Biomedical subjects

Tan Zhu

Publications and source records attributed to Tan Zhu.

4 recordsLinked to original sources

PubMed2002

Chapter one: exposure measurements.

Determining human exposure to suspended particulate concentrations requires measurements that quantify different particle properties in microenvironments where people live, work, and play. Particle mass, size, and chemical composition are important exposure variables, and these are typically measured with time-integrated samples on filters that are later submitted to laboratory analyses. This requires substantial sample handling, quality assurance, and data reduction. Newer technologies are being developed that allow in-situ, time-resolved measurements for mass, carbon, sulfate, nitrate, particle size, and other variables. These are large measurement systems that are more suitable for fixed monitoring sites than for personal applications. Human exposure studies need to be designed to accomplish specific objectives rather than to serve too many purposes. Resources need to be divided among study design, field sampling, laboratory analysis, quality assurance, data management, and data analysis phases. Many exposure projects allocated too little to the non-measurement activities.

Air Pollutants↗

PubMed2002

Chapter three: methodology of exposure modeling.

In this chapter, the concept of exposure assessment and its evolution is introduced, and evaluated by critically appraising the pertinent literature as it applies to exposures to Particulate Matter (PM). Exposure measurement or estimation methodologies and models are reviewed. Three exposure/measurement methodologies are assessed. Estimation methods focus on source evaluation and attribution, sources include those outdoors and indoors as well as in occupational and in-transit environments. Fate and transport models and their inputs are addressed to estimate concentrations outdoors and indoors; source attribution techniques help focus on the contributing sources. Activity pattern techniques are also reviewed and their use in exposure models to estimate inhalation exposure to PM is presented. Deterministic, regression and other stochastic models of exposure to PM are reviewed and evaluated. Strengths, limitations, assumptions and affirmations of the use of exposure assessment as an integral component of risk assessment and risk management are discussed in the conclusions and discussions section of this work.

Air Pollutants↗

PubMed2002

Designing monitoring networks to represent outdoor human exposure.

Measurements of outdoor human exposure to suspended particulate matter (PM) are always constrained by available resources. An effective network design requires tradeoffs between variables measured, the number of sampling locations, sample duration, and sampling frequency. Sampling sites are needed to represent neighborhood and urban spatial scales with minimal influences from nearby sources. Although most PM measurements for determining compliance with standards are taken over 24-h periods every third to sixth day, outdoor human exposure assessment requires measurements taken continuously throughout the day, preferably over durations of 1 h or less. More detailed particle size and chemistry data are also desirable, as smaller size fractions and specific chemicals may be better indicators of adverse health effects than total mass samples.

Air Pollutants↗

PubMed2002

Receptor modeling application framework for particle source apportionment.

Receptor models infer contributions from particulate matter (PM) source types using multivariate measurements of particle chemical and physical properties. Receptor models complement source models that estimate concentrations from emissions inventories and transport meteorology. Enrichment factor, chemical mass balance, multiple linear regression, eigenvector. edge detection, neural network, aerosol evolution, and aerosol equilibrium models have all been used to solve particulate air quality problems, and more than 500 citations of their theory and application document these uses. While elements, ions, and carbons were often used to apportion TSP, PM10, and PM2.5 among many source types, many of these components have been reduced in source emissions such that more complex measurements of carbon fractions, specific organic compounds, single particle characteristics, and isotopic abundances now need to be measured in source and receptor samples. Compliance monitoring networks are not usually designed to obtain data for the observables, locations, and time periods that allow receptor models to be applied. Measurements from existing networks can be used to form conceptual models that allow the needed monitoring network to be optimized. The framework for using receptor models to solve air quality problems consists of: (1) formulating a conceptual model; (2) identifying potential sources; (3) characterizing source emissions; (4) obtaining and analyzing ambient PM samples for major components and source markers; (5) confirming source types with multivariate receptor models; (6) quantifying source contributions with the chemical mass balance; (7) estimating profile changes and the limiting precursor gases for secondary aerosols; and (8) reconciling receptor modeling results with source models, emissions inventories, and receptor data analyses.

Air Pollutants↗