Literature DB >> 27741449

Spatio-temporal measurement of indoor particulate matter concentrations using a wireless network of low-cost sensors in households using solid fuels.

Sameer Patel1, Jiayu Li1, Apoorva Pandey1, Shamsh Pervez2, Rajan K Chakrabarty1, Pratim Biswas3.   

Abstract

Many households use solid fuels for cooking and heating purposes. There is currently a knowledge gap in our understanding of the variations in indoor air quality throughout the household as most of the studies focus on the areas in the close proximity of the cookstove. A low-cost wireless particulate matter (PM) sensor network was developed and deployed in households in Raipur, India to establish the spatio-temporal variation of PM concentrations. The data from multiple sensors were acquired in real-time with a wireless system. Data collected from the sensors agreed well (R2 =0.713) with the reference data collected from a commercially available instrument. Low spatial variability was observed within the kitchen due to its small size and poor ventilation - a common feature of most rural Indian kitchens. Due to insufficient ventilation from open doors and windows, high PM concentrations similar to those found in the kitchen were also found in the adjoining rooms. The same household showed significantly different post-extinguished cookstove PM concentration decay rates (0.26mg/m3-min and 0.87mg/m3-min) on different days, owing to varying natural air exchange rates (7.68m3/min and 37.40m3/min). Copyright Â
© 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cookstoves; Household air pollution; Indoor air quality; Low-cost instrumentation; Spatio-temporal PM(2.5)

Mesh:

Substances:

Year:  2016        PMID: 27741449     DOI: 10.1016/j.envres.2016.10.001

Source DB:  PubMed          Journal:  Environ Res        ISSN: 0013-9351            Impact factor:   6.498


  7 in total

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Review 2.  Towards Personalization of Indoor Air Quality: Review of Sensing Requirements and Field Deployments.

Authors:  Qian Xu; Hui Ci Goh; Ehsan Mousavi; Hamed Nabizadeh Rafsanjani; Zubin Varghese; Yogesh Pandit; Ali Ghahramani
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3.  Spatiotemporal Variations of Indoor PM2.5 Concentrations in Nanjing, China.

Authors:  Zhijuan Shao; Xiangjun Yin; Jun Bi; Zongwei Ma; Jinnan Wang
Journal:  Int J Environ Res Public Health       Date:  2019-01-07       Impact factor: 3.390

4.  Sensor Selection to Improve Estimates of Particulate Matter Concentration from a Low-Cost Network.

Authors:  Sinan Sousan; Alyson Gray; Christopher Zuidema; Larissa Stebounova; Geb Thomas; Kirsten Koehler; Thomas Peters
Journal:  Sensors (Basel)       Date:  2018-09-08       Impact factor: 3.576

5.  Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data.

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Journal:  Sensors (Basel)       Date:  2020-03-04       Impact factor: 3.576

6.  Indoor Carbon Dioxide, Fine Particulate Matter and Total Volatile Organic Compounds in Private Healthcare and Elderly Care Facilities.

Authors:  Alexandre Baudet; Estelle Baurès; Olivier Blanchard; Pierre Le Cann; Jean-Pierre Gangneux; Arnaud Florentin
Journal:  Toxics       Date:  2022-03-12

7.  Measuring Air Quality for Advocacy in Africa (MA3): Feasibility and Practicality of Longitudinal Ambient PM2.5 Measurement Using Low-Cost Sensors.

Authors:  Babatunde I Awokola; Gabriel Okello; Kevin J Mortimer; Christopher P Jewell; Annette Erhart; Sean Semple
Journal:  Int J Environ Res Public Health       Date:  2020-10-03       Impact factor: 3.390

  7 in total

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