Preliminary Analysis on Bio-Acidification Using Coffee Torrefaction Waste and Acetic Acid on Animal Manure from a Dairy Farm

Abstract

This study investigates bio-acidification as a method to decrease the pH of animal manure in dairy farms through the application of coffee silverskin (i.e., a coffee torrefaction waste) and acetic acid. The aim was to focus on the preliminary analysis needed to assess the suitability of using this mitigation strategy. This analysis was carried out by developing a three-step methodology. The first step included the identification of the appropriate proportions of coffee silverskin and acetic acid at the laboratory scale; in the second step, the best treated proportions were analysed in field conditions to compare the statistical differences among the pH of the control and treated samples. In the third step, territorial evaluation was carried out to verify the availability of the coffee waste in the territory based on the use of a Geographic Information System (GIS). Based on the results, a reduction of 38% and 31% in pH was observed in samples treated with acetic acid and coffee silverskin at the laboratory scale and in field conditions, respectively. The territorial analysis showed that it is possible to valorise this agro-industrial waste while minimising environmental impacts due to transportation if the coffee industry is located within a 75 km distance.

1. Introduction

1.1. State of the Art

In recent years, agriculture has been responsible for about 93% of ammonia (NH₃) emissions in Europe [1]. It has been observed that countries with the relatively highest levels of economic activity and funding for agricultural research and development emit progressively more NH₃ from agriculture. Thus, it is crucial for all EU Member States to implement effective, efficient, and sustainable strategies to mitigate NH₃ emissions in order to avoid increasing the adverse effects of this phenomenon [2]. Indeed, NH₃ causes the eutrophication of aquatic ecosystems and the acidification of terrestrial ones, as well as contributes to particulate matter formation, with consequent negative impacts on human and animal health [3]. NH₃ is produced from the nitrogen excreted from animals via manure. In detail, NH₃ is released when manure is exposed to the atmosphere in livestock farms, from manure deposits, and in agricultural fields during the application of manure [4].

In this context, many research studies in the literature have investigated how emissions of pollutants and greenhouse gases can be reduced to decrease negative impacts from the livestock sector [5,6]. Mitigation strategies include animal management, such as diet and third milking [7,8,9]; barn construction, such as specialist floor designs, natural/mechanical ventilation, and the presence of green infrastructures located near livestock farms [10,11,12,13]; and barn management, such as floor cleaning techniques and the activation of cooling systems [14,15].

Acidification is one of the mitigation strategies applied in manure treatment systems [16] to decrease NH₃ emissions by reducing slurry pH value. Indeed, a low pH value limits NH₃ volatilisation by transforming it into ammonium (NH₄), which is a less volatile compound [17]. Based on the literature [18,19,20], manure acidification has been carried out using various acids, such as hydrochloric acid (HCl), sulfuric acid (H₂SO₄), nitric acid (HNO₃), and lactic acid (C₃H₆O₃). However, their use is expensive, and also risky for both human and animal health. To overcome these issues, research studies [21,22,23] have explored the use of organic acids to reduce NH₃ emissions.

Examples of bio-acidification have previously been investigated in the literature [22], analysing the impact of waste cooking oil (WCO) in addition to cattle manure on NH₃ emissions during composting. Indeed, this research demonstrated that WCO with a high lipid content modulates microbial activity and reduces compost pH value, thereby limiting NH₃ volatilisation and mitigating nitrogen losses. Furthermore, the hydrophobic nature of lipids decreases compost moisture levels, contributing to a lower emission of NH₃. Kuroda et al. [22] examined the composting of dairy cattle manure under two different aeration conditions using a laboratory-scale composting apparatus. This setup consisted of a 14-litre stainless-steel cylinder where the composting mixture was placed. In the initial experiment, the aeration rate was adjusted throughout the 20-day composting period to simulate the typical oxygen variations observed in real-world composting scenarios. The findings indicated that higher WCO additions led to increased emissions with higher aeration rates, while it reduced emissions under lower aeration conditions.

Kuroda et al. [23] conducted a pilot-scale experimental analysis of dairy cattle manure composting. The study concluded that, under low aeration conditions, the adopted method was effective in reducing NH₃ emissions in practical-scale composting.

