Postdoctoral Scholar · Stanford University
I study how human activities and atmospheric processes shape environmental conditions, and what that means for communities and policy.
My work combines observations, physical models, and inverse methods to understand emissions and exposure, and to evaluate decisions about transportation, land management, air quality, and climate.
My doctoral work used urban air pollution measurements to estimate concentrations and emissions, assess local interventions, and identify reductions needed to meet policy targets.
I combined mobile and fixed-site measurements using compressive sensing to estimate black carbon concentrations across a city throughout the day.
ES&T 2024 ↗︎I used Bayesian inversion to estimate emissions from roads and facilities and assess how freight rerouting could affect nearby communities.
Science Advances 2026 ↗︎I adapted inverse methods to identify efficient emission reductions for air quality targets while considering climate benefits and exposure disparities.
ES&T 2026 ↗︎I’m an environmental engineer and postdoctoral scholar in the ECHO Lab at Stanford’s Doerr School of Sustainability, working with Marshall Burke.
At Stanford, I’m extending this work to wildfire emissions and smoke exposure, asking how prescribed burning can be planned to reduce future wildfire impacts while limiting harm to nearby and downwind communities.
I earned my Ph.D. in Environmental Engineering at UC Berkeley in 2026, advised by Joshua Apte and Robert Harley. My dissertation examined urban pollution, from reconstructing concentrations at city-block scales to estimating emissions and evaluating control strategies.
Before Berkeley, I studied particulate matter composition and sources at IIT Delhi. I’m interested in how environmental observations can inform decisions about cities and natural resources, particularly when the benefits and burdens fall unevenly across communities.
I develop methods to study environmental processes from incomplete observations and evaluate how different interventions could change their outcomes.
I combine measurements with atmospheric models to estimate conditions that we cannot observe directly, accounting for differences in resolution and uncertainty. Current work focuses on separating wildfire smoke from background pollution, with an interest in incorporating satellite and aircraft observations.
I use Bayesian inversion to estimate emissions from observed concentrations and examine contributions from roads and facilities. I’m exploring faster transport models and differentiable emulators to make repeated inversions practical and test how changes in urban activity could affect exposure.
I use optimization to compare strategies for meeting environmental targets and examine how their benefits are distributed across communities. I’m interested in policies that address air quality and climate together, including how households and firms respond and how those responses affect outcomes. For prescribed burning, I’m interested in where and when to burn, weighing immediate smoke exposure against potential reductions in future wildfire impacts and considering who bears those risks.
C. Manchanda*, L. Koolik*, A. Ünal, I. Fung, J. Marshall, R. Morello-Frosch, A. Turner, R. Harley, and J. Apte. Inverse modeling identifies efficient emission control strategy for mitigating PM2.5 pollution. Environmental Science & Technology, 60, 28610–28621, 2026.
C. Manchanda, L. Koolik, A. Ünal, R. Harley, J. Marshall, and J. Apte. Deconstructing the distributional impacts of air pollution controls. Environmental Science & Technology.
L. Koolik*, C. Manchanda*, A. Ünal, I. Fung, J. Marshall, R. Morello-Frosch, A. Turner, R. Harley, and J. Apte. Modeling optimal pathways to a triple win in air quality, climate, and equity.
C. Manchanda, R. Cohen, R. Alvarez, T. Thompson, M. Harris, A. Turner, J. Marshall, R. Harley, and J. Apte. Hyperlocal sensing and inversion reveal community impacts of urban air pollutant emissions. Science Advances, 2026.
J. Apte and C. Manchanda. High-resolution urban air pollution mapping. Science, 385, 380–385, 2024.
C. Manchanda, R. Harley, J. Marshall, A. Turner, and J. Apte. Integrating mobile and fixed-site black carbon measurements to bridge spatiotemporal gaps in urban air quality. Environmental Science & Technology, 58, 12563–12574, 2024.
C. Manchanda, M. Kumar, V. Singh, N. Hazarika, M. Faisal, V. Lalchandani, A. Shukla, J. Dave, N. Rastogi, and S. N. Tripathi. Chemical speciation and source apportionment of ambient PM2.5 in New Delhi before, during, and after the Diwali fireworks. Atmospheric Pollution Research, 13, 101428, 2022.
C. Manchanda, M. Kumar, and V. Singh. Meteorology governs the variation of Delhi's high particulate-bound chloride levels. Chemosphere, 291, 132879, 2021.
C. Manchanda, M. Kumar, V. Singh, M. Faisal, N. Hazarika, A. Shukla, V. Lalchandani, V. Goel, N. Thamban, D. Ganguly, and S. N. Tripathi. Variation in chemical composition and sources of PM2.5 during the COVID-19 lockdown in Delhi. Environment International, 153, 106541, 2021.
A. Saxena, E. Ng, C. Manchanda, and T. Canchi. Cardiac thermal pulse at the neck-skin surface as a measure of stenosis in the carotid artery. Thermal Science and Engineering Progress, 19, 100603, 2020.
A. Saxena, E. Ng, M. Mathur, C. Manchanda, and N. Jajal. Effect of carotid artery stenosis on neck skin tissue heat transfer. International Journal of Thermal Sciences, 145, 106010, 2019.
* Co-first authorship. Current list on Google Scholar ↗︎ and ORCID ↗︎.
J. Apte, R. Harley, C. Manchanda, L. Koolik, and J. Marshall. Systems, methods, and program products for reducing air pollution for one or more pollutants in a locality.
J. Apte, R. Harley, C. Manchanda, J. Marshall, and A. Turner. Systems, methods, and program products for detecting emissions of an airborne pollutant on a hyperlocal scale.
Postdoctoral Scholar · ECHO Lab · Doerr School of Sustainability
Graduate Student Researcher · Environmental Engineering
Research Associate · Air Quality Research Group
NTU–India Connect Research Scholar