Chang-fu Wu,
Ph.D., CIH
Professor
Department of Public Health
National Taiwan University
Office Address
Department
of Public Health
Phone/Fax: (02) 3366-8096
Email: changfu@ntu.edu.tw
Education:
Ph.D., Department of Environmental
Health, University of
M.S., Department
of Environmental Health, University of
B.S.,
Department of Public Health,
About
Dr. Wu:
My
research interest involves developing and applying innovative technologies and
models for exposure assessment and environmental monitoring. I am also
interested in conducting risk assessment on environmental and occupational
health issues.
Air quality modeling
Developing effective control
strategies to reduce population exposure to certain hazardous air pollutants
(HAPs) requires identifying sources and quantifying their contributions to the
mixture of HAPs and the associated health risks. One approach is to use
receptor-based source apportionment models (e.g. Positive Matrix Factorization or PMF, Multilinear Engine or ME) to distinguish sources.
Once the contributions are determined, the associated risk could be estimated
from the source profiles. In one of our previous projects, the risk
apportionment approach, which is a combination of receptor modeling and risk
assessment, was developed to estimate source-specific lifetime excess cancer
risks of selected hazardous air pollutants. It was found that the diesel
exhaust contributed less than the wood burning on the basis of mass
concentration; nevertheless, they presented similar cancer risks. This
highlights the value of the risk apportionment approach for prioritizing
control strategies to reduce the highest population health risks from exposure
to air pollutants. Other than these receptor models, we are also applying
dispersion models (e.g. ISC3, AERMOD) for simulation studies.
Source-specific Exposure and Health Risk Assessment
Many epidemiological studies
have found adverse health effects from exposure to air pollutants. However, most
of these studies relied on air pollution data collected at central sites. Our
team conducted a panel study of 17 mail carriers by monitoring their personal
ozone and size-fractionated PM exposures, as well as several health indicators
of their cardiovascular functions. The study results showed that personal
exposure to ozone and PM between 1.0 and 2.5 mm (PM2.5-1) affected the vascular functions significantly. The collected
personal PM filters were further analyzed for their elemental concentrations. Through
the receptor model of absolute principal component analysis, three sources of
PM2.5-1 were identified (urban dust, regional sources, and brake wear). The
statistical analysis found a significant linkage between the PM from regional
sources and the observed vascular effects.
Source-specific GIS Modeling
Assigning
exposure based on fixed-site monitoring results in many epidemiological studies
may lead to misclassification. Land use regression models, which were built based on air monitoring data collected at multiple
locations and included predictor variables (e.g., land use, population, and
traffic data) obtained through the geographic information system (GIS), can be
used to capture the intraurban variability in air
pollutant concentrations. Our team has extensive experiences in building land
use regression models for PM2.5 concentrations and compositions. These models
can be used not only for calculating individualized exposures estimates and but
also for identifying major emission sources or activities (e.g., types of land
usages).
Optical remote sensing
techniques
Optical remote sensing (ORS)
instruments are useful tools for monitoring air pollutants. However, they
usually provide only path-integrated data. By applying the Computed Tomography (CT)
algorithm or radial plume mapping (RPM) technique, we can obtain the spatial
distribution information of air pollutants in the environment. Combining with
meteorological data, we can identify emission sources, and further assess their
health impacts on residents in nearby communities. For example, our team
applied this technique to estimate the emission flux of greenhouse gases in
rural China and of VOCs at several industrial areas in Taiwan. The main ORS
instruments applied in our lab include Open-Path Fourier Transform Infrared
Spectroscopy (OP-FTIR), Ultraviolet Differential Optical Absorption
Spectroscopy (UV-DOAS), and LIght Detection and Ranging (LIDAR).