Models of Exposure for Use in Epidemiological Studies of Air Pollution Health Impacts

Bräuer, Michael; Ainslie, Bruce; Buzzelli, Michael; Henderson, Sarah B.; Larson, Tim; Marshall, Julian; Nethery, Elizabeth; Steyn, D. G.; Su, Jason

doi:10.1007/978-1-4020-8453-9_64

Cited by 9 publications

(16 citation statements)

References 33 publications

(24 reference statements)

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“…We made use of modern methods of estimating ambient air pollution at subjects' residences, using fixed-site monitors, land use regression models, and satellite data (Hystad et al, 2012;Brauer et al, 2008), and then averaged these according to the time lived at each residence. Thus, for each subject, the reported 6-character postal codes of all residences were geocoded to latitude and longitude using the 1994 DMTI Inc. postal code database (Hystad et al, 2012).…”

Section: Assessment Of Exposure To Ambient Air Pollutionmentioning

confidence: 99%

Exposure to ambient air pollution in Canada and the risk of adult leukemia

Winters

Goldberg

Hystad

et al. 2015

Science of The Total Environment

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Section: Assessment Of Exposure To Ambient Air Pollutionmentioning

confidence: 99%

Exposure to ambient air pollution in Canada and the risk of adult leukemia

Winters

Goldberg

Hystad

et al. 2015

Science of The Total Environment

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“…A review on state-of-the-art approaches to assessment of population exposure in epidemiological studies, their strengths and limitations, as well as future research are discussed and identified in (Brauer et al 2008). Most of the innovative statistical approaches are discussed and implemented in (Peng and Dominici, 2008).…”

Section: Sustainability Indexmentioning

confidence: 99%

Air quality indices: a review

Plaia

Ruggieri

2010

Rev Environ Sci Biotechnol

110

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National directives on air quality oblige nations to monitor and report on their air quality, allowing the public to be informed on the ambient pollution levels. The last is the reason for the always increasing interest, demonstrated by the number of publications on this topic in recent years, in air quality/ pollution indices: since the concentration of individual pollutants can be confusing, concentration measurements are conveniently transformed in terms of an air quality index. In this way, complex situations are summarized in a single figure, letting comparisons in time and space be possible. In this paper we will give an overview about the Air Quality/Pollution Indices proposed in literature and/or adopted by countries, trying also to categorize them into homogeneous groups. For the classification different approaches can be followed. Since in real life exposure to mixtures of chemicals occurs, with additive, synergistic or antagonistic effects, here we will distinguish between indices that consider the conjoint effect of pollutants and indices only based on the actual most dangerous pollutant. This brief review on air pollution indices shows, on one side, the wide interest in the problem, on the other, the lack of a common strategy which allows to compare the state of the air for cities that follow different directives. The main differences between the indices will be also described.

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“…especially for the future scenarios. These problems lead to lesser use of the dispersion models in the health impact assessment studies compared to the LUR models [23]. On the contrary, the conventional LUR models are encountering problems in modeling the PM 2.5 concentration with high resolutions due to not considering the interaction between emissions and meteorological processes.…”

Section: Scenarios Evaluationsmentioning

confidence: 99%

A Hybrid Fuzzy Inference System Based on Dispersion Model for Quantitative Environmental Health Impact Assessment of Urban Transportation Planning

2017

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Abstract:Characterizing the spatial variation of traffic-related air pollution has been and is a long-standing challenge in quantitative environmental health impact assessment of urban transportation planning. Advanced approaches are required for modeling complex relationships among traffic, air pollution, and adverse health outcomes by considering uncertainties in the available data. A new hybrid fuzzy model is developed and implemented through hierarchical fuzzy inference system (HFIS). This model is integrated with a dispersion model in order to model the effect of transportation system on the PM 2.5 concentration. An improved health metric is developed as well based on a HFIS to model the impact of traffic-related PM 2.5 on health. Two solutions are applied to improve the performance of both the models: the topologies of HFISs are selected according to the problem and used variables, membership functions, and rule set are determined through learning in a simultaneous manner. The capabilities of this proposed approach is examined by assessing the impacts of three traffic scenarios involved in air pollution in the city of Isfahan, Iran, and the model accuracy compared to the results of available models from literature. The advantages here are modeling the spatial variation of PM 2.5 with high resolution, appropriate processing requirements, and considering the interaction between emissions and meteorological processes. These models are capable of using the available qualitative and uncertain data. These models are of appropriate accuracy, and can provide better understanding of the phenomena in addition to assess the impact of each parameter for the planners.

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Models of Exposure for Use in Epidemiological Studies of Air Pollution Health Impacts

Cited by 9 publications

References 33 publications

Exposure to ambient air pollution in Canada and the risk of adult leukemia

Exposure to ambient air pollution in Canada and the risk of adult leukemia

Air quality indices: a review

A Hybrid Fuzzy Inference System Based on Dispersion Model for Quantitative Environmental Health Impact Assessment of Urban Transportation Planning

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