110.75 g NO3

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110.75 g NO3
Table of Contents
Summary.......................................................................................................................... 5
Resumen........................................................................................................................... 7
1 Introduction ............................................................................................................... 9
1.1
Problem definition, research question and method.......................................................10
2 Life Cycle Assessment (LCA)................................................................................. 11
2.1
2.2
2.3
2.4
2.5
2.6
LCA framework............................................................................................................11
Elements of Life Cycle Impact Assessment (LCIA) ....................................................12
Characterisation............................................................................................................13
The fate and exposure factors.......................................................................................14
Temporal aspects ..........................................................................................................14
Concluding remarks......................................................................................................14
3 Nutrients enrichment and further effects ............................................................. 15
3.1
3.2
3.3
Relevant nutrients for aquatic eutrophication...............................................................15
Effect chain of the nutrient enrichment ........................................................................17
Concluding remarks......................................................................................................19
4 The oxygen depletion model ................................................................................... 21
4.1
4.2
4.3
Dissolved Oxygen reaction kinetics .............................................................................21
Calculations of the effect factors and the characterisation factors ...............................25
Concluding remarks......................................................................................................26
5 Results ...................................................................................................................... 27
5.1
5.2
5.3
Effect factors ................................................................................................................27
Characterisation factors ................................................................................................30
Comparison...................................................................................................................31
6 Discussion................................................................................................................. 33
6.1
6.2
6.3
6.4
The model.....................................................................................................................33
The data ........................................................................................................................33
The calculations............................................................................................................34
The results ....................................................................................................................34
7 Conclusions .............................................................................................................. 37
Appendix 1: Variable values ........................................................................................ 43
Appendix 2: Reference concentration......................................................................... 45
Appendix 3: Water temperatures................................................................................ 47
Appendix 4: Comparison of characterisation factors................................................ 49
Appendix 5: Depth profiles of photosynthetic rate.................................................... 53
Summary
The conventional evaluation of aquatic eutrophication in Life Cycle Assessment (LCA) expresses the
contribution of nitrogen and/or phosphorus emissions to biomass production in terms of the equivalent
emission of a reference substance. This assessment does not address environmental mechanisms (fate,
exposure or effects), neither spatial differentiation. In order to improve the accordance between the
actual impact of aquatic eutrophication and the impact predicted in LCA, characterisation factors need
to model site dependent environmental mechanisms. Following this principle, Potting et al. (2004)
developed fate-exposure factors from nitrogen and phosphorus sources for European inland and
marine waters. The present research aims to complete the modelling of the environmental
mechanisms by defining spatial differentiated effect factors that can later be use to calculate the
characterisation factors.
Nitrogen and phosphorus compounds contribute mainly to cultural aquatic eutrophication and are
major nutrients that limit aquatic plant growth. A too large input of these nutrients lead to ecological
cause-effect chain and oxygen depletion is one of the effects. Oxygen depletion can be the result of
oxygen-consuming processes, e.g. decomposition of phytoplankton excess (direct effects), and at the
same time, it may lead to final effects on plant and animal communities, e.g. loss of habitats, fish kills
and phosphorus releases. Oxygen depletion is an effect closer to the endpoints of the cause-effect
chain of aquatic eutrophication and by defining it as the category indicator, the assessment of aquatic
eutrophication in LCA becomes more relevant.
In order to calculate the effect (oxygen depletion) factors, the dissolved oxygen (DO) concentration in
water has to be modelled. The model uses the basic principle of mass balance and includes the process
of reareation from the atmosphere and the biochemical reactions of dissolved oxygen: photosynthesis,
phytoplankton respiration, organic matter oxidation and nitrification. The eutrophication components
are dissolved inorganic nitrogen and phosphorus, phytoplankton and organic matter. Three main
assumptions are defined to obtain the effect factors. Firstly, because LCA does not address temporal
aspects, the dissolved oxygen concentration in water is modelled under steady state conditions.
Nutrient limitation is the second assumption: phosphorus limits biomass growth in inland waters,
whereas nitrogen does it in marine waters. Thirdly, the magnitude of the emissions of nutrients from a
product lifecycle contribute marginal to the reference concentrations in the aquatic systems.
Following this assumptions and defining the oxygen depletion with respect to the saturation level, the
effect factor Effs,e after substance s is emitted to water e, is calculated as the ratio of oxygen depletion
per substance concentration in the water.
Finally, the characterisation factors are the aggregation of the multiplications between the fateexposure factors and the effect factors here calculated for all waters (inland or marine waters) per
country.
The discussion is done at the level of the DO model definition, the data used, the assumptions in the
calculation of the effect factors and the results. Attention is given to physical process and components
that are not included in the model and that can have a relevant influence in the effect of oxygen
depletion in waters. The used values of the variables and the assumptions are discussed in order to
obtain more accurate site dependent effect factors. For example, the limiting factor of light intensity
can include site dependent water depths, while the limiting factor of nutrients can address spatial
differentiated limiting nutrients, especially in seas where the limitation of nitrogen stays unclear.
5
6
Resumen
La forma convencional de asesorar la eutroficación acuática en la Evaluación del Ciclo de Vida
(LCA) es a través de la contribución de las emissiones de nitrógeno o fósforo a la producción de
biomasa en términos de la emissión equivalente de una substancia de referencia. Esta evaluación no
señala los mechanismos ambientales (transporte, exposisción o efectos), como tampoco
differenciación espacial. Para mejorar el acuerdo entre el impacto actual de la eutroficación acuática y
el impact predicado por LCA, los factors de caracterisación necesitan modelar mecanismos
ambientales que dependan de cada lugar en específico. Siguiendo este principio, Potting et al. (2004)
desarrollo factors de transporte-exposición provenientes de fuentes de nitrógeno y fósforo para aguas
superficiales y marinas dentro de Europa. La presente investigación pretende completar el
modelamiento de los mechanismos ambientales a través de la definición de factors del efecto que
pueden ser utilizados posteriormente en la calculación de los factors de characterisación.
Los compuestos de nitrógeno y fósforo contribuyen principalmente a la eutroficación acuática cultural
y son nutrientes mayores en la limitación del crecimiento de plantas acuáticas. Un gran input de
nutrientes provoca una cadena ecológica causa-efecto, donde la reducción de oxígeno es uno de los
efectos. La reducción de oxígeno puede ser el resultado de procesos que consumen oxígeno, como por
ejemplo la descomposición del exceso de fitoplancton (efecto directo), y al mismo tiempo, puede
generar efectos finales en comunidades de plantas y animales, como la pérdida de habitats, la muerte
de peces o la eliminación de fósforo. La reducción de oxígeno es un efecto cercano al punto final de la
cadena causa-efecto de la eutroficación acuática y al definirla como el indicador de la categoría, la
evaluación de la eutroficación acuática dentro de LCA es más relevante.
Con el fin de calcular los factores del efecto (reducción de oxígeno), la concentración de oxígeno
disuelto en el agua tiene que ser modelalda. El modelo sigue el principio del balance de masa e
incluye el proceso de reaireación de la atmósfera y las reacciones bioquímicas del oxígeno disuelto:
fotosíntesis, respiración del fitoplancton, oxidación de la materia orgánica y nitrificación. Los
componentes de la eutroficación son las formas inorgánicas del nitrógeno y fósforo disuelto, el
fitoplancton y la materia orgánica. Tres supuestos fueron definidos para poder obtener los factors del
efecto. Primero, debido a que LCA no incluye aspectos temporales, la concentración de oxígeno
disuelto en el agua es modelada bajo condiciones de estado estacionario. La limitación del nutriente es
el segundo supuesto: fósforo limita el crecimineto de biomasa en aguas superficiales, mientras
nitrógeno lo hace en aguas marinas. Tercero, la magnitud the las emissiones de nutrientes del ciclo de
vida de un producto son marginales comparadas con las concentraciones de referencia en el agua.
Siguiendo estos supuestos y definiendo la reducción de oxígeno con respecto al nivel de saturación, el
factor del efecto Effs,e luego que la substancia s es emitida al agua e, es calculado como el radio de
reducción de oxígeno por concentración de la substancia en el agua. Finalmente, los factores de
caracterisación son la suma de las multilpicaciones entre los factores de transporte-exposición y los
factores del efecto de cada agua (superficial o marina) en un mismo país.
La discusión es presentada al nivel de la definición del modelo, los datos usados, los supuestos en las
calculaciones de los factors del efecto y los resultados. Atención se da a procesos físicos y
componentes que no son incluidos en el modelo pero que pueden tener una gran influencia en el
efecto de reducción de oxígeno en las aguas. Los valores usados para las variables y los supuestos son
discutidos para obtener factores del efecto mas precisos dependiendo de cada agua en particular. Por
ejemplo, la limitación de la intensidad de luz puede incluir la profundidad de cada agua, mientras la
limitación de los nutrientes puede senalar el nutriente limitante en cada agua, especialmente en mares
donde la limitación de nitrógeno no esta del todo clara.
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8
1
Introduction
Aquatic eutrophication can be defined as the enrichment of the aquatic environment with nutrients as
e.g. nitrogen and phosphorous compounds. The aquatic environment here mentioned consists of
inland waters (lakes, reservoirs, and rivers), and marine waters (coastal waters and deep seas). An
increased input of nutrients may push stable communities out of balance and lead through a chain of
effects to a shift of the biological structure. For example, the oxygen depletion, one of the effects of
aquatic eutrophication, experienced in the southern Kattegat water bottom between the years 1985-88,
led the fishery for Norwegian lobster to almost stop in this area until 1999 (Ærtebjerg et al., 2001).
Nutrient enrichment is seen as a widespread problem around the world. Therefore, Life Cycle Impact
Assessment (LCIA) considers aquatic eutrophication as an impact category.
LCIA is a phase of Life Cycle Assessment (LCA) that aims to characterise and assess the magnitude
and significance of the potential environmental impacts of the inputs and outputs of a product system
(Jensen et al., 1997). According to these authors, this assessment has to assign each input and output
to the selected impact category and next calculates the contribution to the selected impact by
converting the input and outputs with the help of characterisation factors into the category indicators.
In the case of aquatic eutrophication, conventional characterisation factors convert the nitrogen and/or
phosphorous emissions into their potential contribution to biomass (algae) production in terms of the
equivalent emission of a reference substance, e.g. ammonia or phosphate (Potting et al., 2004a).
Aquatic eutrophication is a difficult impact category. On the one hand, it has different impact
pathways since nutrients can be emitted to land, air and water. For example, when looking at the
airborne nutrients, only a fraction of them will be deposited directly in the aquatic environment. The
rest deposits on land and only a percentage of them may reach the water system by leaching and/or
run-off. On the other hand, these pathways and the magnitude of the impact depend on sitedependence aspects. The characteristics of the aquatic environment, e.g. the residence time, the water
temperature or the depth, determine to a large extent the sensitivity of the aquatic environment to the
nutrient load (Ærtebjerg et al., 2001). Moreover, different nutrients limit different aquatic systems. In
Europe, nitrogen typically limits production of algae biomass in most marine waters, whereas
phosphorous does so in fresh waters (Potting et al., 2002).
Therefore, LCIA needs to perform spatial differentiation for aquatic eutrophication, instead of relying
on site generic characterisation factors. The location of the emission source; the mode of entry and
transport of an emission into the environment; the sensitivity of the receiving/affected aquatic
environments, are variables that could be taken into consideration (Pennington et al., 2004).
Especially when the systems to compare are more alike, spatial differentiation will increase the
discriminating power of LCIA (Udo de Haes et al., 1999).
In the last few years sets of region-dependent characterisation factors for aquatic eutrophication have
been proposed (Potting et al., 2004b; Seppälä et al., 2004) All these factors cover fate processes but
do not include effect. Potting et al. (2004) establish site-dependent fate-exposure1 factors for inland
and marine waters of 32 European countries. However, in order to obtain an indicator that is closer to
the expected occurrence of the actual aquatic eutrophication, Potting et al. (2002) recommend using
site-dependent characterisation factors that not only include an appropriate estimate of fate and
exposure, but also the marginal effect or effect per product unit of adding substances to the specific
region. For example, as it was mentioned above, a change in the nutrient balance may lead to a shift in
species composition. But the specie being shifted depends on site-specific aspects. The limitation of
assessing aquatic eutrophication in terms of effects is mainly because of the present state-of-art in
modelling this impact assessment (Potting et al., 2004a).
1
Fate modelling relates to all emission, transport and transformation processes of the released substance;
exposure modelling relates to all intake processes (Udo de Haes et al., 1999).
9
1.1 Problem definition, research question and method
Conventional LCA uses site generic characterisation factors that address the potential contribution of
the inputs and outputs of a product lifecycle to the algal growth. Aquatic eutrophication is a difficult
impact category, since it has different impact pathways and relays in site-dependence aspects of the
aquatic environment. The lack of a spatial differentiated effect assessment for aquatic eutrophication
in LCA seems to limit the feasibility of obtaining a category indicator that is closer to the expected
occurrence of the actual impact.
With this in consideration, the research question is then:
Can characterisation factors for aquatic eutrophication cover spatial differentiated effect
assessment? Do these factors cover fate and exposure in a consistent way?
The method followed is presented here as the outline of this research, as well. This research starts
with a literature review on Life Cycle Assessment (LCA) and its framework, with especial attention to
LCIA and aquatic eutrophication as an impact indicator. Main features here were the characterisation
modelling, the focus of this research, and the spatial differentiation and its feasibility of covering
effects. In addition, temporal aspects of LCIA were also studied. This review is presented in Chapter 2
and was based mainly on present LCA articles.
