Impact of COVID-19 lockdown and meteorology on the air quality of Srinagar city: A temperate climatic region in Kashmir Himalayas

Asif, Mohammad; Mahajan, Pranav

doi:10.1016/j.heha.2022.100025

Cited by 3 publications

(1 citation statement)

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“…Our study employed MLR to assess the significance Table 4 of data from 2017 to 2022, as well as to analyze the relationship between air quality and meteorological factors. [5] The multiple linear regression model can be described as shown in Equation 3. In the linear equation (Eq.3), where Y represents the AQI value for observation i and x denotes the meteorological variables, a stand for the intercept term, bm represents the regression coefficient for meteorological factor m, and ε is the error term.…”

Section: Multi Linear Regression Model (Mlr)mentioning

confidence: 99%

Spatial Temporal Analysis of Air Quality and their Relation to Meteorological Parameters, in India

Suman Dash,

Aniruddha Jena

2024

Int Res J Adv Engg Mgt

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Air pollution has become a significant global issue, with India ranking 8th in the world for hazardous air quality based on the latest 2022 report. (World Air Quality Report 2023). The growing urban sprawl and human-induced environmental activities have led to a decline in air quality. The Air Quality Index assesses the level of pollution in the air at a particular region. It is a fundamental right for individuals to be informed about the quality of the air they breathe for their well-being. This study aims to examine air pollution levels and trends across various geographical locations in India using data provided by the Central Pollution Control Board under the Ministry of Environment, Forest, and Climate Change in India. The study focuses on analyzing the annual growth of pollutants such as SO2, NO2, PM10, and PM2.5 from 2016 to 2021, collected from monitoring stations in 28 states across 256 locations. The research evaluates the impact of different particulate matter concentrations and showcases the spatial variation of air pollutants between 2016 and 2021. Results indicate a significant decrease in air pollution levels during lockdown periods compared to pre-lockdown periods. On an average (over all cities), more than 24% decrease has been observed for all the AQI of the pollutants. Additionally, a comparative analysis reveals correlations between meteorological factors and air quality, showing that temperature, relative humidity, and wind speed are negatively correlated with AQI, while surface pressure is positively correlated. Temporal analysis was also conducted to examine the relationship between air pollutant concentrations and meteorological parameters.

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Section: Multi Linear Regression Model (Mlr)mentioning

confidence: 99%