This research was established to accurately forecast daily scale air quality index (AQI) which is an essential environmental index for decision-making. Researchers have projected different types of models and methodologies for AQI forecasting, such as statistical techniques, machine learning (ML), and most recently deep learning (DL) models. The modelling development was adopted for Delhi city, India which is a major city with air pollution issues simialir to entire urban cities of India especially during winter seasons. This research was predicted AQI using different versions of DL models including Long-Short Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM) and Bidirectional Recurrent Neural Networks (Bi-RNN) in addition to Kernel Ridge Regression (KRR). Results indicated that Bi-RNN model consistently outperformed the other models in both training and testing phases, while the KRR model consistently displayed the weakest performance. The outstanding performance of the models development displayed the requirement of adequate data to train the models. The outcomes of the models showed that LSTM, BI-LSTM, KRR had lower performance compared with Bi-RNN models. Statistically, Bi-RNN model attained maximum cofficient of determination (R2 = 0.954) and minimum root mean square error (RMSE = 25.755). The proposed model in this research revealed the robust predictable to provide a valuable base for decision-making in the expansion of combined air pollution anticipation and control policies targeted at addressing composite air pollution problems in the Delhi city.
Nitrogen dioxide (NO2) and sulfur dioxide (SO2) are two major atmospheric pollutants that significantly threaten human health, the environment, and ecosystems worldwide. Despite this, only some studies have investigated the spatiotemporal hotspots of NO2 and SO2, their trends, production, and sources in Asia. Our study presents a literature review covering the production, trends, and sources of NO2 and SO2 across Asian countries (e.g., Bangladesh, China, India, Iran, Japan, Pakistan, Malaysia, Kuwait, and Nepal). Based on the findings of the review, NO2 and SO2 pollution are increasing due to industrial activity, fossil fuel burning, biomass burning, heavy traffic movement, electricity generation, and power plants. There is significant concern about health risks associated with NO2 and SO2 emissions in Bangladesh, China, India, Malaysia, and Iran, as they pay less attention to managing and controlling pollution. Even though the lack of quality datasets and adequate research in most Asian countries further complicates the management and control of NO2 and SO2 pollution. This study has NO2 and SO2 pollution scenarios, including hotspots, trends, sources, and their influences on Asian countries. This study highlights the existing research gaps and recommends new research on identifying integrated sources, their variations, spatiotemporal trends, emission characteristics, and pollution level. Finally, the present study suggests a framework for controlling and monitoring these two pollutants' emissions.
The COVID-19 pandemic enforced nationwide lockdown, which has restricted human activities from March 24 to May 3, 2020, resulted in an improved air quality across India. The present research investigates the connection between COVID-19 pandemic-imposed lockdown and its relation to the present air quality in India; besides, relationship between climate variables and daily new affected cases of Coronavirus and mortality in India during the this period has also been examined. The selected seven air quality pollutant parameters (PM10, PM2.5, CO, NO2, SO2, NH3, and O3) at 223 monitoring stations and temperature recorded in New Delhi were used to investigate the spatial pattern of air quality throughout the lockdown. The results showed that the air quality has improved across the country and average temperature and maximum temperature were connected to the outbreak of the COVID-19 pandemic. This outcomes indicates that there is no such relation between climatic parameters and outbreak and its associated mortality. This study will assist the policy maker, researcher, urban planner, and health expert to make suitable strategies against the spreading of COVID-19 in India and abroad.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00500-021-06012-9.