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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]

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]

Dust suppression system plays a significant role in mining and allied industries. It has become an integral part of the environmental management system. Dust emission from mining and mineral processing industries poses environmental and health problems to workers and surrounding people. Dust creates a reliability issue in machinery and ventilation systems, causing infrastructural damage and the industry's financial losses. This paper deals with a smart dry fog dust suppression system which has been developed for effectively controlling dust emission from mining and mineral processing activities. The system has been implemented in an iron ore crushing and screening plant in India, and its efficacy has been evaluated for controlling dust emission. The installed dry fog system reduced dust concentration to 0.10–0.17 mg m−3 from the prevailing dust concentration of 0.62–1.73 mg m−3 in work zone areas, which was much below the permissible limit below 1 mg m−3 where silica content in the dust was less than 5%. Percentage of free silica in the work zone dust reduced to traces from 3.61 to 4.80%. Similarly, PM10 and PM2.5 concentrations in the ambient air were decreased to 90–99 μg m−3 and 49–58 μg m−3 from 185 to 250 μg m−3 and 148–200 μg m−3, respectively. Further, concentrations of PM10 and PM2.5 were drastically reduced by 51.35–60.4% and 69.69–71.0%, respectively. The reduced dust concentrations in the ambient air were within the prescribed limit of PM10 (100 μg m−3) and PM2.5 (60 μg m−3). The system significantly reduces dust and free silica concentration in the work zone areas below the permissible limit. The system controls dust emission with an increase in production as it has been found that the number of nozzles is directly correlated with a reduction in dust. Furthermore, the system does not change the raw material's mass as water added to dust is less than 0.01% of the raw material. The system is designed to give the best results within the closed environment of the plant. The system helps in eco-friendly and clean mining. The system reduces the breakdown and maintenance cost of mining equipment, thereby decreasing overall operating costs. Further, the system minimizes mine workers' health problems, like silicosis and severe other occupation diseases. The system is automatic, cost-effective, energy efficient, and easy to maintain. Further, the system is capable of handling dust problems in the closed environment of crushing and screening plants. These properties make the system techno-economically feasible for installation in mineral processing plants. [ABSTRACT FROM AUTHOR]

The current nationally determined contributions, pledged by the countries under the Paris Agreement, are far from limiting climate change to below 2 ∘C temperature increase by the end of the century. The necessary ratcheting up of climate policy is projected to come with a wide array of additional benefits, in particular a reduction of today's 4.5 million annual premature deaths due to poor air quality. This paper therefore addresses the question how climate policy and air pollution–related health impacts interplay until 2050 by developing a comprehensive global modeling framework along the cause and effect chain of air pollution–induced social costs. We find that ratcheting up climate policy to a 2 ∘ compliant pathway results in welfare benefits through reduced air pollution that are larger than mitigation costs, even with avoided climate change damages neglected. The regional analysis demonstrates that the 2 ∘C pathway is therefore, from a social cost perspective, a "no-regret option" in the global aggregate, but in particular for China and India due to high air quality benefits, and also for developed regions due to net negative mitigation costs. Energy and resource exporting regions, on the other hand, face higher mitigation cost than benefits. Our analysis further shows that the result of higher health benefits than mitigation costs is robust across various air pollution control scenarios. However, although climate mitigation results in substantial air pollution emission reductions overall, we find significant remaining emissions in the transport and industry sectors even in a 2 ∘C world. We therefore call for further research in how to optimally exploit climate policy and air pollution control, deriving climate change mitigation pathways that maximize co-benefits. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is one of the biggest health calamities that the world has faced, which has infected millions of people and lead to hundreds of thousands of deaths all over the world. It has impacted the economic, social and health aspects of the countries to quite an extreme level. But an indirect positive impact can also be seen on the environment. In this paper, taking the example of Delhi, one of the most polluted cities of India, an analysis has been done to compare the levels of air pollutants (PM2.5, PM10, NOx and ozone) during the lockdown and the same period in the previous years. The study shows that the extent to which the industries, vehicles, power plants etc. release the air pollutants and severely impact the environment and human health. As during the lockdown when all such activities were either stopped or very much restricted, a reduction of almost 60% in the particulate matter pollution and up to 40% in the NOx pollution was observed while the ozone levels were reduced by 30-40% as compared to the same period during the previous two years. In the end, some suggestions have been made which can play some part to control air pollution once the lockdown is over. [ABSTRACT FROM AUTHOR]

