scholarly journals Prediction of Size Distribution and Mass Concentration of Smoke Particles on Moisture Content and Combustion Period from Para Rubber Wood Burning

2021 ◽  
Vol 11 (12) ◽  
pp. 5649
Author(s):  
Wachara Kalasee ◽  
Panya Dangwilailux
Keyword(s):  
Moisture Content ◽  
Size Distribution ◽  
Mass Concentration ◽  
High Volume ◽  
Temperature Data ◽  
Coefficient Of Determination ◽  
Wood Combustion ◽  
Wood Moisture ◽  
Smoke Particles ◽  
Rubber Wood

The size distribution and total particle mass concentration (TPMC) of smoke particles from para rubber wood (Hevea brasiliensis) combustion in the ribbed smoked sheet (RSS) process were studied. In this experiment, temperature data values of para rubber wood combustion were recorded at 500 mm above the base of the fire by K-type thermocouples. The wood moisture content and wood combustion period were used to find and improve an equation of smoke particle size distribution (SPSD) and TPMC by the response surface method (RSM). An eight-stage Andersen air sampler and a high-volume sampler were used to measure and calculate SPSD and TPMC, respectively. Resulting data in this experiment showed that TPMC ranged from 3.12 to 77.42 mg/m3. SPSD was single mode in which MMAD, mass median aerodynamic diameter, ranged from 0.64 to 1.27 microns for para wood with moisture content ranging from 31.5 to 89.7% dry weight basis. The combustion period and moisture content of para wood have a direct effect on the change of temperature data above the base of the fire and the TPMC and MMAD values. For predicting TPMC and MMAD values by the para wood moisture contents in each combustion period, the results found that the second-degree model was a better plot than the first-degree model, confirmed by higher values of the coefficient of determination (R2).

scholarly journals Physical Properties of Tobacco Smoke Particles Produced under Different Conditions

1984 ◽  
Vol 12 (3) ◽  
Author(s):  
Y. Ishizu ◽  
K. Ohta ◽  
H. Tomita
Keyword(s):  
Weight Loss ◽  
Particle Size ◽  
Size Distribution ◽  
Tobacco Smoke ◽  
Mass Concentration ◽  
Inert Gas ◽  
Small Samples ◽  
Size Distributions ◽  
Heating Rates ◽  
Smoke Particles

AbstractSmall samples of tobacco powder, prepared by grinding the dried tobacco leaves, were heated in a micro-thermo-balance in different atmospheres and at different heating rates. The size distribution and the mass concentration of the smoke particles produced were measured simultaneously with a laser particle counter and a piezo balance mass monitor. In addition, the change of weight loss with time was also measured during each experiment. It was found that a larger amount of smoke particles was produced when tobacco was heated in the atmosphere of inert gas and/or at higher heating rates. Furthermore, comparison of measured and calculated size distributions showed that the particle size distribution was governed mainly by coagulation.

scholarly journals Input-adaptive linear mixed-effects model for estimating alveolar Lung Deposited Surface Area (LDSA) using multipollutant datasets

2021 ◽  
Author(s):  
Pak Lun Fung ◽  
Martha A. Zaidan ◽  
Jarkko V. Niemi ◽  
Erkka Saukko ◽  
Hilkka Timonen ◽  
...  
Keyword(s):  
Size Distribution ◽  
Surface Area ◽  
Random Effects ◽  
Mass Concentration ◽  
Random Effect ◽  
Mixed Effects ◽  
Fixed Effect ◽  
Air Pollutant ◽  
Coefficient Of Determination ◽  
Lung Deposited Surface Area

