Journal
ENVIRONMENTAL POLLUTION
Volume 223, Issue -, Pages 62-72Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.envpol.2016.12.031
Keywords
Co-benefits analysis; Scenario design; Transportation sector; PRD region
Categories
Funding
- National Natural Science Foundation of China [41401222]
- Natural Science Foundation of Guangdong Province NEA [2016A030313297]
- Guangdong Provincial Department of Science and Technology [2015B010110005]
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Vehicle emissions have become one of the key factors affecting the urban air quality and climate change in the Pearl River Delta (PRD) region, so it is important to design policies of emission reduction based on quantitative Co-benefits for air pollutants and greenhouse gas (GHG). Emissions of air pollutants and GHG by 2020 was predicted firstly based on the no-control scenario, and five vehicle emissions reduction scenarios were designed in view of the economy, technology and policy, whose emissions reduction were calculated. Then Co-benefits between air pollutants and GHG were quantitatively analyzed by the methods of coordinate system and cross-elasticity. Results show that the emissions reduction effects and the Co-benefits of different measures vary greatly in 2015-2020. If no control scheme was applied, most air pollutants and GHG would increase substantially by 20-64% by 2020, with the exception of CO, VOC and PM2.5. Different control measures had different reduction effects for single air pollutant and GHG. The worst reduction measure was Eliminating Motorcycles with average reducing rate 0.09% for air pollutants and GHG, while the rate from Updated Emission Standard was 41.74%. Eliminating Yellow label Vehicle scenario had an obvious reduction effect for every single pollutant in the earlier years, but Co-benefits would descent to zero in later by 2020. From the perspective of emission reductions and co-control effect, Updated Emission Standard scenario was best for reducing air pollutants and GHG substantially (tan alpha = 1.43 and Els = 1.77). (C) 2016 Elsevier Ltd. All rights reserved.
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