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AGRICULTURE, FOOD AND WATER, INVESTMENT AS A SUSTAINABLE DEVELOPMENT



1) IN ECONOMIC ASPECT



2) SOCIAL ASPECT



3)IN ENVIRONMENTAL ASSPECT


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AGRICULTURE, FOOD AND WATER, INVESTMENT AS A SUSTAINABLE DEVELOPMENT 1) IN ECONOMIC ASPECT 2) SOCIAL ASPECT 3)IN ENVIRONMENTAL ASSPECT Hanna Lakkala & Jarmo Vehmas (editors) TRENDS AND FUTURE OF SUSTAINABLE DEVELOPMENT Proceedings of the Conference “Trends and Future of Sustainable Development” 9-10 June 2011, Tampere, Finland FFRC eBOOK 15/2011 Editors Hanna Lakkala M.Sc., Project Coordinator/Researcher Finland Futures Research Centre, University of Turku hanna.k.lakkala@utu.fi Jarmo Vehmas Ph.D., Regional Manager Finland Futures Research Centre, University of Turku jarmo.vehmas@utu.fi Copyright © 2011 Authors & Finland Futures Research Centre, University of Turku Revisited 10th October 2013 ISBN 978-952-249-131-2 ISSN 1797-1322 Finland Futures Research Centre University of Turku ElectroCity, Tykistökatu 4 B, FI-20014 University of Turku Korkeavuorenkatu 25 A 2, FI-00130 Helsinki Yliopistonkatu 58 D, FI-33100 Tampere Tel. +358 2 333 9530 Fax +358 2 333 8686 utu.fi/ffrc tutu-info@utu.fi, firstname.lastname@utu.fi 2 CONTENTS INTRODUCTION ............................................................................................................... 6 1. SUSTAINABILITY INDICATORS ....................................................................... 8 Grouping and ranking the EU-27 countries by their sustainability performance measured by the Eurostat sustainability indicators .................................................................................... 9 Francesca Allievi, Jyrki Luukkanen, Juha Panula-Ontto and Jarmo Vehmas “Walking in other’s shoes” − experiences of using the DECOIN tools to characterise sustainability trade-offs in Scotland and the Cairngorms National Park ...........................................................21 K.B. Matthews, K.L. Blackstock, K. Buchan, D.G. Miller and M. Rivington Sustainability criteria and indicators − a tool for strategic urban planning .....................................31 Tarja Söderman, Leena Kopperoinen, Sanna-Riikka Saarela, Vesa Yli-Pelkonen, Adriaan Perrels, Juhana Rautiainen and Mirka Härkönen Biorefinery Implementation in Marginal Land − A focus on the multifunctional use of regional agriculture. ....................................................................................................... 43 Sandra Fahd, Gabriella Fiorentino, Salvatore Mellino, Maddalena Ripa and Sergio Ulgiati Supporting sustainable development: Using the SMILE toolkit with stakeholders in Scotland ...............55 K.L. Blackstock, K.M. Matthews, K. Buchan, D. Miller, L. Dinnie and M. Rivington Multi-Scale Integrated Analysis for Sustainable Policies: Romanian Socioeconomic Metabolism ............67 Raluca I. Iorgulescu, Lucian-Liviu Albu and Cristian Stanica Trends of Finnish MFA and Future Prospects .......................................................................... 77 Jukka Hoffrén Trends and Driving Factors in Finnish Forest Sector ................................................................. 86 Jukka Hoffrén 2. SUSTAINABILITY IN NORTH-SOUTH PERSPECTIVES ............................................ 95 “Just Begin” A Case Study in Creating Experimental Spaces in a Time of Transition .........................96 Barbara Heinzen Powering the Future of the Least Developed Countries: World Bank's Role in Developing Renewable Energy in Laos .............................................................................................. 108 Hanna Kaisti and Mira Käkönen Developing Tibet into a Special Sustainability Zone of China? ................................................... 126 Tarja Ketola Copenhagen failure and North-South dynamics ..................................................................... 138 Teea Kortetmäki The Role of Legislation and Policies in Promoting Ecological Sanitation: Case Zambia ..................... 147 Mia O’Neill Global governance of water security in agro-food value chains and networks ............................... 159 Suvi Sojamo 3. SUSTAINABLE CONSUMPTION .................................................................... 172 How to revise the concepts of economy ............................................................................. 173 Pekka Mäkelä 3 Towards sustainable society − transforming materialist consumerism ......................................... 185 Arto O. Salonen and Mauri Åhlberg Maximum and minimum consumption − two-dimensional approach in defining a decent lifestyle ..................................................................................................................... 202 Michael Lettenmeier, Satu Lähteenoja, Tuuli Hirvilammi, Kristiina Aalto and Senja Laakso 4. SUSTAINABILITY AND THE SOCIETY............................................................. 213 A conceptual framework for life cycle thinking in transitions toward sustainable waste management ............................................................................................................... 214 David Lazarevic, Nicolas Buclet and Nils Brandt Land use for bioenergy production − assessing the production potentials and the assumptions of EU bioenergy policy ................................................................................................... 230 Francesca Allievi and Jenny Turunen 5. SUSTAINABLE CULTURE........................................................................... 239 Drivers and Barriers to Sustainable Development: A Historical-Futures Perspective (Case Study) ........ 240 Marcus Bussey, R.W.(Bill) Carter, Jennifer Carter, Robert Mangoyana, Julie Matthews, Denzil Nash, Jeannette Oliver, Russell Richards, Anne Roiko, Marcello Sano, Tim Smith, Dana Thomsen and Estelle Weber Measuring Environmental Sustainability among Universities ...................................................... 253 Maryam Faghihimani Designing Sustainability Together − Disciplinary competences in transdisciplinary knowledge building ....................................................................................................... 263 Tatu Marttila 6. SUSTAINABLE ECONOMY .......................................................................... 273 Innovative fiscal policy in the context of sustainability ........................................................... 274 Olivér Kovács Impact of fiscal policies changes on the budgetary revenues and sustainable economic growth ......... 287 Cristian Nicolae Stanica Analysing drivers of and barriers to the sustainable development: hidden economy and hidden migration .......................................................................................................... 295 Lucian-Liviu Albu, Raluca Iorgulescu and Cristian Stanica Future Trends of Genuine Welfare in Finland ....................................................................... 305 Jukka Hoffrén 7. CORPORATE RESPONSIBILITY .................................................................... 314 Integrating Sustainability into Strategy and Innovation A foresight-inspired systematic approach for businesses .............................................................................................................. 315 Bernhard Albert Disruptive Innovations at the Bottom of the Pyramid Can they impact on the sustainability of today’s companies? .................................................................................................... 325 Abayomi Baiyere and Jaspar Roos Implementation of Total responsibility Management into Corporate Strategy ................................ 337 Štefka Gorenak and Vito Bobek Stakeholders and Corporate Social Responsibility in Corporate Responsibility Disclosure .................. 349 Marileena Koskela 4 Global dispute on sustainable business: Analysing MNE-stakeholder relationships in local media texts ...................................................................................................... 359 Hanna Lehtimäki, Johanna Kujala and Anna Heikkinen Purpose of Sustainability Contractual Clauses ...................................................................... 371 Kateřina Peterková Disclosure of material CSR information − comparison of the mandatory CSR disclosure systems for listed companies in the EU and the US ........................................................................... 385 Dániel Gergely Szabó 8. FUTURES METHODS ............................................................................... 400 Need and usefulness for future foresight − Environmental scanning of the rescue services in Finland: trend analysis and future scenarios 2025+ ............................................................. 401 Esko Kaukonen The significance of wild cards and weak signals for sustainability – case of water services ............... 410 Ossi A. Heino and Annina J. Takala 9. SUSTAINABLE TRANSPORTATION ............................................................... 423 Delphi on Transport and CO2 Emissions − Finnish Scenarios up to 2050 ........................................ 424 Vilja Varho, Petri Tapio and Laura Joki Analysing the sustainability of road freight transport − combining multiple sources of information .... 436 Markus Pöllänen and Heikki Liimatainen Affecting the sustainability innovation acceptance through systematic mapping and re-employing of actors, the case of a renewable energy project ............................................... 447 Anastasia Tsvetkova, Magnus Gustafsson and Krys Markowski Small step towards sustainable transport? Media debate over Finnish car tax reform….……………………458 Nina A. Nygrén, Jari Lyytimäki and Petri Tapio 10. SUSTAINABLE ENERGY........................................................................... 468 CO2 economy in the BRIC countries Decomposition analysis of Brazil, Russia, India and China ........... 469 Jyrki Luukkanen, Juha Panula-Ontto, Jarmo Vehmas, Jari Kaivo-oja, Francesca Allievi, Tytti Pasanen, Petri Tapio and Burkhard Auffermann Microalgae as a biofuel feedstock: risks and challenges .......................................................... 488 Liandong Zhu and Tarja Ketola 11. SUSTAINABILITY IN DESIGN ..................................................................... 499 Designing sustainable innovations ..................................................................................... 500 K. Christoph Keller Sustainability Awareness in Design − Bridging the gap between design research and practice ........... 514 Outi Ugas and Cindy Kohtala Sustainability and industrial design in Finland: barriers and future prospects ............................... 526 Pekka Murto 12. ADDITIONAL PAPERS Governance and Institutions for Sustainable Agricultural and Rural Development in Bosnia & Herzegovina............................................................................................................ 538 Sinisa Berjan, Matteo Vittuari and Hamid El Bilali 5 INTRODUCTION Finland Futures Research Centre’s 13th international conference Trends and Future of Sustainable Development was held in Tampere, Finland in June 9–10, 2011. Sustainable development is a topic that has gained importance in local, regional and global scales and requires multidisciplinary and crosssectorial cooperation and sharing of ideas and viewpoints. Environmentally, socially, economically and culturally sustainable development can only be achieved by encouraging knowledge sharing and cooperation between various sectors and decision makers. Finland Futures Research Centre promotes futures oriented research and thinking. Futures studies include tools for describing possible, probable and desirable variations of the present and drafting possible images of the future. By exploring the variety of different possibilities, we can come closer to shaping the future – rather than predicting it. Thus, futures studies can offer valuable tools for the search of sustainable development paths. The conference brought together 168 participants from 16 different countries. Four keynote speeches representing both academia and private sector were invited: • Prof. Alan Warde (University of Manchester): “Social Sciences and Sustainable Consumption” • Executive Vice President of Corporate Relations and Sustainability Anne Brunila (Fortum Corporations): “Tomorrows Sustainable Energy Solutions and Urban Living” • Prof. Peter Nijkamp (Free University Amsterdam): “Sustainability Challenges to Idyllic Landscapes” • Prof. Richard Aspinall (Macaulay Land Use Research Institute): “Accounting for HumanEnvironmental Relationships: Beyond Ecosystem Assessment” In addition, 32 parallel sessions with the following themes were held. Each theme has its own chapter in this publication. 