Wyniki wyszukiwania - BazTech

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Effect of air pollution on visibility in urban conditions. Warsaw case study

Majewski G., Czechowski P O, Badyda A., Brandyk A.

Environment Protection Engineering

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2014

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Vol. 40, nr 2

47--64

EN

The influence of air pollutants on visibility in Warsaw Agglomeration has been investigated. Following pollutants were considered: PM10, SO2, NO2 and O3, while meteorological parameters included: air temperatures (mean, minimum, maximum), solar radiation, relative air humidity, rainfall rates and wind speed. Initial analyses were performed with the use of principal component analysis (PCA). In next stages, the logistic regression (LR), the analysis of variance (ANOVA), one-way classification and a model path of generalized regression models (GRM) were applied. PCA analysis showed that in the cold season the visibility index depends on PM10, SO2, NO2 and the temperatures: T, Tmin, and Tmax. In the warm season, the index of visibility is mostly shaped by four elements: O3, T, Tmax and solar radiation. Logistic regression model indicated that in the warm season only two variables are significantly related to visibility: PM10 and relative humidity of air. Regularities in the cold season shown by the LR correspond with the conclusions from the PCA. Among meteorological conditions, the most important is air temperature, but only Tmax preserves the same direction of influence as the one pointed by the PCA model.

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Ocena stężenia całkowitej rtęci gazowej (TGM) na terenie stacji tła regionalnego Granica-KPN (województwo mazowieckie, Polska) w latach 2010–2011

Majewski G., Czechowski P O, Badyda A., Kleniewska M., Brandyk A.

Rocznik Ochrona Środowiska

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2013

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Tom 15, cz. 2

1302--1317

EN

The study presents measurement results of the concentration of total gaseous mercury (TGM) in the atmospheric air of 2010–2011 coming from the only measurement station in the Mazovia Province, the Granica-KPN station (λE 20°27'20" φN 52°◦17'09.088"). A series of measurement results of mercury concentration was used to estimate the model which identifies the influence of chosen measurement results, both imission and meteorological ones, on concentrations of gaseous mercury in the atmospheric air. Due to the number of measurements limited to 2 years, the study made an attempt to perform an initial evaluation of seasonal factors. The analyses used included: the Principal Component Analysis (PCA) and a path for the Generalised Regression Model (GRM). Average concentration of TGM in 2010–2011 amounted to 1.52 ng m-3 which is very close to the background values obtained in other European countries. Seasonal dependence of TGM concentration was observed; in the cold half-year the TGM concentration was higher compared to the summer season. The obtained results of identifying the PCA and GRM models enable presenting the following synthetic, final conclusions: The employed models of PCA and GRM show that key factors which shape mercury concentration are the following: suspended dust PM10, gaseous pollutants: SO2 and NO2, and meteorological parameters: air temperature, relative humidity of air and solar radiation intensity. The index of the phenomenon, i.e. the first principal component, identifies this relationship as the strongest and most significant, but it is worth noting that there occurs inversely proportional influence of air temperature and solar radiation intensity. The GRM model shows the occurrence of seasonality in monthly periods and in total as an interaction of the year and the months, which is further confirmed in the PCA model through “distribution” of the effect of specific factors over successive principal components. Ozone, for instance, is connected with the first three components to a different degree (-0.6 with Component 1, 0.3 with Component 2 and 0.62 with Component 3) and not with the first or only one of the components. The PCA model is a linear relationship within each component separately and the relationships, being orthogonal to each other, account for successive parts of the total variance. The variables: ozone, wind velocity and atmospheric pressure are not related to the index of the phenomenon, i.e. to the first component. They are related to next principal components, which may prove a strong irregularity of the relationships or the occurrence of seasonality. To build the model, the study used data from a period of two years: 2010 and 2011. It does not give a sufficient number of observations for stable identification of seasonality (at least 5 repetitive periods) and further correlations of factors, i.e. successive principal components. Those components may indicate not so much the absence of measurement correlations with mercury, but a non-linear character or a strong dependence on various seasonal influences, such as yearly, seasonal or monthly fluctuations.

3

Data mining system for air quality monitoring networks

Czechowski P., Badyda A., Majewski G.

