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Spatial analysis of the wood pellet production for energy in Europe

Blas Mola-Yudego a,b,*, Mari Selkimäki a, José Ramón González-Olabarria c

aUniversity of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI 80101 Joensuu, Finlandb Swedish University of Agricultural Sciences (SLU), Department of Crop Production Ecology, P.O. Box 7016, S-750 07 Uppsala, Swedenc Forest Science Centre of Catalonia, Ctra St. Llorenc de Munys, Km 2, ES-25280 Solsona, Spain

a r t i c l e i n f o

Article history:Received 5 March 2013Accepted 19 August 2013Available online

Keywords:Pellet tradeBioenergyKernel modelsSupplyEnergyBioenergy

* Corresponding author. University of Eastern FinlaP.O. Box 111, FI 80101 Joensuu, Finland. Tel.: þ358 50

E-mail addresses: blas.mola@uef.fi, blasmola@gma

0960-1481/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.renene.2013.08.034

a b s t r a c t

The distribution of the wood pellet plants in Europe was analysed using a geo-statistical kernel basedapproach, in order to identify and define cluster-regions with high concentration of pellet productioncapacity. For that, a database with the location of pellet plants, as well as its capacity, was constructed,identifying 378 pellet plants with annual capacities over 1000 t, and an aggregated production of 11.5million t. The geo-statistical methods facilitated the analysis of the plants with regards to their marketposition at global and local level.

At a European level, four main production areas were identified, defined as: “Central Europe” (Bavaria,Austria, and neighbouring areas of France, Switzerland and Italy), “Scandinavia”, “Finland”, and the“Baltic”. These areas concentrated over 50% of the pellet production, although presented differentcharacteristics regarding market establishment and development, their role in the global pellet trade andtheir raw material availability. The paper provides with methodological tools to identify and characterisethe main pellet production areas in Europe that can have further economic and policy applications.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

In recent years, pellets have become an important fuel in heatand power production across Europe. Pellets are considered to be acompetitive fuel option since the higher fuel density translates in areduction in the transportation and storage costs, and this advan-tage can be used in areas where cost efficient supply is a challengedue to storing and long transportation distances. In addition, theypresent lower moisture content in comparison with unprocessedbiomass higher effective heating value and uniform shape, and aclear burning and reduction of ashes. Finally, they are easy to betransported and stored and can be obtained from different feed-stocks being therefore adaptable to different locations with alter-native raw materials for biomass [1].

These advantages have led to an increase in pellet trade, asdomestic markets have increased the use of high quality pelletsresulting in a rise in the demand that often is fulfilled throughimports [2e4]. Investment subsidies and other national incentiveshave been the driving forces for the development of domestic pelletmarkets, as pellets heating systems are considered an essentialcomponent of European plans to reduce GHG emissions and are

nd, School of Forest Sciences,4422974.il.com (B. Mola-Yudego).

All rights reserved.

targeted by incentive programs in countries such as Germany,Norway, Sweden or Austria [3]. Similarly, in Denmark (one of theforerunners in wood pellet use), large scale pellet combustionbecame an issue in order to meet the renewable energy targets by2020 set by the European Union [5].

However, the supply of raw material, the availability of skilledmanpower, the capacity to adapt to new technological challenges, asufficient demand of a product from local markets, and the pres-ence of investors, are also requirements that should be fulfilled tosuccessfully establish a new transformation industry such as thepellet production. The presence of the these factors, together withthe possibility to capture investment subsidies and the capacity toconsolidate a growing market by ensuring the supply of pellets,could explain the potential aggregation of pellet transformationindustries in pellet production cores. The uneven spatial distribu-tion of economic activities of diverse nature has been studied andverified for a long time (e.g. Refs. [6,7]). By identifying andmeasuring the agglomeration patterns of an economic activity,such as the pellet production, not only would be possible to providea description of the actual situation of the pellet production sectorin Europe, but to establish the framework for future analysis aboutthe pulling forces causing that agglomeration.