Then, attention is given to aquatic eutrophication and its further effects, and is summarised in Chapter
3. This chapter discusses, based on literature, the nutrients that cause aquatic eutrophication in both
inland and marine waters, and selects those human sources that limit the algal growth. The algal
growth is defined as the primary effect, but an ecological chain of further effects can be distinguished,
e.g. oxygen depletion. The first step in the method is the selection of an effect from the cause-effect
chain of aquatic eutrophication, since LCIA assesses an impact category through only one effect
factor. This research studies the oxygen depletion of waters due to aquatic environment as the effect
factor.
Chapter 4 presents the model of dissolved oxygen in waters defined in this research (second step).
Here the boundaries of the model are given. The model is based on the conventional assess of the
concentration of dissolved oxygen in water oxygen under aquatic eutrophication conditions, but it is
adapted to the LCIA context. This means that the factors need to relate to the compound emitted and
the aquatic ecosystem affected.
Through this model, the oxygen depletion experienced in waters can be studied. The following step is
the calculation of effect factors for the different aquatic environments. Then, the characterisation
factors are calculated with the help of the effect factors and fate-exposure factors (Chapter 4). The
fate-exposure factors used in this research are those developed by Potting et al. (2004) for inland and
marine waters of 32 countries.
Chapter 5 presents the results for the effect factors and the characterisation factors. Chapter 6
addresses the discussions with regard to the model definition, the data availability and to the results.
In addition, this chapter includes the conclusions of this research.
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2
Life Cycle Assessment (LCA)
Life Cycle Assessment (LCA) is a methodology for estimating and assessing the overall potential
environmental impacts attributable to the life cycle of a product2. These impacts may be caused by the
energy and materials usages (inputs), and the releases to the environment (outputs) from each stage of
a product life cycle. A life cycle includes a series of processes running from extraction of raw
materials, through design and formulation, processing, manufacturing, packaging, distribution, use,
reuse, recycling and ultimately, waste disposal. Even when there are other environmental system
analysis tools (e.g. Risk Assessment, Environmental Impact Assessment), the cradle-to-grave
approach combined with its focus on the functions that products provide, makes LCA unique
(Finnveden, 2000).
Section 2.1 presents the framework of LCA. A closer look to its phase Life Cycle Impact Assessment
and its elements is given in Section 2.2. Within the characterisation, the modelling of conversion
factors, the main focus of this research, is a key issue and is presented in Section 2.2, while the state
of art in the cause effect chain is presented in Section 2.4. Finally, Section 2.5 reviews the temporal
aspects within LCIA and Section 2.6 gives some concluding remarks.
2.1 LCA framework
The LCA framework, that is defined by ISO (ISO 14040, 1997) and presented in Figure 2.1, consists
of four phases:
LCA Framework
Goal
and
Scope
Definition
Life Cycle
Inventory
Interpretation
Direct Applications:
−
Product
Development
and Improvement
−
Strategic Planning
−
Public Policy Making
−
Marketing
− Other
Life Cycle
Impact
Assessment
Figure 2.1. ISO Framework for LCA (ISO 14040, 1997).
a) Goal and Scope Definition. In order to guide the entire process and to ensure meaningful results,
this phase defines the purpose and method of including environmental impacts of a product life cycle
into the decision-making process. This phase also defines the functional unit and identifies processes
(boundaries), input and output data and environmental effects to be considered in the assessment. The
functional unit is a quantitative description of the service performance of a product system (Rebitzer
et al., 2004) and sets a common basis of comparison for two or more products, or even for an
improved product and its previous version.
2
The term product within this research will refer to any product, process and service.
11
b) Life Cycle Inventory. This phase identifies and quantifies the energy, water and material
consumption (inputs) and environmental releases (outputs) for all single stages in the life cycle, thus
also for the whole life cycle. All data collected in the inventory are expressed as quantities per
functional unit. Depending on the level of accuracy required to inform the decision-makers involved
in the process, the data may address site-specific information (EPA, 2001).
c) Life Cycle Impact Assessment (LCIA). What are the impacts of 25 g of nitrogen or phosphorus
emissions per kg of product released into the water? Which is worse? What are their potential
contributions to aquatic eutrophication? In order to provide a more precise basis of comparison, LCIA
quantifies and assesses the magnitude and relevance of the potential impacts and effects of energy,
water and material usages, as well as environmental releases. The result of this phase is a checklist
where the relative differences in potential environmental impacts for each product are shown. This
research focuses within LCIA.
d) Life Cycle Interpretation. The last phase evaluates the results of the inventory and LCIA to select
the preferred product with a clear understanding of the uncertainty and the assumptions used to
generate the results.
2.2 Elements of Life Cycle Impact Assessment (LCIA)
LCIA contains the following main elements: Impact category definition, Classification,
Characterisation, Normalisation and Valuation/weighting. According to the International
Organisation of Standardisation, the first three steps are mandatory steps for an LCIA and the others
are optional steps depending on the goal and scope of the study (Udo de Haes et al., 1999).
The Impact category definition identifies the relevant environmental impact categories. The
commonly used impact categories are global warming, stratospheric ozone depletion, acidification,
eutrophication (aquatic and terrestrial), photochemical smog, toxicity (terrestrial and aquatic), human
health, resource depletion and land use. This element is basically part of the Goal and scope definition
phase of LCA.
Classification assigns the environmental input and output data of the inventory to the impact
categories selected. Figure 2.2 examplifies this classifying nitrogen (N) and phosphorus (P) emissions
to aquatic eutrophication. Some outputs contribute to different impact categories and therefore, they
have to be mentioned twice.
The element Characterisation, the main focus of this research, aims to calculate science-based factors
in order to convert the contribution of the inventory data to an impact category into category
indicators. A key issue in the characterisation modelling is that each impact category should have a
specific model to relate LCI data to the indicator (Jensen et al., 1997). This is further elaborated in
Section 2.3
Normalisation expresses the category indicators in a way that can be compared among impact
categories (e.g. comparing the aquatic eutrophication impact of P and N for the two options). The
element ‘grouping’ involves sorting or ranking the indicators e.g. by location (local, regional, and
global) or emissions (water and air).
The element Valuation/weighting assigns weights or relative values to the different impact categories
based on their importance or relevance to facilitate comparison across indicators (or normalised
results). The weighting step is made in cases when the impact assessment results alone do not provide
sufficient information for decision-making (EPA, 2001).
12
Life Cycle Inventory results
Input and Output per product unit
kg N, SO2, HCL, P,
etc per product unit
LCIA Mandatory Elements
LCI results
assigned to impact
categories
Impact categories
Aquatic Eutrophication
kg N and P per product unit
Model - Characterisation factors
Category
Indicators
-
PO4
Characterisa
Figure 2.2. Concept of indicators (Udo de Haes et al., 1999)
2.3 Characterisation
Figure 2.3 presents how typically an impact indicator can be calculated (EPA, 2001) and gives an
example of the conventional calculation for aquatic eutrophication. In this equation, the inventory data
can be an emission in terms of the mass released into the environment per functional unit (25 g
waterborne N/ kg product), while the conversion or characterisation factor can e.g. linearly express
the contribution of a unit mass of an emission to an impact category (4.43 g NO3- / g N). The
conventional characterisation factors for aquatic eutrophication express the contribution of N and/or P
emissions to biomass production in terms of the equivalent emission of a reference substance (NO3– or
PO4–). Basically, this is only adding together emissions and thus nor addressing fate, exposures or
effects, neither spatial differentiation.
Inventory Data * Characterisation Factor = Category Indicator
25 g waterborne
N emission per
kg product
*
4.43 g NO3 –
per g N
=
110.75 g NO3 –
per kg product
Figure 2.3. Conventional calculation of category indicator. Example for aquatic eutrophication
General principles have been presented to guide the establishment of characterisation factors (Potting
et al., 2004c; Udo de Haes et al., 1999). Two principles are relevant for this research: the extent to
which environmental mechanisms are modelled in the cause-effect chain, and the performance of
spatial differentiation in the characterisation modelling. These principles aims to improve the
accordance between the expected occurrence of actual impact and the impact predicted in LCA.
The environmental mechanisms correspond to fate, exposure or effect processes. Fate modelling
relates to all environmental processes relating to the emission, transport, and transformation of the
releases, while exposure modelling relates to the concentration of deposition that reaches the
receptors. These environmental mechanisms have to be included in the characterisation modelling to
link the inventory inputs and outputs to a specific impact category. In principle, the characterisation
factors can be defined anywhere in the cause-effect chain, but in order to get closer to the actual
13
impact, there is a tendency to define them closer to the endpoints, since it will make the indicator
more environmental relevant.
Spatial differences in fate and exposure mechanisms or in sensitivity for effects, as well as differences
in the location of the generating release and in its mode of entry into the environment, require the
performance of spatial differentiation in the characterisation modelling (second principle). Usually
LCIA relies on site generic characterisation factors, even when the Life Cycle Inventory can relate to a
large number of sites and locations. Spatial differentiation will increase the discriminating power of
LCIA when the systems to compare are more alike. Moreover, the selection of site-specific impact
models can help to reduce the limitations of the impact assessment’s accuracy (EPA, 2001). As
mention in Section 2.2 the inventory can relate to a very large number of sites and locations.
However, these attributes can make LCA a more complex tool (Pennington et al., 2004)
2.4 The fate and exposure factors
Following the principles above mentioned, Potting et al. (2004) developed fate-exposure factors for
101 rivers and 41 coastal seas in 32 European countries with the help of the Cause effect Relation
Model to Environmental Negotiations (CARMEN model). The model is one-layer GIS based model,
which aims to analyse and evaluate strategies to reduce nitrogen and phosphorus loading of inland and
marine waters in Europe. The model considers three main sources for nitrogen and phosphorus to
surface waters: agriculture, municipal wastewater and atmospheric deposition (only for nitrogen). The
strength of this model is a simulation of the large scale transport through the soil and the water of
nitrogen and phosphorus compounds from their sources to the European coastal seas (Beusen, not
publised). However, the CARMEN model does actually not contain an effect assessment whether
nutrient loading actually results into biomass growth and what ecological effects this has on water.
Finally, the fate-exposure factors relate the amount of nutrient released in a given country to its share
to eutrophication of European inland waters and coastal seas.
2.5 Temporal aspects
LCA essentially integrates over time. This implies that all impacts, irrespective of the moment that
they occur, are equally included (Udo de Haes et al., 1999). However, it is not clear whether this
integration relates to the residence times of the relevant substance or to the duration of the impact
(Potting et al., 2002). This authors understand integration over time as the period over which the
relevant substances directly exert their impact. The lack of a time dimension in the Life Cycle
Inventory limits a proper modelling of the concentration(Potting, 2000). Some characterisation models
usually assume steady state conditions for the assessed compound in the receiving environment. Then,
time characteristics of the emission are no longer relevant.
2.6 Concluding remarks
Characterisation aims to calculate conversion factors to convert the relative contribution of each
inventory data to a specific impact category into category indicators. Conventionally assessment of
aquatic eutrophication expresses the contribution of N and/or P emissions to biomass production in
terms of the equivalent emission of a reference substance. It does not address fate, exposures or
effects, neither spatial differentiation. In order to improve the accordance between the actual impact
and the impact predicted in LCA, characterisation factors need to model the environmental
mechanisms, as well as address spatial differentiation. Following this, Potting et al. (2004) developed
fate-exposure factors for 101 rivers and 41 coastal seas in 32 European countries. This research aims
to complete the modelling of the environmental mechanisms by defining spatial differentiated effect
factors that can be later use together with the fate-exposure factors to calculate the characterisation
factors.
14
3
Nutrients enrichment and further effects
Aquatic eutrophication can be defined as the nutrients enrichment of aquatic systems, i.e. inland and
marine waters (Leonard et al., 1999). Aquatic nutrients may come from both natural, e.g. rocks and
sediments, and human sources, e.g. agricultural practices (diffuse sources), municipal wastewater or
industrial emissions (point sources). Human nutrient sources lead to the so-called cultural aquatic
eutrophication, which is assessed through LCA by looking at the releases to the environment from a
product life cycle.
Nutrients can limit the algal growth when the presence of one of these nutrients in plant available
forms is too small (Nijboer et al., 2004). This is the concept of limiting nutrient, which is not a static
thing. The limiting nutrient can change depending on the total supply of all essential nutrients, the
local condition of the aquatic systems, the season, the species composition, and the structure (e.g.
grow from, density) of the community.
Crouzet et al. (1999), reviews the compounds that can be considered to be nutrients in aquatic
systems, and they are discussed in Section 3.1 with emphasis in the human sources and their limiting
character. The chain of further effects due to phosphorus and nitrogen enrichment is described in
section 3.2. Finally, section 3.3 gives some concluding remarks and explains the selection of oxygen
depletion as the effect to be modelled for aquatic eutrophication.
3.1 Relevant nutrients for aquatic eutrophication
Inland waters
The major nutrients in inland waters presented by Crouzet et al. in their report “Nutrients in European
ecosystems” (1999) are phosphorus, nitrogen and inorganic carbon. Plant growth in inland waters, not
affected by human influence, is limited only by the lack of available phosphorus. Phosphorus is
therefore the major limiting nutrient in surface fresh waters and its bioavailable form is phosphate
(PO43-) ion. The main source of phosphorus emissions in densely populated areas is human waste (i.e.
excreta from humans and detergents). The extent to which these emissions are discharged into surface
waters is mainly defined by the level of sewage treatment. The excesses of phosphate fertilisers and
manure that run off, is a second significant source of phosphorus in inland waters.
The major forms of nitrogen that are ultimately bioavailable are ammonia (NH3) and nitrate (NO3-).
