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Diwali has become an occasion of air and noise pollution, and the release of particulate matter and toxic gases has chronic and acute effects on people and their environment. Thus, an air quality assessment study was done by CSIR-CSMCRI covering the pre-to-post Diwali 2021 period (5 days) in the three locations (traffic, residential, and control) of Bhavnagar. The average 24-h concentration of PM10 (380 µg/m3), PM2.5 (182.2 µg/m3), and SPM (403 µg/m3) was significantly higher during Diwali, exceeding the National Ambient Air Quality Standards (NAAQS). The concentrations of SO2 and NO2 were 121.8 µg/m3 and 102.1 µg/m3. Metals like Zn, Al, Pb, and Mn were found in higher concentrations during the study. The air quality index (AQI) was maximum on Diwali, resembling very poor air quality. More elements and oxides were detected in PM2.5 (S, Al, Mg, Ba, and Zn and their oxides) than in PM10 (Fe and S) through WDXRF. Water-soluble anions like SO42−, Cl−, and NO3− were observed during the study, with a higher SO42− (64%) on Diwali. The PM10 morphology and mapping of elements were done using SEM–EDX. Emerging contaminants, specifically phthalate groups, were detected through GCMS. The enrichment factor (EF) showed Zn and Pb originating from anthropogenic activities. The air quality data was validated using a variance test, least significance difference (LSD), correlation, and principal component analysis (PCA). This paper is the first to highlight the air quality assessment during Diwali for a western coastal place in India. It is time to implement regulations on burning firecrackers for pollution reduction, aiming to achieve a sustainable atmosphere. [ABSTRACT FROM AUTHOR]

Over the past decades, air pollution has turned out to be a major cause of environmental degradation and health effects, particularly in developing countries like India. Various measures are taken by scholars and governments to control or mitigate air pollution. The air quality prediction model triggers an alarm when the quality of air changes to hazardous or when the pollutant concentration surpasses the defined limit. Accurate air quality assessment becomes an indispensable step in many urban and industrial areas to monitor and preserve the quality of air. To accomplish this goal, this paper proposes a novel Attention Convolutional Bidirectional Gated Recurrent Unit based Dynamic Arithmetic Optimization (ACBiGRU-DAO) approach. The Attention Convolutional Bidirectional Gated Recurrent Unit (ACBiGRU) model is determined in which the fine-tuning parameters are used to enhance the proposed method by Dynamic Arithmetic Optimization (DAO) algorithm. The air quality data of India was acquired from the Kaggle website. From the dataset, the most-influencing features such as Air Quality Index (AQI), particulate matter namely PM2.5 and PM10, carbon monoxide (CO) concentration, nitrogen dioxide (NO2) concentration, sulfur dioxide (SO2) concentration, and ozone (O3) concentration are taken as input data. Initially, they are preprocessed through two different pipelines namely imputation of missing values and data transformation. Finally, the proposed ACBiGRU-DAO approach predicts air quality and classifies based on their severities into six AQI stages. The efficiency of the proposed ACBiGRU-DAO approach is examined using diverse evaluation indicators namely Accuracy, Maximum Prediction Error (MPE), Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Correlation Coefficient (CC). The simulation result inherits that the proposed ACBiGRU-DAO approach achieves a greater percentage of accuracy of about 95.34% than other compared methods. [ABSTRACT FROM AUTHOR]