In this context, the aim of this paper is to define the pellet supplyareas in Europe based on extensive data on the location and pro-duction capacity of the pellet plants. To do that, the paper in-vestigates the application of a geostatistical approach based in

B. Mola-Yudego et al. / Renewable Energy 63 (2014) 76e83 77

kernel methods in order to define, if possible, core areas from thepattern of geographical concentration of the pellet production atvarious spatial levels in order to better describe those areas and itspossible applications for market analysis.

2. Material and methods

2.1. Inventory of pellet capacity

An inventory of capacity was performed for the countries ana-lysed, including the capacity and location of the pellets plants. Theinventory aimed to be exhaustive. The location of the plants wasbased on different accounts of pellet producers, complemented andupdated by using the companies’ homepages and the companies’official financial reports. The accounts included the databases ofpellet plants for Sweden [8], Finland [9], Austria and Germany [10]and the rest of Europe [11,12]. Additional sources of informationwere based on existing scientific literature, company’s financialsummaries, and companies’ homepages. The collection of infor-mation involved in some cases direct contacts with pellet pro-ducers and pellet associations in some of the countries studied. Thelocation of the pellet plants was geo-referred, using their preciselocation or the closest urban centre, the last when the preciselocation of the plant was not available.

Only pellet plants with capacities over 1000 t a�1 were includedin the database in order to facilitate the data collection. In case thatthe pellet plant capacity was not available, but there was infor-mation about the location of the pellet plant and data on thecompany suggesting a significant pellet production, then anaverage value was attributed to the plant in order to minimise anypotential bias in the definition of the areas.

2.2. Geo-statistical methods

The analysis of the location of the pellet factories was based ongeospatial kernels. This approach is a non-parametric method forthe estimation of the spatial distribution of probabilities of occur-rence based on a pool of observed events. For a spatial region, acontinuous grid is first created, and the probability of occurrence ofa specific event for all the points of the grid is calculated, creating adensity function according to the number and distance of the pelletplants.

The kernel function was used in this study to calculate theprobability of occurrence of a pellet plant, and the geo-spatial ag-gregation of pellet capacity in a given area, using:

f^ðxÞ ¼ 1

nh2Xn

i¼1

KðuiÞ (1)

ui ¼ðx� xiÞ

h(2)

where x is the vector of coordinates of a given location, K is thekernel function used, h is the bandwidth radius, which affects thedispersion of the density function and Xi is the vector of coordinatesof the i observed pellet plants: therefore xeXi is the distance be-tween a point where the density function is to be estimated andeach of the observed pellet plants used to define the density areas.

The variables used were the Universal Transverse Mercator(UTM) coordinates of the pellet plants, The calculations were basedon the spatial statistic package SPlancs [13] adapted for R [14] toestimate the probability densities. A quartic kernel function with afixed bandwidth was applied, considering a method for correctingthe border effect based on Diggle [15] and Berman and Diggle [16].

By this means, the factories at the bordering areas are not over-represented. In addition, the pellet plants were weighted by theirproduction capacity.

The bandwidth radius determines the level of aggregation of thedata in the density function, and significantly affects the finaloutcome [17,18]. Although there is not a broadly accepted meth-odology to determine the optimal radius, as it also depends of thepurpose of the mapping [17,19], a common method is an ad hocchoice, referring h to a parameter [18]. In this study, the parameterof reference (h100) was calculated according to Worton [20] andused to aggregate the probabilities of pellet plant occurrence atlocal or global level by using different proportions of h100. There-fore, it was used h80, h40 and h20 corresponding to the 80%, 40%and 20% of the h100 value used to define the radius of search.

To analyse the resulting kernel estimations, raster maps withstandardised isopleths were created. The isopleths were based onpercent volume contours (PVC), in order to compare areas defininga high concentration of pellet production capacity. The PVCs definethe volumes under the utilisation distribution, and represent adefined percentage of the total pellet capacity in the smallestpossible area. For instance, the isopleths containing the 10thpercentile area shows the areas with the highest concentration ofpellet production, since it represents the smallest possible area tocontain 10% of the pellet capacity in Europe (i.e. the core productionarea). On the other hand, the 90th percentile area represents thelowest concentration, since it contains almost the total pellet ca-pacity. In this study, we assume that this line defines the supplymarket for pellet production. The resulting maps were presentedusing a 150 � 150 grid cells resolution.