Abstract. Lung deposited surface area (LDSA) has been considered to be a better metric to explain nanoparticle toxicity instead of the commonly used particulate mass concentration. LDSA concentrations can be obtained either by direct measurements or by calculation based on the empirical lung deposition model and measurements of particle size distribution. However, the LDSA or size distribution measurements are neither compulsory nor regulated by the government. As a result, LDSA data are often scarce spatially and temporally. In light of this, we develop a novel statistical model, named input-adaptive mixed-effects (IAME) model, to estimate LDSA based on other already existing measurements of air pollutant variables and meteorological conditions. During the measurement period in 2017–2018, we retrieved LDSA data measured by Pegasor AQ Urban and other variables at a street canyon (SC, average LDSA = 19.7 ± 11.3 μm2 cm−3) site and an urban background (UB, average LDSA = 11.2 ± 7.1 μm2 cm−3) site in Helsinki, Finland. For the continuous estimation of LDSA, IAME model is automatised to select the best combination of input variables, including a maximum of three fixed effect variables and three time indictors as random effect variables. Altogether, 696 sub-models were generated and ranked by the coefficient of determination (R2), mean absolute error (MAE) and centred root-mean-square differences (cRMSD) in order. At the SC site, the LDSA concentrations were best estimated by mass concentration of particle of diameters smaller than 2.5 μm (PM2.5), total particle number concentration (PNC) and black carbon (BC), all of which are closely connected with the vehicular emissions. At the UB site the LDSA concentrations were found to be correlated with PM2.5, BC and carbon monoxide (CO). The accuracy of the overall model was better at the SC site (R2 = 0.80, MAE = 3.7 μm2 cm−3) than at the UB site (R2 =  0.77, MAE = 2.3 μm2 cm−3) plausibly because the LDSA source was more tightly controlled by the close-by vehicular emission source. The results also demonstrate that the additional adjustment by taking random effects into account improves the sensitivity and the accuracy of the fixed effect model. Due to its adaptive input selection and inclusion of random effects, IAME could fill up missing data or even serve as a network of virtual sensors to complement the measurements at reference stations.

Examination of moisture content variation within an operational wet deck

TAPPI Journal ◽  
2013 ◽  
Vol 12 (1) ◽  
pp. 45-50 ◽  
Author(s):  
LAURENCE SCHIMLECK ◽  
KIM LOVE-MYERS ◽  
JOE SANDERS ◽  
HEATH RAYBON ◽  
RICHARD DANIELS ◽  
...  
Keyword(s):  
Moisture Content ◽  
Southeastern United States ◽  
Forest Products ◽  
Time Domain Reflectometry ◽  
Water Application ◽  
Wood Moisture ◽  
International Paper ◽  
Content Variation ◽  
Moisture Variation

Many forest products companies in the southeastern United States store large volumes of roundwood under wet storage. Log quality depends on maintaining a high and constant wood moisture content; however, limited knowledge exists regarding moisture variation within individual logs, and within wet decks as a whole, making it impossible to recommend appropriate water application strategies. To better understand moisture variation within a wet deck, time domain reflectometry (TDR) was used to monitor the moisture variation of 30 southern pine logs over an 11-week period for a wet deck at the International Paper McBean woodyard. Three 125 mm long TDR probes were inserted into each log (before the deck was built) at 3, 4.5, and 7.5 m from the butt. The position of each log within the stack was also recorded. Mixed-effects analysis of variance (ANOVA) was used to examine moisture variation over the study period. Moisture content varied within the log, while position within the stack was generally not significant. The performance of the TDR probes was consistent throughout the study, indicating that they would be suitable for long term (e.g., 12 months) monitoring.

Temporal change in wood quality attributes in standing dead beetle-killed lodgepole pine

2008 ◽  
Vol 84 (3) ◽  
pp. 392-400
Author(s):  
Steen Magnussen ◽  
Dave Harrison
Keyword(s):  
Moisture Content ◽  
Wood Quality ◽  
Basal Area ◽  
Wood Moisture ◽  
Moisture Regimes ◽  
Standing Dead ◽  
Blue Stain ◽  
Lodgepole Pines ◽  
Ring Analysis ◽  
One Year

The number and size of checks, wood moisture content, extent of blue-stain, rot and decay was examined by stem analysis in 360 mature standing beetle-killed lodgepole pines. Trees came from three areas (Burns Lake, Quesnel, and Vanderhoof) in Central British Columbia. Each area was represented by 14 to 16 sampling areas (stands) distributed evenly across three soil moisture regimes (dry, mesic, wet). Year of death was estimated from tree ring-analysis, local knowledge and insect and disease survey maps. An approximately equal number of trees had been dead for one or two years, three or four years, or for five or more years. During the first five years since death by beetle attack the number of checks per tree increased from 2.5 to 10.2 and the average depth of checks increased from 4.3 cm to 5.1 cm. Checks were deeper, wider, and longer on the drier sites than on mesic and wet sites. Moisture content of sapwood and heartwood was near the fibre saturation point (ca 30%) one year after death and continued to decrease at a rate of approximately 1.7% per year. Both the incidence and the extent (relative to basal area) of rot and decay increased significantly with time since death. All trees had an extensive blue-stain discoloration. Deterioration of wood quality was fastest during the first two years after a beetle attack. Key words: wood checks, moisture content, blue-stain, wood quality, spiral grain, bark beetle

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