Evidence map›Paper›PMID 33499394›Full record

ArticleInternational journal of environmental research and public health2021

Contribution of Subway Expansions to Air Quality Improvement and the Corresponding Health Implications in Nanjing, China.

Meina Zheng, Xiucheng Guo, Feng Liu, Jiayan Shen

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

4 authors.

Meina ZhengJiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China.
Xiucheng GuoJiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China.
Feng LiuSchool of Economics and Management, Southeast University, Nanjing 210096, China.ORCID 0000-0002-9406-8625
Jiayan ShenJiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China.ORCID 0000-0002-0144-9067

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With China's rapid economic development, particularly its accelerated urbanization, air pollution has been one of the serious environmental issues across China. Most major cities in China expand their subway systems to handle this problem. This study takes both long- and short-term effects of subway expansions on air quality and its corresponding health implications into account based on a network density-based time series analysis and a distance-based difference-in-differences analysis. The daily and hourly monitor-level air quality data on Nanjing from 13 May 2014 to 31 December 2018, combining with corresponding weather variables, are used to quantify the effect of subway expansions on local air pollution caused by eight new subway lines in Nanjing. The results reveal that subway expansions result in a statistically significant decrease in the air pollution level; specifically, the air pollution level experiences a 3.93% larger reduction in the areas close to subway lines. Heterogeneous analysis of different air pollutants indicates that the air pollution reduction effect of subway expansions is more significant in terms of Particulate Matter (PM

Indexed as

Air PollutantsAir PollutionRailroadsChinaCitiesEnvironmental MonitoringParticulate MatterQuality ImprovementAir PollutantsParticulate Matterair pollutiondifference-in-differences analysisnetwork densitysubway

Identifiers

PMID33499394
PMCPMC7908424

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.