Particle number size distributions generated by different Korean pork cooking methods

Won, Soo Ran; Shim, In-Keun; Kwon, Myung-Hee; Ji, Hyun Ah; Park, Ki-soo; Ghim, Young Sung

doi:10.1007/s11869-020-00837-3

Cited by 3 publications

(2 citation statements)

References 19 publications

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Section: Resultsmentioning

confidence: 99%

“…Various studies support the findings of this work that the particle emissions during cooking heavily depend on the type of meal and preparation method. For example, frying generates more particles than boiling [15,48,49] The OPC-N3 built-in algorithm allows estimation of PM concentrations as a function of particle number concentration in corresponding particle diameter bins, with the assumption of an average particle density of 1.65 g/cm 3 . The PM values are determined according to European Standard EN 481.…”

Section: Daymentioning

confidence: 99%

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Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown

Kaliszewski

Włodarski

Młyńczak

et al. 2020

Sensors

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This study shows the results of air monitoring in high- and low-occupancy rooms using two combinations of sensors, AeroTrak8220(TSI)/OPC-N3 (AlphaSense, Great Notley, UK) and OPC-N3/PMS5003 (Plantower, Beijing, China), respectively. The tests were conducted in a flat in Warsaw during the restrictions imposed due to the COVID-19 lockdown. The results showed that OPC-N3 underestimates the PN (particle number concentration) by about 2–3 times compared to the AeroTrak8220. Subsequently, the OPC-N3 was compared with another low-cost sensor, the PMS5003. Both devices showed similar efficiency in PN estimation, whereas PM (particulate matter) concentration estimation differed significantly. Moreover, the relationship among the PM1–PM2.5–PM10 readings obtained with the PMS5003 appeared improbably linear regarding the natural indoor conditions. The correlation of PM concentrations obtained with the PMS5003 suggests an oversimplified calculation method of PM. The studies also demonstrated that PM1, PM2.5, and PM10 concentrations in the high- to low-occupancy rooms were about 3, 2, and 1.5 times, respectively. On the other hand, the use of an air purifier considerably reduced the PM concentrations to similar levels in both rooms. All the sensors showed that frying and toast-making were the major sources of particulate matter, about 10 times higher compared to average levels. Considerably lower particle levels were measured in the low-occupancy room.

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Section: Resultsmentioning

confidence: 99%