6 • Sustainability Indicators • Sustainability in North-South Perspectives • Sustainable Consumption • Sustainability and the Society • Sustainable Culture • Sustainable Economy • Corporate Responsibility • Futures Methods • Sustainable Transportation • Sustainable Energy • Sustainability in Design In addition, an expert panel chaired by Prof. Markku Wilenius discussed “Measurement and indicators of sustainable development”. The panelists included Prof. Em. Pentti Malaska (Finland Futures Research Centre), Mr. Oras Tynkkynen (Finnish Parliament), Prof. Sergio Ulgiati (Parthenope University of Naples) and Prof. Mario Giampietro (Autonomous University of Barcelona). Hanna Lakkala & Jarmo Vehmas 7 1. 8 SUSTAINABILITY INDICATORS GROUPING AND RANKING THE EU-27 COUNTRIES BY THEIR SUSTAINABILITY PERFORMANCE MEASURED BY THE EUROSTAT SUSTAINABILITY INDICATORS Francesca Allievi, Jyrki Luukkanen, Juha Panula-Ontto and Jarmo Vehmas Finland Futures Research Centre University of Turku ABSTRACT – This paper presents the results of a sustainability indicator study on the EU-27 countries where the countries are grouped by hierarchical cluster analysis on the basis of their performance measured with the used sustainability indicators. The used sustainability indicators can themselves be grouped into social, environmental and economic indicator groups, reflecting the different “aspects” of sustainability. In the study, indicators in the three groups have also been calculated into aggregate indicators and the EU-27 countries can be compared and ranked according to their performance measured by these aggregate indicators. 1. Introduction to the EU-27 case study This case study was developed within the FP7 project SMILE (Synergies in Multi-scale Inter-Linkages of Eco-social systems, more information available at: http://www.smile-fp7.eu/ ) and was one of the case studies designed to assess the sustainability in the EU context from the economic, environmental and social point of view. Specifically this case study was carried out as part of task 3.7, which requested a study where EU27 countries are grouped in terms of their sustainability performance, assessed by using a set of sustainability indicators. These will be described in detail later on. The grouping of the countries considered is carried out by applying hierarchical cluster analysis to the selected indicators. Sustainability performance is evaluated also through the calculation of aggregate indicators for the different dimensions of sustainability, so that it is possible to rank the countries in terms of their performance. The aim of this paper is therefore to present both the methodology used and the results of this cluster analysis and of the aggregate indicators created. 9 2. Material and methods 2.1. The Eurostat sustainability indicator data set The Eurostat Sustainable Development Indicators (SDIs) are used to monitor the EU sustainable Development Strategy (EU SDS). This set is constituted by more than 100 indicators divided into subthemes, such as Demographic changes, Climate change and energy, Sustainable transport and Social inclusion (Eurostat, 2011). Of these 19 indicators were selected according to their relevance for each of the sustainability dimensions considered in this study. They will be described in paragraphs 2.4.1, 2.4.2 and 2.4.3. 2.2. Cluster analysis as a method of grouping EU-27 countries Cluster analysis is used in many disciplines for different purposes, but with the same aim of creating groups; cluster analysis is an umbrella-term for different algorithms that generate groups of statistical cases whose members are similar to other members of the same group on the basis of a certain criteria. The basic data needed as input for the cluster analysis is thus a matrix X containing the variable values for each of the objects under investigation, which in the present work correspond to the EU27 countries, that is  x11   x 21 X = :  x  n1 x12 x 22 ... ... xn 2 ... x1 p   x2 p  :   x np  The purpose of cluster analysis in this case is thus to group the countries, represented by the n rows of X, according to similarities (or proximities) reported in the p columns of X, which in our case are the values for each of the indicators considered. Different methods are available to proceed with the analysis, but in the case of hierarchical agglomerative clustering, which is used in this study, the classification consists of a series of partitions of the data where the first consists of n single-members clusters, while the last is made by a single group containing all n individuals: at each step individuals or groups of individuals which are closest are fused together (Everitt, 1993). As the indicators included in this analysis were of various natures, the cluster analysis was executed on the normalized distance matrices of the indicators. Thus, before proceeding with the cluster analysis the distance matrix of each indicator had to be calculated and the distances normalized. However, since the indicators were of different measurement scales (years, percentages, kgoe, etc.), they could be put in the same matrix only after they had been normalized. To compute the distances of each indicator, the city block distance was used. This distance measure represents the distance between points in a city road grid and examines the absolute differences between the coordinates of a pair of 10 n objects, i.e. countries. The city block distance is calculated as: dij = ∑ xik − x jk k =1 . The entries of the obtained distance matrix were then normalized by dividing them by the maximum value of the distance matrix. 2.3. Scoring and ranking The countries analyzed in this study were scored according to their sustainability performance measured with the selected indicators. For each indicator a weight and a ranking logic were selected. The weight measures the relative importance of the indicator in respect to the other indicators in the same dimension, and it also determines the maximum scoring points available from that indicator, i.e. the points given to the best performing country measured by the indicator. The ranking logic determines if the smallest or greatest value of the indicator is seen as the best performance: normal ranking logic implies a higher score for a greater value, while reversed ranking logic implies a higher score for a smaller value. For each indicator, the best performing country was given the number of points equal to the weight of the indicator, while the worst performing country was given a score of zero; the other countries received a linearly scaled score according to their relative performance in respect to the best performing country. The normalized total score indicates the country’s performance measured by the selection of sustainability indicators in comparison to the overall best performing country in the EU-27 group. This analysis does not give a picture of the development of performance over time, only the performance of the EU-27 countries in relation to each other. 2.4. Indicator and relative weight selection 2.4.1. Social dimension indicators Weight Ranking logic Indicator 4 2 4 4 4 Reversed Normal Reversed Reversed Reversed Total longterm unemployment rate (%) Life expectancy at age 65 for males Suicide death rate (crude death rate per 300 000 persons) Persons with low educational attainment (%) Early schoolleavers (%) Total long-term unemployment rate (%): this indicator was selected for its relevance in the context of social sustainability. Unemployment is known to go hand in hand with a number of other social problems. A weight of 4 was chosen as it is the only indicator relative to the working conditions which is present in this analysis. 11 Life expectancy at 65 for males (years): life expectancy at 65 gives a view to the general health of the population as well as the health care system. Life expectancy for males displays more variance than female (or total) life expectancy and was therefore selected. Suicide death rate (crude death rate per 300 000 persons): this indicator was chosen as a proxy indicator of the happiness of the population. The suicide death rate of three age classes (15-19 years, 5054 years and over 85 years) were summed up so to calculate the “total suicide death rate” for each country. Persons with low educational attainment (%): education was considered as a very relevant aspect of sustainability within the social dimension, thus a weight of 4 was given to this indicator. Data was adequately available only from 2000 onwards. Early school leavers (%): for the same reason presented above, also this indicator received a weight equal to 4. Data was adequately available only from 2000 onwards. 2.1.2 Environmental dimension indicators Weight Ranking logic Indicator Weight Ranking logic Indicator 2,5 4 2,5 2,5 3 Reversed Normal Reversed Reversed Reversed Final energy consumption of road transport (TOE/capita) Renewable energy (% gross electricity consumption) Municipal waste generated (kg/capita) Motorization rate (number of cars per 1000 people) Emissions of particulate matter from road transport (kg per capita) 1,5 Reversed Emissions of acidifying substances (kg per capita) 1,5 2,5 Reversed Reversed Emissions of ozone Domestic precursors (kg Material of ozoneConsumption forming (tonnes/capita) potential / capita) 1,5 Normal Area under organic farming (% of utilized agricultural area) Final energy consumption of road transport (toe/capita): this indicator was selected to describe the transportation pattern of the countries considered. As there are also two other indicators dealing with road transport, a weight of 2,5 was chosen. Renewable energy (% in total energy consumption): being the only indicator relative to the use of renewable energy in this set, it was given a weight equal to 4. Municipal waste (Kg/capita): Municipal waste indicates a strain on the environment that a consuming population cannot easily export to other statistical geographic entities and is for this reason a well suited indicator of sustainability at the local level when compared to, for example, heavy industry emissions. A weight of 2,5 was chosen for this indicator as it is relevant, but gives no indication of the waste treatment typology. 12 Motorization rate (number of cars/ 1000 people): this indicator was selected because of its relevance in describing the transportation habits of a country. As there are also two other indicators dealing with road transport, a weight of 2,5 was chosen. Emissions of PM from road transport (kg/capita): This indicator was considered relevant in assessing the pollution deriving from the transportation sector. As there are also two other indicators dealing with road transport, a weight of 3 was chosen. This indicator can be criticized on the grounds that the average population densities of EU27 countries differ greatly. Emissions of acidifying substances (kg/capita): together with the other two indicators relative to pollution, it assesses the air quality of the countries considered. A problem with industry emissions is that production of consumer goods is global and an economy consuming products of industries producing acidifying substances might not be the same statistical geographic entity. A weight of only 1,5 was chosen, as it is difficult to estimate the emissions deriving from industries established abroad (especially in Asia) by EU countries. Emissions of ozone precursors (kg/capita): the same description of the previous indicator is valid. Domestic Material Consumption (tonne/capita): this indicator was chosen because it assesses the amount of material used by an economy. For this indicator data was adequately available only from 2000 onwards. Area under organic farming (% of utilized agricultural area): this indicator was selected in order to give information concerning the consumers’ demand for organic produce. For this indicator data was adequately available only from 2000 onwards. 