Recent epidemiological evidence suggests that the logarithm of concentration is a better predictor of mortality risk from long-term exposure to ambient PM2.5 and NO2 than concentration itself. A log-concentration-response function (CRF) predicts a heightened excess risk per unit concentration at low levels of exposure that further increases as the air becomes less polluted. Using an adjoint air quality model, we estimate the public health benefits of reducing NOx emissions, on a per-ton and source-by-source basis. Our estimates of benefits-per-ton assume linear in concentration and log-concentration CRFs for NO2 and a CRF that is linear in concentration for O3. We apply risk coefficients estimated using the Canadian Census Health and Environment Cohort. We find that a log-concentration CRF for NO2 leads almost consistently to larger benefits-per-ton than a linear in concentration CRF (e.g., $500 000 ton−1 compared to $270 000 ton−1 for Ottawa). We observe that concentrations gradually decline due to widespread, progressive emissions abatement, entailing increasing health benefits as a result of (1) a log-concentration CRF for NO2 and (2) the nonlinear response of O3 to NOx emissions. Our results indicate that NOx abatement has the potential to incur substantial and increasing health benefits, by up to five times with 85% emission reductions, for Canada into the future.
Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON, Canada;Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON, Canada;Safe Environments Directorate, HECSB, Health Canada, Ottawa, ON, Canada;Environmental and Radiation Health Sciences Directorate, HECSB, Health Canada, Ottawa, ON, Canada;Environmental and Radiation Health Sciences Directorate, HECSB, Health Canada, Ottawa, ON, Canada;Environmental and Radiation Health Sciences Directorate, HECSB, Health Canada, Ottawa, ON, Canada
Recommended Citation:
A J Pappin,A Hakami,P Blagden,et al. Health benefits of reducing NO x emissions in the presence of epidemiological and atmospheric nonlinearities[J]. Environmental Research Letters,2016-01-01,11(6)