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The present study explores the impact of economic growth; urban expansion; and consumption of fossil fuels, solid fuels, and renewable energy on environmental degradation in developing economies of Sub-Saharan Africa. To demonstrate its findings in detail, the study adopts a system generalized method of moment (GMM) on a panel of 34 emerging economies for the period from 1995 to 2015. The results describe that the consumption of fossil and solid fuels for cooking and expansion of urban areas are significantly contributing to carbon dioxide emissions, on one end, and stimulating air pollution, on the other. The results also exhibit an inverted U-shape relationship between per capita economic growth and carbon emissions. This relation confirms the existence of an environmental Kuznets curve (EKC) in middle- and low-income economies of Sub-Saharan Africa. Furthermore, the findings reveal that the use of renewable energy alternatives improves air quality by controlling carbon emissions and lowering the direct interaction of households with toxic gases. Thus, the use of renewable energy alternatives helps the economies to achieve sustainable development targets.

In this study, the distribution and alterations of ozone concentrations in Tehran, Iran, in 2021 were investigated. The impacts of precursors (i.e., CO, NO2, and NO) on ozone were examined using the data collected over 12 months (i.e., January 2021 to December 2021) from 21 stations of the Air Quality Control Company (AQCC). The results of monthly heat mapping of tropospheric ozone concentrations indicated the lowest value in December and the highest value in July. The lowest and highest seasonal concentrations were in winter and summer, respectively. Moreover, there was a negative correlation between ozone and its precursors. The Inverse Distance Weighting (IDW) method was then implemented to obtain air pollution zoning maps. Then, ozone concentration modeled by the IDW method was compared with the average monthly change of total column density of ozone derived from Sentinel-5 satellite data in the Google Earth Engine (GEE) cloud platform. A good agreement was discovered despite the harsh circumstances that both ground-based and satellite measurements were subjected to. The results obtained from both datasets showed that the west of the city of Tehran had the highest averaged O3 concentration. In this study, the status of the concentration of ozone precursors and tropospheric ozone in 2022 was also predicted. For this purpose, the Box-Jenkins Seasonal Autoregressive Integrated Moving Average (SARIMA) approach was implemented to predict the monthly air quality parameters. Overall, it was observed that the SARIMA approach was an efficient tool for forecasting air quality. Finally, the results showed that the trends of ozone obtained from terrestrial and satellite observations throughout 2021 were slightly different due to the contribution of the tropospheric ozone precursor concentration and meteorology conditions.

Government has implemented various scattered and un-quantified control actions in Delhi city to reduce the air pollution levels; however, it still exceeds the National Ambient Air Quality Standards (NAAQS). The present study has been designed to assess the air quality status, identify Air Quality Control Region (AQCR), and evaluate control strategies in the city. Out of eight selected locations, ambient PM 10 , PM 2.5 , and NO 2 concentrations were found exceeding the daily as well as annual standards at selected AQCR with peak levels during post-monsoon than winter and summer. Anand Vihar was found to be most polluted and thus, selected as an AQCR. AERMOD performed satisfactorily in predicting pollutant concentration during winter and summer having an index of agreement in the range 0.54–0.80. PM 10 and PM 2.5 can be reduced substantially by increasing frequency of efficient mechanized cleaning of roads and sprinkling of water on the roads. Progressive decrease in NO 2 concentrations can be achieved by restricting entry of truck in the study area through alternate path. The cumulative impact of all selected control strategies indicates a substantial decrease in air pollution within AQCR. The study also suggests a policy framework to manage the urban air quality through local scale air quality guidelines.

Few studies regarding the health effects of long-term exposure to particulate matter with an aerodynamic diameter of 2.5 μm or less (PM 2.5 ) have been carried out in Asia or the Middle East. The objective of our study was to assess total, lung cancer and chronic obstructive pulmonary disease (COPD) mortality attributed to long-term exposure to PM 2.5 among adults aged over 30 years in Tehran from March 2013 to March 2016 using AirQ + software. AirQ + modeling software was used to estimate the number of deaths attributed to PM 2.5 concentrations higher than 10 μg m −3 . Air quality data were obtained from the Department of Environment (DOE) and Tehran Air Quality Control Company (TAQCC). Only valid stations with data completeness of 75% in all 3 years were selected for entry into the model. The 3-year average of the 24-h concentrations was 39.17 μg m −3 . The results showed that the annual average concentration of PM 2.5 in 2015–2016 was reduced by 13% compared to that in 2013–2014. The annual average number of all natural, COPD, and lung cancer deaths attributable to long-term exposure to PM 2.5 in adults aged more than 30 years was 5073, 158, and 142 cases, respectively. The results of all three health endpoints indicate that the mortality attributable to PM 2.5 decreased yearly from 2013 to 2016 and that the reduced mortality was related to a corresponding reduction in the PM 2.5 concentration. Considering these first positive results, the steps that have been currently taken for reducing air pollution in Tehran should be continued to further improve the already positive effects of these measures on reducing health outcomes.

In southern Chile, epidemiological studies have linked high levels of air pollution produced by the use of wood-burning stoves with the incidence of numerous diseases. Using a quasi-experimental design, this study explores the potential of participatory sensing strategies to transform experiences, perceptions, attitudes, and daily routine activities in 15 households equipped with wood-burning stoves in the city of Temuco, Chile. The results suggest that the experience of using a low-cost sensor improves household members’ awareness levels of air pollution. However, the information provided by the sensors does not seem to improve the participants’ self-efficacy to control air quality and protect themselves from pollution. The high degree of involvement with the participatory sensing experience indicates that the distribution of low-cost sensors could be a key element in the risk communication policies.