2.1.3. Economic dimension indicators Weight Ranking logic 2 3 3 2 3 Normal Reversed Normal Reversed Normal General government gross debt GDP per capita in Purchasing Power Standards (PPS) (EU-27 = 100) Energy dependency Total employment rate (%) Indicator Total R&D expenditure (%of GDP) Total R&D expenditure (% of GDP): this indicator was selected for its relevancy in evaluating the willingness of a government to invest in research and development, as well as the amount of money available for that. However, a weight of only 2 was chosen because the added sustainability largely depends on what type of R&D activities derive from these investments. General government gross debt (% of GDP): this indicator was selected to give information concerning the financial health of the governments in the EU countries. As it is considered quite relevant to assess the economic prosperity, a weight equal to 3 was given. 13 GDP per capita (PPS with EU27=100): this is the most direct measure of economic prosperity, thus a weight of 3 was given. Energy dependency (% of consumption): this indicator was selected to evaluate the selfsufficiency of a country in energy terms. The sustainability level depends on what kind of energy is imported Total employment rate (%): this is another straightforward measure of the financial health of a country, thus a weight of 3 was selected. Time series from 1996 to 2006 was selected, but the best data coverage was between 1997 and 2005. In the case of missing values, data was imputed through the use of, average, backcasting or forecasting formulas, depending on the specific case. The threshold of data imputation was set to 15%: if more than this share of data was missing for a specific year, that indicator was excluded from the analysis. 3. Results 3.1. Cluster analysis results Figure 1. Results for the cluster analysis within each dimension for year 2005 In Figure 1 above are reported the results of the hierarchical agglomerative clustering carried out on the EU-27 countries for the three dimensions of sustainability for the year 2005. Each color denotes a different cluster. The clusters described here were obtained by choosing the point of the dendogram with the longest distance between two consequent iterations. The dendogram was derived using the statistical analysis program SPSS, by running the hierarchical clustering process on the distance matrixes described previously. In the Social Dimension the clusters formed are the following: Cluster 1: Estonia, Latvia, Hungary, Lithuania Cluster 2: Poland, Slovakia Cluster 3: Czech Republic, Slovenia, Bulgaria, Romania Cluster 4: Denmark, Finland, Sweden, Austria, France, Germany Cluster 5: Ireland, United Kingdom, Luxembourg, Netherlands, Belgium, Greece, Cyprus Cluster 6: Malta, Portugal 14 Cluster 7: Italy, Spain As can be understood from the clusters above, there is a clear distinction between the developing economies and countries such as Germany, UK and France which fall in two separate - but close clusters. Another cluster is made of the Mediterranean countries: Malta, Portugal, Cyprus and Greece, with Italy and Spain very close as well. In the case of the Environmental Dimension, the clusters obtained are the following: Cluster 1: Estonia, Greece, Czech Republic, Portugal, Slovenia, Spain, Belgium, Italy, Sweden Cluster 2: Hungary, Lithuania, France, United Kingdom, Germany, Netherlands, Malta Cluster 3: Poland, Slovakia, Romania, Bulgaria, Latvia Cluster 4: Cyprus, Ireland Cluster 5: Denmark, Finland, Austria Outlier: Luxembourg In this dimension the clusters appear more varied than in the social dimension. The distinction between developing economies and richer countries is not that clear anymore in the clusters. This is especially evident in Cluster 1 and 2, which group countries very different among themselves. Luxembourg is completely separated from all the other countries and remains an outlier until the last iteration. For the Economic Dimension the clusters are the following: Cluster 1: Latvia, Lithuania, Estonia, Bulgaria, Romania, Poland, Hungary, Slovakia Cluster 2: Cyprus, Portugal, Greece, Italy, Malta Cluster 3: Czech Republic, Slovenia, Ireland, Spain Cluster 4: Austria, Germany, France, Belgium Cluster 5: Netherlands, United Kingdom, Finland, Sweden Outliers: Denmark, Luxembourg In the case of the Economic Dimension, it appears that the developing economies end up mostly in Cluster 1, Mediterranean countries in Cluster 2 and the bigger economies in Cluster 4 and Cluster 5. Luxembourg is again an outlier, together with Denmark. It is important to note that each dimension presents a different set of groups, so there is no evident cohesion in the grouping of the countries for the three thematic areas. This underlines how important it is to keep this distinction when analyzing sustainability at the national level, as it cannot be assumed that the behavior in one dimension will be replicated in the other two as well. 3.2. Ranking results In this chapter the ranking results are presented for each dimension and for the years 1997 and 2005. 15 3.2.1. Social dimension Cyprus Sw eden Denmark Netherlands Austria United Kingdom Germany Czech Republic Luxembourg Greece Finland Country Poland France Romania Slovenia Belgium Ireland Portugal Italy Estonia Slovakia Malta Spain Latvia Lithuania Bulgaria Hungary 2 0 10 8 6 4 12 14 Score Figure 2.a. Ranking results for the social dimension in 1997 Sw eden United Kingdom Denmark Cyprus Ireland Finland Netherlands Austria Luxembourg Belgium Czech Republic Country Greece Slovenia Germany France Italy Poland Romania Spain Latvia Estonia Slovakia Lithuania Hungary Bulgaria Malta Portugal 0 2 4 6 8 10 12 14 16 Score Figure 2.b. Ranking results for the social dimension in 2005 Figure 2.a shows the ranking and the scores for the social dimension in 1997. Cyprus is the best performing country in the EU27 group. It performs well when measured by the selected social dimension indicators by having very low unemployment, low suicide rate and high life expectancy at 65. When measured by the education related indicators Cyprus does not perform as well. Data for early school leavers was sufficiently available only from 2000 onward, so it is missing from 1997 year ranking. 16 The northwestern European cluster is also performing well in the social dimension, having moderate to high scores in suicide, unemployment and life expectancy indicators and high scores in education indicators. The eastern European cluster appears to be performing very well when measured by the educational indicators, but poorly with the other indicators. As shown in Figure 2.b, the ranking by social indicators for the year 2005 is mostly the same. The difference in scores between eastern European cluster and the northwestern cluster have become smaller. Portugal’s relative performance has worsened greatly. 3.2.2. Environmental dimension Latvia Romania Slovakia Portugal Austria Lithuania Poland Sw eden Greece Hungary Bulgaria Country Malta Czech Republic Netherlands Spain Estonia France Italy Belgium Finland Ireland Germany Slovenia United Kingdom Denmark Cyprus Luxembourg 0 4 2 8 6 10 14 12 16 Score Figure 3.a. Ranking results for the environmental dimension in 1997 Latvia Romania Slovakia Sw eden Poland Czech Republic Lithuania Austria Portugal Italy Hungary Country Greece Germany Netherlands France United Kingdom Bulgaria Slovenia Malta Estonia Denmark Finland Belgium Spain Ireland Luxembourg Cyprus 0 2 4 6 8 10 12 14 16 18 20 Score Figure 3.b. Ranking results for the environmental dimension in 2005 17 As can be seen in Figure 3.a, countries in the eastern European cluster perform very well in the environmental dimension with the selected set of indicators by having low energy consumption of road transport and generating little municipal waste and emissions, and also by having a relatively low motorization rate. From the northwestern European cluster Sweden is performing best, by having average emissions and municipal waste generation and a high score in renewable energy use, as other countries with large hydroelectric reserves do. Indicators that would consider emissions and waste in relation to the wealth generated in the economy could give very different results and ranking. Figure 3.b shows the total score of the environmental dimension for year 2005. The eastern European countries are still scoring high on many indicators, but the upward trend in the standard of living has made the difference between western and Eastern Europe in environmental dimension scores grow smaller. 3.2.3. Economic dimension Figure 4.a shows the economic dimension total score for the year 1997. For most indicators the northwestern European countries perform best. Eastern european countries have little government debt and receive high scores when measured with that indicator. Southern Europe performs quite poorly with all indicators. United Kingdom Denmark Luxembourg Sweden Netherlands Czech Republic Finland Germany Austria France Slovenia Country Estonia Poland Romania Portugal Lithuania Ireland Latvia Cyprus Slovakia Belgium Spain Hungary Malta Italy Greece Bulgaria 0 1 2 3 4 5 6 7 8 9 10 Score Figure 4.a. 18 Ranking results for the economic dimension in 1997 Denmark Sweden Luxembourg United Kingdom Finland Netherlands Ireland Estonia Austria Slovenia Czech Republic Country Germany France Latvia Lithuania Spain Romania Portugal Cyprus Belgium Slovakia Bulgaria Poland Hungary Greece Italy Malta 0 1 2 3 4 5 6 7 8 9 10 Score Figure 4.b. Ranking results for the economic dimension in 2005 Figure 4.b shows the total score for economic dimension for the year 2005. It can be noted that differences between EU27-countries’ relative performance have become much greater and Denmark’s superior performance is even more pronounced than in 1997. 4. Discussion and Conclusions As can be seen from what was presented here, this analysis should be considered solely as an example of what can be done to study sustainability in EU27 countries with the data currently available. Lack of data has been the major problem in this study and the final set used implied a relevant amount of data imputation. For the same reason certain indicators which would have given an interesting contribute to the analysis, had to be left out (i.e. gender pay gap). This issue therefore limits the wideness of the indicators set and should be one of the main points to be taken into account when evaluating the final results. The final results, especially the ranking, depend also on the choices made in the selection of the related weights, which are in the end arbitrary. In order to see the effects of a different selection, the tool created for this purpose can be used and new results can be obtained rather quickly. Results of different assumptions should be then compared to evaluate their consistency. Further developments of this study could include a deeper sensitivity analysis, for example through the use of different cluster analysis and ranking techniques, and the comparison of the obtained results. If forecasted data was available, it would also be possible to carry out the same analysis for future years, thus contributing to the creation of possible scenarios and future planning. The comprehensive set of results and data used is available on an excel file available on the SMILE website (http://www.smile-fp7.eu/). 19 References Eurostat (2011) Eurostat sustainable development indicators, http://epp.eurostat.ec.europa.eu/portal/page/portal/sdi/indicators, retrieved 4.5.2011. Everitt, B.S., 1993. Cluster Analysis, third ed. Arnold, London. 20 “WALKING IN OTHER’S SHOES” – EXPERIENCES OF USING THE DECOIN TOOLS TO CHARACTERISE SUSTAINABILITY TRADE-OFFS IN SCOTLAND AND THE CAIRNGORMS NATIONAL PARK K.B. Matthews, K.L. Blackstock, K. Buchan, D.G. Miller and M. Rivington The James Hutton Institute Institute, Craigiebuckler, Aberdeen, AB15 8QH, k.matthews@macaulay.ac.uk ABSTRACT − The paper presents the experiences of using two of the DECOIN tools, SUMMA (Sustainability Multi-criteria Multi-scale Assessment) and MuSIASEM (Multi-Scale Integrated Analysis Societal Ecosystem Metabolism), to characterise sustainability trade-offs in Scotland and the Cairngorms National Park (CNP). The paper reflects on the theoretical basis of the two tools that provide for complex eco-social systems a coherent conceptual and methodological framework within which to understand better sustainability trade-offs. Translating theory into practice, particularly using tools and methods developed by others, however, remains a challenge. The paper reports the progress of the analysis of changes in the sustainability of the agriculture sector (1991 to 2007 using SUMMA) and for the wider economy (2005-2009 using MuSIASEM) for Scotland and the CNP. Approaches to the communication of SUMMA and MuSIASEM outputs for stakeholder audiences are also presented. The paper concludes that the DECOIN tools have significant utility in conducting theoretically coherent, practical for implementation and policy relevant assessments of sustainability trade-offs but that “walking in others shoes” is not always comfortable. 