Freshwater algae have a marked preference for ammonia nitrogen. Agriculture activities contribute to
over 90 % of atmospheric emissions of ammonia. Airborne nitrogen emissions, including NOx coming
from fossil fuel combustion, can be deposited as reduced nitrogen on inland waters and on land, from
which it finally may be washed out into inland or marine waters. However, deposition of airborne
nitrogen has minor importance for inland waters (Potting et al., 2004). Ammonia can also come from
wastewater. Because of sewage treatment, less than half of the total nitrogen loads to wastewater
reaches surface waters. Nitrate is used in agricultural practices (fertiliser and manure use), and its
excess reaches the surface waters through run off. Another source of nitrogen emissions is fish
farming, which may lead ammonia to reach high concentrations in watersheds.
Inorganic carbon (dissolved carbon dioxide and carbon acid) is another major nutrient in inland
waters. Its presence is controlled by the calco-carbonic equilibrium, in which CO2 is fixed as
carbonate minerals (bioavailable form) instead of been released in the surface layer (AWI, 2002). The
presence of mineral carbon, possibly including sources of organic carbon, in inland waters can be
attributable to human sources.
15
Marine waters
Nitrogen, phosphorus, silicon, inorganic carbon, iron, boron and potassium are relevant nutrients in
marine waters according to Crouzet et al. (1999). Nitrogen exerts an important influence on marine
phytoplankton and seaweed production, as the limiting nutrient. In coastal waters, nitrogen levels
result mainly from human related loads, i.e waterborne nitrogen loads (wastewater), run off (fertiliser
and manure), deposition of airborne ammonia emissions and nitrogen oxide (fossil fuel combustion),
and fish farming.
The amount of bioavailable phosphorus in marine waters is mainly determinate by the speed of
mineralisation of organic phosphorus and the exchange with suspended matter or sediment. Even
when nitrogen is considered as the limiting nutrient in marine waters, this definition stays still unclear.
For example, the nitrogen limitation of the Mediterranean Sea has been discussed, since some data
show phosphorus limitation in these seas (Izzo et al., 1999).
Silicon is the third most common nutrient, after phosphorus and nitrogen, that limits the plant growth
mainly in marine waters (Tallberg, 2004). Silicate or silic acid, Si(OH)4 and its ions, is the
bioavailable form of silicon in the marine system and only limits the growth of the phytoplankton
group diatoms (Ærtebjerg et al., 2001). About three quarters of the primary production (algae) in
coastal water and oceans consist of diatoms (AWI, 2002). However, it is assumed that the supply of
silicate does not come from human activities. Instead, silicon comes naturally from inland water
inputs into coastal waters, or from recycling in open seas.
As in inland waters, inorganic carbon is also essential nutrients in marine waters. However, inorganic
carbon is not considered as a limiting nutrient because of its high concentrations in marine waters.
Iron, boron and potassium are present in significant quantities in marine waters. Iron can be present at
very variable concentrations. It is found in certain minerals and nearly all soils and mineral waters
(EVM, 2003). Iron may control phosphorus post-depositional mobility in sediments, depending on its
oxidation level, (Crouzet et al., 1999), and thus it has an effect in the bioavailability of phosphorus,
rather than as a limiting nutrient.
Boron is naturally found in oceans and sedimentary rocks (EVM, 2003), and therefore not considered
as a limiting nutrient. Boron can be released into water supplies and groundwater through weathering
processes and, to a much smaller extent, through human discharges such as sewage outfalls.
Atmospheric emissions of borate’s (H3BO3) are mainly the result of volatilisation from the sea and
volcanic activity.
Potassium is widely distributed in silicate rocks in marine waters. Fertilisers and nutrients plants are a
potassium anthropogenic source, where it can be found as potassium chloride (EVM, 2003). However,
its effects as limiting nutrient are insignificant (Crouzet et al., 1999).
Table 3.1 summarises the nutrients discussed above and indicates those with anthropogenic sources
and considered as limiting nutrients. It can be concluded that mainly nitrogen and phosphorus
compounds contribute to cultural aquatic eutrophication and they are also the major nutrients that
limit aquatic plant growth. Silicon requires special attention as limiting nutrient in marine waters, but
because it comes from natural sources, it is not studied in this research. While phosphate is considered
a limiting nutrient in inland waters, the situation in marine waters remains unclear. However, for
effects of this research, ammonium and nitrate are considered as the limiting nutrients in marine
waters. Therefore, this research will focus in the aquatic enrichment of phosphorus and nitrogen
compounds, and their further effects.
16
Table 3.1. Nutrient presence in aquatic systems due to human activities and their definition as
limiting nutrient
Inland waters
Human
Limiting
Sources
nutrient
Phosphate (PO43-)
Yes
Yes
Ammonia (NH3)
Yes
No
Nitrate (NO3-)
Yes
No
Inorganic Carbon
Yes
(*)
Silicon (Si)
Iron
Boron
Potassium
(*) controlled by the calco-carbonic equilibrium
Nutrient
Marine waters
Human
Limiting
Sources
nutrient
Yes
No
Yes
Yes
Yes
Yes
No
No
No
Yes
No
No
Small
No
Small
No
3.2 Effect chain of the nutrient enrichment
A too large input of nitrogen and/or phosphorus compounds pushes the stable community of plants
and animals out of balance and may through an ecological effect chain lead to the oxygen depletion of
waters and fish kills. This chain of ecological effect of aquatic eutrophication is presented in Figure
3.1 and discussed below based on the definitions of Baltic On-Line Interactive Geographical and
Environmental Information Service (BOING, 2002).
a) Increase of algae in the water. In order to perform photosynthesis and reproduce, algae depend on
the availability of nutrients and sunlight, and on water temperature. The growth of phytoplankton
(free-floating microscopic algae) and macroalgae is called primary production in the aquatic
environment and they constitute the first and absolutely essential building link in the aquatic food
web. Algal growth is therefore a natural process, but it can become a problem when a large input of
plant–available nutrients leads to a large increase in primary production. A eutrophicated water
system demonstrates almost continuously primary production. Moreover, the quantity and
composition of the bioavailable nutrients change very much. Because algal species may have different
nutrient requirements, some species can benefit from these changes whereas others can not.
Conditions might deteriorate for species that once were dominating, and other species might then take
over because the new conditions suit them just fine.
b) Algae make the water turbid and bloc sunlight. The more algae in the water the more turbid the
water gets. This effect under conditions of eutrophication is a critical feedback for the algae, because
light attenuation limits algae growth (Parslow et al., 2002). This means, for instance, that deeper algae
can not grow because the sunlight can not penetrate deeper the water due to the increase of algae.
c) Increase of zooplankton in the water. Algae constitute food for zooplankton (small free-floating
animals). Zooplankton is the secondary production in the aquatic system and they are eaten by larger
animals, including fish, or by bottom-living animals. Aquatic eutrophication leads to more food for
zooplankton-eating species.
d) Increase of sedimentation on the bottom. The excess of living phytoplankton and zooplankton due
to aquatic eutrophication, that is not eaten while still in water, settles down to the bottom zone. Then,
it becomes food for the bottom-living animals, including fish. This is a normal process up to the point
when the concentrations of sediments are too large and then it becomes a problem.
17
Increase of
Increase of limiting
limiting nutrients
nutrient growth in
in water
the water
More
Moroe
phytoplankton in
the water
Laminated
sediments
Oxygen depletion
More zooplankton
in the water
Submerged plants
disappear
Phosphate
Release
from
sediments
Fish kill and
lifeless bottoms
Water becomes
turbid and sunlight
is been bloqued
Fish community
becomes
dominated by
zooplankton-eating
species
Nitrogen
conservation
Increased
sedimentation
(organic and
inorganic matter)
Excess of
phytoplankton
Figure 3.1. Chain of ecological effects (After Potting et al., 2004)
e) Oxygen depletion. Oxygen depletion as a result of organic pollution is well known. However,
aquatic eutrophication can result in oxygen depletion as well. Primary producers play an important
role in the oxygen balance in water, since respiration occurs during the whole day, while oxygen
production photosynthesis only takes place during daylight (Nijboer et al., 2004). Sediments on the
bottom that are not eaten will decompose. Through decomposition, bacteria break down the organic
matter, consume oxygen and release the nutrients which are bound in the organic matter to recirculate
to the ecosystem. A combined effect of both increased primary production and increased
decomposition rates, results in extremely low oxygen contents, because an increase of algae also
means an increase of sediments. In oxygen-poor deeper bottoms with heavy sedimentation, a higher
risk of oxygen deficiency development can be observed due to the decomposition of the sediments.
Nitrification, is finally another process that consumes oxygen. In this process, ammonia is often
chemically altered into ammonium (NH4+) and nitrite (NO2-) and further, into nitrate (NO3-). An
increase in the ammonia concentrations in waters (aquatic eutrophication) means an increase in
oxygen consumption.
f) Less or no fish and bottom-living animals. Under lowered oxygen conditions, animals respond by
regulating oxygen consumption, but when the situation becomes worse they will eventually leave the
habitat if possible, reduce activity levels or even die (Levinton, 1995). Moreover, less bottom-living
animals are found and when they disappear, laminated sediments form.
g) Laminated sediments. Bottom-living animals play an important role in the cycling of nutrients and
oxygen in the water. In well-oxygenated sediments these animals eat from the sediments, while during
18
digging and shifting of material, they help to oxygenate the sediments. As a result of oxygen depletion
and bottom-living animal deaths the decomposition process is not completely achieved, which can be
seen in the sediment colours.
Conservation of nitrogen. Denitrification is a process in which the water can rid itself of surplus
nitrogen. In this process the denitrifying bacteria remove the oxygen from nitrite and nitrate ions for
their own use, releasing N2 and/or N2O back to the atmosphere. However, denitrification can be
severely hampered and even stop when the bottom is continuously fed with large quantities of organic
matter that cannot be properly decomposed because of oxygen depletion problems. More of the
nitrogen in the organic matter will, instead, be converted into ammonia, which recirculates in the
water and goes back into the system through new algae and thus aggravate the aquatic eutrophication
process.
h) Release of phosphate from sediments. When there is no oxygen left in the sediments, phosphate
will be released. In contrast, when the bottom is rich in oxygen phosphate ions are bound to iron in the
sediments. If the oxygen disappears, these compounds are transformed and the phosphate released
into the water for further circulation.
3.3 Concluding remarks
Nitrogen and phosphorus compounds contribute mainly to cultural aquatic eutrophication and are
major nutrients that limit aquatic plant growth. While phosphate is considered a limiting nutrient in
inland waters, ammonium and nitrate are in marine waters. A too large input of these nutrients pushes
the stable community of phytoplankton, zooplankton and animals, including fish, out of balance.
Oxygen depletion plays an important role as link between the direct effects and the final effects on the
environment. It can be a result of oxygen-consuming processes (direct effects), like nitrification and
decomposition of settled phytoplankton excess. But at the same time, oxygen depletion may lead to
final effects on plant and animal communities, such as the loss of habitats, fish kills and phosphorus
releases. With LCA, the definition of the category indicator closer to the endpoints of the cause-effect
chain makes the indicator more environmental relevant (Udo de Haes et al., 1999). Therefore, this
research considers the oxygen depletion of the aquatic environment as the effect of aquatic
eutrophication to be modelled in LCA.
19
20
4
The oxygen depletion model
The dissolved oxygen (DO) concentration in waters can be affected by physical, chemical and
biological processes, which can lead to oxygen depletion in the water. Physical processes are
advection and dispersion, while biochemical processes refer to the decomposition of biodegradable
materials and nutrient uptake by algae (EPA, 1997). Advection, mainly in streams, represents the
primary transport process of pollutant inflow in the downstream direction. Dispersion represents the
mixing due to vertical and lateral velocity gradients. This research looks at the processes of reareation
from the atmosphere and the biochemical reactions of dissolved oxygen, omitting advection and
diffusion. The biochemical reactions can be photosynthesis by phytoplankton, respiration by
phytoplankton and zooplankton, organic matter oxidation, sediment oxygen demand, nitrification and
denitrification. The sediment oxygen demand (SOD) considers the processes of decomposition of
settled organic matter and respiration of benthic invertebrates. However, because of the complexity
and difficulty to estimated analytically and independently the SOD (EPA, 1997), sediments are
excluded of the model. For simplification reasons denitrification is also omitted in the model.
The eutrophication models (EPA, 1997; Wei-Bing et al., 2002; Iowa DNR, 2004) usually consider the
following functional components: Dissolved inorganic nitrogen (ammonia, nitrite and nitrate),
dissolved inorganic phosphorus (phosphate), phytoplankton, zooplankton and non-living organic
nitrogen and phosphorus. For simplification reasons, the model in this research omits zooplankton and
non-living organic nitrogen and phosphorus. The rest of the components drive the major processes
controlling the destiny of nutrient loads: Nutrient uptake, phytoplankton growth and decay. Figure 4.1
presents a schematic definition of the model of oxygen depletion due to aquatic eutrophication
designed for this research.
The basic principle used to model the DO in water is the mass balance in equilibrium (under steady
state conditions). That means what goes in is equal to what goes out, and therefore there is no
accumulation. Mathematically, it can be presented in Equation 4.1.
reareation + photosynthesis = respiration + oxidationOM + nitrification
4.1
The terms on the left represent, respectively, reaeration and the oxygen production in the
photosynthesis, whereas the terms of the right represent the phytoplankton respiration, the
decomposition of phytoplankton and the oxygen consumption by nitrification. These terms are in the
next section further developed.
