Journal Publications
2024
- Das, A., & Sahu, M. (2024). Leveraging Satellite Data for Predicting PM10 Concentration with Machine Learning Models: A Study in the Plains of North Bengal, India. Aerosol and Air Quality Research, 24, 240066.
- Kumar, V., Sahu, M., Biswal, B., Prakash, J., Choudhary, S., Raliya, R., Chadha, T. S., Fang, J., & Biswas, P. (2024). Real-Time Source Apportionment of Particulate Matter from Low-Cost Particle Sensors Using Machine Learning. Aerosol Science and Engineering, 1-11.
- Malyan, V., Kumar, V., Moni, M., Sahu, M., Prakash, J., Choudhary, S., Raliya, R., Chadha, T. S., Fang, J., & Biswas, P. (2024). Assessing the spatial transferability of calibration models across a low-cost sensors network. Journal of Aerosol Science, 181, 106437.
- Kumar, V., Malyan, V., Sahu, M., & Biswal, B. (2024). Aerosol sources characterization and apportionment from low-cost particle sensors in an urban environment. Atmospheric Environment: X, 22, 100271.
- Sahu, M., Seth, I., George, S. J., & Maitra, U. (2024). Off–On Pathway Complexity in Self-Assembly of Cadmium Cholate Hydrogel with Topological Evolution Triggered by Secondary Nucleation. Chemistry of Materials.
- Kumar, V., Malyan, V., Sahu, M., & Biswal, B. (2024). Aerosol sources characterization and apportionment from low-cost particle sensors in an urban environment. Atmospheric Environment: X, 22, 100271.
- Malyan, V., Kumar, V., Sahu, M., Prakash, J., Choudhary, S., Raliya, R., Chadha, T. S., Fang, J., & Biswas, P. (2024). Calibrating low-cost sensors using MERRA-2 reconstructed PM2.5 mass concentration as a proxy. Atmospheric Pollution Research, 15(3), 102027.
- Prajapati, B., Dharaiya, V. R., Sahu, M., Venkatraman, C., Biswas, P., Yadav, K., Pullokaran, D., Raman, R. S., Bhat, R., Najar, T. A., & Jehangir, A. (2024). Development of a physics-based method for calibration of low-cost particulate matter sensors and comparison with machine learning. Journal of Aerosol Science, 175, 106284.
- Ghosh, S., and Sahu, M. (2024).Ultrasound for the degradation of endocrine disrupting compounds in aqueous solution: A review on mechanisms, influence of operating parameters and cost estimation. Chemosphere, 349, 140864.
2023
- Agrawal, A., and Sahu, M. (2023). Forecasting PM2.5 Concentrations using Statistical Modeling for Bengaluru and Delhi Regions, Environmental Monitoring and Assessment, 2023, 195, 502.
- Chen, S., Cao, Q., Kuehn, T. H., Lo, C., Sahu, M., Mayya, Y. S., and D. Y. H. Pui, D. Y. H. (2023). Design of a Medium Scale Ambient PM2.5 Cleaning System, Aerosol and Air Quality Research, 23 (2),220437.
- Nishad V., Mandal, C., and Sahu, M. (2023). Study of Bioaerosol Disinfection Kinetics and Application of Non-linear Regression Analysis for Optimization of TiO2 based Photocatalytic Disinfection Process. Nanotechnology for Environmental Engineering.
- Ghosh, S., & Sahu, M. (2023). Adsorptive removal of dimethyl phthalate using peanut shell-derived biochar from aqueous solutions: equilibrium, kinetics, and mechanistic studies. Environmental Science and Pollution Research.
- Kumar, V., Malyan, V., Sahu, M., Biswal, B., Pawar, M., & Dev, I. (2023). Spatiotemporal analysis of fine particulate matter for India (1980–2021) from MERRA-2 using ensemble machine learning. Atmospheric Pollution Research, 101834.
- Kumar, V., Malyan, V., Sahu, M., & Biswal, B. (2023). Machine Learning Classification Model to Label Sources Derived from Factor Analysis Receptor Models for Source Apportionment. Aerosol and Air Quality Research, 23, 220386.
- Dharaiya, V. R., Malyan, V., Kumar, V., Sahu, M., Venkatraman, C., Biswas, P., Yadav, K., Haswani, D., Raman, R. S., Bhat, R., Najar, T. A., Jehangir, A., Patil, R. P., Pandithurai, G., Duhan, S. S., & Laura, J. S. (2023). Evaluating the Performance of Low-cost PM Sensors over Multiple COALESCE Network Sites. Aerosol and Air Quality Research, 23(5), 220390.
- Kumar, A., Malyan, V., & Sahu, M. (2023). Air Pollution Control Technologies for Indoor Particulate Matter Pollution: A Review. Aerosol Science and Engineering.
- Mandal, C., Vartika Nishad, & Sahu, M. (2023). Impact of spatial distribution of light intensity on disinfection kinetics of Mycobacterium smegmatis and E. coli using TiO2-based photocatalyst. Nanotechnology for Environmental Engineering, 8(2), 567–579.
2022
- Malyan, V., Kumar, V., & Sahu, M. (2022). Significance of sources and size distribution on calibration of low-cost particle sensors: Evidence from a field sampling campaign. Journal of Aerosol Science, 106114.
- Ghosh, S., & Sahu, M. (2022). Phthalate pollution and remediation strategies: A review. Journal of Hazardous Materials Advances, 6, 100065.
- Kumar, V., Malyan, V., & Sahu, M. (2022). Significance of Meteorological Feature Selection and Seasonal Variation on Performance and Calibration of a Low-Cost Particle Sensor. Atmosphere, 13(4), 587.
- Kumar, V., Sahu, M., & Biswas, P. (2022). Source Apportionment of Particulate Matter by Application of Machine Learning Clustering Algorithms. Aerosol and Air Quality Research, 22, 210240.
2021
- Kumar, V., & Sahu, M. (2021). Evaluation of nine machine learning regression algorithms for calibration of low-cost PM2.5 sensor. Journal of Aerosol Science, 105809.
Book Chapters
- Nawale, P., & Sahu, M. (2024). Comparative Study of Testing Indigenous Air Filters for Coarse and Fine PM Removal. In Pollution Control for Clean Environment – Volume 2 (pp. 79-84). Springer Nature.
- Ghosh, S., & Sahu, M. (2023). Perspective Chapter: Mechanistic Understanding of Stability and Photocatalytic Efficiency of Titanium Dioxide Nanomaterials in Aquatic Media – A Sol-Gel Approach. In intechopen.com. IntechOpen.
- Sahu, M., Malyan, V., & Mayya, Y. S. (2021). Technologies for Controlling Particulate Matter Emissions from Industries. Pollution Control Technologies, 253–290.
- Mandal, C., & Sahu, M. (2021). Application of Metal and Metal Oxide Nanoparticles as Potential Antibacterial Agents. Energy, Environment, and Sustainability.
Policy Brief/Report (s)
- Malyan, V., Kumar, V., Sahu, M., Mayya, Y.S., Biswas, P., Venkatraman, C. (2023). Improving Air Quality Monitoring in G20 Countries Through Low Cost Sensor-Satellite Synergies. T20 Policy Brief.