1. Introduction The Synergies in Multi-Level Inter-Linkages in Eco-social Systems (SMILE) 1 project seeks to further develop and apply the DECOIN 2 tool kit. This toolkit consists of three models: SUMMA (Sustainability Multi-criteria Multi-scale Assessment); MuSIASEM (Multi-Scale Integrated Analysis Societal Ecosystem Metabolism) and ASA (Advanced Sustainability Analysis). The ambition of the SMILE project is to combine these tools into a system of sustainability accounting that provides useful insights into the dynamics of the sustainability of complex coupled eco-social systems (Giampietro et al. 2009). 1 2 http://www.smile-fp7.eu/ http://www.decoin.eu 21 The authors applied both the SUMMA and MuSIASEM tools in a case study focused on the Cairngorms National Park (CNP). The objectives of the research were to test the utility for end-users and transferability of the DECOIN tools beyond their development teams and applications. This is reported in Blackstock et al. (in this proceeding). The case-study also tried to assess the role of economic growth in achieving sustainability objectives and the trade-offs between sustainability objectives. This paper reports progress made towards these objectives and highlights the strengths and weaknesses of the DECOIN tools. The SUMMA and MuSIASEM tools take complementary but distinct approaches to the characterisation of the sustainability of eco-social systems. SUMMA is a life-cycle oriented assessment of the economic-environmental performance of a system. SUMMA uses multiple metrics to characterise system performance. SUMMA considers both the upstream draw on resources and the downstream consequences of waste. MuSIASEM is a conceptual approach to assessing overall performance and performance of components of a system. MuSIASEM incorporates human activity, value added, energy use and land, without resorting to a weightings based normalisation to a single unit of measure. Combined together as defined by the MuSIASEM “grammar” these dimensions provide a coherent and systemic characterisation using indicators of stocks and flows of resources. A key feature of SUMMA and MuSIASEM is the multi-scale nature of the analysis. This allows the explicit comparison of overall performance and of components, be they sectors or geographically defined regions. This can be highly informative as the “averages” of higher level performance may be made up of very distinctive elements, such that policy or other interventions based on the averages may be entirely inappropriate. In both SUMMA and MuSIASEM the extent and intensity of resource use is simultaneously considered. This is essential to ensure that improvements in efficiency are not eliminated by a rebound in consumption (Jevon’s paradox). 2. Materials and Methods 2.1. Case-studies The Cairngorms National Park was created as a result of the National Park (Scotland) Act in 2003. It is home to approximately 16,000 human residents as well as significant protected habitats and species. National Parks in Scotland are explicitly required to achieve ‘sustainable development’. Therefore, they are not ‘wilderness reserves’ but fit the IUCN category V (protected landscape). With partners at Parthenope University it was decided that the SUMMA based analysis would focus on the productionoriented land-based industries (PoLbI) (agriculture, forestry and sporting estates). The importance of the sector has been variously argued from minimal (gross value added), to marginal (employment), to important (downstream environmental impacts) and finally as crucial (landscape/character of the region). The focus on PoLbI played to the strengths of the authors and built on a tested SUMMA model for the agricultural sector in Campania (Ulgiati et al. 2008). For the MuSIASEM analysis the case study undertook analyses at Scotland wide level, local authority level and for the CNP as a whole. The analyses considered societal averages, the paid work and industry based sub-sectors. The MuSIASEM case-study followed existing published approaches (Giampietro 2004;Giampietro and Mayumi 2000). 22 2.2. Methods Figure illustrates the key stages in the case study analysis. For more in-depth description of the materials and methods see the relevant SMILE deliverables 1. The key challenges in undertaking the analyses were familiarisation with the DECOIN methods (WP2), agreeing a scope with the CNPA through the systems diagramming activity (WP2) and sourcing and integrating the required datasets (WP3). SUMMA is demanding in terms of its data requirements (>250 input values for each of the three time periods). While with MuSIASEM it is possible to progressively step into the degree of detailed required, there were many challenges of incompatible sectoral classifications and units of spatial collection. Several of these could be overcome by accessing more detailed datasets, but energy throughput datasets were limiting both in terms of spatial resolution and length of time series available, (only from 2005). For land use there are multiple sources but their integration (beyond the agricultural sector) is limited. Indeed it was not possible to complete the within-CNP land use analysis within the scope of SMILE. WP4 WP2 CNP CNPA DECOIN D23 D16 D30 Data WP3 D29 WP5 D28 with with he tools other actions and cales occur amiliarization or nd the trade at different offs economic Systems processes Diagramming Diagrams Scoping Setting How synergies Up Thematic Utility Comparative Case (this Study document|) report Analyses Report the Analyses with ocial/policy if sing data the available) Role of policy and Gathering objectives chieving rowth in multiple -& Modifying the nterfacing WP4 WP2 CNP CNPA DECOIN D23 D16 D30 Data WP3 D29 WP5 D28 with with he tools other actions and cales Role of economic occur amiliarization or nd the trade at different offs Systems processes Diagramming Diagrams Scoping Setting How synergies Up Thematic Utility Comparative Case (this Study document|) report Analyses Report the Analyses with ocial/policy if sing data the available) policy and Gathering objectives chieving rowth in multiple -& Modifying the nterfacing Figure 1. Scotland case study activities and deliverables. 3. Results Within this paper it is only possible to present examples of the key types of outputs used in communications with stakeholders at CNPA, not to summarise all the outputs generated 2. 1 2 www.macaulay.ac.uk/SMILE See www.macaulay.ac.uk/SMILE for more comprehensive examples. 23 3.1. SUMMA examples Emissions are a key issue for land use in Scotland. The extent of emissions tonnages for ScotAG and CNPAG relative to the baseline year (1991) is presented in Figure. Note that to assess the GHG potential for each of the tonnages presented they need to be converted to tonnes of CO2 equivalent. In terms of CO2 it can be seen that for both the CNP and Scotland there is an increase in the emissions from 1991 to 2001 followed by a decrease to below 1991 values by 2007. This reflects a process of intensification based on the structure of agricultural subsidies that was reversed after 2003. For methane and nitrous oxide the pattern is of a reduction from 1991 but with less reduction after 2001. 1.10 CO2 1.10 1.00 CH4 0.90 1.00 CH4 CO 0.80 0.70 0.70 N2O NOx PM10 Figure 2. CO 0.90 0.80 CNP1991 CO2 N2O PM10 SO2 CNP2001 NOx CNP2007 Sco1991 SO2 Sco2001 Sco2007 Total Emissions from ScotAG and CNPAG 1991-2007 The relative pattern of emissions for CNPAG and ScotAG have strong similarities in terms of the overall shape of the spider plots. Scotland has a stronger increase by 2001 in CO2, NOx, SO2 and PM10’s associated with more mechanised sectors of agriculture, but also a greater reduction (by 2007), perhaps reflecting a greater reduction in intensity in more remote rural areas pulling down the overall Scotland totals. Comparing CNPAG and ScotAG also provides useful information about the different nature of their production systems. Figure presents the relative emissions intensities for CNPAG and ScotAG for each of the indicators for 2007 (earlier patterns are consistent but with minor variations). The emissions per ha shows the CNPAG as a very low intensity system (less so in terms of CO2 but still low) compared with an overall ScotAG average. In terms of emissions per kg of dry matter and per Mj of embodied energy the CNPAG system can be seen to be relatively inefficient since it requires up to six times emissions to generate a comparable output. This reflects the marginal nature of the bio-physical resource available to land managers within the park (in terms of production). This lack of efficiency, is though, offset by the higher value per unit of production so that emission per € are three rather than six times the ScotAG average. 24 Emissions per ha - 2007 CH4 N2O 1.00 0.80 0.60 0.40 0.20 - Emissions per kg dry matter - 2007 CO2 6.00 CO NOx CNP2007 Figure 3. SO2 CNP2007 Sco2007 Sco2007 Emissions per € - 2007 CO2 PM10 NOx PM10 Emissions per Mj - 2007 N2O CO - N2O SO2 CNP2007 CH4 4.00 CH4 2.00 PM10 8.00 6.00 4.00 2.00 - CO2 3.00 CO CO2 2.00 CH4 CO 1.00 NOx SO2 Sco2007 - N2O PM10 CNP2007 NOx SO2 Sco2007 Emissions intensities for CNPAG relative to ScotAG in 2007 3.2. MuSIASEM examples The combination of Exosomatic Metabolic Rate (mj/hr of activity, EMR) and Economic Labour Productivity (£/hr of activity, ELP) is a particularly useful compound indicator of the sustainability trajectory. This combined analysis reveals complex systems behaviour in terms of trajectories and groups of the regions that can be considered together. Two versions are presented: the societal average and paid work. Figure presents the societal average EMR/ELP trajectories. Overall there is a pattern of increasing ELPSA with (in nearly all cases) no increase in EMRSA. There is a distinctive pattern to the trajectories, with increases in ELPSA between 2005 and 2007 followed by stagnation (or even decline). For EMRSA the pattern is of either consistent reduction or fairly constant values (2005 to 2007) followed by reductions (2007 to 2009). For regions with lower values for ELPSA the increases in ELP are smaller and in some cases the reductions in EMR are significant (e.g. Clackmannanshire and Fife perhaps reflecting further deindustrialisation). Contrast this with the main population centres (Edinburgh, Glasgow and Aberdeen with its hinterland) where there is significant increase in ELPSA combined with reductions in EMRSA. An overall interpretation from Figure could be that at a societal average level there is a trend to more sustainable growth (albeit to a limited extent). Societal average indicators, however, contain both paid work and household sectors that are behaving quite differently. For the paid work sector the analysis of EMR/ELP has distinct features. It is clear that for some regions the improved performance for EMR at societal average level is an improvement in the household 25 sector not in the paid work sector as the EMRPW value is near constant (e.g. Edinburgh and Glasgow). Note that for both these cities despite near static EMR values there has continued to be apparent growth in ELPPW. also shows the value of combining EMRPW and ELPPW in terms of distinguishing distinctive clusters of regions with common sustainability characteristics. These clusters include the main cities as noted above, the Scottish Islands (Orkney, Shetland and Western Isles), city regions (Aberdeen and Dundee but also the Greater Glasgow area) and regions that retain industry or intensive agriculture (East and Mid Lothian, Clackmannanshire and Fife, Perth, Kinross and Stirling and Dumfries and Galloway). The MuSIASEM fund-flow (FF) diagram is a means of simultaneously presenting the relationship between a fund (e.g. human activity) and a flow (e.g. energy throughput) and at two scales (e.g. societal average and paid work, or paid work and sectors of the economy). The FF diagram is helpful in presenting both the extent (on the axes) and the intensity (on the diagonals) of resource use. Figure compares the CNP and Scotland for each sector using THA, GVA and ELP. Within each FF figure it is possible to assess the relative importance of each sector (by size) and the relative efficiency as defined by the ELP. Comparing FF diagrams the balance of sectors within both regions is apparent. Note that all the FF diagrams are scaled in both THA and GVA relative to the largest sectors present. This allows structural comparisons. Note that the shape of the quadrants provides a visual representation of the balance between THA and GVA. Where the proportions are equivalent the quadrant is a square (e.g. construction), where longer in the x-axis the sector generates more GVA than its proportion of THA would predict (e.g. Business, Services and Finance), where longer in the y-axis the sector generates less GVA than the THA would predict (e.g. Pubic Administration and Services and Retail, Recreation and Transport). 