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Maffia et al. Carbon Footprints 2026, 5, 7 Page 7 of 19

ton of fertilizer. A cradle-to-gate approach was applied, which considered the environmental impacts from
raw material extraction up to the factory gate. The system boundaries were divided into three modules:
upstream, core, and downstream. The upstream module included the production of raw materials for the
fertilizers. The core module comprised transportation, production processes (dosing, homogenization,
granulation, drying), and related emissions. The downstream module covered the use phase, in which
emissions to air and water following fertilizer application were calculated. The functional unit (F.U.) was set
as 1 ton of fertilizer.

II. Inventory Analysis (LCI): Data were collected for all inputs and outputs related to the production of one
ton of fertilizer. Primary data from field measurements were used for the core module, while upstream
processes were modeled using the Ecoinvent 3.9 database, complemented with supply chain information.
Emissions during the downstream phase were estimated following PCR 2010:20 (EPD, 2010). For waste
management in the core module, the scenario followed Legislative Decree 152/2006, distinguishing between
recovery and disposal operations. During composting and related processes, gaseous emissions such as CO ,
2
CH , and N O were considered, representing the main GHGs. As reported in previous studies [41-44] .
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III. Impact Assessment (LCIA): The environmental impact assessment was carried out using SimaPro v.9.01
software (PRé Consultants, 2015). In this study, only the GWP (100 years) was considered, since it directly
quantifies the CFP of fertilizers. This category integrates the contributions of CO , CH , and N O emissions,
2
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allowing their comparison on a common basis (kg CO eq).
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IV. Interpretation: The characterization of emissions enabled the quantification of the CFP for each fertilizer
treatment. No normalization or weighting procedures were applied, as the analysis focused exclusively on the
GWP indicator.

Statistical analysis
All statistical analyses were performed using JMP software (version 14, SAS Institute Inc., Cary, NC, USA).
Analysis of variance (ANOVA) was used for all datasets, and one-way ANOVA followed by Tukey’s
Honestly Significant Difference (HSD) post hoc test was applied to evaluate differences among treatments.
Student’s t-test was used where appropriate. The effects were considered significant at P ≤ 0.05. Principal
Component Analysis (PCA) was used to analyze the relationships among fertilizer treatments and
environmental impact analysis.

RESULTS
The degree of humification of different fertilizers can be estimated using the HA/FA ratio [Table 1]. A higher
HA/FA ratio corresponds to a greater degree of humification of organic material, and this is further
supported by the calculated humification indices.

Among the tested materials, compost and vermicompost showed the highest HA/FA ratio. Compost showed
the greatest values of HI and HD, while vermicompost had the highest HR. Vermicompost contained the
largest amount of TOC and TEC. The E4/E6 spectral ratio, which reflects the aromaticity and condensation
of organic matter and is indicative of molecular size, also varied across the treatments. The lowest E4/E6
ratio - signifying the highest degree of organic matter polymerization - was observed in compost, while the
highest ratio was detected in digestate, which also contained substantial amounts of water-soluble phenols.
SBO contained a small amount of TOC and TEC, and did not contain humified material. Soil analysis
showed that, compared to the initial soil, untreated soil maintained the same pH, whereas pH decreased with
all treatments, with the greatest reduction observed in the presence of SBO. Conversely, EC increased relative
to the initial soil state, with the largest increase observed for compost and digestate. Water Content, Water