Meiling Gao won an ISEE Outstanding Student Poster award, for her work, “Population Exposure Assessment Based on a Distributed Network of Low-Cost Continuous Reading PM2.5 Sensors in Xi’an, China”. Last winter we had an opportunity to deploy a sensor network at Meiling’s research sites in Xi’an to measure the spatial and temporal variations in PM2.5 across the city. We deployed the latest generation of the Personal University of Washington Particle (PUWP) monitor, and calibrated it against the BAM, Dustrak, and Minivol. At each node of the network, we collocated the PUWP with a Minivol for further validation of the network’s performance. The deployment was completed in collaboration with the Institute of Earth Sciences of the Chinese Academy of Sciences.
“SpaceNeedleQAClose” by MyName (Cacophony) – Own work. Licensed under CC.
The International Society for Exposure Assessment conference is always a fun gathering and learning experience. This year is special because it’s being held in Seattle at the UW.
Elena Austin will be presenting recent work we’ve done in the laboratory evaluating low cost Shinyei PM sensor. We’ve looked at its sensitivity to different sized particles. We’ve integrated this sensor into both fixed site monitors for distributed sensor networks, as well as small battery-operated personal exposure monitors. This recent work, combined with previous work by David Holstius, has greatly informed our understanding of how to use this sensor in environmental health studies.
Meiling Gao will be presenting her recent research in Xi’an, China. She will be presenting a talk on her dissertation research looking at the associations between the built environment and mental and physical health using two validated instruments. Additionally, she will be presenting a poster on her recent findings from her deployment of several Portable University of Washington Particle (PUWP) monitors developed by my lab in a distributed sensor network last winter in Xi’an. The monitors recorded very high concentrations in the city, provided good spatial temporal data of PM variations, and compared quite nicely against collocated BAM, TSI Dustrak, and Minivols.
Finally, I will be presenting a poster of work that Hilary Ong (UCSF) and collaborators from Kunming Medical University conducted using the PANDA portable monitors a couple years ago in a pilot study in which we developed a model of children’s PM exposures in Kunming, China.
My group will be working with researchers from UC Davis on a newly awarded NIH P01 Center Grant, “Quantifying Heterogeneities in Dengue Virus Transmission Dynamics”, a 5-year $7.3 million study that will examine as one of its aims, the role of human mobility on contributing to virus transmission and spread. The study builds upon previous studies conducted by UC Davis researchers on dengue transmission in Iquitos, Peru. My group is involved in the data core project for the new center.
A new R21 study funded by the NIH NIAID (PI Robert Spear at UCB) will examine factors related to the O. viverrini, a liver fluke that causes human disease in Thailand.
The study will make use of mobile technologies developed by my group at UW.
Congratulations to David Holstius, who graduated over the weekend with a PhD in Environmental Health Sciences. David’s dissertation, entitled “Monitoring Particulate Matter with Commodity Hardware”, describes work he’s done to develop and utilize lower-cost PM instruments for improved exposure assessment and environmental epidemiological studies.
Just heard, NIH NHLBI will fund a new study with collaborators from USC (Genevieve Dunton, Mary Ann Pentz, and Chih-Ping Chou), UC Berkeley (Michael Jerrett), and Northeastern (Stephen Intille), and UW (Edmund Seto) to develop new statistical modeling approaches to analyze large data from Ecological Momentary Assessment (EMA) studies.
This new study builds upon the work we’ve done with the CalFit system, using smartphone-based EMAs to study the associations between mood, physical activity, and a person’s environment.
I’m participating in this event organized by Internews at Berkeley on April 30th. I’ll report soon on the technology I’m developing for this project…
Groundtruth and Airwaves: Sensor Networks and Emerging Technology for Environmental Journalism
Technology–as remote as satellites and as close as our smartphones–offers new opportunities for collecting data about environmental topics. Evidence of rising sea levels, poor air quality, noise pollution and more can now be gathered from wireless sensor networks, open public data sets, and user-generated data from social media platforms. These tools make it simpler to gather, analyze and visualize data, helping to drive news stories for journalists and more thoughtful engagement and advocacy by activists.
“Groundtruth and Airwaves” will showcase a number of newsworthy environmental and health-related sensor projects currently underway. After a session of Lightning Talks, working journalists from around the world will join a panel of technology experts and research scientists to explore opportunities and challenges found at the nexus of DIY sensors, crowdsourced data, and environmental and health journalism.
In the past I’ve taught a few years of a Public Health-focused GIS course at Berkeley. And since 2006, I’ve taught a graduate-level course on Health Impact Assessment with Rajiv Bhatia. I’ve also co-taught the MPH-breadth course, Introduction to Environmental Health with Kirk Smith, and even an accelerated online version of the course. I was teaching both semesters, 9 months out of the year.
Because UW is on a quarter system, my required teaching load is less, and there are already existing courses in some of the previous topics that I’ve taught, I have some flexibility in teaching in new areas. To get a feel for the quarter system and teaching at UW in general, I’ll be co-teaching with Chris Simpson, ENVH 555 Instrumental Methods for Industrial Hygiene Measurement: Laboratory. I’m also planning to contribute some lectures and time to Andy Dannenberg’s HIA course, ENVH 536/URBDP536: Health Impact Assessment.
Moving forward, I’ll probably introduce a couple new courses of my own. The first in the fall will likely be a GIS course that makes use of the excellent computer teaching facilities within the school. As usual for my courses, there will be strong practical element to the assignments, and projects that allow students to learn-by-doing and by interacting with other students in teams.
The current drought in California highlights how precious a resource water is to the lives of California residents, the state’s natural ecosystems, and its agricultural economy. Over the last few decades, recycled water — the reuse of treated wastewater — has played an important role in meeting ever increasing demands for water. Since the early days of water reuse, questions concerning the safety to public health have been raised numerous times. And, the practice of quantitative microbial risk assessment has responded by evaluating the efficacy of treatment processes on the removal of infectious agents in wastewater, and by assessing quantitatively using risk models, the potential for water reuse to result in infection and disease in human populations through various exposure scenarios.
I was involved in the quantitative microbial risk assessment (QMRA) modeling for a recent review of water reuse for California’s agricultural irrigation. The QMRA was part of a process that involved input from a panel of experts, who addressed a number of issues relevant to developing assumptions for the QMRA, as well as relevant to the interpretation of the QMRA’s findings. The panel and QMRA were commissioned by the California Department of Public Health, which recognized the need to reassess risks given the potential for increasing water reuse in agricultural irrigation, improved knowledge of the concentrations of microbial pathogens found in wastewater, and new treatment processes. The report of the findings from this process is available here.
For the NIH-funded Black Women’s Health Study, my group is estimating exposures to traffic-related air and noise pollution. Previously, the traffic noise modeling was described here.
I now have preliminary results for NOx (NO and NO2) traffic air pollution dispersion model. The model uses the best available roadway geometries, and traffic data, and emissions modeling to derive estimates of exposures. Moreover, the exposure assessment methodology can be run anywhere in the U.S. The figure shown is a coarse resolution example of the model applied to 5 boroughs of New York City. But, the model is being run to estimate NOx concentrations at the exact residential address of each person in the Black Women’s Health Study.
Currently the model makes use of parallel computing on a high performance cluster so that hundreds of thousands of exposures can be estimated in reasonable amounts of time.
For another application of our traffic air pollutant model see this, as well as recent the publication in Circulation, and conference proceeding from the 2013 Air & Waste Management Association 106th Annual Conference.