Socio-demographic determinants of municipal waste generation: case study of the Czech Republic (original) (raw)
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Environmental Research, 2021
Better municipal solid waste (MSW) management can help to address environmental concerns and supports economic and social development. Because MSW characteristics can change over time, management strategies should also evolve and be applied correspondingly. However, many previous studies have focused on MSW characterization or investigated specific management strategies for a target MSW. Few studies have assessed the spatial variations of MSW characteristics and socio-economic (SE) conditions as well as their associations. This study evaluated the feasibility of using an integrated unsupervised method (cluster analysis and cross-tabulation analysis) to explore these topics for MSW management. Results suggest that the integrated method can successfully help to reveal key information. Seven jointed MSW-SE scenarios were investigated based on 259 individual observations of Taiwan. Associations between MSW compositions and SE conditions were identified statistically significant for four MSW-SE scenarios. In general, the general SE type (SE1) is very likely to generate high food wastes and other combustible, low paper, wood, and rubber wastes (MSW1). The small island SE type (SE3) is more likely to produce high paper and low wood, rubber, textile, and other noncombustible wastes (MSW2). Overall, the method applied in this study could help to reveal statistical associations between MSW and SE, which can help decision-makers comprehend underlying facts and develop effective management strategies.
International Research Journal of Environment Sciences, 2015
This study is aimed at developing a spatial model for municipal solid waste (MSW) generation rate based on socio-economic, demographic and climatic variables for Nigeria. The outcome is targeted at effective forecasting and management of MSW in the country. Secondary data sources were used to obtain the variables, then screened and linked to the administrative boundaries of the 36 States and the Federal Capital Territory (Abuja). Geographically Weighted Regression (GWR) tool in ArcGIS 10.0® was used to analyse the data. The analysis gives an acceptable condition number of 16.63, while local R2 ranges from 0.54 to 0.90. The model also explains 65 per cent of the total variation in the dependent variables. The findings of this study revealed that nearer States tend to have similar coefficients than the distant ones and that dependent variables vary among States. In addition, the β coefficient estimates of unemployment rate, employment in crop farming, literate adults above 15 years, per-capita average household expenditure on food and non-food items, and excess proceeds of crude oil to local government areas exhibit positive relationship with MSW throughout the country. Whereas, only rainfall variable exhibited positive and negative relationship in northern and southern part of the country, respectively. The paper contributed towards improving the understanding of factors affecting MSW generation rate in Nigeria.
Waste Management, 2020
Existing studies have studied influencing factors of MSW generation behaviour at different spatial levels of organization, but always one at a time and not simultaneously. Income is a strong influencing factor, affecting MSW generation from the individual to the country level, capable of hiding the effects of the others. This study shows that when MSW generation behaviour is holistically analysed across multiple levels of organization Highlights • Sudden changes in MSW generations behaviours are common to developing countries. • Determined by social practices at multiple hierarchical spatial levels of organization. • Different influencing factors of MSW generation behaviour appear at each level. • Income is mostly the main influencing factor of MSW generation behaviour. • Most studies conclude this from analyzing this link one spatial level at a time. • Simultaneous analysis can reveal influencing factors others than income.
Effects of socio-economic factors on quantity and type of municipal solid waste
Management of Environmental Quality: An International Journal, 2020
PurposeThe purpose of this paper is to determine the socio-economic factors related to household solid waste generation and its type based on field surveys in South Delhi Municipal Corporation area in Delhi, India.Design/methodology/approachThis paper develops a framework to systematically identify the socio-economic factors related to household waste generation and its type. The framework uses both primary and secondary data. The primary data are collected through the instruments of questionnaire and interviews, and the secondary data are collected from the literature available in public domain. Multinomial logistic models are developed. The models are analyzed using the SPSS software version 22.0.FindingsThe study reports that socio-economic parameters like monthly income of the family, number of family members, occupation, education are statistically significant predictors. Further, detailed disaggregated models reveal more insights that are not apparent otherwise, such as the nu...
