Prognostic model of Czech municipal waste production

International Environmental Modelling and Software Society (iEMSs)
7th Intl. Congress on Env. Modelling and Software, San Diego, CA, USA,
Daniel P. Ames, Nigel W.T. Quinn and Andrea E. Rizzoli (Eds.)
http://www.iemss.org/society/index.php/iemss-2014-proceedings
Case study: Prognostic model of Czech municipal
waste production and treatment
MSc. Jiří Kalina, Prof. Dr. Jiří Hřebíček, PhD., Gabriela Bulková
Institute of Biostatistics and Analyses at the Faculty of Medicine and the Faculty of Science of the
Masaryk University, Kamenice 126/3, 625 00 Brno, Czech Republic, [email protected],
[email protected]
Ministry of the Environment, Vršovická 65, 100 10 Praha, Czech Republic, [email protected]
Abstract: The paper introduces the application of multidimensional regression methods and a
mathematically applicable waste streams structure model for the development of new complex model
of municipal waste management (production and treatment) of the Czech Republic. This model was
developed for purposes of the Ministry of the Environment of the Czech Republic and consequently of
the European Environment Agency. It can evaluate the sustainability of environmental decisions on
the national level with the focus on waste management data requirements, national strategies for
waste data acquisition, management and processing to support sustainability of waste management
in accordance with the European waste legislation.
Keywords: waste management; environmental modeling; municipal waste.
1
INTRODUCTION
Waste is an unavoidable by-product of human activities. Economic development, urbanization and
improved living standards in municipalities have increased the quantity and complexity of generated
municipal waste (MW). MW is defined as all waste generated within municipalities (cities and villages)
by the activities of its inhabitants (households) and businesses (e.g. trade waste), which is separated
into its components and transported to waste treatment facilities, where it is recovered or disposed.
Cherian and Jacob (2012) reviewed waste management models and introduced a concept of
municipal waste classification. The waste of interest can be according this concept classified as urban
solid waste (USW), i.e. the waste, which is created in an urban environment. USW is further divided
into two different categories – household waste (HW) and similar commercial, industrial and
institutional wastes (NHW). HW refers to waste that is generated by households and NHW is the
waste that is produced by the commercial sector (industries, organizations).
When it comes to making appropriate decision in relation to the waste management of USW, two
factors are important – the total volume of the waste and its composition. Both of these factors
change with time and socioeconomic conditions (Hejč, Hřebíček, 2008; Soukopová et al., 2011; Singh
et al., 2011).
We consider in our USW model that this waste usually contains remains of food and vegetables,
paper: i.e., biodegradable waste (BMW); plastic, glass and metal containers, printed matter
(newspapers, magazines, and books): i.e., recyclable waste (RMW); destroyed products, ashes and
rubbish, used or unwanted consumer goods, including shoes and clothing: i.e., mixed household
waste (MMW); and the rest of waste which does not belong to BMW, RMW and MMW (Hřebíček et
al., 2013b), where we follow the European List of Waste (Commission Decision 2000/532/EC) and
Annex III to Directive 2008/98/EC.
Moreover, there are several wastes, which could be classified in more than one of the groups BMW,
RMW and MMW, see Figure 1. For example, plastics fall into both RMW and in MMW; waste paper is
included in all three groups BMW, RMW and MMW, etc.
Kalina J, Hřebíček J., Bulková G. Case study: Model of the prognosis of Czech municipal waste production and treatment
Figure 1. Composition of municipal waste in the Czech Republic in 2012
(Hřebíček, Kalina, Soukopová, 2013b).
We assume that BMW (or its components) can be composted or used in anaerobic digestion (AD)
plants, RMW can be used as raw material (paper, plastic, glass, and metals), and MMW can be used
in energy recovery (incineration) plants or disposed in landfills (Hřebíček et al., 2009). The separation
of MMW components into BMW, RMW groups may take place at the source (separate collection of
BMW and RMW in the municipalities) or in the mechanical biological treatment (MBT) facilities. These
principal streams of MW are not distinct and there are therefore several intersections in the
distribution of wastes into them, see Figure 1.
