A tale of two cities: contrasting equity of greenspace benefits in relation to PM2.5 exposure

•Background: Urban air pollution is the second highest risk factor for non-communicable diseases. Socioeconomically deprived populations are at greater risk from related adverse health outcomes and often bear the additional burden of living in areas with higher pollution exposure. To reduce this inequality policy makers need to understand the relationship between the location of interventions and improvements in air quality. The 3–30-300 greening rule outlines guidance to improve residents’ access to trees and greenspace. No studies have yet evaluated its implications for reductions in inequalities or co-benefits beyond greenspace access. This paper explores the relationship between exposure to PM2.5 and socioeconomic status in Paris and Aarhus, and the potential impact of the 3–30-300 rule on health inequalities. •Method: We use air quality models and socioeconomic data to calculate disparities in access to greenspace and exposure to fine particulate air pollution across subgroups using two land cover scenarios: existing greenspace conditions and potential enhancements following the 3–30 rule. The following socioeconomic data were disaggregated to residential buildings: households in poverty, age group, citizenship, employment, and education. Exposure to air pollution was calculated as the population-weighted average of PM2.5 concentration (µg m−3). •Results: The relationship between socioeconomic characteristics and exposure to poor air quality differed in each city: In Paris, populations often considered more vulnerable to adverse health outcomes (unemployed, non-citizens, lower education level, lowest income) were exposed to higher concentrations of PM2.5, (although the relationship with income was nonlinear), whilst both older and younger populations had slightly lower particulate exposure than working age populations. By contrast, in Aarhus, populations with higher socioeconomic status (and by association, lower vulnerability) in terms of income, education, citizenship and employment status, were exposed to higher concentrations of PM2.5, whilst children were the age group least exposed to fine particulates. Increasing greenspace under the 3–30 had contrasting effects on inequities in each city: mitigations improved air quality for all populations in both but, in Paris, the greatest benefit was experienced by those with lower baseline exposure as well as lower vulnerability. In Aarhus larger air quality improvements were experienced by populations with the highest baseline exposure except for the income characteristic. These were not groups expected to be at greater risk of adverse health outcomes. •Conclusions: Reductions in PM2.5 concentration can be produced via targeted increases in trees. The impact on public health outcomes depends in part, on the spatial distribution of socioeconomic groups. Somewhat counter-intuitively, the 3–30 rule in both cities gave greater benefit to those with lower vulnerability.