Integrated geo-referenced data and statistical analysis for dividing livestock farms into geographical zones in the Valencian Community (Spain)

The livestock sector in the Valencian Community (Spain) has experienced an increase in the intensity of farming with an increase in the number and size of pig and poultry facilities. The absence of previous environmental requirements in this region has produced a high concentration of facilities in some areas, and urban sprawl has resulted in many farms located in problematic areas close to villages or towns, residential areas and protected areas. Conflicts surrounding land use and environmental issues have been a problem in the region for many years. The initial step to solve this problem is to produce a territorial planning system to intervene and correct the current development and adapt to new European environmental regulations. The objectives of this study are to group farms with homogeneous characteristics in the Valencian Community and to characterise and search for spatial dependency patterns within the livestock sector. These objectives have the final aim of contributing basic scientific information to subsequent administrative planning decisions for livestock. This study presented methodology based on Geographic Information Systems and statistical methods for dividing livestock farms into zones and for characterising these areas. We obtained nineteen livestock geographical areas with unique characteristics (such as livestock species composition) and verified that these areas did not follow a spatial pattern.Calafat Marzal, MC.; Gallego Salguero, AC.; Quintanilla García, I. (2015). Integrated geo-referenced data and statistical analysis for dividing livestock farms into geographical zones in the Valencian Community (Spain). Computers and Electronics in Agriculture. 114:58-67. doi:10.1016/j.compag.2015.03.005586711

Drivers of winegrowers' decision on land use abandonment based on exploratory spatial data analysis and multilevel models

The frequency of producers opting to abandon agricultural land has become increasingly, highlighting the significance of this phenomenon due to its environmental, landscape, and socio-economic impacts. The decisions of producers to abandon or maintain/improve their farms depend on individual and contextual factors. The aims of this research are twofold. Firstly, to evaluate the influence of the neighbours on the winegrowers' decisions, using spatial analysis. Secondly, to clarify the specific importance of each of the individual and contextual drivers in farmers' decisions to improve their farms, to keep them unchanged or to abandon them, using multilevel models. The results obtained for the case study of vineyards in Spain, reveal a strong agglomeration phenomenon in farmers' decisions indicating that producers make land use decisions influenced by what their neighbours do. A multilevel analysis identifies that individual factors are determinant and that the influence of contextual factors is conditioned by the innovation process at farm level. Individual drivers, such as size, innovation, Protected Designations of Origin and irrigation influence vineyard area, with irrigation having the greatest overall influence, and is expected to be decisive in climate change projections. The Protected Designations of Origin are driving forces that dynamize the territory and achieve productive concentrations, encouraging winegrowers to replant, but they are not enough to halt abandonment. The elements that slow down the abandonment of plots are irrigation and the combination of innovation and context variables, mainly the combination of modernised plots in the municipalities with trading options.Ministry of Science and Innovation, Spain, European Regional Development Fund, European Commission. Project “Strengthening innovation policy in the agri-food sector” (RTI2018-093791-B-C22). And the authors acknowledge the support received from the Universitat Politècnica de València through the research project “Young people and social and organizational innovation in areas with demographic risk” integrated in the research line "Socio-economic analysis of innovation in sustainable agri-food systems (SAS)" and the Universidad Pública de Navarra through the research project 2022 PRO-UPNA 11504