4.1 Dissolved Oxygen reaction kinetics
With the exception of oxidation of organic matter and phytoplankton concentration in water, the rest
of the terms of the DO model follow the definitions of EPA (1997). In general, they are referred to the
substance s (ammonia, nitrite, nitrate and phosphate) and/or the water e (inland or marine waters).
This is further explained in section 4.2. The variable values used in the following equations are
considered under average conditions for waters, and are presented in Appendix 1. Only, substance
concentrations in water (Appendix 2) and water temperatures (Appendix 3) are considered site
dependent for each inland and marine waters. The concentrations given are acctually nitrogen and
phosphorus loads (ton) from the CARMEN model taken as concentrations (ton/km3).
21
Phosphorus
concentration
Nitrogen concentration
PO3
NH3
Nutrient uptake
NO2
NO3
Nutrient uptake
PHYTOPLANKTO
N
OM
C-Phyto death
Photosynthes
is
Atmospheric O2
Respiration
OM
oxidation
Nitrification
DISSOLVED OXYGEN (DO)
Reaeration
Figure 4.1. Model diagram for Dissolved Oxygen (DO) concentration in water (After EPA, 1997)
22
Reaeration (EPA, 1997)
If oxygen is removed from the water column and the concentration drops below the saturation level
(DOS), oxygen from the atmosphere is transferred through the surface into the water at a certain rate.
The other way around, if oxygen is added and the water column concentration is greater than the
saturation level, oxygen is transferred from water to the air. Reaeration (g O2/m3-day) takes place only
at the water surface and is expressed in the following equation, where ka is the corrected aeration rate
(day-1), DOS is the oxygen saturation level in water and DO is the initial dissolved oxygen
concentration in water.
reareation s ,e = k a * ( DOS e − DOs ,e )
4.2
Photosynthesis and respiration (EPA, 1997)
Through photosynthesis and respiration, phytoplankton can significantly affect the dissolved oxygen
levels in the water. The daily average oxygen production during the day comes from photosynthesis
(Equation 4.3), while the daily average oxygen reduction at night is due to algal respiration rate
(Equation 4.4). Both are expressed as g O2/m3-day.
α1
α2
µs,e
ρ
PHYs,e
=
=
=
=
=
photosynth esis s ,e = α 1 * µ s ,e * PHYs ,e
4.3
respiration s ,e = α 2 * ρ * PHYs ,e
4.4
Stoichiometric ratio of oxygen production per unit of nitrogen (g O2 /g N)
Stoichiometric ratio of oxygen uptake per unit of nitrogen respired (g O2 /g N)
phytoplankton specific growth rate (day-1)in water
Corrected phytoplankton endogenous respiration rate (day-1)
Initial phytoplankton concentration in water in terms of nitrogen content
(g N/m3)
The phytoplankton specific growth rate (day-1) is modelled as a maximum growth rate µmax (day-1),
reduced by the dimensionless effects of light intensity, temperature and limiting nutrient factors
(Equation 4.5). The limiting factor of light intensity fI (Equation 4.6) says that in the darkness there
is no photosynthesis, but as the light intensity increases gradually some photosynthetic O2 production
takes place (Iowa DNR, 2004). The limiting factor of temperature fT (Equation 4.7) says if
phytoplankton is exposed to a given series of temperature, the photosynthetic capacity varies
exponentially with temperature (Baird et al., 2004). The factor of the limiting nutrient fS (Equation
4.8) says that the nutrient level increases, the phytoplankton growth is initially linearly proportional to
the availability of nutrients. However, as the nutrient level continues to increase, the effect on the
phytoplankton growth is saturated. Such relationship is described by the Monod formulation (Flynn,
2003). The half saturation constant kS (g/ m3) is the limiting nutrient concentration for which fS is half
the maximum growth rate.
µ s ,e = µ max* f I * f T e * f S e
fI =
4.5
I
I + KI
f T e = Q10
4.6
Te − 20
10
4.7
23
fSe =
Ie
KI
Te
LSe
=
=
=
=
LS e
LS e + k S
4.8
Average light intensity in water (W/m2)
Michaelis-Menten half saturation constant for light (W/m2)
Water temperature (°C)
Initial limiting nutrient concentration in water in nitrogen terms (g N/ m3). In the case of
phosphorus, the concentration is expressed in terms of the equivalent emission of
nitrogen through the Redfield ratio (rN/P =7.226)
The initial phytoplankton concentration in water in terms of nitrogen content (g N/m3) is assumed in
this research as the fraction (γ) of limiting nutrient LS that is taken up by the phytoplankton (Equation
4.9).
PHYs ,e = γ * LS e
4.9
Oxidation organic matter (OM)
In the estimation of the amount of oxygen needed in the receiving water to oxidate the organic matter,
two approaches are typically distinguished: Chemical Oxygen Demand (COD) and Biological Oxygen
Demand (BOD). COD estimates the oxygen demand to oxide the total organic matter by chemical
processes, while BOD measures the oxygen demand for biological degradation. The latter is measured
during the first five days (after taking the test), and thus underestimates the total biological oxygen
demand (Kärrman et al., 2001). Moreover, BOD is further increased by nitrification (Myers et al.,
2003). Based on this arguments, the COD approach is used in this research to estimate the organic
matter oxidation. The organic matter refers in this research as the carbon content of dead
phytoplankton. The stable portion of the dissolved organic matter from phytoplankton can be
expressed through the empirical formula C18H24O12 and its oxidation is presented in Equation 4.10
(Kinne, 1978). From this equation, it can be deduced that the stoichiometric ratio of oxygen per unit
of organic matter oxidised (α3) 1.63 g O2. Then, the oxidation of organic matter (g O2 / m3-day) is
presented in Equation 4.11 as it is modelled in this research.
C18 H 24 O12 + 21.8O2 → 18CO2 + 9.5 H 2 0
oxidationOM s ,e = α 3 * δ OM * OM s ,e
4.10
4.11
where δOM is the corrected oxidation rate (day-1) of organic matter and OMs,e corresponds to the
reference concentration of organic matter (g C/m3) which is modelled as the dead phytoplankton
(Equation 4.12).
OM s ,e = α 4 * β * PHYs ,e
4.12
where α4 is the C/N ratio in the phytoplankton (the Redfield ratio), β the % of initial phytoplankton
that dies.
Nitrification (EPA, 1997)
Nitrification involves the oxidation of ammonia through nitrite (Equation 4.13) to nitrate (Equation
4.14).
24
NH 4+ + 1.5O2 → NO2− + H 2 O + 2 H +
4.13
NO2− + 0.5O2 → NO3−
4.14
Stoichiometrically, 3.43 and 1.14 grams of oxygen are required to transform each gram of ammonia
nitrogen to nitrite nitrogen and nitrite nitrogen to nitrate nitrogen, respectively (Kärrman et al., 2001).
The oxygen demand due to nitrification will depend on the nitrogen compound assessed. For the
complete oxidation of ammonia, the oxygen demand per gram of nitrogen is 4.57, while for nitrite is
only 1.14. Nitrate is already oxidised. Then, nitrification (g O2 / m3-day) is modelled in Equation 4.15.
nitrification s ,e = α N * δ N * N e
4.15
where αN is the stoichiometric ratio of oxygen per g nitrogen (ammonia or nitrite), δN is the corrected
nitrogen oxidation rate coefficient (day-1) and Ne is the initial ammonia or nitrite load (g/m3) in water.
4.2 Calculations of the effect factors and the characterisation factors
In order to calculate the effect factors, three assumptions are considered. Firstly, dissolved oxygen
concentration in waters is modelled under steady state (Equation 4.1). Due to the lack of temporal
aspects in LCA, characterisation models assume steady state conditions for the assessed compound in
the receiving environment (Potting, 2000). By replacing Equation 4.2 in Equation 4.1, the following
equation for the concentration of dissolved oxygen (g O2/m3) in water can be obtained:
DOs ,e = DOS e +
photosynthesis s ,e − respiration s ,e − oxidationOM s ,e − nitrification s ,e
ka
4.16
In order to solve Equation 4.16, the terms here presented have to be replaced by equations 4.3 to
4.15. The nutrient concentrations in water are in terms of phosphorus and nitrogen, but these nutrients
can be in the form of phosphate, ammonia, nitrite and nitrate. Each one of these nutrients will affect
the concentration of dissolved oxygen differently. Therefore, Equation 4.16 is a function of the
substance s.
The second assumption has to do with the limiting nutrient. As it was presented in chapter 3,
phosphate is considered the limiting nutrient in inland waters, whereas ammonium and nitrate are in
marine waters. This is a main issue in the definition of the effect factors, since it implies that nitrogen
emissions will not affect inland waters, while phosphorus emissions will not affect marine waters. The
waters correspond to 101 rivers and 41 seas defined by the CARMEN model in 31 European
countries. Therefore, Equation 4.16 depends on the water e.
The last assumption corresponds to marginal emissions. In LCA, the substance emissions from a
product lifecycle contribute marginal to the concentration of that substance in the water. The
concentration/effect curve gives the impact from a concentration increase. As long as the
concentration increase is marginal compared to the reference concentration, the impact per unit of
concentration increase may be put on a par with the slope of the concentration/effect curve, and thus
be taken as linear (Potting, 2000). In order to do this, the reference concentration has to reflect the
total environmental concentration from many sources together to which the full emission of a single
source only contributes marginally. Finally, if the full emission from a single source can be regarded
as marginal contributing, the same inherently holds true for the emission related to on product unit.
The effect chosen in this research is oxygen depletion and is defined as (DOS – DO), also knows as
oxygen deficit. This definition considers the difference in oxygen concentration for no nutrients in the
water (DOS) and for the reference concentration of nutrients in the water (DO). In order to obtain the
slope of the curve oxygen-depletion/nutrient-concentration the effect (DOS – DO) is divided by the
25
average addition of nutrients to the water, which is the average difference between no nutrients in the
water and the reference concentration of nutrients in the water (AVGs,e). An average (difference)
concentration is used as a base to be able to compare the effect factors and is calculated for each
water category from the concentrations in inland waters and marine waters. This slope (g O2/g N) of
the nutrient-concentration/oxygen-depletion curve defines effect factor (Eff) from a substance s
emitted to water e and is calculated in Equation 4.17. This is done for all 101 rivers and 41 seas.
Mathematically, this is presented in the following equation:
Eff s ,e =
DOS e − DOs ,e
4.17
AVG s ,e
Nitrogen emissions can be in the form of ammonia from wastewater and airborne emissions, nitrite
from airborne emissions and nitrate from fertiliser, manure and airborne emissions. In the case of
phosphorus emissions, which are agricultural and from wastewater, they are in the form of phosphate,
but expressed in terms of nitrogen emissions through an equivalency factor (Redfield ratio).
Finally, the characterisation factors CFs,j (mg O2/g N) of nitrogen or phosphorus compound s emitted
to all waters e (inland or marine waters) in country j, is determined by:
CFs , j = ∑ FE s , j ,e * Eff s ,e
4.18
e
where FEs,j,e are the fate-exposure factors representing the fraction of compound s emitted to the water
e in country j (dimensionless), and Effs,e are the effect factors from substance s emitted to water e in
country j.
4.3 Concluding remarks
This research considers the oxygen depletion of the aquatic environment as the effect of aquatic
eutrophication. In order to define this effect, a model for DO in water was used following the basic
principle of mass balance and considers the processes of DO: reaereation, photosynthesis,
phytoplankton respiration, organic matter oxidation and nitrification. The eutrophication components
represented in this model are dissolved inorganic nitrogen (ammonia, nitrite and nitrate), dissolved
inorganic phosphorus (phosphate) and phytoplankton. For simplification reasons, the model omits
zooplankton, non-living organic nitrogen and phosphorus, and sediments. The process of
denitrification is also not considered in the model.
Three main assumptions are defined in order to solve the DO model. Firstly, because LCA does not
address temporal aspects, DO in water is modelled under steady state conditions. This first
assumptions allows to define an equation for the DO concentration that does not depend on time.
Nutrient limitation is the second assumption: phosphate is considered a limiting nutrient in inland
waters, whereas ammonium and nitrate are in marine waters. Thirdly, the magnitude of the emissions
of nutrients from a product lifecycle are marginal compared with the reference concentrations of the
aquatic systems. Therefore, the concentration of dissolved oxygen is analysed at a marginal level of
nutrient emission. This is defined as the effect factor Effs,e for aquatic eutrophication within LCA,
after substance s is emitted to water e.
Finally, the characterisation factors are the aggregation of the multiplication’s between the fateexposure factors and the effect factors for all water (inland or marine water) in a country.
26
5
Results
5.1 Effect factors
The results of the calculations for the effect factors (mg O2/g N) are presented in Table 5.1 for the 101
rivers and in Table 5.2 for the 41 seas. They are separate in substances s: phosphate and ammonia for
inland waters and nitrate, ammonia and NOx for marine waters. The effect factors represent the ratio
of oxygen depletion per unit of nitrogen emitted to a given water receptor (inland or marine waters).
As it was presented in the previous chapter the calculation of the effect factors followed the
assumption of the limiting nutrient. Therefore, it can be observed that the effect factors for inland
waters from nitrogen compounds and for marine waters from phosphorus compounds are zero. This
means that biomass is not dependent on the non-limiting nutrient, even when there is an excess of it,
and thus no oxygen will be consumed due to eutrophication processes. The only exception is the
effect factors for inland waters from nitrogen coming from wastewater. This is because wastewater is
considered rich in ammonia (NH3), which once in water will be oxidised through nitrite into nitrate,
and thus consume oxygen.
In order to calibrate the model when calculating the dissolved oxygen concentration in water, some
concentration had to be changed. The nitrogen concentrations of the rivers Volga, Dnjepr, Don and
middle Danube were to high and resulted in negative DO concentrations (not oxygen depletion).
