Mixed norm spaces and rearrangement invariant estimates

Our main goal in this work is to further improve the mixed norm estimates due to Fournier, and also Algervik and Kolyada, to more general rearrangement invariant (r.i.) spaces. In particular we find the optimal domains and the optimal ranges for these embeddings between mixed norm spaces and r.i. spaces

Estudio del empleo de la variedad Sikitita como patrón enanizante en una plantación superintensiva de manzanilla de Sevilla

En el mundo se estima que hay más de 1.000 millones de olivos, siendo España el primer productor con 5,3 millones de toneladas. De esta producción el 5,81% se destina para el aderezo de aceituna, concentrando esta producción mayoritariamente en la comunidad autónoma de Andalucía con el 76% de la producción, y más concretamente en la provincia de Sevilla con el 55%. Estas producciones van en aumento, pues desde la década de los 90, innovaciones como eficacia de los riegos, mejora en la elección de variedades, incremento de la densidad de plantación con la consiguiente intensificación del cultivo y la mecanización de las labores, principalmente de la recolección, han favorecido las plantaciones de olivar en detrimento de otros cultivos. El olivar de verdeo, en la retaguardia de los avances en el cultivo, no ha experimentado grandes mejoras, pues las principales variedades son muy vigorosas, encontrando dificultades técnicas para intensificar el cultivo, como es el caso de ‘Manzanilla de Sevilla’. Sin embargo, investigaciones recientes apuntan a que sería posible una recolección con cabalgadora sin mermas significativas de calidad. Mediante mejora genética se obtuvo ‘Shikitita’, considerada una variedad enana y comercializada para plantaciones en superintensivas de aceite. Este proyecto pretende estudiar la viabilidad de la utilización de ‘Shikitita’ como patrón de ‘Manzanilla de Sevilla’ para plantaciones de alta densidad. Se ha realizado un ensayo en la finca experimental “La Hampa” en Coria del Río (Sevilla), propiedad del Consejo Superior de Investigaciones Científicas (CSIC). Se trata de una parcela de olivar de 4 años de edad con un marco de 4*1,75 m de la variedad Manzanilla de Sevilla en condiciones de regadío con 4 goteros por árbol de 8 L/hora, en el que se ha estudiado por segundo año consecutivo el efecto que ‘Shikitita’ como patrón por su posible efecto enanizante. El diseño experimental ha sido en bloques al azar con 7 repeticiones por tratamiento, formándose los bloques por una única fila con tres árboles por tratamiento, siendo el árbol central el utilizado como árbol control. Los árboles injertados se obtuvieron en el año 2011 en las instalaciones del IFAPA de “Alameda del Obispo” (Córdoba), mientras que los árboles francos se propagaron en 2012. La plantación se realizó en mayo de 2013. La programación del riego se realiza en función de valores de potencial hídrico de tallo para asegurar un estado hídrico óptimo en la etapa vegetativa y una restricción del riego durante el endurecimiento de hueso, con posterior rehidratación antes de cosecha. La evaluación del efecto del patrón se ha realizado estudiando los haces vasculares y tomando medidas de crecimiento vegetativo, desarrollo fenológico, relaciones hídricas del cultivo, datos de cosecha. El crecimiento no experimentó mermas significativas en la longitud de ramos ni en la tasa de crecimiento empleando ‘Shikitita’ como patrón, reduciéndose simplemente el 6 – 7% la elongación de los entrenudos. El diámetro del tronco a 35 cm del suelo resultó ser un 12% inferior en el tratamiento ‘Manzanilla de Sevilla’/Shikitita con respecto al tratamiento franco. La producción y calidad de la cosecha no presentaron diferencias significativas para ambos tratamientos, aunque los árboles de Shikitita presentaron una tendencia a mayor cosecha (un 10% más aproximadamente) y menor tamaño de fruto (un 10% menos aproximadamente). Este trabajo describe la primera cosecha realmente comercial de la plantación estando sus características a niveles similares a las descritas en la bibliografía para plantaciones tradicionales. ‘Shikitita’ presenta indicios en algunos parámetros de posible efecto enanizante sobre ‘Manzanilla de Sevilla’ aunque no presenta diferencias estadísticamente significativas generalizadas. Por lo que no se puede decir que se comporte como patrón enanizante de la variedad Manzanilla de Sevilla. Sería necesario seguir estudiando la evolución de la plantación en los próximos años para poder evaluar el efecto de ‘Shikitita’ como posible patrón enanizante de ‘Manzanilla de Sevilla’.Universidad de Sevilla. Máster en Ingeniería Agronómicx