Modelo de negocio para la recuperación de estruvita a partir de purines de cerdo

[ES] El objetivo principal de este Trabajo fin de máster (TFM) es formular un modelo de negocio para la producción de estruvita a partir del tratamiento de deyecciones ganaderas a pequeña escala. La investigación del mercado potencial y clientes objetivo incluye la elaboración de un mapa de empatía que evalúa lo que pueden ver, pensar, oír y hacer los clientes potenciales del proceso de recuperación de fósforo, incluyendo entre ellos a agricultores y ganaderos con cierta capacidad de innovación y sensibilidad ambiental. Se aplicaron modelos de formulación estratégica (Design Thinking y Modelo Lean Canvas) al estudio de viabilidad de la reutilización de purines de cerdo y otros influentes orgánicos para la cristalización de estruvita. El estudio se sitúa en el marco del proyecto internacional Interreg RE-LIVE WASTE, orientado a un enfoque circular de valorización de residuos ganaderos, en países del Mediterráneo europeo. La formulación del modelo de negocio tiene en cuenta la complejidad del problema y la necesaria colaboración de agentes implicados. Se cuenta con la colaboración de un grupo interdisciplinar en el que participaron una organización profesional agraria, una cooperativa ganadera, un centro de investigación, una fundación ambientalista y un socio tecnológico. Se aportan también datos de una experiencia piloto que consiste en una planta de tratamiento capaz de procesar 40 m3 de purín líquido al día para la producción del precipitado.[EN] The concentration of pig farms in some territories can induce soil and water pollution derived from the surplus of nutrients. A classic way out is the agronomic recovery of manure as a fertilizer. This process is complex due to the livestock concentration in some areas that makes its agricultural application difficult due to the costs of handling and transporting the slurry. The main objective of this study is to formulate a business model to produce struvite from the treatment of small-scale livestock manure. The research of the potential market and target customers included the development of an empathy map that considers what potential clients of the P recovery process can see, think, hear and do, including farmers with some capacity for innovation and environmental concern. Strategic formulation models (Design Thinking and Lean Canvas Model) were applied to the feasibility study of the reutilization of pig slurry and other organic influents for struvite crystallization. The study was carried out within the framework of the international project Interreg RE-LIVE WASTE, aimed at following a circular approach to the valorisation of livestock waste, in European Mediterranean countries. The pilot experience consists of a treatment plant capable of processing 40m 3 of liquid slurry per day to produce the struvite precipitate. For this, a technology is proposed that largely reuses and improves previous installations and adapts to the needs of small users. Net treatment costs are estimated to be between €0.1/m3 in the most favourable scenario and €5.7/m3 in the most unfavourable scenario. The formulation of the business model considers the complexity of the problem and the necessary collaboration of the agents involved. The model was supported by an interdisciplinary group in which an agricultural professional organization, a livestock cooperative, a research centre, an environmental foundation, and a technological partner. The study has an informative and pedagogical interest in that it illustrates how a pilot plant can be designed, improving another pre-existing treatment plant with a limited investment cost. The first tests have validated the effectiveness of the process and raised some questions about its commercial viability, considering regulatory issues and the need for more tests. The dissemination of the project contributes to raising awareness of the opportunities offered by a circular approach in areas of high livestock density and excess nutrients.Este trabajo no habría sido posible sin la posibilidad de haber colaborado en el Proyecto XXX Re-Live Waste financiado por el Programa Interreg de la Unión Europea.García Ibáñez, CI. (2020). Modelo de negocio para la recuperación de estruvita a partir de purines de cerdo. http://hdl.handle.net/10251/147962TFG