In order to survive, mankind needs air. The quality of life depends on the purity of the air we breathe in. Hazardous pollutants are stirred up in our environment by various activities everyday. In a developing country like India, which has huge population, protecting public health is important. In general, air quality is measured using the air quality index, which records the pollutants level in the air. These recordings are to be mentioned across various places, to know about the air quality level. The advancement of the recent artificial intelligence can be replaced by the human efforts and to automate the system in flowless manner. Hence, an effort has been taken in this paper, by proposing a framework of predicting the air quality seasonally using regularized combinational LSTM (REG-CLSTM). For an efficient air quality level prediction with an improved error rate, time, and accuracy, the study has implemented Reg-CLSTM with a large amount of real-time dataset. To improvise the comprehensiveness and the potentiality of the proposed model, the significant feature is extracted by the rough set-wrapper method. The significant challenge is to provide a seasonal limit range for each considered pollutant in place of a generalized range partition. Aiming at this problem, the proposed model is able to identify the highest concerning pollutants occurrence in individual seasons. Through this study, pyramid learning-based hybridized deep learning framework is developed which can play a crucial role in warning the policy maker to reduce the activities that instigate air pollution. [ABSTRACT FROM AUTHOR]

To monitor the spread of the novel coronavirus (COVID-19), India, during the last week of March 2020, imposed national restrictions on the movement of its citizens (lockdown). Although India's economy was shut down due to restrictions, the nation observed a sharp decline in particulate matter (PM) concentrations. In recent years, Delhi has experienced rapid economic growth, leading to pollution, especially in urban and industrial areas. In this paper, we explored the linkages between air quality and the nationwide lockdown of the city of Delhi using a geographic information system (GIS)-based approach. Data from 37 stations were monitored from 12 March, 2020 to 2 April, 2020 and it was found that the Air Quality Index for the city was almost reduced by 37% and 46% concerning PM2.5 and PM10, respectively. The study highlights that, in regular conditions, the atmosphere's natural healing rate against anthropogenic activities is lower, as indicated by a higher AQI. However, during the lockdown, this sudden cessation of anthropogenic activities leads to a period in which the natural healing rate is greater than the induced disturbances, resulting in a lower AQI, and thus proving that this pandemic has given a small window for the environment to breathe and helped the districts of Delhi to recover from serious issues related to bad air quality. If such healing windows are incorporated into policy and decision-making, these can prove to be effective measures for controlling air pollution in heavily polluted regions of the World. [ABSTRACT FROM AUTHOR]

Chandrapur City of Maharashtra state of India has undergone rapid industrialization, development, and infrastructure facilities along with prominent increase in population. Therefore, the present study was undertaken to study the air quality of the city. The mitigation measures of air pollution in the city were also discussed in the present study. Air quality monitoring was carried out at each monitoring station taken twice a week for 24 hours for particulate matter (PM10), particulate matter (PM2.5), sulphur dioxides (SO2), nitrogen dioxides NO2, and carbon monoxides (CO). The data revealed the high levels of particulate matter (PM10 and PM2.5) to approximately 1.56-2.15 times and 1.47-2.21 times higher than National Ambient Air Quality Standards (NAAQS), respectively and were many times higher than WHO Global Air Quality Guidelines. The major sources of pollution were the emission from industries, mining activities and traffic. Observed concentrations of SO2 (24.88 to 45 μg/m³), NO2 (45.4 to 70.6 μg/m³ ) and (0.63 to 0.88 mg/m³) were below NAAQS. The obtained data was also processed for the calculation of air quality index (AQI). The AQI value at Chandrapur super thermal power station (CSTPS) was found higher (310) followed by MIDC with AQI of 302 (Very poor air quality) mainly due to higher particulate pollution, indicating respiratory illness to the people on prolonged exposure. AQI for remaining three stations namely, Jatpura gate, Bimba gate and Babupeth ranged from 264 to 284 (Poor air quality) mainly due to vehicular pollution indicating breathing discomfort to people on prolonged exposure. All the pollutants were observed higher than the concentrations recorded in earlier studies and showed increasing trend as compared to records of previous studies. [ABSTRACT FROM AUTHOR]