We analyzed models from the reviews of modelling municipal solid waste generation (Beigl et al.,
2008; Cherian, Jacob 2012) and European Reference Model on Municipal Waste Management
(Waste model, 2012) and decided to modify their approaches and develop the own more complex
model of USW generation and treatment (Hřebíček, Hejč, 2008, Soukopová, Hřebíček, 2011), which
is introduced herein. It consists of two connected sub-models (the first one for forecasting of MW
generation, the second one for forecasting MW treatment), where the second sub-model uses
forecasted results of the first sub-model.
The objective of the paper is introducing both sub-models, the first one in the Section 2 and the
second one in the Section 3 including some their output results. They were used for modeling and
forecasting of USW (production and treatment) in the Czech Republic within the period 2015–2024
(Hřebíček et al., 2013a, 2013b). These sub-models allow for the evaluation of the sustainability of
environmental decisions on a national level with the focus on waste management data requirements,
national strategies for waste data acquisition, management and processing in a similar way as was
done by Hung, Ma, Yang, (2007); and Liao, Chiu, (2011).
2
SUBMODEL OF FORECASTING MUNICIPAL WASTE GENERATION
The first sub-model for forecasting the USW generation is introduced in this section. It considers USW
composition (Hřebíček et al., 2012), household socioeconomic conditions (Hřebíček et al., 2013a,
2013b), etc. Two different approaches were deployed in forecasting the USW generation:
1. The first approach consists of construction of a multidimensional sub-model of USW generation
depending on a scale of municipal parameters (taking into account 14 parameters, such as
population, different acreages and land use inside the municipalities, civic amenities, living
standards etc.) and expected development of these parameters in a form of time series for the
period 2015–2024 (Hřebíček et al., 2013b).
Kalina J, Hřebíček J., Bulková G. Case study: Model of the prognosis of Czech municipal waste production and treatment
We used open linked data of the individual municipalities in the Czech Republic available in e1
2
3
4
Government systems (RISY , UFIS , ISOH , Ministry of the Interior ) and the Czech Statistical
5
Office . Of this number of municipal parameters, 19 predictors (i.e. independent variables of the
model) of the multiplication terms in total were created for each of the 6,245 municipalities inside
the Czech Republic by different (but only meaningful) products of type (Hřebíček et al., 2013a)
𝑃𝑗 = ∏𝑖∈𝐼𝑗 (𝑝𝑖 + 𝑐𝑖 )
(1)
determined by an index set 𝐼𝑗 for this predictor (i.e. the set contains such numbers 𝑖, that (𝑝𝑖 + 𝑐𝑖 )
should occur in the product), where 𝑃𝑗 denotes the 𝑗-th predictor, 𝑝𝑖 denotes 𝑖-th municipal
parameter and 𝑐𝑖 denotes an empirical constant tuned during the calibration phase of modeling
which is detail described in (Hřebíček et al., 2013a). In the next step, a verification of
independency of predictors was performed by computing correlation matrix (non-parametric
Spearman correlation coefficient was used on the 95% significance level) of them and excluding 5
highly correlated predictors from the further modeling (Hřebíček et al., 2013a, 2013b).
The general form of the USW generation is then given as
𝑃 = ∑𝑚
𝑗=1(𝑎𝑗 ∙ 𝑃𝑗 ) + 𝑒 ,
(2)
where P denotes the amount of USW generation in given municipality, Pj denotes the j-th
predictor, aj denotes the j-th coefficient, m = 15 and e indicates an error estimate of municipal
waste production P in a given municipality. Submodel (1), (2) was calibrated (using least squares
method) with the data from the annual reports of the MW generation and treatment in 2011 of all
municipalities of the Czech Republic using the database of the Waste information system ISOH
passed from the Ministry of the Environment (MoE).