Finally, the maps and the calculated PVCs were used to identifyand characterise the main pellet production markets in Europe,defined as continuous geographic areas with large shares of pelletcapacity. For those areas, additional parameters concerning landuses [21] and population [22] were calculated, as well as mainnational indicators of pellet trade [23], in order to describe the areawith regard to potential raw material supply, potential demand,and current trade.

3. Results

After the inventory of pellet production plants was finalised, 378pellet plants were identified, capable of producing annually a totalof 11.5 million tonnes of pellets (Fig. 1).

Based on the estimation of the radius of reference (h100), equalto 231 km, the spatial distribution of the pellet occurrence proba-bility was estimated using h100 and h80 for defining globalagglomerations, and using h40 and h20 for defining local agglom-erations (Fig. 2).

Each plant was therefore classified according to the estimationof probability of occurrence for h20 and h80 (Fig. 3), defining acompetition index: plants with a high value for h20 are located inan area with a high concentration of pellet capacity at local level,and plants with a high value for h80 are located in areas with highconcentration of pellet capacity at European level. The highestvalue for h20 would correspond to pellet plants with a position oflocal dominance of the production market (risk of local monopoly),and the highest values for h80 would correspond to global domi-nance of the production market (risk of global monopoly).

Using this competition index, country averages were calculatedwith the average values of all the plants. In this case, high countryaverages for the h20 estimates implied that are few pellet plantsbut they concentrate most of the local production of pellets(local dominance). This would be the cases of Portugal and theNetherlands. On the other hand, countries with high averages forh80 implied that those plants concentrate a large share of the pellet

Fig. 1. Countries analysed and total number of pellet plants included in the study.

B. Mola-Yudego et al. / Renewable Energy 63 (2014) 76e8378

capacity at European level (global dominance), which would be thecase of Austria, Germany and Sweden (Fig. 4).

At European level, four main production areas were defined,based on the use of the PVC curves for the h100 and h80 scores(Fig. 5). Those were defined as: “Central Europe” (including Bavaria,Austria, and neighbouring areas of France, Switzerland and Italy),“Scandinavia” (including South and Central Sweden and parts ofDenmark), “Finland” (including mostly southern Finland), and the“Baltic” (including Estonia, Latvia and Lithuania).

The area defined as “Central Europe” covered about 25% of theestimated total capacity (Table 1). This area has higher populationdensity than the remaining areas defined, and on the other hand,has a lower share of forest land. In total, this area includes over 70%of the total production capacity of Austria, Germany and Belgium(Table 2).

Finally, the area “Central Europe” combines exporter countrieslike Germany (Table 3) with net importers like Austria. The “Baltic”and “Finland” areas are clearly exporters, whereas the area “Scan-dinavia” is on average importing more than they produce.

4. Discussion

The identification of the European core areas for pellet pro-duction can be an important step in the field of economic analysisand energy policy. In the one hand it can facilitate the study of tradeflows and the forecasts of the market. It can, as well, be the subjectof policy framework analysis that can explain why pellets are

produced in some areas and not in others. In this context, thepresent study provides both data and methods.

It must be stressed that there is still an important lack of officialstatistics on pellet production and trade, which makes difficult thestudy on the development of pellet markets [4]. Although theidentification and location of pellet plants was partly based onexisting databases, it required an important effort to standardiseand complete existing records in order to be exhaustive, and insome cases included the verification of the documented figures.The final database included different number of plants and capacityfigures than other existing accounts (e.g. Pellet@las [12] included630 pellet producers and c. 8 million tonnes) which can be in partexplained by the decision of excluding small pellet plants, in orderto standardise the data, and by the inclusion of large plants missingin other accounts. Although those small producers excluded canbias some of the results (e.g. in Italy or Spain), it is assumed thatthose biases should be small since the calculations were weighted.Therefore, despite the number of small plants is numerically high,their actual share of the total capacity is negligible and would notsignificantly change the PVCs.

