The Environmental Costing Model: a tool to advise policy
makers in Flanders on issues of cost efficiency
Meynaerts E., Lodewijks P., Duerinck J.
Flemish Institute for Technological Research (VITO)
Boeretang 200, 2400 Mol, Belgium
(erika.meynaerts@vito.be)
This paper has not been submitted elsewhere in identical or similar
form, nor will it be during the first three months after its
submission to the Publisher.
Abstract
Information and knowledge about environmental costs and cost
efficiency become more and more important in the context of
international and European environmental policy. In recent
literature, references are found of the growing interest for
environmental costs and cost efficiency in e.g. the Netherlands,
Germany, France. In Belgium, the Flemish Institute for
Technological Research started in June 2001 with the development
of the Environmental Costing Model. This model is a tool to
1
determine the costs of environmental policy and to contribute to a
more
efficient
environmental
policy
by
indicating
how
environmental targets can be realised in a cost effective way.
Initially, the model is developed for the industrial emission sources
of SO2, NOx and VOC in Flanders. The choice of the test case is
inspired by the emission targets imposed by the NEC Directive.
The results illustrate the added value of the model as a tool to
determine the least-cost combination of abatement measures to
satisfy multi-pollutant targets. In addition to the optimal solution,
other scenarios can be simulated with the model to support the
policy makers in making well-founded policy choices.
Keywords: abatement measure, cost efficiency, emission source,
environmental costing model, marginal cost curve, mixed integer
programming, multi-pollutant
2
Introduction
Information and knowledge about environmental costs and cost
efficiency become more and more important in the context of
international
and
European
environmental
policy.
The
determination of environmental targets and the burden sharing
between countries are increasingly based on economic analyses.
For instance, the RAINS model has been used for the negotiations
of the Gothenburg Protocol and the Directive 2001/81/EC on
National Emissions Ceilings for certain atmospheric pollutants
(Amann et al. 1999). In order to negotiate on issues as international
burden sharing, the policy makers need information about the cost
effectiveness of the possible abatement measures. Sometimes, the
cost efficiency analysis is a compulsory step in order to comply
with regulation, e.g. in the Water Framework Directive (Article 11,
Annex III) it is stated that all EU Member States have to develop a
river basin management plan by 2009, including programmes of
cost effective measures (Working Group 2.6 – WATECO 2003). A
consistent framework and a tool for optimization are needed to
advise the policy makers on issues of cost efficiency.
3
In recent literature, references are found of the growing interest for
environmental costs and cost efficiency. In the Netherlands, Brink
et al. (2003; 2001) investigated interrelations in emission reduction
strategies for ammonia, nitrous oxide and methane from
agricultural activities in Europe and analyzed their impact on cost
effective emission reduction strategies. Van der Veeren (2002)
developed a decision analytic tool that can be used to identify the
trade-offs between costs and the economic and environmental
consequences of nutrient abatement policies in their spatial setting.
Further work on modelling the relationship between water and
economics in the Netherlands is currently being done by Brouwer
et al. (2005). In Germany, Interwies et al. (2004) developed a
multi-step evaluation process to determine the programmes of costeffective measures as defined in the Water Framework Directive. In
France, Rentz et al. (1999) elaborated (marginal) cost functions for
the reduction of the emissions of VOC in France. The MERLIN
project (Multi-pollutant, Multi-Effect Assessment of European Air
Pollution Control Strategies: an Integrated Approach), coordinated
by the University of Stuttgart (IER), aims at developing an
integrated assessment framework, which includes the assessment of
4
costs and benefits as well as the macro-economic impacts of
emission controls (Reis et al. 2005)[12].
In Belgium, the BAT-Centre of the Flemish Institute for
Technological Research (VITO) started in June 2001, under the
authority of the Flemish Government, with the development of the
Environmental Costing Model (MilieuKostenModel or MKM in
Dutch). The Flemish Government aims at developing a tool (i) to
determine the costs of environmental policy and (ii) to contribute to
a more efficient environmental policy by indicating how
environmental targets can be realised in a cost effective way.
Initially, the model is developed for the industrial emission sources
of SO2, NOx and VOC in Flanders. The choice of this test case is
inspired by the emission targets imposed on Belgium (and
Flanders) by Directive 2001/81/EC of the European Parliament and
of the Council on National Emission Ceilings for certain pollutants.
This paper is structured as follows. First, the methodology and
features of the Environmental Costing Model are described. Next,
the functionalities of the model are demonstrated by means of a
5
numerical example. Finally, an overview is given of the main
conclusions and suggestions for further research are made.