In the study of Arcidiacono et al. [24], processing residue from the coffee industry was applied to manure together with acetic acid in a dairy barn for bio-acidification. In this study, the authors found that this application reduced approximately 50% of NH₃ emissions based on the field experiment, without experimental evidence at the laboratory scale. The choice of using coffee residue is appropriate due to its easy availability in many territories. Moreover, this material might prevent cows from slipping due to its low moisture content and capability to absorb the liquid fraction on the barn floor. Nevertheless, most of the valorisation strategies explored in the literature for coffee wastes are related to energy purposes [25]. Specifically, coffee silverskin is frequently disposed of as a unique waste, as it is the only by-product of the torrefaction process in coffee-consuming countries, and there is a lack of scientific research investigating its valorisation and sustainability characteristics [26]. Consequently, there is a need to explore alternative uses for this coffee torrefaction residue. To gain a deeper knowledge of the environmental issues related to biomass valorisation, it is important to analyse waste disposal burdens and transportation impact [27].

An analysis of the literature highlights that there is a lack of extensive experimental studies investigating bio-acidification as an alternative to the use of chemicals such as strong acids.

1.2. Aims and Objectives of the Research

This research study is a preliminary analysis aiming to assess bio-acidification for pH reduction in manure produced in dairy farming. This investigation includes the application of an agro-industrial waste on the manure, with particular attention on the availability in the investigated territory. This study’s novelty lies in the integration of a multidisciplinary research strategy involving different levels of investigation, from the laboratory to the territorial level.

Indeed, this study answers the following research questions:

RQ1: Which is the most effective proportion of coffee silverskin and acid to be applied to manure for pH reduction at the laboratory scale?

RQ2: Is the proposed mix consistent and effective as a pH-lowering agent in field conditions?

RQ3: Is the application of coffee waste environmentally sustainable in the investigated territory?

2. Materials and Methods

2.1. Research Methodology

This study applied a multi-level approach. Based on bio-acidification principles, this study explores the effectiveness of applying an agro-industrial waste. The methodology consists of three steps. The first step involves experiments to estimate the potential reduction in pH in manure in laboratory conditions. Based on the laboratory tests, the second step validates the results of the first step in field conditions, specifically in a dairy barn, by using a comparative approach between manure with and without bio-acidification treatment. The third step is a territorial assessment aimed at finding the maximum distance between coffee companies and the barn analysed in the case study for which the application of the mitigation strategy is still environmentally sustainable, compared to silverskin waste decomposition on the ground.

2.2. Materials Used for Bio-Acidification

The primary material investigated for the acidification of manure is silverskin (Figure 1) [28], a thin layer that covers the coffee bean and is separated during the roasting process. The silverskin considered in this study is derived from a roasting process that incorporates a blend of 50% robusta coffee and 50% arabica coffee species.

Based on the literature, the amounts of caffeine, caffeoylquinic acid (3-, 4-, 5-CQA), and 5-hydroxymethylfurfural (HMF) were quantified for silverskin. These amounts are expressed as follows: caffeine (g/100 g), caffeoylquinic acids (mg/100 g), and 5-hydroxymethylfurfural (mg/100 g). In detail, the obtained concentrations with related standard deviations were the following [29,30]:

Caffeine: 0.71 ± 0.02;

3-CQA: 9.44 ± 0.22;

5-CQA: 52.53 ± 0.83;

4-CQA: 17.71 ± 0.30;

HMF: 39.52 ± 1.07.

Other compounds of silverskin include acetic acid, butanoic acid, 2-/3 Methylbutanoic acid, 4-Methyloctnoic acid, and Phenylacteic acid.

Based on the principle of bio-acidification, this material contributes to reducing pH, thereby establishing a more acidic environment. Coffee silverskin was chosen for its low moisture content and stability, which allows it to keep its properties over time. It is also commonly used as a soil conditioner in agriculture due to its organic composition. In addition, its high absorbent capacity has also been utilised to reduce the risk of slipping in livestock areas. Traditionally, this waste is disposed of by incineration or composting.

2.3. Barn Selection and Description

Data on livestock farms in Sicily were acquired from the National Zootechnical Registry of the Italian Ministry of Health (IZS) ([31]) for the year 2024 (Table 1). The location of the case study was selected to be within the province of Ragusa, located in south-eastern Sicily, since this is the area with the highest density of cows, according to the IZS database (Figure 2). The selected company was a dairy farm specialising in the breeding of Frisona dairy cattle.

