Evidence map›Paper›PMID 34855792›Full record

ArticlePloS one2021

A novel approach of creating sustainable urban planning solutions that optimise the local air quality and environmental equity in Helsinki, Finland: The CouSCOUS study protocol.

Joanne C Demmler, Ákos Gosztonyi, Yaxing Du, Matti Leinonen, Laura Ruotsalainen, Leena Järvi, Sanna Ala-Mantila

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Joanne C DemmlerFaculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.ORCID 0000-0002-4675-6271
Ákos GosztonyiFaculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.ORCID 0000-0002-5424-3732
Yaxing DuInstitute for Atmospheric and Earth System Research (INAR), University of Helsinki, Helsinki, Finland.
Matti LeinonenDepartment of Computer Science, University of Helsinki, Helsinki, Finland.
Laura RuotsalainenHelsinki Institute of Sustainability Science (HELSUS), University of Helsinki, Helsinki, Finland.
Leena JärviHelsinki Institute of Sustainability Science (HELSUS), University of Helsinki, Helsinki, Finland.
Sanna Ala-MantilaFaculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAir pollution is one of the major environmental challenges cities worldwide face today. Planning healthy environments for all future populations, whilst considering the ongoing demand for urbanisation and provisions needed to combat climate change, remains a difficult task.

objectiveTo combine artificial intelligence (AI), atmospheric and social sciences to provide urban planning solutions that optimise local air quality by applying novel methods and taking into consideration population structures and traffic flows.

methodsWe will use high-resolution spatial data and linked electronic population cohort for Helsinki Metropolitan Area (Finland) to model (a) population dynamics and urban inequality related to air pollution; (b) detailed aerosol dynamics, aerosol and gas-phase chemistry together with detailed flow characteristics; (c) high-resolution traffic flow addressing dynamical changes at the city environment, such as accidents, construction work and unexpected congestion. Finally, we will fuse the information resulting from these models into an optimal city planning model balancing air quality, comfort, accessibility and travelling efficiency.

Indexed as

Air PollutionAir PollutantsArtificial IntelligenceCity PlanningDatabases, FactualFinlandHumansModels, TheoreticalMotor VehiclesSustainable DevelopmentUrban PopulationAir Pollutants

Identifiers

PMID34855792
PMCPMC8638916

What Socratic 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 Socratic graph.