Ionic liquids at the air/water interface

We present molecular dynamics experiments of Langmuir monolayers of iodide and chloride salts of 1-octyl-3-methylimidazolium adsorbed at water/air interfaces, covering a concentration range that spans from a dilute regime up to the experimental surface saturation for both systems. For the chloride case we observed a propensity to form monolayers with nearly equal surface concentration of both cations and anions; whereas for the iodide system, the more marked propensity to surface solvation of the anionic species leads to the appearance of quasi-double-layered structures. At the surface, the imidazolium rings remain in contact with the aqueous substrate, with a wide variety of orientations with respect to the surface normal direction. Theglobal tilt of the hydrophobic tail of the cations was found to be θtl~40°and 50°, for the chloride and iodide salts, respectively. Polarization fluctuations of the interface are analyzed in terms of those describing charge distributions of the adsorbed species and the electrical response of the solvent as well. The characteristics of the local densities for the ionic species at the interface provide arguments for the microscopic interpretation of the differences observed in scattering experiments on the dependence of the surface tension with the surfactant concentration.Fil: Clavero, Esteban Dario. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes; ArgentinaFil: Rodriguez, Javier. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Comisión Nacional de Energía Atómica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Mathematical Modeling of the Biogas Production in MSW Landfills. Impact of the Implementation of Organic Matter and Food Waste Selective Collection Systems