Livestock odour dispersion and its implications for rural tourism: case study of Valencian Community (Spain)

[EN] Aim of study: To study the relationship between the problem odours caused by livestock farms and the evolution of rural tourism. Area of study: A coastal region in Spain, the Valencian Community. Material and methods: The odour emission rates of 4,984 farms have been calculated, and the ambient odour concentration was determined to assess the odour nuisance. The odour concentration was modelled by applying the Gaussian model based on emission data and the most unfavourable meteorological conditions of the 45 climatic stations distributed throughout the analysis area. The dispersion model was implemented in a geographic information system, deducing the municipalities affected using the odour concentration thresholds. Furthermore, the evolution of rural tourism in municipalities was studied during the period of 2006-2017. The relationship between the evolution of rural tourism and the effects of odours is studied by means of a bivariate spatial correlation analysis. Main results: Pigs are the predominant species in areas with the greatest odour emission problems; similar to 29% of farms can result in annoyances among the population with odour concentrations greater than 5 OU/m(3), and 46% of municipalities can be affected by odour problems. These odour nuisances had negative consequences in the municipality where measures were carried out to favour rural development, such as rural tourism. Municipalities were detected in which the problem of odours can be a deterrent to rural tourism, whereas in other municipalities it was observed that minimizing livestock activity can be a method to promote rural tourism. Research highlights: This study provides a methodology that allows modeling the odour dispersion of livestock and relates its implications to rural tourism. Municipalities have been identified where livestock odours can cause a stagnation of the rural tourism income.Calafat Marzal, C.; Gallego Salguero, AC. (2020). Livestock odour dispersion and its implications for rural tourism: case study of Valencian Community (Spain). Spanish Journal of Agricultural Research (Online). 18(2):1-17. https://doi.org/10.5424/sjar/2020182-15819S117182Aatamila M, Verkasalo PK, Korhonen MJ, Suominen AL, Hirvonen MR, Viluksela MK, Nevalainen A, 2011. Odour annoyance and physical symptoms among residents living near waste treatment centres. Environ Res 111: 164-170.Amador J, Dominguez J, 2005. Application of geographical information systems to rural electrification with renewable energy sources. Renew Energ 30: 1897-1912.Amadou ML, Villamor GB, Kyei-Baffour N, 2018. Simulating agricultural land-use adaptation decisions to climate change: An empirical agent-based modelling in northern Ghana. Agric Syst 166: 196-209.Anselin L, 1995. Local indicators of spatial association-LISA. Geograph Anal 27: 93-115.Anselin L, Syabri I, Kho Y, 2006. GeoDa : An introduction to spatial data analysis. Geograph Anal 38 (1): 5-22.BOE, 1995. Ley 11/1994, de 27 de diciembre, de espacios naturales protegidos de la Comunidad Valenciana. Boletín Oficial del Estado (España), BOE-A-1995-3325.BOE, 2007. RD 1071/2007, de 27 de julio, por el que se regula el sistema geodésico de referencia oficial en España. Boletín Oficial del Estado (España), 35986-35989.Boers D, Geelen L, Erbrink H, Smit LAM, Heederik D, Hooiveld M, Yzermans CJ, Huijbregts M, Wouters IM, 2016. The relation between modeled odor exposure from livestock farming and odor annoyance among neighboring residents. Int Arch Occup Environ Health 89: 521-530.Brancher M, Schauberger G, Franco D, De Melo Lisboa H, 2016. Odour impact criteria in south American regulations. Chem Eng Trans 54: 169-174.Brancher M, Griffiths KD, Franco D, de Melo Lisboa H, 2017. A review of odour impact criteria in selected countries around the world. Chemosphere 168: 1531-1570.Cai L, Koziel JA, Zhang S, 2011. Odorous chemical emissions from livestock operations in United States. Int Conf on Remote Sens Environ Transport Eng, IEEE, pp: 532-535.Calafat C, Gallego A, Quintanilla I, 2015. Integrated geo-referenced data and statistical analysis for