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The aim of this study is to evaluate time distribution of gaseous pollutants’ concentration levels, sulphur dioxide (SO₂, μg · m⁻³), nitrogen dioxide (NO₂, μg · m⁻³) and to characterise biothermal conditions, based on subjective temperature index (STI, °C) in Legnica, Lower Silesian Voivodeship. Assessment of the seasonal and daily SO₂ and NO₂ concentration and STI values in the studied period was based on descriptive statistics. The analysis of NO₂ and SO₂ concentration frequency was performed in reference to the scale applied in the interpretation of the STI. The assessment of the analysed period’s biothermal conditions did not show an occurrence of thermal sensation “boiling hot”. The most adverse aerosanitary conditions caused by high concentration of SO₂ in the air are accompanied by a sensation of “freezing”. The highest fluctuation in the content of NO₂ and SO₂ in the air was characteristic for the winter with the occurrence of “freezing” and “very cold” sensation. The highest concentration of SO₂ amounting to 234 μg ∙ m⁻³ was recorded in the winter of 2005 and highest NO₂ concentration was recorded in the spring of 2009, amounting to 184 μg ∙ m⁻³. The NO₂ and SO₂ concentration shows a reverse circadian course in comparison to the course of apparent temperature.
Emissions of gaseous and particulate pollutants of the air have given rise to a host of environmental problems on global, regional and local scales. Issues such as global warming, ozone layer depletion, acid deposition and urban air pollution have received considerable attention in recent years and have been the focus of major international research projects and collaborative monitoring programmes. In the last twenty years there has been a strong need for an integrated approach to air quality in urban and remote areas by developing environmental information technology. The most important international efforts in this field are presented in this review.
The main sources of pollution, related pollutants, their emission rates and ways of liberating indoor air are presented. Health symptoms in air spaces with different ventilation systems and risks associated with particular sources are compared. Also, different sampling and analytical techniques and source characterization methods are described. The advantages and shortcomings of the five basic approaches to indoor air monitoring are discussed. Special stress is put on passive samplers whose types theories and areas of application and newest designs are given.
Caring for indoor air quality (IAQ) in so-called non-industrial areas has become increasingly common. Because of people's awareness of hazards related to the presence of different substances in indoor air. A review with 103 references concerning the presence of organic compounds in non-industrial indoor environments is discussed. The main sources of indoor air pollutants are presented. Topics discussed also include: total volatile organic compounds (TVOC) concepts in IAQ evaluation, concentrations of organic compounds in indoor and outdoor air, and the influence of outdoor air on indoor air quality expressed as ratios of indoor (I) to outdoor (O) concentrations (I/O).
This paper presents the tasks, procedures and instrumental trends in analytics and monitoring of air pollution. The classification of methods and analytical techniques used for atmospheric air studies are also discussed.
In this study, artificial neural networks are proposed to predict the concentrations of S02 and PM at two different stations in Zonguldak city, a major coastal mining area in Turkey. The established artificial neural network models involve meteorological parameters and historical data on observed S02, PM as input variables. The models are based on a three-layer neural network trained by a back-propagation algorithm. The models accurately measure the trend of SO2 and PM concentrations. The results obtained through the proposed models show that artificial neural networks can efficiently be used in the analysis and prediction of air quality.
The article reports the results of an exploratory analysis of an air monitoring data set, collected at a monitoring station in the biggest, most congested and most polluted city of the silesian region, Katowice. In order to extract important information on air pollution in this city, the strategy of exploring the data set with missing elements and outliers simultaneously existing in the data was used. The strategy assumed the initial estimation of missing elements based on the application of robust Partial Least Squares (rPLS) and outli­ers identification based on the so-called robust distance. After outliers identification and replacing them with missing elements, the Expectation-Maximization iterative approach (built into Principal Component Analysis (PCA)) was used for the construction of the final model.
A permanent improvement in ambient air quality in the Urban Area of Katowice over recent years could have resulted in a decreased risk of air pollution-related daily mortality. Our study investigates the risk associated with the levels of PM₁₀ and SO₂, obtained seven years apart (time-series analyses in 1994-95 and 2001- 02). For both periods the acute mortality risk depends more on SO₂ than on PM₁₀ levels. The permanent improvement in ambient air pollution was associated with a decrease in relative risk of mortality, only for SO₂ levels. For example, the magnitude of the total mortality relative risk related to a 10 μg/m³ increase in pollutant’s concentration (a 3-day moving average) was for SO₂ 1.019 (1.015-1.023) in 1994-95 and 1.012 (1.005- 1.019) in 2001-02, and for PM₁₀ 1.007 (1.004-1.011) in 1994-95 and 1.007 (1.003-1.011) in 2001-02.