Our accounts reflected the situation by 2008, when some plantscould already be under construction or starting activity. However,the methods presented are rather flexible to update and do notassume any pre-defined distribution, allowing the definition ofnew ranges and the identification of the areas where there is a highconcentration of pellet factories. Therefore they can incorporateany update in the location of new plants or changes in their

Fig. 2. European pellet capacity aggregations for different values of the bandwidth radius of reference (h100 ¼ 231 km). The indices represent percentages of this value (h20: 28 km,h40: 128 km, h80: 185 km).

B. Mola-Yudego et al. / Renewable Energy 63 (2014) 76e83 79

capacity (due to the continuous developments of the pellet pro-duction) as new core areas can be calculated if new data are pro-vided. The use of similar geostatistical techniques to defineproduction areas have been previously used to define raw-materialproduction areas for bioenergy in Sweden [24] and for mapping the

Fig. 3. Representation of the pellet plants according to their concentration (weighted probarespectively).

aggregated centres of economic activity [25] revealing a high po-tential for analysis.

The use of alternative bandwidth radius to aggregate the ca-pacity presented many advantages. The reference parameter wasused to find general trends at a global level, and a shorter radius to

bility of occurrence) at a global and local level (h80 and h20, for left and right figures,

Fig. 4. Country averages for the pellet plants analysed, for global and local concen-tration indices (h20 and h80, respectively). The size of the circles represents thecountry’s total pellet capacity.

B. Mola-Yudego et al. / Renewable Energy 63 (2014) 76e8380

reveal locally clustered production areas. It is generally acceptedthat a bandwidth radius must be defined according to the nature ofthe study, and different methodologies have been proposed fromthe statistical point of view [20], although no general rules havebeen broadly adopted [17]. In our case, the use of a radius of

Fig. 5. Pellet capacity concentration in Europe for bandwidth radius of 231 km (h100, rightareas concentrate 50% of the total capacity, and lighter areas would include 90% of the totaEurope, B: Scandinavia, C: Finland, D: Baltic.

reference was based in the recommendations of Worton [20]grounded mostly on a statistical basis. However, this value wasscaled resulting of an aggregation radius over 250 km for generaltrends, and lower than 30 km for local concentration patterns,which was decided considering the profitable thresholds for pelletdelivery [4] and the average transportation distance for wood chipmaterials [26]. By this means the resulting values can be used as amarket index: a pellet plant plants with high values of concentra-tion using shorter radius would imply that the local pellet capacity(e.g. for a municipality or county) is clustered, implying intensiveuse of rawmaterials, and has implications in the logistics associatedas well as in the expectedmarket developments. On the other hand,a plant presenting high values of concentration using a large radius(h100) means that is located in an area that concentrates a largeshare of the total pellet production, and is competing for the do-mestic market with other plants. In both cases, they reflect areaswith a large domestic market or export oriented.

At a local scale, Portugal and Netherlands presented high valuesof concentration (h20). In both cases, their pellet markets are ofrecent development, they are dominated by one or few pellet plantswith large capacities, and they are somehow isolated from themainproduction areas. Concerning raw materials, in both cases thereare clear limitations as the feedstock potential for the productionof wood pellets from domestic industry (Netherlands [27]) orfrom agricultural/forest residues is rather limited (Portugal [28]).There are some specific characteristics: Portugal has an annual

). Dark areas concentrate 30% of the total pellet capacity estimated for Europe. Stripedl capacity. Based on the higher concentrations, four main areas are defined: A: Central

Table 3Country’s pellet exports and imports for the four main areas defined (�103 t).