Since the predictors values are known for the whole set of municipalities in the Czech Republic
(6,245) and the USW generation is known for most of them (e.g., 5,208 municipalities reported
their HW generation and 1,253 municipalities reported their BMW generation in 2011), it was
possible to compute the multidimensional model with 15 independent (predictors) and 1
dependent (production) variable, which provided the coefficients that precisely described the
dependence of bio-waste production on the input parameters. For instance, the resulting
estimation for BMW production (Mg) in any municipality calibrated on data from 2011 has
following resulting form (Hřebíček et al., 2013b):
𝐵𝑀𝑊𝑡𝑜𝑡𝑎𝑙 = 886 + 0.0531 ∙ 𝑖𝑛ℎ + 921 ∙ 𝑠𝑡𝑠 − 6.634 ∙ 𝑟𝑒𝑡 − 15.9 ∙ 𝑢𝑛𝑒 − 16.1 ∙ 𝑔𝑎𝑠 − 0.00749 ∙ 𝑠𝑡𝑠 ∙
𝑖𝑛ℎ ∙ 𝑟𝑒𝑡 + 0.000885 ∙ 𝑖𝑛ℎ ∙ 𝑟𝑒𝑡 ∙ 𝑢𝑛𝑒 − 0.00309 ∙ 𝑠𝑡𝑠 ∙ 𝑖𝑛ℎ ∙ 𝑢𝑛𝑒 + 1.33 ∙ 𝑟𝑒𝑡 ∙ 𝑢𝑛𝑒 + 0.257 ∙ 𝑠𝑡𝑠 ∙ 𝑖𝑛ℎ −
0.00442 ∙ 𝑖𝑛ℎ ∙ 𝑟𝑒𝑡 − 11.2 ∙ 𝑠𝑡𝑠 ∙ 𝑟𝑒𝑡 − 0.0106 ∙ 𝑖𝑛ℎ ∙ 𝑢𝑛𝑒 − 4.63 ∙ 𝑠𝑡𝑠 ∙ 𝑢𝑛𝑒 + 37.6 ∙ 𝑠𝑡𝑠 ∙ 𝑔𝑎𝑠 + 5.76 ∙
(3)
𝑠𝑡𝑠 ∙ 𝑙𝑜𝑛 − 0.0766 ∙ 𝑔𝑟𝑠 ∙ 𝑠𝑡𝑠
with socioeconomic parameters, where 𝑖𝑛ℎ denotes total number of inhabitants, 𝑠𝑡𝑠 denotes index
of municipal status (e.g. village, town, county, city, etc.), 𝑟𝑒𝑡 is a retirement inhabitants ratio, 𝑢𝑛𝑒
is a share of unemployed, 𝑔𝑎𝑠 is an index of gasification (reduces production of ashes), 𝑙𝑜𝑛
denotes longitude and 𝑔𝑟𝑠 a grass acreage within the municipality.
A population distribution model was used for the forecasting of inhabitants time series (number of
inhabitants of different age groups) with slowly decreasing trend from 2011 up to 2024 predicted
by the Czech Statistical Office; forecasting development of unemployment and individual
consumption were taken into account as well, wrapped from several economical prognoses in the
near future and assumed to be constant and rather optimistic in a long-term perspective.
1
http://www.risy.cz/cs
http://wwwinfo.mfcr.cz/ufis/
3
http://isoh.cenia.cz/groupisoh/
4
http://www.mvcr.cz/clanek/statistiky-pocty-obyvatel-v-obcich.aspx
5
http://www.czso.cz/animgraf/projekce_1950_2101/index.htm
2
Kalina J, Hřebíček J., Bulková G. Case study: Model of the prognosis of Czech municipal waste production and treatment
This sub-model (1), (2) did not direct the time series modelling of HW generation using
extrapolation depending on time, but on the contrary to the static model of MW generation
depending on time series of individual municipality parameters. In the given year, so knowledge of
the parameters of the municipalities gives the prediction of MW generation and it is modeled
according to the change of these parameters over time (due to the relatively long forecasting
period it was necessary to work with a specific uncertainty).
