Assessing the Economic Profitability ofBiorefinery Schemes

Maurizio PROSPERISTAR*AgroEnergy Group, University of Foggia, Italy

University of Foggia, Dip. SAFE

Via Napoli 25, 71122 Foggia, ITALY

Tel. +39-0881-589.356

Email: maurizio.prosperi@unifg.it

Biorefinery for the Production of Energy and Bio-Based Products – 29-30 October, 2013, Torin, Italy

University of Foggia, STAR*AgroEnergy Group Via Napoli 25,71122 Foggia, Italy

Outline

• Background and motivation• Objective• Methodological framework• Economic tools• Empirical exercises• Discussion

Background and Motivation

• According to current state-of-the-art, biorefinery seems very promising for multipurpuse use of biomass:

- food & feed ingredients- chemicals- advanced materials- bioenergy (biofuels, power and/or heat)

• (partial) substitute of already existing fossil carbon derivates

• Besides the private approach (profitability & competitiveness), public aspects should be economically considered:

- Substitution of exhaustible with renewable resources

- Reduction of CO2 emissions

- Valorization of idle resources: local heterogenous biomass, socially embedded knowledge, unemployed people

--> strong interest in Rural Areas

Economic Value of Biorefiny: Who cares?

Economic evaluation = Economic accounting

Economics helps decision making: pursuing the highest benefit, with minimum use of resources

Economic agents interested in biorefinery schemes:

• Researchers (and students)

• Private investors (e.g. Banks; Venture capital)

• Industrialists

• Farmers

• Policy makers / Decision makers (e.g. EU, member states, local governments)

• Consumers, etc...

Objective

• Identification of methodologies leading to the ¨economic value¨ of biorefinery schemes

• Basic approach: Cost-Benefit Analysis (CBA)

– Private perspective: quantifying the profitability of a biorefinery, assuming a hypothetical competitive market (demand and supply)

– Public perspective: quantifying the expected benefit to whole society (i.e. Environment, public health, jobs, equity, justice, quality of life,...)

Methodological Framework (CLASSIC)

Cost-Benefit Analysis: requires Input & Output evaluation:

• Marketable goods --> market prices

• Non-marketable goods: a) Use value, b) non-use value, c) option value, d) bequest value :

– Production cost (a)

– Comparison with similar traded goods (a)

– Substitution value (a)

– Complementary value (a)

– Transformation value (a)

– Edonic price (b) ( - travel cost (a+b) )

– Opportunity cost (a+b+c)

– Willingness to pay (WTP) or to accept (WTA) (a+b+c+d)

• best choice criteria: depends on data availability, time and budget

Static vs Dynamic analysis

Economic agents are assumed to perform their choices in different ways:

• Static: decision making is referred at a specific time ¨t¨ (e.g. One year), and every analysis is conducted ¨ceteris paribus¨ (i.e. by assuming a set of conditions as constant)

• Dynamic: considering a given time horizon (e.g. 10 years), with 2 main critical issues:

– Discount rate: needed to compare economic values which are referred to different time

– agents´expectations• change over time• are ¨path dependant• are affected by the ¨learning curve¨• depend on information, technological transfer, experience, etc.

t

$

r=0

r>0

Technology Readiness Level (TRL)

- Economic analysis is based on people´ expectations

- Education, knowledge, information, trust, etc. are affected by TRL

- TRL: measures

the maturing of

evolving

technologies

- Economic agents

1-2: researchers,institutions

3-6: researchers,institutions, SMEs

7-9: researchers,

institutions, SMEs,investors, consum.

Source: Florin Paun, internet document

Evaluation methods and TRL

1 2 3 4

QualitativeAnalysis- SWOT- Focus Gr.- scenario analysis

6 7 9

QualitativeAnalysis- SWOT- Focus Gr.

MulticriteriaDecision Making models (comparison among alternatives)

CBA (descriptive)

Qualitative Analysis- SWOT-SOR-Fuzzy Cognitive Maps

Quantitative Analysis- Net Present Value- CBA- all evaluation criteria

Source: our elaboration

Main issues

- Difficult to deal with innovative process & goods

- How to allocate costs & benefits to multiple co-products or by-products of the biorefinery?

- Which discount rate?* private perspective (risk of the investment)* public perspective (time preference)

• Intedisciplinary approach (e.g. Chemistry + engineering + economics + … ) needed to perform a scientifically sound and logically consistent analysis !!!

Empirical exercise n.1 (TRL 6 ; complementary value)

• Estimating the complementary (synergic) effect of biochar related to the enhancement of H

2O holding capacity on 1 ha of irrigated crop,

included in a farm of 20 ha, in semi-arid region

• Data: 20 ha, 5000 mc of irrigation H2O, water tariff at 0.20 Eur/mc; labor

and capital endowment are not binding.

1) static analysis: let´s suppose that by adding ca 10 Mg/ha of biochar, will lead to an enhancement of rain water, for a corresponding 10% of irrigation water saving. Therefore:5000 mc x 10% = 500 mc (saved water)

500 mc x 0,20 Eur/mc = 100 Eur/ha

In the case of a biochar stable for at least 50 years, and supposing a discount rate of 2%:

V = R/r ; V= 100/0.02 = 5,000 Eur --> Value of biochar

2) dynamic analysis: the 500 mc of H2O shall be used by the farmer to

cultivate additional 0.1 ha of irrigated crop, leading to an increase of profit by 150 Eur. Therefore, the value is V=150/0,02 = 7500 Eur

Empirical exercise n.2(TRL 7 ; hedonic price)

- Evaluation of the premium price of bioplastics for agricultural uses (e.g. Plastic mulching)

- Adoption of a survey among 16 farmers to determine their WTP (total economc value)

- Results:

a) WTP = +5~10% of plastics

b) 40% of subsity may be financed by the EU Rural Development plan

Empirical exercise n.3 (TRL 3 ; substitution value)

- Economic value of SOS from municipal organic waste

- Adoption of the substitution value of a similar product already existing in the market ¨potassium humate¨ (80-85% of humic substances)

- FOB price: 0.5-1.5 $/kg

- Value of 1 kg of SOS: depends on its content in humic substances (e.g. 70%): 1 $ : 82.5% = x : 70%

X = 0.85 $

Occorre considerare le diverse determinanti che possono influire sul valore finale: scala di produzione, distanza dai mercati, tipo di formulato, ecc.

Discussion

• Interdisciplinary approach is needed to data collection, modelling, results discussion, implications --> suggestions to decision maker(s)

• Economic evaluation must be ¨science based¨

• ¨Scientists¨ have to consider economic agents´ expectations and their decision making process

Thank you for your attention!

Acknowledgments:

- EUBIS – Cost Action

- 7FP ¨STAR*AgroEnergy¨ project

- Fondazione Caripuglia