| Title |
Method for identifying industrial symbiosis opportunities |
| ID_Doc |
24771 |
| Authors |
Patricio, J; Kalmykova, Y; Rosado, L; Cohen, J; Westin, A; Gil, J |
| Title |
Method for identifying industrial symbiosis opportunities |
| Year |
2022 |
| Published |
|
| DOI |
10.1016/j.resconrec.2022.106437 |
| Abstract |
Industrial Symbiosis (IS) can reduce industrial waste and the need for virgin material extraction by utilizing waste generated by one industry as a raw material for another. Input-output matching is a commonly used approach for identifying potential IS partnerships. Usually, to collect necessary data for input-output matching, companies are asked to participate in workshops or surveys. However, such activities can be costly and time consuming. Additionally, companies may be unwilling to participate due to issues around data confidentiality. This article aims to show how these barriers can be overcome by a new method for identification of IS oppor-tunities, which does not require companies to be surveyed. The developed matching approach uses statistical datasets and IS databases. The underlying principle is to use known IS partnerships and databases developed by the authors containing data on typical waste generation and resource use by industries, to expand and link other potential donors and receivers. This allows the expansion of one IS example into multiple potential relationships. The method promotes Circular Economy development by identifying more opportunities to utilize more sec-ondary resources through connecting previously unrelated industry sectors. The method has been tested in Sweden, where the goal was to identify potential partnerships between industries that generate sawdust as a waste product and companies that could utilize sawdust in their industrial processes. Out of 6,726,534 potential symbiotic links identified by the method, 159,630 were shortlisted using prioritization criteria reflecting an increased likelihood of symbiosis. |
| Author Keywords |
Industrialsymbiosis; Circulareconomy; Industrialwaste; Industrialsymbiosisdatabase; Inputoutputmatching |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000831649600003 |
| WoS Category |
Engineering, Environmental; Environmental Sciences |
| Research Area |
Engineering; Environmental Sciences & Ecology |
| PDF |
https://doi.org/10.1016/j.resconrec.2022.106437
|