Methodology
Cost efficiency plays a key role in the Environmental Costing
Model. If only one environmental objective, for one pollutant and
few emission sources has to be taken into account, the cost
efficiency analysis is a straightforward exercise. In this case, it is
sufficient to rank possible abatement measures based on their
(marginal) costs and reduction potential and to select the cheapest
measure or combination of measures to realize the environmental
objective. However, often the analysis involves multiple emission
sources, pollutants, abatement measures, interactions and tradeoffs. The least cost solution can not be determined by a simple
overview of the (marginal) costs and emission reduction potential
of abatement measures.
The interactions and trade-offs mentioned above, are taken into
account in the Environmental Costing Model. The model makes it
6
possible to optimize for one or multiple pollutants at the same time
(e.g. What is the least cost solution to reduce emissions? What is
the marginal cost curve for a particular pollutant) and to simulate
scenarios (e.g. What is the impact of more stringent environmental
objectives on the least cost solution?).
Obviously, it is important to have a well-founded and unambiguous
methodology in support of the model. A lot of effort has been put
in making well-considered choices about the definition of e.g.
environmental costs and cost efficiency and the methodology to
analyse the cost efficiency of abatement measures.
Model description
Features of the database
The core of the Environmental Costing Model is a database of
emission sources and abatement measures with their associated
emission reduction potential and annual costs.
7
Emission sources
If emissions for one or more pollutants exceed a certain threshold,
companies in Flanders are legally bounded to report to the Flemish
Environmental Agency (VMM). This reporting obligation relates to
all emission sources and includes for each emission source typical
characteristics such as mass flow, emission concentration, number
of operational hours and energy consumption. The database of the
Flemish Environmental Agency is used to identify and describe
industrial (point) emission sources in the Environmental Costing
Model. Other sources of information are literature, surveys and/or
contacts with e.g. experts and industry federations.
Depending on the data available, emission sources are identified on
the level of a sector or an individual company. The format of the
database makes it possible to describe emission sources either as
individual installations or as so-called ‘reference installations’. A
‘reference installation’ is a representative category of installations
for which the same emission abatement measures are available and
for which a particular abatement measure has similar abatement
results and costs.
8
For each pollutant, emissions are linked to an activity that can be
considered as the source of the pollution e.g. the amount of fuel or
solvent consumed, the amount of products produced. Consequently,
the Environmental Costing Model can be used to forecast
emissions based on the evolution of the activities or emission
factor. Also, it is possible to compare data with the input of other
models e.g. the RAINS model.
Abatement measures
Abatement measures are described by means of their investment
costs, operating costs, lifetime, capacity, reduction efficiency. The
main sources of information are literature, surveys and/or contacts
with e.g. experts and industry federations.
Abatement measures are defined as exclusive. This means that two
or more abatement measures can not be implemented at the same
time on a particular emission source. Of course, an abatement
measure can be defined in the model as a combination of
techniques.
9
The format of the database makes it possible to describe processintegrated measures (e.g. fuel switch) and end-of-pipe techniques
(e.g. flue gas cleaning). If surveys and/or contacts with e.g. experts
and industry federations show that a particular abatement measure
is implemented, the model can take into account the (exogenous)
implementation for a particular year. A distinction can be made
between:
(1)
The abatement measure is used for its total capacity i.e. the
investment costs and operational costs are taken into account
for 100%.
(2)
The abatement measure is not used for its total capacity i.e.
the investment costs are taken into account for 100%, but the
operational costs depend on the use of the measure.
Features of the algorithm
Mixed integer programming
By means of mixed integer programming the Environmental
Costing Model determines the least-cost combination of abatement
10
measures to satisfy multi-pollutant targets. A mixed integer
programming (or MIP) problem is a problem where some of the
decision variables are constrained to have only integer values in the
optimal solution.
The model can be operated for multiple sources and multiple
pollutants at the same time. Environmental targets can be set at the
overall Flemish level, at the sector level or at the level of a
(reference) installation. If multi-pollutant targets are set, positive or
negative interaction effects between pollutants can be taken into
account, e.g. an incinerator reduces emissions of VOC, but
increases emissions of CO2.
The basic mathematical structure of the Environmental Costing
Model is based on MARKAL (Loulou et al. 2004). MARKAL is a
generic model that represents all energy demand, supply activities
and technologies for a country. As the model is formulated as a
dynamic
optimisation
model,
it
can
produce
alternative
developments for energy supply and demand to achieve emission
reduction goals at least cost. Simultaneously, the model makes
11
prospective energy and emission balances, tests the potential of
new energy technologies and contributes to R&D policy
formulation.