4. Discussion and Conclusions The SUMMA analysis found that there have been significant changes in the extent and intensity of agricultural production and its environmental impacts. Our conclusion is that for the agricultural sector as a whole there are unavoidable trade-offs between production and environmental impacts and little or no evidence of synergies, win-wins, dematerialisation or sustainable growth. There is a pattern of increasing resource use and impact from 1991 to 2001 and a subsequent reduction back to 1991 levels by 2007. This fits well with agricultural policy over the period 1991 to 2007. The high water mark of intensification was pre the 2003 CAP reforms with subsequent reduction in production on the least intensive areas. There is little to suggest fundamental changes in the relationships between resource inputs, the outputs from the system and the environmental load. The MuSIASEM analysis has shown that there is a complex relationship between economic growth and the other indicators of sustainability. This complexity is in terms of the distribution (spatial, sectoral and between social groups) but also in terms of the nature of the growth. In some cases growth simply means increasing extent with more people supported at the same standard of living. In other cases there are changes in the intensity (productivity of labour and energy). From within this complexity it has been possible to begin to identify groupings of regions, their trajectories in terms of growth and the other indicators and to use these to better understand the overall Scotland level assessment and to contextualise the CNP. 26 The MuSIASEM results for the CNP are significantly different from the a priori expectations of the research team. That the CNP has features in common with the cities of Scotland was unexpected. The importance within the area of tourism and recreation means that the CNP has a significant retail and recreation sector. The attractiveness of the area (physical environment) also means that there is a larger than expected business sector with businesses located in the CNP but providing services beyond the park boundary. That the CNP has a more city-like population distribution, retaining young adults, could indicate a successful and sustainable rural economy. It could also mean that the CNP supports a minimum-wage based service economy based on migrant labour. The CNP GVA figure are noted by the CNPA as being inflated by the distilling industry with the income “leaking” from the Park. From the MuSIASEM analysis there is little or no evidence of ongoing dematerialisation, that is a break in the fundamental relationship between energy use and wealth (or at least GVA) generation. Lower values of EMR simply reflect a post-industrial sectoral mix that has the net effect of exporting the energy and environmental footprint elsewhere. Given Scotland’s commitment to an 80% cut in greenhouse gas emissions by 2050 it is difficult to see how this can be achieved with the current population and/or standard of living, without fundamentally rethinking and reorganising patterns of production and expectations of consumption. 4.1. Strengths and weaknesses of the tools SUMMA looks both upstream at the effect of inputs drawn into the system and downstream to the outputs and wastes. It is thus possible to make explicit judgements on the costs and benefits of a system. Emergy analysis, particularly the intensity ratios, is effective in providing a high level summary of the nature of resource use. Time series of SUMMA outputs identify trends and the impacts of key drivers. Comparison between systems or scales provides an external referent against which to objectively judge system performance. Where there is an existing SUMMA application the process of use is simpler than for MuSIASEM. If, however, modifications need to be made, these cannot be easily undertaken by nonexperts. This implies a dependence on the SUMMA developers that can be difficult for them to service. Consideration should be given to investing in the development of a more modular and reusable SUMMA tool that is suited to supporting the development of new applications by third parties. MuSIASEM provides a systematic evaluation of sustainability, linking evaluations of economic growth to population, energy and land use. The use of a decomposition approach is effective in ensuring that “average” values are fully understood as being the outcomes of mixes at regional or sectoral level. The approach is also effective in demonstrating the dependencies between productive and consumptive sectors. The strongly empirical nature of the MuSIASEM analysis means it is grounded in reality as perceived by stakeholders. This is effective in making it accessible to stakeholders but MuSIASEM’s more challenging conceptual basis can be a barrier to credibility. There were significant challenges in sourcing adequate data to support some of the MuSIASEM analysis despite experience and expertise in data integration and manipulation. This can lead to undesirable compromise the indicators used (data shaping the modelling). Both SUMMA and MuSIASEM are strongest in analysing the links between environment and economics. They make these analyses in a scientifically coherent fashion, rather than through the use of ad hoc indicators. Where they perform less well is in including the social and cultural dimension of 27 sustainability. While non-use and existence values have been debated within the SMILE consortium there still remains a significant intellectual challenge in defining analyses that are salient, credible and legitimate. Indeed it may be that such social aspects are inherently unsuitable for computer-based modelling and quantification and need to use mixed methods (incorporating qualitative analysis and participatory research processes). 4.2. Implications for mainstreaming the use of SUMMA and MuSIASEM Both SUMMA and MuSIASEM face an implementation gap in terms of being used for policy-making or management. There are challenges in how to communicate the outputs of the research in a form that is succinct and accessible but does not lose rigour or oversimplify. Issues raised by stakeholders include making transparent the assumptions within the input data, demonstrating how the calculations of the indicators are made and the unfamiliarity of concepts such as emergy. These challenges are doubly difficult when they question established orthodoxy, both in what is important in policy terms (growth) and how it is measured and interpreted. There are significant and powerful vested interests that would be undermined by a more holistic view of sustainability and a more nuanced view of the benefits and detriments of growth. Mainstreaming will require the undertaking of transdisciplinary research, including both academics and stakeholders, with the stakeholders having a more formal role in shaping of research. Such projects ensure the salience of the research and build credibility for the methods and data through processes of stakeholder peer-review. The authors conclude that SUMMA and MuSIASEM have significant utility in conducting theoretically coherent, practical for implementation and policy relevant assessments of sustainability trade-offs but that “walking in others shoes” is not always comfortable. References Giampietro, M. 2004. Multi-scale integrated analysis of agroecosystems Boca Raton, Florida., CRC Press. Giampietro, M. & Mayumi, K. 2000. Multiple-scales integrated assessments of societal metabolism: Integrating biophysical and economic representations across scales. Population and Environment, 22, (2) 155-210 Giampietro, M., Serrano, T., & Sorman, A. 2009, Tool Manual, DECOIN: Development and Comparison of Sustainability Indicators, Project No 044428, FP6-2005-SSP-5A, Deliverable D4.4 of WP4. Ulgiati, S., Zucaro, A., Bargigli, S., Franzese, P., Raugei, M., Vehmas, J., Luukkanen, J., Pihaljamaki, M., Giampietro, M., Gamboa, G., Lobo, A., Sorman, A., & Waldron, T. 2008, Documentation - User and client documentation for the DECOIN tools, SMILE: Synergies in Multi-scale Inter-Linkages of Eco-social systems, Project No 217213, FP7-SSH-2007-1, Deliverable 3 of WP2. Acknowledgments This research was funded by EU FP7 SSH project SMILE (Project No. 217213) and by the Scottish Goverment research programme “Environment: Land Use and Rural Stewardship”. 28 Figure 4. ELPSA vs. EMRSA for Scotland, CNP & NUTS3 (omitting Falkirk) 29 Figure 5. 30 Fund-Flow analysis of Scotland and CNP by sector using GVA and THA SUSTAINABILITY CRITERIA AND INDICATORS – A TOOL FOR STRATEGIC URBAN PLANNING Tarja Söderman1, Leena Kopperoinen1, Sanna-Riikka Saarela1, Vesa Yli-Pelkonen2, Adriaan Perrels3, Juhana Rautiainen4 and Mirka Härkönen4 1Finnish Environment Institute SYKE, Built Environment Unit, Helsinki, Finland email: firstname.surname@ymparisto.fi 2University of Helsinki, Department of Environmental Sciences, Finland email: firstname.surname@helsinki.fi 3Government Institute for Economic Research, Helsinki, Finland email: firstname.surname@vatt.fi 4Sito Group, Espoo, Finland email: firstname.surname@sito.fi ABSTRACT – Urban planners work in the midst of many requirements and expectations, compounded in the need to promote sustainable environment. The process of planning is often hectic, while the planner lacks tools to assess sustainability of different planning options. To enable this assessment sustainability criteria and indicators were developed in an inter-disciplinary research project. Sustainability criteria comprise ecological, social, and economic criteria. The three sets of criteria together include 85 indicators. The criteria were designed for strategic decision making, impact assessment, and monitoring in medium sized urban regions in Finland. The indicators have been tested in two urban regions, Lahti and Oulu. 1. Introduction and Background Urban planning entails complex compromising between different expectations and challenges. These include the laws and strategies, which guide and control the planning, the objectives set at different jurisdictional levels, the requirements of different stakeholders and special challenges related e.g. to urban sprawl, ageing population, and climate change. The need for sustainable communities and sustainable development in general has been an important issue in academic forums and environmental policies for long. According to the Finnish national strategy on sustainable development (Finnish National Commission on Sustainable Development, 2006) sustainable communities mean balanced regional structure, dynamic development rising from individual strengths, functionally diverse and structurally coherent communities and good living environment, availability of public services, functional transport system and prevention of social exclusion. Strategies and plans of actions have been made to enhance sustainable development in numerous municipalities, companies and associations. A special challenge, however, is to connect sustainable development to regional level planning and find regional level solutions for the promotion of sustainability. Planning problems demanding regional 31 examination concern e.g. dispersal of urban structure, growing amount of transport, car dependence, fragmentation of green areas, and competition for tax payers between municipalities. To enable this assessment sustainability criteria and indicators were developed in an inter-disciplinary research project called "Sustainable urban land use and transport" (Seutukeke), running from 2008 to 2011. In this project all three