly, VOCs, O3, RH% and temperature were measured through a portable aeroqual series 500 after using relevant sensors. The sampling period for all pollutants were 8-hours. The concentration levels of VOCs, O3 and PM10 were higher during working hours as compared to the before. Only the level of in all selected hair salons was above the recommended exposure limits (&gt; 0.20-0.50 ppm). The ventilation system was insufficient. Indoor air pollutants exposure level in hair salons was higher during working hours as compared to the before. However, all pollutants were within the prescribed exposure limits except VOCs. Uses of less hazardous chemical products, regular biological monitoring, and proper ventilation system along with large sample size of hair salons are recommended for further studies. Keywords: Particulate matter, Environmental pollutants, Volatile organic compounds, Ozone, Carbon dioxide

Separately resolving NOx and VOC contributions to ozone formation

Ozone (O3) is widely recognized as a significant air pollutant that affects public health across the globe. O3 is formed from precursor emissions of oxides of nitrogen (NOx) and volatile organic compounds (VOCs) that react in the atmosphere, making it complex to identify the major source contributions to O3 concentrations. O3 source apportionment calculations within chemical transport models (CTMs) provide a specialized approach to resolve source contributions. Traditional O3 apportionment techniques track source contributions based on the chemical formation regime, but they do not separately distinguish between NOx and VOC source contributions. In this study, a new O3 source apportionment technique was developed to explicitly resolve the contributions from both NOx and VOC sources in order to provide a more detailed view on O3 source origins so that policy makers can design more effective emission control strategies. The new technique is flexible and can be configured to identify the original source of precursors that contribute to O3 formation or the most recent source depending on the choice of the tagging method. The detailed features of the new technique are demonstrated during a peak O3 event in September 2010 in Los Angeles, while trends in O3 source contributions over time are evaluated during two additional simulations in July 2005 and August 2015. Quality control checks show that the new source apportionment methodology does not alter predicted total O3 concentrations, and the detailed source apportionment information can be averaged to yield results that are consistent with traditional O3 source apportionment calculations. The detailed O3 source apportionment results during Sept 2010 show that, among NOx sources, on-road gasoline, on-road diesel, off-road diesel, and soil NOx account for over 60% of the ground level O3 concentrations. Among VOC sources, upwind boundary conditions and biogenic sources account for approximately 90% of the ground-level O3 formed. The formaldehyde to NO2 ratio suggests that the chemical regime in the year 2015 was VOC-limited, but given the uncontrollable nature of the VOC emissions, the results suggest that NOx emission controls would have been the preferred emission control strategy to reduce O3 concentration in Los Angeles at that time, with the understanding that some period of O3 disbenefits would need to be tolerated until the emissions control program shifts the atmospheric chemistry back into the NOx-limited regime. The NOx source apportionment results for O3 identify the largest NOx sources that could be reduced in an effort to reach NOx-limited conditions. The chemical regime in the Los Angeles atmosphere is continuously evolving, and so these calculations would need to be repeated under current conditions to determine if we have arrived at this NOx limited regime. Future studies will undertake this analysis.

Characteristics and Sources of VOCs at Different Ozone Concentration Levels in Tianjin

To further study the effect of volatile organic compounds (VOCs) on ozone pollution, the characteristics and sources of VOCs at different ozone (O3) concentration levels were analyzed, using high-resolution online monitoring data obtained from Tianjin in the summer of 2019. Results showed that VOCs concentrations were 32.94, 38.10, 42.41, and 47.12 μg ·m-3, when the O3 concentration levels were categorized as excellent, good, light pollution, and moderate pollution, respectively. VOCs were composed of alkanes, alkenes, alkynes and aromatics, which accounted for 61.72%-63.36%, 14.96%-15.51%, 2.73%-4.13%, and 18.53%-19.10%, respectively, of VOCs concentrations at different O3 concentration levels. Among them, the proportion of alkanes was slightly higher when O3 concentration was categorized as good or light pollution, alkenes and alkynes accounted for the highest proportion when O3 concentration was excellent, and the proportion of aromatics was highest during periods of moderate pollution. The main VOCs species were propane, ethane, ethylene, toluent, n-butane, isopentane, m/p-xylene, propylene, acetylene, n-hexane, isobutene, benzene, n-pentane, isoprene, and 1,2,3-trimethylbenzene. The concentration percentage of isopentane, n-pentane, benzene, ethylene, propylene, n-butane, and isobutane increased gradually as O3 concentration increased. Significant increases in isoprene and 1,2,3-trimethylbenzene were observed during periods of light and moderate pollution. Alkenes and aromatics had higher ozone formation potential (OFP), and the contribution of alkenes to OFP declined as the O3 level rose, whereas that of aromatics increased. Ethylene, propylene, m/p-xylene, 1,2,3-trimethylbenzene, toluene, isoprene, trans-2-butene, and cis-2-pentene were the key species for O3 generation, and the contribution ratio of 1,2,3-trimethylbenzene, isoprene, propylene, and ethylene to OFP increased significantly during light or moderate O3 pollution. Positive matrix factorization was applied to estimate the source contributions of VOCs. Automobile exhaust, solvent usage, liquefied petroleum gas (LPG)/gasoline evaporation, combustion, petrochemical industrial emissions, natural sources, and other industrial emissions were identified as major sources of VOCs in summer. As O3 concentration level rose, the contribution percentage of automobile exhaust, LPG/gasoline evaporation, petrochemical industrial emissions, and natural sources increased gradually, whereas the contribution of combustion and other industrial emissions decreased overall. The contribution of solvent usage was lower when O3 levels indicated light or moderate pollution than when it was good.