The current study was conducted around the province of Haldwani City, Uttarakhand, India, to understand the seasonal variation of ambient air pollutants (PM2.5, PM10, SO2, and NO2) and their impact on four tree species, i.e., neem (Azadirachta indica), mountain cedar (Toona ciliate), bottlebrush (Callistemon citrinus), and guava (Psidium guajava) during 2020–2021. Multiple linear regression (MLR)-based prediction analysis showed that the selected air quality variables (PM2.5, PM10, SO2, and NO2) had a significant impact on the biochemical responses of selected tree spp. including, pH, ascorbic acid (AA), total chlorophyll content (T. Chl.), relative water content (RWC), and dust deposition potential. In this, the coefficient of variance (R2) of the developed models was in the range of 0.70–0.98. The ambient air pollutants showed significant seasonal variations as depicted by using the air pollution tolerance index (APTI) and anticipated performance index (API). The tree species from polluted sites observed more pollution tolerance than the tree species from the control site. Regression analysis showed a significant positive association between the biochemical characteristics and APTI, with the highest influence by AA (R2 = 0.961) followed by T. Chl., RWC, and pH. The APTI and API score was observed as maximum for A. indica and minimum for C. citrinus. The impact of air pollutants on the morphology of foliar surface was investigated by the scanning electron microscopy (SEM) and recorded various dust deposition patterns, stomatal blockages, and damage of guard cells in the trees growing along the polluted site (S2). The present study can assist environmental managers to examine the pollution-induced variables and develop an effective green belt for combating air pollution in polluted areas. [ABSTRACT FROM AUTHOR]

Due to massive population migration, most Indian cities have experienced rapid urbanization, increased construction activity, traffic and industry related pollution, and unplanned expansion. As a result, pollution hotspots exist in these cities with levels well surpassing the authorized mark. Air pollution is generally classified as extremely hyper-local, indicating that the pollution index decreases as we travel away from hotspots. Since the pollution data collected from traditional sources is occasionally inadequate, the extended consequences of such hotspots on neighbouring communities remain largely unidentified. If the flux in pollution values in neighbouring locales is efficiently mapped as we move away from identified hotspots, AQI levels for these areas can be fore casted and projected. In this research, the Air Quality Index (AQI) data was accurately gathered at an identified pollution hotspot and its immediate neighbourhood over a defined period along a specific route. A mathematical model was then developed to forecast how AQI varies with distance into the neighbourhood, as we move away from the hotspots. [ABSTRACT FROM AUTHOR]

Mining is a significant part of the transforming economy, which is generally considered as essential as well as social evil at the same time. It is one of the potential contributors to air and water pollution and possesses long-term impact on their quality. Keeping in view the exponential mining activities, we have selected an iron mine area in Bailadila, Chhattisgarh, India, as a sampling site and investigated the impact of mining activities on the air as well as water quality by setting up seven air quality and thirty water quality monitoring stations. From the results obtained, it was observed that concentration of air pollutants such as SO2, NO2, PM2.5 and PM10 for the year 2015 lies in the range of 11.5–13.0 µg/m3, 11.5–13.0 µg/m3, 24.9–33.4 ppm and 61.6–74.2 ppm, respectively, while for the year 2018, it lies in the range of 10.3–11.7 µg/m3, 10.5–14.7 µg/m3, 18.3–50.8 ppm and 23.7–60.7 ppm, respectively. Furthermore, results obtained revealed that air pollutants such as SO2, NO2, PM2.5 and PM10 were within the permissible limits but they contributed towards the light air pollution (air pollution index: 25–50) at all the air monitoring stations. Moreover, PM10 was considered as criterion pollutant in the Bailadila, Chhattisgarh region. On the other hand, it was observed that groundwater quality was deteriorated in the subsequent years. Most of the water quality parameters were in the permissible limits except iron (Fe). Moreover, on the basis of water quality indexing, water quality was classified as "poor" in ~ 30% of the sites and "very poor" in ~ 34% sites. The water quality was "unhealthy for drinking" in 3% and 6% sites in the year 2015 and 2018, respectively. [ABSTRACT FROM AUTHOR]