In recent studies, various reports reveal that stubble burning of crop residues in India generates nearly 150 million tons of carbon dioxide (CO2), more than 9 million tons of carbon monoxide (CO), a quarter-million tons of sulphur oxides (SOX), 1 million tons of particulate matter and more than half a million tons of black carbon. These contribute directly to environmental pollution, as well as the haze in the Indian capital, New Delhi, and the diminishing glaciers of the Himalayas. Although stubble burning crop residue is a crime under Section 188 of the Indian Penal Code (IPC) and the Air and Pollution Control Act (APCA) of 1981, a lack of implementation of these government acts has been witnessed across the country. Instead of burning, crop residues can be utilized in various alternative ways, including use as cattle feed, compost with manure, rural roofing, bioenergy, beverage production, packaging materials, wood, paper, and bioethanol, etc. This review article aims to present the current status of stubble-burning practices for disposal of crop residues in India and discuss several alternative methods for valorization of crop residues. Overall, this review article offers a solid understanding of the negative impacts of mismanagement of the crop residues via stubble burning in India and the other more promising management approaches including use for bioenergy, which, if widely employed, could not only reduce the environmental impacts of crop residue management, but generate additional value for the agricultural sector globally. [ABSTRACT FROM AUTHOR]

This world has a wide range of technologies and possibilities that are available to control air pollution. Still, finding the best solution to control the contamination of the air without having any impact on humans is a complicated task. This proposal helps to improve the air quality using the multi-criteria decision making method. The decision to improve air quality is a challenging problem with today's technology and environmental development level. The multi-criteria decision making method is quite often faced with conditions of uncertainty, which can be tackled by employing fuzzy set theory. In this paper, based on an objective weighting method (CCSD), we explore the improved fuzzy MULTIMOORA approach. We use the classical Interval-Valued Triangular Fuzzy Numbers (IVTFNs), viz. the symmetric lower and upper triangular numbers, as the basis. The triangular fuzzy number is identified by the triplets; the lowest, the most promising, and the highest possible values, symmetric with respect to the most promising value. When the lower and upper membership functions are equated to one, we get the normalized interval-valued triangular fuzzy numbers, which consist of symmetric intervals. We evaluate five alternatives among the four criteria using an improved MULTIMOORA method and select the best method for improving air quality in Tamil Nadu, India. Finally, a numerical example is illustrated to show the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Electric vehicles have attracted the attention of India's policy makers as clean technology alternatives due to their multiple advantages like higher efficiency and lower air pollution in short to medium term and reduced CO 2 emissions as electricity gets decarbonized in the long-run under low carbon scenarios. This paper uses an energy system model ANSWER-MARKAL to analyse the role of electric vehicles (EV) in India. The modelling assessment spans the period 2010 to 2050 and analyses future EV demand in India under three scenarios: i) a ‘Reference’ scenario which includes the continuation of existing EV policies as outlined in India's Intended Nationally Determined Contribution (INDC); ii) a ‘EV policy’ scenario which, in line with India's INDCs, follows targeted supply-side push policies for EVs, but without the budget constraints; and iii) a ‘low carbon’ scenario which uses an exogenous price for CO 2 in line with the global target of 2 °C temperature stabilization. The scenarios analysis delineates penetration of EVs and their co-benefits as well as co-costs. The co-benefits relate to local air quality, national energy security and CO 2 emissions in India whereas the co-costs (risks) are related to sourcing of raw materials for batteries and battery reprocessing and disposal. The findings show that: i) in the reference scenario, the EVs 2-wheelers will achieve a significant share by 2050. Electric 4-wheelers though would have a small share even in 2050; ii) EV push policies though lead to significant diffusion of electric 2- wheelers in India by 2030. These policies enhance diffusion of electric 4-wheelers only if financial incentives are sustained in the long-term, iii) the application of global carbon price on the Indian economy in the 2° C stabilization scenario increases competitiveness of EVs and results in near total share of electric 2-wheelers by 2030 and a sizable share of electric 4-wheelers by 2050. The high and rising carbon price in low carbon scenario cause deep decarbonisation of electricity and enables EVs to deliver deep cut in CO 2 emissions. The results show asymmetry in the impacts of national and global policies on co-benefits from EV. The EV supply-push policies deliver moderate benefits vis-à-vis air pollution and energy security indicators but make insignificant contribution CO 2 emissions reduction. On the other hand, the global carbon price in the global 2° C stabilization scenario delivers sizable co-benefits vis-à-vis all three indicators. This asymmetry reveal important policy insights: i) the policy sequencing is vital to gain co-benefits, ii) EV technology push policies are good for creating early domestic market for a clean vehicle technology but they may not deliver sizable co-benefits vis-à-vis CO 2 emissions which are global externalities, and iii) implementing strong climate policies early would lead to EVs delivering high co-benefits, in case of India, vis-à-vis all three indicators. [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]