dividing livestock farms into geographical zones in the Valencian Community (Spain). Comput Electron Agric 114: 58-67.Capelli L, Sironi S, Del Rosso R, Guillot JM, 2013. Measuring odours in the environment vs. dispersion modelling: A review. Atmos Environ 79: 731-743.Chasco C, Fernández G, 2008. Análisis de datos espacio-temporales en geomarketing: difusión espacial del lanzamiento de un nuevo producto. Invest Market 98: 56-61.Danuso F, Rocca A, Ceccon P, Ginaldi F, 2015. A software application for mapping livestock waste odour dispersion. Environ Model Softw 69: 175-186.EC, 1996. Council Directive 96/62/EC of September 27, 1966 on ambient air quality assessment and managementEC, 2015. Programa de desarrollo rural de la Comunitat Valenciana Cofinanciado por FEADER para el periodo 2007-2013. European Commission. http://www.avfga.gva.es/es/pdr-cv-2007-2013EC, 2017. Programa de desarrollo rural de la Comunitat Valenciana Cofinanciado por FEADER para el periodo 2014-2020.pdf. European Commission. http://www.avfga.gva.es/es/pdr-cv-2014-2020.Exceltur, 2018. Perspectivas turisticas. 65-2018. https://www.exceltur.org/perspectivas-turisticas/Fortuin FTJM, Omta SWF, 2009. Innovation drivers and barriers in food processing. Br. Food J 111 (8): 839-851.Gallego A, Calafat C, Segura M, Quintanilla I, 2019. Land use policy land planning and risk assessment for livestock production based on an outranking approach and GIS. Land Use Policy 83: 606-621.Generalitat Valenciana, 2006. El turismo rural en la Comunitat Valenciana. Conselleria de Turisme.Generalitat Valenciana, 2008. Guía técnica para la gestión de las emisiones odoríferas generadas por las explotaciones ganaderas intensivas [Technical guide for the management of odour emission rates generated by intensive livestock farms].Gifford F, 1959. Statistical properties of a fluctuating plume dispersion model. Adv Geophys 6: 117-137.Guffanti P, Pifferi V, Falciola L, Ferrante V, 2018. Analyses of odours from concentrated animal feeding operations: A review. Atmos Environ 175: 100-108.Gulickx MMC, Verburg PH, Stoorvogel JJ, Kok K, Veldkamp A, 2013. Mapping landscape services: A case study in a multifunctional rural landscape in the Netherlands. Ecol Indic 24: 273-283.Guo H, Jacobson L, Schmidt D, Nicolai R, Janni K, 2004. Comparison of five models for setback distance determination from livestock sites. Can Biosyst Eng 46 (6): 17-25.Hayes ET, Curran TP, Dodd VA, 2006. A dispersion modelling approach to determine the odour impact of intensive poultry production units in Ireland. Bioresour Technol 97: 1773-1779.Henshaw P, Nicell J, Sikdar A, 2006. Parameters for the assessment of odour impacts on communities. Atmos Environ 40: 1016-1029.Hernandez G, Trabue S, Sauer T, Pfeiffer R, Tyndall J, 2012. Odor mitigation with tree buffers: Swine production case study. Agric Ecosyst Environ 149: 154-163.Janes KR., Yang SX, Hacker RR, 2004. Single-component modelling of pig farm odour with statistical methods and neural networks. Biosyst Eng 88: 271-279.Janicke U, Müller WJ, Both R, Trukenmüller A, 2012. Comment on "Empirical model derived from dispersion calculations to determine separation distances between livestock buildings and residential areas to avoid odour nuisance" by G. Schauberger, R. Schmitzer, M. Kamp, A. Sowa, R. Koch, W. Eckhof, F. Eichler. Atmos Environ 50: 385-386. https://doi.org/10.1016/j.atmosenv.2011.12.010.Lin XJ, Barrington S, Nicell J, Choinière D, Vézina A, 2006. Influence of windbreaks on livestock odour dispersion plume in the field. Agric Ecosyst Environ 116: 263-272.Lucernoni F, Tapparo F, Capelli L, Sironi S, 2016. Evaluation of an odour emission factor (OEF) to estimate odour emissions from landfill surfaces. Atmos Environ 144: 87-99.Molina-Ruiz J, Martínez-Sánchez MJ, Pérez-Sirvent C, Tudela-Serrano ML, García-Lorenzo ML, 2011. Developing and applying a GIS-assisted approach to evaluate visual impact in wind farms. Renew Energ 36: 1125-1132.Moreno R, Vayá E, 2000. Técnicas econométricas para el tratamiento de datos espaciales: La econometría espacial. Universitat de Barcelona, Col UB 44, manuals.Oettl D, Kropsch M, Mandl M, 2018. Odour assessment in the vicinity of a pig-fatting farm using field inspections (EN 16841-1) and dispersion modelling. Atmos Environ 181: 54-60.Olaizola