[EN] Municipal solid waste (MSW) landfills are one of the main sources of greenhouse gas emissions. Biogas is formed under anaerobic conditions by decomposition of the organic matter present in waste. The estimation of biogas production, which depends fundamentally on the type of waste deposited in the landfill, is essential when designing the gas capture system and the possible generation of energy. BIOLEACH, a mathematical model for the real-time management of MSW landfills, enables the estimation of biogas generation based on the waste mix characteristics and the local meteorological conditions. This work studies the impact of installing selective organic matter collection systems on landfill biogas production. These systems reduce the content of food waste that will eventually be deposited in the landfill. Results obtained using BIOLEACH on a set of scenarios under real climate conditions in a real landfill located in the Region of Murcia (Spain) are shown. Results demonstrate that actual CH4 and CO2 production depends fundamentally on the monthly amount of waste stored in the landfill, its chemical composition and the availability and distribution of water inside the landfill mass.Rodrigo-Ilarri, J.; Rodrigo-Clavero, M. (2020). Mathematical Modeling of the Biogas Production in MSW Landfills. Impact of the Implementation of Organic Matter and Food Waste Selective Collection Systems. Atmosphere. 11(12):1-18. https://doi.org/10.3390/atmos11121306S1181112Calculation of CH4 and CO2 Emission Rate in Kahrizak Landfill Site THROUGH LandGEM Mathematical Model. In Proceedings of the 4th World Sustainability Forumhttps://sciforum.net/conference/wsf-4Krause, M. J., W. Chickering, G., Townsend, T. G., & Reinhart, D. R. (2016). Critical review of the methane generation potential of municipal solid waste. Critical Reviews in Environmental Science and Technology, 46(13), 1117-1182. doi:10.1080/10643389.2016.1204812Allen, M. R., Braithwaite, A., & Hills, C. C. (1997). Trace Organic Compounds in Landfill Gas at Seven U.K. Waste Disposal Sites. Environmental Science & Technology, 31(4), 1054-1061. doi:10.1021/es9605634Eklund, B., Anderson, E. P., Walker, B. L., & Burrows, D. B. (1998). Characterization of Landfill Gas Composition at the Fresh Kills Municipal Solid-Waste Landfill. Environmental Science & Technology, 32(15), 2233-2237. doi:10.1021/es980004sRey, M. D., Font, R., & Aracil, I. (2013). Biogas from MSW landfill: Composition and determination of chlorine content with the AOX (adsorbable organically bound halogens) technique. Energy, 63, 161-167. doi:10.1016/j.energy.2013.09.017Harborth, P., Fuß, R., Münnich, K., Flessa, H., & Fricke, K. (2013). Spatial variability of nitrous oxide and methane emissions from an MBT landfill in operation: Strong N2O hotspots at the working face. Waste Management, 33(10), 2099-2107. doi:10.1016/j.wasman.2013.01.028Brown, K. A., & Maunder, D. H. (1994). Exploitation of landfill gas: a UK perspective. Water Science and Technology, 30(12), 143-151. doi:10.2166/wst.1994.0599Abbasi, T., Tauseef, S. M., & Abbasi, S. A. (2012). Biogas Energy. doi:10.1007/978-1-4614-1040-9El-Fadel, M., Findikakis, A. N., & Leckie, J. O. (1997). Environmental Impacts of Solid Waste Landfilling. Journal of Environmental Management, 50(1), 1-25. doi:10.1006/jema.1995.0131Levis, J. W., & Barlaz, M. A. (2011). Is Biodegradability a Desirable Attribute for Discarded Solid Waste? Perspectives from a National Landfill Greenhouse Gas Inventory Model. Environmental Science & Technology, 45(13), 5470-5476. doi:10.1021/es200721sFarquhar, G. J., & Rovers, F. A. (1973). Gas production during refuse decomposition. Water, Air, & Soil Pollution, 2(4), 483-495. doi:10.1007/bf00585092Rees, J. F. (2007). Optimisation of methane production and refuse decomposition in landfills by temperature control. Journal of Chemical Technology and Biotechnology, 30(1), 458-465. doi:10.1002/jctb.503300158Kasali, G. B., Senior, E., & Watson-Craik, I. A. (1990). Solid-state refuse methanogenic fermentation: control and promotion by water addition. Letters in Applied Microbiology, 11(1), 22-26. doi:10.1111/j.1472-765x.1990.tb00127.xGurijala, K. R., & Suflita, J. M. (1993). Environmental factors influencing methanogenesis from refuse in landfill samples. Environmental Science & Technology, 27(6), 1176-1181. doi:10.1021/es00043a018Shariatmad, N., Sabour, M. R., Kamalan, H., Mansouri, A., & Abolfazlza, M. (2007). Applying Simple Numerical Model to Predict Methane Emission from Landfill. Journal of Applied Sciences, 7(11), 1511-1515. doi:10.3923/jas.2007.1511.1515Peer, R. L., Thorneloe, S. A., & Epperson, D. L. (1993). A comparison of methods for estimating global methane emissions from landfills. Chemosphere, 26(1-4), 387-400. doi:10.1016/0045-6535(93)90433-6Kamalan, H., Sabour, M., & Shariatmad, N. (2011). A Review on Available Landfill Gas Models. Journal of Environmental Science and Technology, 4(2), 79-92. doi:10.3923/jest.2011.79.92Majdinasab, A., Zhang, Z., & Yuan, Q. (2017). Modelling of landfill gas generation: a review. Reviews in Environmental Science and Bio/Technology, 16(2), 361-380. doi:10.1007/s11157-017-9425-2Buswell, A. M., & Mueller, H. F. (1952). Mechanism of Methane Fermentation. Industrial & Engineering Chemistry, 44(3), 550-552. doi:10.1021/ie50507a033Symons, G. E., & Buswell, A. M. (1933). The Methane Fermentation of Carbohydrates1,2. Journal of the American Chemical Society, 55(5), 2028-2036. doi:10.1021/ja01332a039Boyle, W. C. (1977). ENERGY RECOVERY FROM SANITARY LANDFILLS - A REVIEW. Microbial Energy Conversion, 