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Optimizing Forest-Biomass-Distribution Logistics from a Multi-Level Perspective - Review
Forest and wood biomass represent a sustainable reservoir of raw materials and energy, offering a viable alternative to fossil fuels. These resources find extensive use in producing bioproducts, including solid wood and wood materials. The judicious exploitation of forest and wood biomass can be pivotal in reducing carbon emissions and securing material and energy independence. The business viability of producing valuable goods from woody biomass hinges on ensuring its sustained availability. This necessitates access to high-quality biomass at a minimal cost, demanding the efficient design of wood-biomass-distribution logistics. Furthermore, it is imperative to give equal weight to social and ecological considerations in shaping the forest- and wood-biomass-distribution logistics, thereby ensuring the sustainable utilization of this renewable raw material source. This article presents research focused on the business optimization of distribution logistics for specific forms of forest biomass used in wood material production. While most studies have primarily concentrated on the business or ecological issues of biomass utilization, this article offers a comprehensive insight by addressing business, ecological, and social facets in assessing and optimizing wood-biomass-distribution logistics. Multi-stakeholder life-cycle-assessment optimization takes into account the reduction of greenhouse gases as an ecological metric, with production costs and capital expenditure forming the business metrics. At the same time, the generation of employment opportunities is commonly regarded as the pivotal social criterion. There remains a necessity for further exploration into the potential social impacts of forest biomass utilization. Additionally, developing enhanced methodologies and decision-support tools for scheduling wood-biomass-distribution logistics that holistically consider business, ecological, and social criteria is an essential ongoing task.
Comparative efficiency of roundwood processing into pallet lumber
Abstract The article is an attempt to determine the impact of market changes and sawnwood production on the utilisation of a limited supply of wood raw material, taking into account coniferous species and selected grades found on the market for the production of pallet lumber. The proposal to include the raw material value factor in the econometric model provides a measurable benchmark. Closed efficiency through the criterion of maximising the added value of wood in industrial processing takes into account the parameters that shape the impact of the value of the product and wood raw material. This criterion is derived from the supply of roundwood and customer demand for particular species and grades. The efficiency index is a reference to the price factors of market change over a variable period of time with the ability to forecast the direction of change.
Fuel use reduction and economic savings from optimization of road transportation of coniferous roundwood
One of the 10 priorities of the Green New Deal is sustainable transportation. It should be considered in the perspective of long-term ecological and economic sustainability, according to the trend of opportunities for sustainable development. The economic and environmental aspects of transportation related to the harvesting and movement of timber play a special role in the energy cost and their environmental impact per distance of raw material supply. The principles of rational and energy-efficient use of transportation equipment play a key role in the movement of raw timber. These are influenced by the availability of timber resources, limitation of vehicle payloads, reduction of energy consumption expressed in terms of reduction of fuel combustion, or current legal and road regulations for timber transportation. The paper evaluates economic and environmental factors in relation to the demand for fuels necessary for the implementation of road transportation of softwood timber. The aim of this paper was to present the current situation of the use of transportation means in the movement of bulky timber, as well as opportunities to optimize fuel consumption and CO2 emissions, affecting the economic and environmental effects. Previous studies on fuel consumption in the transportation of roundwood indicate irrational use of vehicles. This indicates unused payload capacity increasing energy inputs expressed in fuel consumption. It has been empirically investigated that this is the result of improperly approved transport sets adapted to the material being transported. In addition, it was shown that there is a clear correlation between the vehicle payload utilization rate and economic and environmental factors. The results of this study point to the potential to increase the use of transportation vehicles for timber transportation and reduce fuel combustion and CO2 emissions by 7–20%.
Biomass Price Prediction Based on the Example of Poland
The aim of the study was to test the applicability of forecasting in the analysis of the variability of prices and supply of wood in Poland. It relies on the autoregressive integrated model (ARIMA) that takes into account the level of cyclic, seasonal, and irregular fluctuations and the long-term trend as tools for the assessment of the predictions of the prices of selected medium-sized wood assortments. Elements of the time series were determined taking into account the cyclical character of the quarterly distribution. The data included quarterly information about the supply (amount) and prices (value) of wood sold by state forests in the years 2018–2022. The analysis was conducted for the most popular assortments: logging slash (M2, M2ZE), firewood S4, and medium-sized wood S2AP. In the period studied (years 2018–2022), the average rate of price variation was widely scattered. The average rate of price variation for the M2ZE assortment amounted to 7%. The average rate for M2 assortment was 1%, while the medium-sized S2AP assortment displayed the greatest variation of 99%. This means that between 2018 and the present, the price increased by nearly 100%. No major fluctuations were observed for the S4 assortment and its average rate of variation amounted to 0%. The analysis found seasonal variation was observed only for S4 firewood, the price of which went up each year in October, November, and December. For this reason, the forecast was made with the seasonal autoregressive integrated moving average (SARIMA) version of the model. It is difficult to forecast the price of wood due to variations in the market and the impact of global factors related to fluctuations in supply.
Predicting Post-Production Biomass Prices
This paper presents the application of prediction in the analysis of market price volatility in Polish conditions of wood processing by-products in the form of biomass. The ARIMA model, which takes into account cyclical, seasonal, irregular fluctuations of historical data on the basis of which the forecast and long-term trends of selected wood products were made, was used in predicting prices. Comparisons were made between the ARIMA prediction method and the multiplicative Winters–Holt model. During the period studied (2017–2022), the changes in the market price of biomass were characterized by a wide spread of values. On average, the price of these products increased from 2017 to the end of 2022 by 125%. The price prediction analysis showed seasonal fluctuations in the case of wood chips. The uncertainty in price prediction is due to changes in supply resulting from the influence of global factors. The Diebold–Mariano test of matching accuracy confirms that the price prediction of the analyzed by-product sorts using the ARIMA and WH models is possible. The conclusion reached by comparing these two methods is that each can be used under certain market conditions of certain assortments. In the case of a stable wood product, the choice of the ARIMA model should be resolved, while in the case of price volatile products, WH will be a better choice. The difference between the predicted and actual price with ARIMA ranged from 2.4% to 11.6% and for WH from 3.7% to 29.8%.