The COVID-19 pandemic caused a setback for Nepal, leading to nationwide lockdowns. The study analyzed the impact of lockdown on air quality during the first and second waves of the COVID-19 pandemic in the Kathmandu Valley. We analyzed 5 years of ground-based air quality monitoring data (2017–2021) from March to July and April to June for the first and second wave lockdowns, respectively. A significant decrease in PM 2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 μm) concentrations was observed during the lockdowns. The highest rate of decline in PM 2.5 levels was observed during May and July compared to the pre-pandemic year. The PM 2.5 concentration during the lockdown period remained within the WHO guideline limit and NAAQS for the maximum number of days compared to the lockdown window in the pre-pandemic years (2017–2019). Likewise, lower PM 2.5 levels were observed during the second wave lockdown, which was characterized by a targeted lockdown approach (smart lockdown). We found a significant correlation of PM 2.5 concentration with community mobility changes (i.e., walking, driving, and using public transport) from the Spearman correlation analysis. Lockdown measures restricted human mobility that led to a lowering of PM 2.5 concentrations. Our findings can be helpful in developing urban air quality control measures and management strategies, especially during high pollution episodes.

Techniques for improving the removal of pollution from urban canyons are crucial for air quality control in cities. The removal mainly occurs at the building roof level, where it is supported by turbulent mixing and hampered by roof shear, which tends to isolate the internal canyon region from the atmospheric flow. Here, a modification of roof infrastructures is proposed with the aim of increasing the former and reducing the latter, overall enhancing the removal mechanisms. The topic is investigated by numerical experiment, using large-eddy simulation to study the paradigmatic case of a periodic square urban canyon at Re=2×104. Two geometries are analyzed: one with a smooth building roof, the other having a series of solid obstacles atop the upwind building roof. The pollutant is released at the street level. The simulations are successfully validated against laboratory and numerical datasets, and the primary vortex displacement detected in some laboratory experiments is discussed. The turbulence triggered by the obstacles destroys the sharp shear layer that separates the canyon and the surrounding flow, increasing the mixing. Greater vertical turbulent mass fluxes and more frequent ejection events near the upwind building (where pollution accumulates) are detected. Overall, the obstacles lead to a reduction in the pollution concentration within the canyon of about 34%.

Novel machine learning models (MLMs) using the seasonal indexing approach that captures the variation in air quality caused due to meteorological changes have been used to provide short-term, real-time forecasts of PM 2.5 concentration for one of the most polluted air quality control regions (AQCR) in the capital city of Delhi. Two MLMs—multi-linear regression and random forest—have been developed for using time series data for 1-h and 24-h average PM 2.5 concentration. Short-term, real-time forecasts have been made using the developed models. Various model performance evaluation indices indicate satisfactory model performance. R 2 values for the hourly and daily models varied between 0.95 and 0.72 and between 0.76 and 0.68 for the 1st to 5th h/day, respectively. The lagged values of PM 2.5 concentration (persistence) and the hourly and daily indices are the most influential variables for the forecasts for immediate time steps. In contrast, seasonal indices become more important with the forecasting time horizon. The developed models can be used for making short-term, real-time air quality forecasts and issuing a warning when the pollution levels go beyond acceptable limits.

Since COVID-19 pandemic, indoor air quality control has become a priority, and the development of air purification devices effective for disinfecting airborne viruses and bacteria is of outmost relevance. In this work, a photocatalytic device for the removal of airborne microorganisms is presented. It is an annular reactor filled with TiO 2 -coated glass rings and irradiated internally and externally by UV-A lamps. B. subtilis spores and vegetative cells have been employed as model biological pollutants. Three types of assays with aerosolized bacterial suspensions were performed to evaluate distinct purification processes: filtration, photocatalytic inactivation in the air phase, and photocatalytic inactivation over the TiO 2 -coated rings. The radiation distribution inside the reactor was analysed by performing Monte Carlo simulations of photon absorption in the photocatalytic bed. Complete removal of a high load of microorganisms in the air stream could be achieved in 1 h. Nevertheless, inactivation of retained bacteria in the reactor bed required longer irradiation periods: after 8 h under internal and external irradiation, the initial concentration of retained spores and vegetative cells was reduced by 68% and 99%, respectively. Efficiency parameters were also calculated to evaluate the influence of the irradiation conditions on the photocatalytic inactivation of bacteria attached at the coated rings.

Over the past 30–40 years, vehicle tailpipe emissions of particulate matter (PM), nitrogen oxides (NO x ), carbon monoxide (CO), and hydrocarbons (HCs) have decreased significantly. Advanced emission after-treatment technologies have been developed for gasoline and diesel vehicles to meet increasingly stringent regulations, yielding absolute emission reductions from the fleet despite increased vehicle travel. As a result of mobile and stationary source emission controls, air quality has generally improved substantially in cities across the US and Europe. Emission regulations (such as Tier 3 in the US, LEV III in California, and Euro 6 rules in the EU) will lead to even lower vehicle emissions and further improvements in air quality. We review historical vehicle emission and air quality trends, discuss the future outlook for air quality, and note that modern internal combustion engine vehicles typically have lower exhaust emissions than battery electric vehicle upstream emissions. As vehicle manufacturers and city officials grapple with questions about future mobility in cities, we raise the question “how low should we go?” for future vehicle criteria emissions. The answer to this question will have profound implications for automotive and fuel companies and for the future economic and environmental health of urban areas.