Elsevier

Applied Energy

Volume 144, 15 April 2015, Pages 193-203
Applied Energy

A spatial analysis of woodfuel based on WISDOM GIS methodology: Multiscale approach in Northern Spain

https://doi.org/10.1016/j.apenergy.2015.01.099Get rights and content

Highlights

  • A multiscale GIS analysis of woodfuel supply/demand.

  • Template for scale or scenario dependant integration of data into WISDOM methodology.

  • Pixel level calculation of all data enables operations between rasterized maps.

  • Shows benefits of analytical GIS tools in bioenergy system management and planning.

Abstract

Given the complexity of generating energy from biomass, the need has arisen for support tools to assist in balancing energy and forestry policies which are sufficiently flexible to address the issues of planning and management at small and large scales.

The present study aims to adapt WISDOM GIS methodology for application in the autonomous region of Asturias (Northern Spain) and thereby, by creating a geodatabase, to contribute to a support tool for investigating the potential of woodfuel. This will aid the public administration by providing information on woodfuel supply and demand at the regional, municipality and site-specific level, and thus assist in decision making in terms of formulating new energy strategies.

In terms of supply (t year1), in this work, woodfuel from forest area is defined as the crown fraction only (branches and leaves), although in the case of Eucalyptus spp., bark is also included as it is remains on-site following extraction of eucalypts for the pulp industry. Non-Forest Direct Supply was calculated on the basis of the relevant categories from an agricultural land use inventory and average woodfuel productivity. In addition, physical and legal constraints related to accessibility of the woodfuel were considered, the former applying restriction filters with values weighted depending on the interaction between slope map, road networks and centres of population, and the latter considering legal limitations in protected areas. In addition, unused waste from the wood processing industry was included. To calculate total woodfuel demand (t year1) for energy generation (heat and electricity), both the residential and industrial sector were taken into account.

All data was georeferenced through Geographic Information Systems (GISs), which allow operations between raster maps to be performed to generate numeric and spatial results focusing on logistics and biomass strategies, depending on the inputs data and scale employed for each scenario considered. In addition, the application of the methodology at the site-specific level illustrates the practical implementation at the small scale of the geodatabase created, by evaluating the woodfuel available to feed, in case 1, a wood-fired power plant in a specific proposed location and, in case 2, this plant combined with a second plant in a different municipality, both cases also taking into consideration industrial demand.

Introduction

Current key challenges in high population areas such as Europe are to meet an ever increasing energy demand and ensure both the security and sustainability of energy supply. Biomass, whether it is from agricultural or forest sources, plays an ever more important role in meeting these challenges and is key to achieving CO2 emission targets in relation to climate change. Recently, the Biomass Panel of the RHC-Platform established the implementation actions for 2014–2020 [1], according to the European Strategic Research Priorities for Biomass Technology published in April 2012 [2]. One goal is that by 2020, biomass supply should double compared to current levels ensuring that adequate feedstock is available at competitive prices. This promotion of biomass generation and use, not only addresses the issue of energy security, but has the added value of creating jobs in the sector and particularly in rural areas. Furthermore, Directive 2009/28/CE of the European Parliament and Council, related to promoting the use of energy from renewable sources, established that each Member State of the European Union (EU) was to develop an action plan for renewable energies for the period 2011–2020 in order to achieve the objectives set out in the Directive.

The use of Geographic Information System (GIS) framework may be considered one of the best tools to enable and facilitate this policy challenge [3]. Developments using GIS technology have revolutionised the possibilities available for improving knowledge of existing bioenergy systems (supply and demand) through spatial analysis, and to quantify their potential availability and the practicalities of meeting demand taking into account the various constraints and limitations existing in an area that impact on the viability of exploitation. This information allows the identification of supply opportunities and new markets which can be opened and are compatible with forest, energy and environmental strategies [4].

