Investigation of Air Quality beside a Municipal Landfill: The Fate of Malodour Compounds as a Model VOC

This paper presents the results of an investigation on ambient air odour quality in the vicinity of a municipal landfill. The investigations were carried out during the spring–winter and the spring seasons using two types of the electronic nose instrument. The field olfactometers were employed to determine the mean odour concentration, which was from 2.1 to 32.2 ou/m3 depending on the measurement site and season of the year. In the case of the investigation performed with two types of the electronic nose, a classification of the ambient air samples with respect to the collection site was carried out using the k-nearest neighbours (kNN) algorithm supported with the cross-validation method. Correct classification of the ambient air samples collected during the spring–winter season was at the level from 71.9% to 87.5% and from 84.4% to 94.8% for the samples collected during the spring season depending on the electronic nose type utilized in the studies. It was also revealed that the kNN algorithm applied for classification of the samples exhibited better discrimination abilities than the algorithms of the linear discriminant analysis (LDA) and quadratic discriminant function (QDA) type. Performed seasonal investigations proved the ability of the electronic nose to discriminate the ambient air samples differing in odorants’ concentration and collection site

Investigation of Air Quality beside a Municipal Landfill: The Fate of Malodour Compounds as a Model VOC

This paper presents the results of an investigation on ambient air odour quality in the vicinity of a municipal landfill. The investigations were carried out during the spring–winter and the spring seasons using two types of the electronic nose instrument. The field olfactometers were employed to determine the mean odour concentration, which was from 2.1 to 32.2 ou/m3 depending on the measurement site and season of the year. In the case of the investigation performed with two types of the electronic nose, a classification of the ambient air samples with respect to the collection site was carried out using the k-nearest neighbours (kNN) algorithm supported with the cross-validation method. Correct classification of the ambient air samples collected during the spring–winter season was at the level from 71.9% to 87.5% and from 84.4% to 94.8% for the samples collected during the spring season depending on the electronic nose type utilized in the studies. It was also revealed that the kNN algorithm applied for classification of the samples exhibited better discrimination abilities than the algorithms of the linear discriminant analysis (LDA) and quadratic discriminant function (QDA) type. Performed seasonal investigations proved the ability of the electronic nose to discriminate the ambient air samples differing in odorants’ concentration and collection site

Określanie zawartości benzo(a)pirenu w PM10 za pomocą metod regresyjnych

The paper presents an attempt of application of multidimensional linear regression to estimation of an empirical model describing the factors influencing on B(a)P content in suspended dust PM10 in Olsztyn and Elbląg city regions between 2010 and 2013. During this period annual average concentration of B(a)P in PM10 exceeded the admissible level 1.5-3 times. Conducted investigations confirm that the reasons of B(a)P concentration increase are low-efficiency individual home heat stations or low-temperature heat sources, which are responsible for so-called low emission during heating period. Dependences between the following quantities were analysed: concentration of PM10 dust in air, air temperature, wind velocity, air humidity. A measure of model fitting to actual B(a)P concentration in PM10 was the coefficient of determination of the model. Application of multidimensional linear regression yielded the equations characterized by high values of the coefficient of determination of the model, especially during heating season. This parameter ranged from 0.54 to 0.80 during the analyzed period.W pracy przedstawiono próbę zastosowania wielowymiarowej regresji liniowej do szacowania empirycznego modelu opisującego czynniki wpływające na zawartość B(a)P w pyle zawieszonym PM10 na terenie Olsztyna i Elbląga w latach 2010-2013. W tym okresie średnioroczne stężenie B(a)P w pyle PM10 ponad 1,5-3 krotnie przewyższało poziom docelowy. Przeprowadzone badania potwierdziły, że główną przyczyną wzrostu stężenia jest nieefektywność domowych kotłowni czy niskotemperaturowych źródeł ciepła, które odpowiadają za tzw. niską emisję w okresie grzewczym. Analizie poddano wzajemne zależności: stężenia pyłu PM10 w powietrzu, temperaturę powietrza, prędkość wiatru, kierunek wiatru, wilgotność powietrza. Miarą dopasowania modelu do rzeczywistego stężenia B(a)P w PM10 był współczynnik determinacji modelu. Zastosowanie wielowymiarowej regresji liniowej, przyczyniło się do opracowania równań charakteryzujących się wysokimi wartościami współczynnika determinacji modelu zwłaszcza w okresie grzewczym. Parametr ten w analizowanym okresie był na poziomie od 0,54 do 0,80

Electronic nose – an instrument for odour nuisances monitoring

An increasingly frequent problem of people living in urban agglomerations is the occurrence of odour nuisance. Although the source of these nuisances is different, their common feature is that they are a complex mixture of odour compounds with different odour thresholds. However, from a practical point of view, the most valuable would be a direct link between the odour intensity and the results of on-line analytical air monitoring. Such a possibility is created by the use of electronic noses (devices that are supposed to imitate the human sense of smell) to measure odours. The paper presents the use of an electronic nose combined with multiple liear regression model (MLR) to determine the odour intensity of the two-component mixture samples of commonly known odour compounds: trimethylamine (TMA) and triethylamine (TEA) in concentration range 50–200 ppm v/v. The obtained results were compared with the theoretical values determined using Zwaardemaker and euclidean additivity (EA) models. For high concentrations of substances in the mixtures (> 150 ppm v/v), the masking effect was observed