2. The second approach considered spatially aggregated time series of USW generation from the
period 2008–2012. In total input data contained by a series of 51 966, 52 131, 54 729, 54 724 and
54 974 records were processed. They were used for the construction of linear and exponential
trends of USW generation of selected waste streams (total USW, MMW, BMW, RMW). USW
generation is affected by a plenty of parameters, which are difficult to analyze and describe (Beigl
et al., 2008; Hejč, Hřebíček, 2008; Soukopová, Kalina 2012; Cherian, Jacob 2012). Therefore, an
expert approach was chosen to describe the future development as a weighted average of linear
and exponential trends (an assumption that the increase of generation will not be quicker than the
exponential one and the decrease will be not quicker than the linear one). Thus, for all the time
series (for individual waste streams), a pair of models were constructed and the result was
obtained as 1:1 average of both. Several exceptions to this ratio occurred: an expert approach
was used due to known changes (e.g. legislative ones) in a near future, which could not arise
from the time series itself.
The final forecast of the USW generation of the Czech Republic for the period 2015-2024 was
obtained as a weighted average of both approaches described above.
2.1
Results
In Table1 is presented the forecasting USW generation in the Czech Republic for the period 20152024, which is split into two different categories – household waste (HW) forecast and commercial,
industrial and institutional wastes (NHW) forecast. It follows from Table 1 that total amount of USW
generation will slowly decrease in the 2015 - 2024 period.
Table 1: Forecasting USW generation in the Czech Republic [Tg]
Year
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
Sum
5,44
5,43
5,39
5,38
5,36
5,34
5,33
5,31
5,30
5,30
HW
3,97
3,97
3,94
3,94
3,94
3,94
3,94
3,93
3,93
3,94
NHW
1,47
1,46
1,45
1,44
1,42
1,40
1,39
1,38
1,37
1,36
The results of the USW generation sub-model subsequently entered into the USW treatment submodel, which was built as a set of non-linear equations covering the whole area of municipal waste
management (Hřebíček et al., 2013b).
3
SUBMODEL OF FORECASTING MUNICIPAL WASTE TREATMENT
Once the USW generation is known, it is necessary to treat it in its full scope. There is a need to
outline the main processes of waste management and their aims to satisfy the main waste
management objectives of the framework of the European Union (EU) environmental policies (7EAP,
2013) and legislation. It was necessary to summarize all EU legislative and environmental objectives
(usually in the form of thresholds/limits) as well as the initial (infrastructure) conditions of waste
management in 2012 in the form of a mathematically applicable structure model.
It was defined for the same five principal waste streams (total USW, MMW, BMW, RMW and
hazardous substances in USW) as in the USW generation sub-model; nevertheless, these waste
streams are not distinct sets and their intersections change their sizes (in term of their percentages),
see Figure 1, which are necessary to be included into the construction of the USW treatment submodel.
Kalina J, Hřebíček J., Bulková G. Case study: Model of the prognosis of Czech municipal waste production and treatment
Therefore, eight distinct waste sub-streams were defined in the sub-model to enter the computation
and entirely describe all the waste streams of interest (Hřebíček et al., 2013b):
1.
2.
3.
4.
5.
6.
7.
8.
Amount 𝑟𝑚𝑤 of separated recyclable waste except paper (plastics, glass, metals etc.) in USW;
Amount 𝑏𝑚𝑤 of separated BMW except for paper;
Amount 𝑏𝑟𝑚𝑤 of separated paper and wood;
Amount 𝑏𝑚𝑚𝑤 of kitchen and garden waste in MMW;
Amount 𝑚𝑟𝑚𝑤 of recyclable wastes in MMW except for paper;
Amount 𝑏𝑚𝑟𝑚𝑤 of paper in MMW;
Amount 𝑚𝑚𝑤 of non-usable part of MMW (ashes, particulated matter, composites etc.);
Amount 𝑟𝑒𝑠𝑡 of the rest USW (bulky waste, some hazardous parts, electro waste, … etc.).
In addition to these streams, the whole amount 𝑢𝑠𝑤 of USW stream was defined as a sum of all
above mentioned streams. The amount ℎ𝑤 of hazardous waste stream is included in all above
streams and thus we modeled it separately.