pillars of sustainability – ecological, social, and economic – were examined in functional urban regions, each containing various municipalities. Sustainability in urban regions implies that growth and development will not endanger even in a long run biodiversity and ecosystem services (ecological dimension), well-being of people and social justice (social dimension), and economic progress (economic dimension). The criteria were designed to be used for setting of objectives, impact assessment, and monitoring of land use and transport planning in medium sized urban regions of about 80 000 - 200 000 inhabitants in Finland. In addition, the indicators can also be used in strategic level planning and decision making. Another target of the project was to enhance the use of data and analysis methods in planning. A lot of different datasets, registers and systems with readily usable analysis methods exist in public state and municipal sources, but little is used because of ignorance, lack of skills, or lack of time. In this project criteria and indicators were developed according to the best available scientific knowledge connected to easily available data and methods to enable planning departments in urban regions to carry out the analyses and calculate the indicators by themselves. Because of the regional perspective spatial GIS data was used as much as possible to overcome the problem of administrative borders. Examined phenomena are seldom restricted to administrative borders but form different kind of functional areas. In addition, functional areas are of different shape and size for different phenomena. In order to compare different urban regions to each other, the urban region in the Seutukeke project was formed using a uniform method, according to which it consists of a functional urban region (densely populated areas belonging to one commuting area) (Ristimäki et al., 2003) and surrounding 10 and 15 km distance zones. These buffer zones were selected on the basis of the distance from which urban dwellers in Finland mainly consume cultural ecosystem services in a form of outdoor recreation (Pouta and Heikkilä, 1998). 2. Material and Methods The work for developing sustainability criteria and indicators for urban regions was started with putting up an interdisciplinary research team of several research institutes. Leader of the project is the Finnish Environment Institute which mainly contributed to the ecological criteria and indicators together with the University of Helsinki/Department of Environmental Sciences, Sito Group, and VTT Technical Research Centre of Finland. Economic criteria and indicators were developed by Government Institute for Economic Research and social criteria and indicators by Sito Group and National Institute for Health and Welfare. Planning for the criteria was initiated in big workshops where all researchers co-operated to find a common understanding on the targets and working methods of the project and after that to adjust the different dimensions of sustainability together to form a concise and unified set of criteria and indicators. The research group consulted also other researchers and experts when needed to find the best scientific knowledge for the research. The consulted experts include e.g. landscape planners, ground and surface water researchers, transport experts, and GIS experts. The project outline and later a draft 32 set of criteria and indicators were presented to stakeholders in seminars. The feedback received in these was taken into account in further work. At the beginning of the actual research work the most important criteria for each dimension of sustainability were formulated. The criteria are expressed as statements describing a desirable state of affairs. The more general main criteria were further split into sub-criteria expressing more detailed statements. Finally, exact indicators describing the criteria and sub-criteria were developed. The development work was based on literature reviews to find out what kind of sustainability indicators have already been recommended for different levels of administration and what is seen important in scientific literature. The most promising indicators were collected or new ones developed and their suitability for urban regions was examined. Suitable ones were thereafter further studied on the basis of available data. Even very descriptive and good indicators had to be rejected if no data was available or if the data was very difficult to obtain. During the course of the research work about 200 suitable indicators were collected but about half of them were later rejected or set aside for the time being because of the previously mentioned reasons. As a result a set of 15 main criteria, 44 second order criteria, and 85 indicators was formed. Because the different dimensions of sustainability are often linked there appeared to be a need to include same kind of indicators in two or even in all three sets – economic, social, and ecological. The preliminary set of criteria was screened so as to remove duplicate indicators, whereas indicators representing more than one dimension of sustainability were marked. About half of the indicators appeared to represent more than one dimension, e.g. describe both social and economic sustainability. Indicators were also marked according to representing climate change or urban structure related issues. 3. Results Ecological sustainability Ecological sustainability has been described and defined in many different ways nationally and internationally (e.g. Ministry of the Environment, 1999, Secretariat of the Convention on Biological Diversity, 2000, Euroopan unionin neuvosto, 2006, Commission of the European communities, 2009, Finnish National Commission on Sustainable Development, 2006) but all definitions of the concept emphasize the capability of ecosystems of (a) maintaining central functions and processes and (b) conserving biological diversity in all its forms to present and future generations. The concept is often connected also to sustainable use of natural resources and diminishing the carbon footprint of humankind. The Seutukeke perspective on ecological sustainability is strongly linked to land use of urban regions. Such growth and development of an urban region, which does not endanger biological diversity and ecosystem services even in the long run, can be regarded as sustainable. Sustainability is addressed at the scale of an ecologically functional urban region, which is not limited inside the boundaries of densely populated urban areas, but consists of a continuum of different areas and functions at wider urban region. Discussion on dispersing community structure and consolidation as its counterforce, and climate change mitigation and adaptation, are topical perspectives related to ecologically sustainable land-use. 33 These interlinked themes strongly affect land-use planning and at the same time land-use decisions have an impact on climate change, although it is more widely also linked to other areas in the society. In the Seutukeke project, different dimensions of ecological sustainability related to land-use are being concretized with the ecosystem service approach. Ecosystem services (benefits humans get from nature) have become a significant topic of discussion and application beside traditional nature conservation (Millenium Ecosystem Assessment, 2005, Hiedanpää et al., 2010b, Kniivilä et al., 2011), because such a fresh approach is for instance in Finland seen better in enabling a discussion between nature conservation and use and management of natural resources (Hiedanpää et al., 2010a). Ecosystem services are usually classified in provisioning, regulating, supporting, and cultural services. In the Seutukeke project, regulating and supporting services are emphasized, because they represent the central mechanisms and processes for ecosystems to function (Kolström, 2010). An example of such regulating services is storm water absorption (and via it flood peaks moderation), which is enabled by vegetation, pervious surface, and soil (Niemelä et al., 2010). Moreover, cultural ecosystem services, especially recreational services providing possibilities for outdoor recreation and nature experiences, are significant in urban regions. Cultural services are produced by natural environments with varying modification levels, built urban parks and rural areas surrounding cities (Niemelä et al., 2010). Livelihood in cities is not often directly dependent on ecosystem services as in rural agricultural and forestry areas, but they significantly affect the living of urban inhabitants and the function of a city as a physical body of biotic and abiotic environmental factors. Land-use changes in urban regions can deteriorate ecosystem services by worsening their quality or endangering their very existence in certain areas. This may have an impact on how urban nature can resist or mitigate adverse phenomena, such as heat waves, floods and pollution (Colding, 2011). Thus it is essential to preserve enough different kinds of nature areas in urban regions and cities in order to maintain ecosystem services. In today’s urban planning and research related to it, the concept Green Infrastructure has been considered as one way to preserve green areas and ecosystem services. Although most of the Seutukeke ecological criteria and indicators describe ecosystem services directly or indirectly, some also refer to other aspects of ecological sustainability. A number of indicators represent urban structure which is connected e.g. to the use of natural resources and energy for building, infrastructure, and transport, emissions of air pollutants and carbon dioxide and, by implication, impact on climate change, and loss of peri-urban productive land. Also the load caused by human activities in urban region to e.g. surface and groundwater is examined through parameters indicating the quality of water and risk assessment of groundwater areas. Ecological criteria and indicators 1. Land use: Land use of the urban region supports maintenance of biodiversity and safeguarding of ecosystem services • Community structure is consolidated (proportion of dwellings built outside local master plan areas, proportion of apartments, jobs and large shopping units located in different urban zones, proportion of inhabitants living in densely and sparsely built areas, proportion of families with two or no cars, commuting travels and commuted distances per 34 day, proportion of people living in peri-urban villages of all inhabitants living in sparsely populated area) • Important nature areas are safeguarded (proportion of protected areas of all green areas) • There are noiseless and silent areas in the urban region (proportion of noiseless and silent areas of the whole land area) • There are carbon sinks in the urban region (total area and proportion of forests and mires in the urban region) • Culturally valuable areas are preserved (culturally valuable sites identified on all plan levels) 2. Green infrastructure: The urban region hosts large and ecologically functional contiguous nature areas and ecological connections • There are large and contiguous forest areas in the urban region (proportion of large and contiguous forest areas of total land area) • There are core nature areas in the urban region (proportion of core nature areas of all forest areas) • There are functional ecological connections in the urban region (proportion of core nature areas having several ecological connections with other core nature areas) • There is as little fragmentation as possible (proportion of forest edge zones of the whole forest area and proportion of forest areas larger than 5 hectares of all green and forested areas inside the densely populated area) 3. Recreation: All inhabitants have a possibility for recreation in nature • Recreational green areas are preserved (proportion of areas suitable for recreation) • Recreational green areas are close-to-home (proportion of inhabitants living max. 300 m distance from area suitable for recreation) • Shores are accessible for recreation (proportion of free shore line) • Recreation does not threaten conservation of biodiversity (proportion of inhabitants to areas suitable for recreation) 4. Water: Functional water cycle enables use of water and good living environment • Surface waters produce ecosystem services (water visibility, amount of chlorophyll a, and microbiological quality) • Clean ground waters are not threatened (proportion of groundwater areas under risk) • Land use supports water cycle and carbon sequestration (proportion of impervious land area in ground water areas) 5. Transport: Transport system does not endanger biodiversity • Traffic amounts do not threaten biodiversity (traffic amounts in proportion to inhabitants) • Traffic network does not prevent animal movements or cause fragmentation (road density, area of roads in proportion to inhabitants) 35 Social sustainability Social sustainability is an integral part of sustainable development. According to Kautto and Metso (Kautto and Metso, 2008) sustainability considers over generational effects and coherence of politics. There is no universal definition of social sustainability. Several definitions of social sustainability include justice and equality, possibility to affect one’s life, and strengthening communal identity. The national sustainability strategy of Finland determines social sustainability goals (Ministry of the Environment, 2009). These include 1) cohesion between different generations, 2) functionally diverse and structurally sound communities, 3) a good living environment promoting healthy lifestyles, functional capacity, and preventing health threats, 4) preventing social exclusion and poverty, 5) quality of working life, 6) ensuring the availability of services, 7) citizen’s satisfaction of service quality, and 8) promoting civil activity. Finland’s National Land Use Guidelines also require the safeguarding of peoples’ well-being and the promotion of social justice (Ministry of the Environment, 2002). Often, the social sustainability in urban planning is taken into account by providing participation in planning. This does not, however, systematically take into account all required social sustainability that can be done with social criteria and indicators (Juslén, 1995 cited in STAKES, 2006). There is a need to recognize the effects of transportation and land-use plans on different groups on a regional and local scale. The Seutukeke social criteria and indicators have been drafted by taking into account the top-down approach of the EU and national context of social sustainability as well as bottom-up approach of individual needs. An important factor has been to consider the basic needs of individuals as defined by Maslow (Maslow, 1973) and Allardt (Allardt, 1973). The provision of basic needs better necessitates the fulfilment of higher level needs. Culture, which is often seen as the fourth element of sustainability, is taken into account in the Seutukeke definition of social sustainability. The spatial scope of criteria chosen is based on the everyday actions of individuals within the region. Land-use and transport affect the everyday life and possibilities of individuals, which in turn affect how individuals can fulfil their needs. The emphasis of social equality and justice sets some guidelines on forming the criteria. Firstly, it requires considering average indicators that measure the general well-being of the public as well as the differences between different genders, generations, residences, or socioeconomic groups. Secondly, the goals of social sustainability have to be constantly reconfigured. Indicators do not have a certain fixed threshold and must be adjusted to local conditions and aims. Indicators vary subjectively through time between individuals and different demographic and sociocultural groups. Thirdly, social indicators vary spatially significantly. I.e. the same level of services cannot be guaranteed equally throughout the region to all individuals. Services conglomerate naturally which leads to emphasising the accessibility of services to different groups. It is challenging to determine social indicators at a regional scale. Most social sustainability measures are drafted at a national scale through strategies and policies. Local planning (including master plans and local plans) has a greater effect on social sustainability than regional plans. Land use policy has mostly indirect effect on social sustainability through the changes in land-use. A significant part of social sustainability, along with land-use planning, is affected through the policies of other municipal institutions, such as health services. 36 The chosen indicators aim to consider differences between different demographic and socioeconomic groups, take into consideration national strategy and individual needs, as well as work through space and time. Also other criteria and indicators were considered but discarded due to lack of data. Social impacts constitute parts of a larger entity and should not be studied detached from other environmental impacts (Välimäki and Kauppinen, 2000). When dealing with social data, individual privacy must be considered. Because of this some of the indicators were generalized to a municipality scale although they could also be calculated to a grid of adequate square size to generalize individual data. Social criteria and indicators 1. The region has a diverse and vibrant social community • Age structure is balanced (age groups by municipality) • Socioeconomic structure is balanced (long-time low income, linguistic division) • Culture and sports facilities are accessible (built culture and sports facilities, culture and sports facilities in public transport zones) • 2. Citizens are active (voting turnout, civic organisations) The region has diverse employment and education opportunities • Diverse and sufficient provision of employment (unemployment by municipality, income groups by municipality) • Workplaces are accessible (commuting distance) • Diverse and sufficient provision of education (proportion of vocational graduates, enrolments, enrolments by sector) 3. The environment is healthy and safe • Harmful effects of land-use are allocated fairly (facilities causing disturbance) • The environment does not harm health (citizens affected by noise pollution, air-quality, transport emissions) • 4. The environment is safe (injuries caused by traffic accidents, violent and property crimes) The region has a diverse residential supply • Sufficient occupancy rate (occupancy rate, overcrowding) • Residential supply is sufficient and diverse (residential zoning types, home ownership types) 5. Basic services are accessible for all • 6. Daily local services are accessible (daily local services) Easily accessible public and pedestrian transport services are provided • Service quality of public transport encourages use (bus stops, train stops) 37 Economic sustainability The existence of cities is based on concentration and agglomeration advantages. This means that the proximity of various producers and consumers creates common advantages in comparison to a dispersed settlement pattern. The advantages can be born at the input side, in the form of shared cost of common facilities (e.g. harbour), as well as at the output side in the form of scale effects in markets (more nearby clients, and less search cost for clients). For business it is also advantageous to have sufficient choice in labour supply (diversity, no scarcity) and vice versa for workers it is advantageous to have more choice in jobs and careers. In turn a large employment base means also a concentration of purchasing power, which attracts an expanding scope of consumer oriented services (retail, education, entertainment, etc.). With all these factors present a more dynamic set of agglomeration advantages emerges, which can lead to further accumulation of population and economic activity. As a consequence at least in some parts of the urban area the productivity per acre gets so high that it also significantly pushes up land prices and hence real estate prices. Consequently, a process of selective expulsion (from economic core areas) starts up. In turn this implies that, in absence of further measures, the city starts to expand over an ever larger area and to show more spatial segregation in functions. Both expansion and segregation stimulate transport demand, while motorised private road transport gains market share over non-motorised modes and public transport. Depending on landscape, climate, hydrology, economic structure, and urban form all kinds of environmental external effects may occur in such an expanding city, e.g. pollution of the air, soils, and water, as well as noise and degradation of natural habitats. There is an ongoing discourse in spatial economics about what constitutes optimal city size (e.g. Arnott, 2004, Capello, 2000, Kanemoto et al., 1996). The number of theoretical and conceptual contributions is much larger than actual applications to cities (Kanemoto et al., 1996, is a rare example). Furthermore, for a long living system such as a city static optimality is of little value, instead the best possible resilient pathway over time is more important. Next to existing economic and geographic models there are also approaches based on physical concepts such as material flow analysis (MFA), in which the city is described as a metabolic system (Moll et al., 2005), and entropy models of urban systems (Zhang et al., 2006). These studies indicate that a fully fledged treatment of sustainability will probably change the assessment and judgement for many cities, but they stop short of providing an alternative assessment system. Furthermore, these studies often focus on one particular aspect, e.g. transport. Since spatial dynamics embodies very complicated processes neither consumers nor producers can fully grasp the longer term consequences of their location choices. When cities start to attain larger sizes and external effects start to become noticeable, a spatial development which is mostly based on individual private decisions (and interests) has a very high risk to acquire ever more features that weaken the social and environmental realm of sustainability. In turn the degradation of these realms eventually undermines the economic sustainability, either because problems arise at the input side (lack of natural resources, extra cleaning cost, lack of skilled labour) or at the output side (new emerging sectors choose other cities, skilled workers migrate to better paying regions). In other words the maintenance of agglomeration effects requires also sufficient sustainability in the social and environmental realm. 38 All in all sustainable urban economics, which also accounts for the interaction with the social and environmental realm, would imply in this context that a city or city region succeeds in • keeping up already strong sectors for considerable time by facilitating cost efficiency and innovativeness, but prevent that the city’s resources get wound up in once strong activities with structurally low productivity, • fostering new sectors with substantial growth potential so as to promote diversification, to facilitate cross-fertilisation in innovations, and to prepare for shifts out of declining sectors, • devising funding structures for adequate public services and infrastructures that sustain the changes in economic, demographic and spatial structure, and suffice to create attractive, healthy, and safe living and working environments with minimal environmental footprints. Economic criteria and indicators The proposed set is preliminary, limited by data availability and lack of use experience. In a learning-bydoing-process, including generation of new data, the set will evolve over time. The indicator sets are subdivided in four sections, which typically represent the key dimensions that drive economic sustainability. The first two dimensions, productivity and regeneration, deal with economic core elements. The next two dimensions, public infrastructure and environmental effects deal with important facilitating and conditioning elements for promoting economic prosperity and overall sustainability. 