Kishore K Madhipatla
A5080418648- Air Quality and Health Impacts
- Climate Change and Health Impacts
- Air Quality Monitoring and Forecasting
- Energy and Environment Impacts
- COVID-19 impact on air quality
- Health, Environment, Cognitive Aging
- Atmospheric chemistry and aerosols
- Maritime Transport Emissions and Efficiency
- Vehicle emissions and performance
- Global Health Care Issues
- Energy Load and Power Forecasting
Centre for Chronic Disease Control
2019-2024
Lubrizol Life Science Health (United States)
2024
Carnegie Mellon University
2022-2024
Indian Institute of Technology Madras
2015
Air pollution is a major planetary health risk, with India estimated to have some of the worst levels globally. To inform action at subnational in India, we exposure air and its impact on deaths, disease burden, life expectancy every state 2017.We pollution, including ambient particulate matter defined as annual average gridded concentration PM2.5, household percentage households using solid cooking fuels corresponding across states accessible data from multiple sources part Global Burden...
The association of air pollution with multiple adverse health outcomes is becoming well established, but its negative economic impact less appreciated. It important to elucidate this for the states India.
Abstract High-resolution assessment of historical levels is essential for assessing the health effects ambient air pollution in large Indian population. The diversity geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture spatiotemporal patterns fine particulate matter (PM2.5) India. We developed model daily average PM2.5 between 2008 2020 based on data, meteorology, land use, satellite...
Ambient particulate matter of aerodynamic diameter less than 2.5 microns PM2.5) levels in Delhi routinely exceed World Health Organization (WHO) guidelines and Indian National Air Quality Standards (NAAQS) for acceptable daily exposure. Only a handful studies have examined the short-term mortality effects PM India, with none from examining contribution PM2.5.We aimed to analyze association between PM2.5 exposures nonaccidental Delhi, India.Using generalized additive Poisson regression...
Air pollution is a growing public health concern in developing countries and poses huge epidemiological burden. Despite the awareness of ill effects air pollution, evidence linking sparse. This requires environmental exposure scientist researchers to work more cohesively generate on impacts for policy advocacy. In Global Environmental Occupational Health (GEOHealth) Program, we aim build assessment model estimate ambient at very fine resolution which can be linked with outcomes leveraging...
Air pollution presents a major public health threat to India, affecting more than three quarters of the country's population. In current project, GEOHealth Health Effects Selected Environmental Exposomes Across Life CourSe-India, we aim study effect environmental exposomes-fine particulate matter (PM
BACKGROUND AND AIM: High levels of ambient particulate matter (PM) combined with sparse ground monitoring networks, specifically concentrated in urban areas India, pose massive challenges to studying health effects PM India. Thus it is important develop robust predictive models that provide exposure estimates at high spatiotemporal resolution across METHODS: We used a machine-learning-based approach by ensemble averaging four different learners model calibrated against...
OPS 47: Increasing spatiotemporal resolution in assessment of exposure to outdoor air pollutants, Room 412, Floor 4, August 27, 2019, 4:30 PM - 5:30 Aim: High levels ambient pollution has been implicated as a major risk factor for morbidities and premature mortality India. In this work, we retrospectively assessed daily average PM2.5 at 1 km × grids Delhi, India from 2010-2016, using multiple data sources ensemble averaging approaches that combine machine learning algorithms. addition,...
Aim: In this work, we retrospectively assessed daily average PM2.5 exposure at 1 km × grids in two major Indian cities, Delhi and Chennai from 2010-2016, using multiple data sources ensemble averaging approaches that combine machine learning algorithms.Methods: We implemented a multi-stage modeling exercise involving satellite data, land use variables, reanalysis based meteorological variables population density. The relationship between spatiotemporal predictors was modeled six learners;...