Deterioration of air quality through the combustion of hydrocarbon fuels has been one of the global transboundary problems put before the research community since last five decades. According to the updated statistics, 79% of energy needs in India are met by fossil fuel combustion which results in the emission of toxic pollutants like carbon monoxide, oxides of nitrogen, and unburned hydrocarbons. Air quality has seriously been affected in many parts of India, and statistically, 13 out of 15 most polluted cities in the world lie in India. Magnetic field-assisted combustion has been proven as a reliable technology in internal combustion engines for enhancing the combustion of fuels and reduction of harmful emissions that are the byproducts of incomplete combustion of fuels. In the present work, the magnetic field-assisted combustion of a liquid-phase and a gas-phase fuel (gasoline and LPG) has been studied in a multicylinder automobile engine replicating on road driving conditions in a laboratory focusing on the levels of emissions in comparison with normal combustion of both the fuels. The experimental study concludes that the applied magnetic field positively influences combustion, resulting in reduced level of emission of toxic components irrespective of the phase of hydrocarbon fuels. It is also observed that the percentage reduction in emissions increases with increase in intensity of magnetization. The maximum reduction obtained for CO and UBHC emissions through this technique is 20.58% and 14.47%, respectively. The effectiveness of MFAC in countering air pollution from vehicular exhaust is also studied with respect to fuel phase and mode of operation. The effectiveness of MFAC is observed to be more in high-speed operation of the engine and decreases in the order CO > UBHC > NO. The obtained emission results have a cumulative significance as 45% of total air pollution in India is caused by combustion of hydrocarbons in automotive engines. [ABSTRACT FROM AUTHOR]

Aim The association of air pollution with prevalence of undernutrition indices (namely, anaemia, stunting, wasting and underweight) among under-five children in India was investigated. Methods Estimates of population weighted annual average gridded PM2.5 concentrations and proportion of households using solid cooking fuel (HSCF usage percent) during 2017 in India, reflecting the magnitude of ambient and household air pollution respectively, were extracted in a state-wise manner from India State Level Disease Burden Initiative (ISLDBI) reports. Their relationships with the corresponding prevalence of anaemia, underweight, wasting and stunting in under-five children were analysed. Results The state-level PM2.5 concentrations (mean: 65.5 µg/m3; median: 49.2 µg/m3; range: 17.3–209.0 µg/m3) correlated significantly (P < 0.01) with anaemia (r = 0.65), stunting (r = 0.58) and underweight (r = 0.50) prevalence; while HSCF usage (mean: 49.3%; median: 46.0%; range: 1.9–81.5%) correlated significantly (P < 0.01) with stunting (r = 0.69) and underweight (r = 0.58) prevalence. When examined across median cut-offs and after adjusting for socio-demographic index, the association of anaemia prevalence with PM2.5 concentrations persisted. This association was maintained even after controlling for the coverage of anaemia-specific interventions (namely, iron supplements and deworming medications). The mean difference in PM2.5 concentrations between the high and low PM2.5 states was 58.6 µg/m3, which accounted for 11.8% higher anaemia prevalence in the former as compared to the latter. Conclusion The burden of childhood undernutrition, particularly anaemia, in India may be linked to PM2.5 levels. To mitigate this burden, it may be necessary to complement the ongoing nutritional interventions with air pollution control measures. [ABSTRACT FROM AUTHOR]