Models of Air Pollution Propagation in the Selected Region of Katowice

Foszcz, D.; Niedoba, Tomasz; Siewior, J.

doi:10.3390/atmos12060695

Cited by 5 publications

(4 citation statements)

References 29 publications

(30 reference statements)

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“…In Wrocław agglomeration, in addition to low emissions, pollutants of traffic origin still tend to dominate despite evolving mobility policies (Koczan 2021 ). In Katowice agglomeration, pollutants are primarily of industrial and municipal origins, where exceedances of standards are often encountered (Góra 2020 ), which leads to work on modelling and forecasting of pollution (Foszcz et al 2021 ). Thus, the complex problems and consequences of anthropogenic activities lead to the formation and movement of pollutants that vary in composition (Kowalska 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Seasonal toxicity of urban road dust in runoff process-studies in Poland

Rybak,

Ziembik,

Wróbel

et al. 2024

Environ Sci Pollut Res

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Urban road dust (URD) is one of the most important non-point sources of pollution in agglomerations. The aim of this study was to assess the seasonal toxic effects of URD runoff in two regions of Poland. The concentrations of elements in URD and leachate were studied. The impact of pollutants in URD runoff on water organisms was evaluated using Daphtoxkit F and Rotoxkit F (LC50). The acute toxicity tests for crustaceans and rotifers were selected as the response of these taxa reflects the impact on zooplankton, a key component of aquatic ecosystem and the basis of most food webs. The concentrations of elements were found to vary depending on the site, although URD samples collected in Katowice agglomeration (Upper Silesia) had higher values of elements (Mn, Cu, Zn, As) compared to Wrocław (Lower Silesia). The concentrations of Mn, Zn, As, Cr, and Mg in water-soluble fraction of URD were higher in summer and winter in the Upper Silesia region due to rainwater runoff resulting from traffic, industries, post-industrial waste, and the presence of old heating systems. When comparing the content of elements in the water-soluble fraction between seasons, Zn, As, Cr, and Al concentrations were slightly higher in winter. The highest mortality of Daphnia magna and Brachiouns calyciflorus was observed in URD from both agglomerations in winter. However, the mortality is likely due to the concentration of elements or/and the coexistence of an unknown compound or a synergistic effect of the studied elements. This study highlights the alarming seasonal sources of elements in URD runoff, which will directly enter the food chain and affect the entire ecosystem, and human health.

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Section: Introductionmentioning

confidence: 99%

Seasonal toxicity of urban road dust in runoff process-studies in Poland

Rybak,

Ziembik,

Wróbel

et al. 2024

Environ Sci Pollut Res

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“…The ability to anticipate the levels of PM 2.5 is crucial as it can guide the people in the area on how to avoid exposure to air pollutants. Many techniques, such as machine learning and regression models, have been used to study and forecast PM concentrations using air pollutants and meteorological data [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Statistical and Deep Learning Methods for Forecasting PM<sub>2.5</sub> Concentration in Northern Thailand

Wongrin¹,

Chaisee²,

Suphawan³

2023

Pol. J. Environ. Stud.

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This study applies statistical methods and deep learning techniques to forecast the daily average PM 2.5 concentration in northern Thailand, where the concentration is usually high and exceeds the safe level. The data used in the analysis are collected from January 2018 to December 2020 from 16 air monitoring stations. The statistical methods used are Holt-Winters exponential smoothing (ETS), autoregressive integrated moving average (ARIMA), and dynamic linear model (DLM). The deep learning techniques considered in this study are the recurrent neural network (RNN) and long-short term memory (LSTM). To compare the predictive performance of both methods, we use the root mean square error (RMSE). The result indicates that statistical methods, especially ARIMA, perform better than the deep learning techniques in most stations. Moreover, LSTM tends to provide higher accuracy than the RNN, especially with more number of nodes.

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“…One of the main environmental challenges, apart from GHG emissions (and their consequences), has been air pollution caused by mineral or anthropogenic particulates [1] which cause adverse effects on humans and the environment [2][3][4][5]. The types of air pollution with the most detrimental influence on people's health are: particulate matter (PM) [3,[5][6][7], nitrogen dioxide (NO 2 ), ozone (O 3 ) and sulphur dioxide (SO 2 ) [8][9][10][11]. Air pollution causes respiratory and circulatory problems and contributes to premature death [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Awareness of Air Pollution and Ecosystem Services Provided by Trees: The Case Study of Warsaw City

2021

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One of the consequences of the constant urban development in numerous countries is a growing concentration of air pollution, which adversely affects both the environment and people’s health. One of the ways of changing this negative trend is to maintain green areas and trees within cities, as they serve many ecosystem functions, including biological absorption of particles and other types of air pollution. This article provides the findings of a study carried out among the residents of Warsaw, the capital of Poland, in order to assess social awareness of air pollution and the importance of trees. The study of the residents’ awareness was supplemented with the assessment of the parameters of the trees’ capacity for pollution absorption in selected locations performed with the help of the i-Tree Eco tool, which allowed the authors to compare the residents’ impressions on the role of trees in the process of absorption of pollution with their actual potential. The analyses showed that the majority of city residents are concerned with the problem of air in the city, but at the same time failing to notice its negative impact on their health. The majority of respondents were not aware of the role the trees play in the process of pollution absorption, suggesting that there is a real need for raising social awareness of functions served by trees and green areas in urban spaces. The comparison of the city residents’ opinions on the importance of trees in the process of pollution absorption with objective data obtained with the help of i-Tree Eco tool shows that the majority of people’s impressions of pollution absorption by trees in urban areas is correct.

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Models of Air Pollution Propagation in the Selected Region of Katowice

Cited by 5 publications

References 29 publications

Seasonal toxicity of urban road dust in runoff process-studies in Poland

Seasonal toxicity of urban road dust in runoff process-studies in Poland

Comparison of Statistical and Deep Learning Methods for Forecasting PM<sub>2.5</sub> Concentration in Northern Thailand

Awareness of Air Pollution and Ecosystem Services Provided by Trees: The Case Study of Warsaw City

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