Publications
2024
Multi-season mobile monitoring campaign of on-road air pollution in Bengaluru, India: High-resolution mapping and estimation of quasi-emission factors.
Upadhya, A. R., Kushwaha, M., Agrawal, P., Gingrich, J. D., Asundi, J., Sreekanth, V., . . . Apte, J. S. (2024). Multi-season mobile monitoring campaign of on-road air pollution in Bengaluru, India: High-resolution mapping and estimation of quasi-emission factors.. The Science of the total environment, 914, 169987. doi:10.1016/j.scitotenv.2024.169987
Household concentrations and female and child exposures to air pollution in peri-urban sub-Saharan Africa: measurements from the CLEAN-Air(Africa) study.
Shupler, M., Tawiah, T., Nix, E., Baame, M., Lorenzetti, F., Betang, E., . . . Mbatchou Ngahane, B. H. (2024). Household concentrations and female and child exposures to air pollution in peri-urban sub-Saharan Africa: measurements from the CLEAN-Air(Africa) study.. The Lancet. Planetary health, 8(2), e95-e107. doi:10.1016/s2542-5196(23)00272-3
Urban Air-Quality Estimation Using Visual Cues and a Deep Convolutional Neural Network in Bengaluru (Bangalore), India.
Feldman, A., Kendler, S., Marshall, J., Kushwaha, M., Sreekanth, V., Upadhya, A. R., . . . Fishbain, B. (2024). Urban Air-Quality Estimation Using Visual Cues and a Deep Convolutional Neural Network in Bengaluru (Bangalore), India.. Environmental science & technology, 58(1), 480-487. doi:10.1021/acs.est.3c04495
2023
Development of land use regression (LUR) models for criteria air pollutants in Delhi: Use of regulatory monitoring data
Upadhya, A., Kulkarni, P., Kalshetty, M., Srishti, S., Kushwaha, M., Agrawal, P., & Vakacherla, S. (2023). Development of land use regression (LUR) models for criteria air pollutants in Delhi: Use of regulatory monitoring data. doi:10.5194/egusphere-egu23-5586
2022
Which model to choose? Performance comparison of statistical and machine learning models in predicting PM2.5 from high-resolution satellite aerosol optical depth
Kulkarni, P., Sreekanth, V., Upadhya, A. R., & Gautam, H. C. (2022). Which model to choose? Performance comparison of statistical and machine learning models in predicting PM2.5 from high-resolution satellite aerosol optical depth. Atmospheric Environment, 282, 119164. doi:10.1016/j.atmosenv.2022.119164
Bias in PM<sub>2.5</sub> measurements using collocated reference-grade and optical instruments.
Kushwaha, M., Sreekanth, V., Upadhya, A. R., Agrawal, P., Apte, J. S., & Marshall, J. D. (2022). Bias in PM<sub>2.5</sub> measurements using collocated reference-grade and optical instruments.. Environmental monitoring and assessment, 194(9), 610. doi:10.1007/s10661-022-10293-4
Ten simple rules to host an inclusive conference
Joo, R., Sanchez-Tapia, A., Mortara, S., Saibene, Y. B., Turner, H., Peter, D. H., . . . Ravi, J. (2022). Ten simple rules to host an inclusive conference. PLOS COMPUTATIONAL BIOLOGY, 18(7). doi:10.1371/journal.pcbi.1010164
Indoor and Ambient Air Pollution in Chennai, India during COVID-19 Lockdown: An Affordable Sensors Study
Puttaswamy, N., Sreekanth, V., Pillarisetti, A., Upadhya, A. R., Saidam, S., Veerappan, B., . . . Balakrishnan, K. (2022). Indoor and Ambient Air Pollution in Chennai, India during COVID-19 Lockdown: An Affordable Sensors Study. Aerosol and Air Quality Research, 22(1), 210170. doi:10.4209/aaqr.210170
2021
pollucheck v1.0: A package to explore open-source air pollution data
Upadhya, A., Agrawal, P., Vakacherla, S., & Kushwaha, M. (2021). pollucheck v1.0: A package to explore open-source air pollution data. Journal of Open Source Software, 6(63), 3435. doi:10.21105/joss.03435
PM2.5/PM10 ratio characteristics over urban sites of India
Spandana, B., Srinivasa Rao, S., Upadhya, A. R., Kulkarni, P., & Sreekanth, V. (2021). PM2.5/PM10 ratio characteristics over urban sites of India. Advances in Space Research, 67(10), 3134-3146. doi:10.1016/j.asr.2021.02.008
Impact of COVID-19 lockdown on the fine particulate matter concentration levels: Results from Bengaluru megacity, India.
Sreekanth, V., Kushwaha, M., Kulkarni, P., Upadhya, A. R., Spandana, B., & Prabhu, V. (2021). Impact of COVID-19 lockdown on the fine particulate matter concentration levels: Results from Bengaluru megacity, India.. Advances in space research : the official journal of the Committee on Space Research (COSPAR), 67(7), 2140-2150. doi:10.1016/j.asr.2021.01.017
2020
mmaqshiny v1.0: R-Shiny package to explore Air-Quality Mobile-Monitoring data
Upadhya, A., Agrawal, P., Vakacherla, S., & Kushwaha, M. (2020). mmaqshiny v1.0: R-Shiny package to explore Air-Quality Mobile-Monitoring data. Journal of Open Source Software, 5(50), 2250. doi:10.21105/joss.02250