ArticleEnvironmental monitoring and assessment2022
Prediction and assessment of the impact of COVID-19 lockdown on air quality over Kolkata: a deep transfer learning approach.
Article in Environmental monitoring and assessment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Comparative Impacts of Freight and Non-truck Traffic on NOACS ES&T air · 2026Article
- Deep transfer learning and attention based P2.5 forecasting in Delhi using a decade of winter season data.Scientific reports · 2025Article
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Authors and funding
2 authors.
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Abstract
The present study focuses on the prediction and assessment of the impact of lockdown because of coronavirus pandemic on the air quality during three different phases, viz., normal periods (1 January 2018-23 March 2020), complete lockdown (24 March 2020-31 May 2020), and partial lockdown (1 June 2020-30 September 2020). We identify the most important air pollutants influencing the air quality of Kolkata during three different periods using Random Forest, a tree-based machine learning (ML) algorithm. It is found that the ambient air quality of Kolkata is mainly affected with the aid of particulate matter or PM (PM
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