Therefore, these values were replaced for the higher nitrogen concentration value between the other
rivers. The same was done for the marine waters the southern part of the North Sea and the northern
part of the Black Sea, were the nitrogen concentration also resulted in negative DO concentrations.
The nitrogen concentration of the southern part of the North Sea was replaced by the nitrogen
concentration of the northern part, and the one of the northern part of the Black Sea was replaced with
the concentration of the middle part. The Baltic Sea (part below 15 and 17) did not present reference
concentrations, and they were replaced with the concentration of west and east from Gotland. The
Black Sea (deeper waters) did not present reference concentration either and thus, no factor was
calculated for this part of the sea.
The rivers with the higher effect factors (mg O2/g N) are the Volga: 712.08 from phosphate emissions;
and the Don: 168.14 from ammonia emissions coming from waste water. Other rivers with high
oxygen depletion ratio from both sources are the Dnjepr, the Vistula, the middle and lower Danube,
the Po, the Sakarya, the Elbe and the middle Rhine. The rivers north Iceland and east Corse have
lowest oxygen depletion per g nitrogen: 3.05 from phosphate and 1.09 from ammonia, respectively.
There is a factor 233 and 154 between the maximum and minimum effect factor from phosphorus
sources and nitrogen in wastewater, respectively. More than 68% of the rivers are below the mean
values.
With respect to the effect factors for marine waters, the sea with the higher oxygen depletion ratio
from all nitrogen sources (mg O2/g N) is the Baltic Sea (below 17): 33.04 from nitrate, 61.72 from
NH3 and 68.58 from NOx. The seas that follow (in decreasing order) are Baltic Sea (east from
Gotland), Golf of Biscay, Sea of Azov and Venice bay. The western part of the Irish Sea corresponds
to the sea with the lower oxygen depletion ratio from nitrogen sources (mg O2/g N): 3.91 from nitrate,
4.94 from NH3 and 5.19 from NOx. There is a highest factor 13 between the maximum and minimum
effect factor from a NOx. About 68% of the seas are below the mean values (excluding the seas
without data). In order to understand this better and as an example, Figure 5.1 presents the oxygen
depletion in marine water due to agricultural sources of nitrogen.
27
Table 5.1. Effect factors for inland waters in mg O2/ g N
River
N. Iceland
S. Iceland
Klar
N. Kola
Cardigan
Kalix
Kandalaks
Dvina
Pecora
Sogne
Setesdal
Tyri
Oslo
Gota
Angerman
Logan
Kumo
Neva
Volga
Lorne
Moray
Forth
Konge
Belt
Venta
Daugava
Neman
Shannon
Staney
Lee
Lake Distric
Humber
Severn
Thames
Avon
W eser
Elbe
Mecklenburg
Oder
Vistula
Dnjepr
Don
Lower Rhine
Middle Rhine
Upper Rhine
Manche
Scheldt
Meuse
Caspian
Aulne
Vilaine
Phosphate
mg O2/g N
3.05
3.07
9.28
7.20
8.93
15.40
4.90
28.01
5.15
4.39
5.73
5.32
9.89
10.32
7.31
13.59
15.18
108.02
712.08
36.21
22.74
59.69
16.20
13.26
37.69
47.39
73.19
160.46
41.23
56.48
100.49
120.33
107.55
125.66
33.54
74.80
206.95
14.47
191.39
318.35
505.05
275.55
51.20
201.14
93.36
25.59
115.91
76.67
134.28
56.85
25.28
Ammonia
mg O2/g N
4.97
5.18
5.26
3.20
2.08
14.69
4.72
26.50
4.82
3.53
5.40
2.78
6.66
11.61
8.12
16.43
15.50
68.51
155.56
7.87
6.66
16.53
12.39
13.98
17.89
28.37
32.82
27.29
13.07
11.70
26.37
47.55
34.78
44.17
12.00
47.75
130.86
13.29
100.76
157.83
155.56
168.14
23.26
114.87
31.85
13.15
48.83
37.26
8.85
23.93
14.05
River
Loire
Seine
Rhone
Charente
Garonne
Adour
Aude
Var
Nervion
Galicia
Douro
Mondego
Tajo
Sado
Guadiana
Guadalqivir
Andarax
Segura
Jucar
Balearic
Ebro
Llobregat
Arno
Adriatic
Tevere
Gaeta
Lipari
Agri
Simeto
W . Corse
E. Corse
W . Sardinia
E. Sardinia
Cetina
Drin
Acheloos
Maritsa
Istrandca
Sakarya
S. Marmara
Gedis
Menderes
Crete
Po
Adige
Upper Danube
Middle Danube
Lower Danube
Dniestr
Don
Mean
Standad deviation
Maximum
Minimum
28
Phosphate
mg O2/g N
183.64
163.23
168.41
29.99
130.64
26.16
12.79
14.34
38.73
65.19
94.53
13.71
158.20
6.87
30.59
92.60
24.71
23.07
45.22
145.95
63.45
44.12
47.79
101.24
76.73
42.79
19.00
54.00
36.01
7.10
9.90
21.58
6.43
49.53
81.03
104.81
55.95
20.76
216.20
24.13
48.08
57.54
10.63
245.12
83.02
190.57
485.90
314.20
124.31
75.70
Ammonia
mg O2/g N
86.78
79.94
54.01
15.25
53.19
6.92
5.24
4.86
13.46
20.83
57.00
4.68
73.11
4.12
34.25
47.95
11.00
10.16
25.28
9.89
43.44
15.98
21.26
42.51
31.48
15.09
7.45
22.95
21.02
1.53
1.09
10.60
3.09
17.86
28.45
52.22
28.41
11.14
120.21
10.61
21.93
23.71
5.53
96.04
28.11
79.43
159.74
152.05
64.46
33.30
84.97
111.83
712.08
3.05
35.62
41.30
168.14
1.09
Table 5.2. Effect factors for marine water in mg O2/ g N
Sea
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
Irish sea (eastern part)
Irish sea (St. George Channel)
Irish sea (western part)
Celtic sea
English Channel (western part)
English Channel (eastern part)
Golf of Biscay
Atlantic ocean (around Scotland)
North sea/Norwegian sea
North sea (northern part)
North sea (southern part)
Skagerrak
Kattegat
Øresund/Great and Small Bealt
Baltic sea (west from Gotland)
Baltic sea (below 15)
Baltic sea (east from Gotland)
Baltic sea (below 17)
Gulf of Riga
Gulf of Finland
Gulf of Bothnia (southern part)
Gulf of Bothnia (northern part)
Norwegian sea
Venice bay
Adriatic sea (northern part)
Adriatic sea (southern part)
Aegean sea (western part)
Black sea (northern part)
Sea of Azov
Black sea (middle part)
Black sea (south/eastern part)
Marmara sea
Aegean sea (eastern part)
Sea of Crete
Ballearic basin (northern part)
Gulf of Lion/Ligurian sea
Algero Provencal basin
Tyrrhenian basin (northern part
Tyrrhenian basin (southern part)
Balearic basin (southern part)
Black sea (deep water)
Mean
Standard deviation
Maximum
Minimum
Nitrogen
Nitrate
Ammonia
NOx
mg O2/g N mg O2/g N mg O2/g N
7.17
10.52
11.32
5.06
6.65
7.04
3.91
4.94
5.19
11.46
18.65
20.37
10.75
17.09
18.60
14.34
24.37
26.76
25.49
47.23
52.42
9.08
13.98
15.15
10.27
16.39
17.85
15.10
25.89
28.47
15.50
26.62
29.28
7.36
10.44
11.17
5.69
7.84
8.35
9.86
15.58
16.94
7.40
11.31
12.24
7.92
12.03
13.02
32.90
61.40
68.22
33.04
61.72
68.58
5.93
8.61
9.25
10.24
16.76
18.32
6.69
10.01
10.80
4.83
6.66
7.10
6.73
9.88
10.64
17.30
30.27
33.37
10.30
15.57
16.83
9.88
14.39
15.47
9.39
13.76
14.80
11.87
19.48
21.30
21.51
38.88
43.03
12.06
19.78
21.62
11.95
19.49
21.29
5.40
7.09
7.50
10.46
15.79
17.07
10.45
15.55
16.77
11.51
17.95
19.49
14.05
23.40
25.63
6.05
7.64
8.03
14.36
24.05
26.37
10.65
15.97
17.24
7.93
10.67
11.32
11.55
6.65
33.04
3.91
18.86
13.16
61.72
4.94
20.61
14.72
68.58
5.19
29
Excessive: 20 -35
High: 15-20
Significant: 10-15
Low: 3-10
Figure 5.1. Effect factors (mg O2 / g N) from nitrate emissions to marine waters. Each sea is
indicated with its list number
5.2 Characterisation factors
As it was mention in the previous chapter, the characterisation factors are the result of multiplying the
fate-exposure factors from substance s emitted to water e in country j, and the effect factors from
substance s emitted to water e. The substance s can be ammonia, nitrite, nitrate or phosphate and the
water e refers to inland or marine waters. In order to obtain a factor per country, the characterisation
factors of all waters (inland or marine waters) in a particular country are aggregated. The results of the
characterisation factors (mg O2/g N) for inland and marine waters in 29 countries are presented in
Table 5.4. The countries Iceland, Turkey and Caucasus are excluded from the list of countries defined
by CARMEN model, because of the inconsistency of their initial loads. The characterisation factors
are separated in nutrient sources. For inland waters, the sources are the use of fertilisers (nitrate and
phosphate) and manure (nitrate and phosphate) in agriculture, as diffuse sources, and municipal
wastewater (ammonia and phosphate), as a point source. Depositions of nitrogen airborne emissions
(ammonia and NOX) in marine waters have usually a major importance than in inland waters, and
therefore are included as sources for marine waters.
In the case of Portugal, no values are calculated in Table 5.4 for the characterisation factors from
nitrogen sources (fertiliser, manure and wastewater) in marine waters. The reason for this is that the
Atlantic coastal waters are not considered. No fate exposure factors were presented from nitrogen
airborne emissions (ammonia and NOX) and ammonia airborne emissions for Byelorussia and
Albania, respectively. This is because these airborne emissions are not considered to be deposited in
seas covered by the CARMEN model.
30
The assumption of the limiting nutrient in the calculation of the effect factors results also in the
absence of characterisation factors for the non-limiting nutrients. For inland waters there is no factors
for nitrogen sources, with the exception of ammonia from wastewater (values expressing
nitrification), while marine waters have no characterisation factors for phosphorus sources.
For inland waters, the characterisation factors from phosphorus coming from fertilisers and manure
are the same. This is because of the similitude in the fate-exposure factors from these sources
(phosphorus fertiliser and manure). Hungary is the country with the highest factors from nitrogen and
phosphorus coming from wastewater, 111.44 and 484.50 mg O2/g N. Austria is the country with the
highest values from phosphorus coming from agricultural practices, 36.2 mg O2/g N. In the same
categories, other countries with high values are the east European countries, like Romania, Poland,
Ukraine, Czechia & Slovakia, Yugoslavia, Russia and Byelorussia. The only west European country
that requires special attention is Austria, with a high factor from phosphorus coming from wastewater
(326.19). The country with the lowest values from phosphorus from agricultural practices is Denmark
(0.36). Other countries that follow the low factors are (in ascending order) Sweden, Norway, Finland
and the Netherlands. More than 55% of the countries are over the mean values of the characterisation
factors. There is a maximum factor of 100 (phosphorus from agriculture) between the maximum and
minimum values.
For marine waters, the characterisation factors from nitrogen coming from fertiliser and manure are
very similar. Again, this is due to the fate-exposure factors. Within these categories the country with
the highest value is Poland: 15.41 and 15.33 mg O2/g N, as well as from nitrogen from wastewater
(42.93). The Baltic countries, Czechia & Slovakia and France are other countries with high factors
from nitrogen direct emitted to water. With regard to airborne emissions, Ireland has the highest
values: 11.4 and 12.85 mg O2/g N. United Kingdom, Norway and Denmark require attention within
this category since they also have high values. The lowest values are given to Spain from agriculture
(1.90 and 1.93)3, Ireland from wastewater (5.70), Austria from airborne NH3 (1.10), and Romania
from airborne NOx (2.02). About 55% of the countries are below the mean values. There is a
maximum factor 2.3 (nitrogen from agriculture) between the maximum and minimum values.
5.3 Comparison
In order to analyse the relative relevance of the characterisation factors calculated with the effect
factors (from this point forward referred as “new” factors) they are compared with the characterisation
factors developed only with the fate-exposure factors (from this point forward referred as “previous”
factors). However, they can not be compared directly. Therefore, both characterisation factors are
normalised with respect to one country, the Netherlands. This is done by dividing all factor values by
the values obtained for the Netherlands. The results of the normalisation are presented through graphs
in Appendix 4. Table 5.3 presents the comparison of standard deviations of the factors, excluding the
non-limiting nutrients.
