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Table 2 Sustainability assessment tools shown with their orientations, main strengths and weaknesses and examples of their extensions and combinations with other tools

From: Indicators and tools for assessing sustainability impacts of the forest bioeconomy

Tool

Orientation

Strengths

Weaknesses

Extensions & combinations

Cost-benefit analysis (CBA)

Economic

Monetary valuation of gained benefits. Monetized impacts are especially suitable to policy making. The total of benefits for society is possible to make well illustrated.

Problems in ethical and democratic considerations. Value is often subjective. Allocation of total costs to one benefit is invalid - e.g. odor reduction itself does not cost the full value of the investment.

Combination with other tools to monetize the non-monetary values and vice versa, for example with input-output.

Input-output (IO) methods

Economic

Economic tables are commonly available for IO-analysis and are well and reliably documented. Preciseness is better if markets are well-known. Especially suitable for industry once cost structure and profitability is applied.

Assumption of linear market responses. Markets needs to be well established and known for higher certainty levels. In this case, the new products make much uncertainty and pulp and paper experience much price fluctuations.

Extensions to environmental dimension (EE-IO).

Environment (environmentally extended IO)

Environmental extension of IO is obtainable from commonly available statistics.

Shares the weaknesses of IO. In addition, EE-IO may produce large datasets which are cumbersome to operate.

LCA databases or MFA calculations may be applied

Life cycle analysis (LCA) methods

Environment (ELCA)

Comprehensive consideration of all inputs and emissions of a product during its life-cycle. Inclusion of indirect emissions, such as those from steel or fossil fuel production. Standardized method and comprehensive databases are available.

Highly demanding in data and large data sets are demanding to handle. Datasets not always available, but access only via costly licenses. Datasets outdate fast. Datasets not fully transparent in documentation

Combination with material flow analysis possible.

Social (SLCA)

Social aspects are often connected to economic and ecological issues. Hence, much data is available.

Methods to assess and derive social impacts from existing data are in infant state. Cannot be directly attached to environmental LCA because of high site specific nature.

Data from other LCA methods

 

Economic (LCC)

Economy is often of high interest to any decision maker and economic information supports social impact assessment too.

Some economic information may be difficult to obtain because of trade secrets. Market price fluctuations and changes in consumption patterns cause uncertainties

Combining with OI, MFA or the other LCA methods is possible.

Material flow analysis (MFA)

Environment

Focus on loads of materials needed in production of a specific (end) product enables identification of inefficient material uses and production phases. Can be comprehensive, yet simple to operate.

May inherit a limited view in respect to inclusion of externalities outside the examined system.

MFA-model tools are capable to add many different indicators if the functional unit permits it. Combination with LCA is possible.

Multi-criteria analysis (MCA)

Any

Number of approaches available. Enables thorough evaluation and balancing between alternatives with respect to indicators, dimensions and stakeholders via outranking, weighting, voting, for example. Inclusion of intangible and highly subjective aspects is possible.

Known unsustainable alternatives need to be excluded beforehand. Preferences have to be obtained e.g. via questionnaires which may make the MCA. Stakeholders' lack of knowledge and risk of personally biased preferences may corrupt the evaluation.

Multi-criteria analysis can use results of any impact assessment method. MCA method then has to be chosen accordingly to the task complexity and data availability.