Data in the Air: Air Pollution, Residential Energy, and Transportation Behavior
As an example of policy intervention in complicated systems, effective air quality management is often challenged by the complex and non-linear dependence of ambient pollution on emissions and meteorology. By introducing machine learning (clustering) methods into the sensitivity analysis with a regional chemical transport model, I have delineated the limiting precursor emissions and their meteorology dependence for an ozone season in the San Joaquin Valley. Further extending this framework of the clustering and reduction of large, complex data sets, I have applied it to the fields of residential energy consumption and transportation behavior research, allowing the extraction of load patterns from smart meter data and identification of personal lifestyles in the Whole Traveler survey. These application cases exemplify the combination of domain knowledge with machine learning for the identification of efficient and effective policy interventions in complex and heterogenous systems.
Energy/Environmental Policy Research Scientist/Engineer, Sustainable Energy Systems Group, Sustainable Energy & Environmental Systems Department, Energy Analysis & Environmental Impacts Division, Transportation Initiative
Ling Jin has multidisciplinary training in air quality engineering, statistics, and resources economics. She develops and applies diagnostic and sensitivity analysis tools in photochemical transport modeling systems to identify effective pollution control strategies. She also strives to bring state-of-the-art data science (statistical, machine learning, and econometric techniques) to the domains of climate/atmospheric science, electricity market, and transportation. She has led projects on air quality modeling, spatial pattern and time series mining, social sequence analysis, with work published by AGU, ACS, Atmospheric Environment, AAAI, IEEE, and ACM. She is currently a Research Scientist and holds a PhD in Energy and Resources, a MA in Statistics, both from UC Berkeley, and a BS in Physical Geography from Peking University.