119-138. doi:10.1016/b978-0-08-021791-8.50019-6GARCIADECORTAZAR, A., & MONZON, I. (2007). MODUELO 2: A new version of an integrated simulation model for municipal solid waste landfills. Environmental Modelling & Software, 22(1), 59-72. doi:10.1016/j.envsoft.2005.11.003White, J. K., & Beaven, R. P. (2013). Developments to a landfill processes model following its application to two landfill modelling challenges. Waste Management, 33(10), 1969-1981. doi:10.1016/j.wasman.2012.12.006McDougall, J. (2007). A hydro-bio-mechanical model for settlement and other behaviour in landfilled waste. Computers and Geotechnics, 34(4), 229-246. doi:10.1016/j.compgeo.2007.02.004Bareither, C. A., Benson, C. H., & Edil, T. B. (2013). Compression of Municipal Solid Waste in Bioreactor Landfills: Mechanical Creep and Biocompression. Journal of Geotechnical and Geoenvironmental Engineering, 139(7), 1007-1021. doi:10.1061/(asce)gt.1943-5606.0000835Lu, S.-F., Xiong, J.-H., Feng, S.-J., Chen, H.-X., Bai, Z.-B., Fu, W.-D., & Lü, F. (2019). A finite-volume numerical model for bio-hydro-mechanical behaviors of municipal solid waste in landfills. Computers and Geotechnics, 109, 204-219. doi:10.1016/j.compgeo.2019.01.012Liu, X., Shi, J., Qian, X., Hu, Y., & Peng, G. (2011). One-dimensional model for municipal solid waste (MSW) settlement considering coupled mechanical-hydraulic-gaseous effect and concise calculation. Waste Management, 31(12), 2473-2483. doi:10.1016/j.wasman.2011.07.013Hettiarachchi, H., Meegoda, J., & Hettiaratchi, P. (2009). Effects of gas and moisture on modeling of bioreactor landfill settlement. Waste Management, 29(3), 1018-1025. doi:10.1016/j.wasman.2008.08.018Chen, Y., Xu, X., & Zhan, L. (2011). Analysis of solid-liquid-gas interactions in landfilled municipal solid waste by a bio-hydro-mechanical coupled model. Science China Technological Sciences, 55(1), 81-89. doi:10.1007/s11431-011-4667-7Staub, M. J., Gourc, J.-P., Drut, N., Stoltz, G., & Mansour, A. A. (2013). Large-Scale Bioreactor Pilots for Monitoring the Long-Term Hydromechanics of MSW. Journal of Hazardous, Toxic, and Radioactive Waste, 17(4), 285-294. doi:10.1061/(asce)hz.2153-5515.0000160Machado, S. L., Vilar, O. M., & Carvalho, M. F. (2008). Constitutive model for long term municipal solid waste mechanical behavior. Computers and Geotechnics, 35(5), 775-790. doi:10.1016/j.compgeo.2007.11.008Hettiarachchi, C. H., Meegoda, J. N., Tavantzis, J., & Hettiaratchi, P. (2007). Numerical model to predict settlements coupled with landfill gas pressure in bioreactor landfills. Journal of Hazardous Materials, 139(3), 514-522. doi:10.1016/j.jhazmat.2006.02.067Sivakumar Babu, G. L., Reddy, K. R., Chouskey, S. K., & Kulkarni, H. S. (2010). Prediction of Long-Term Municipal Solid Waste Landfill Settlement Using Constitutive Model. Practice Periodical of Hazardous, Toxic, and Radioactive Waste Management, 14(2), 139-150. doi:10.1061/(asce)hz.1944-8376.0000024Hanson, J. L., Yeşiller, N., Onnen, M. T., Liu, W.-L., Oettle, N. K., & Marinos, J. A. (2013). Development of numerical model for predicting heat generation and temperatures in MSW landfills. Waste Management, 33(10), 1993-2000. doi:10.1016/j.wasman.2013.04.003Gawande, N. A., Reinhart, D. R., & Yeh, G.-T. (2010). Modeling microbiological and chemical processes in municipal solid waste bioreactor, part I: Development of a three-phase numerical model BIOKEMOD-3P. Waste Management, 30(2), 202-210. doi:10.1016/j.wasman.2009.09.009GHOLAMIFARD, S., EYMARD, R., & DUQUENNOI, C. (2008). Modeling anaerobic bioreactor landfills in methanogenic phase: Long term and short term behaviors. Water Research, 42(20), 5061-5071. doi:10.1016/j.watres.2008.09.040Garg, A., & Achari, G. (2010). A Comprehensive Numerical Model Simulating Gas, Heat, and Moisture Transport in Sanitary Landfills and Methane Oxidation in Final Covers. Environmental Modeling & Assessment, 15(5), 397-410. doi:10.1007/s10666-009-9217-3Feng, S.-J., Lu, S.-F., Chen, H. X., Fu, W.-D., & Lü, F. (2017). Three-dimensional modelling of coupled leachate and gas flow in bioreactor landfills. Computers and Geotechnics, 84, 138-151. doi:10.1016/j.compgeo.2016.11.024Grugnaletti, M., Pantini, S., Verginelli, I., & Lombardi, F. (2016). An easy-to-use tool for the evaluation of leachate production at landfill sites. Waste Management, 55, 204-219. doi:10.1016/j.wasman.2016.03.030Lei, L., Bing, L., Qiang, X., Ying, Z., & Chun, Y. (2011). The modelling of biochemical-thermal coupling effect on gas generation and transport in MSW landfill. International Journal of Environment and Pollution, 46(3/4), 216. doi:10.1504/ijep.2011.045480Zacharof, A. I., & Butler, A. P. (2004). Stochastic modelling of landfill leachate and biogas production incorporating waste heterogeneity. Model formulation and uncertainty analysis. Waste Management, 24(5), 453-462. doi:10.1016/j.wasman.2003.09.010Pommier, S., Chenu, D., Quintard, M., & Lefebvre, X. (2007). A logistic model for the prediction of the influence of water on the solid waste methanization in landfills. Biotechnology and Bioengineering, 97(3), 473-482. doi:10.1002/bit.21241Abdallah, M., Fernandes, L., Warith, M., & Rendra, S. (2009). A fuzzy logic model for biogas generation in bioreactor landfillsA paper submitted to the Journal of Environmental Engineering and Science. Canadian Journal of Civil Engineering, 36(4), 701-708. doi:10.1139/l09-015Rodrigo-Ilarri, J., Rodrigo-Clavero, M.-E., & Cassiraga, E. (2020). BIOLEACH: A New Decision Support Model for the Real-Time Management of Municipal Solid Waste Bioreactor Landfills. International Journal of Environmental Research and Public Health, 17(5), 1675. doi:10.3390/ijerph1705167