AM, Ameen F, Manrique E, 2015. Potential strategies of adaptation of mixed sheep-crop systems to changes in the economic environment in a Mediterranean mountain area. Livest Sci 176: 166-180.Pagans E, Domíngues R, van Harreveld AP, 2010. Gestión de impactos por emisiones odoríferas procedentes de actividades ganaderas. Int. Workshop on Anaerobic Digestion of Slaughterhouse Waste; Bonmatí A, et al. (Eds.), pp: 23-32.Pasquill F, 1961. The estimate of the dispersion of windborne material. Met Mag 90: 33.Piringer M, Knauder W, Petz E, Schauberger G, 2016. Factors influencing separation distances against odour annoyance calculated by Gaussian and Lagrangian dispersion models. Atmos Environ 140: 69-83.Rich KM, Rich M, Dizyee K, 2018. Participatory systems approaches for urban and peri-urban agriculture planning: The role of system dynamics and spatial group model building. Agric Syst 160: 110-123.Romain AC, Nicolas J, Cobut P, Delva J, Nicks B, Philippe FX, 2013. Continuous odour measurement from fattening pig units. Atmos Environ 77: 935-942.Schauberger G, Piringer M, Jovanovic O, Petz E, 2012a. A new empirical model to calculate separation distances between livestock buildings and residential areas applied to the Austrian guideline to avoid odour nuisance. Atmos Environ 47: 341-347.Schauberger G, Schmitzer R, Kamp M, Sowa A, Koch R, Eckhof W, Eichler F, Grimm E, Kypke J, Hartung E, 2012b. Empirical model derived from dispersion calculations to determine separation distances between livestock buildings and residential areas to avoid odour nuisance. Atmos Environ 46: 508-515.Schauberger G, Lim TT, Ni JQ, Bundy DS, Haymore BL, Diehl CA, Duggirala RK, Heber AJ, 2013. Empirical model of odor emission from deep-pit swine finishing barns to derive a standardized odor emission factor. Atmos Environ 66: 84-90.Schauberger G, Piringer M, Heber AJ, 2014. Odour emission scenarios for fattening pigs as input for dispersion models: A step from an annual mean value to time series. Agric Ecosyst Environ 193: 108-116.Smith RJ, 1995. A Gaussian model for estimating odour emissions from area sources. Math Comput Model 21: 23-29.Solsona-Monzonís J, 2014. Análisis prospectivo del turismo rural: El caso de la comunitat valenciana. Cuad Tur: 313-334.Sommer-Quabach E, Piringer M, Petz E, Schauberger G, 2014. Comparability of separation distances between odour sources and residential areas determined by various national odour impact criteria. Atmos Environ 95: 20-28.Sucker K, Both R, Bischoff M, Guski R, Winneke G, 2008. Odor frequency and odor annoyance. Part I: assessment of frequency, intensity and hedonic tone of environmental odors in the field. Int Arch Occup Environ Health 81: 671-682.Ubeda Y, Ferrer M, Sanchis E, Calvet S, Nicolas J, López PA, 2010. Evaluation of odour impact from a landfill area and a waste treatment facility through the application of two approaches of a Gaussian dispersion model. Proc 5th Bienn Conf Int Environ Model Softw Soc iEMSs 1: 322-331. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2473&context=iemssconferenceUNE, 2004. UNE-EN 13725:2004 Air quality - Determination of odour concentration by dynamic olfactometry.Vanhaverbeke W, Cloodt M, 2006. Open innovation in value networks. In: Open innovation: Researching a new paradigm; Chesbrough H, Vanhaverbeke W, West J (Eds.). Oxford Univ Press, pp: 258-281.Willemen L, Verburg PH, Hein L, van Mensvoort MEF, 2008. Spatial characterization of landscape functions. Landsc Urban Plan 88: 34-43.Wu C, Liu J, Zhao P, Piringer M, Schauberger G, 2016. Determination of the odour concentration and odour intensity of a mixture of odorous substances by chemical concentrations: A comparison of methods. Chem Eng Trans 54: 283-292.Yamashita R, Hoshino S, 2018. Development of an agent-based model for estimation of agricultural land preservation in rural Japan. Agric Econ 164: 264-276.Yepes V, 1995. Turismo sostenible en el interior de la Comunidad Valenciana: posibilidad de un desarrollo turístico complementario al del "sol y playa". Papers de Turisme 17: 75-87.Zahn JA, DiSpirito AA, Do YS, Brooks BE, Cooper EE, Hatfield JL, 2001. Correlation of human olfactory responses to airborne concentrations of malodorous volatile organic compounds emitted from swine effluent. J Environ Qual 30: 624-634