Demographic and socio-economic factors including sustainability related indexes in waste generation and recovery
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F21%3APU143305" target="_blank" >RIV/00216305:26210/21:PU143305 - isvavai.cz</a>
Result on the web
<a href="https://www-tandfonline-com.ezproxy.lib.vutbr.cz/doi/full/10.1080/15567036.2021.1974610" target="_blank" >https://www-tandfonline-com.ezproxy.lib.vutbr.cz/doi/full/10.1080/15567036.2021.1974610</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/15567036.2021.1974610" target="_blank" >10.1080/15567036.2021.1974610</a>
Alternative languages
Result language
angličtina
Original language name
Demographic and socio-economic factors including sustainability related indexes in waste generation and recovery
Original language description
There has been plenty of research on the influence of various socio-economic and demographic data on waste generation to develop effective and targeted waste reduction measures, including energy recovery. This study evaluates the relationship between the waste generation and Circular Material Use rate, Environmental Tax Revenue, and Global Innovation Index beyond the typical socio-economic factors (e.g., gross domestic product or population). Correlation analysis is conducted on the EU-27 datasets before the development of the predictive model. The correlation strength between the factors is discussed to identify the potential rebound effect from the central driver of economic growth and development. A positive correlation and partial rebound effect are identified in the data. The waste amount ending in disposal and energy recovery treatment increases with the Circular Material Use rate, suggesting that the expected gains from Circular Material Use rate are offset by other socio-economic factors such as increasing population or gross domestic product. However, a diminishing trend is observed in the rebound effect over the years. Multiple linear regression with validation is applied to identify the best fit model for predicting waste generation. Using population, gross domestic product, Circular Material Use rate, and Environmental Tax Revenues as independent variables, a model is generated with a mean absolute percentage error of 18.65% (7% lower than the benchmark) and R-2 (coefficient of determination) of 0.995.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20704 - Energy and fuels
Result continuities
Project
<a href="/en/project/EF15_003%2F0000456" target="_blank" >EF15_003/0000456: Sustainable Process Integration Laboratory (SPIL)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Energy Sources Part A-Recovery Utilization and Environmental Effects
ISSN
1556-7036
e-ISSN
1556-7230
Volume of the periodical
neuveden
Issue of the periodical within the volume
September
Country of publishing house
US - UNITED STATES
Number of pages
14
Pages from-to
„“-„“
UT code for WoS article
000695729200001
EID of the result in the Scopus database
2-s2.0-85114616248