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Estimating health co-benefits of greenhouse gas reduction strategies with a simplified energy balance based model: The Suzhou City case

Authors :
Miaomiao Liu
Matti Jantunen
Xingyu Liu
Yining Huang
Zhou Jin
Jun Bi
Source :
Journal of Cleaner Production. 142:3332-3342
Publication Year :
2017
Publisher :
Elsevier BV, 2017.

Abstract

To translate scientific evidence into policy decisions, a universal, integrate and rapid–calculation model is needed for estimating the air quality associated health co–benefits of climate change mitigation strategies. This study developed such a greenhouse gas policy assessment model (GHG–PAM) based upon the annually published energy balances tables. To examine the applicability of this model, we select Suzhou, one of the national low-carbon pilot cities located in the east of China, as a case study. It was determined that carbon dioxide (CO2) emissions in Suzhou would increase from 148 million tons in 2010 to 297, 284, 180, and 173 million tons in 2020 under Business As Usual (BAU), Industrial Structure Dominated (ISD), Technology Dominated (TD), and Integrate Carbon Reduction (ICR) scenarios, of which only ICR scenario meets its carbon intensity target. Under the ICR scenario, the implementation of greenhouse gas policies reduces the air pollution associated burden of diseases, measured by Disability-Adjusted Life Years (DALY), by 44.1% in 2020 compared to BAU, although even with this scenario the burden of diseases would still be higher than that in 2010. In addition, the model can also identify sectors and industries with greater health co–benefits per unit CO2 emission reduction, which provides a useful guide for Suzhou's climate policy makers to formulate cost–effective measures. However, it should be carefully used where there is a mismatch between sectors with high potential for CO2 emission reductions and sectors with high health co–benefits per unit CO2 emission reduction.

Details

ISSN :
09596526
Volume :
142
Database :
OpenAIRE
Journal :
Journal of Cleaner Production
Accession number :
edsair.doi...........54987feddb874099afe80cd7f96532ed