ArticleScientific reports2024
Assessment of the ecological and environmental effects of large-scale photovoltaic development in desert areas.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- A mosaic of microclimates: biodiversity outcomes and wildlife habitat potential in large-scale solar facilities.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Photovoltaic Microhabitats Reorganize Vegetation and Soil Carbon Pools in an Alpine Dryland Grassland.Biology · 2026Article
- Article
- Desert Physio-Ecological Adaptation ofPlants (Basel, Switzerland) · 2026Article
- Identifying the causal effects of photovoltaic installations on grassland productivity using double machine learning: a case study in inner Mongolia.Scientific reports · 2026Article
- Effects of Two Ecological Governance Measures for Photovoltaic Power Stations on Plant Growth and Soil Nutrients.Plants (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Photovoltaic development has played a crucial role in mitigating the energy crisis and addressing global climate change. However, it has also had significant impacts on the ecological environment. To ensure the sustainable growth of the photovoltaic industry, it is essential to establish an indicator system to assess the ecological and environmental effects of photovoltaic development. This study utilizes the Driving-Pressure-Status-Impact-Response (DPSIR) framework to create an indicator system for evaluating the ecological and environmental effects of desert photovoltaic development. The study evaluates the ecological and environmental effects at the on-site (WPS), transitional zone (TPS), and off-site (OPS) areas of the Qinghai Gonghe Photovoltaic Park in China. The entropy weight method was utilized to calculate indicator weights, while the evaluation model and indicators were transformed uniformly to obtain standardized scores for ecological and environmental effects. and conducting a thorough analysis of the distribution characteristics and factors influencing the evaluation indicators' scores. Overall, the large-scale development of desert photovoltaics in Gonghe County has had a positive impact on the ecological environment. The WPS had better ecological and environmental conditions than did the TPS and OPS, and the ecological and environmental evaluation levels of the WPS were categorized as "general" (0.439), while the ecological and environmental effect evaluation levels of the TPS (0.286) and OPS (0.28) were both "poor", indicating significant room for improvement. Moreover, all indicators in the scheme layer, which are used to evaluate ecological and environmental quality, yielded higher scores for the WPS than for the TPS and OPS, demonstrating that photovoltaic development has a positive effect on desert area ecology and the environment.
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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.