Journal
CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
Volume 24, Issue 10, Pages 3047-3059Publisher
SPRINGER
DOI: 10.1007/s10098-022-02344-8
Keywords
Waste-to-energy; Optimisation; Immission load; Integration of heat sources; Dispersion model
Categories
Funding
- project Sustainable Process Integration Laboratory - SPIL [CZ.02.1.01/0. 0/0.0/15_ 003/0000456]
- Czech Republic Operational Programme Research
- Technology Agency of the Czech Republic (TACR) within the research project National Centres of Competence, National Centre for Energy [TN1000007]
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This study presents a method to directly quantify the impact of waste-to-energy plant integration on the health burden of the surrounding population. Real-world data shows that the pollutant load can be significantly reduced in the calculation scenario.
Landfilling is still the most common way of municipal waste treatment in around half of the EU countries. It has been shown that diverting some of the waste-to-energy recovery makes it possible to reduce emissions of various pollutants, especially when the waste replaces lower-quality fossil fuels in heating plants. A methodology is presented to determine the influence of a waste-to-energy plant with a processing capacity in the range of 10 to 150 kt/y integrated into an existing district heating system on the air pollution load in the surrounding area. The change in emission production is determined using an optimisation tool previously developed in the GAMS environment. The parameters of the existing heating plant, such as the fuels used, the boiler output range, etc., are considered. A Gaussian scatter model is then used to determine the immission loads of individual pollutants in the surrounding area. Using the methodology, it is possible to directly quantify the impact of waste-to-energy plant integration on the health burden of the surrounding population in comparison with the reference state. This strategy is presented via a case study involving real-world data, in which it turned out that the immission load can be significantly reduced (up to 83%) compared to the original state in the calculation scenario. [GRAPHICS] .
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