Evidence map›Paper›PMID 38332171›Full record

ArticleScientific reports2024

Exploring the relationship between land use/land cover and apparent temperature in China (1996-2020): implications for urban planning.

Han Ding, Qiuru Ren, Chengcheng Wang, Haitao Chen, Yuqiu Wang

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Han Ding *College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
Qiuru Ren *College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
Chengcheng WangCollege of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
Haitao ChenCollege of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
Yuqiu WangCollege of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China. yqwang@nankai.edu.cn.

Funding

National Water Pollution Control and Treatment Science and Technology Major Project 2017ZX07301-001National Water Pollution Control and Treatment Science and Technology Major Project 2017ZX07301-002
6 · The paper itself

Abstract

In recent decades, rising air temperatures (AT) and apparent temperatures (AP) have posed growing health risks. In the context of China's rapid urbanization and global climate change, it is crucial to understand the impact of urban land use/land cover (LULC) changes on AP. This study investigates the spatial distribution and long-term variation patterns of AT and AP, using data from 834 meteorological stations across China from 1996 to 2020. It also explores the relationship between AT, AP, and LULC in the urban core areas of 30 major cities. Study reveals that AT and AP exhibit overall high spatial similarity, albeit with greater spatial variance in AP. Notably, regions with significant disparities between the two have been identified. Furthermore, it's observed that the spatial range of high AP change rates is wider than that of AT. Moreover, the study suggests a potential bivariate quadratic function relationship between ΔT (the difference between AT and AP) and Wa_ratio and Ar_ratio, indicating the presence of a Least Suitable Curve (LSC), [Formula: see text]. Urban LULC planning should carefully avoid intersecting with this curve. These findings can provide valuable insights for urban LULC planning, ultimately enhancing the thermal comfort of urban residents.

Indexed as

Apparent temperatureLULC changeThermal comfortUrban planning

Identifiers

PMID38332171
PMCPMC10853208

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Registered trials

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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.