Nexus of Climate Change, Urban Infrastructure, Transportation and Health

Civil Engineering; Public Health; Climate; Urban Studies

Our goal is to establish the nexus among climate change, urban infrastructure, transportation and health using cross section study based on real time data as well as historical data.

Research Interests
  • Health policy
  • Transportation
  • Climate change
  • public heath

Our main motivation is to establish nexus among climatechange, urban infrastructure, transportation and health, and to propose active transportationsystem management strategies (in short term) and urban infrastructure redesign approaches(in long term) that could improve both climate and health.

Studies including WHO’s 2013 report on Health Effects ofParticular Matter pointed out that fine particulate matter (PM2.5)has detrimental health and climate effects. They estimated that over 3.1million world-wide deaths in 2010 is due to PM2.5.

Thus, our study will start with particulate matter as we canrelatively easily collect such data in real time using a low cost urban sensingsystem, to be developed in this project using Raspberry Pi with various sensorsmeasuring PM, temperature, and transportation information (i.e., congestionlevel using travel time). We propose to conduct cross sectional study based onboth real time data to be collected using our urban sensing system as well as historicaldata such as transportation data (e.g., average annual daily traffic, traveltime, emissions from traffic, etc.), heath data (e.g., # of hospital visits anddeaths due to PM related diseases such as Asthma, and lung cancer), and urbaninfrastructure data (e.g., urban density, transportation network, travelpatterns, outdoor activities, etc.). Our cross sectional study will consider afew selected locations in Northern Virginia (as a test site with healthconcerns due to high PM measures) and Charlottesville (as control site).

Desired outcomes

Based on this 3C project, we plan to establish preliminary datasupporting short term and long term changes in PM measures. For example, anyshort-term changes in transportation system management strategies (e.g., highoccupancy toll, improved transit system, implementation of advanced trafficsignal system, etc.) could provide statistically meaningful reductions in PMmeasures. Furthermore, historical data and cross sectional study supportpotential long term impacts on PM measures. We will target to prepare proposals to NIH and/or NSF.