Using Building Heights and Street Configuration to Enhance Intraurban PM₁₀, NO_X, and NO₂ Land Use Regression Models

Land use regression (LUR) models have been widely used to provide long-term air pollution exposure assessment in epidemiological studies. However, models have rarely offered variables that account for the dispersion environment close to the source (e.g., street canyons, position and dimensions of buildings, road width). This study used newly available data on building heights and geometry to enhance the representation of land use and the dispersion field in LUR. Models were developed for PM₁₀, NO_X, and NO₂ for 2008–2011 for London, U.K. A separate set of models using “traditional” land use and traffic indicators (e.g., distance from road, area of housing within circular buffers) were also developed and their performance was compared with “enhanced” models. Models were evaluated using leave-one-out (<i>n</i> – 1) (LOOCV) and grouped (<i>n</i> – 25%) cross-validation (GCV). LOOCV R² values were 0.71, 0.50, 0.66 and 0.73, 0.79, 0.78 for traditional and enhanced PM₁₀, NO_X, and NO₂ models, respectively. GCV R² values were 0.71, 0.53, 0.64 and 0.68, 0.77, 0.77 for traditional and enhanced PM₁₀, NO_X, and NO₂ models, respectively. Data on building volume within the area common to a 20 m road buffer within a 25 m circular buffer substantially improved the performance (R² > 13%) of NO_X and NO₂ LUR models

Predicting daily concentrations of nitrogen dioxide, particulate matter and ozone at fine spatial scale in Great Britain

Short-term exposure studies have often relied on time-series of air pollution measurements from monitoring sites. However, this approach does not capture short-term changes in spatial contrasts in air pollution. To address this, models representing both the spatial and temporal variability in air pollution have emerged in recent years. Here, we modelled daily average concentrations of nitrogen dioxide (NO2), particulate matter (PM2.5 and PM10) and ozone (O3) on a 25 m grid for Great Britain from 2011 to 2015 using a generalised additive mixed model, with penalised spline smooth functions for covariates. The models included local-scale predictors derived using a Geographic Information System (GIS), daily estimates from a chemical transport model, and daily meteorological characteristics. The models performed well in explaining the variability in daily averaged measured concentrations at 48–85 sites: 63% for NO2, 77% for PM2.5, 80% for PM10 and 85% for O3. Outputs of the study include daily air pollution maps that can be applied in epidemiological studies across Great Britain. Daily concentration values can also be predicted for specific locations, such as residential addresses or schools, and aggregated to other exposure time periods (including weeks, months, or pregnancy trimesters) to facilitate the needs of different health analyses

Development and transferability of ultrafine particle land use regression models in London

Due to a lack of routine monitoring, bespoke measurements are required to develop ultrafine particle (UFP) land use regression (LUR) models, which is especially challenging in megacities due to their large area. As an alternative, for London, we developed separate models for three urban residential areas, models combining two areas, and models using all three areas. Models were developed against annual mean ultrafine particle count cm−3 estimated from repeated 30-min fixed-site measurements, in different seasons (2016–2018), at forty sites per area, that were subsequently temporally adjusted using continuous measurements from a single reference site within or close to each area. A single model and 10 models were developed for each individual area and combination of areas. Within each area, sites were split into 10 groups using stratified random sampling. Each of the 10 models were developed using 90% of sites. Hold-out validation was performed by pooling the 10% of sites held-out each time. The transferability of models was tested by applying individual and two-area models to external area(s). In model evaluation, within-area mean squared error (MSE) R2 ranged from 14% to 48%. Transferring individual- and combined-area models to external areas without calibration yielded MSE-R2 ranging from −18 to 0. MSE-R2 was in the range 21% to 41% when using particle number count (PNC) measurements in external areas to calibrate models. Our results suggest that the UFP models could be transferred to other areas without calibration in London to assess relative ranking in exposures but not for estimating absolute values of PNC

Development and Back-Extrapolation of NO₂ Land Use Regression Models for Historic Exposure Assessment in Great Britain

Modeling historic air pollution exposures is often restricted by availability of monitored concentration data. We evaluated back-extrapolation of land use regression (LUR) models for annual mean NO₂ concentrations in Great Britain for up to 18 years earlier. LUR variables were created in a geographic information system (GIS) using land cover and road network data summarized within buffers, site coordinates, and altitude. Four models were developed for 2009 and 2001 using 75% of monitoring sites (in different groupings) and evaluated on the remaining 25%. Variables selected were generally stable between models. Within year, hold-out validation yielded mean-squared-error-based <i>R</i>² (MSE-<i>R</i>²) (i.e., fit around the 1:1 line) values of 0.25–0.63 and 0.51–0.65 for 2001 and 2009, respectively. Back-extrapolation was conducted for 2009 and 2001 models to 1991 and for 2009 models to 2001, adjusting to the year using two background NO₂ monitoring sites. Evaluation of back-extrapolated predictions used 100% of sites from an historic national NO₂ diffusion tube network (<i>n</i> = 451) for 1991 and 70 independent sites from automatic monitoring in 2001. Values of MSE-<i>R</i>² for back-extrapolation to 1991 were 0.42–0.45 and 0.52–0.55 for 2001 and 2009 models, respectively, but model performance varied by region. Back-extrapolation of LUR models appears valid for exposure assessment for NO₂ back to 1991 for Great Britain

Inequalities in Exposure to Nitrogen Dioxide in Parks and Playgrounds in Greater London.

