Efficiency of Shaping the Value Chain in the Area of the Use of Raw Materials in Agro-Biorefinery in Sustainable Development
Abstract
:1. Introduction
- Refineries from whole crops—the substrate is the whole plant, e.g., oil refinery, in which oilseeds (rapeseed, sunflower, soybeans) are used;
- ‘green’ refineries with inedible ‘green’ parts of plants or whole energy crops (e.g., wet biomass, green grass, alfalfa, clover, unripe grain, unsuitable for agriculture, and food industry plants or their parts);
- Lignocellulosic refineries, based on lignocellulosic biomass (e.g., straw, forestry waste, wood, paper);
- Two-platform refineries (producing syngas and sugars in one product in the first technology platform with simultaneous fuel production in the second platform), based on renewable raw materials (waste from agriculture, forestry, food industry, biodegradable municipal waste).
- Biomass from crop production.
- Biodegradable waste products of plant or animal origin.
- Dedicated plants grown for energy purposes.
2. Analysis of the Processes That Make up Value Chains in an Agricultural Biorefinery
2.1. Supplying Raw Materials (Input)
2.2. Refining (Pre-Treatment and Biomass Conversion)
2.3. Selling Conversion Products (Output)
3. Sustainable Development Determinants in Biomass Processing
4. Resource Assessment (Waste Valorization)
5. Social Significance of Agro-Biorefinery Development
6. Environmental Assessment of Biomass Refineries
- Waste management.
- Use of targeted biomass.
- Use of surplus biomass.
- Reduction of greenhouse gas emissions.
- Reduction of acidifying impurities.
- Use of products resulting from biorefining.
- CLM method—a method of intermediate points, in which the following indicators are used: depletion of abiotic resources (ADP), global warming potential (GWP), reduction of stratospheric ozone resources (ODP), soil toxicity potential, soil acidification (AP), eutrophication potential, and resource perceptibility potential (OTV).
- Umberto program—allows for analyzing the energy and materials flow in companies, production installations, or facilities, calculating operating costs and lifecycle, choosing an ecologically optimal version of the product, etc.
- SimaPro program—uses the eco-indicator method for assessing the damage caused to the environment by the adverse impact of a process or product.
7. Value Chain Efficiency
7.1. Logistic Efficiency of Biomass
- Staryfy(d. s)—the cost of transport according to the basic tariff for a given vehicle s and distance d.
- ks/km—rate in PLN/km for vehicle s.
- upowr—negotiated discount of the return fee.
- Ks post—additional fee for parking after exceeding 4 h of driving (we assume that it will be added for each subsequent 250 km of the route).
- Ks difficulties—additional fee for difficulties specific to a given route (driving through large cities, poor road conditions).
7.2. Biomass Energy Efficiency
7.3. Environmental Efficiency
7.4. Economic Efficiency of Biorefineries
8. Conclusions
- The processing of biomass in agro-biorefineries achieves environmental, social, and economic objectives;
- A rational supply chain makes it possible to exploit the potential of biomass and adapt transport to the type of biomass, cargo volume, cargo weight, distance, and travel costs. It also has a positive effect on reducing CO2 emissions during transport;
- A favorable amount of energy produced from biomass can be obtained, as exemplified by the studies of Witaszek, Pilarska, and Pilarski [42] that included the pre-treatment analyses. By selecting the biomass share appropriately, a much higher profitability of the treatment used can be achieved;
- Based on an environmental performance analysis, the optimal biorefinery technology can be selected, mainly being regionally diverse, taking into account the sustainable availability of raw materials, and the environmental impacts identification. The environmental impact of a biorefining investment can also be estimated, including the level of reductions in emissions of methane, carbon dioxide, nitrogen oxides, sulfur oxides, and dust;
- Studies have shown that, for example, the annual revenue from biogas production in a biogas plant with a capacity of 0.5 MW and production of approx. 4000 MWh may amount to almost PLN 3 million (EUR 0.6 million).
