Literature DB >> 30055492

Long-term prediction of greenhouse gas risk to the Chinese hydropower reservoirs.

Amit Kumar1, Tao Yang2, M P Sharma3.   

Abstract

China is undergoing an extensive hydropower development, but the magnitude of greenhouse gas (GHG) emissions risk to reservoirs is not well known. Electricity generation from hydropower is a challenging issue when it comes to sustainable development. In this study, the data on Chinese hydropower reservoirs (n = 12) were collected from the literature and is used as in input to Greenhouse Gas Risk Assessment Tool (GRAT) to predict long-term GHG (CO2 &amp; CH4) risk to the hydropower reservoirs and its associated lifecycle GHG emissions (GHG-LCA). The model predicted that till recently (i.e., year 2018) the hydropower reservoirs found under medium risk (i.e., 109 < CO2 ≤ 628 and 3 < CH4 ≤ 45 mg·m-2·d-1) which will reduce slowly over a period of 100 years. Out of 12 hydropower reservoirs studied, TGR presently under high risk of CH4 (i.e., 47 mg·m-2·d-1) and medium CO2 risk. Therefore, assessment is required to know the magnitude of CH4 and its effect on regional climate so that mitigation measures could be taken in advance. The carbon emissions as CO2eq of the studied reservoirs are found as 134.69 ± 225.23 Gg yr-1, with a large share from CH4 emission. The associated life cycle GHG emissions are also estimated as 0.06 ± 0.09 gCO2eq·kWh-1, which is higher than the global estimates (i.e. 0.015 gCO2eq·kWh-1).
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Emission; GRAT; Greenhouse gas; Reservoir; Risk

Year:  2018        PMID: 30055492     DOI: 10.1016/j.scitotenv.2018.07.314

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


  1 in total

1.  Public Attitudes, Preferences and Willingness to Pay for River Ecosystem Services.

Authors:  Imran Khan; Hongdou Lei; Gaffar Ali; Shahid Ali; Minjuan Zhao
Journal:  Int J Environ Res Public Health       Date:  2019-10-01       Impact factor: 3.390

  1 in total

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