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Res Rep Health Eff Inst. 2018 Feb;(194):1-65.

A Dynamic Three-Dimensional Air Pollution Exposure Model for Hong Kong.

Research report (Health Effects Institute)

B Barratt, M Lee, P Wong, R Tang, T H Tsui, W Cheng, Y Yang, P-C Lai, L Tian, T-Q Thach, R Allen, M Brauer

Affiliations

  1. King's College London, UK.
  2. University of British Columbia, Canada.
  3. The University of Hong Kong, Hong Kong SAR.
  4. Simon Fraser University, Canada.

PMID: 31883241

Abstract

INTRODUCTION: High-density high-rise cities have become a more prominent feature globally. Air quality is a significant public health risk in many of these cities. There is a need to better understand the extent to which vertical variation in air pollution and population mobility in such cities affect exposure and exposure-response relationships in epidemiological studies.

METHODS: We used a novel strategy to execute a staged model development that incorporated horizontal and vertical pollutant dispersion, building infiltration, and population mobility patterns in estimating traffic-related air pollution (TRAP) exposures in the Hong Kong Special Administrative Region (HK SAR).

Two street-level spatial monitoring campaigns were undertaken to facilitate the creation of a two-dimensional land-use regression (LUR) model. A network of approximately 100 passive nitric oxide-nitrogen dioxide (NO-NO

Vertical air pollution monitoring was carried out at six strategic locations for two weeks in the warm season and two weeks in the cool season. Continuous measurements were carried out at four different heights of a residential building and on both sides of a street canyon. The heights ranged from as close to street level as practically possible up to a maximum of 50 meters (i.e., below the 20th floor). Paired indoor monitoring was included to allow the calculation of infiltration coefficients to feed into the dynamic component of the exposure model.

The final phase of model development addressed population mobility. A population-representative travel behavior survey (

Development of the exposure model in distinct packages allowed the application of a staged approach to an existing cohort data set. Mortality risk estimates for an elderly cohort of 66,000 Hong Kong residents were calculated using increasing exposure model complexity.

RESULTS: The street-level (2-dimensional [2D]) LUR modeling captured important spatial parameters and represented spatial patterns of air quality in Hong Kong that were consistent with the literature. Higher concentrations of gaseous pollutants were centered in Kowloon and the northern region of Hong Kong Island. PM

Exponential decay rates (

We found that values of the median infiltration efficiencies (

Dynamic exposure estimates were compared against home outdoor estimates. As expected, the addition of an indoor component decreased time-weighted exposure estimates, which were balanced out to some extent by the inclusion of transport microenvironments. Overall, mean time-weighted exposures for the full dynamic model were around 20% lower than home outdoor estimates.

Higher levels of exposures were found with working adults and students than for those neither in work nor study. This was due to the increased mobility of people going to work or school. The exposures to PM

The availability of an existing cohort data set of elderly Hong Kong residents (

Overall, results indicated that the application of exposure estimates that incorporated infiltration, vertical, and to a lesser extent, dynamic components resulted in higher hazard ratios (HRs) than the standard street-level model and increased the number of significant associations with all-natural-cause, cardiovascular, and respiratory mortality outcomes.

CONCLUSIONS: The results from the study provided the first evidence that considering air pollution exposure in a dynamic 3D landscape would benefit epidemiological studies. Higher HRs and a greater number of significant associations were found between mortality and pollutant exposures that would not have been found had standard 2D exposure models been used. Dynamic models can also identify differential exposures between population subtypes (e.g., students and working adults; those neither in work nor study).

Improved urban building design appears to be stimulating the dispersion of local TRAP in street canyons. Conversely,

We have demonstrated that the creation of effective advanced exposure models is possible in Asian cities without an undue burden on resources. We recommend that vertical exposure patterns be incorporated in future epidemiological studies in high-rise cities where the floor of residence is recorded in health record data.

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