Archives of Environmental Protection

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2013

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Vol. 39, no. 4

123--147

EN

The use of quantitative methods, including stochastic and exploratory techniques in environmental studies does not seem to be sufficient in practical aspects. There is no comprehensive analytical system dedicated to this issue, as well as research regarding this subject. The aim of this study is to present the Eco Data Miner system, its idea, construction and implementation possibility to the existing environmental information systems. The methodological emphasis was placed on the one-dimensional data quality assessment issue in terms of using the proposed QAAH1 method - using harmonic model and robust estimators beside the classical tests of outlier values with their iterative expansions. The results received demonstrate both the complementarity of proposed classical methods solution as well as the fact that they allow for extending the range of applications significantly. The practical usefulness is also highly significant due to the high effectiveness and numerical efficiency as well as simplicity of using this new tool.

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Transport publiczny - zagrożenie czy szansa dla środowiska

Badyda A., Kraszewski A.

Transport Miejski i Regionalny

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2010

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nr 7-8

19--25

PL

Problemy transportu w miastach. Szanse i zagrożenia ze strony transportu publicznego dla środowiska. Analiza przeprowadzona w oparciu o model przyczynowo-skutkowy (siła sprawcza, presja, stan, skutek, reakcja).

EN

Some problems of transport in cities. The chances and threats caused by public transport for environment. The analysis elaborated basing on cause-and-effect model (driving force, pressure, state, mpact, response).

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Wpływ ruchu drogowego na poziom zanieczyszczeń powietrza oraz ryzyko chorób układu oddechowego. Cz. I - opis zależności poziomów zanieczyszczeń od natężenia ruchu i innych wybranych parametrów z wykorzystaniem modeli statystycznych

Badyda A.

Modelowanie Inżynierskie

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2009

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T. 6, nr 37

11-18

PL

W pracy przedstawiono wyniki pomiarów natężenia ruchu pojazdów w przekroju jednej z bardziej obciążonych ruchem arterii komunikacyjnych Warszawy oraz pomiarów monitoringu jakości powietrza i podstawowych parametrów meteorologicznych. W celu precyzyjnego wyjaśnienia mechanizmu powiązania stężeń zanieczyszczeń powietrza z natężeniem ruchu i czynnikami meteorologicznymi na podstawie zebranych danych wykonano modele regresji wielokrotnej.

EN

Paper presents the results of vehicles density measurement made across one of the busiest road in Warsaw, Poland and air quality monitoring results as well as selected meteorological parameters. Collected data were used to build the multiple regression models in order to explain precisely the mechanism of the interrelation between air pollutants concentration, traffic density and meteorological conditions.

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Wpływ ruchu drogowego na poziom zanieczyszczeń powietrza oraz ryzyko chorób układu oddechowego. Cz. II - zastosowanie modeli regresji logistycznej w ocenie ryzyka wystąpienia chorób układu oddechowego wskutek oddziaływania zanieczyszczeń komunikacyjnych

Badyda A.

Modelowanie Inżynierskie

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2009

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T. 6, nr 37

19-26

PL

Praca prezentuje wyniki badań sprawności wentylacyjnej płuc przeprowadzonych w latach 2005-2006 wśród mieszkańców jednej z silniej obciążonych ruchem ulic Warszawy, przy uwzględnieniu wyników grupy kontrolnej, którą stanowili mieszkańcy obszarów pozamiejskich o niskich poziomach zanieczyszczeń powietrza. Stosując modele regresji logistycznej, oszacowano również ryzyko zachorowania z powodu przewlekłej obturacyjnej choroby płuc (POChP) przy uwzględnieniu wybranych czynników.

EN

The article presents the pulmonary function test results made in 2005- 2006 among the inhabitants of one of the most busy roads in Warsaw, Poland. The results of tests made among rural area citizens (where the air pollutants concentrations were lower) were also taken into consideration. The rural area inhabitants were the control group. Using the logistic regression models, the risk of chronic obstructive pulmonary disease (COPD), taking selected factors into account, was also evaluated.

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Analiza zmienności stężenia zanieczyszczeń komunikacyjnych w aglomeracji miejskiej na tle natężenia ruchu pojazdów i warunków meteorologicznych

Badyda A., Majewski G.

