ArticleEnvironmental science and pollution research international2022
Impact of uncertainty on regional carbon peak paths: an analysis based on carbon emissions accounting, modeling, and driving factors.
Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 22 citations in OpenAlex.
- Carbon emission effects of land use change in Nanchang, West of Central China Region.Scientific reports · 2025Article
- Influencing factors and trend prediction of PMEnvironment, development and sustainability · 2022Article
- Spatio-Temporal Effects of Multi-Dimensional Urbanization on Carbon Emission Efficiency: Analysis Based on Panel Data of 283 Cities in China.International journal of environmental research and public health · 2021Article
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 at 2 institutions in 1 country.
Funding
Abstract
Regional carbon emission paths have an important impact on the realization of China's carbon emission peak target. Due to the uncertainty of future development model, the change of carbon emissions will also face uncertainty, which will make achieving the peak target challenging. Taking Shandong, Henan, and Guangdong, three of China's most populous provinces, as examples, this study analyzed the impacts of uncertainties in carbon accounting principles, driving factors, and simulation mechanism on achieving the peak target. The results show that (1) under the baseline scenario, the accounting principles based on primary energy consumption and IPCC sector consumption will make the peaking time of Guangdong be evaluated as 2018 and 2030, respectively, and the simulation based on IPCC sector accounting will advance the peaking time of Shandong by at least 5 years, while Henan will be less affected. (2) When considering the impact of the energy structure, Guangdong and Henan are estimated to peak in 2011 and 2018, while without considering the impact of the energy structure, the peak in the two provinces may be after 2035. Energy structure has no effect on the estimation of peaking time for Shandong. In addition, the k value in the ridge regression method also has no effect on the peaking time for the three provinces; it only affects the simulations of annual carbon emissions. This study also presented the carbon emission trajectory under different scenarios; from the simulation results, environmental regulation measures such as accelerating industrial structure transformation and increasing energy consumption intensity may help to achieve the peak carbon emission target as soon as possible. It also suggests that uncertainty should be included in future carbon assessments to present a more complete carbon emission trajectory.
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.