Evidence map›Paper›PMID 38058633›Full record

ArticleHeliyon2023

Spatial and socioeconomic characteristics of CO

Ainun Hasanah, Jing Wu

Abstract read
In one paragraph

Article in Heliyon, 2023. 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

2 authors.

Ainun HasanahDepartment of Urban and Rural Planning, School of Urban Design, Wuhan University, Wuhan, 430072, China.
Jing WuDepartment of Urban and Rural Planning, School of Urban Design, Wuhan University, Wuhan, 430072, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In dealing with the impacts of climate change, mitigation efforts play a crucial role. As one of the G20 countries on the list of the top 5 biggest contributors to emissions, Indonesia must play an active role. With all their characteristics and as one of the most significant contributors to global emissions, cities are fully responsible as a core area for climate mitigation. By analyzing the spatial and socioeconomic characteristics within the city scope, this study examines 32 representative cities and municipalities in Indonesia to understand the condition of carbon emissions and sequestration. Emissions and sequestration in selected cities in Indonesia show varying statuses; most cities have higher emission levels than sequestration, but some cities do the opposite. In addition, emissions and sequestration are also influenced by many complex and interrelated factors, including spatial (distribution, intensity, LULC, geographical conditions, total area), social (total population, urbanization rate, employment rate), economic (GDP/GRDP), and technological (industry structure and energy sector). As an archipelagic country, the uniqueness of cities in Indonesia, primarily located in coastal and waterfront areas, also influences the emission intensity, which tends to be lower in these areas on a micro basis. Cities classified as economically developed contribute more emissions at the national level. Therefore, a characteristic-based classification of the selected cities can encourage policy implications according to the characteristics of each city. These cities can learn from each other, especially from cities with high sequestration rates, to develop in a sustainable way while supporting national mitigation targets.

Indexed as

Carbon balanceClimate mitigationEmissionsSequestrationSpatial characteristics

Identifiers

PMID38058633
PMCPMC10696057

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.