Oligomerization and Nitration of the Grass Pollen Allergen Phl p 5 by Ozone, Nitrogen Dioxide, and Peroxynitrite: Reaction Products, Kinetics, and Health Effects.

The allergenic and inflammatory potential of proteins can be enhanced by chemical modification upon exposure to atmospheric or physiological oxidants. The molecular mechanisms and kinetics of such modifications, however, have not yet been fully resolved. We investigated the oligomerization and nitration of the grass pollen allergen Phl p 5 by ozone (O3), nitrogen dioxide (NO2), and peroxynitrite (ONOO–). Within several hours of exposure to atmospherically relevant concentration levels of O3 and NO2, up to 50% of Phl p 5 were converted into protein oligomers, likely by formation of dityrosine cross-links. Assuming that tyrosine residues are the preferential site of nitration, up to 10% of the 12 tyrosine residues per protein monomer were nitrated. For the reaction with peroxynitrite, the largest oligomer mass fractions (up to 50%) were found for equimolar concentrations of peroxynitrite over tyrosine residues. With excess peroxynitrite, the nitration degrees increased up to 40% whereas the oligomer mass fractions decreased to 20%. Our results suggest that protein oligomerization and nitration are competing processes, which is consistent with a two-step mechanism involving a reactive oxygen intermediate (ROI), as observed for other proteins. The modified proteins can promote pro-inflammatory cellular signaling that may contribute to chronic inflammation and allergies in response to air pollution.

Relations between Air Quality and Covid-19 Lockdown Measures in Valencia, Spain.

The set of measures to contain the diffusion of COVID-19 instituted by the European governments gave an unparalleled opportunity to improve our understanding of the transport and industrial sectors’ contribution to urban air pollution. The purpose of this study was to assess the impacts of the lockdown measures on air quality and pollutant emissions in Valencia, Spain. For this reason, we determined if there was a significant difference in the concentration levels of different particulate matter (PM) sizes, PM10, PM2.5, and NOx, NO2, NO, and O3, between the period of restrictions in 2020 and the same period in 2019. Our findings indicated that PM pollutant levels during the lockdown period were significantly different from the same period of the previous year, even if there is variability in the different local areas. The highest variations reduction in the PM10 and PM2.5 levels were observed for the València Centre, València Avd Francia, and València Pista de Silla (all of the urban traffic type) in which there was a reduction of 58%–42%, 56%–53%, and 60%–41% respectively. Moreover, consistent with recent studies, we observed a significant reduction in nitric oxide levels in all the air monitoring stations. In all seven monitoring stations, it was observed, in 2020, NOx, NO2, and NO concentrations decreased by 48.5%–49.8%–46.2%, 62.1%–67.4%–45.7%, 37.4%–35.7%–35.3%, 60.7%–67.7%–47.1%, 65.5%–65.8%–63.5%, 60.0%–64.5%–41.3%, and 60.4%–61.6%–52.5%, respectively. Lastly, overall O3 levels decreased during the lockdown period, although this phenomenon was more closely related to weather conditions. Overall, no significant differences were observed between the meteorological conditions in 2019 and 2020. Our findings suggest that further studies on the effect of human activities on air quality are needed and encourage the adoption of a holistic approach to improve urban air quality.

Robust Inferential Techniques Applied to the Analysis of the Tropospheric Ozone Concentration in an Urban Area.

