A. Karpušenkaitė “Forecasting methods for hazardous and other specific waste generation: case study of Lithuania” doctoral dissertation defence

Author, Institution: Aistė Karpušenkaitė, Kaunas University of Technology

Science area, field of science: Technological Sciences, Environmental Engineering, T004

Scientific Supervisor: Prof. Dr. Gintaras Denafas (Kaunas University of Technology, Technological Sciences, Environmental Engineering, T004).

Scientific Consultant: Assoc. Prof. Dr. Tomas Ruzgas (Kaunas University of Technology, Natural Sciences, Mathematics, N 001).

Dissertation Defence Board of Environmental Engineering Science Field:
Prof. Dr. Habil. Jurgis Kazimieras Staniškis (Kaunas University of Technology, Technological Sciences, Environmental Engineering, T004) – chairman,
Prof. dr. Dimitrios Komilis (Democritus University of Thrace, Greece, Technological Sciences, Environmental Engineering, T004),
Prof. Dr. Mait Kriipsalu (Estonian University of Life Sciences, Estonia, Technological Sciences, Environmental Engineering, T004),
Prof. Dr. Jolita Kruopienė (Kaunas University of Technology, Technological Sciences, Environmental Engineering, T004),
Prof. Dr. Arvydas Povilaitis (Vytautas Magnus University Agriculture Academy, Technological Sciences,  Environmental Engineering, T004)

The doctoral dissertation is available at libraries of Kaunas University of Technology (Donelaičio 20, Kaunas), Vytautas Magnus University (K. Donelaičio g. 52, Kaunas) and Lithuanian Energy Institute (Breslaujos   g. 3, Kaunas).

Annotation:

The overview of previously conducted research on the waste matter showed that various mathematical forecasting methods were used to predict mainly solid waste generation, rarely hazardous (mainly medical) waste. The possibility of making accurate and reasonable forecasts on various types and total hazardous waste generation is an important aspect in making waste management decisions in short and long terms. Such knowledge can influence the choosing and development of effective hazardous waste utilization methods or the establishment of certain facilities.
This research compared thirteen different statistical modelling methods and determined which models with their specific features would work best with medical, automotive and fluorescent tubes and other mercury–containing waste generation data. Approaches to forecast with and without influencing factors were tested and revealed that in certain situations different models have advantages. Research of this broad scale and including different types of hazardous waste yet searching for similarities between tendencies in their generation was done one of the first times and has lain foundations for further in–depth research exploring possibilities to develop more unique forecasting models for hazardous or other specific waste generation.