Integration of data such as forest inventories with GIS data allows the description of the spatial distribution of these resources and can be combined with data relating to consumption to support energy planning policies. In order to be in a position to make decisions about how limited resources are used and managed within an existing area, it is preliminarily necessary to understand how effectively resource conservation is addressed at present in any given area [5]. What is more, GIS support tools enable multiscale approaches to be implemented which facilitate and verify decision making processes. For example, Thomas [6] analysed the spatial supply and demand relationships for biomass energy potential for England and Sacchelli et al. [7], working in the Italian Alps, created a spatial model to quantify the potential amount of woodfuel from the forestry sector at several scales.

One of the many GIS tools developed in recent years is WISDOM, the result of a collaboration between FAO, and the Centre for Ecosystem Research of the National Autonomous University of Mexico (UNAM). WISDOM (Woodfuel Integrated Supply/Demand Overview Mapping) is based on certain key characteristics of wood energy systems: geographic specificity, heterogeneity of woodfuel supply sources and provides the user with great flexibility to adapt the methodology to specific scenarios and scales. A detailed description of the potential and specific application of the methodology has been published by Drigo et al. [8] and Masera et al. [9]. Many case studies have been published applying WISDOM at different spatial scales, such as for countries [10], [11] or cities [12].

In Spain, the National Renewable Energies Action Plan [13], specifies that renewable energies (REs) should account for 20% of total energy consumption by 2020. In 2009, the base year, REs accounted for 9.4% of primary energy in Spain, 3.9% of this coming from biomass. In parallel with and to complement this, the Spanish Renewable Energies Plan, estimated the energy input from woody biomass for 2015 as 1582 ktep, and for 2020 as 2081 ktep. Furthermore, woodfuels coming indirectly from woody biomass (i.e. from the wood processing industry) were expected to reach 1679 ktep and 1702 ktep respectively in the same year [14].

In recent years, in Asturias, an autonomous region in Northern Spain, there has been an increase in biomass use to generate energy, enhanced by subsidies for renewable energy use from the Regional Government, which was expected to subsidize in 2013 roughly 200 biomass and geothermal energy projects. During recent years, regional biomass R + D, studies of productivity and cost in biomass logging operations [15], [16] have been conducted as well as estimations of biomass quantity for different forest species [17], [18], [19]. Recently, in addition, the Government of Asturias has commissioned CETEMAS to carry out WISDOM-Asturias. In this study, a qualitative and quantitative biomass supply and demand evaluation at region, municipality, and site specific levels was developed using the WISDOM GIS methodology and its results mapped through ArcMap GIS software [20]. The current study, in addition, provides results both before and after applying filters which take into account physical and legal accessibility constraints, similar to other authors [7], [21].

In practice, however, the final objective is to adapt the WISDOM GIS methodology for a specific region, in this case in the north of Spain, to have all this information available as a support tool to investigate the potential of woodfuel at the regional and municipality level. Furthermore, we aim to show how this methodology can aid the decision making of the public administration to, for example, evaluate the suitability of proposed wood-fired power plants at a site-specific level, as in the work of Viana et al. [22] or to accurately ascertain productions costs so as to promote the use of energy woody biomass. This is important given that woody biomass production costs vary with factors such as the scale of demand, the location of the processing plants and, when considering multi-sources of biomass, rotation periods, production technologies and human accessibility to the biomass resources [23], [24].

The work uses data currently available and due to the large quantity and the multitude of formats, as well as the difficulties of analysing it in a uniform manner, this study had to consider specific ways of calculating annual woodfuel at pixel level to adapt the methodology. This work will therefore serve as a template of how to integrate data into the methodology for future applications at different scales and scenarios in other areas.

