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Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Climate, Infrastructure and Environment Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. November 6th, 2025 Zaragoza, Spain Mapping forest and agricultural biomass and assessment for solar-powered biorefineries in the Mediterranean region Erico Kutchartt, Neus Puy, Núria Aquilué PYSOLO –Stakeholder Event
www.pysolo.eu Stakeholder Event, Erico Kutchartt, 06.11.2025 2 Methodology to quantify biomass types and identify optimal biorefinery locations through different criteria •Quantify forest aboveground biomass (AGB) in areas with high potential direct normal irradiation (DNI) across Spain, Italy, and Greece. •Classify forest AGB into three main species groups:pines, oaks, and other species. •Identify optimal locations for the storage and processing of forest AGB. Forest Biomass Residual Agricultural Biomass •Identify the two main crop types in the Mediterranean region:vineyards and olive groves. •Determine crop yield by province and region and quantify residual biomass from grape pomace and olive mill waste. •Identify optimal locations to deposit both residual agricultural biomass.
www.pysolo.eu Stakeholder Event, Erico Kutchartt, 06.11.2025 3 Forest Biomass DNI (kWh·m -2 ) Level >2500 6 - Very high 2000 – 2500 5 –High 1700 – 2000 4 -Medium-heigh 1300 – 1700 3 –Medium 1000 – 1300 2 -Medium-low <1000 1 –Low Pirotti et al. 2023 ESMAP, 2019 The forest AGB is mainly distributed in areas with relatively low DNI values. Therefore, DNI was integrated in alater stage. First, it was essential to account for spatial restrictions,followed by a multi-criteria analysis to calculate the suitability index (SI) values.
www.pysolo.eu Stakeholder Event, Erico Kutchartt, 06.11.2025 4 What restrictions were identified to establish asolar-powered biorefinery plant? Vegetational (Environmental) -Operational (Accessibility) The three main restrictions were based on: • Avoid forest degradation • Skip biomass extractions in protected areas • Reduce forest operational costs Kutchartt et al. under review
www.pysolo.eu Stakeholder Event, Erico Kutchartt, 06.11.2025 5 Results from the MCA based on normalized values [0 – 1] Scenario 2 Scenario 5
www.pysolo.eu Stakeholder Event, Erico Kutchartt, 06.11.2025 6 To determine the optimal localization, we used the simulate annealing algorithm City Potential Biomass (106Mg) Effective Biomass (106 Mg) Proximal Biomass (106 Mg) Without Natura 2000 (106Mg) Algeciras 18.8 11.7 (62.1%) 1.08 (5.8%) 0.01 (0.1%) Leon 85.2 41.1 (48.2%) 2.33 (2.7%) 1.66 (1.9%) Logroño 99.7 69.6 (69.8%) 24.3 (24.4%) 11.4 (11.5%) Madrid 13.9 10.2 (73.8%) 3.07 (22.1%) 0.16 (1.2%) Mataro 60.7 37.3 (61.5%) 8.02 (13.2%) 4.29 (7.1%) Ourense 131 59.7 (45.6%) 3.52 (2.7) 3.30 (2.5%) Kutchartt et al. under review The cost-function was based on: • Suitability areas (MCA) • Road network (OpenStreetMap) • Direct normal irradiation (DNI – WB)
www.pysolo.eu Stakeholder Event, Erico Kutchartt, 06.11.2025 7 Biomass proximity (Mg) by tree species -Spain Biomass proximity considered only the biomass (Mg) within a100 km radius of the optimal hub and was very important to mask the areas that overlap Natura 2000 protected areas. Proximal Biomass Without Natura 2000 City Pines Oaks Others Pines Oaks Others Algeciras 561.6 518.4 07.6 2.9 0 Leon 1,980.5 93.2 256.3 1,427.6 83.0 149.4 Logrono 10,206.0 6,804.0 7,290.0 5,700.0 2,964.0 2,736.0 Madrid 2,732.3 337.7 097.2 64.8 0 Mataro 1,924.8 5,694.2 401.0 1,458.6 2,659.8 171.6 Ourense 2,921.6 105.6 492.8 2,739.0 99.0 462.0
www.pysolo.eu Stakeholder Event, Erico Kutchartt, 06.11.2025 8 Residual Agricultural Biomass Residual agricultural biomass was quantified using the CORINE Land Cover map and crop yield data (kg/ha) at the provincial and regional scales. Region Rainfed (kg/ha) Irrigated (kg/ha) Total rainfed (Mg) Total irrigated (Mg) Castilla –La Mancha 3,939 14,079 1,727,749 6,176,061 Extremadura 3,955 10,865 298,782 820,801 Castile and Leon 3,862 6,782 282,070 495,340 Valencian Community 4,968 7,802 321,559 504,952 Catalonia 6,435 9,658 370,180 555,586 La Rioja 5,790 7,970 275,924 379,812 Aragon 2,666 6,773 93,020 236,319 Region of Murcia 2,720 6,490 80,610 192,338 Andalusia 4,956 6,782 130,773 178,949 Galicia 6,928 - 149,284 - Navarra 5,355 6,552 100,223 122,625 Basque Country 5,890 8,572 83,603 121,672 Madrid 1,397 3,340 12,635 30,209
www.pysolo.eu Stakeholder Event, Erico Kutchartt, 06.11.2025 9 Vineyards – 21% Region Res. Rain. (Mg) Res. Irr. (Mg) Castilla –La Mancha 362,827 1,296,973 Extremadura 62,744 172,368 Castile and Leon 59,235 104,021 Valencian Community 67,527 106,040 Catalonia 77,738 116,673 La Rioja 57,944 79,761 Aragon 19,534 49,627 Region of Murcia 16,928 40,391 Andalusia 27,462 37,579 Galicia 31,350 - Navarra 21,047 25,751 Basque Country 17,557 25,551 Madrid 2,653 6,344 Potential Residue after wine production in Spain In wine production, about 21%of the grapes become pomace. However, the table on the right only estimates potential residues from wine production, assuming all vineyards identified in the CORINE land cover produce wine.