Application of fuzzy logic to determine the odour intensity of model gas mixtures using electronic nose

The paper presents the possibility of application of fuzzy logic to determine the odour intensity of model, ternary gas mixtures (α-pinene, toluene and triethylamine) using electronic nose prototype. The results obtained using fuzzy logic algorithms were compared with the values obtained using multiple linear regression (MLR) model and sensory analysis. As the results of the studies, it was found the electronic nose prototype along with the fuzzy logic pattern recognition system can be successfully used to estimate the odour intensity of tested gas mixtures. The correctness of the results obtained using fuzzy logic was equal to 68%

Application of fuzzy logic to determine the odour intensity of model gas mixtures using electronic nose

The paper presents the possibility of application of fuzzy logic to determine the odour intensity of model, ternary gas mixtures (α-pinene, toluene and triethylamine) using electronic nose prototype. The results obtained using fuzzy logic algorithms were compared with the values obtained using multiple linear regression (MLR) model and sensory analysis. As the results of the studies, it was found the electronic nose prototype along with the fuzzy logic pattern recognition system can be successfully used to estimate the odour intensity of tested gas mixtures. The correctness of the results obtained using fuzzy logic was equal to 68%

Determination of Odour Interactions of Three-Component Gas Mixtures Using an Electronic Nose

The paper presents an application of an electronic nose prototype comprised of six TGS-type sensors and one PID-type sensor to identify odour interaction phenomena in odorous three-component mixtures. The investigation encompassed eight odorous mixtures—toluene-acetone-triethylamine and formaldehyde-butyric acid-pinene—characterized by different odour intensity and hedonic tone. A principal component regression (PCR) calibration model was used for evaluation of predicted odour intensity and hedonic tone. Correctness of identification of odour interactions in the odorous three-component mixtures was determined based on the results obtained with the electronic nose. The results indicated a level of 75–80% for odour intensity and 57–73% for hedonic tone. The average root mean square error of prediction amounted to 0.03–0.06 for odour intensity determination and 0.07–0.34 for hedonic tone evaluation of the odorous three-component mixtures

Evaluation of Health Hazard Due to Emission of Volatile Organic Compounds from Various Processing Units of Wastewater Treatment Plant

The paper describes an attempt at health risk assessment and odour concentration determination in the most important units of a wastewater treatment plant. The cancer risk (CR) and hazard index (HI) parameters in selected measurement locations were calculated based on the results of chromatographic analyses (GCxGC-TOF-MS) and the United States Environmental Protection Agency (US EPA) guidelines. No exceedance of the CR and HI acceptable levels was observed for identified and quantitatively determined compounds from the VOCs group. The acceptable level was exceeded for the summary HI parameter. Following a classification of the International Agency for Research on Cancer (IARC), it was noticed that the highest hazard was connected to the presence of formaldehyde belonging to group 1—the compounds regarded as carcinogenic. Based on the olfactometric analyses, it was estimated that the highest odour concentration, 37.2 ou/m3, occurred at the solid waste composting piles. It was also revealed that an increase in odour concentration corresponded to a higher health risk for employees of the wastewater treatment plant, due to exposure to volatile odorous compounds. Accordingly, this method of odour measurement can be a fast indicator describing health risk level

The applicability of low-cost PM10 sensors for atmospheric air quality monitoring

Described in this work are the results of field tests carried out in the Tricity Agglomeration between 01 April 2018 and 30 June 2018 in order to evaluate the usefulness of low-cost PM10 sensors in atmospheric air quality monitoring. The results were juxtaposed with the results obtained using reference methods. The results were validated based on the measurement uncertainty as described in the EU report "Demonstration of Equivalence of Ambient Air Monitoring Methods. EC Working Group on Guidance for the Demonstration of Equivalence". Moreover, the impact of external factors (humidity, pressure, temperature) on the obtained results was also assessed. It was shown that the low-cost sensors display measurement uncertainty which exceeds the acceptable values as compared to the reference methods and correction factors depending on the measured PM10 concentration need to be introduced in order to fulfil the criteria of equivalence

The applicability of low-cost PM10 sensors for atmospheric air quality monitoring

Described in this work are the results of field tests carried out in the Tricity Agglomeration between 01 April 2018 and 30 June 2018 in order to evaluate the usefulness of low-cost PM10 sensors in atmospheric air quality monitoring. The results were juxtaposed with the results obtained using reference methods. The results were validated based on the measurement uncertainty as described in the EU report "Demonstration of Equivalence of Ambient Air Monitoring Methods. EC Working Group on Guidance for the Demonstration of Equivalence". Moreover, the impact of external factors (humidity, pressure, temperature) on the obtained results was also assessed. It was shown that the low-cost sensors display measurement uncertainty which exceeds the acceptable values as compared to the reference methods and correction factors depending on the measured PM10 concentration need to be introduced in order to fulfil the criteria of equivalence