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
RM | Road map |
FIT455 | Program EU “Fit for Fifthy Five” |
GreenDeal | Program EU for Climate Saving |
RES | Renewable Energy Sources |
LCA | Life Cycle Assessment |
ADP | Depletion of abiotic resources |
GWP | Global warming potential |
AP | Soil acidification |
LCC | Lifecycle cost calculation |
eLCC | Environmental lifecycle cost calculation |
sLCC | Social lifecycle cost calculation |
ODP | Stratospheric ozone resources |
OTV | Resource perceptibility potential |
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Index | Statistical Code/Field | Description |
---|---|---|
sAll | Averaging period | The basic data averaging period at a measurement site. The results of measurements are averaged in the form of annual series in accordance with that period. |
All | Average | The average annual concentration. |
SO2 | L 350 (S1) | The number of hours in a calendar year when the average 1 h concentration exceeded 350 µg/m3 (rounded to an integer). |
SO2 | L 125 (S24) | The number of hours in a calendar year when the average 24-h concentration exceeded 125 µg/m3 (rounded to an integer). |
NO2 | L 200 (S1) | The number of hours in a calendar year when the average 24-h concentration exceeded 200 µg/m3 (rounded to an integer). |
NO2 | 19th max. (S1) | The 19th maximum value in an annual series of results—1 h averages, in [µg/m3]. |
PM10 | L 50 (S24) | The number of hours in a calendar year when the average 24-h concentration exceeded 50 µg/m3 (rounded to an integer). |
PM10 | Max. (S24) | The maximum average 24 h concentration in a year. |
Distance above Threshold 2 | Cargo Volume 15 m3 Load Weight 7 t * | Cargo Volume 15 m3 Load Weight 14 t * | Cargo Volume 80 m3 Load Weight 24 t ** | Cargo Volume 80 m3 Load Weight 38 t ** | ||||
---|---|---|---|---|---|---|---|---|
Rate over Threshold 2 (1.9 pln/km) | Increase % | Rate over Threshold 2 (0.68 pln/km) | Increase % | Rate over Threshold 2 (3.3 pln/km) | Increase % | Rate above Threshold 2 (1.13 pln/km) | Increase % | |
5 | 64.50 | 17 | 58.40 | 6 | 716.50 | 2 | 705.65 | 1 |
10 | 74.00 | 35 | 61.80 | 12 | 733.00 | 5 | 711.30 | 2 |
20 | 93.00 | 69 | 68.60 | 25 | 766.00 | 9 | 722.60 | 3 |
40 | 131.00 | 138 | 82.20 | 49 | 832.00 | 19 | 745.20 | 6 |
60 | 169.00 | 207 | 95.80 | 74 | 898.00 | 28 | 767.80 | 10 |
80 | 207.00 | 276 | 109.40 | 99 | 964.00 | 38 | 790.40 | 13 |
100 | 245.00 | 345 | 123.00 | 124 | 1030.00 | 47 | 813.00 | 16 |
120 | 283.00 | 415 | 136.60 | 148 | 1096.00 | 57 | 835.60 | 19 |
140 | 321.00 | 484 | 150.20 | 173 | 1162.00 | 66 | 858.20 | 23 |
160 | 359.00 | 553 | 163.80 | 198 | 1228.00 | 75 | 880.80 | 26 |
180 | 397.00 | 622 | 177.40 | 223 | 1294.00 | 85 | 903.40 | 29 |
200 | 435.00 | 691 | 191.00 | 247 | 1360.00 | 94 | 926.00 | 32 |
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Bartkowiak, A.; Bartkowiak, P.; Kinelski, G. Efficiency of Shaping the Value Chain in the Area of the Use of Raw Materials in Agro-Biorefinery in Sustainable Development. Energies 2022, 15, 6260. https://doi.org/10.3390/en15176260
Bartkowiak A, Bartkowiak P, Kinelski G. Efficiency of Shaping the Value Chain in the Area of the Use of Raw Materials in Agro-Biorefinery in Sustainable Development. Energies. 2022; 15(17):6260. https://doi.org/10.3390/en15176260
Chicago/Turabian StyleBartkowiak, Anna, Piotr Bartkowiak, and Grzegorz Kinelski. 2022. "Efficiency of Shaping the Value Chain in the Area of the Use of Raw Materials in Agro-Biorefinery in Sustainable Development" Energies 15, no. 17: 6260. https://doi.org/10.3390/en15176260