1. The economic life and the development of it´s sectors is productive and profitable • Economic growth supports sustainable development (region’s GDP development, degree of concentration in few sectors) • Supply of employment is diverse (employment by sector, employment by sector by municipality) • Purchasing power grows in all sectors (purchasing power of households, purchasing power of households per municipality) • Housing market is in balance (housing prices and rents per m2, share of rental apartments of all apartments, available rental apartments) • Municipal tax rates and indebtedness of the urban region is moderate (region’s municipal tax rates for income and real estate tax, municipal indebtedness and it´s growth) 2. Economic life of the urban region is capable of regeneration • Development of labour meets the demand (municipal self-sufficiency rate of employment, labour population by age category, rate of unemployed and people outside labour to employed in municipalities) • Labour is mobile and enterprise structure is dynamic (job vacancies, new company establishments and company closures) • Productive capacity of the urban region regenerates (private investment’s share in GDP, region’s research and development effort) 3. Infrastructure and other public services in the urban region are adequate and working 39 • Public transport is efficient (supply (frequency) of public transport connections, public subsidy of public transport/trip) 4. Environmental impacts of economy are as small as possible • Energy efficiency of the urban region is getting better (energy consumption in public buildings, region’s electricity consumption per capita) • Climate impacts of the urban regions and environmental load of industries are small or getting smaller (region’s greenhouse gas emissions, region’s production of renewable energy, industrial energy consumption) • Basic material flows are ecologically sustainable (recycling rate of municipal waste, landfill waste) Pilots Two urban regions, Lahti in southern Finland and Oulu in northern Finland were involved in the development of the sustainability criteria and indicators. All indicators were tested in these two pilot regions which differ remarkably from each other both physically and functionally. The results were presented to urban planners and decision-makers and discussed with them. Local knowledge was valuable in the development work for assessing the validity and usability of analyses and results. All results will be presented in the forthcoming final report of the project with map representations together with tables and graphs. 4. Discussion and Conclusions The criteria and indicators developed in the Seutukeke project describe sustainability and sustainable communities from different angles. They can be used at different phases of land use planning ranging from objective setting to impact assessment and further to monitoring. The large amount of indicators does not mean that all of them should be applied in every planning case. Instead of that, a suitable set of indicators can be selected and further analyzed, or the whole set of indicators can be used as a check list in impact assessment scoping phase. However, there are certain challenges related to the use of indicators: adequate and valid data, proper scale of an analysis and suitable and right use of results as a part of the planning case. These challenges, as well as further development of criteria and indicators, are in the core of our future research activities. Some of the criteria and indicators have been used in a real world planning case in the city of Lahti in early 2011 and an assessment of Päijät-Häme regional plan and strategy with Seutukeke indicators is also under preparation. In the future the development of indicators is heavily dependent on planners' experiences. The criteria and indicators will be published in Finnish as a final report in late 2011. The report can be used as a guidance book in concrete land use and transport planning. Detailed information on GIS analysis and ecological criteria will be presented in separate special guidance reports. 40 References ALLARDT, E. (1973) About Dimensions of Welfare, An Exploratory Analysis of a Comparative Scandinavian Survey, Helsinki. ARNOTT, R. (2004) Does the Henry George Theorem provide a practical guide to optimal city size? The American Journal of Economics and Sociology, 63, 1057-1090. CAPELLO, R. (2000) Beyond Optimal City Size: An Evaluation of Alternative Urban Growth Patterns. Urban Studies, 37, 1479-1496. COLDING, J. (2011) The Role of Ecosystem Services in Contemporary Urban Planning. IN NIEMELÄ, J. (Ed.) Urban ecology - patterns, processes, and applications. Oxford University Press. COMMISSION OF THE EUROPEAN COMMUNITIES (2009) Mainstreaming sustainable development into EU policies: 2009 Review of the European Union Strategy for Sustainable Development, Brussels, Commission of the European communities. EUROOPAN UNIONIN NEUVOSTO (2006) EU:n uudistettu kestävän kehityksen strategia, Bryssel, Euroopan unionin neuvosto. FINNISH NATIONAL COMMISSION ON SUSTAINABLE DEVELOPMENT (2006) Kohti kestäviä valintoja. Kansallisesti ja globaalisti kestävä Suomi. Kansallinen kestävän kehityksen strategia, Helsinki, Valtioneuvoston kanslia. HIEDANPÄÄ, J., SUVANTOLA, L. & NASKALI, A. (2010a) Ekosysteemipalvelun käsitteen lupaus. IN HIEDANPÄÄ, J., SUVANTOLA, L. & NASKALI, A. (Eds.) Hyödyllinen luonto ekosysteemipalvelut hyvinvointimme perustana. Tampere, Vastapaino. HIEDANPÄÄ, J., SUVANTOLA, L. & NASKALI, A. (Eds.) (2010b) Hyödyllinen luonto ekosysteemipalvelut hyvinvointimme perustana, Tampere, Vastapaino. KANEMOTO, Y., OHKAWARA, T. & SUZUKI, T. (1996) Agglomeration Economies and a Test for Optimal City Sizes in Japan. Journal of the Japanese and International Economies, 10, 379-398. KAUTTO, M. & METSO, L. (2008) Yhteiskuntapolitiikka, 73, 411-420. Sosiaalinen kestävyys - uusi poliittinen horisontti? KNIIVILÄ, M., HORNE, P., HYTÖNEN, M., JÄPPINEN, J.-P., NASKALI, A., PRIMMER, E. & RINNE, J. (2011) Monia hyötyjä metsistä - ekosysteemipalveluiden yhteistuotanto ja tuotteistaminen, Helsinki, Pellervon taloustutkimus. KOLSTRÖM, T. (2010) Mitä ekosysteemipalvelut ovat? IN HIEDANPÄÄ, J., SUVANTOLA, L. & NASKALI, A. (Eds.) Hyödyllinen luonto - ekosysteemipalvelut hyvinvointimme perustana. Tampere, Vastapaino. MASLOW (1973) A theory of human motivation. Psychological Review, 50, 370-396. MILLENIUM ECOSYSTEM ASSESSMENT (2005) Ecosystems and Human Well-Being: Biodiversity Synthesis, Washington, DC, World Resources Institute. MINISTRY OF THE ENVIRONMENT (1999) Maankäyttö- ja rakennuslaki, Helsinki, Edita. MINISTRY OF THE ENVIRONMENT (2002) Finland’s National Land Use Guidelines, Helsinki, Ministry of the Environment, Land Use Department. MINISTRY OF THE ENVIRONMENT (2009) National assessment of sustainable development, Helsinki, Ministry of the Environment, Department of Environmental Protection. MOLL, H., NOORMAN, K. J., KOK, R., ENGSTRÖM, R., THRONE-HOLST, H. & CLARK, C. (2005) Pursuing more sustainable consumption patterns by analysing household metabolism in European countries and cities. Journal of Industrial Ecology, 9, 259-275. NIEMELÄ, J., SAARELA, S.-R., SÖDERMAN, T., KOPPEROINEN, L., YLI-PELKONEN, V. & VÄRE, S. (2010) Kaupunkiluonnon ekosysteemipalvelut. IN HIEDANPÄÄ, J., NASKALI, A. & SUVANTOLA, L. (Eds.) Hyödyllinen luonto - Ekosysteemipalvelut hyvinvointimme perustana. Tampere, Vastapaino. POUTA, E. & HEIKKILÄ, M. (Eds.) (1998) Virkistysalueiden suunnittelu ja hoito, Helsinki, Ministry of the Environment. RISTIMÄKI, M., OINONEN, K., PITKÄRANTA, H. & HARJU, K. (2003) Kaupunkiseutujen väestönmuutos ja alueellinen kasvu, Helsinki, Ministry of the Environment. 41 SECRETARIAT OF THE CONVENTION ON BIOLOGICAL DIVERSITY (2000) Sustaining life on Earth. How the Convention on Biological Diversity promotes nature and human well-being, Montreal, Secretariat of the Convention on Biological Diversity. STAKES (2006) Social Impact Assessment: A Look Into Finnish Experiences, Helsinki, National Research & Development Centre for Welfare and Health, STAKES. VÄLIMÄKI, J. & KAUPPINEN, T. (2000) Ympäristövaikutukset arvioidaan - missä on ihminen? (Assessing Environmental Impacts - What about People?), Helsinki, STAKES. ZHANG, Y., YANG, Z. & LI, W. (2006) Analyses of urban ecosystem based on information entropy. Ecological Modelling, 1-12. 42 BIOREFINERY IMPLEMENTATION IN MARGINAL LANDA FOCUS ON THE MULTIFUNCTIONAL USE OF REGIONAL AGRICULTURE. Sandra Fahd, Gabriella Fiorentino1, Salvatore Mellino, Maddalena Ripa and Sergio Ulgiati Department of Sciences for the Environment, Parthenope University of Naples, Italy ABSTRACT − In times of depletion of fossil resources and increasing environmental concerns, more focus needs to be placed on energy and materials co-production patterns. The search for new sources of energy is often leading to intensified use of available land for energy cropping in competition with food production, although recent studies show that land conversion from forest, savannah and grassland into biofuels crops causes significant increases of CO2 emissions. Within the EU funded SMILE project, an alternative design for marginal land use in central-southern Italy was hypothesized by assuming marginal lands to be cropped with Brassica carinata, a non-food crop, for biodiesel production from seeds and, at the same time, biochemicals extraction from residues. The actual potential of the biorefinery concept applied to marginal or abandoned lands was deeply investigated. The effectiveness of an expanded LCA approach, named SUMMA (SUstainability Multimethod Multiscale Assessment), based on the consistent application of different assessment methods to the input and output inventory of local processes, was tested by means of the comparison of two different scenarios (bioenergy approach versus biorefinery approach). A further integration within the SUMMA method consisted in a specific spatial parameterisation by means of Geographic Information System (GIS) procedures. Results achieved show that the energy and environmental performance of biodiesel and heat generation from Brassica residues is unlikely to be profitable and desirable at the level of Campania regional agriculture, due to the fact that the economic cost of the whole process largely exceeds the value of the saved fossil fuels. If straw and oilseed cake meals are accounted for, in addition to the biodiesel production, the performance results to be higher from an energetic point of view, but the process is still not fully satisfactory in economic and environmental terms. Instead, if agricultural residues are exploited for the extraction of chemical building blocks, through the so-called Biofine process or other biorefinery patterns, the performance is improved, thanks to the high added value of generated biochemicals. 1 Corresponding Author. Email: gabriella.fiorentino@uniparthenope.it. 43 1. Introduction and Background The development of large scale industrial production systems based on renewable resources, rather than non-renewable ones, is a crucial item on the international agenda, in times of increasing depletion of fossil reservoirs. In such a framework, biomass and, in particular, plant-based raw materials are of great interest from both economic and ecological standpoints as alternative feedstocks for industrial production, addressing both the energy and non-energy sectors including chemicals and materials (EC, 2004). The search for new sources of energy and materials gave rise to an intensified exploitation of available land for energy cropping: energy cropping is however constrained by the large amount of soil required for the production of raw materials. Soil use as well as other related environmental resources (water, topsoil, biodiversity etc.) aff...
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Introduction



 Sustainable development is a
situation whereby development
is done without the depletion of
natural resources. For example,
making products that are
environmentally friendly while
making profits at the same time,
and improving the quality of life
of the individuals involved.
Thereby, the environment is
preserved, and the economy is
strengthened at the same time.
None comes at the cost of
another.

Economic Aspect

 Agriculture is a large
industry sector providing
for the livelihood of many
people in the world.
 Certain countries like
Myanmar mainly depend
on agriculture for survival,
as
do
many
other
developing countries.
 Most people in the rural
area primarily depend on
agriculture for survival,
seeing as many industrial
developments are done in
urban areas.

Continuation…

 Due to the high dependence
in agriculture for low and
middle-income
countries,
there is a need for the
government to increase
investment in this sector.
 If the government pours
more resources to the
agricultural
sector,
production will increase,
employment opportunities
will go up, farmers will
generate more income, and
the economy of the country
as a whole will get
strengthened.

Continuation…

 Pests are a menace in the
agricultural sector. ...


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