Publication

Assessment and Prediction of Air Quality Level Using ARIMA Model: A Case Study of Surat City, Gujarat State, India

Mallikarjunaswamy, S, Fulwani, Sapna, Mahendra, H. N, Kashyap, Shubhali, Kumar, D. Mahesh, Kumari, Shilpi, Chatterjee, Aishee

2023

Overview

Air quality has recently been a huge concern as it directly affects people’s lives. An air quality level assessment and prediction system is essential to keep track of air quality. Therefore, developing an efficient air quality assessment and prediction system has become one of the most important concerns. In the present work air quality level of Surat city, India is assessed and predicted for the period from 2020 to 2023 using the Autoregressive integrated moving average (ARIMA) model. Experimental results show that the ARIMA model outperforms the other models. According to the findings, the maximum quantity of SO2 and NO2 present in the air in 2020 is 37 mm and 18 mm, respectively, with a maximum of 27 mm and 31 mm in 2021. Thus, we can observe that even though SO2 has reduced a bit, the amount of NO2 has increased, thus degrading the quality of air.

• Publisher: Technoscience Publications
• Subject: Accuracy / Air pollution / Air quality / Air quality assessments / air quality, arima model, monitoring of air, prediction system / Algorithms / Artificial intelligence / Autoregressive moving-average models / Cities / Indoor air quality / Machine learning / Neural networks / Nitrogen dioxide / Outdoor air quality / Pollutants / Predictions / Quality assessment / Quality control / Remote sensing / Sulfur dioxide / Support vector machines / VOCs / Volatile organic compounds