Evidence map›Paper›PMID 27537903›Full record

ArticleInternational journal of environmental research and public health2016

A Well-Mixed Computational Model for Estimating Room Air Levels of Selected Constituents from E-Vapor Product Use.

Ali A Rostami, Yezdi B Pithawalla, Jianmin Liu, Michael J Oldham, Karl A Wagner, Kimberly Frost-Pineda, Mohamadi A Sarkar

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

7 authors at 1 institution in 1 country.

Ali A RostamiResearch, Development and Regulatory Affairs, Altria Client Services LLC, 601 East Jackson Street, Richmond, VA 23219, USA. Ali.A.Rostami@altria.com.
Yezdi B PithawallaResearch, Development and Regulatory Affairs, Altria Client Services LLC, 601 East Jackson Street, Richmond, VA 23219, USA. yezdi.b.pithawalla@altria.com.
Jianmin LiuResearch, Development and Regulatory Affairs, Altria Client Services LLC, 601 East Jackson Street, Richmond, VA 23219, USA. Jianmin.liu@altria.com.
Michael J OldhamResearch, Development and Regulatory Affairs, Altria Client Services LLC, 601 East Jackson Street, Richmond, VA 23219, USA. Michael.J.Oldham@altria.com.
Karl A WagnerResearch, Development and Regulatory Affairs, Altria Client Services LLC, 601 East Jackson Street, Richmond, VA 23219, USA. Karl.a.wagner@altria.com.
Kimberly Frost-PinedaResearch, Development and Regulatory Affairs, Altria Client Services LLC, 601 East Jackson Street, Richmond, VA 23219, USA. Kimberly.frost-pineda@altria.com.
Mohamadi A SarkarResearch, Development and Regulatory Affairs, Altria Client Services LLC, 601 East Jackson Street, Richmond, VA 23219, USA. Mohamadi.a.sarkar@altria.com.
Altria (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Concerns have been raised in the literature for the potential of secondhand exposure from e-vapor product (EVP) use. It would be difficult to experimentally determine the impact of various factors on secondhand exposure including, but not limited to, room characteristics (indoor space size, ventilation rate), device specifications (aerosol mass delivery, e-liquid composition), and use behavior (number of users and usage frequency). Therefore, a well-mixed computational model was developed to estimate the indoor levels of constituents from EVPs under a variety of conditions. The model is based on physical and thermodynamic interactions between aerosol, vapor, and air, similar to indoor air models referred to by the Environmental Protection Agency. The model results agree well with measured indoor air levels of nicotine from two sources: smoking machine-generated aerosol and aerosol exhaled from EVP use. Sensitivity analysis indicated that increasing air exchange rate reduces room air level of constituents, as more material is carried away. The effect of the amount of aerosol released into the space due to variability in exhalation was also evaluated. The model can estimate the room air level of constituents as a function of time, which may be used to assess the level of non-user exposure over time.

Indexed as

SmokingTobacco Smoke PollutionAerosolsAir Pollution, IndoorExhalationGasesHumansModels, StatisticalNicotineAerosolsGasesNicotineTobacco Smoke Pollutionaerosolcomputational modele-cigarettee-vapor productEVPexhaled breathindoor air qualitymodelingpassive vapingsecondhand exposure

Identifiers

PMID27537903
PMCPMC4997514
OpenAlexW2513886205

What OpenQuestion 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 OpenQuestion graph.