Evidence map›Paper›PMID 36474671›Full record

ArticleAtmospheric pollution research2022

Lessons learnt for air pollution mitigation policies from the COVID-19 pandemic: The Italian perspective.

Massimo D'Isidoro, Ilaria D'Elia, Lina Vitali, Gino Briganti, Andrea Cappelletti, Antonio Piersanti, Sandro Finardi, Giuseppe Calori, Nicola Pepe, Alessandro Di Giosa and 2 more

Open access · greenAbstract read
In one paragraph

Article in Atmospheric pollution research, 2022. 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
0.8field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. Response of PMEnvironmental pollution (Barking, Essex : 1987) · 2023
    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

12 authors at 2 institutions in 2 countries.

Massimo D'IsidoroENEA - Italian Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy.
Ilaria D'EliaENEA - Italian Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy.
Lina VitaliENEA - Italian Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy.
Gino BrigantiENEA - Italian Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy.
Andrea CappellettiENEA - Italian Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy.
Antonio PiersantiENEA - Italian Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy.
Sandro FinardiArianet s.r.l., Milano, Italy.
Giuseppe CaloriArianet s.r.l., Milano, Italy.
Nicola PepeArianet s.r.l., Milano, Italy.
Alessandro Di GiosaARPA-Lazio Environmental Protection Agency of the Lazio Region, Rome, Italy.
Andrea BolignanoARPA-Lazio Environmental Protection Agency of the Lazio Region, Rome, Italy.
Gabriele ZaniniENEA - Italian Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy.
National Agency for New Technologies, Energy and Sustainable Economic Development · ITAgenzia Regionale per la Protezione Ambientale del Piemonte · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Policies to improve air quality need to be based on effective plans for reducing anthropogenic emissions. In 2020, the outbreak of COVID-19 pandemic resulted in significant reductions of anthropogenic pollutant emissions, offering an unexpected opportunity to observe their consequences on ambient concentrations. Taking the national lockdown occurred in Italy between March and May 2020 as a case study, this work tries to infer if and what lessons may be learnt concerning the impact of emission reduction policies on air quality. Variations of NO

Indexed as

Air pollutionAir quality modellingAir quality policiesCOVID-19Lockdown

Identifiers

PMID36474671
PMCPMC9716127
OpenAlexW4311989206

What OpenQuestion holds

Textmetadata
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.