Table 5.3. Standard deviations of normalised factors
Normalised
Factors
Previous factors
New Factors
3
Standard Deviation
Inland waters
Marine waters
Nitrogen
Phosphorus
Nitrogen
Wastewater Agriculture Wastewater Agriculture Wastewater Air NH3 Air NOx
0.35
1.25
0.44
0.19
0.01
0.52
0.37
3.99
5.29
6.34
0.57
0.44
0.51
0.36
No Atlantic coastal waters are included
31
Table 5.4. Characterisation factors (mg O2/g N) for inland and marine waters in 29 European countries
Country
Fertilizer
Bulgaria
0.00
Czechia & Slovakia
0.00
Hungary
0.00
Poland
0.00
Romania
0.00
Russia
0.00
Yugoslavia
0.00
Byelorussia
0.00
Baltic countries
0.00
Moldavia
0.00
Ukraine
0.00
the Netherlands
0.00
W est Germany
0.00
France
0.00
Italy
0.00
Spain
0.00
Sweden
0.00
United Kingdom
0.00
Norway
0.00
Finland
0.00
Ireland
0.00
Denmark
0.00
Belgium & Luxembourg 0.00
East Germany
0.00
Switzerland
0.00
Austria
0.00
Portugal
0.00
Greece
0.00
Albania
0.00
Mean
0.00
Standard deviation
0.00
Maximum
0.00
Minimum
0.00
32
INLAND W ATERS
MARINE W ATERS
Nitrogen
Phosphorus
Nitrogen
Phosphorus
Manure W astewater Fertilizer Manure W astewater Fertilizer Manure W astewater Air NH3 Air NOx Fertilizer Manure W astewater
0.00
55.75
4.98
4.98
162.58
6.00
6.27
12.51
1.65
2.61
0.00
0.00
0.00
0.00
97.38
21.39 21.39
326.98
10.01 10.12
20.40
1.62
2.93
0.00
0.00
0.00
0.00
111.44
14.18 14.18
484.50
6.00
5.87
13.48
1.28
2.46
0.00
0.00
0.00
0.00
93.89
8.36
8.36
266.75
15.41 15.33
42.93
3.11
4.25
0.00
0.00
0.00
0.00
106.16
12.48 12.48
321.50
6.66
6.79
13.54
1.26
2.02
0.00
0.00
0.00
0.00
82.35
19.24 19.24
448.15
4.51
4.52
6.74
2.92
4.32
0.00
0.00
0.00
0.00
88.83
29.39 29.39
378.70
6.59
6.68
13.21
1.21
2.10
0.00
0.00
0.00
0.00
84.13
13.24 13.24
367.29
7.11
7.13
21.12
0.00
0.00
0.00
0.00
20.70
2.93
2.93
56.84
10.58 10.47
31.64
4.83
4.20
0.00
0.00
0.00
0.00
51.85
3.34
3.34
146.94
5.33
6.11
13.34
1.67
2.62
0.00
0.00
0.00
0.00
98.76
11.45 11.45
388.76
6.60
6.59
17.23
1.86
2.32
0.00
0.00
0.00
0.00
9.00
1.62
1.62
22.97
5.54
5.53
19.06
6.76
8.00
0.00
0.00
0.00
0.00
58.50
9.47
9.47
152.81
7.70
7.66
17.95
3.73
7.44
0.00
0.00
0.00
0.00
39.56
7.89
7.89
127.85
11.70 11.76
21.78
6.55
6.62
0.00
0.00
0.00
0.00
29.15
6.89
6.89
105.84
6.84
7.27
15.56
4.56
4.51
0.00
0.00
0.00
0.00
23.66
2.70
2.70
68.47
1.90
1.93
7.02
3.68
4.28
0.00
0.00
0.00
0.00
7.61
0.46
0.46
9.89
4.05
4.06
7.23
8.34
6.68
0.00
0.00
0.00
0.00
20.44
7.07
7.07
87.13
7.55
7.57
15.12
10.85
10.82
0.00
0.00
0.00
0.00
2.57
0.63
0.63
5.38
4.67
4.75
8.51
10.37
7.09
0.00
0.00
0.00
0.00
13.43
1.46
1.46
25.20
4.55
4.48
8.96
6.14
5.41
0.00
0.00
0.00
0.00
10.60
16.18 16.18
72.02
2.78
2.80
5.70
11.43
12.85
0.00
0.00
0.00
0.00
4.73
0.36
0.36
7.01
4.56
4.57
11.82
11.27
8.37
0.00
0.00
0.00
0.00
31.70
5.65
5.65
102.33
8.89
8.92
18.57
4.43
5.88
0.00
0.00
0.00
0.00
79.25
5.33
5.33
180.16
8.91
8.92
18.92
3.73
4.69
0.00
0.00
0.00
0.00
25.22
13.11 13.11
106.48
10.03 10.03
18.44
1.25
2.52
0.00
0.00
0.00
0.00
81.55
36.20 36.20
326.19
7.38
7.38
13.80
1.10
2.22
0.00
0.00
0.00
0.00
28.35
5.85
5.85
85.50
5.76
4.41
0.00
0.00
0.00
0.00
20.79
4.14
4.14
63.67
4.68
4.75
7.82
4.42
3.77
0.00
0.00
0.00
0.00
17.06
7.81
7.81
67.41
3.66
3.66
6.14
2.39
0.00
0.00
0.00
0.00
48.08
9.44
9.44
171.22
6.79
6.85
15.31
4.66
4.92
0.00
0.00
0.00
0.00
35.88
8.58
8.58
145.63
2.92
2.90
8.06
3.33
2.75
0.00
0.00
0.00
0.00
111.44
36.20 36.20
484.50
15.41 15.33
42.93
11.43
12.85
0.00
0.00
0.00
0.00
2.57
0.36
0.36
5.38
1.90
1.93
5.70
1.10
2.02
0.00
0.00
0.00
6
Discussion
6.1 The model
The present section discusses the definition of the model of dissolved oxygen (DO) in water
developed in this research. A common feature of modelling is generalisation and simplification, and
this model is not an exception. It focuses only on reareation from the atmosphere and biochemical
reactions of dissolved oxygen, although the behaviour of a dissolved substance in water is also the
result of advection or dispersion processes (EPA, 1997). Advection is of high relevance, since it
defines an input to the in-stream concentration of DO, directly via inland waters and indirectly into
marine waters from inland waters. For example, considering that the mean DO concentration in
European rivers is about 9.4 g/m3 (Kristensen et al., 1994), the oxygen input via inland waters into
marine waters (once diluted) is significant, depending of course in the amount of rivers. This fact may
help to diminish oxygen depletion and thus, to give lower effect factors.
The model focuses on phytoplankton as primary producers and neglects sediments (see Chapter 4).
However, benthic plants such as seagrass or macroalgae can be major or dominant primary producers
in shallow waters (Parslow et al., 2002) and the sediment oxygen demand, which includes benthic
respiration, can be a significant fraction of the total oxygen demand. Moreover and particularly in
fast-moving shallow rivers, benthic processes can dominate up to 80 to 95% of the total nitrification
in the water column (EPA, 1997). This means that in these rivers the effect factors of this research
only address at maximum 20% of the total nitrification. It is important to see here that the effect
factors from nitrogen in wastewater in inland waters are the result of nitrification. Nevertheless, a
major part of the transfer of nutrients in the aquatic system is a function of the sediments, e.g.
ammonia and phosphate sediment releases, and organic nitrogen and phosphorus settling to sediment
(Flynn, 2003). In some systems, the impact of sediment nutrient releases can be notable and result in
continuing eutrophication problems even after control measures have been applied to point sources
(EPA, 1997). For example, increased sedimentation of phytoplankton may explain the increased
oxygen consumption in the bottom water of the Greater North Sea (Ærtebjerg et al., 2001).
Another limitation of the model is the definition of the limiting factor of light intensity in the nutrient
uptake. This factor is modelled without the influence of depth water. But light intensity at different
water depths inhibits photosynthesis differently. A diminution in the specific photosynthetic rate is
commonly observed near the surface when measuring the depth profile of photosynthetic activity
(Kirk, 1994). Appendix 5 shows examples of depth profiles of phytoplankton photosynthetic rate in
coastal and inland waters. Increasing depth and diminishing light intensity lead to a maximum, lightsaturated but not inhibited, photosynthetic rate. With further increase in depth, irradiance falls to the
point at which light intensity becomes limiting, and the photosynthetic rate diminishes roughly
exponentially with depth. Therefore, the addition of this definition to the model with site dependent
water depths will help to give a better spatial differentiation of the effect factors.
6.2 The data
With the exception of the maximum phytoplankton growth rate, water temperature and nutrient
concentration, the data values used in the model do not describe the differences between inland and
marine waters. In general, the model focuses on values under average conditions in water. However,
mechanisms of oxygen production and consumption can vary between waters. For instance, the
reareation capacity in fresh waters is directly related to the flowing water and the change in water
surface elevation (Iowa DNR, 2004); whereas in sea waters it can change with the temperature,
salinity and wind speeds (Levinton, 1995). In the same way, phytoplankton composition also varies
between inland and marine waters. Changes in phytoplankton composition can define changes in the
rate of many biological characteristics, or in capabilities for photosynthetic and nutrient acquisition
(Baird et al., 2004). In particular, considerable variations of the average atomic ratios of carbon,
nitrogen and phosphorus content in phytoplankton (the Redfield ratio) do occur between inland and
33
marine waters. For instance, values of the nitrogen-phosphorus ratio usually can be between 5 and 15
in marine waters (Burton et al., 1976), while fresh water limited by phosphorus will always have a
greater N:P ratio than the Redfield ratio (Crouzet et al., 1999). In order to obtain more accurate site
dependent results for the oxygen depletion in waters, these values are expected to change not only
between inland and marine waters in general, but also within waters.
As it was presented in Chapter 4, the concentrations correspond to the load from the CARMEN model
taken as concentrations. The problem with this definition is that the dilution process of the substances
into the water is not considered. For example, for a given load, the concentration in water will be high
if the volume of the water is small, but it will be lower if the volume of the water is larger. This means
that the effect factors are expected to change once the real concentrations of substance in inland and
marine water are used.
6.3 The calculations
Due to the lack of temporal aspects in LCA, the dissolved oxygen in water in the aquatic systems is
modelled under steady state conditions (equilibrium). However, an important fact when modelling
eutrophication is that plant growth processes have a time dimension. Plants accumulate and mineralise
nutrients at different rates and thus certain sequences of nutrient use can occur and some nutrients can
even be used up. Moreover, phytoplankton growth has a seasonal variation. For instance, in midlatitudes, the spring bloom is followed by a notable decline of biomass in the summer caused by
zooplankton grazing and sedimentation (Levinton, 1995). Not only plants have a time dimension, but
also waters, like the residence time of substances in waters. Short residence times due to rapid
transport of pollutants leads to minimal ecological damage, while low-flow conditions and long time
residence time may cause severe nutrient enrichment, which leads to oxygen depletion and further
effects (EPA, 1997). However, until LCA does include a time dimension in the inventory and
characterisation, the modelling of dissolved oxygen in water will have to be done under steady state
conditions.
Another assumptions in the calculations is nutrient limitation: Phosphorus limits phytoplankton
growth in inland waters, whereas nitrogen does in marine waters. However, this definition of nutrient
limitation stays still unclear, especially for marine waters. For example, the nitrogen limitation of the
Mediterranean Sea has been discussed, as well as the Adriatic Sea, mainly due to data credibility.
Some data show phosphorus limitation in these seas (Izzo et al., 1999). It is clear that the relevance of
the nutrient limitation concept follows the need to identify the main nutrient causing eutrophication in
order to provide appropriate response measures. However, it is important to know exactly which
nutrient is limiting the biomass growth, since the factors say that phosphorus in marine waters has no
effect, whereas in reality the phosphorus could be the limiting nutrient in some sea. Therefore, the
concept of limiting nutrient has to be site dependent.
6.4 The results
The discussion of the results is done firstly for the effect factors by comparing them with values of the
present state of oxygen depletion in European waters. Finally, the discussion follows a comparison
between the new factors and the previous factors (see Chapter 5).
Since no information of the state of DO concentration in European rivers could be found, only the
effect factors for marine waters are evaluated. The results of oxygen depletion per nitrate emissions in
marine waters are chosen to be compared with the topic report of the European Environmental
Agency ‘Eutrophication in Europe’s coastal waters’ (Ærtebjerg et al., 2001). According to this report,
there is no indication of eutrophication in the north Atlantic coasts of the Shetlands Islands and
Norwegian coast. By looking at Figure 5.1, the results reflect that the Norwegian Sea has a low effect
(green colour) of oxygen depletion, with a factor 6.73 mg O2/g N. The North Sea/Norwegian Sea has
a significant effect (yellow colour), with a factor of 10.27 mg O2/g N.
34
The report says that all areas of the Baltic Sea are affected by eutrophication, least in the Gulf of
Bothnia. According to the effect factors, the eastern part of the Baltic Sea has excessive problems of
oxygen depletion (red colour), with factors 32.9/33.04 mg O2/g N. However, the results also present
low effects for the western part of the Baltic Sea (7.40/7.92), as well as the Gulf of Bothnia
(6.69/4.83).
Following the report, in the Wadden Sea, the southern and German Bights, the Kattegat and the
eastern Skagerrak, oxygen depletion is widespread. The results of this research give a high factor
(orange colour) of oxygen depletion to the North Sea (15.10/15.50), but they give low effects to the
Skagerrak and Kattegat, with factors 7.36 and 5.69 mg O2/g N respectively.
In a number of Irish estuaries, the report presents decreases in oxygen concentration. The effect
factors indicate low oxygen depletion in the Irish seas: 7.17/5.06/3.91 mg O2/g N.
Mediterranean surface waters in the open sea are classified among the poorest in nutrients of the
world seas. However, the report argues that several and sometimes severe cases of eutrophication are
evident, especially in enclosed coastal bays. By comparing effects of the northern part of Balearic
Basin, the Gulf of Lion, the Tyrrhenian Basin and the Venice Bay, they have significant oxygen
depletion, whereas the Allegro Basin and the southern part of the Balearic Basin have lower effects.
