JUSTIFICATION OF MAXIMUM (ONE-TIME) ALLOWABLE CONCENTRATION OF VOLATILE ORGANIC COMPOUNDS, EMERGING DURING THE HIGH TEMPERATURE TREATMENT OF WOOD IN CHIPBOARD PRODUCTION, IN THE AMBIENT AIR

2017 ◽  
pp. 42-47 ◽  
Author(s):  
O. V. Budarina ◽  
M. A. Pinigin ◽  
L. A. Fedotova ◽  
Z. F. Sabirova ◽  
Z. V. Shipulina
Keyword(s):  
High Temperature ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Experimental Studies ◽  
Ambient Air ◽  
High Temperature Treatment ◽  
Residential Areas ◽  
Atmospheric Air ◽  
Volatile Organic ◽  
High Temperature Processing

Results of experimental studies are reported on the substantiation of the maximum single permissible concentration (MAC maximum single) of volatile organic compounds, formed during a high temperature processing of wood in chipboard production (based on tererpene hydrocarbons), in the atmospheric air of residential areas at the level of 0.05 mg/m3. The magnitude was established on the basis of olfacto-odorimetry taking into account new approaches to the determination of «obsessive» odor thresholds as a limiting criterion for the MAC maximum single justification in accordance with the international practice of setting odor limits and our home experience gained in the standardization of odorous substances in the ambient air. The selection of priority substances for the control of the designed value (α-pinene, β-pinene, 3-carene, limonene, camphene) was based on the analysis results of the composition of releases from a high temperature processing of wood and atmospheric air in the enterprise location area.

scholarly journals Seasonal and Spatial Variation of Volatile Organic Compounds in Ambient Air of Almaty City, Kazakhstan

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1592
Author(s):  
Olga P. Ibragimova ◽  
Anara Omarova ◽  
Bauyrzhan Bukenov ◽  
Aray Zhakupbekova ◽  
Nassiba Baimatova
Keyword(s):  
Air Pollution ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Power Plants ◽  
Ambient Air ◽  
Spatial Variations ◽  
Primary Sources ◽  
Volatile Organic ◽  
Seasonal And Spatial Variations ◽  
Before And After

Air pollution is one of the primary sources of risk to human health in the world. In this study, seasonal and spatial variations of multiple volatile organic compounds (VOCs) were measured at six sampling sites in Almaty, Kazakhstan. The seasonal and spatial variations of 19 VOCs were evaluated in 2020, including the periods before and after COVID-19 lockdown. The concentrations of 9 out of 19 VOCs had been changed significantly (p < 0.01) during 2020. The maximum concentrations of total VOCs (TVOCs) were observed on 15, 17, and 19 January and ranged from 233 to 420 µg m−3. The spatial distribution of TVOCs concentrations in the air during sampling seasons correlated with the elevation and increased from southern to northern part of Almaty, where Combined Heat and Power Plants are located. The sources of air pollution by VOCs were studied by correlations analysis and BTEX ratios. The ranges of toluene to benzene ratio and benzene, toluene, and ethylbenzene demonstrated two primary sources of BTEX in 2020: traffic emissions and biomass/biofuel/coal burning. Most of m-, p-xylenes to ethylbenzene ratios in this study were lower than 3 in all sampling periods, evidencing the presence of aged air masses at studied sampling sites from remote sources.

scholarly journals Underway seawater and atmospheric measurements of volatile organic compounds in the Southern Ocean

2020 ◽  
Vol 17 (9) ◽  
pp. 2593-2619 ◽  
Author(s):  
Charel Wohl ◽  
Ian Brown ◽  
Vassilis Kitidis ◽  
Anna E. Jones ◽  
William T. Sturges ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Southern Ocean ◽  
Organic Compounds ◽  
Dimethyl Sulfide ◽  
Ambient Air ◽  
Atmospheric Measurements ◽  
Mixing Ratios ◽  
Volatile Organic ◽  
Air Mixing ◽  
Net Flux

