Evidence map›Paper›PMID 37235218›Full record

ArticleToxics2023

Can Green-Technology Innovation Reduce Atmospheric Environmental Pollution?

Jingkun Zhou, Yunkai Zhou, Xu Bai

Abstract read
In one paragraph

Article in Toxics, 2023. 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.

Jingkun ZhouSchool of Business, Ludong University, 186 Hongqizhong Road, Yantai 264025, China.
Yunkai ZhouAdam Smith Business School, University of Glasgow, Glasgow G12 8QQ, UK.
Xu BaiSchool of Public Administration, Hebei University of Economics and Business, Shijiazhuang 050061, China.

Funding

The National Social Science Fund of China 20BGL193
6 · The paper itself

Abstract

Rapid economic growth leads to such problems as resource scarcity and environmental degradation. Local governments successively take measures such as technological innovation to solve atmospheric environmental pollution; however, technological innovation fails to fundamentally alleviate atmospheric environmental pollution. Therefore, local governments come to realize the importance of green-technology innovation, which means an inevitable choice for various countries in the world to seek long-term development and win competitive advantage. Under such circumstances, this paper chooses the panel data of 30 provinces and regions in China from 2005 to 2018, takes environmental regulation as the threshold variable, and empirically analyzes the relationship between green-technology innovation and atmospheric environmental pollution by constructing a Spatial Measurement Model and Panel Regression Model. As evinced, green-technology innovation has a significant inhibitory effect and a spatial spillover effect on atmospheric environmental pollution. When environmental regulation reaches a level of intensity, green-technology innovation can effectively curb atmospheric environmental pollution. Accordingly, relevant parties should strengthen green-technology innovation, coordinate the development of the governance system of green-technology innovation, establish a joint prevention and control mechanism, increase the investment in green technology research and development, and augment the role of green-technology innovation.

Indexed as

atmospheric environmental pollutiongreen-technology innovationspatial spillover effectthreshold characteristic

Identifiers

PMID37235218
PMCPMC10222100

What OpenQuestion holds

Textmetadata
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.