Most governmental initiatives in India, to leash down urban air pollution, have yielded little results till date, largely due to purely technocratic vision, which is shrouded by technological, economic, social, institutional, and political hardships. We present this reflective article on urban greenery, as a proposition to urban authorities (e.g., pollution regulators, environmental systems' managers, urban landscape planners, environmental policy makers), shift from purely technocratic way of thinking to thinking with nature, by strategic greening of urban spaces, for long-term air pollution prevention and control measures. To that end, we offer a meta-analysis of recent (post 2005) global literature using four-stage PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach. We open the narrative by briefing about main pollutant filtration mechanisms by trees, followed by cognitive aspects of species selection (e.g., deciduous vs. evergreen, air pollution tolerance index, environmental stressors). Till date, most Indian studies on urban greenery mostly but focused on physiological aspects of trees. Here, we draw attention of urban authorities to an equally compelling, but yet less explored, aspect: design criteria, with reference to two most common urban configurations, namely, street canyon and open road. With pictorial depictions, we enumerate various categories of street canyons and discuss aspect ratio (building height to street width) and various wind flow regimes (isolated roughness, wake interface, and skimming), that the urban authorities should be cognizant about to maximize pollutant removal efficiency. For open road, we discuss vegetation barriers, with special emphasis on canopy porosity/density functions. In the final sections, we reflect on a potential systems' thinking approach for on-ground implementation, comprising of revamping of urban forestry programs, research and development, community mobilization and stakeholder engagement, and strategic outreach. In addition, we emphasize on means to harness co-benefits of urban greenery, beyond mere pollutant removal, to garner support from urban residents' communities. Last but not the least, we also caution the urban authorities about the undesirable outcomes of urban greenery that will require more process-level research. [ABSTRACT FROM AUTHOR]

The impact of air pollution on the roadside plants in the Hadapsar suburban was determined using six different plant species. To assess the effects of air pollutants on roadside plants of Hadapsar area in Pune city, APTI (Air Pollution Tolerance Index) was determined of six plant species. Plants species selected for the study were Polyalthia long folia, Ficus racemosa, Terminalia catappa, Ficus benghalensis, Ficus religiosa, Samanea saman of nearly the same age size and were found in abundance. Physiological and biochemical parameters such as pH, Relative water content (RWC), Total Chlorophyll (T.C.), Ascorbic acid (A.A.) contents were determined to calculate APTI. Results indicated that all of the plants selected for the study were found to be sensitive & heavily impacted due to air pollution. Thus, these plants can be used as Bio-indicators in monitoring air pollution. [ABSTRACT FROM AUTHOR]

Industrialization, urbanization, and rapid socioeconomic growth are the prime factors regarding development of an urban city. These activities deteriorate the environment slowly by increasing harmful pollutants and the impact of which will be observed in near future in terms of several natural calamities, disease, and ecological consequences. Various urban ecosystems like urban forestry, wetland, grassland, parks/gardens etc. are the main criteria of urban health in respect to delivering multiple of benefits to the surrounding biota. But these regulatory systems have been affected severely through different industrial pollution stresses resulting into deterioration of their physicochemical quality and biotic diversity. The study revealed that the annual average air pollution index (API) exceeded the higher threshold value (i.e. >100) during the study period and recognized Durgapur as the severely polluted region in West Bengal, India. The characteristics of major air pollutants like SO2, NOx, and suspended particulate matter (SPM) and their temporal trends have been evaluated. The objective of this study was to detect the effect of industrial pollution on the aforesaid urban ecosystems in terms of variable ecological services such as purification of polluted air, atmospheric regulation, reduction of noise, proper drainage of rainwater, and sewage treatment. The outcome of this review work was to evaluate thoroughly the physiological, biochemical, and morphological symptoms of plant species under air pollution stress. On the other hand, the effect of air pollution on human and animal populations regarding various diseases (like bronchitis, cardiopulmonary arrest, cancer, liver and kidney dysfunction) has also been discussed. [ABSTRACT FROM AUTHOR]