The major contradiction between the EEA-report and the results is the Golf of Biscay. The report says
that there is no evidence of eutrophication of coastal zones in this region, while the effect is
represented excessive (25.49) according to the results. However, the report explains that this
assessment relies on few data.
Considering the simplifications of the model and the data quality, the factors developed in this
research indicate relevant tendencies in the nutrient concentration-oxygen depletion relations on a
continental scale. With the respect to the characterisation factors, the aggregation of them by waters
per country may be a problem when interpreting the factors, since it considers the aggregation of
oxygen depletion of all waters in a given country.
The new characterisation factors present a clearer (spatial) differentiation between countries than the
previous factors, with the exception of nitrogen airborne emissions. This can be especially observed
for inland water, where the range for the new factors is very high (from 3.99 to 6.34), while the range
of the previous goes from 0.35 to 1.25. In the case of marine water, particular attention requires the
values of nitrogen from wastewater. In this case, the previous factors do not present much difference
between countries, with a standard deviation about 0.01; while the new factors are larger
differentiated (0.44). Factors from nitrogen airborne emissions have a very similar variation in marine
waters.
With respect to the relevance that both factors give to countries within sources categories, there are
some differences. For example, by comparing the countries with the maximum values of both
normalised factors, they only agree for phosphorus coming from agriculture and NOx airborne
emissions. For the other source categories both factors give different rankings. This situation can also
be observed in general by comparing both normalised factors.
35
36
7
Conclusions
Oxygen depletion is as right effect chosen to calculate the effect factors since it is an important link
between the direct effects and the final effects on the environment. For example, the excess of
phytoplankton due to a nutrient increase in water (direct effect) will be oxidated if it is not eaten by
the zooplankton and thus becoming part of the oxygen-consuming processes. But at the same time,
oxygen depletion may lead to final effects on plant and animal communities, such as the loss of
habitats, fish kills and phosphorus releases. Moreover, oxygen depletion is an effect closer to the
endpoints of the cause-effect chain and therefore the assessment of aquatic eutrophication will be
more environmental relevant.
Considering the simplifications of the model and the data quality, the factors developed in this
research indicate relevant tendencies in the nutrient concentration-oxygen depletion relations on a
continental scale. According to the effect factors calculated in this research, the rivers with the higher
effect factors are the Volga from phosphate emissions and the Don from ammonia emissions coming
from wastewater. Other rivers with high oxygen depletion ratio from both sources are the Dnjepr, the
Vistula, the middle and lower Danube, the Po, the Sakarya, the Elbe and the middle Rhine. The rivers
north Iceland and east Corse have lowest oxygen depletion per g nitrogen.
With respect to marine waters, the sea with the higher oxygen depletion ratio from all nitrogen
sources is the Baltic Sea (below 17. The seas that follow (in decreasing order) are Baltic Sea (east
from Gotland), Golf of Biscay, Sea of Azov and Venice bay. The western part of the Irish Sea
corresponds to the sea with the lower oxygen depletion ratio from nitrogen sources. When comparing
the oxygen depletion per nitrate emissions in marine waters with the assessment done by European
Environmental Agency (EEA), most of the results are confirmed: the low oxygen depletion in the
Norwegian Sea, the Irish seas and opened coastal bays (Allegro Basin) of the Mediterranean, but still
significant in enclosed coastal bays (Venice Bay), the high oxygen depletion for the North Sea and
excessive in the eastern part of the Baltic Sea. However, the are also some contradictions. The effect
factors do not present high effect in the Skagerrak, Kattegat or in all areas of the Baltic Sea, like in the
western part of the Baltic Sea end the Gulf of Bothnia, like the EEA report says. The major
contradiction between the EEA-report and the results of this research is in the Golf of Biscay, where
the effect factors indicate an excessive oxygen depletion, while the report gives no evidence of
eutrophication.
With regard to the characterisation factors, the new factors present a clearer (spatial) differentiation
between countries than the previous factors, especially the characterisation factors from nitrogen from
wastewater emitted to marine waters. The characterisation factors from nitrogen airborne emissions
have a very similar variation between marine waters. Moreover, The relevance that both factors give
to countries within sources categories changes.
This research also presents recommendations to improve the assessment of oxygen depletion due to
aquatic eutrophication in LCA. Firstly, the model of dissolved oxygen concentration in water needs to
consider physical processes, like advection, and not only focuses on reareation from the atmosphere
and biochemical reactions of dissolved oxygen. Advection is of high relevance since it defines an
input to the in-stream concentration of DO and thus may help to diminish oxygen depletion. Secondly,
the internal transfers of nutrients in the aquatic system from ammonia and phosphate sediment
releases, and to organic nitrogen and phosphorus sediment are major sources. For example, increased
sedimentation of phytoplankton may explain the increased oxygen consumption in some bottom
waters, like in the Greater North Sea. Thirdly, In order to obtain more accurate site dependent results
for the oxygen depletion in waters, the variable values used in the model are expected to change not
only between inland and marine waters in general, but also within waters. In addition to this, by
defining the limiting factor of light intensity in the nutrient uptake in terms of site dependent depth
waters, better spatial differentiated the effect factors can be obtained. In the same way, the concept of
the limiting nutrient has to be site dependent within marine waters, since the limitation of nitrogen in
37
the biomass growth remains unclear for some seas. The last recommendation is to use real
concentrations of nitrogen and phosphorus in the European inland and marine waters instead of loads,
since the volume of the water will define the actual concentration of the load in the water.
Finally, the answer to the research question ‘Can characterisation factors for aquatic
eutrophication cover spatial differentiated effect assessment?’ will be positive. In order to
complete the modelling of the environmental mechanisms, this research defines spatial differentiated
effect factors that can be later use together with the fate-exposure factors to calculate the
characterisation factors for aquatic eutrophication in LCA.
38
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41
42
Appendix 1: Variable values
Variable
Definition
ka ’
α1
Aeration rate
Stoichiometric
ratio of oxygen
production per
unit
of
phytoplankton
nitrogen
α2
Stoichiometric
ratio of oxygen
uptake per unit
of
phytoplankton
nitrogen respired
ρ'
Phytoplankton
endogenous
respiration rate
at 20 °C
α3
Stoichiometric
ratio of oxygen
per unit of OM
oxidised
δOM’
Organic matter
oxidation rate at
20°C
α4
C/N ratio in the
phytoplankton
(Redfield ratio)
α5
Stoichiometric
(ammonia)
ratio of oxygen
per
unit
of
ammonia
nitrogen
oxidised
α5 (nitrite)
Stoichiometric
ratio of oxygen
per unit of nitrite
nitrogen
oxidised
δN
’ Rate
of
(ammonia)
oxidation
of
NH3 to NO2 at
20 °C
δN ’ (nitrite)
Rate
of
oxidation
of
NO2 to NO3 at
20 °C
4
5
Unit
Range of values
Used
1/day
g O2/g N
0-100 (Iowa DNR, 2004)
15.14 (Wei-Bing et al., 2002)
17.5-22.5 (Iowa DNR, 2004)
50
15.14
g O2/g N
20.72 (Wei-Bing et al., 2002)
20-28.76 (Iowa DNR, 2004)
28.76
(max)
1/day
0.15 (EPA, 1997)
0.05-0.5 (Iowa DNR, 2004)
0.5
(max)
g O2/g C
1.63 (Kinne, 1978)
1.63
1/day
0.02-3.44 (Iowa DNR, 2004)
1.8
g C/g N
5.68 (Potting et al., 2004)
5.68
g
O2/g 3.43 (EPA, 1997)
NH3-N
3.43
g
O2/g 1.14 (EPA, 1997)
NO2-N
1.14
1/day
0.05- 0.55 (López, 1998)
0.1-1.0 (Iowa DNR, 2004)
1/day
0.2-2.0 (Iowa DNR, 2004)
IW: 0.5
(calibrate)
MW: 0.1
(calibrate)
MW: 0.5
(calibrate)
Carbonaceous deoxygenation rate
Values for deep waters
43
µmax
Maximum
growth rate
I
Average
intensity
kI
MichaelisMenten
half
saturation
constant
for
light
Temperature
coefficient
half saturation
constant
for
nitrogen
limitation
half saturation
constant
for
phosphorus
limitation
%
phytoplankton
uptake
%
phytoplankton
lost
by
respiration
N/P ratio in the
phytoplankton
(Redfield ratio)
Q10
kN
kP
γ
β
rN/P
1/day
Inland water: 1.8 (EPA, 1997)
Inland water: 1-3 (Iowa DNR, 2004)
Marine water: 1.36, 2.0 (Baird, 2004)
70 (Wei-Bing et al., 2002)
This value correspond to the optimal
light intensity (see chapter 4)
14.664 (Iowa DNR, 2004)
IW: 1.5
MW: 1.36
2.3 (Kirk, 1994)
2.3
g N/ m3
0.01-20 (Iowa DNR, 2004)
10
g P/ m3
0.01-0.05 (Iowa DNR, 2004)
0.025
g N/g P
0.3 (Izzo et al., 1999)
0.3
Only value found. Value for the
Mediterranean Sea
0.03-0.4 (Burton et al., 1976)
IW: 0.4
(calibrate)
MW: .22
(calibrate)
7.226 (Potting et al., 2004)
7.226
light W/m2
W/m2
Temperature corrections
Corrected aeration rate
Corrected
phytoplankton
respiration rate
Corrected
organic
matter
oxidation rate at 20°C
Corrected nitrification rate
ka
ρ
δOM
δN
44
ka' * 1.0150(Te-20)
ρ' * 1.08(Te-20)
Iowa DNR, 2004
EPA, 1997
δOM’ * 1.08(Te-20)
Iowa DNR, 2004
δN’ * 1.047(Te-20)
Iowa DNR, 2004
70
14.664
Appendix 2: Reference concentration
The concentrations here presented are acctually loads from the CARMEN model expressed as
concentrations.
Inland waters
River
N. Iceland
S. Iceland
Klar
N. Kola
Cardigan
Kalix
Kandalaks
Dvina
Pecora
Sogne
Setesdal
Tyri
Oslo
Gota
Angerm an
Logan
Kum o
Neva
Volga
Lorne
Moray
Forth
Konge
Belt
Venta
Daugava
Nem an
Shannon
Staney
Lee
Lake Distric
Hum ber
Severn
Tham es
Avon
W eser
Elbe
Mecklenburg
Oder
Vistula
Dnjepr
Don
Lower Rhine
Middle Rhine
Upper Rhine
Manche
Scheldt
Meuse
Caspian
Aulne
Vilaine
Reference Concetrations (g/m 3)
Nitrogen
Phosphorus
River
Nitrogen Phosphorus
6.13
0.14
Loire
100.78
14.07
6.38
0.14
Seine
88.20
11.95
6.97
0.70
Rhone
64.26
13.18
4.10
0.50
Charente
17.23
2.12
2.56
0.61
Garonne
58.68
9.53
19.57
1.25
Adour
7.82
1.84
6.13
0.31
Aude
5.77
0.80
31.83
2.10
Var
5.35
0.92
6.73
0.38
Nervion
13.62
2.53
4.40
0.25
Galicia
21.07
4.37
6.73
0.36
Douro
59.75
6.58
3.47
0.32
Mondego
4.87
0.82
8.82
0.76
Tajo
75.03
10.96
15.37
0.79
Sado
4.14
0.32
10.76
0.53
Guadiana
34.42
1.95
Guadalqivir
44.15
5.96
23.09
1.17
20.91
1.25
Andarax
11.12
1.56
92.39
9.56
Segura
10.28
1.44
505.86
58.75
Jucar
25.58
2.98
9.70
2.83
Balearic
10.00
10.00
8.20
1.73
Ebro
46.92
4.47
20.36
4.75
Llobregat
17.08
3.04
14.90
1.16
Arno
21.88
3.20
17.49
0.98
Adriatic
45.54
7.18
22.33
2.99
Tevere
29.87
4.98
35.39
3.79
Gaeta
16.16
2.95
40.95
5.93
Lipari
7.98
1.23
33.19
12.82
Agri
24.58
3.76
15.90
3.20
Sim eto
22.51
2.46
14.05
4.37
W.
1.73
0.40
32.47
8.08
E.
1.23
0.61
58.55
9.70
W.
11.36
1.41
42.82
8.65
E.
3.31
0.32
51.29
9.58
Cetina
22.29
3.97
14.54
2.57
Drin
30.27
5.69
56.47
5.75
Acheloos
55.39
7.38
160.93
16.75
Maritsa
29.69
3.82
15.56
0.99
Istrandca
11.62
1.32
118.08
14.79
Sakarya
125.62
15.23
194.09
25.83
S.