Zone Country To/from Export to Import from

“CentralEurope”

Germany Austria 90.9 49.1France 20.8 60.3EU27 321.6 204.8 Exporter

Austria CzechRepublic

0 66.0

Italy 124.4 0EU27 136.1 174.6 Importer

Switzerland Germany 1.5 22.6Italy 3.8 0EU27 5.6 43.6 Importer

Italy Austria 0.1 266.3Slovenia 1.5 57.2EU27 2.2 529.7 Importer

“Baltic” Estonia Denmark 208.6 0Latvia 1.0 95.1EU27 281.3 89.3 Exporter

Latvia Lithuania 1.0 2.9Sweden 66.5 0EU27 157.5 3.5 Exporter

Lithuania Denmark 32.4 0Latvia 2.7 25.3EU27 62.6 24.3 Exporter

“Scandinavia” Sweden Finland 2.1 72.6Denmark 98.5 2.1EU27 102.9 373.4 Importer

Denmark Sweden 7.1 61.7Estonia 0 174.0EU27 9.7 689.1 Importer

“Finland” Finland Sweden 60.5 0.1Estonia 0 4.2EU27 125.2 6.6 Exporter

Table 1Characterisation of the four main areas defined, according to their shares of thepellet capacity, their population and forest land covered.

Central Baltic Scandinavia Finland

N plants 69 18 72 18% European plants 18 % 5 % 19 % 5 %Pellet capacity 2924 993 1975 834% European capacity 25 % 8 % 17 % 7 %Population (hab. x106) 58.5 2.9 7.2 2.9Population density (hab. km�2) 157.5 31.9 35.5 27.6% Forest land 48 % 52 % 68 % 68 %% Agriculture land 45 % 41 % 17 % 15 %Total area (�103 km2) 371.1 90.5 204.0 105.1

B. Mola-Yudego et al. / Renewable Energy 63 (2014) 76e83 81

production close to 100 000 t, and about 90% of the production isexported, as it lacks a domestic market [28]. The production in theNetherlands, on the other hand, is oriented to the domestic market,and about 95% of the pellets are co-fired in large coal power plants[27].

At a global scale, we identified four main areas that concentratemost of the pellet production in Europe: Central Europe, Scandi-navia, Finland and the Baltic. In general, these areas have beenleading theway of pellet market development during the last years.Most of the countries included in these main areas carried outimportant efforts towards the implementation of a common qualitystandard in the production of pellets. In the area defined as CentralEurope these countries already had a quality standard for pellets[29], and in the area defined as Scandinavia, Sweden developed itsown national standards [7,30]. More recently, most of the countriesenclosed in these areas have actively been implementing thecommon European standard (EN 14961-2) by 2011 [30]. Since highquality pellets reduce the maintenance of the pellet boilers, com-mon standards contribute to provide confidence to the end users. Inthis sense, ensuring the fuel quality is a vital matter for establishinga strong market position.

In Central Europewe recognised a core area for pellet productionin the area of South Germany and Austria, and in both countriespellet markets are very well established: production and con-sumption of pellets are one of the highest in Europe. These coun-tries have in common that they produce enough pellets for thedomestic market and also for exportation [22,30]. In Austria, thecompanies in the pellet sector are well cooperated and they havehad a common aim to expand the pellet markets. The earlydevelopment of pellet quality standard (ÖNORM M7135 standard)helped both the pellet producer as well as the boiler manufacturesto improve their products. Austria is also the only country which

Table 2Pellet capacity per country included in the main four areas defined. Countriesunderlined form the area’s core.

Area Countries Capacity(�103 t y�1)

% (Countrytotal capacity)

“Central Europe” Austria 957 95%Germany 1388 74%Belgium 235 87%Switzerland 19 25%France 170 15%Italy 145 31%Slovenia 10 18%

