Evidence map›Paper›PMID 35990172›Full record

ArticleInnovation (Cambridge (Mass.))2022

Navigating Chinese cities to achieve sustainable development goals by 2030.

Huijuan Xiao, Zhenci Xu, Jingzheng Ren, Ya Zhou, Ruojue Lin, Sheng Bao, Long Zhang, Shengfang Lu, Carman K M Lee, Jianguo Liu

Open access · goldAbstract read
In one paragraph

Article in Innovation (Cambridge (Mass.)), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
19.4field-weighted citation impact, top 1% of its field
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

9 citing papers in PubMed, 53 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Steep sustainability challenges in transboundary basins worldwide.Environmental science and ecotechnology · 2025
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. 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

10 authors at 4 institutions in 3 countries.

Huijuan XiaoDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Zhenci XuDepartment of Geography, The University of Hong Kong, Hong Kong SAR, China.
Jingzheng RenDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Ya ZhouKey Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou 510006, China.
Ruojue LinDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Sheng BaoOtto Poon C. F. Smart Cities Research Institute, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Long ZhangDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Shengfang LuDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Carman K M LeeDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Jianguo LiuCenter for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA.
Hong Kong Polytechnic University · HKMichigan State University · USSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou) · CNUniversity of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Achieving the 17 United Nations sustainable development goals (SDGs) in China largely depends on the transition of cities toward sustainable development. However, significant knowledge gaps exist in evaluating the SDG index at the city scale and in understanding how to simulate pathways to achieve the 17 SDGs for Chinese cities by 2030. This study aimed to quantify the SDG index of 285 Chinese cities and developed a forecasting model to simulate the performance of each SDG in each city until 2030 using varied scenarios. The results indicated that although the SDG index in Chinese cities increased by 33.97% during 2005-2016, Chinese cities, which continued their past paths, achieved an average of only five SDGs by 2030. To promote the joint achievement of all SDGs, we designed different paths for all SDGs of each of the 285 cities and simulated their SDG index until 2030. Under the scenarios, 216 Chinese cities (75.79%) could achieve 9-13 more SDGs in 2030 and the overall SDG index can improve from 74.57 in 2030 to 97.49 (target score 100) by adopting more intensive path adjustment. We lastly determined a cost-effective path for each SDG of each city to promote joint achievement of all SDGs by 2030. The proposed simulation model and cost-effective path serve as a foundation for other countries to simulate SDG progress and develop pathways for achieving SDGs in the future.

Identifiers

PMID35990172
PMCPMC9382565
OpenAlexW4285599931

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.