Control remoto del sistema B+G del Observatorio Astronómico del Montsec: monitorización de funciones.

En el año 2001 la Generalitat de Cataluña creó el Consorcio del Montsec para la ejecución del proyecto Montsec Sostenible. En el marco de este proyecto y mediante la colaboración de diversos departamentos de las Universidades públicas de Cataluña, entre las cuales se encuentran los departamentos de Física Aplicada (FA) y de Física e Ingeniería Nuclear (FEN), de la Universidad Politécnica de Cataluña (UPC), se creó el Parque Astronómico del Montsec (PAM). El Observatorio Astronómico del Montsec (OAM), situado en el municipio de Sant Esteve de la Sarga y a una altura de 1570 metros, en la divisoria del Montsec d'Ares, constituye el núcleo básico de la actividad investigadora y de la formación universitaria, tanto para estudiantes de física como de ingeniería. Dado el difícil acceso a las instalaciones del OAM se decidió automatizar la mayor parte de sus instalaciones (tanto científicas como de infraestructura general) para poder operar remotamente el telescopio y así realizar todas las observaciones astronómicas telemáticamente, reduciendo de esta manera los costes de operación y mantenimiento. En proyectos anteriores se plantearon las bases para poder monitorizar a distancia el grupo electrógeno que abastece de energía eléctrica al OAM. En el primer proyecto se diseñó el programa que trabaja directamente con la central de control del grupo electrógeno, el panel de control GC-M02. En el segundo proyecto se implementó un programa servidor-cliente que se encarga de la conexión a través de Internet para la monitorización de datos. En este proyecto se han solucionado problemas surgidos en los dos proyectos anteriores y se han integrado de manera que funcionen como un único software de control. Ahora es posible monitorizar el estado de los componentes del grupo electrógeno y saber si hay algún problema en el sistema sin necesidad de desplazarse hasta el OAM

Mobile services in the Rector Gabriel Ferraté Library - Technical University of Catalonia

Purpose – The purpose of this paper is to compile and explain the mobile services developed by the Rector Gabriel Ferraté Library (BRGF) of the Technical University of Catalonia (UPC), in Barcelona, Spain. From a larger amount of technological features that distinguish the BRGF, only those with a main mobile component are grouped here. Design/methodology/approach – A case study perspective is used to give a detailed picture of the mobile services and features offered by the library in both the university and the Spanish technological contexts. The paper aims to show the effectiveness and potential to deliver library services through the preferred tools of a new generation of students. Findings – Offering mobile services has amplified the use of the library in different ways and has improved the image of the library as a technological reference for users and librarians. From a general point of view, being ahead of the game has been revealed to be an appropriate strategy for the library when implementing new technological services. Originality/value – The paper will be useful for libraries searching new and innovative technological channels to communicate and deliver their services. So far, there have been very few papers about mobile services in European libraries and very few Spanish libraries with a significant number of these services for their users

Land Use/Land Cover Assessment over Time Using a New Weighted Environmental Index (WEI) Based on an Object-Oriented Model and GIS data

