Evidence map›Paper›PMID 40218673›Full record

ArticleSensors (Basel, Switzerland)2025

A Fuzzy-Based Model to Detect Hotspots of Air Pollutants During Heatwaves in Urban Settlements.

Barbara Cardone, Ferdinando Di Martino, Cristiano Mauriello, Vittorio Miraglia

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Barbara CardoneDepartment of Architecture, University of Naples Federico II, Via Toledo 402, 80134 Napoli, Italy.ORCID 0000-0002-9844-9513
Ferdinando Di MartinoDepartment of Architecture, University of Naples Federico II, Via Toledo 402, 80134 Napoli, Italy.ORCID 0000-0001-5690-5384
Cristiano MaurielloDepartment of Architecture, University of Naples Federico II, Via Toledo 402, 80134 Napoli, Italy.
Vittorio MiragliaDepartment of Architecture, University of Naples Federico II, Via Toledo 402, 80134 Napoli, Italy.ORCID 0009-0005-1817-4142

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High concentrations of pollutants in urban areas generate cardiovascular and respiratory problems in citizens; these are aggravated by the persistence of summer heatwaves. For this reason, in this research, we propose a fuzzy-based method for detecting air pollutant hotspots and determining critical urban areas for air pollution during heatwaves. After acquiring the pollutant concentration values recorded by monitoring stations during heatwaves, a spatial interpolation method is applied to obtain the distribution of the pollutant concentration during heatwaves and, subsequently, a fuzzification process is performed to determine urban hotspots in which the pollutant concentration assumes critical values. Finally, the critical urban areas are determined, consisting of the areas within hotspots with a high population density exposed to health risks. The method was implemented in a GIS platform and tested on an urban study area in the Lombardy region, Italy, to determine the urban areas with high criticality during the heatwaves that occurred in the summer months of 2024. The test results show that the method can provide valid support for decision makers and local administrators when evaluating which urban areas are most critical for the population due to the high rate of air pollution during heatwaves.

Indexed as

Air PollutantsAir PollutionEnvironmental MonitoringCitiesFuzzy LogicHot TemperatureHumansItalySeasonsAir Pollutantsair pollutionfuzzy partitionheatwavehotspotspatial interpolation

Identifiers

PMID40218673
PMCPMC11990986

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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.