Evidence map›Paper›PMID 33594348›Full record

ArticleAtmospheric Environment: X2020

Indoor secondary organic aerosols: Towards an improved representation of their formation and composition in models.

M Kruza, G McFiggans, M S Waring, J R Wells, N Carslaw

Open access · greenAbstract read
In one paragraph

Article in Atmospheric Environment: X, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

5 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

5 authors at 4 institutions in 2 countries.

M KruzaDepartment of Environment and Geography, University of York, Wentworth Way, York, YO10 5NG, UK.
G McFiggansSchool of Earth and Environmental Sciences, University of Manchester, Manchester, UK.
M S WaringDepartment of Civil, Architectural and Environmental Engineering, Drexel University, Philadelphia, PA, USA.
J R WellsNational Institute for Occupational Safety and Health, Morgantown, WV, USA.
N CarslawDepartment of Environment and Geography, University of York, Wentworth Way, York, YO10 5NG, UK.
University of York · GBDrexel University · USNational Institute for Occupational Safety and Health · USUniversity of Manchester · GB

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

The formation of secondary organic aerosol (SOA) indoors is one of the many consequences of the rich and complex chemistry that occurs therein. Given particulate matter has well documented health effects, we need to understand the mechanism for SOA formation indoors and its resulting composition. This study evaluates some uncertainties that exist in quantifying gas-to-particle partitioning of SOA-forming compounds using an indoor detailed chemical model. In particular, we investigate the impacts of using different methods to estimate compound vapour pressures as well as simulating the formation of highly oxygenated organic molecules (HOM) via auto-oxidation on SOA formation indoors. Estimation of vapour pressures for 136 α-pinene oxidation species by six investigated methods led to standard deviations of 28-216%. Inclusion of HOM formation improved model performance across three of the six assessed vapour pressure estimation methods when comparing against experimental data, particularly when the NO

Indexed as

Highly oxygenated organic moleculesIndoor air chemistrySecondary organic aerosolVapour pressureVolatile organic compound

Identifiers

PMID33594348
PMCPMC7884095
OpenAlexW3047349210

What OpenQuestion holds

Textmetadata
LicenceTDM
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.