Evidence map›Paper›PMID 38409508›Full record

ArticleEnvironmental monitoring and assessment2024

Carbon emission change based on land use in Gansu Province.

Wei Wei, Yuanyuan Li, Libang Ma, Binbin Xie, Ruijun Hao, Dibo Chen, Shilong Yang

Abstract read
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Article in Environmental monitoring and assessment, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Wei WeiCollege of Geography and Environmental Science, Northwest Normal University, 967 Anning East Road, Lanzhou, 730070, Gansu, China.
Yuanyuan LiCollege of Geography and Environmental Science, Northwest Normal University, 967 Anning East Road, Lanzhou, 730070, Gansu, China. Lyy01206@163.com.
Libang MaCollege of Geography and Environmental Science, Northwest Normal University, 967 Anning East Road, Lanzhou, 730070, Gansu, China.
Binbin XieSchool of Urban Management, Lanzhou City University, Lanzhou, 730070, Gansu, China.
Ruijun HaoCollege of Geography and Environmental Science, Northwest Normal University, 967 Anning East Road, Lanzhou, 730070, Gansu, China.
Dibo ChenCollege of Geography and Environmental Science, Northwest Normal University, 967 Anning East Road, Lanzhou, 730070, Gansu, China.
Shilong YangCollege of Geography and Environmental Science, Northwest Normal University, 967 Anning East Road, Lanzhou, 730070, Gansu, China.

Funding

National Natural Science Foundation of China 42261023Natural Science Foundation of Gansu Province 23JRRA713
6 · The paper itself

Abstract

Carbon emissions from land use change have become one of the main sources of regional carbon emissions. In order to explore the changes, 87 districts and counties in Gansu Province are taken as research objects. Based on the remote sensing data and statistical data of land use, the carbon emission coefficient method was used to investigate the spatial characteristics of land use carbon emission of each district and county in Gansu Province in recent 20 years from the perspective of carbon ecological support coefficient and per capita carbon footprint. The main results are as follows: (1) the growth of land use carbon emissions in Gansu Province from 2000 to 2020 was significant, but the growth of carbon emissions after 2010 was fast, and the growth of carbon sinks was relatively slow. (2) The ecological support coefficient of carbon emissions at county level in Gansu Province showed a trend of high in the south and low in the north, high in the east and low in the west, and this trend became more and more obvious with the passage of time. (3) Based on carbon emission, county population, and carbon ecological support capacity, the per capita carbon footprint of each county in Gansu Province was analyzed. The results showed that the per capita carbon footprint in Gansu Province was increasing, indicating that the gap between carbon emission and carbon absorption in each county was widening. By the above result, the author divides the counties of Gansu Province into three regions, low-carbon maintenance area, green development area, and ecological optimization area, and puts forward development suggestions for different regions, respectively. Therefore, this paper can also provide a theoretical reference for the formulation of carbon neutral planning measures in inland northwest China.

Indexed as

CarbonEnvironmental MonitoringCarbon DioxideCarbon FootprintCarbon SequestrationChinaEconomic DevelopmentCarbonCarbon DioxideCarbon emission analysisGansu Province, ChinaLand use carbon emission

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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.