The effect of gender and age structure on municipal waste generation in Poland

Tałałaj, Izabela Anna; Walery, Maria

doi:10.1016/j.wasman.2015.03.020

Cited by 40 publications

(31 citation statements)

References 20 publications

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“…For the purpose of waste production analysis, the data of waste amount produced per person per day in kilograms were tested to find if there was a relationship between the mentioned variable and people's age, origin, and sex. Whereas according to [18] and their study in Poland waste quantity is influenced by gender and age structure, our research revealed no statistically provable relationship between the amount of waste produced and a respondent's sex. The same applies to respondent's origin, even though there exist studies like the one from [19], which claims that people from rural areas produce less waste than people living in a city.…”

Section: Resultscontrasting

confidence: 79%

An Analysis of Waste Management in the Republic of Moldova: A Comparison of Rural and Urban Areas

Procházková

Ivanova

Muntean

2019

Pol. J. Environ. Stud.

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There is no doubt that the global production of waste is increasing. Facts that can be seen as the main causes of this massive waste expansion are high population growth and migration to cities. Other major causes are general economic and social development or enhancement of population living standards [1]. Another critical issue, except for the generated waste amount, is waste composition. The rate of municipal solid waste is 2 billion tons worldwide [2], and this is annually increasing by 8% [3]. Also, we have seen explosive growth of plastics representation in waste composition. Since 1950 the amount of plastic waste has increased by around 280 million tonnes [4]. Therefore, an effective and sophisticated waste management system is a must, and special attention should be paid to such a challenging matter [5].

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Section: Resultscontrasting

confidence: 79%

An Analysis of Waste Management in the Republic of Moldova: A Comparison of Rural and Urban Areas

Procházková

Ivanova

Muntean

2019

Pol. J. Environ. Stud.

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“…On this basis, the results representative for the entire county were elaborated and the rates for the mass accumulation of municipal waste, including selectivity, and divided into year and day, were defined. The rates of waste accumulation per capita in tests were also used by Talalaj and Walery (2015). The study refers to Directive 2008/98 / EC according to which selective collection is required, which should include at least waste of paper and cardboard, metal, plastic and glass.…”

Section: Methodsmentioning

confidence: 99%

Factors of Changes in Waste Management in a Mountain Region of Southern Poland

Przydatek

2019

J. Ecol. Eng.

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The aim of the work was to analyse the changes in the effectiveness of municipal waste management for the period 2009-2015, in one of the largest counties in the mountainous region of southern Poland. Socio-demographic factors, as well as changes as a result of the implementation of the provisions of Directive 1999/31/WE and Directive 2008/98/EC into Polish legislation, are considered. Over the period of seven years, there was a significant increase in the amount of municipal waste generated in the county of 32%, with a simultaneous increase in the number of inhabitants and a decrease in the number of individuals registered as unemployed. An increase in the amount of waste that is non-selectively collected and the number of properties covered by collections of municipal waste occurred before there were any changes in waste management. However, after the changes, the amount of six types of waste selectively collected (paper and cardboard, plastic, metal, bulky, WEEE) increased, with a significant 40% share of glass waste reference to the selectively collected waste. This may result from the changes in waste management. However, over the whole research period, more than 80% of waste was non-selectively collected, which may result from a lack of ecological awareness.

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“…administrative, functional, and economic type of the municipality [2] affluence ("standard of living") and inhabitants' lifestyle [15,16] average size of a household [5] buildings type and heating system [2,5,12] climate factors (the temperature and precipitation) and the season of the year [7,12,17,18] eating habits and health indicators, such as lifespan and infant mortality, as well as the age structure of population [17,19] fees for waste collection and disposal calculated per one inhabitant or per one ton and the frequency of waste collection [7,12] household size [2,5,15,20] level of contamination in selectively collected waste [7,12] municipality's income from taxes calculated per one inhabitant [13,21,22] other technical and sanitary equipment of buildings [5] participation in taxes comprising national budget income personal income tax [5] participation of ashes and/or biodegradable waste in the mixed municipal waste stream [7,12] participation of households composting organic waste [7,12]…”

Section: Independent Variablesmentioning

confidence: 99%

“…participation of households equipped with furnace for solid fuels [5] participation of waste collected selectively [7,12] participation of waste from infrastructural facilities in the total weight of municipal waste [7,12] percentage of municipality's/city's inhabitants covered under waste collection system [7,12] population density [5,6,20,23] saturation of technical infrastructure facilities [2] social factors [2,5,6,13,19,23] the number and capacity of containers calculated per one household-furnishing houses with small capacity containers motivates the inhabitants to collect waste selectively [7,12] the number of unemployed people, the level and structure of employment [5,19,20] tourism-the number of accommodation places, hotels, guesthouses, etc. [17] tradition and people's habits [6,17] urbanization level [2,4,20,23] The approaches to analyzing the rate of mass accumulation of waste, presented in the chosen literature, use mainly statistical methods in the form of linear regression models [17,18,24], multiple regression [5,19,25,26], Rough Set Theory [22], multivariate grey models [20], and artificial neural networks [1,…”

Section: Independent Variables: Referencementioning

confidence: 99%

Identification and Analysis of Sets Variables for of Municipal Waste Management Modelling

2019

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Due to the large quantities of municipal waste generated, their harmful effects on the environment should be minimized. The rationalization of waste management is therefore necessary to achieve a more sustainable development system. In order to support the decision-making process for municipal waste management, this document focuses on developing models for practical use by local authorities in forecasting and managing the size of waste stream in their area. This action, because of its specificity, is a difficult task, especially because of the systemic changes made and the territorial differentiation and changes in the living level of the population. The work presents studies conducted in 2479 municipalities for which mass accumulation index forecasts were developed, using selected methods based on readily available input variables that have not yet been used (structure municipalities and typology of municipalities by scope of influence). The studies confirmed the hypothesis that the amount of municipal waste collected from households depends both on the administrative type of the municipality and on the factors related to the location and socioeconomic function of the area. The inclusion of localization and socioeconomic factors, which so far were not used to model the municipal waste stream, allowed for the reduction of the prediction error of this indicator. Relevant waste stream forecasts will allow local governments to achieve more effectively the objective of sustainable waste management and thus reduce their environmental impact. The achievement of this objective will be possible not only through the preparation of infrastructure to serve the projected waste volumes; it will also identify the waste management areas where the municipal waste reception process is inadequate. Thus, it will help to eliminate illegal processing and the landfill of waste. Keywords: municipal waste; sustainable waste management; ecological modelling; forecasting the amount of waste; limiting the impact of waste on the environment

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The effect of gender and age structure on municipal waste generation in Poland

Cited by 40 publications

References 20 publications

An Analysis of Waste Management in the Republic of Moldova: A Comparison of Rural and Urban Areas

An Analysis of Waste Management in the Republic of Moldova: A Comparison of Rural and Urban Areas

Factors of Changes in Waste Management in a Mountain Region of Southern Poland

Identification and Analysis of Sets Variables for of Municipal Waste Management Modelling

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