Section snippets

Multiscale structure approach

GISs are scale dependent, and it is necessary to consider the appropriate spatial scale required in each case. In this study data from Asturias – an autonomous region in the north of Spain – was analysed through WISDOM GIS methodology at the pixel level (50 × 50 m) and then scaled-up to make inferences about supply of and demand (oven dry tonnes) for woodfuel at various spatial levels: regional, municipality and site-specific. Such a small pixel size was used due to the reduced size of many forest

Results and discussion

From this analysis of supply and demand, various results, considering oven dry tonnes, were generated, a selection of which are discussed below. GISs are scale dependent, and it is necessary to consider the appropriate spatial scale required in each case. For this study different scales were considered: regional, municipality and the level of a specifically defined small area. At this latter scale, with ownership categories such as private, forest industries or state, it is possible to take

Conclusions

In this study, a regional analysis of available woodfuel based on Geographic Information Systems and the balance between supply and demand was conducted. Accessible supply of woodfuel from forest area and non-forest area, and supply from the wood processing industry was calculated to provide Total Supply. Moreover, Total Demand was calculated considering residential and industrial demand. Thus, information related to bioenergy systems was able to be integrated into a geodatabase. This is

Acknowledgements

The authors are grateful to the Plan for Science, Technology and Innovation (PCTI) and the Forest Service of the Principality of Asturias for funding the research project “WISDOM-ASTURIAS”. Desarrollo de una herramienta de gestión para la Biomasa del Principado de Asturias” and we acknowledge receipt of the Severo Ochoa Asturian fellowship (subsidised by the Government of the Principality of Asturias) awarded to SSG. Also special thanks are due to the technical assistance of Miguel Trossero,

References (35)

  • RHC-Platform. Renewable heating & cooling. European technology platform. Strategic Research priorities for biomass...
  • J. Randolph
    (2004)
  • S. Sacchelli et al.

    Bioenergy production and forest multifunctionality: a trade-off analysis using multiscale GIS model in a case study in Italy

    Appl Energy

    (2012)
  • Drigo R, Masera OR, Trossero MA. Woodfuel Integrated Supply/Demand Overview Mapping – WISDOM: a geographical...
  • Masera O, Drigo R, Trossero MA. A methodological approach for assessing woodfuel sustainability and support wood energy...
  • Drigo R, Veselic Ž. Woodfuel Integrated Supply/Demand Overview Mapping (WISDOM) – Slovenia – Spatial woodfuel...
  • Drigo R. WISDOM – East Africa – Spatial woodfuel production and consumption analysis of selected African countries. FAO...
  • Cited by (20)

    • A GIS methodology for optimal location of a wood-fired power plant: Quantification of available woodfuel, supply chain costs and GHG emissions

      2017, Journal of Cleaner Production
      Citation Excerpt :

      The authors then calculated DSW (t/year) from the forest area according to different levels of accessibility depending on the interaction between slope map, road networks, population centres, legal limitations in protected areas such as National Parks, Natural Parks, Sites of Community Importance (SCIs) and Special Protection Areas (SPAs), as well as restrictions related to logging operations. Using this data from Sánchez-García et al. (2015a) the following results (in oven dry tonnes) for DSW are used in this current work: no constraints (Level 1; 895,847 t/year), physical access constraints (Level 2; 580,005 t/year) and physical and legal access constraints (Level 3; 546,965 t/year). In the current study, in order to work at a plot level and consider each plot as a supply point, as in works by other authors (Anttila et al., 2011; Forsell et al., 2013; Laitila et al., 2015), it was assumed that the EDSW in each stratum is distributed uniformly across its plots, i.e. for a stratum with n plots, the EDSW of each plot is equal to the EDSW of that stratum divided by n. Considering the municipality as the smallest administrative area, it was decided to take the value of EDSW at each level of accessibility by municipality and divide it by the number of plots belonging to each municipality.

    • Analysis of factors affecting productivity and costs for a high-performance chip supply system

      2017, Applied Energy
      Citation Excerpt :

      Transport costs also affects tactical and operational decisions e.g. from which areas should the biomass be sourced, how much should be chipped on the landing and how much at the terminal and what equipment should be used. Optimisation [13–19], simulation [20–22] and GIS-techniques [23–25] have been used to find feasible solutions at these planning levels. To increase payloads and thereby reduce transport costs, many forest fuel assortments are chipped on the landing prior to transport.

    View all citing articles on Scopus
    View full text