2008-2009

The development of more efficient photovoltaic and photosynthetic devices is a central challenge for solar energy utilization and a sustainable energy economy. A promising route towards higher energy efficiency is light harvesting. In nature, light harvesting is widely used by phototrophic organisms to increase overall conversion efficiencies and extend the spectral range of absorption energies.

This project is to develop proof-of-concept experimental data for an extramural proposal submission to the U.S. Department of Energy on the fluid mechanical properties of hydrate slurries. Hydrates have the potential for high-density storage of light hydrocarbons, for safely tapping the reserves of low-carbon fuel sources trapped in deep oceans, and for sequestering CO2. All of these processes, and in particularly evaluating their viability and potential environmental impact, depends on exploring methods for efficiently transporting the hydrates.

This project will combine measurements of emissions of short lived global warming species such as methane and black carbon with in vitro assessment of oxidative stress in lung macrophage cells from small-scale industries in rural Mexico to characterize the environmental health burden that these industries pose on local communities and the potential health co-benefits that can be achieved through improvements in combustion technology in these previously uncharacterized industries.

This project will determine the structure and interactions of lignin and nitrogen in plant litter, monitoring changes during decomposition under high and low nitrogen availability. Product will be a chapter in dissertation and an associated journal article.

This project will examine the impact of roadway emissions on the local air quality of communities around Los Angeles and Long Beach, including parcel-level population exposure to key air pollutants. Product will be a peer-reviewed journal article and part of a doctoral thesis.

Many people find it difficult to engage with environmental issues, in part because global change occurs on scales of time and space that are relatively large compared to the usual scope of human decision making. People respond enthusiastically to fast-acting disasters such as fires and earthquakes, but less so to issues that occur more gradually over many years, even when the consequences are far greater. To date, there has been little research on how to connect long-term global environmental change to human scales of time and space in a systematic way, thereby enabling behavioral change.

This project will apply a Bayesian spatial dynamic factor model to study the determinants of coastal water quality and its dependence on environmental conditions. The approach will take advantage of data from the Southern California Coastal Ocean Observing System (SCCOOS) on water quality, temperature, salinity, precipitation, solar radiation, tide cycle, wind, and currents. Product will be a peer-reviewed publication.