This simple model provides the first set of equations describing the relations between the principal
streams (generation of which is known) and sub-streams. For the whole USW stream, the equation is
apparent:
𝑢𝑠𝑤 = 𝑏𝑚𝑤 + 𝑚𝑚𝑤 + 𝑟𝑚𝑤 + 𝑏𝑚𝑚𝑤 + 𝑏𝑟𝑚𝑤 + 𝑚𝑟𝑚𝑤 + 𝑏𝑚𝑟𝑚𝑤 + 𝑟𝑒𝑠𝑡
(4)
Equations for remaining streams are similar and are not repeated here. For example, in the BMW
stream the equation of total amount of BMW is equal to the sum of above listed sub-streams 2, 3, 4
and 6.
The further set of equations in the treatment sub-model arises as a logical consequence of dividing
above mentioned waste streams according to the possible treatment. Each of the sub-stream’s
amounts can be further divided to five non-negative amounts responding to the following treatment:
material recovery, energy recovery, composting and anaerobic digestion (AD), landfilling and
combustion denoted by last five letters in the name of the model variables: matre, enere, compo,
landf, comb, see the equation for USW treatment:
𝑢𝑠𝑤 = 𝑢𝑠𝑤𝑚𝑎𝑡𝑟𝑒 + 𝑢𝑠𝑤𝑒𝑛𝑒𝑟𝑒 + 𝑢𝑠𝑤𝑐𝑜𝑚𝑝𝑜 + 𝑢𝑠𝑤𝑙𝑎𝑛𝑑𝑓 + 𝑢𝑠𝑤𝑐𝑜𝑚𝑏𝑢
(5)
Equations for remaining streams treatment are similar and we will not repeat them. Some of these
amounts in above equations should be zero (such as composting of glass, metal etc. or material
recovery of the unusable rest).
The additional set of equations describes the key demands of EU and national environmental
legislation and decision makers of the Ministry of Environment. For example: Directive 99/31/EC on
the landfill of waste (Landfill Directive) laying down the thresholds of household BMW share diverted
from the flow to landfills: at least 50% in 2013 and 75% in 2020 compared to the amount of BMW
landfilled in 1995 (i.e. 1,530 Tg in the Czech Republic); Directive 2008/98/EC on waste (Waste
Framework Directive) sets demands specifying the amount of household RMW to be recovered in
2020: the threshold is 50% here.
The equations covering demands of both directives bring an element of non-linearity to the treatment
sub-model, due to their nature of ratios (both consist of the proportion of a treated part of particular
waste stream). E.g., the Landfill Directive criterion in 2020 could be expressed as:
𝑏𝑚𝑤𝑙𝑎𝑛𝑑𝑓+𝑏𝑚𝑚𝑤𝑙𝑎𝑛𝑑𝑓+𝑏𝑟𝑚𝑤𝑙𝑎𝑛𝑑𝑓+𝑏𝑚𝑟𝑚𝑤𝑙𝑎𝑛𝑑𝑓
𝑏𝑚𝑤+𝑏𝑚𝑚𝑤+𝑏𝑟𝑚𝑤+𝑏𝑚𝑟𝑚𝑤
< 0.35
(6)
The last set of equations describes the assumed capacity of waste treatment facilities in the Czech
Republic in the period 2015–2024, particularly energy recovery, and composting and AD plants which
play a key role in the diversion of BMW from landfills.
Kalina J, Hřebíček J., Bulková G. Case study: Model of the prognosis of Czech municipal waste production and treatment
The above developed treatment sub-model contains 35 equations which could be used as a task
assignment of non-linear programming to find non-negative solutions for all waste streams and substreams in individual years (we consider a 1-year granularity for changes, mainly due to the Czech
system of waste reporting, which provides data on waste production and treatment annually).
Nevertheless, such a solution does not respect some of the finer relations and patterns and thus it
was necessary to add a set of further 40 equations to preserve all aspects of model feasibility and full
control of the solution. This complete set of equations for “refining” the treatment sub-model was
established in several steps as a result of discussions with waste management experts of different
branches to obtain fully meaningful solution with high precision and applicability (Hřebíček et al.,
2013b).