Przegląd Naukowy Inżynieria i Kształtowanie Środowiska

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2006

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Vol. 15, No. 1

146--157

EN

This paper presents an analysis of the relationship between the traffic emissions concentration and the traffic flow changes measured in the cross-section of one of the thoroughfares in Warsaw (Poland). The changes in meteorological conditions were also taken into account. The habitation in the vicinity of communication arteries with a substantial traffic flow, causes the more significant exposure to the influence of air pollutants. This is confirmed with statistically significant higher pollutant concentrations registered at the air pollution monitoring station localized near the relatively busy thoroughfare in comparison with stations situated in a certain distance of the direct impact of vehicular traffic. Air pollutant concentrations are best explained by the following independent variables: in the summer period - traffic volume, wind velocity, temperature and solar radiation intensity; in the winter period - traffic volume, wind velocity, temperature, atmospheric precipitation quantity and for PM10 - relative humidity as well.

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Wykorzystanie własności wskaźnika dopasowania IGF w celu ograniczania liczby punktów opróbowania w cyklicznych kampaniach pomiarowych

Badyda A., Wawrzonek R., Zawadzki J.

Technika Poszukiwań Geologicznych

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2003

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R. 42, nr 3

41-52

PL

Jednym z zagadnień związanych z ochroną gleb jest problem wysokiej koncentracji metali ciężkich. Dane dotyczące stężeń tych pierwiastków w glebach uzyskuje się na drodze kampanii pomiarowych, obejmujących kosztowne analizy chemiczne. W Stanach Zjednoczonych planuje się objęcie corocznymi kampaniami pomiarowymi terenów o łącznej powierzchni 2 milionów km2, na których przewiduje się wykonywanie analiz 50 parametrów, w tym m.in. wskaźników jakości gleb. Łączne nakłady finansowe na objęcie badaniami tych terenów, przy założeniu gęstości próbkowania 1 próba na 10 km2, sięgnąć mogą kilkuset milionów USD rocznie. Na obszarach o dużej zmienności badanego zjawiska taka gęstość opróbowania będzie zdecydowanie za mała. Zwiększenie liczby punktów pomiarowych oznacza wzrost kosztów, a co za tym idzie niemożliwe będzie zrealizowanie niektórych planowanych badań, szczególnie w krajach uboższych. Ze względów ekonomicznych, zatem, konieczne staje się poszukiwanie metod, które pozwolą ograniczyć koszty badań. Artykuł prezentuje sposób ograniczenia liczebności zbioru punktów pomiarowych w kampaniach prowadzonych cyklicznie. Wykorzystanie metody krigingu, modelowania wariogramów oraz wskaźnika dopasowania Indicative Goodness of Fit (IGF), umożliwia zmniejszenie liczby punktów opróbowania w taki sposób, aby zachować odpowiednią jakość końcowych wyników. Na podstawie danych dotyczących stężenia Pb w glebach Warszawy i okolic zaprezentowano przykład praktycznego wykorzystania tej metody. Wyniki uzyskane w drodze przeprowadzonej analizy potwierdzają, iż metody geostatystyczne, oparte na modelowaniu wariogramów oraz własnościach wskaźnika dopasowania, są narzędziami, które umożliwiają odraniczenie liczby punktów pomiarowych w cyklicznie prowadzonych badaniach bez znacznego pogorszenia jakości otrzymanych wyników.

EN

One of the matters connected with soil protection is the problem of high concentration of heavy metals. Data concerning concentrations of these elements in soil are obtained during measurement campaigns, including costly chemical analysis. In the United States of America, it is planned to proceed with annual campaigns over the area of two million square kilometers. It is anticipated to perform analysis of 50 parameters on these terrains, including soil quality indicators. The total financial costs needed for these measurements, assuming that the sampling density will amount to one sample for ever 10 sq. km, could reach several hundreds million USDs per year. On terrains where the variability of measured phenomena is considerable, such sampling density will definitely be insufficient. Increasing the number of sampling points leads to increasing costs, and by extension it will be impossible to obtain some planned measurements, especially in poorer countries. When considering the economics, it will be necessary to search for methods that will reduce the costs measurements. This article presents the method of reducing the number of sample points in periodic measurement campaignes. Using the kriging method, variogram modeling and Indicative Goods of Fit (IGF) will decrease the number of sampling points so that the quality of the final results will be satisfied. Using data of the concentration of Pb in soil from Warsaw and its environs, an example of the practical using of these methods are presented. The results, received after the analysis, confirm that the geostatistical methods based on the variogram modeling and properties of IGF are good instruments which will allow a decrease in the number of sampling points in periodic research without large quality deterioration of the results.