Dissertation Research
Optimal Placement of Pollution Monitors in Ambient Air Pollution Regulation
Local and regional pollutants like particulate matter (PM) have large health impacts and require government regulation due to a tragedy of the commons occurring in the atmosphere. In the United States, a critical component of PM regulation involves enforcing standards on ambient levels of PM using expensive in-situ (ground-based) pollution monitoring stations. These monitors relay measurements back to the regulator to allow for enforcement of the regulation where monitors measure ambient PM above the regulatory standards. The placement of monitoring sites is crucial in this enforcement because locations with no monitor cannot be regulated and locations upwind are most incentivized to reduce pollution under the regulation. However, there has been little published work on choosing optimal locations for new monitors. This project examines the optimal pollution monitor siting decision in an effort to address two groups of questions.
- Under the current regime of ambient pollution standards, where should new pollution monitors be placed to generate the most social value? What groups of people are represented by the monitoring network under this style of pollution regulation? This importantly includes estimating how regulation will be enforced where the new monitor is placed.
- If ambient ambient pollution taxes were used instead of standards, how would the network change? How would the distribution of regulated locations change?
Ambient Air Pollution Regulation vs Regulating at the source
Air pollutants are emitted from various sources and mixed into the atmosphere, where they chemically react, diffuse, and travel to the locations where they eventually cause damage. Air pollution regulation is designed to control or limit the amount of damage inflicted by air pollution, where one of the major types of air pollution policy is the regulation of ambient air pollution levels. Ambient air pollution is the concentration of pollutants found in the air in and around where people live, at the location where the damages occur. Ambient air pollution regulation is often distinct from air pollution regulations that control the amount of pollution coming from pollution sources. This is necessary because even if many pollution sources are limited to low levels of pollution, geography and weather may push pollution into hotspots, creating an uneven pollution distribution over space. Measuring and regulating air pollution concentrations around population centers has become an important tool in reducing damages of pollution, but measuring air pollution levels accurately at many locations where people live and work is still prohibitively expensive.
The ideal data for implementing ambient air pollution regulation would be measurements of ambient concentrations over time, at all points in space (or at least a reasonably dense number of measurement locations). However, the level of accuracy and precision required for pollution data in order to implement legally enforceable pollution regulation is high, and therefore expensive due to current technology constraints. There are cheaper pollution measurement devices coming online, however these currently only exist for a few pollutants (e.g., PM2.5 and ozone) and do not currently meet the high accuracy needs of regulation. The expensive nature of collecting accurate pollution data implies a budgetary constraint on number of pollution monitoring stations state and federal governments are willing to place. This constraint on the number of monitors is the primary motivation for estimating optimal monitor locations.
Ongoing Projects
- Ambient air pollution monitoring in the US: placement, timing, network valuation
- Identification of parameters in a joint model with AR(1) errors, with Larry Karp
- Machine learning and satellite imagery: building a cheaper honey bee census from space
- Taking the multicollinearity out of survey data to estimate total effects: beekeeper surveys
- Using machine learning and statistical analysis to aid in sample selection: sampling honey bee colonies to test for mites
Aaron C Watt 