Evidence map›Paper›PMID 33802159›Full record

ArticleInternational journal of environmental research and public health2021

Eco-Efficiency of the English and Welsh Water Companies: A Cross Performance Assessment.

Ramon Sala-Garrido, Manuel Mocholi-Arce, Maria Molinos-Senante, Michail Smyrnakis, Alexandros Maziotis

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ramon Sala-GarridoDepartment of Mathematics for Economics, University of Valencia, 46010 Valencia, Spain.ORCID 0000-0002-4693-3944
Manuel Mocholi-ArceDepartment of Mathematics for Economics, University of Valencia, 46010 Valencia, Spain.ORCID 0000-0003-3574-503X
Maria Molinos-SenanteDepartamento de Ingeniería Hidráulica y Ambiental, Pontificia Universidad Católica de Chile, 4860 Santiago, Chile.
Michail SmyrnakisHartree Centre, Science and Technology Facility Council (STFC), Daresbury, Warrington WA4 4AD, UK.
Alexandros MaziotisDepartamento de Ingeniería Hidráulica y Ambiental, Pontificia Universidad Católica de Chile, 4860 Santiago, Chile.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analyzing costs and greenhouse gas (GHG) emissions could be of great importance for the water utilities to supply water services in a healthy and sustainable manner. In this study, we measured the eco-efficiency of several water utilities in England and Wales by incorporating GHG as an undesirable output. For the first time, we evaluated the eco-efficiency of the water production process using robust cross-efficiency data envelopment analysis (DEA) techniques. The further use of clustering and regression techniques allowed us to better understand the drivers of eco-efficiency. The results showed that the mean eco-efficiency of the water sector was 0.748, which indicates that costs and GHG emissions could be reduced by 25.2% to generate the same level of output. Large water companies with high energy costs and levels of GHG emissions belonged to the less eco-efficient group. Environmental factors related to density, topography, and treatment complexity further impacted eco-efficiency. Finally, we linked our results to the regulatory cycle and discuss some policy implications.

Indexed as

EfficiencyWaterEnglandGreenhouse EffectWalesWater SupplyWatercross eco-efficiencyEngland and Walesenvironmental variablesgreenhouse gas emissionswater utilities

Identifiers

PMID33802159
PMCPMC8001277

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.