I seek to measure pollution and environmental impacts in innovative ways (Data & Maps) and study how policies affect these environmental outcomes, and subsequently, human health.
Shao, Qinglong, and Shiran Shen. “When Reduced Working Time Harms the Environment: A Panel Threshold Analysis for EU-15, 1970-2010.” Journal of Cleaner Production 147 (2017): 319 – 329.
Abstract: Conventional wisdom has it that less working time is good for mitigating environmental pressure. Only a few studies have documented contradictory evidence. In this paper, we use panel threshold model, which is arguably the first of its kind in environmental analysis, to further document nonlinear relationships between working time and environmental pressure in EU-15 countries between 1970 and 2010. We find that the sign of this relationship shifts from positive to negative, as the working hours per worker decreases; France, Denmark, Germany, and the Netherlands experienced more environmental pressure with shorter working week. To the backdrop of reduced working time during our research period, our paper sheds new light on the traditional view of “the less, the better,” as curtailing working time beyond certain thresholds may inadvertently incur exacerbation of environmental pressure.
Shen, S. Victoria. “Pricing Carbon to Contain Violence.”
Shen, Shiran, and Blane Wilson. “Where Can Clean Technology Help? Machine Learning to Identify Environmentally At-Risk Communities in the United States.” View poster.
Abstract: Inspired by CalEnviroScreen, an environmental health assessment tool used to identify environmentally at-risk communities in California, we calculate pollution burden scores at the census tract level for the entire contiguous United States. Pollution burden is a composite score that encompasses 12 environmental (air, water, waste) indicators. We combine actual pollution burden indicator data with predicted statistics using machine learning. We create a novel National (Lower 48) Pollution Burden Map using ArcGIS.