Myriam Tobollik1, Menno Keuken2, Clive Sabel3, Hilary Cowie4, Jouni Tuomisto5, Denis Sarigiannis6, Nino Künzli7, Laura Perez7, Pierpaolo Mudu8. 1. School of Public Health, Bielefeld University, Bielefeld, Germany; German Environment Agency, Section Exposure Assessment and Environmental Health Indicators, Corrensplatz 1, 14195 Berlin, Germany. Electronic address: mtobollik@uni-bielefeld.de. 2. Netherlands Applied Research Organization (TNO), Utrecht, the Netherlands. 3. School of Geographical Sciences, University of Bristol, Bristol, United Kingdom. 4. Institute of Occupational Medicine, Edinburgh, United Kingdom. 5. National Institute for Health and Welfare Kuopio, Kuopio, Finland. 6. Aristotle University of Thessaloniki, Thessaloniki, Greece. 7. Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland. 8. WHO European Centre for Environment and Health, World Health Organization Regional Office for Europe, Bonn, Germany. Electronic address: mudup@ecehbonn.euro.who.int.
Abstract
BACKGROUND: Green house gas (GHG) mitigation policies can be evaluated by showing their co-benefits to health. METHOD: Health Impact Assessment (HIA) was used to quantify co-benefits of GHG mitigation policies in Rotterdam. The effects of two separate interventions (10% reduction of private vehicle kilometers and a share of 50% electric-powered private vehicle kilometers) on particulate matter (PM2.5), elemental carbon (EC) and noise (engine noise and tyre noise) were assessed using Years of Life Lost (YLL) and Years Lived with Disability (YLD). The baseline was 2010 and the end of the assessment 2020. RESULTS: The intervention aimed at reducing traffic is associated with a decreased exposure to noise resulting in a reduction of 21 (confidence interval (CI): 11-129) YLDs due to annoyance and 35 (CI: 20-51) YLDs due to sleep disturbance for the population per year. The effects of 50% electric-powered car use are slightly higher with a reduction of 26 (CI: 13-116) and 41 (CI: 24-60) YLDs, respectively. The two interventions have marginal effects on air pollution, because already implemented traffic policies will reduce PM2.5 and EC by around 40% and 60% respectively, from 2010 to 2020. DISCUSSION: The evaluation of planned interventions, related to climate change policies, targeting only the transport sector can result in small co-benefits for health, if the analysis is limited to air pollution and noise. This urges to expand the analysis by including other impacts, e.g. physical activity and well-being, as a necessary step to better understanding consequences of interventions and carefully orienting resources useful to build knowledge to improve public health.
BACKGROUND: Green house gas (GHG) mitigation policies can be evaluated by showing their co-benefits to health. METHOD: Health Impact Assessment (HIA) was used to quantify co-benefits of GHG mitigation policies in Rotterdam. The effects of two separate interventions (10% reduction of private vehicle kilometers and a share of 50% electric-powered private vehicle kilometers) on particulate matter (PM2.5), elemental carbon (EC) and noise (engine noise and tyre noise) were assessed using Years of Life Lost (YLL) and Years Lived with Disability (YLD). The baseline was 2010 and the end of the assessment 2020. RESULTS: The intervention aimed at reducing traffic is associated with a decreased exposure to noise resulting in a reduction of 21 (confidence interval (CI): 11-129) YLDs due to annoyance and 35 (CI: 20-51) YLDs due to sleep disturbance for the population per year. The effects of 50% electric-powered car use are slightly higher with a reduction of 26 (CI: 13-116) and 41 (CI: 24-60) YLDs, respectively. The two interventions have marginal effects on air pollution, because already implemented traffic policies will reduce PM2.5 and EC by around 40% and 60% respectively, from 2010 to 2020. DISCUSSION: The evaluation of planned interventions, related to climate change policies, targeting only the transport sector can result in small co-benefits for health, if the analysis is limited to air pollution and noise. This urges to expand the analysis by including other impacts, e.g. physical activity and well-being, as a necessary step to better understanding consequences of interventions and carefully orienting resources useful to build knowledge to improve public health.
Authors: Matthias Braubach; Myriam Tobollik; Pierpaolo Mudu; Rosemary Hiscock; Dimitris Chapizanis; Denis A Sarigiannis; Menno Keuken; Laura Perez; Marco Martuzzi Journal: Int J Environ Res Public Health Date: 2015-05-26 Impact factor: 3.390
Authors: Clive E Sabel; Rosemary Hiscock; Arja Asikainen; Jun Bi; Mike Depledge; Sef van den Elshout; Rainer Friedrich; Ganlin Huang; Fintan Hurley; Matti Jantunen; Spyros P Karakitsios; Menno Keuken; Simon Kingham; Periklis Kontoroupis; Nino Kuenzli; Miaomiao Liu; Marco Martuzzi; Katie Morton; Pierpaolo Mudu; Marjo Niittynen; Laura Perez; Denis Sarigiannis; Will Stahl-Timmins; Myriam Tobollik; Jouni Tuomisto; Saskia Willers Journal: Environ Health Date: 2016-03-08 Impact factor: 5.984
Authors: Ianis Delpla; Thierno Amadou Diallo; Michael Keeling; Olivier Bellefleur Journal: Int J Environ Res Public Health Date: 2021-03-04 Impact factor: 3.390