11.07
1.56
341.44
41.64
Gedis
22.88
3.26
204.97
21.06
Menderes
24.74
3.93
26.77
3.79
Crete
5.77
0.60
128.66
14.94
Po
98.85
17.10
39.05
7.46
Adige
37.51
7.24
14.85
1.79
Upper
95.64
15.10
52.75
8.30
Middle
259.18
39.03
38.24
5.23
Lower
189.83
25.87
10.00
10.00
Dniestr
80.43
10.15
27.03
4.15
Don
38.44
5.69
15.88
1.77
45
Marine waters
Reference Concetrations (g/m3)
Sea
Nitrogen Phosphorus
Irish sea (eastern part)
56.17
9.28
Irish sea (St. George Channel)
25.96
3.14
Irish sea (western part)
17.33
1.66
Celtic sea
117.11
14.79
English Channel (western part)
100.19
8.21
English Channel (eastern part)
161.86
16.52
Golf of Biscay
333.29
34.06
Atlantic ocean (around Scotland)
79.80
5.82
North sea/Norwegian sea
101.11
0.74
North sea (northern part)
174.22
7.66
North sea (southern part)
812.08
86.92
Skagerrak
47.77
1.78
Kattegat
36.07
1.25
Øresund/Great and Small Bealt
94.13
3.21
Baltic sea (west from Gotland)
70.56
1.30
Baltic sea (below 15)
0.00
0.00
Baltic sea (east from Gotland)
502.12
51.07
Baltic sea (below 17)
0.00
0.00
Gulf of Riga
48.48
4.00
Gulf of Finland
118.10
11.16
Gulf of Bothnia (southern part)
60.00
2.04
Gulf of Bothnia (northern part)
33.16
1.32
Norwegian sea
54.88
0.87
Venice bay
192.97
28.38
Adriatic sea (northern part)
74.89
8.04
Adriatic sea (southern part)
61.34
6.04
Aegean sea (western part)
62.02
6.45
Black sea (northern part)
1054.90
135.42
Sea of Azov
278.59
27.78
Black sea (middle part)
123.82
8.99
Black sea (south/eastern part)
119.09
8.99
Marmara sea
26.78
2.90
Aegean sea (eastern part)
74.65
8.52
Sea of Crete
69.33
6.45
Ballearic basin (northern part)
90.17
8.22
Gulf of Lion/Ligurian sea
134.98
18.10
Algero Provencal basin
22.36
1.21
Tyrrhenian basin (northern part
139.95
16.43
Tyrrhenian basin (southern part)
72.24
3.21
Balearic basin (southern part)
37.14
3.38
Black sea (deep water)
0.00
0.00
46
Appendix 3: Water temperatures
Inland waters
River
Temp (C)
N. Iceland
9.6
S. Iceland
9.6
Klar
5.2
N. Kola
9.1
Cardigan
5.2
Kalix
5.2
Kandalaks
5.2
Dvina
10.4
Pecora
5.4
Sogne
9.1
Setesdal
9.1
Tyri
9.1
Oslo
9.1
Gota
5.2
Angerman
6.5
Logan
6.5
Kumo
6.5
Neva
10.1
Volga
15.5
Lorne
9.6
Moray
9.6
Forth
9.6
Konge
9.6
Belt
5.2
Venta
10.4
Daugava
10.4
Neman
10.4
Shannon
10.4
Staney
10.4
Lee
10.4
Lake Distric
9.6
Humber
9.6
Severn
9.6
Thames
11.5
Avon
10.1
Weser
10.9
Elbe
9.6
Mecklenburg
11.2
Oder
11.2
Vistula
9.6
Dnjepr
Don
11.7
Lower Rhine
11.8
Middle Rhine
12.7
Upper Rhine
9.7
Manche
12.4
Scheldt
13.9
Meuse
15.6
Caspian
12.4
Aulne
12.4
River
Temp (C)
Vilaine
12.4
Loire
11.5
Seine
13.2
Rhone
10.7
Charente
12.4
Garonne
13.2
Adour
12.4
Aude
12.4
Var
12.4
Nervion
16.1
Galicia
16.1
Douro
14.9
Mondego
15.1
Tajo
15.6
Sado
16.3
Guadiana
16.3
Guadalqivir
19.2
Andarax
16.1
Segura
16.1
Jucar
16.1
Balearic
16.1
Ebro
13.9
Llobregat
16.1
Arno
15.5
Adriatic
14.2
Tevere
18.2
Gaeta
14.2
Lipari
14.2
Agri
14.2
Simeto
14.2
W. Corse
14.2
E. Corse
14.2
W. Sardinia
14.2
E. Sardinia
14.2
Cetina
14.2
Drin
14.5
Acheloos
14.5
Maritsa
14.5
Istrandca
14.5
Sakarya
15.0
S. Marmara
15.1
Gedis
15.1
Menderes
15.1
Crete
15.1
Po
15.5
Adige
6.9
Upper
10.3
Middle
10.0
Lower
9.1
Dniestr
9.1
Don
11.7
(1) http://www.gemswater.org/publications/index-e.html
(*) Average water temperature in the country
*
*
*
*
*
*
*
1
1
*
*
*
*
*
*
*
*
1
1
*
*
*
*
*
*
*
*
*
*
*
*
*
*
1
1
1
1
*
1
1
1
*
1
1
1
1
1
1
*
*
*
1
1
1
*
1
*
*
*
*
*
1
1
1
*
1
1
*
*
*
*
1
*
1
*
1
*
*
*
*
*
*
*
*
*
*
1
*
*
1
*
*
*
*
1
1
1
1
1
*
1
47
Inland waters
Sea
Temp (C)
Source
Irish sea (eastern part)
10
http://www.offshore-sea.org.uk/sea/dev/media_file/SEA6_Oceanography.pdf
Irish sea (St. George Channel)
11
http://www.offshore-sea.org.uk/sea/dev/media_file/SEA6_Oceanography.pdf
Irish sea (western part)
10
http://www.offshore-sea.org.uk/sea/dev/media_file/SEA6_Oceanography.pdf
Celtic sea
11
http://www.met.ie/gfd/data_sea.asp
English Channel (western part)
12
http://27.1911encyclopedia.org/E/EN/ENGLISH_CHANNEL.htm
English Channel (eastern part)
11.3
http://27.1911encyclopedia.org/E/EN/ENGLISH_CHANNEL.htm
Golf of Biscay
13
*
Atlantic ocean (around Scotland)
11
http://www.ospar.org/eng/doc/pdfs/R2C2.pdf
North sea/Norwegian sea
10.5
*
North sea (northern part)
11.3
*
North sea (southern part)
12.3
*
Skagerrak
12.6 http://www.smhi.se/oceanografi/oce_info_data/reports/aarsrapp/2001/anrep01.html#anholte
Kattegat
10 http://www.smhi.se/oceanografi/oce_info_data/reports/aarsrapp/2001/anrep01.html#anholte
Øresund/Great and Small Bealt
10.6 http://www.smhi.se/oceanografi/oce_info_data/reports/aarsrapp/2001/anrep01.html#anholte
Baltic sea (west from Gotland)
7.6 http://www.smhi.se/oceanografi/oce_info_data/reports/aarsrapp/2001/anrep01.html#anholte
Baltic sea (below 15)
9.3 http://www.smhi.se/oceanografi/oce_info_data/reports/aarsrapp/2001/anrep01.html#anholte
Baltic sea (east from Gotland)
8.4 http://www.smhi.se/oceanografi/oce_info_data/reports/aarsrapp/2001/anrep01.html#anholte
Baltic sea (below 17)
8.6 http://www.smhi.se/oceanografi/oce_info_data/reports/aarsrapp/2001/anrep01.html#anholte
Gulf of Riga
7.5
*
Gulf of Finland
7.5
*
Gulf of Bothnia (southern part)
7.5
*
Gulf of Bothnia (northern part)
7.5
*
Norwegian sea
8.8
http://www.soc.soton.ac.uk/JRD/ICES_WGOH/IAOCSS1998/IAOCSS1998.html
Venice bay
14
http://thayer.dartmouth.edu/other/adriatic/databanks/hydrography/hydrography.html
Adriatic sea (northern part)
15.5
http://thayer.dartmouth.edu/other/adriatic/databanks/hydrography/hydrography.html
Adriatic sea (southern part)
17
http://thayer.dartmouth.edu/other/adriatic/databanks/hydrography/hydrography.html
Aegean sea (western part)
15.5
http://www.adiyamanli.org/aegeansea.html
Black sea (northern part)
11
http://www.gis.rnd.runnet.ru/team/projects/mtbase/MTBASE.html
Sea of Azov
11.5
http://www.gis.rnd.runnet.ru/team/projects/mtbase/MTBASE.html
Black sea (middle part)
11.5
http://www.gis.rnd.runnet.ru/team/projects/mtbase/MTBASE.html
Black sea (south/eastern part)
12
http://www.gis.rnd.runnet.ru/team/projects/mtbase/MTBASE.html
Marmara sea
12
*
Aegean sea (eastern part)
16
http://www.adiyamanli.org/aegeansea.html
Sea of Crete
17
*
Ballearic basin (northern part)
16
*
Gulf of Lion/Ligurian sea
15
*
Algero Provencal basin
16
*
Tyrrhenian basin (northern part
15
*
Tyrrhenian basin (southern part)
17
*
Balearic basin (southern part)
17
*
Black sea (deep water)
9
http://www.encyclopediaofukraine.com/
(*) interpolated
48
Appendix 4: Comparison of characterisation factors
Inland waters
For all graphs the blue bars correspond to characterisation factors calculated with fate-exposure
factors and effect factors, while the orange bars correspond to characterisation factors calculated only
with fate-exposure factors.
Inland water: N wastewater
14.00
12.00
Normalised factor
10.00
8.00
New factors
Previous factors
6.00
4.00
2.00
Greece
Albania
Austria
Portugal
Switzerland
East Germany
Belgium&Luxembourg
Ireland
Denmark
Finland
Norway
Sweden
United Kingdom
Italy
Spain
France
West Germany
Ukraine
the Netherlands
Moldavia
Byelorussia
Baltic countries
Russia
Yugoslavia
Poland
Romania
Hungary
Bulgaria
Czechia&Slovakia
0.00
Country
Figure 2. Normalised characterisation factors for nitrogen coming from municipal wastewater
Inland waters: P agriculture
25.00
15.00
New factors
Previous factors
10.00
5.00
Albania
Greece
Portugal
Austria
Switzerland
East Germany
Belgium&Luxembourg
Denmark
Ireland
Finland
Norway
Sweden
United Kingdom
Spain
Italy
France
West Germany
the Netherlands
Ukraine
Moldavia
Byelorussia
Baltic countries
Russia
Yugoslavia
Romania
Poland
Hungary
Bulgaria
0.00
Czechia&Slovakia
Normalised factor
20.00
Country
Figure 3. Normalised characterisation factors for phosphorus coming from agriculture
49
Inland waters: P wastewater
25.00
Normalised factor
20.00
15.00
New factors
Previous factors
10.00
5.00
Greece
Albania
Austria
Portugal
Switzerland
East Germany
Belgium&Luxembourg
Ireland
Denmark
Finland
Norway
Sweden
United Kingdom
Italy
Spain
France
West Germany
Ukraine
the Netherlands
Moldavia
Byelorussia
Baltic countries
Russia
Yugoslavia
Poland
Romania
Hungary
Bulgaria
Czechia&Slovakia
0.00
Country
Figure 4. Normalised characterisation factors for phosphorus coming from municipal
wastewater
Marine waters
The normalisation of the characterisation factors for marine waters is done by using the values
obtained for the Netherlands as reference. For all graphs the blue bars correspond to characterisation
factors calculated with fate-exposure factors and effect factors, while the green bars correspond to
characterisation factors calculated only with fate-exposure factors.
Marine waters: N fertiliser
3.00
2.00
New factors
1.50
Previous factors
1.00
0.50
Greece
Albania
Portugal
Austria
Switzerland
East Germany
Belgium&Luxembourg
Denmark
Ireland
Finland
Norway
Sweden
United Kingdom
Spain
Italy
France
West Germany
the Netherlands
Ukraine
Moldavia
Byelorussia
Baltic countries
Russia
Yugoslavia
Romania
Poland
Hungary
Bulgaria
0.00
Czechia&Slovakia
Normalised factor
2.50
Country
Figure 5. Normalised characterisation factors for nitrogen coming from agriculture
50
Bulgaria
Albania
Greece
Portugal
Austria
Switzerland
East Germany
Belgium&Luxembourg
Denmark
Ireland
Finland
Norway
United Kingdom
Sweden
Spain
Italy
France
West Germany
the Netherlands
Ukraine
Moldavia
Baltic countries
Byelorussia
Yugoslavia
Russia
Romania
Poland
Hungary
Czechia&Slovakia
Normalised factor
Bulgaria
Albania
Greece
Portugal
Austria
Switzerland
East Germany
Belgium&Luxembourg
Denmark
Ireland
Finland
Norway
United Kingdom
Sweden
Spain
Italy
France
West Germany
the Netherlands
Ukraine
Moldavia
Baltic countries
Byelorussia
Yugoslavia
Russia
Romania
Poland
Hungary
Czechia&Slovakia
Normalised factor
Marine waters: N wastewater
2.50
2.00
1.50
New factors
1.00
Previous factors
0.50
0.00
Country
Figure 6. Normalised characterisation factors for nitrogen coming from municipal wastewater
Marine waters: N NH3 airborne
2.00
1.80
1.60
1.40
1.20
1.00
New factors
0.80
Previous factors
0.60
0.40
0.20
0.00
Country
Figure 7. Normalised characterisation factors for nitrogen coming from NH3 airborne emissions
51
52
Bulgaria
Albania
Greece
Portugal
Austria
Switzerland
East Germany
Belgium&Luxembourg
Denmark
Ireland
Finland
Norway
United Kingdom
Sweden
Spain
Italy
France
West Germany
the Netherlands
Ukraine
Moldavia
Baltic countries
Byelorussia
Yugoslavia
Russia
Romania
Poland
Hungary
Czechia&Slovakia
Normalised factor
Marine waters: N NOx
2.00
1.80
1.60
1.40
1.20
1.00
New factors
0.80
Previous factors
0.60
0.40
0.20
0.00
Country
Figure 8. Normalised characterisation factors for nitrogen coming from NOX airborne
emissions
Appendix 5: Depth profiles of photosynthetic rate
Depth profiles of phytoplankton photosynthetic rate per unit volume of water.
The curves are for Lake Windermere, England (inland waters) and Bedford
Basin, Canada (coastal waters) (Kirk, 1994)
53

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