Elevated levels of nitrogen dioxide (NO2) have been associated with adverse health outcomes in children, including reduced lung function and increased rates of asthma. Many parts of London continue to exceed the annual average NO2 concentration of 40 µg/m3 set by the EU directive. Using high-resolution maps of annual average NO2 for 2016 from the London Atmospheric Emissions Inventory and detailed maps of open spaces from Britain's national mapping agency, Ordnance Survey, we estimated average NO2 concentrations for every open space in Greater London and analysed geospatial patterns comparing Inner verses Outer London and the 32 London Boroughs. Across Greater London, 24% of play spaces, 67% of private parks and 27% of public parks had average levels of NO2 that exceeded the EU limit for NO2. Rates of exceedance were higher in Inner London; open spaces in the City of London had the highest average NO2 values among all the London Boroughs. The closest play space for more than 250,000 children (14% of children) under 16 years old in Greater London had NO2 concentrations above the recommended levels. Of these children, 66% (~165,000 children) lived in the most deprived areas of London, as measured by the Index of Multiple Deprivations, where average NO2 concentrations in play spaces were on average 6 µg/m3 higher than for play spaces in the least deprived quintile. More action is needed to reduce NO2 in open spaces to safe levels through pollution reduction and mitigation efforts, as currently, open spaces in Greater London, including play spaces, parks and gardens, still have dangerously high levels of NO2, according to the most recent NO2 map

Automation of cleaning and reconstructing residential address histories to assign environmental exposures in longitudinal studies.

BACKGROUND:We have developed an open-source ALgorithm for Generating Address Exposures (ALGAE) that cleans residential address records to construct address histories and assign spatially-determined exposures to cohort participants. The first application of this algorithm was to construct prenatal and early life air pollution exposure for individuals of the Avon Longitudinal Study of Parents and Children (ALSPAC) in the South West of England, using previously estimated particulate matter ≤10  µm (PM10) concentrations. METHODS:ALSPAC recruited 14 541 pregnant women between 1991 and 1992. We assigned trimester-specific estimated PM10 exposures for 12 752 pregnancies, and first year of life exposures for 12 525 births, based on maternal residence and residential mobility. RESULTS:Average PM10 exposure was 32.6  µg/m3 [standard deviation (S.D.) 3.0  µg/m3] during pregnancy and 31.4 µg/m3 (S.D. 2.6  µg/m3) during the first year of life; 6.7% of women changed address during pregnancy, and 18.0% moved during first year of life of their infant. Exposure differences ranged from -5.3  µg/m3 to 12.4  µg/m3 (up to 26% difference) during pregnancy and -7.22  µg/m3 to 7.64  µg/m3 (up to 27% difference) in the first year of life, when comparing estimated exposure using the address at birth and that assessed using the complete cleaned address history. For the majority of individuals exposure changed by <5%, but some relatively large changes were seen both in pregnancy and in infancy. CONCLUSIONS:ALGAE provides a generic and adaptable, open-source solution to clean addresses stored in a cohort contact database and assign life stage-specific exposure estimates with the potential to reduce exposure misclassification

Land Use Regression Modeling To Estimate Historic (1962−1991) Concentrations of Black Smoke and Sulfur Dioxide for Great Britain

Land-use regression modeling was used to develop maps of annual average black smoke (BS) and sulfur dioxide (SO₂) concentrations in 1962, 1971, 1981, and 1991 for Great Britain on a 1 km grid for use in epidemiological studies. Models were developed in a GIS using data on land cover, the road network, and population, summarized within circular buffers around air pollution monitoring sites, together with altitude and coordinates of monitoring sites to consider global trend surfaces. Models were developed against the log-normal (LN) concentration, yielding R² values of 0.68 (<i>n</i> = 534), 0.68 (<i>n</i> = 767), 0.41 (<i>n</i> = 771), and 0.39 (<i>n</i> = 155) for BS and 0.61 (<i>n</i> = 482), 0.65 (<i>n</i> = 733), 0.38 (<i>n</i> = 756), and 0.24 (<i>n</i> = 153) for SO₂ in 1962, 1971, 1981, and 1991, respectively. Model evaluation was undertaken using concentrations at an independent set of monitoring sites. For BS, values of R² were 0.56 (<i>n</i> = 133), 0.41 (<i>n</i> = 191), 0.38 (<i>n</i> = 193), and 0.34 (<i>n</i> = 37), and for SO₂ values of R² were 0.71 (<i>n</i> = 121), 0.57 (<i>n</i> = 183), 0.26 (<i>n</i> = 189), and 0.31 (<i>n</i> = 38) for 1962, 1971, 1981, and 1991, respectively. Models slightly underpredicted (fractional bias: 0∼−0.1) monitored concentrations of both pollutants for all years. This is the first study to produce historic concentration maps at a national level going back to the 1960s

