(441e) An Ontological Approach Enabling “a Priori” Quantitative Assessment of Is Networks

Cecelja, F., University of Surrey
Trokanas, N., University of Surrey
Raafat, T., University of Surrey

Industrial Symbiosis (IS) is a growingly accepted paradigm for processing waste into material, energy and water with benefits to participants measured by economic and environmental gains, among others. Although the practice of IS has demonstrated the need for evaluating these benefits either in the process of screening of impending options or monitoring the operation of symbiotic networks and despite of some attempts to quantify them (Chertow and Lombardi 2005), no unified metrics or concomitant methods for calculating them has been proposed. In the same line, the existence of such metrics is also anticipated to have impact on further promotion and advancement of IS practice, but also on ameliorating the screening process and serving as a decision making tool.

This paper presents an innovative approach based on knowledge modelling which facilitates “a priori” calculation of IS metrics (Raafat et al. 2013). Metrics are implemented as ontology properties of materials, waste types and processing technologies participating in IS, calculated during the process of I/O matching and include the cost savings, CO2 emissions, landfill diversion and water savings.  More specifically, properties used in calculations are material quantities (for inputs and outputs), waste composition, processing cost, material prices, CO2 emissions and geographical location. Metrics used for screening the options are inferred from tacit and explicit knowledge embedded in ontology, while metrics for monitoring purposes are mainly extracted from explicit knowledge provided by the user. In addition to property values predefined in ontology, i.e. hasComposite, and property values provided by users, i.e. hasPatternOfSupply, dynamic nature of properties, such as prices and quantities, are also accounted for. In cases of missing values, default values obtained from literature are used instead. The results of the screening process are presented with respective semantic relevance calculated during the I/O matching. Also, during the I/O matching priorities to certain aspects of the synergy such as proximity, environmental effects or economic outlook can be set.

The calculation of the metrics occurs in three forms: i) Input savings – representing savings that occur due to changes in input materials (i.e. using substitute or recycled materials), ii) Process savings – representing savings that occur due to changes in the process (i.e. changes in transportation or location) and iii) Disposal savings – representing savings that occur due to changes in the disposal process (i.e. landfill diversion or by-product utilization). Economic gains are calculated from respective properties: i) market price of a material either as a recyclate or a by-product, ii) operational costs of the process and iii) the disposal savings occurring either from eliminating the cost of disposal or generating new income from selling the by-product. By the same token, environmental benefits are calculated from i) the embodied energy of the materials and by-products, ii) the distance between IS participants, iii) the carbon footprint of the process, iv) quantities of materials and by-products diverted from landfill and v) changes in water needs or utilization of waste water.

The approach has been verified as part of a web service platform that has been tested in several cases in the Viotia region, Greece. The platform offers an industrial symbiosis web service to hundreds of participating companies. The effort has been funded by the LIFE+ initiative (LIFE 09 ENV/GR/000300), which authors acknowledge.


Chertow, M. and D. Lombardi (2005). Quantifying Economic and Environmental Benefits of Co-Located Firms. Environmental Science & Technology 39(17): pp  6535-6541.

Raafat, T., F. Cecelja, N. Trokanas and X. Bimi (2013). An Ontological Approach Towards Enabling Processing Technologies Participation in Industrial Symbiosis. To be published in Computers & Chemical Engineering 52: pp.