This paper analyzes 12 years of tropospheric ozone (O3) concentration measurements using robust techniques. The measurements were taken at an air quality monitoring station called Belisario, which is in Quito, Ecuador; the data collection time period was 1 January 2008 to 31 December 2019, and the measurements were carried out using photometric O3 analyzers. Here, the measurement results were used to build variables that represented hours, days, months, and years, and were then classified and categorized. The index of air quality (IAQ) of the city was used to make the classifications, and robust and nonrobust confidence intervals were used to make the categorizations. Furthermore, robust analysis methods were compared with classical methods, nonparametric methods, and bootstrap-based methods. The results showed that the analysis using robust methods is better than the analysis using nonrobust methods, which are not immune to the influence of extreme observations. Using all of the aforementioned methods, confidence intervals were used to both establish and quantify differences between categories of the groups of variables under study. In addition, the central tendency and variability of the O3 concentration at Belisario station were exhaustively analyzed, concluding that said concentration was stable for years, highly variable for months and hours, and slightly changing between the days of the week. Additionally, according to the criteria established by the IAQ, it was shown that in Quito, the O3 concentration levels during the study period were not harmful to human health.

Impacts of COVID-19 on Air Quality in India

The COVID-19 pandemic spread all over the world in early 2020. India imposed a nationwide lockdown on March 25, 2020, for more than a month to contain the COVID-19 infection. During the nationwide lockdown, transport, industries, and commercial activities were suspended, except for essential services. We made a detailed analysis of the impacts of COVID-19 on air quality in India by using the data from more than 200 Continuous Ambient Air Quality Monitoring Stations (CAAQMS) and reported a change in the National Air Quality Index (NAQI), spatial distribution and concentration levels of PM10, PM2.5, CO, NO2, SO2, and O3 from January to April 2020 nationwide and in five major cities, namely, Delhi, Mumbai, Kolkata, Chennai, and Hyderabad. We defined the period between February 25 to March 24, 2020, as ‘before lockdown’ and March 25 to April 30, 2020, as ‘during lockdown’. The NAQI and satellite visual maps of AOD, NO2, CO, and SO2 from January to April 2020 showed a significant decrease in air pollution levels in India. The average concentration levels of PM10, PM2.5, CO, NO2, and SO2 have decreased nationwide by 33, 34, 21, 47, and 21%, respectively, during the nationwide lockdown compared to their concentration levels before the lockdown. While comparing their concentration levels of the nationwide lockdown period with those observed in April 2019 at the same CAAQMS, it was found that the nationwide average concentration levels of PM10, PM2.5, CO, NO2, and SO2 were decreased by 53, 45, 27, 54, and 35%, respectively. The trends of decreasing air pollutants during the lockdown in five major cities were almost the same as nationwide. The concentration levels of O3 have shown an increasing trend from January–April 2020 including during the nationwide lockdown. The COVID-19 has provided a rare opportunity for India for the collection of air pollution baseline data which could be useful in the formulation of air pollution reduction policies in the future.

COVID-19 Fatality: Statistical Evidence to Engender the Need for Focal Shift from Air Pollutants to Multi-dimensional Intervention

Since the outbreak of COVID-19 pandemic, several researchers worldwide have suggested chronic exposure to air pollutants viz. PM2.5, NO2, and O3 as one of the influencing factors for the increased rate of fatality. However, most of these studies lacked a comprehensive international outlook. A strong correlation on a regional scale might require further investigations to evaluate the transboundary validity. Therefore, the current study aims to explore the statistical soundness of association of COVID-19 fatality with PM2.5, NO2, and O3 concentration levels across 463 air quality monitoring stations located in 35 selected cities from USA, India and European Regions (France, Germany and Italy). An aggregated open-source air quality data source was used to download the PM2.5, NO2, and O3 concentration for > 900 days in the selected cities. The median of this long-term exposure was tested against the COVID-19 fatality rates. A strength of association parameter, ω2, and the coefficient of determination, R2, were used to evaluate the transboundary association. ω2 results indicated that only 24.6%, 0.03% and 15.4% of the variation in COVID-19 fatality rates could be explained using PM2.5, NO2, and O3 concentrations respectively for all the analyzed cities. Further, low values of R2 between pollutant concentrations and COVID-19 fatality rates corroborated the results (0.27 for PM2.5, 0.00038 for NO2 and 0.18 for O3). These observations strongly suggest a focal shift towards the inclusion of more explanatory variables and an extensive multi-disciplinary work is required in order to understand the cause of COVID-19 fatality.

A Machine Learning Approach to Investigate the Surface Ozone Behavior

The concentration of surface ozone (O3) strongly depends on environmental and meteorological variables through a series of complex and non-linear functions. This study aims to explore the performances of an advanced machine learning (ML) method, the boosted regression trees (BRT) technique, in exploring the relationships between surface O3 and its driving factors, and in predicting the levels of O3 concentrations. To this end, a BRT model was trained on hourly data of air pollutants and meteorological parameters, acquired, over the 2016–2018 period, in a rural area affected by an anthropic source of air pollutants. The abilities of the BRT model in ranking, visualizing, and predicting the relationship between ground-level O3 concentrations and its driving factors were analyzed and illustrated. A comparison with a multiple linear regression (MLR) model was performed based on several statistical indicators. The results obtained indicated that the BRT model was able to account for 81% of changes in O3 concentrations; it slightly outperforms the MLR model in terms of the predictions accuracy and allows a better identification of the main factors influencing O3 variability on a local scale. This knowledge is expected to be useful in defining effective measures to prevent and/or mitigate the health damages associated with O3 exposure.

