Five years left – How are the EU member states contributing to the 20% target for EU's renewable energy consumption; the role of woody biomass

Published Date
Biomass and Bioenergy
December 2016, Vol.95:64–77, doi:10.1016/j.biombioe.2016.09.016
Research paper

• Author 

• Svetlana Proskurina ^a,,,
• Richard Sikkema ^b
• Jussi Heinimö ^c
• Esa Vakkilainen ^a

• aLappeenranta University of Technology, Skinnarilankatu 34, 53850, Lappeenranta, Finland
• bEuropean Commission – Joint Research Centre (EC-JRC), Directorate Sustainable Resources/Bio-economy (D1), Italy
• cMikkeli Development Miksei Ltd, Sammonkatu 12, 50130, Mikkeli, Finland

Received 12 December 2015. Revised 27 August 2016. Accepted 15 September 2016. Available online 23 September 2016. 

Highlights

• •
  All EU-28 countries are making efforts to reach the RE EU's target.
• •
  The role of woody biomass in renewable energy as GFEC was evaluated.
• •
  Woody biomass development is unbalanced among EU-28 countries.
• •
  Some MS with high energy consumption pattern can miss own national RE targets.

Abstract

The European Union has set ambitious targets of raising the share of EU energy consumption produced from renewable resources from 20% by 2020 to 27% by 2030. The aim of this paper is to assess the role of woody biomass in renewable energy as gross final energy consumption in the European Union (the EU-28). The paper identifies leading and lagging countries in biomass development by focusing on their current biomass use and forecasts future perspectives. The research compares and evaluates the role of biomass in renewable energy in the EU-28 focusing on countries' potential resources and policy support. The study shows that all countries are making efforts to reach the 20% target in 2020 and exhibit a trend of increasing renewable energy as gross final energy consumption towards the new target of 2030. Solid biomass plays an important role in reaching the EU's renewable energy targets. The majority of the EU-28 countries are close to reaching their national renewable energy targets and show a very attractive biomass development. Unless energy consumption decreases however, some member states will face serious problems in reaching their renewable energy target in 2020. Following our analysis, the largest problems occur in those MS having a relative high-energy consumption pattern: France, Germany and the United Kingdom. It is unlikely that they can comply with expected renewable energy demand, unless they mobilize more woody biomass from their available domestic potential (France, Germany) or considerably increase their woody biomass imports (mostly wood pellets) from elsewhere (United Kingdom).

Keywords

Renewable energy

Bioenergy

Biomass

Renewable energy targets

National Renewable Energy Action Plan

European Union

List of abbreviations, conversion factors and definitions

AEBIOM

European Biomass Association

CFB

Circulating fluidized bed

CHP

Combined heat and power

CO₂

Carbon dioxide

EEA

European Environment Agency

EU

European Union

EU-28

Member States of the European Union since January 2013, when Croatia joined the EU

FSC

Forest Stewardship Council

GDP

Gross Domestic Production

GFEC

Gross Final Energy Consumption

GHG

Greenhouse Gas

GIC

Gross Inland Consumption

H&C

Heating & Cooling sectors

IEA

International Energy Agency

IEC

Inland Energy Consumption

IRENA

International Renewable Energy Agency

JRC

Joint Research Centre

MS

Member State

NREAP

National Renewable Energy Action Plan

R&D

Research and Development

RE

Renewable Energy

REN 21

Renewable Energy Policy Network for the 21st Century

RES

Renewable Energy Sources

RES-E

Renewable Energy Sources in Electricity sector

RES-H

Renewable Energy Sources in Heating sector

ROC

Renewables Obligations Certificate

UK

United Kingdom

WBA

World Bioenergy Association

Units

GWh

Gigawatt-hour(s) = 1000 MWh

1 MWh ≈ 0.51 tonnes of wood pellets = 8.98 primary GJ

bases on lower heating value of 17.6 GJ per tonne and an efficiency rate for 10% pellet co-firing of 40.1% [1]

Mm³ = 1000 000

m³ = 7.1 PJ (global average) [2]

Definitions

Bioenergy

Bioenergy refers to energy derived from biofuels

Biomass

Refers to the biodegradable fraction of products, waste and residues from agricultural (including vegetal and animal substances), forestry and related industries, as well as the biodegradable fraction of industrial and municipal waste

Woody biomass

Refers to the trees and woody plants, including limbs, tops, needles, leaves, and other woody parts, grown in a forest, woodland, or rangeland environment, that are the by-products of forest management

Biofuels (=biomass fuel)

Fuel produced directly or indirectly from biomass. The fuel may have undergone mechanical, chemical or biological processing or conversion or it may have had a previous use. Biofuel refers to solid, gaseous and liquid biomass-derived fuels

Bioliquids

Refers to the liquid fuels made from biomass for energy purposes other than transport (i.e. heating and electricity)

Gross inland consumption of energy (GIC)

Gross inland consumption of energy (GIC) is the first aggregate in the national energy balances. It refers to “apparent” consumption and is derived from the formula that takes into account primary production, exports, imports and stock changes. It includes the primary energy from fossil fuels, from renewable energies (biomass, wind, solar, hydro), derived heat and trade of electrical energy

Gross final energy consumption (GFEC)

Gross final energy consumption (GFEC) is calculated from national energy balances. GFEC starts with the GIC data, after which transformation losses, distribution losses and own consumption of electricity and heat within the energy sector are subtracted. The GFEC data can be divided over the sectors involved in the energy consumption, after the subtraction of non-energy consumption (e.g. use of cokes for chemical products). At the end, we remain with final energy consumption by industry, transport and households [3]

 Table 1

Table 1.

 Table 2

Table 2.

Fig. 1.

Fig. 2.

 Table 3

Table 3.

Fig. 3.

Fig. 4.

