Comparative evaluation of Spatio-Temporal Exposure Assessment Methods for estimating the health effects of air pollution (STEAM)

Background: Epidemiological studies have linked long- and short-term outdoor air pollution exposures to increased risks of death and morbidity. Cohort studies evaluate the health effects of long-term exposure by exploiting spatial heterogeneity in annual air pollution concentrations whereas time-series studies evaluate acute effects exploiting temporal variability in pollution concentrations. The extent to which the adverse health effects reported by these different study designs overlap has important implications for health impact assessment and policy development and to date this has not been investigated outside the US. In the past, both study designs have been limited by the availability of monitored pollution data but the development of dispersion and land use regression models have improved exposure assessment in cohort studies and enabled the investigation of a broader range of pollutants. The extension of these models to provide spatially resolved daily estimates of pollutant concentrations will enable an integrated assessment of health effects arising from both long- and short-term exposures to a wide range of pollutants and with applicability to locations with sparse or no monitoring.
Objectives: 1.To develop, validate and compare dispersion, land use regression and satellite data based pollution models for London at both fine spatial (postcode level) and temporal (daily) scales. 2. To assess the performance of these methods and their combinations in estimating the health effects of long and short-term exposures to air pollutants. 3. To use the optimum integrated exposure method to estimate the relative importance of the effects of long-and short-term exposure for selected health outcomes. To achieve these objectives the project will use the expertise developed within the MRC-PHE Centre for Environment and Health and will need to draw upon the expertise of pioneering international groups (in the U.S. & Greece) in modelling, simulation studies and time series analyses.
Methods: Models will be developed for particulate and gaseous pollutants and validated using measured concentrations from the London Air Quality Network. Their applicability to locations with sparse or no monitoring will be assessed using sequentially smaller parts of the available exposure information. An extensive simulation study, in which the "true" effect is known, will investigate the implications of using each exposure method on the health effect estimation (precision and bias).To enable proof of concept for the simultaneous estimation of long- and short-term effects on various health outcomes, the analysis of selected endpoints including GP consultations, hospital admissions and mortality data will be applied.
Innovation aspects:
1. Application of air pollution modelling approaches at a fine time and spatial resolution
2. Integration of the different exposure assessment methods for optimizing their performance.
3. Use of simulation methods to evaluate simultaneously the performance of models in assessing the effects of long- and short-term exposure to particulate and gaseous pollutants.
4. Simultaneous estimation of health effects of long- and short-term exposure to air pollution in existing large health data sets to enable a comparison of their relative importance.
Policy implications:
1. Information on the advantages and disadvantages of each exposure model will inform the optimum extent and density of monitoring systems and other inputs to local models.
2. The simultaneous estimation of the effects of short and long-term exposures will provide a rationale for the balance between emergency short-term action and long-term pollution management interventions.
3. Informing the development of modelling in areas of Europe and the World where monitoring is not so dense.
4. Informing health studies about the comparative importance of short vs long-term effects in areas of Europe and the World where health outcome data bases are limited

The aim of this study is to develop, validate and compare three integrated air pollution exposure assessment methods for estimating simultaneously the health effects of short and long-term exposure to outdoor air pollutants. The dispersion model will use CMAQ-urban which couples the USEPA regional model, CMAQ and the Atmospheric Dispersion Modelling System roads model incorporating emissions data. This combined model will provide hourly predictions at 20x20m spatial resolution for Greater London for PM10, PM2.5, NO2 and O3. Spatio-temporal LUR models for PM10, PM2.5, NO2 and O3 will use a semiparametric approach with covariates that vary primarily in space (e.g. distance to major road, traffic counts) and covariates that vary primarily in time (e.g. meteorology) and a bivariate smooth thin plate function for the geographical co-ordinates. New methods, similar to Chudnovsky 2014, will use a hybrid model, with AOD, land use, and meteorological data to estimate daily PM2.5. Spatial predictors will include population and traffic density, land use (Landsat) and emissions as well as time varying predictors (e.g. vegetative index from MODIS, meteorology). Each method will be evaluated using simulation techniques developed from previous work. We propose to construct scenarios where 'true' temporally and spatially resolved air pollution data are associated with health outcomes by a priori defined concentration response functions (such as those proposed by W.H.O. HRAPIE project). Model performance will be assessed under a variety of scenarios using a number of parameters including bias, statistical power and coverage intervals. Finally the model predictions will be used in conjunction with selected health outcomes to demonstrate proof of concept in estimating simultaneous associations between health outcomes and long- and short-term exposure to air pollution.

National and international governmental agencies responsible for air pollution policy development and monitoring and for health impact assessment will be the main beneficiaries of this research. In the UK, Defra, the Department of Health, Public Health England and Local Authorities will be able to utilise the methodologies derived from the project to plan the deployment of air pollution monitoring sites, assess health impacts and determine local and national air pollution mitigation strategies in both the long- and short-term. Similarly, the WHO, the European Environment Agency and other devolved government and government agencies or regulators can also utilise the methodology with particular application in locations where less comprehensive monitoring networks exist. Examples of health impact assessment exercises at national and international levels include exercises here in the UK [COMEAP report] and in the EC [HRAPIE]. The central topic of our project is better estimation of a population exposure to ambient air pollution and the subsequent impact on human health. We therefore anticipate that the general public, both here in the UK as well as abroad, will benefit from better pollution management policies and a greater awareness of the links between air pollutant exposure and health. The academic community (epidemiology/Public Health, and air pollution science) will also benefit especially from the methodological developments.

How will they benefit from this research?
Health effects of acute and chronic exposure to air pollution have usually been studied separately and their results used for separate health impact assessment exercises. In a number of cases the lack of evidence for health effects of long term exposure from cohort studies has been supplemented by the evidence from short-term exposure (time series) studies. The methods used to derive exposure measures in cohort studies often vary and make synthesis difficult. Transferability of results from the regions of the world where studies have been conducted to less well studied locations is also problematical. This project will attempt to address many of these difficulties by 1) assessing the advantages and disadvantages of each exposure model to inform the optimum extent and density of monitoring systems and other inputs to local models required in any region of the world; 2) inform the development of modelling in areas where monitoring networks are sparse to facilitate exposure assessment; 3) facilitate the simultaneous estimation of the effects of long- and short-term exposures and provide a rationale for the balance between emergency short-term action and long-term pollution management interventions applicable to local and national needs; and 4) inform health studies about the comparative importance of short vs long-term effects in areas of Europe and the World where health outcome data bases are limited. The novel methods developed in this project will provide the tools policy analysts require to undertake more informed policy formulation and assessment exercises providing relevant information to local, national and international agencies responsible for air pollution policy.