A novel approach using synthetic population models to assess how urban vegetation alters health inequalities in PM2.5 exposure

Poor air quality is a significant environmental risk factor for health. Urban vegetation has the potential to improve air quality through the removal of harmful pollutants. Our analysis combines atmospheric chemistry transport models with novel health impact assessment methods to estimate the health and equity impacts of PM2.5 removal by urban vegetation on London's all-cause mortality. An atmospheric chemistry model that represents meteorological and chemical interactions was used to determine the change in annual average PM2.5 concentrations attributable to urban vegetation. The impact of PM2.5 change on annual mortality and how those impacts varied by inequality were determined using a georeferenced synthetic population representative of the London population, with input data on the change in concentrations, area-level mortality rates, and existing exposure-response coefficients. We found socio-economic and area disparities in both PM2.5 exposure and in the reduction in annual concentrations attributable to urban vegetation. Although annual mean PM2.5 exposure was highest in the most deprived areas, the most affluent areas had a greater reduction in exposure (1.17 µg/m3) compared to the most deprived areas (1.05 µg/m3). Avoided annual deaths were estimated as 408 (95%CI: 309–457), equivalent to a 7% reduction in mortality attributed to PM2.5. There was less indication of inequality in the avoided deaths when grouped by deprivation deciles. Urban vegetation can help reduce mortality impacts associated with PM2.5 in the Greater London region, with variations by area and by socio-economic status. To address inequities in pollutant removal and maximise health benefits, green interventions should be implemented alongside actions that reduce pollution at source.