RESUMO
CONTEXT: Policies aiming at decreasing air pollutants (e.g., fine particulate matter, PM2.5) are often designed without targeting an explicit health benefit nor carrying out cost-benefit analyses. METHODS: We developed a transdisciplinary backward and forward approach at the conurbation level: from health objectives set by local decision-makers, we estimated which reductions in PM2.5 exposures and emissions would allow to reach them, and identified urban policies leading to these reductions (backward approach). We finally conducted health impact and cost-benefit analyses of these policies (forward approach). The policies were related to the most emitting sectors in the considered area (Grenoble, France), wood heating and transport sectors. The forward approach also considered the health impact and co-benefits of these policies related to changes in physical activity and CO2 emissions. FINDINGS: Decision-makers set three health targets, corresponding to decreases by 33% to 67% in PM2.5-attributable mortality in 2030, compared to 2016. A decrease by 42% in PM2.5 exposure (from 13.9 µg/m3) was required to reach the decrease by 67% in PM2.5-attributable mortality. For each Euro invested, the total benefit was about 30 for policies focusing on wood heating, and 1 to 68 for traffic policies. Acting on a single sector was not enough to attain a 67% decrease in PM2.5-attributable mortality. This target could be achieved by replacing all inefficient wood heating equipment by low-emission pellet stoves and reducing by 36% the traffic of private motorized vehicles. This would require to increase the share of active modes (walking, biking ), inducing increases in physical activity and additional health benefits beyond the initial target. Annual net benefits were between 484 and 629 per capita for policies with report on active modes, compared to between 162 and 270 without. CONCLUSIONS: Urban policies strongly reducing air pollution-attributable mortality can be identified by our approach. Such policies can be cost-efficient.
