A5018725721- Air Quality Monitoring and Forecasting
- Air Quality and Health Impacts
- Atmospheric chemistry and aerosols
- COVID-19 impact on air quality
- Water Quality Monitoring Technologies
- Aerosol Filtration and Electrostatic Precipitation
- Water Quality Monitoring and Analysis
- Odor and Emission Control Technologies
Indian Institute of Technology Bombay
2021-2024
Air quality is a global concern, with particulate matter receiving considerable attention due to its impact on human health and climate change. Recent advances in low-cost sensors allow their deployment large number measure spatio-temporal real-time air data. Low-cost need careful evaluation both regulatory approved methods other data sets understand efficacy. In this work, PM concentrations measured by deploying at four regional sites are evaluated through comparison satellite-based model...
Low-cost sensors (LCS) have the potential to provide accurate and reliable measurements of air quality in real-time. This improves our ability monitor, identify sources pollution develop mitigation strategies for effective management. However, recent research on LCS has primarily focused monitoring, exposure assessment, calibration. In this study, we investigate applicability data collected at ambient sites characterizing apportioning aerosol sources. Non-negative matrix factorization (NMF)...
Factor analysis (FA) receptor models are widely used for source apportionment (SA) due to their ability extract the contribution and profile from data. However, there is subjectivity in identification labelling manual interpretation, which time-consuming. This raises a barrier development of real-time SA process. In this study, machine learning (ML) classification algorithm, k-nearest neighbour (kNN), applied profiles obtained United States Environmental Protection Agency's (US EPA) SPECIATE...
Poor air quality is a major environmental concern worldwide, but people living in low- and middle-income countries are disproportionately affected. Measurement of PM2.5 essential for establishing regulatory standards developing policy frameworks. Low-cost sensors (LCS) can construct high spatiotemporal resolution network, the calibration dependencies subject to biases LCS due variable meteorological parameters limit their deployment air-quality measurements. This study used data collected...
Low-cost sensors (LCS) are gathering the interest of researchers and monitoring agencies worldwide due to their compact size economic feasibility. However, data recorded by LCS is often low quality owing its calibration dependencies biases. An intensive field sampling campaign was conducted at five sites inside IIT Bombay campus understand fundamental issues associated with LCS. PA-II OPC-N2 were collocated BAM-1020 OPS- 3330 at locations for inter-comparison. shows a good...
Particle exposure affects more humans globally than any other air pollutant. However, due to expensive instruments and infrastructural deficiency, a high spatiotemporal network of monitoring stations is not possible, leading data-scarce regions. Satellite reanalysis datasets can be implemented estimate particulate matter, but they do provide surface concentration needs reconstructed from the components. In this study, machine learning (ML) framework reconstruct PM2.5 MERRA-2 data components,...