Airborne particulate matter (PM) is presently an environmental problem of primary concern, whose role in air quality, climatic and ecological issues is well recognized, though still a matter of extensive investigations (Intergovernmental Panel on Climate Change, 2007).It is of great scientific interest to detect sources of atmospheric particulate matter and quantify their influence on the global and local scales. Unfortunately, emissions are usually not directly available, while PM concentration time series are experimentally accessible, so that the problem often consists in "inverting" these data to determine the region of influence that caused the measured concentration. In this paper we are concerned with an alternative approach to inverse modeling based on backward trajectory analysis (BTA); this approach has the potential to overcome some limitations associated with traditional BTA.We apply this method to the analysis of PM time series from the Monte Cimone observatory, hereafter MCT, a high altitude station on the top of the Italian Northern Apennines, with the aim of estimate the contribution of Saharan dust transport on PM concentration levels registered in the Mediterranean region.
Life quality of humans, and their health in particular, are affected by a considerable number of factors, one of the most important of which is the condition of the environment. It is known that the quality of the environment affects the health status of the human population in about 15-20%. Air quality assessment is performed for pollutants that have limit values of air pollution (SO2, NO2, NOx, PM10 particles, Pb, CO, benzene), target levels for ozone, PM2,5 and precursor of ozone. After assessing the overall development of the measured emissions in the territory of the Slovak Republic as determined in the EMEP network (Environment Monitoring and Evaluation Programme) for the period of 2001-2007, we came to the conclusion that the limit values were not exceeded at any of the EMEP stations. The limit values that we used for comparison with measured emissions were in accordance with the decree of the Ministry of Environment on air quality, No. 705/2002.
Bioaerosols significantly influence indoor and outdoor air quality and may cause numerous allergies and diseases. Our study presents results of an evaluation of air quality in the forest recreation park in Myślęcinek. In the forest recreation park in Myślęcinek, microbiological air tests were conducted with the use of two methods of air sampling, namely the sedimentation method and the impaction method. The analysis indicate that mould fungi were the most abundant, constituting nearly 66% of all the microbial forms according to the sedimentation method, or 75% according to the impaction method. Heterotrophic bacteria were less numerous, making up to 32% of all microorganisms (the sedimentation method) or 24% (the impaction method). Actinomycetes and mannitol-positive staphylococci occurred in minimal concentrations. The highest count of microorganisms was recorded at Site V located on the verge of the forest near the tram terminus in Rekreacyjna Street, though staphylococci were the most abundant at Site I in the Polish Fauna Zoo Garden. The air was of high quality (containing the smallest number of microorganisms) at Site III located near Lake Myślęcińskie.
Two-dimensional variance analysis of the results of determination of NO₃⁻, SO₄²⁻, F⁻, Al³⁺, Cl⁻, NH₄⁺,PO₄³⁻, Fe³⁺, Ca²⁺, K⁺ and Mg²⁺, and pH and electrolytic conductivity of precipitation water samples collected in the Tricity area showed that transregional transport of pollutants affects air quality in this region. Over the large area of the Tricity agglomeration fluctuations in analyte concentrations in precipitation water samples are not affected on a statistically significant level by localizing sampling sites, but the area affected by transport direction of air mass movement.
Emission of sulphur compounds was absorbed from the atmosphere to an alkaline surface of a filter containing sodium carbonate in the region of Nitra - Malanta. Sulphates were determined by titration with ethanolic solution of Ba(C104)2. Results from January 1st - December 31st 1999 show that mean S02 concentrations at Nitra were 18.3 ug.m-3 S02 and 15.4 mg ■ m-2- d-1 SO2. The average (January 1st - December 31st 2000) value of area fallout was 11.6 mg m-2 d -1 S02 and the value of content concentration was 14.9 ug m-3 S02. The area fallout of emission of S is connected with the given meteorological situation (precipitation, average temperature, direction and speed of wind). The fact was confirmed by the results of our experiment.
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