Literature DB >> 30245416

A comprehensive city-level GHGs inventory accounting quantitative estimation with an empirical case of Baoding.

Can Lu1, Wei Li2.   

Abstract

Cities represent a critical source and primary unit of Greenhouse Gas (GHG) emissions. The accurate emission accounts of cities provide robust and solid data support for further emission analysis as well as the local low-carbon policy making. Restricted by the data and method lacking, there is a relative lag in city-level emission accounts. Thus, this study attempts to build an investigation-based GHG emission inventory framework for cities. We include CO2, CH4, N2O, and SF6 emissions from five sources: energy activity, industrial processes/product use, agriculture, land use change/forestry, and waste disposal. This study then uses Baoding as a case study to analyse its emission characteristics. Baoding is a low-carbon pilot city in China, which is a core and crucial city in Jing-Jin-Ji area. It is also the origin of the recently established Xiongan New Area, which has great strategic development significance. The results show that energy activity is the highest emission source followed by waste disposal processes in Baoding. Emissions induced by electricity input that brought from other provinces or cities account for another considerable emission proportion as well. Moreover, agricultural activity, which is a pillar industry in Baoding, contributes the most to methane emissions. Several emissions reduction policy recommendations are provided.
Copyright © 2018. Published by Elsevier B.V.

Entities:  

Keywords:  Emission inventory; Energy activity; Greenhouse gases; Municipal waste treatment; Uncertainty analysis

Year:  2018        PMID: 30245416     DOI: 10.1016/j.scitotenv.2018.09.223

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Forecast and Analysis on Reducing China's CO₂ Emissions from Lime Industrial Process.

Authors:  Qing Tong; Sheng Zhou; Yuefeng Guo; Yang Zhang; Xinyang Wei
Journal:  Int J Environ Res Public Health       Date:  2019-02-11       Impact factor: 3.390

  1 in total

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