ArticleScientific reports2025
The technological advancement environmental regulations and their impact on energy efficiency and CO
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 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
2 citing papers in PubMed.
- Study on urban passenger transport carbon reduction pathways based on system dynamics.Scientific reports · 2025Article
- Process Development for Hybrid Brake Pedals Using Compression Molding with Integrated In-Mold Assembly.Polymers · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
Abstract
Environmental rules and regulations are essential instruments the government administration uses to control environmental problems in this era of advanced technologies and smooth economic growth. This paper aims to examine how environmental regulations, both mandatory and incentive-based, impact on carbon dioxide (CO2) emissions in the presence of urbanization, foreign trade, economic growth and energy efficiency (EE) in logistics transportation. The influence of explicating factors on dependent variables, such as the highest, lowest, and mean, is estimated using the quantile regression model. We applied a number of econometric techniques like unit root test, panel co-integration, quantiles regression (CO2), quantiles regression (Energy efficiency), endogeneity test, and finally, we applied the robustness test to verify the results. This research uses quantile regression to estimate the influence of environmental regulations on releasing carbon dioxide and energy efficiency, using panel data of China's thirty provinces from 2005 to 2019. Environmental policies in the Ningxia, Qinghai, and Hainan provinces impose higher pollution penalties, which significantly impact reducing CO2 emissions. These regions release more environmental regulations, and in the provinces that fall between the 25th and 50th percentiles, mandatory environmental regulations significantly lower CO2 emissions. Incentive environmental regulations regarding the environment have a more significant effect on energy efficiency in the 50th-75th, 75th-90th, and higher 90th percentile groups since these groups have made more significant investments in research and development. Meanwhile, the Yunnan, Heilongjiang, and Xinjiang provinces have higher energy efficiency levels due to mandatory environmental legislation. The results provide the correct information to the government to implement effective environmental regulations to achieve sustainable development goals.
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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.