“Baltic” Estonia 385 100%Latvia 14 9%Lithuania 514 88%

“Scandinavia” Denmark 180 44%Sweden 1785 72%

“Finland” Finland 834 72%

has a standard to ensure the quality of pellets during transportation(ÖNORMM7136) as well as quality criteria for wood pellet storagesin households (ÖNORM M7137). In general, the public measureshave played an important role [31] and both state and provinceshave been subsidising the pellet heating systemwhich compensatethe higher investment cost compared with e.g. oil heating system[32]. The efforts invested to pellet production, development ofboilers, transportation and storages as well as the policy supporthas resulted a very develop and dynamic pellet markets. In Ger-many, large part of the pellet producers are located in South andSoutheWest Germany, where there are high concentrations ofwood related industries and therefore raw material supply. Theproduction and the number of plants have increased, enough tocover the domestic demand of pellets and to export large shared.However, of the total pellet production capacity only about 60%wasin used in 2008, perhaps suggesting a market saturation that wouldagree with the estimates of global and local concentration found inthis study for those years.

Concerning Scandinavia, Sweden is the largest producer andconsumer of wood pellets in the world [8,33]. In Sweden threefactors have been identified affecting the rapid development of thepellet industry: availability of raw materials, taxation systemfavourable to biofuels and extended district heating networks[32,34]. The number of small and medium scale producers is thehighest of all countries studied and many small scale wood pro-cessing industries process the residues to high quality pellets as thehigh price of pellets makes the investment profitable even for smallentrepreneurs [35]. Since the sector of small scale pellet consumershas been growing and continues, the demand for high qualitypellets and pellets sold in small sacks has been growing, whichcould have been one of the reasons boosting the number of smallscale producers. The number of small and medium scale pelletusers is expected to keep on growing in the near future, while the

B. Mola-Yudego et al. / Renewable Energy 63 (2014) 76e8382

number of large scale users is not expected to grow remarkably.Furthermore, it is possible that the large scale CHP-plants mightreplace part of the fuel pellets with forest residuals [36].

In Finland, there were 24 pellet plants operating in 2008, withfive additional plants planned or being constructed [3], raising theestimated production capacity of 1.16 million tons. The total pro-duction estimate for 2020 is 1.5 million tons of pellets which wouldrequire establishing new pellet plants or enlarging the existingplants [37]. As the area presents large forest resources and lowpopulation, the pellet market has been long time export orientedbut recently the domestic consumption has started to increase. Stillabout 58% of the total pellet production was exported in 2007,while in 2006 the share was 75% of the production [38]. Most of thepellet plants are medium or large scale producers, and only a fewsmaller producers exist on the markets. However, during the 2009the economic situation reduced the wood industry and saw millproduction which decreased the availability of raw materials. Thisled to the reduction in domestic pellet production down to299 000 t and the importation increased to 50 000 t [39].

Finally, the pellet market in the Baltic area has different char-acteristics comparedwith the rest of themarket areas recognised. Inone hand, general, the pellet production is quite new, started around2000 and it was the Finnish and Swedish companies that introducedthe pellet plants. However, in this case the pellet plants werefounded to fulfil the need of pellet of the other countries nearby,mainly in Scandinavia, as a domestic market was not firmly estab-lished [40]. In addition, in all three countries there is a shortage ofraw materials due to the rapid establishment of the pellet plants inparallel to a reduction in the saw mill production, resulting in anincrease of raw material costs [33]. However, the region presents alarge share of forest lands and unutilised potentials for the provisionof wood energy [41] as well as for the establishment of fast growingplantations [42] that should secure the supply of raw materials ifproper technical and economic incentives are provided.

5. Conclusions

This is the first study to the authors’ knowledge that analysesthe location and production figures of the wood pellet markets forenergy based on a geostatistical method. The methodology pro-posed helps to identify areas where pellet production is wellestablished, and provides indicators for market analysis. Furtheranalysis can be oriented in the evolution of the core areas alongtime linked to developments in the national policy framework. Themethods and data presented, complemented by additional vari-ables, can also be used in future research in order to study, at globallevel the trends in biofuel trade, and at local level, to define optimalor expected locations for the establishment of future pellet plants.

Acknowledgements

Financial support for this project was provided by the FinnishCultural Foundation. Our gratitude to Prof Paavo Pelkonen, ProfLauri Sikanen, Dr Dominik Röser, Surya Magar and Robert Prinz forall their valuable cooperation and assistance.

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