Trimester effects of source-specific PM10 on birth weight outcomes in the Avon Longitudinal Study of Parents and Children (ALSPAC)

BackgroundEvidence suggests that exposure to particulate matter with aerodynamic diameter less than 10 μm (PM10) is associated with reduced birth weight, but information is limited on the sources of PM10 and exposure misclassification from assigning exposures to place of residence at birth.MethodsTrimester and source-specific PM10 exposures (PM10 from road source, local non-road source, and total source) in pregnancy were estimated using dispersion models and a full maternal residential history for 12,020 births from the Avon longitudinal study of parents and children (ALSPAC) cohort in 1990-1992 in the Bristol area. Information on birth outcomes were obtained from birth records. Maternal sociodemographic and lifestyle factors were obtained from questionnaires. We used linear regression models for continuous outcomes (birth weight, head circumference (HC), and birth length (BL) and logistic regression models for binary outcomes (preterm birth (PTB), term low birth weight (TLBW) and small for gestational age (SGA)). Sensitivity analysis was performed using multiple imputation for missing covariate data.ResultsAfter adjustment, interquartile range increases in source specific PM10 from traffic were associated with 17 to 18% increased odds of TLBW in all pregnancy periods. We also found odds of TLBW increased by 40% (OR: 1.40, 95%CI: 1.12, 1.75) and odds of SGA increased by 18% (OR: 1.18, 95%CI: 1.05, 1.32) per IQR (6.54 μg/m3) increase of total PM10 exposure in the third trimester.ConclusionThis study adds to evidence that maternal PM10 exposures affect birth weight, with particular concern in relation to exposures to PM10 from road transport sources; results for total PM10 suggest greatest effect in the third trimester. Effect size estimates relate to exposures in the 1990s and are higher than those for recent studies - this may relate to reduced exposure misclassification through use of full residential history information, changes in air pollution toxicity over time and/or residual confounding

Prenatal, early-life and childhood exposure to air pollution and lung function in the UK Avon Longitudinal Study of Parents and Children (ALSPAC) cohort

Rationale: This study investigated asssociations of source-specific air pollution exposure during pregnancy trimesters, infancy and childhood in relation to lung function at ages eight and 15 years in ~14,000 children.Methods: Individual exposure to primary road, local and long range particulate matter with diameter ≤10µm (PM10) were estimated using dispersion modelling for each pregnancy trimester, ages 0-6 months, 7-12 months (1990-1993) and annually to age 15 years (1991-2008). Forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) were measured at age eight and 15 years and converted into age-height-gender adjusted z-scores. Linear regression analyses were conducted, adjusting for potential confounders.Results: 13,963 study children were included in the analysis. At age 8 years, exposure to interquartile range (IQR) higher primary PM10 (0.72µg/m3) from road traffic during the first trimester was associated with lower FEV1 (-0.049, 95%CI:-0.082 to -0.016) and FVC (-0.048, 95%CI:-0.081 to -0.015) z-scores. Similar associations were also seen for exposures during the second and third trimester, and during 0-6 months, 7-12 months, and 0-7 years. Associations were stronger among boys, children whose mother had a lower education level or smoked in pregnancy. PM10 from all sources during the third trimester was significantly associated with lower FVC z-scores. No significant negative associations were seen at age 15 years.Conclusions: Exposure to road-traffic PM10 from as early as in the first trimester may result in small but significant reductions in lung function at age eight years.</p

Green Walkability and Physical Activity in UK Biobank: A Cross-Sectional Analysis of Adults in Greater London.

Urban greenspace provides opportunities for outdoor exercise and may increase physical activity, with accompanying health benefits. Areas suitable for walking (walkability) are also associated with increased physical activity, but interactions with greenspace are poorly understood. We investigated associations of walkability and green walkability with physical activity in an urban adult cohort. We used cross-sectional data from Greater London UK Biobank participants (n = 57,726) and assessed walkability along roads and footpaths within 1000 m of their residential addresses. Additionally, we assessed green walkability by integrating trees and low-lying vegetation into the walkability index. Physical activity outcomes included self-reported and accelerometer-measured physical activity and active transport. We assessed associations using log-linear, logistic and linear regression models, adjusted for individual- and area-level confounders. Higher green walkability was associated with favourable International Physical Activity Questionnaire responses and achievement of weekly UK government physical activity guideline recommendations. Participants living in the highest versus lowest quintile of green walkability participated in 2.41 min (95% confidence intervals: 0.22, 4.60) additional minutes of moderate-and-vigorous physical activity per day. Higher walkability and green walkability scores were also associated with choosing active transport modes such as walking and cycling. Our green walkability approach demonstrates the utility in accounting for walkability and greenspace simultaneously to understand the role of the built environment on physical activity