The link with MARKAL has the advantage that other MARKAL
facilities can be integrated in the Environmental Costing Model.
For example: at the moment the model is one-shot dynamic, i.e.
only one future time period (e.g. 2010 for the test case) is
considered in which abatement measures can be implemented and
environmental targets can be imposed. The link with MARKAL
facilitates the adaptation of the Environmental Costing Model to
dynamic modelling. But also other features can be integrated in the
model such as elastic demand and endogenous learning.
Endogenous and exogenous variables
The objective function minimises the sum of the total annual costs
of abatement measures n that can be implemented at various
emission sources k to achieve multi-pollutant targets.
12
Min  c(k )
kK
For all emission sources k, pollutants p and abatement measures n,
the following main constraints are imposed.


e(k,p) =  k , p   X k   1   ak , n   k , n, p   k є K, p є P
 nN

The annual emissions e(k,p) for all emission sources k and
pollutants p depend on the activity level X k  , the emission factor
ε(k,p), the implementation rate a(k,n) and the reduction efficiency
ρ(k,n,p) of abatement measure n. The level of activity per year
X k  is determined exogenously. Consequently, emissions can not
be reduced by changing the activity level (i.e. the amount of
products or energy produced, the amount of solvents consumed).
c(k) =
 ak , n   k , n  X k   bk , n   k , n
nN
13
kєK
The total annual cost c(k) for all emission sources k is the sum of
the annual operating and investment costs of all the abatement
measures that are implemented. The operating costs are defined as
the product of the activity level X k  , the unit cost γ(k,n) (i.e. cost
per unit of activity) and the implementation rate a(k,n) of
abatement measure n. The annual investment cost λ(k,n) is a
function of the binary implementation rate b(k,n).
K
 ek , n   E  p 
pєP
k 1
For all pollutants p, the total emissions (i.e. for all emission sources
k) have to comply with the emission target E  p  . Environmental
targets can be set at the overall Flemish level, at the sector level or
at the level of a (reference) installation.
 ak , n  1
kєK
nN
 k є K, n є N
a(k,n) ≥ 0
14
For all emission sources k, the sum of the implementation rates
a(k,n) of the abatement measures n should not exceed 100%. Of
course, an abatement measure can be defined in the model as a
combination of techniques.
b is binary
 k є K, n є N
b(k,n) ≥ a(k,n)
For all emission sources k, the implementation rate b(k,n) of
abatement measure n is binary, i.e. equal to 0 or 1. The
implementation rate is greater than or equal to a(k,n). This implies
that an abatement measure n can be implemented (investment
costs) without being operational (no operating costs).
Numerical illustration
Description of the test case
Directive 2001/81/EC of the European Parliament and of the
Council on National Emission Ceilings (NECs) for certain
15
pollutants sets upper limits for each Member State for the total
emissions in 2010 of the four pollutants responsible for
acidification, eutrophication and ground-level ozone pollution
(SO2, NOx, VOC and NH3). The Directive leaves it largely to the
Member States to decide which measures to take in order to
comply. In 2010 the Flemish Region of Belgium has to comply
with the following emission ceilings: 65,8 kton SO2, 58,3 kton
NOx, 70,9 kton VOC and 45,0 kton NH3.
In order to meet these ambitious emission ceilings, the emission
reduction potential of the different polluters has to be carefully
balanced against each other. Under the authority of the Flemish
Environmental Administration AMINAL, Ecolas and VITO
developed a methodology to allocate emission ceilings to different
polluters in the most cost effective way, taking into account the
economic feasibility and cost efficiency of potential abatement
measures (Van Biervliet et al. 2005). The methodology was applied
to the industrial emission sources of SO2, NOx and VOC in
Flanders. As Flanders has to comply with the emission ceilings in
16
2010, the optimization and simulations were carried out for the
year 2010.
The Environmental Costing Model for Flanders was used to
determine the least cost combination of abatement measures to
satisfy the multi-pollutant target for SO2, NOx and VOC in 2010. In
order to test the sensitivity of the model, the most cost effective
solution was also determined for more stringent environmental
targets (i.e. reduction of the emission ceilings with 5% and 10%)
and less stringent environmental targets (i.e. increase of emission
ceilings with 5% and 10%).
Results
Techno-economic database
The test case resulted in a techno-economic database that describes
1.001 (reference) installations and 2.153 abatement measures for
the year 2010. The level of detail (e.g. source specific compared to
generic) varies between sectors.
