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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]

During 2019 to 2022, a comprehensive study was conducted across 71 stations spanning over 15 states in India to investigate air quality variations during the pre-Diwali, Diwali, and post-Diwali periods. The investigation, centred on the extensive use of firecrackers during festive times, revealed a short-term deterioration in air quality with long-lasting impacts. PM2.5 and PM10 levels were found to significantly increase during Diwali and the post-Diwali period compared to the pre-Diwali period. The levels of PM2.5 and PM10 experience respective increases of 44.66% and 11.03%, 29.12% and 05.41%, 52.63% and 23.38%, and 39.65% and 17.61% during Diwali period from 2019 to 2022, where 68.84% and 34.32%, 44.42% and 29.42%, and 48.70% and 25.22% in 2019, 2021 and 2022 in post-Diwali period compared to the pre-Diwali. The Mann–Kendall and Sen's slope analyses reveal statistically significant positive trends (increasing) in both PM10 and PM2.5 levels during the Diwali festival period. Notably, the study introduced the Health Hazard-based Air Quality Index (HAQI), which demonstrated higher values than the National Ambient Air Quality Index (NAAQI). Unlike NAAQI, which considers individual pollutant sub-index values, and considered highest one of sub-index values in AQI analysis. HAQI provides a more comprehensive assessment of health risks associated with exposure to multiple pollutants effects. In 2022, AQI and HAQI values during pre-Diwali were 114 and 146.18, during Diwali were 173 and 332.18, and post-Diwali were 191 and 414.14, respectively. These findings underscore the elevated risk during Diwali and the post-Diwali period due to heightened pollution levels, emphasizing the need for public awareness and potential mitigation strategies. The study calls attention to the importance of considering cumulative health impacts and suggests the adoption of HAQI for more informative air quality assessments. [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]