Evidence map›Paper›PMID 41653340›Full record

ArticleCarbon balance and management2026

Differentiated carbon reduction effects of clean heating policies: evidence from pilot projects in Northern China.

Hongjie Ji, Handi Yang, Jintao Lu

Abstract read
In one paragraph

Article in Carbon balance and management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Hongjie JiSchool of Economics and Management, Shanxi University, Taiyuan, 030006, China.ORCID http://orcid.org/0009-0002-4721-2257
Handi YangSociology, St. Mary's College, Durham University, Durham, UK.ORCID http://orcid.org/0009-0005-8925-3040
Jintao LuSchool of Economics and Management, Shanxi University, Taiyuan, 030006, China. lut2002@163.com.ORCID http://orcid.org/0000-0001-9331-1411

Funding

National Social Science Foundation of China 20BJL105the 2025 Graduate Academic Innovation Project of Shanxi Province 2025XS007
6 · The paper itself

Abstract

As a far-reaching initiative in China's air pollution control and energy transition efforts, the clean heating policy has sparked considerable debate in both academia and practice regarding its effectiveness in reducing carbon emissions. This study uses panel data from 15 prefecture-level cities in northern China from 2013 to 2023 and constructs a multi-period difference-in-differences model to empirically examine the impact of the clean heating policy on regional carbon emissions. The results are summarized as follows: (1) The policy effectively promotes the reduction of regional unit GDP and per capita carbon emission intensity in Northern China, but it has no evident effect on regional total carbon emissions. (2) The policy can exert the multiplier effect of the central government funds and structural effect to facilitate regional low-carbon transformation, but no significant Porter effect has been observed. (3) The carbon reduction effects exhibit significant regional heterogeneity. The policy has a more significant effect on carbon emissions of nonprovincial capital cities, coal-resource cities, and regions without coal power output, but it may significantly increase emissions in coal power-exporting regions. The clean heating policy should continue to be vigorously implemented, but its implementation strategy should be optimized by strengthening the transmission mechanism and addressing regional differences.

Indexed as

Carbon emission reductionClean heatingMultiplier effectPorter effectStructural effect

Identifiers

PMID41653340
PMCPMC12977588

What OpenQuestion holds

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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.