Evidence map›Paper›PMID 36011951›Full record

ArticleInternational journal of environmental research and public health2022

A Novel Credible Carbon Footprint Traceability System for Low Carbon Economy Using Blockchain Technology.

Chunhua Ju, Zhonghua Shen, Fuguang Bao, Pengtong Weng, Yihang Xu, Chonghuan Xu

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. 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

6 authors.

Chunhua JuDepartment of Modern Business Research Center, Zhejiang Gongshang University, Hangzhou 310018, China.
Zhonghua ShenSchool of Management Engineering and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China.ORCID 0000-0003-1584-1307
Fuguang BaoDepartment of Modern Business Research Center, Zhejiang Gongshang University, Hangzhou 310018, China.
Pengtong WengSchool of Management Engineering and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China.
Yihang XuSchool of Management Engineering and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China.
Chonghuan XuAcademy of Zhejiang Culture Industry Innovation and Development, Zhejiang Gongshang University, Hangzhou 310018, China.ORCID 0000-0001-9757-1915

Funding

Contemporary Business and Trade Research Center of Zhejiang Gongshang University XT202103 and XT202105Natural Science Foundation of Zhejiang Province LQ20G010002project of China (Hangzhou) cross-border electricity business school 2021KXYJ06Soft Science Research Program of Zhejiang Province 2021C25010
6 · The paper itself

Abstract

To achieve the goal of carbon neutrality, many countries have established regional carbon emission trading markets and tried to build a low-carbon economic system. At present, the implementation of carbon emission trading and low-carbon economic systems faces many challenges such as manipulation, corruption, opacity, lack of trust, and lack of data tracking means. The application of blockchain technology can perfectly solve the above problems. However, the data recorded on a blockchain are often multi-type and heterogeneous, and users at different levels such as regulators, enterprises, and consumers have different requirements for data types and granularity. This requires a quick and trustworthy method for monitoring the carbon footprint of enterprises and products. In this paper, the carbon footprint traceability of enterprises and products is taken as an application scenario, and the distributed traceability concept of "traceability off the chain and verification on the chain" is adopted. By reconstructing the pointer of the file structure of the distributed storage, an interactive traceability structure supporting type filtering is constructed, which enables fast retrieval and locating of carbon emission data in the mixed data on the chain. The experimental results show that using the interactive traceability structure that supports type filtering for traceability not only releases the computing power of full nodes but also greatly improves the traceability efficiency of the long-span transaction chain. The proposed carbon footprint traceability system can rapidly trace and track data on an enterprise's and a product's carbon footprint, as well as meet the needs of users at all levels for traceability. It also offers more advantages when handling large amounts of data requests.

Indexed as

blockchaincarbon emission tradingcarbon footprintinteractive traceabilityIPFStraceability off the chaintype filtering

Identifiers

PMID36011951
PMCPMC9407757

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.