Open AccessThe impact decades-long dependence on hydropower in El Niño impact-prone Zambia is having on carbon emissions through backup diesel generation
Author(s) -
Imaduddin Ahmed,
Priti Parikh,
Graham Sianjase,
D’Maris Coffman
Publication year - 2020
Publication title -
environmental research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.37
H-Index - 124
ISSN - 1748-9326
DOI - 10.1088/1748-9326/abb6a1
Subject(s) - greenhouse gas , diesel generator , hydropower , environmental science , electricity generation , backup , electricity , diesel fuel , computer science , database , automotive engineering , engineering , power (physics) , geology , physics , oceanography , electrical engineering , quantum mechanics
Emissions associated with hydropower are often forgotten. Lifecycle assessments of greenhouse gas emissions emanating from hydropower must count embedded carbon, emissions from reservoir lakes and the loss of carbon sinks, as well as backup diesel generation emissions when dependence on hydropower fails to deliver energy. Using Zambia as a case study, we estimate using a bottom-up approach that the emissions associated with backup diesel generation from Zambia’s power utility ZESCO and three largest sectors of consumers were up to 27 000 tonnes of C O 2 in the worst months of drought in 2019. This is significantly higher than what a previous top-down approach would have estimated. We worked out ZESCO’s diesel generation attributable to drought using trend analysis. We worked out the mining sector’s emissions using copper production data, on-grid electricity consumption and calculated electricity intensity to infer off-grid electricity consumption in years of drought. From our household survey we learned average duration of generator use, average capacities of generators and acquired household income and generator use data which we ran in a Tobit regression. These together with labour force survey data helped us infer the level of diesel generation by households of different income brackets. For manufacturing firms we surveyed 123 firms. We collected rich diesel generation use data covering years of drought, input this into an OLS regression to identify predictors of diesel generation use (installed capacity of generator in kVA, in litres and whether generation was in a drought year) which we then used to extrapolate implied diesel generation for the firms for which we had less rich data. As global average temperatures and the frequency of El Niño droughts rise in hydropower dependent countries which account for a fifth of the world’s population, backup generation emissions have implications for the formulation of low carbon energy policy.