[EN] For the first time, this paper introduces and describes a new Weighted Environmental Index (WEI) based on object-oriented models and GIS data. The index has been designed to integrate all the available information from extensive and detailed GIS databases. After the conceptual definition of the index has been justified, two applications for the regional and local scales of the WEI are shown. The applications analyze the evolution over time of the environmental value from land-use change for two different case studies in Spain: the Valencian Region and the L'Alcora municipality. Data have been obtained from the Spanish Land Occupation Information System (SIOSE) public database and integrate GIS information about land use/land cover on an extensive, high-detailed scale. Results demonstrate the application of the WEI to real case studies and the importance of integrating statistical analysis of WEI evolution over time to arrive at a better understanding of the socio-economic and environmental processes that induce land-use change.Rodrigo-Ilarri, J.; Romero, CP.; Rodrigo-Clavero, M. (2020). Land Use/Land Cover Assessment over Time Using a New Weighted Environmental Index (WEI) Based on an Object-Oriented Model and GIS data. Sustainability. 12(24):1-22. https://doi.org/10.3390/su122410234S1221224Bockstaller, C., & Girardin, P. (2003). How to validate environmental indicators. Agricultural Systems, 76(2), 639-653. doi:10.1016/s0308-521x(02)00053-7Niemeijer, D., & de Groot, R. S. (2008). A conceptual framework for selecting environmental indicator sets. Ecological Indicators, 8(1), 14-25. doi:10.1016/j.ecolind.2006.11.012(1999). Environmental Indicators for Agriculture. doi:10.1787/9789264173873-en(2001). OECD Environmental Indicators. doi:10.1787/9789264193499-enCloquell-Ballester, V.-A., Cloquell-Ballester, V.-A., Monterde-Díaz, R., & Santamarina-Siurana, M.-C. (2006). Indicators validation for the improvement of environmental and social impact quantitative assessment. Environmental Impact Assessment Review, 26(1), 79-105. doi:10.1016/j.eiar.2005.06.002Nicholson, M., & Fryer, R. (2002). Developing effective environmental indicators––does a new dog need old tricks? Marine Pollution Bulletin, 45(1-12), 53-61. doi:10.1016/s0025-326x(02)00123-6Dale, V. H., & Beyeler, S. C. (2001). Challenges in the development and use of ecological indicators. Ecological Indicators, 1(1), 3-10. doi:10.1016/s1470-160x(01)00003-6Butt, B. (2018). Environmental indicators and governance. Current Opinion in Environmental Sustainability, 32, 84-89. doi:10.1016/j.cosust.2018.05.006Girardin, P., Bockstaller, C., & Werf, H. V. der. (1999). Indicators: Tools to Evaluate the Environmental Impacts of Farming Systems. Journal of Sustainable Agriculture, 13(4), 5-21. doi:10.1300/j064v13n04_03Gallopín, G. C. (1996). Environmental and sustainability indicators and the concept of situational indicators. A systems approach. Environmental Modeling & Assessment, 1(3), 101-117. doi:10.1007/bf01874899Saltelli, A., & Tarantola, S. (2002). On the Relative Importance of Input Factors in Mathematical Models. Journal of the American Statistical Association, 97(459), 702-709. doi:10.1198/016214502388618447Heink, U., & Kowarik, I. (2010). What are indicators? On the definition of indicators in ecology and environmental planning. Ecological Indicators, 10(3), 584-593. doi:10.1016/j.ecolind.2009.09.009Pannell, D. J., & Glenn, N. A. (2000). A framework for the economic evaluation and selection of sustainability indicators in agriculture. Ecological Economics, 33(1), 135-149. doi:10.1016/s0921-8009(99)00134-2Kurtz, J. C., Jackson, L. E., & Fisher, W. S. (2001). Strategies for evaluating indicators based on guidelines from the Environmental Protection Agency’s Office of Research and Development. Ecological Indicators, 1(1), 49-60. doi:10.1016/s1470-160x(01)00004-8Ziegler, C. R., Webb, J. A., Norton, S. B., Pullin, A. S., & Melcher, A. H. (2015). Digital repository of associations between environmental variables: A new resource to facilitate knowledge synthesis. Ecological Indicators, 53, 61-69. doi:10.1016/j.ecolind.2015.01.003Brambila, A., & Flombaum, P. (2017). Comparison of environmental indicator sets using a unified indicator classification framework. Ecological Indicators, 83, 96-102. doi:10.1016/j.ecolind.2017.07.023Handbook on Constructing Composite Indicators. (2005). OECD Statistics Working Papers. doi:10.1787/533411815016Knox Lovell, C. A., Pastor, J. T., & Turner, J. A. (1995). Measuring macroeconomic performance in the OECD: A comparison of European and non-European countries. 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