London Hybrid Exposure Model: Improving Human Exposure Estimates to NO₂ and PM_2.5 in an Urban Setting

Abstract

Here we describe the development of the London Hybrid Exposure Model (LHEM), which calculates exposure of the Greater London population to outdoor air pollution sources, in-buildings, in-vehicles, and outdoors, using survey data of when and where people spend their time. For comparison and to estimate exposure misclassification we compared Londoners LHEM exposure with exposure at the residential address, a commonly used exposure metric in epidemiological research. In 2011, the mean annual LHEM exposure to outdoor sources was estimated to be 37% lower for PM and 63% lower for NO than at the residential address. These decreased estimates reflect the effects of reduced exposure indoors, the amount of time spent indoors (∼95%), and the mode and duration of travel in London. We find that an individual's exposure to PM and NO outside their residential address is highly correlated (Pearson's R of 0.9). In contrast, LHEM exposure estimates for PM and NO suggest that the degree of correlation is influenced by their exposure in different transport modes. Further development of the LHEM has the potential to increase the understanding of exposure error and bias in time-series and cohort studies and thus better distinguish the independent effects of NO and PM.

Air quality simulations for London using a coupled regional-to-local modelling system

“…Such detailed pollutant spatial distributions have applications in health-related exposure analysis (Smith et al, 2016). The coupled system could also be used to assess the effects of air quality policies at a range of scales.…”

“…In addition, short-term intensive campaigns making use of specialist monitoring equipment, as for example carried out for the ClearfLo project (Clean Air for London; Bohnenstengel et al, 2015), are of great value for detailed assessment of model performance and underlying processes, whilst sampling equipment can also be carried by moving vehicles or individuals for short-term detailed studies. In contrast to measurements, air quality or atmospheric chemistry transport models, evaluated with the above data, allow pollutant concentrations to be simulated with complete spatial-temporal coverage leading to detailed calculations of population exposure (Smith et al, 2016).…”

Personal Exposure to PM2.5 in the Megacity of Mexico: A Multi-Mode Transport Study

“…The exposure concentrations to PM 2.5 were measured using portable aerosol real-time photometric monitors (pDR-1500, Thermo Scientific, Franklin, MA, USA), operated at a frequency of 1 Hz, with stated precision for 30-days of ±2% (±0.005 mg m −3 ) at (2σ) 2 . During all journeys, 2 monitors were carried on the chest of volunteers and operated simultaneously.…”

“…Although personal exposure in transport micro-environments represents only between 1-5% of the time spent in a day [1,2], in large urban areas this time may increase significantly. For example, within the Mexico City Metropolitan Area (MCMA), a typical single journey may take between 41 and 81 mins, while average journeys of 51 mins represent spending 16 h per week in transport micro-environments [3].…”

“…For instance, Dons et al [5] reported a difference of 2-fold in personal exposure to black carbon for commuters in Belgium compared with non-commuters. Within the Greater London Area, Smith et al [2] reported that daily commutes contribute around 9% of total daily exposure to PM 2.5 . However, this can be further exacerbated during traffic rush hours, when exposure concentrations of PM 2.5 may increase by between 5-20% [6,7].…”