Data-driven modeling of CO2 emission-allowance compensation for wood-purchasing optimization toward carbon–neutral forest industry

Abstract

The faster market changes of EU’s CO2 emission allowance price have increased operation challenges in wood supply of forest industry. The objectives of this study are to present basics of its data-driven modeling for purchasing renewable forest wood. Particularly, the effects of the changes in prices and available carbon sink are considered in management of wood purchasing at the level of the local districts. Two scenarios described procurement situations in non-renewable carbon sinks. The results were compared to the scenario in renewable carbon sink of carbon–neutral forestry. Time-varying emission-allowance parameters of models affected wood purchase and deliveries in the districts. Therefore, cost efficiency of wood-supply operations, as well as the utilization rate of renewable wood resources, can be optimized by data-driven dynamic wood-flow models in digitalized decision support. In addition, the results testify that the model optimizes wood purchasing in the districts at the way of CO2 emission allowance market. Therefore, by using the model wood-supply operations could be optimized toward carbon neutrality, which is important success factor of forest industry.