Research

Understanding how humans impact the atmosphere & what to do next.
I use different climate models and all types of measurements of gas and particle composition in the atmosphere to understand the impacts of chemical reactions that: (1) control the lifetimes of greenhouse gases & (2) contribute to the formation of harmful air pollutants.
My Research Themes: Oxidants, NOx & Heterogenous Chemistry
Oxidants control how long gases like methane stay in the atmosphere. When gases get oxidized they're more likely to form aerosols. Such heterogenous chemistry processes are hard to measure & poorly modeled. My research focuses on these topics to improve our understanding of how emissions are processed & removed from the atmosphere with climate and air pollution implications.
Machine Learning & Data Science in Atmospheric Chemistry.
We have a lot of data. I want to use it. I'm interested in using modern computer science techniques to get the most out of our atmospheric data sets, and to make our climate models smarter. Parameterizing sub-grid-scale processes has never been more exciting.
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Innovatively Leveraging Observations to Improve Predictive Models

Chemical reactions that take place in the atmosphere determine the severity of two of the most challenging modern environmental crises: air pollution and climate change. These global challenges have enormous human health, socio-political, and environmental implications, with the most harmful and disruptive risks disproportionately placed on the most vulnerable populations. To develop practical solutions, we must understand how the chemical composition of the atmosphere will change in response to our efforts to control anthropogenic emissions in a warming atmosphere.

model-measurements on description of Jessica Haskins research interests page

One of the largest looming challenges our field faces now and, in the future, will be connecting an ever-growing dataset of highly localized measurements to scientifically accurate, but computationally efficient representations in predictive global models. My research focuses on using all available data we have to improve predictive models and inform decision makers. Using traditional analysis techniques, data science, machine learning and artificial intelligence methods, my research assimilates data from satellites, observation networks, aircraft campaigns, and government records to improve the accuracy and speed of global models of atmospheric composition to answer critical questions relevant to air pollution and climate.

I’m interested in connecting real world data to how we represent physical and chemical processes in models. I’m committed to doing this in a way that’s open source, accessible, and takes advantage of the data science and machine learning tools that are currently available. 

Oxidants, NOx and Heterogeneous Chemistry

Atmospheric oxidants control how long gases like methane stay in the atmosphere. When many atmospheric gases get oxidized they’re more likely to form aerosols harmful to humans when inhaled. The concentrations of common atmospheric oxidants like OH, O3, NO3, and Cl radicals are dependent on a variety of different variables, from atmospheric water vapor concentrations, exposure to sunlight, temperature, aerosol surface area, emissions of gases like NOx from combustion, etc. Seasonal shifts in meteorology, regional emissions standards, and climate change can all impact these oxidants and, therefore, can impact air quality and climate. 

Heterogenous chemistry connects gas phase anthropogenic emissions of pollutant precursors, like NOx, and natural emissions from the biosphere, like isoprene, to the formation of particulate matter in the aerosol phase. My research focuses on these topics to improve our understanding of how emissions are processed & removed from the atmosphere with climate and air pollution implications.
Many heterogenous processes are mitigated by particle pH, aerosol surface area, availability of water vapor, concentrations of precursor species, and oxidants in the atmosphere. These processes are challenging to measure and therefore challenging to represent in models, and much remains to be discovered! My past research has focused on these themes as they applied to the role of chlorine in the troposphere, and my current research focuses on these themes as they apply to aerosol organic nitrate formation.
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