Bio

Emma is interested in exploring how we can promote the health of people and the environment in a changing world. Her research aims to measure, value, and predict the impacts of global environmental change on our ecosystems, environmental quality, and human health. She leverages different types and scales of data, including field collected ecological data to remotely sensed data to epidemiological data on human health outcomes, and she relates these datasets together by drawing on methods and tools from various disciplines, such as machine learning, causal inference, and exposure assessment. Her current research focuses on how changes to air quality, land use, and water quality, which are three resources that are critical to the functioning of healthy ecosystems have consequences for both the environment and human health. Emma is co-advised by Erin Mordecai and Marshall Burke, and she is a NSF Graduate Research Fellow, a Stanford EDGE Fellow, and a Stanford Data Science Scholar.

Prior to starting her PhD, Emma worked as a Research Analyst at the Global Policy Lab at UC Berkeley (now at Stanford). During her time at GPL, she was part of a project that aimed to identify land-based sources of nonpoint source water pollution in national-scale river systems in New Zealand and the US Mississippi River Basin. Emma completed her MPH in global and environmental health science and global health at Columbia University and received a BA in behavioral neuroscience from Colgate University.

When she isn’t at her desk, you can find her outside - most likely running or hiking up a mountain. She also co-founded a trivia company and loves to host trivia nights to bring communities together.

Honors & Awards

  • Stanford Data Science Scholar, Stanford Data Science (2023 - 2025)
  • Graduate Research Fellow, National Science Foundation (2022 - 2027)
  • EDGE Fellow, Stanford University (2022 - 2025)

Education & Certifications

  • BA, Colgate University, Behavioral Neuroscience (2015)
  • MPH, Columbia University, Environmental Health Sciences, Global Health Certificate (2017)

Personal Interests

running, trivia, hiking, kayaking, crossword puzzle solving + constructing

Contact

  • Academic
    emmars@stanford.edu
    University - Student Department: Emmett Interdisciplinary Program in Environment and Resources Position: Graduate

Additional Info

All Publications

  • The Influence of Wildfire Smoke on Ambient PM2.5 Chemical Species Concentrations in the Contiguous US. Environmental science & technology Krasovich Southworth, E., Qiu, M., Gould, C. F., Kawano, A., Wen, J., Heft-Neal, S., Kilpatrick Voss, K., Lopez, A., Fendorf, S., Burney, J. A., Burke, M. 2025

    Abstract

    Wildfires significantly contribute to ambient air pollution, yet our understanding of how wildfire smoke influences specific chemicals and their resulting concentration in smoke remains incomplete. We combine 15 years of daily species-specific PM2.5 concentrations from 700 air pollution monitors with satellite-derived ambient wildfire smoke PM2.5, and use a panel regression to estimate wildfire smoke's contribution to the concentrations of 27 different chemical species in PM2.5. Wildfire smoke drives detectable increases in the concentration of 25 out of the 27 species with the largest increases observed for organic carbon, elemental carbon, and potassium. We find that smoke originating from wildfires that burned structures had higher concentrations of copper, lead, zinc, and nickel relative to smoke from fires that did not burn structures. Wildfire smoke is responsible for an increasing share of ambient concentrations of multiple species, some of which are particularly harmful to health. Using a risk assessment approach, we find that wildfire-induced enhancement of carcinogenic species concentrations could cause increases in population cancer risk, but these increases are very small relative to other environmental risks. We demonstrate how combining ground-monitored and satellite-derived data can be used to measure wildfire smoke's influence on chemical concentrations and estimate population exposures at large scales.

    View details for DOI 10.1021/acs.est.4c09011

    View details for PubMedID 39899563

  • Harmonized nitrogen and phosphorus concentrations in the Mississippi/Atchafalaya River Basin from 1980 to 2018 SCIENTIFIC DATA Krasovich, E., Lau, P., Tseng, J., Longmate, J., Bell, K., Hsiang, S. 2022; 9 (1): 524

    Abstract

    Water quality monitoring can inform policies that address pollution; however, inconsistent measurement and reporting practices render many observations incomparable across bodies of water, thereby impeding efforts to characterize spatial patterns and long-term trends in pollution. Here, we harmonized 9.2 million publicly available monitor readings from 226 distinct water monitoring authorities spanning the entirety of the Mississippi/Atchafalaya River Basin (MARB) in the United States. We created the Standardized Nitrogen and Phosphorus Dataset (SNAPD), a novel dataset of 4.8 million standardized observations for nitrogen- and phosphorus-containing compounds from 107 thousand sites during 1980-2018. To the best of our knowledge, this dataset represents the largest record of these pollutants in a single river network where measurements can be compared across time and space. We addressed numerous well-documented issues associated with the reporting and interpretation of these water quality data, heretofore unaddressed at this scale, and our approach to water quality data processing can be applied to other nutrient compounds and regions.

    View details for DOI 10.1038/s41597-022-01650-6

    View details for Web of Science ID 000846233000007

    View details for PubMedID 36030259

    View details for PubMedCentralID PMC9420138

  • The effect of large-scale anti-contagion policies on the COVID-19 pandemic (vol 584, pg 262, 2020) NATURE Hsiang, S., Allen, D., Annan-Phan, S., Bell, K., Bolliger, I., Chong, T., Druckenmiller, H., Huang, L., Hultgren, A., Krasovich, E., Lau, P., Lee, J., Rolf, E., Tseng, J., Wu, T. 2020; 585 (7824): E7

    Abstract

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

    View details for DOI 10.1038/s41586-020-2691-0

    View details for Web of Science ID 000618113400001

    View details for PubMedID 32826960

https://orcid.org/0000-0003-4718-5527