The greenhouse gas emissions, water consumption, and heat emissions of global steam-electric power production: a generating unit level analysis and database

Abstract

Steam-electric power dominates global electricity production. Mitigating its environmental burdens relies on quantifying them globally, on a high resolution. Here, with an unprecedented combination of detail and coverage, the Rankine cycle was individually modelled for >21 000 geocoded steam-electric generating units globally. Accounting for different cooling systems and fuels enabled the calculation of three major environmental stressors on a generating unit level. Geographical, chronological, and technological patterns are examined, as are trade-offs and improvement scenarios. Greenhouse gases (GHG) emissions from young (>2000) Chinese coal-fuelled generating units are equal to the sum of GHG emissions from all steam-electric power plants of all ages in the U.S. and Europe, and occupy 5% of all GHG emissions from the entire global economy. Twenty-four per cent of freshwater consumed from steam-electric power originates from nuclear power units from the 1970s/1980s, mainly in the U.S. and Europe. One per cent of steam-electric generating units is responsible for 50% of global heat emissions to freshwater. The median carbon intensity of Indian coal-fired units (≥50 MW) is 7%–16% higher than that in any other region globally. As concerns GHGs, technology-related efficiency differences (Rankine cycle, cooling system) play a small role compared to the fuel, which dominates the carbon intensity (GHGs/GJ el.). With the highest shares of cogeneration, 1 GJ electricity from tower-cooled coal units in Russia consumes on average 8%–49% less freshwater compared to respective units globally. There is a small margin for improvement based on alternative steam-electric technologies: retiring inefficient units and replacing their demand by ramping up more efficient ones with the same fuel, within the same country results in, respectively, ∼1%, 6%, and 11% fewer GHG emissions, freshwater consumption, and heat emissions globally. The full environmental benefits of completely retiring old units (<1970) consist of 9% fewer GHG emissions, 7% less freshwater consumed, and 18% fewer thermal emissions globally.

Water for energy: Characterizing co‐evolving energy and water systems under twin climate and energy system nonstationarities

“…Efforts have differed both in scope (e.g., electricity generation—Macknick, Newmark, et al, 2012; Peer & Sanders, 2016, 2018; Pfister et al, 2011; single fuel cycles—Klise et al, 2013; Nicot & Scanlon, 2012; Scanlon et al, 2014; Wu et al, 2014; or snapshots of energy systems—Gleick, 1994; Grubert & Sanders, 2018) and in categorization, with particular differences observed in the way that characterization studies have dealt with the fact that “water” is not fully descriptive of the resource in question (Boulay et al, 2011; Grubert et al, 2020). For example, choices to evaluate only freshwater (Raptis et al, 2020) versus multiple water qualities (Grubert & Sanders, 2018), and how those choices are described and justified, vary by study. One proposal for water categorization includes 17 separate categories (Boulay et al, 2011): high resolution is desirable but can be evasive in practice given water data quality constraints (Grubert et al, 2020; Perrone et al, 2015).…”

“…Note that the color scale differs between panels. In each panel, both size and color are used to illustrate the respective value of interest choices to evaluate only freshwater (Raptis et al, 2020) versus multiple water qualities (Grubert & Sanders, 2018), and how those choices are described and justified, vary by study. One proposal for water categorization includes 17 separate categories (Boulay et al, 2011): high resolution is desirable but can be evasive in practice given water data quality constraints (Grubert et al, 2020;Perrone et al, 2015).…”

“…The likely location, timing, source, quality, and alternative demands for water resources used for energy development pathways are at least directionally knowable due to practical constraints on energy infrastructure deployment, so scenarios can be developed with more specificity than volumetric water requirements alone. As such, water-for-energy requirements associated with energy transition deployment pathways represent an opportunity to develop and improve methods for evaluating spatiotemporally resolved environmental impacts under high uncertainty that could actively support decisions leading to path dependencies with serious potential consequences or opportunities for water management (Chini & Delorit, 2021;Peer et al, 2019;Peer & Sanders, 2018;Raptis et al, 2017Raptis et al, , 2020Tarroja et al, 2019Tarroja et al, , 2020. Success in this arena could also have longer term implications for sustainability assessment practice, as lessons learned from evaluating water for energy may be relevant to other noncarbon sustainability issues.…”

Globally Regionalized Monthly Life Cycle Impact Assessment of Particulate Matter

“…Case study data, source code for the model (R v3.6.0) (55), and characterization factor maps are available from http://dx.doi.org/10.17632/8jnj4vzbh6.1 (56). The case study data is fully compatible with the power plant data sets from (49,(57)(58)(59)(60).…”

“…The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.0c05691. Extended descriptions of methods and additional results including aggregated CFs for countries, provinces, ecoinvent regions, universal LCI-LCIA matching polygons from refs , , and the world; the case study data, the source code for the model (R v3.6.0), and characterization factor maps are available from ; and the case study data is fully compatible with the power plant data sets from refs , − (PDF) Supplementary Tables 1−16 (XLSX) …”