scholarly journals A scripted activity study of the impact of protective advice on personal exposure to ultra-fine and fine particulate matter and volatile organic compounds

2007 ◽  
Vol 18 (5) ◽  
pp. 495-502 ◽  
Author(s):  
David M Stieb ◽  
Gregory J Evans ◽  
Kelly Sabaliauskas ◽  
L I Chen ◽  
Monica E Campbell ◽  
...  
Sensors ◽  
2018 ◽  
Vol 18 (1) ◽  
pp. 265 ◽  
Author(s):  
Chee-Loon Ng ◽  
Fuu-Ming Kai ◽  
Ming-Hui Tee ◽  
Nicholas Tan ◽  
Harold Hemond

2018 ◽  
Vol 7 (1) ◽  
pp. 373-388 ◽  
Author(s):  
Alejandro Moreno-Rangel ◽  
Tim Sharpe ◽  
Filbert Musau ◽  
Gráinne McGill

Abstract. Measurements of temporal and spatial changes to indoor contaminant concentrations are vital to understanding pollution characteristics. Whilst scientific instruments provide high temporal resolution of indoor pollutants, their cost and complexity make them unfeasible for large-scale projects. Low-cost monitors offer an opportunity to collect high-density temporal and spatial data in a broader range of households. This paper presents a user study to assess the precision, accuracy, and usability of a low-cost indoor air quality monitor in a residential environment to collect data about the indoor pollution. Temperature, relative humidity, total volatile organic compounds (tVOC), carbon dioxide (CO2) equivalents, and fine particulate matter (PM2.5) data were measured with five low-cost (“Foobot”) monitors and were compared with data from other monitors reported to be scientifically validated. The study found a significant agreement between the instruments with regard to temperature, relative humidity, total volatile organic compounds, and fine particulate matter data. Foobot CO2 equivalent was found to provide misleading CO2 levels as indicators of ventilation. Calibration equations were derived for tVOC, CO2, and PM2.5 to improve sensors' accuracy. The data were analysed based on the percentage of time pollutant levels that exceeded WHO thresholds. The performance of low-cost monitors to measure total volatile organic compounds and particulate matter 2.5 µm has not been properly addressed. The findings suggest that Foobot is sufficiently accurate for identifying high pollutant exposures with potential health risks and for providing data at high granularity and good potential for user or scientific applications due to remote data retrieval. It may also be well suited to remote and larger-scale studies in quantifying exposure to pollutants.


2020 ◽  
Vol 4 (3) ◽  
pp. 001-012
Author(s):  
Ademu Tanko Ogah ◽  
Obaje Daniel Opaluwa ◽  
Mohammed Alkali ◽  
Kumo Lass

Anthropogenic activity especially coal mining contributes immensely to environmental pollution within coalmine and the host community especially if not well managed. This study is on the assessment of air quality in and around Maiganga coalmine, with the objectives of finding out the ambient concentration levels of criteria air pollutants within the coalmine, the Maiganga community and the four control sites 2km north, south, east and west of the coalmine, as well as compare the findings with the concentration levels of pollutants recommended as acceptable safety limits set by Federal Ministry of Environment, FMEnv. Six sampling locations were selected for detail assessment, with one point in each of the sites mentioned. Measurement of concentrations of criteria air pollutants; sulphur dioxide (SO2), nitrogen dioxide (NO2) volatile organic compounds (VOCs), carbon monoxide (CO), ammonia (NH3), and ozone (O3) were taken in-situ using Personal Toxic Gas Monitor (Tango TXI single gas monitor). Fine particulate matter (PM2.5), coarse particulate matter (PM10), were collected using a Portable Counter HT – 9601 (PM2.5 and PM10) personal dust meter high volume gravity sampler. Volatile organic compounds (VOCs) were also measured using a Portable Hand Held Gas Detector (Porcheck+). The study was done during the dry season and the results revealed that, coarse paticulate matter (PM10) was above the stipulated safety limit of 250µg/m3 set by the FMEnv for the coal mine area and Maiganga community but all other parameters were within the safety limits of the FMEnv. CO, NO2, SO2, and NH3 in coalmine area had concentrations lower than in that in control areas because of other anthropogenic activities like burning, heating, waste disposal, agricultural practices and a host of others taking place in the control area and which are not available in the coalmine area. However, the concentrations of the aforementioned parameters were higher in Maiganga community than in the control areas due to higher rate of anthropogenic activities in the community than in the control areas. The hypothesis were tested using student t – test, and the alternative hypothesis was accepted which showed there was no significant variations in the values of fine particulate matter (PM2.5), coarse particulate matter (PM10), sulphur dioxide (SO2), nitrogen dioxide (NO2), volatile organic compounds (VOCs), carbon monoxide (CO), ammonia (NH3), and ozone (O3) obtain from the coalmine, Maiganga community and the Control (N.S.E.W) with safety limits set by FMEnv. It is however, recommended that the Federal Ministry of Environment and National Environmental Standards and Regulations Enforcement Agency (NESREA) should ensure strict compliance with safety and environmental standards agreed upon during Environmental Impact Assessment (EIA).


Author(s):  
Jiyoung Shin ◽  
Jongmin Oh ◽  
In Sook Kang ◽  
Eunhee Ha ◽  
Wook Bum Pyun

Background/Aim: Previous studies have suggested that the short-term ambient air pollution and temperature are associated with myocardial infarction. In this study, we aimed to conduct a time-series analysis to assess the impact of fine particulate matter (PM2.5) and temperature on acute myocardial infarction (AMI) among adults over 20 years of age in Korea by using the data from the Korean National Health Information Database (KNHID). Methods: The daily data of 192,567 AMI cases in Seoul were collected from the nationwide, population-based KNHID from 2005 to 2014. The monitoring data of ambient PM2.5 from the Seoul Research Institute of Public Health and Environment were also collected. A generalized additive model (GAM) that allowed for a quasi-Poisson distribution was used to analyze the effects of PM2.5 and temperature on the incidence of AMI. Results: The models with PM2.5 lag structures of lag 0 and 2-day averages of lag 0 and 1 (lag 01) showed significant associations with AMI (Relative risk [RR]: 1.011, CI: 1.003–1.020 for lag 0, RR: 1.010, CI: 1.000–1.020 for lag 01) after adjusting the covariates. Stratification analysis conducted in the cold season (October–April) and the warm season (May–September) showed a significant lag 0 effect for AMI cases in the cold season only. Conclusions: In conclusion, acute exposure to PM2.5 was significantly associated with AMI morbidity at lag 0 in Seoul, Korea. This increased risk was also observed at low temperatures.


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