Household indoor concentration levels of NO2, SO2 and O3 in Nsukka, Nigeria

The concentrations of nitrogen dioxide (NO2), sulfur dioxide (SO2) and ozone (O3) were determined at 20 locations (10 urban and 10 rural) in both indoor (cooking areas) and ambient air in the Nsukka area during two one-week sampling periods in both dry (11–January 26, 2019) and wet (11–August 22, 2017) seasons. During the dry season, the pollutants were also measured in the living rooms (urban and rural locations) and bedrooms (urban locations). Radiello passive samplers were used to sample the target pollutants. The indoor concentration in the kitchens ranges from 15 to 722 μg/m³ (median: 174, IQR:74–336 μg/m³) for NO2, 3–101 μg/m³ (median: 5, IQR:4–9 μg/m³) for SO2 and 2–46 μg/m³ (median: 10, IQR:5–15 μg/m³) for ozone. Within the urban household, the median concentrations of the NO2 (94, IQR: 64–175 μg/m³) in the kitchens were larger than in other rooms by at least a factor 2, in contrast to SO2 (3–4 μg/m³) and O3 (14–20 μg/m³) median levels which were respectively similar in all the rooms. The indoor to outdoor (I/O) ratio with respect to the kitchens varied from 2 to 435 for NO2 and 0.6 to 25 for SO2. The O3 levels could be a factor 8, 18 and 25 higher outdoors than found respectively in the kitchens, living rooms and the bedrooms.The concentrations of NO2 are higher in households using solid fuels such as firewood (101–722 μg/m³; n = 11) and charcoal (134–356 μg/m³; n = 2) compared to those using LPG (19–174 μg/m³; n = 4). Seasonal variation of the concentration levels was observed for both indoor and outdoor environments, the outdoor concentrations of NO2, (median: 22 μg/m³, range: 10–72 μg/m3), and O3 (median: 64 μg/m³, range:14–106 μg/m3) in dry season were significantly (p ≤ 0.001) larger than the corresponding levels (median: 4 μg/m³ range:1–28 μg/m³) and (median: 10 μg/m³, range: 8–13 μg/m3) respectively in wet season. The concentration levels of outdoor SO2 (median: 4 μg/m³, range: 3–5 μg/m3) median: 4 μg/m³, range: 3–4 μg/m³ were similar in both seasons. The dry season indoor SO2 (median: 9 μg/m³, range:3–101 μg/m3) and O3 (median: 15 μg/m³, range: 10–46 μg/m3) are larger than the corresponding (median: 5 μg/m³, range: 4–8 μg/m3) and (median: 5 μg/m³, range: 2–15 μg/m3) wet season levels. However, the concentration of indoor NO2 (median 174 μg/m³, range: 18–480 μg/m³) in the dry season was lower than found (median 207 μg/m³, range: 15–722 μg/m³) in wet seasons. This work provides some novel data indicating poor indoor air quality in the study area.

A new model of ozone stress in wheat including grain yield loss and plant acclimation to the pollutant

Abstract Surface ozone (O3) is an important air pollutant globally and enhanced concentrations lead to crop yield penalties in many parts of the world. Crop models simulate production and yield and they are often used for various applications. However, most of the existing models neglect the effect of O3 and only limited parameterization schemes exist. In addition, the existing O3 modelling approaches do not take into account the plant acclimation to the pollutant as a mechanism of survival and maintenance of performance. Here, we introduce a simple modelling method to simulate the O3 damage to wheat with consideration of the plant acclimation process. The O3 parameterization scheme was incorporated into the GLAM-Parti crop model, resulting in a new model version GLAM-ROC (i.e. GLAM – Relative Ozone Concentrations). The new model simulates the effect of O3 on crop growth and development and was evaluated against data from control-environment chambers with high O3 concentration levels and variable duration of exposure to the pollutant. GLAM-ROC successfully reproduced the observed plant response to O3 as well as the final biomass and yield. The incorporation of plant acclimation allowed the prediction of crop yield loss at variable duration of O3 exposure. The statistical response formula neglected the acclimation process and overestimated the relative O3 damage to yield by 56.5%, when fumigation increased from 32 to 106 days. We conclude that the plant acclimation to chronic O3 environment is significant and should be taken into account for the effect of O3 on wheat performance and yield.