Abstract. Dimethyl sulfide and volatile organic compounds (VOCs) are important for atmospheric chemistry. The emissions of biogenically derived organic gases, including dimethyl sulfide and especially isoprene, are not well constrained in the Southern Ocean. Due to a paucity of measurements, the role of the ocean in the atmospheric budgets of atmospheric methanol, acetone, and acetaldehyde is even more poorly known. In order to quantify the air–sea fluxes of these gases, we measured their seawater concentrations and air mixing ratios in the Atlantic sector of the Southern Ocean, along a ∼ 11 000 km long transect at approximately 60∘ S in February–April 2019. Concentrations, oceanic saturations, and estimated fluxes of five simultaneously sampled gases (dimethyl sulfide, isoprene, methanol, acetone, and acetaldehyde) are presented here. Campaign mean (±1σ) surface water concentrations of dimethyl sulfide, isoprene, methanol, acetone, and acetaldehyde were 2.60 (±3.94), 0.0133 (±0.0063), 67 (±35), 5.5 (±2.5), and 2.6 (±2.7) nmol dm−3 respectively. In this dataset, seawater isoprene and methanol concentrations correlated positively. Furthermore, seawater acetone, methanol, and isoprene concentrations were found to correlate negatively with the fugacity of carbon dioxide, possibly due to a common biological origin. Campaign mean (±1σ) air mixing ratios of dimethyl sulfide, isoprene, methanol, acetone, and acetaldehyde were 0.17 (±0.09), 0.053 (±0.034), 0.17 (±0.08), 0.081 (±0.031), and 0.049 (±0.040) ppbv. We observed diel changes in averaged acetaldehyde concentrations in seawater and ambient air (and to a lesser degree also for acetone and isoprene), which suggest light-driven production. Campaign mean (±1σ) fluxes of 4.3 (±7.4) µmol m−2 d−1 DMS and 0.028 (±0.021) µmol m−2 d−1 isoprene are determined where a positive flux indicates from the ocean to the atmosphere. Methanol was largely undersaturated in the surface ocean with a mean (±1σ) net flux of −2.4 (±4.7) µmol m−2 d−1, but it also had a few occasional episodes of outgassing. This section of the Southern Ocean was found to be a source and a sink for acetone and acetaldehyde this time of the year, depending on location, resulting in a mean net flux of −0.55 (±1.14) µmol m−2 d−1 for acetone and −0.28 (±1.22) µmol m−2 d−1 for acetaldehyde. The data collected here will be important for constraining the air–sea exchange, cycling, and atmospheric impact of these gases, especially over the Southern Ocean.

scholarly journals Target Analysis of Volatile Organic Compounds in Exhaled Breath for Lung Cancer Discrimination from Other Pulmonary Diseases and Healthy Persons

Metabolites ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 317
Author(s):  
Michalis Koureas ◽  
Paraskevi Kirgou ◽  
Grigoris Amoutzias ◽  
Christos Hadjichristodoulou ◽  
Konstantinos Gourgoulianis ◽  
...  
Keyword(s):  
Machine Learning ◽  
Computed Tomography ◽  
Lung Cancer ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Ambient Air ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
Healthy Controls ◽  
Volatile Organic

The aim of the present study was to investigate the ability of breath analysis to distinguish lung cancer (LC) patients from patients with other respiratory diseases and healthy people. The population sample consisted of 51 patients with confirmed LC, 38 patients with pathological computed tomography (CT) findings not diagnosed with LC, and 53 healthy controls. The concentrations of 19 volatile organic compounds (VOCs) were quantified in the exhaled breath of study participants by solid phase microextraction (SPME) of the VOCs and subsequent gas chromatography-mass spectrometry (GC-MS) analysis. Kruskal–Wallis and Mann–Whitney tests were used to identify significant differences between subgroups. Machine learning methods were used to determine the discriminant power of the method. Several compounds were found to differ significantly between LC patients and healthy controls. Strong associations were identified for 2-propanol, 1-propanol, toluene, ethylbenzene, and styrene (p-values < 0.001–0.006). These associations remained significant when ambient air concentrations were subtracted from breath concentrations. VOC levels were found to be affected by ambient air concentrations and a few by smoking status. The random forest machine learning algorithm achieved a correct classification of patients of 88.5% (area under the curve—AUC 0.94). However, none of the methods used achieved adequate discrimination between LC patients and patients with abnormal computed tomography (CT) findings. Biomarker sets, consisting mainly of the exogenous monoaromatic compounds and 1- and 2- propanol, adequately discriminated LC patients from healthy controls. The breath concentrations of these compounds may reflect the alterations in patient’s physiological and biochemical status and perhaps can be used as probes for the investigation of these statuses or normalization of patient-related factors in breath analysis.

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