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robustness of the findings is evaluated through a Monte Carlo uncertainty analysis that quantifies the
influence on the results of variability in key parameters.

METHODS

Feedstock availability
To promote solutions and industrial networks within the same sector, thereby limiting issues for resource
competition with cross-sectoral interactions, this analysis focuses exclusively on the two most abundant
biomass feedstocks identified within the olive oil agro-industry in Andalusia: EOP and OP residues. EOP is a
by-product of the pomace oil extraction process, generating about 1.52 Mt annually . Currently, 83% of this
[19]
EOP is used for thermal and electric purposes, and the rest is self-consumed (9%) or sold (8%). Our analysis
assumes the entire amount of EOP (dry basis) is available for biochar production, instead of being used for
energy production. In our integrated approach, introduction of AVS can compensate for the potential loss of
renewable electricity generation, thereby enabling the simultaneous exploration of carbon sequestration
benefits from biochar together with new renewable energy generation from AVS.

OP residues represent a larger potential residue stream of about 2.62 Mt annually. However, the dominant
current practice (> 80%) is to shred this biomass and leave it into the soil, a method that aims to provide
nutrients to the olive groves . Our scenario analysis explores cases with and without the use of OP for
[19]
biochar production. When OP are used, a conservative collection rate of 30% (of the 80% fraction, i.e.,
0.63 Mt) is considered to minimize disruption to the existing management practice and reduce the logistical
challenges of collecting low-density biomass across more dispersed groves .
[39]
Scenario definition
A reference system (baseline) and five alternative scenarios (S1-S5) are considered [Figure 1]. The baseline
represents current system practices, where EOP is used in biomass power plants for energy generation and
OP are largely left on the field. The first scenario (S1) introduces an alternative use for EOP, converting the
EOP to biochar via a pyrolysis system. Scenario 2 (S2) combines S1 with a low deployment of AVS, i.e., on
50% of the identified suitable areas (see description below). Scenario 3 (S3) increases biochar production by
adding pruning residues (EOP + 30% OP), and it is still combined with a low deployment of AVS. Scenario 4
(S4) considers the implementation of AVS as a standalone strategy as an addition to the baseline system,
using a high deployment level (100% of suitable area) with no biochar production. Finally, Scenario 5 (S5)
combines a large-scale implementation of both biochar (EOP + 30% OP) and AVS (high deployment).

Life cycle assessment (LCA)
The environmental performance of the proposed scenarios was evaluated using an LCA approach. The
assessment system boundary covers agricultural operations, grouped into fertilizing, herbicide application,
irrigation, and farming activities, where the latter encompasses pruning and harvesting processing, and soil
management. It also includes biomass logistics and conversion, including EOP extraction and the pyrolysis
plant, alongside the AVS infrastructure covering PV manufacturing and installation.

The analysis investigates several environmental impact categories. Climate change (GWP100) was assessed
alongside terrestrial acidification (TAP), freshwater and marine eutrophication (FEP, MEP), particulate
matter formation (PMFP), and terrestrial ecotoxicity (TETP) using the ReCiPe 2016 v1.03, midpoint (H)
method . Human toxicity was assessed using USEtox v2.13 . Given the variety of products and the
[41]
[40]
complexity of the scenarios, the results are shown by year, representing the regional management of the
1.53 million hectares of olive groves. Supplementary Tables 1-4 provide detailed life cycle inventories (LCI).