110.75 g NO3
Transkript
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. 7 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. 10 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. 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Available: http://ccar.ust.hk/cis/ 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