17
The (reference) emissions for the year 2010 were calculated based
on projections concerning the activity level, the energy
consumption and the energy efficiency, and the degree of
implementation of abatement measures between 2000 and 2010.
Environmental regulation that would come into force in Flanders
between 2000 and 2010 (e.g. the Solvent Directive 1999/13/EC),
was not taken into account. The total (reference) emissions of
stationary sources in Flanders in 2010 were estimated at 117 kton
SO2, 82 kton NOx and 91 kton VOC. Table 1 presents a more
detailed overview per sector of the estimated emissions of SO2,
NOx and VOC for 2010.
18
Table 1: estimated emissions of SO2, NOx and VOC per sector for 2010
Emissions 2010 (ton)
Sector
SO2
Automobile industry
NOx
VOC
30
201
4.580
6.801
13.182
17.692
179
524
16.032
32.269
25.869
0
905
1.508
58
5.453
2.320
1.008
3
21
6.813
205
1.805
25
8.123
7.434
891
300
163
0
11.287
677
650
Non ferrous metals
3.021
742
1.293
Paper industry
1.152
249
3
576
265
1.586
26.918
7.912
10.737
59
170
361
1.291
864
42
18.635
17.821
29.437
Chemical industry
Coatings
Power plants
Glass industry
Glasshouse horticulture
Printing industry
Municipal waste incineration
Iron and steel
Intensive livestock farming
Ceramics
Production of vegetable oils
Refineries
Textile industry
Food industry
Other sources of SO2, NOX and VOC
Marginal cost curves
The Environmental Costing Model was used to generate marginal
cost curves. These curves describe for one pollutant the most cost
effective combination of abatement measures for various emission
reductions. Also, the effect on other pollutants was examined.
19
Marginal cost curve for SO2 (see Figure 1). The cost curve for SO2
starts at an emission level of 117 kton. Emissions can be reduced to
37 kton or there is a maximum reduction potential of 68%. In order
to realize the emission ceiling of 65,8 kton, abatement measures
with a marginal cost of less than 2,5 EUR per kg have to be
implemented. The additional effect on NOx and CO2 is limited,
with an emission reduction of 3 kton and 376 kton respectively.
The reduction of SO2 is mainly realized by the sectors ‘power
plants’ (39%), ‘refineries’ (32%), ‘ceramics’ (18%), ‘iron and
steel’ (4%) and ‘non ferrous metals’ (4%).
20
Figure 1: SO2 marginal cost curve for Flanders
+ bonus effect on NOx and CO2
10
9
Marginal cost SO2 [€/kg reduction]
8
7
6
5
4
3
2
1
0
0
10.000
20.000
30.000
40.000
50.000
60.000
70.000
80.000
90.000
100.000
110.000
120.000
Residual emissions
NOx bonus (ton)
CO2 bonus (kton)
SO2 (ton)
SO2 NEC (ton)
Marginal cost curve for NOx (see Figure 2). The cost curve for
NOx starts at an emission level of 82 kton. Emissions can be
reduced to 40 kton, which means that there is a maximum reduction
potential of 51%. In order to realize the emission ceiling of 58,3
kton, abatement measures with a marginal cost of less than 6,6
EUR per kg have to be implemented. The additional effect on SO2
and CO2 is significant with an emission reduction of 9 kton and 513
kton respectively. The reduction of NOx is mainly achieved by the
21
sectors ‘power plants’ (68%), ‘iron and steel’ (14%) and
‘refineries’ (6%).
Figure 2: NOx marginal cost curve for Flanders
+ bonus effect on SO2 and CO2
10
Marginal cost NOx [EUR per kg reduction]
9
8
7
6
5
4
3
2
1
0
0
10.000
20.000
30.000
40.000
50.000
60.000
70.000
80.000
90.000
100.000
110.000
120.000
Residual emissions
SO2 bonus (ton)
CO2 bonus (kton)
NOx (ton)
NOx NEC (ton)
Marginal cost curve for VOC (see Figure 3). The cost curve for
VOC starts at 91 kton and emissions can be reduced to 65 kton;
which means that there is a maximal reduction potential of 29%. In
order to realize the emission ceiling of 70,9 kton abatement
measures, with a marginal cost of less than 3,1 EUR per kg have to
22
be implemented. The abatement measures that are implemented for
the reduction of VOC have no effect on SO2 or NOx. The reduction
of VOC is mainly achieved by the sectors ‘coatings’ (i.e. metal and
plastic) (21%), ‘refineries’ (18%) and ‘printing industry’ (14%).