Results of (Benešová et al, 2011; Hřebíček et al., 2012) about MMW composition in several Czech
cities were included as well as the test of yield and usability of RMW from separate collections in
municipalities (which yields more non-linear equations).
The complete set of equations of treatment sub-model achieved number 75 and it is naturally not
possible to describe all of them in this paper. Fortunately, the solution of the above optimization
problem of non-linear programming here meets a unique solution of the developed set of equations,
which means that it is not necessary to determine price functions for all the waste streams, which
usually demands implementation of LCA study (Emerya et al., 2007; Kirkeby et al., 2006), i.e.,
relatively expensive and time-consuming solution.
The resulting set of non-linear equations was solved by a computer algebra system Maple (Maple,
2014) to obtain final results of different municipal waste treatment methods, which will serve as a base
for the Czech government’s decision in the next decade.
3.1
Results
The main results of USW treatment sub-model are represented by a forecasting of material balance in
five principal waste streams, as shown in Table 2 and Figure 2.
It is apparent that the total amount of USW will decrease slowly as well as MMW which represents its
principal part. We can see the shift of USW from landfilling to other ways of waste treatment, driven
mainly by combined pressure to meet all the legislation conditions. Moreover, there are results related
to both EU directives showing the way of fulfillment of set limits as apparent from Figure 2 and Table
2.
Table 2: Forecasting USW treatment [Tg]
Streams\Year
Material
recovery
Composting
and AD
Energy
recovery
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
1,91
1,94
1,96
1,99
2,03
2,07
2,12
2,17
2,23
2,31
0,37
0,43
0,49
0,54
0,60
0,65
0,70
0,75
0,80
0,85
0,68
0,72
0,72
0,72
0,80
0,95
1,15
1,15
1,37
1,47
Landfilling
2,46
2,32
2,21
2,10
1,91
1,65
1,34
1,12
0,87
0,65
Combustion
0,01
0,02
0,02
0,02
0,02
0,02
0,02
0,02
0,02
0,02
The leading motive of changes in the Czech waste management within the period 2015–2024 is the
diversion of USW (and especially BMW) from the landfills to all other types of waste treatment
facilities. The treatment sub-model indicates that USW landfilling should decrease from 49.6% in 2015
to 12.3% in 2024, which opens the door to a complete cessation of landfilling of untreated MMW in
the period 2025–2030.
On the other hand, the material recovery should increase from 33.9% to 43.5% in the same period,
accompanied by the increase of composting and anaerobic digestion from current 4.7% to 16.1% in
Kalina J, Hřebíček J., Bulková G. Case study: Model of the prognosis of Czech municipal waste production and treatment
2024 and energy recovery from 11.6% to 27.7%. These relatively large changes are conditioned
primarily by dynamic changes in the MMW treatment, which currently represents the most important
component of USW, but at the same time hides the highest potential to achieve the legislation
demands and environmentally beneficial changes.
Figure 2. Forecasting principal waste streams treatment 2015–2024.
4
CONCLUSION
The new model of forecasting the Czech municipal waste generation and treatment was developed
following the state of the art of municipal waste modeling. It was introduced its two connected submodels: the first one for USW generation and the second one for USW treatment. They were used for
the newly developed Plan of Waste Management of the Czech Republic for the 2015–2024 period.
This model has brought new decision support tools for the Czech Ministry of the Environment in the
field of waste generation and treatment (e.g. national lawmaking, subsidy policy, building new facilities
etc.). It supports the sustainable waste management of the Czech Republic in accordance with the
EU waste legislation. Therefore, it could be applied for all EU Member States.
ACKNOWLEDGMENTS
The paper is supported by the Ministry of the Environment of the Czech Republic within the project
"Development of the forecast of production and treatment of municipal waste for the Czech Republic
in the period 2015–2024”.
Kalina J, Hřebíček J., Bulková G. Case study: Model of the prognosis of Czech municipal waste production and treatment
5
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