ArticlePloS one2024
What drives water conservation in the supply chain of the Yellow River Basin? An empirical analysis based on SPD.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Industrial water saving is an objective requirement for the high-quality development of the Yellow River Basin, as water resource is the largest rigid constraint. In this study, water resources input-output model, structural decomposition analysis (SDA) and structural path analysis (SPA) were constructed to decompose the driving factors of total water use in typical water-deficient provinces (Ningxia, Shanxi, and Henan) in China's Yellow River Basin, to calculate their water use at each production stage and identify their key water-saving pathways. The results were as follows: (i) Water intensity had the most obvious impact on total water saving, resulting in efficiency improvements of 81.39%, 9.21%, and 78.45% for each province, respectively. The next factor was the final demand structure, which suppressed total water-saving efforts by 24.23%, 11.52%, and 113.12% in the respective provinces. (ii) The key water-saving paths in the typical water-deficient provinces of the Yellow River Basin were primarily centered around Sector 1. (iii) Water intensity had a strong water-saving effect on the key paths in the three provinces, with contribution rates of 100.42%, 59.02%, and 42.34% for Ningxia, Henan, and Shanxi, respectively. Final demand also contributed to water-saving in the key paths of Shanxi and Henan, with contribution rates of 35.06% and 28.23%, respectively. However, it inhibited water-saving efforts in the key paths of Ningxia, reducing it by 8.64%. Policy measures should be tailored to local conditions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.