Figure 3: VOC marginal cost curve for Flanders
10
9
Marginal cost VOC [EUR per kg reduction]
8
7
6
5
4
3
2
1
0
0
10.000
20.000
30.000
40.000
50.000
60.000
70.000
80.000
90.000
100.000
110.000
120.000
Residual emissions
VOC (ton)
VOC NEC (ton)
Optimal solution
As mentioned above, the Environmental Costing Model was used
to determine the optimal (i.e. least cost or cost effective) allocation
of emission reduction efforts to achieve the emission ceilings for
23
SO2, NOx and VOC (for stationary sources) in 2010. In the
calculations a discount rate of 5% was used.
The model calculated that the total annual costs for Flanders to
comply with the emission ceilings in 2010 are 92 million EUR or
0,05% of the annual turnover of the sectors ‘industry’, ‘energy’ and
‘agriculture’ in Flanders in 2003. The sectors with the highest total
annual costs are ‘power plants’ (30 million EUR), ‘refineries’ (21
million EUR) and ‘glasshouse horticulture’ (9 million EUR). Table
2 presents a more detailed overview of the emission reduction and
the total annual costs per sector.
24
Table 2: emission reduction and total annual costs per sector
Emission reduction (ton)
Total annual cost
(kEUR)
Sector
SO2
Automobile industry
NOx
VOC
0
43
0
36
1.337
2.015
5.455
11.612
0
23
7.709
7.753
19.869
14.269
0
30.031
0
319
0
33
3.643
953
0
9.013
Printing industry
2
1
2.954
1.151
Municipal waste incineration
0
0
0
0
2.005
3.257
0
5.975
0
0
0
0
7.362
2
-3
3.830
402
37
-4
467
57
66
-2
54
0
0
476
448
16.237
2.227
3.717
20.961
0
0
0
0
171
256
5
161
0
50
0
8
Chemical industry
Coatings
Power plants
Glass industry
Glasshouse horticulture
Iron and steel
Intensive livestock farming
Ceramics
Non ferrous metals
Paper industry
Production of vegetable oils
Refineries
Textile industry
Food industry
Other sources of SO2, NOx, VOC
These results illustrate the added value of the model as a tool to
determine the least-cost combination of abatement measures for
multiple pollutants at the same time. If the optimal solution is
determined for each pollutant separately (see marginal cost curves),
25
the total annual cost for Flanders to comply with the emission
ceilings in 2010 is overestimated with 20 million EUR (+21%).
Emission ceilings 5 and 10% more stringent
If the emission ceilings for SO2, NOx and VOC are 5% more
stringent, total annual costs exceed 119 million EUR, i.e. an
increase of 30% in comparison with NEC. It has to be noticed that
the reduction of NOx plays a key role in the selection of abatement
measures that can reduce emissions of boilers and furnaces. If only
the emission ceiling for NOx is reduced with 5%, the total annual
costs increase with 9% to 100 million EUR. If the emission ceilings
for SO2 and NOx are 10% more stringent, the total annual costs
increase with 41% to 129 million EUR.
Emission ceilings 5% and 10% less stringent
If the emission ceilings for SO2, NOx and VOC are 5% less
stringent, the total annual costs are 72 million EUR, i.e. a decrease
of 22% in comparison with NEC. If the emission ceiling for SO2,
NOx and VOC are 10% less stringent, the total annual costs
decrease with 38% to 57 million EUR.
26
Conclusions and suggestions for further research
The results illustrate the added value of the Environmental Costing
Model as a tool to determine the least-cost combination of
abatement measures to comply with multi-pollutant targets for SO2,
NOx and VOC. If the optimal solution is determined for each
pollutant separately, the total annual costs are overestimated. In
addition to the optimal solution, other scenarios can be simulated to
support the policy makers in making well-founded policy choices.
Although the test case focuses on the industrial emission sources of
SO2, NOx and VOC in Flanders, the format of the database and the
structure of the algorithm allows for application of the model in
other countries or regions. Also, analyses on different scales are
possible as the model can be operated at the level of a country or
region, at the level of a sector or at the level of a (reference)
installation.
However, the model has certain limitations that can be subject of
further research. One of the most important limitations of the
current version of the model is that it is static. Consequently, the
27
(remaining) lifetime of the existing installations and the abatement
measures is not taken into account. Interesting questions such as
the time-legged effect of abatement measures can not be answered
with the current version of the model.
As environmental regulation changes continuously, the database of
the model has to be extended in order to optimize and simulate
beyond 2010. In addition to SO2, NOx and VOC, also the pollutants
CO2 en particulate matter have to be taken into account.
28
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