Waste management planning requires reliable data concerning waste generation, influencing factors on waste generation and forecasts of waste quantities based on facts. This paper aims at identifying and quantifying differences between different municipalities' municipal solid waste (MSW) collection quantities based on data from waste management and on socio-economic indicators. A large set of 116 indicators from 542 municipalities in the Province of Styria was investigated. The resulting regression model included municipal tax revenue per capita, household size and the percentage of buildings with solid fuel heating systems. The model explains 74.3% of the MSW variation and the model assumptions are met. Other factors such as tourism, home composting or age distribution of the population did not significantly improve the model. According to the model, 21% of MSW collected in Styria was commercial waste and 18% of the generated MSW was burned in domestic heating systems. While the percentage of commercial waste is consistent with literature data, practically no literature data are available for the quantity of MSW burned, which seems to be overestimated by the model. The resulting regression model was used as basis for a waste prognosis model (Beigl and Lebersorger, in preparation).
Municipal Waste Generation and Socioeconomic Drivers
The Journal of Environment & Development, 2008
Using data sets from Italian provinces that include rich northern and poorer southern regions, this article examines to what extent income and municipal waste generation are linked and at what level of income they become delinked. The analysis shows that the turning point occurs at very high levels of value added per capita (in the range of 22,586 to 31,611), exemplified by a very limited number of wealthy (northern) Italian provinces. The authors also find that some recently adopted waste policy and waste management instruments have influenced waste generation at source, independent of socioeconomic characteristics. This supports the argument that more effective waste management instruments that target waste prevention at the source need to be implemented in line with the stated priorities of the EU and member countries. The findings also imply that developing countries in particular should not wait to implement waste reduction policies until household incomes and consumption level...
Disparities in municipal waste management across EU-27. A geographical approach
Inadequate waste management leads to many environmental issues and the adoption of an efficient and sustainable waste management has become a priority objective of the EU. However, besides the demographic factors, the various socio-economic and geographical conditions of this complex space lead to major disparities in municipal waste management between North and South, East and West. This paper aims to do a spatial-temporal analysis of the Eurostat indicators using ascending hierarchical cluster analysis that divides the member states into five typological classes. The resulted maps highlight territorial disparities among Member States on municipal waste management and also reveal the evolution of environmental policies between 2003-2009 related to the EU acquis.
Rural waste generation : a geographical survey at local scale (preprint version)
14th International Multidisciplinary Scientific GeoConference on ECOLOGY, ECONOMICS, EDUCATION AND LEGISLATION SGEM 2014 ,Conference Proceedings vol.1 : 585 – 592, ISSN 1314- 2704, 2014
The paper examines the per capita waste generation rates from from rural areas of Neamț County (Romania) using thematic cartography. Geographical approach of this issue is difficult because the lack of a geostatistic database at commune scale. Spatial analysis of waste indicators reveals several disparities between localities. Comparability of data between communes located in various geographical conditions must be carrefully made according to local waste management systems. Several dysfunctionalities are outlined in order to compare these results, on the one hand, between localities and on the one hand, between recent years. Geographical analysis of waste generation rates is imperative for a proper monitoring of this sector. Data from 2009, 2010 and 2012 shows that rural waste management is in a full process of change towards a more organized, stable and efficient system.
Management Models of Municipal Solid Waste: A Review Focusing on Socio Economic Factors
International Journal of Economics and Finance, 2012
Waste management is a complex process that requires a lot of information from various sources such as factors on waste generation and waste quantity forecasts. When operations related to promotion of waste management systems are considered it is observed that generation of waste and planning is found to be influenced by different factor of which are impacted by socio demographics. The main aim of this paper is to review previously tested models related to municipal solid waste generation and identify possible factors which will help in identifying the crucial design options within the framework of statistical modelling.
RURAL WASTE GENERATION: A GEOGRAPHICAL SURVEY AT LOCAL SCALE
14th SGEM GeoConference on ECOLOGY, ECONOMICS, EDUCATION AND LEGISLATION, 2014
The paper examines the per capita waste generation rates from from rural areas of Neamț County (Romania) using thematic cartography. Geographical approach of this issue is difficult because the lack of a geostatistic database at commune scale. Spatial analysis of waste indicators reveals several disparities between localities. Comparability of data between communes located in various geographical conditions must be carrefully made according to local waste management systems. Several dysfunctionalities are outlined in order to compare these results, on the one hand, between localities and on the one hand, between recent years. Geographical analysis of waste generation rates is imperative for a proper monitoring of this sector. Data from 2009, 2010 and 2012 shows that rural waste management is in a full process of change towards a more organized, stable and efficient system.