Fig. 5.

Fig. 6.

Fig. 7.

Fig. 8.

• DOCX (25K)

• ∗ 
  Corresponding author.

For further details log on website :
http://www.sciencedirect.com/science/article/pii/S0961953416303063

Soft Independent Modelling of Class Analogy applied to infrared spectroscopy for rapid discrimination between hardwood and softwood

Published Date
Energy
15 December 2016, Vol.117:251–258, doi:10.1016/j.energy.2016.10.092

• Author 

• D. Duca
• M. Mancini
• G. Rossini
• C. Mengarelli
• E. Foppa Pedretti
• G. Toscano
• A. Pizzi ^,

• Università Politecnica delle Marche - Agricultural, Food and Environmental Sciences, Via Brecce Bianche, 60131 Ancona, Italy

Received 15 October 2015. Revised 14 September 2016. Accepted 21 October 2016. Available online 28 October 2016. 

Highlights

• •
  Quality parameters such as origin and source are required by pellet standards.
• •
  The study aims to discriminate hardwoods and softwoods.
• •
  FTIR spectroscopy coupled with SIMCA has been evaluated as a suitable tool.
• •
  110 wood samples belonging to 12 species and 4 blends were analysed.
• •
  The method shows good performance and could be useful to verify standard compliance.

Abstract

European policy promotes renewable energies and sets specific targets. Solid biofuels can play a significant role and the quality is an important aspect to be checked. Quality parameters such as origin and source are also required by specific biofuel standards. Therefore it could be useful to develop a rapid and cheap tool to distinguish between hardwoods and softwoods especially in unstructured, milled or densified wood in order to check the compliance of producer's declarations. Compared to other analytical methods, infrared spectroscopy is fast, non-destructive and low cost. In this study Fourier transform infrared (FTIR) spectroscopy coupled with Soft Independent Modelling of Class Analogy (SIMCA) has been evaluated as a method for discrimination purpose. A large dataset of 110 wood samples belonging to 12 species were analysed. In addition 4 blends were also analysed to test the discrimination performance of the tool. FTIR-SIMCA has correctly classified 93% of hardwood samples and 100% of softwood samples at high significance level. Furthermore, 100% of tested blends were associated with no class, showing a discrimination ability of the technique in recognizing blends from pure material. This method could be useful to verify the compliance of producer declarations about wood origin and source.

Keywords

MIR

Pellet

Woody biomass

SIMCA

Multivariate analysis

Biomass blends

---

 Table 1

Table 1.

Fig. 1.

 Table 2

Table 2.

Fig. 2.

Fig. 3.

 Table 3

Table 3.

Fig. 4.

Fig. 5.

Fig. 6.

 Table 4

Table 4.

• ∗ 
  Corresponding author.

For further details log on website :
http://www.sciencedirect.com/science/article/pii/S0360544216315377

The wood pellet business in Russia with the role of North-West Russian regions: Present trends and future challenges

Published Date
Renewable and Sustainable Energy Reviews
November 2015, Vol.51:730–740, doi:10.1016/j.rser.2015.06.051

Author 

• Svetlana Proskurina ^a,,,
• Jussi Heinimö ^b
• Mirja Mikkilä ^a
• Esa Vakkilainen ^a

• aLappeenranta University of Technology, Skinnarilankatu 34, 53850 Lappeenranta, Finland
• bMikkeli Development Miksei Ltd, Sammonkatu 12, 50130 Mikkeli, Finland

Received 5 September 2014. Revised 27 April 2015. Accepted 29 June 2015. Available online 17 July 2015. 

Abstract

The Russian wood pellet business has expanded rapidly in the last decade. The first Russian pellet production plant was built in 2003 and within ten years, Russia has become an important exporter of pellets, mainly to the Nordic and Baltic area. The aim of this paper is to present an overview of the current status of the Russian pellet market with particular emphasis on pellet exports. In addition to reviewing the state of the pellet market in Russia, the paper addresses challenges facing the Russian wood pellet business, both domestically and in key export markets. The paper is based on a review of published scientific literature, trade magazines, the latest Russian official documents and reports, as well as interviews with experts and the materials of IEA Bioenergy Task 40. Attempts have been made to reconcile the varying and conflicting data given in different Russian documentation sources, thus permitting a more accurate representation of the Russian pellet business, an important player in the global pellet trade. Despite its importance, there is limited work available on the Russian pellet industry and this paper thus contributes to greater understanding of the Russian pellet business. Based on an analysis of the market situation, challenges and opportunities are presented for future scenarios of Russian pellet exports. The study further demonstrates the important role that Russia plays in the global pellet market. This paper finds that although the Russian pellet business developed very rapidly during 2004–2009, the industry now faces considerable challenges. Due to an oligopolistic market structure, inadequate infrastructure and lack of foreign investments, it is expected that, despite its obvious potential, the Russian wood pellet industry may not develop significantly in the near future and exports to Europe could even decline.

Abbreviations

CO₂, carbon dioxide

CPM, California pellet mill

EPC, European Pellet Council

EU, European Union

EU-27, Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, the Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom

FSC, Forest Stewardship Council

GHG, greenhouse gas

IEA, International Energy Agency

MDF, medium density fiberboard

NRAP, National Renewable Action Plan

UK, United Kingdom

Keywords

Wood pellets

Import

Export

Russia

Market

Challenges

---

Fig. 1.

 Table 1

Table 1.

Fig. 2.

Fig. 3.

Fig. 4.

 Table 2

Table 2.

 Table 3

Table 3.

 Table 4

Table 4.

 Table 5

Table 5.

Fig. 5.

Fig. 6.

• ⁎ 
  Corresponding author. Tel.: +358 466 322 953.

For further details log on website :
http://www.sciencedirect.com/science/article/pii/S1364032115006231