The experiments were carried out in the breeding environment of lactating cows, within a barn with three open sides and one side enclosed by a continuous wall with four small openings. The barn had a rectangular layout, with a length of 55.5 m and a width of 20.8 m. The gable roof was covered with fibre-reinforced concrete panels and had a ridge height of 7.0 m, sloping to 4.0 m at the eaves.

The barn breeding system was based on a free stall design, and it was subdivided into three pens, organised in different functional areas. The resting area was composed of 64 head-to-head stalls, arranged in two rows with sand bedding. The barn’s southwest side included an office and calf pens.

2.4. Laboratory Tests on Manure Samples

To achieve an effective reduction in the pH of manure, coffee silverskin was combined with a weak acid. Acetic acid, characterised by a pH of 2.4, was selected for its effectiveness in lowering the pH of manure deposited on the floors of dairy cattle barns and to facilitate the conversion of NH₃ into NH₄⁺, which is significantly less volatile than NH₃.

Based on the literature, a target pH between 4.7 and 5.5 [20,24,32,33,34] was identified as the optimal trade-off to effectively reduce NH₃ volatilisation without compromising environmental safety or animal welfare. In particular, excessively low pH levels could pose a risk to cattle hoof health.

Preliminary laboratory tests were conducted to determine the optimal proportion of weak acid and coffee silverskin required to approach the target pH while avoiding excessive acidification. Following the laboratory analyses, the strategy was implemented and tested in the field. A detailed description of the experimental procedures is provided below.

The laboratory experiments were conducted at the Agro-Chemistry Laboratory of the Department of Agriculture, Food, and Environment (Di3A) of the University of Catania. During these experiments, the pH of the manure was determined using a digital pH meter (Ehomfy, China) with an accuracy of ±0.01 pH and a measurement temperature range of 0.1 to 60 °C. Prior to each measurement session, the instrument was calibrated with standard solutions (i.e., pH of 6.86, 4.00, and 9.18). The manure samples (Figure 3), collected from the barn under investigation on the same morning as the measurements (see barn description in Section 2.3), were prepared with varying proportions of acetic acid and coffee silverskin. Prior to the start of the pH measurements, performed using a pH meter, all samples were put on a shaker with distilled water [35]. Several measurements were taken during the shaking process to observe any changes in pH at various intervals. Moreover, a shaking period of 6 h was carried out according to Santos [36], and was compared to a 5 min shaking period.

Preliminary evaluations showed no notable difference in pH between samples shaken for six hours continuously and those agitated for just five minutes. From this observation, it was concluded that the best procedure would be to shake the samples for five minutes, then let them rest for fifteen minutes before taking pH measurements.

Five samples were examined to evaluate various pH properties. One sample was utilised to measure the pH of coffee silverskin, another to determine the pH of manure, and a third one to assess the potential reduction in pH from the mixture of manure and coffee silverskin without acid. Additionally, two more samples were prepared with different amounts of acetic acid in combination with coffee silverskin and manure. The rationale behind the experimental design was to quantify the pH values of coffee silverskin and manure separately, and then to identify an optimal mixture of both silverskin and manure for acidification with a pH value close to the above-mentioned target between 4.7 and 5.5.

The pH of the samples was measured, always maintaining a ratio of 1:5 between the organic matrix and distilled water [32].

In the control sample, manure was the only constituent used. In sample 0, the unique constituent was coffee silverskin. In sample 1, a mixture of manure and silverskin was used in a 2:1 ratio. In samples 2 and 3, animal manure and silverskin were mixed in a 1:2 ratio, yet with a different acetic acid volume. In detail, in sample 2, a volume of acetic acid equivalent to 10% of the total acidity was added (to obtain a 6% concentration), and in sample 3, the amount of acetic acid was twice that of sample 2.

To ensure the statistical reliability of the results, each formulation was replicated in triplicate. The difference between the five groups of samples analysed was assessed using a one-way analysis of variance (ANOVA) with a level of significance p lower than 0.05. When the test was significant (p < 0.05), the Tukey post hoc test was carried out to identify statistical differences between groups using different letters of the alphabet. The proportions of acetic acid, coffee silverskin, and manure used in the most efficient sample, which achieved the greatest reduction in pH, were thus selected for application during the subsequent field experiments.

In addition, the dry matter of manure and silverskin was measured by placing the materials in a drying oven (Thermo Scientific Heratherm, Waltham, MA, USA) at 105 °C until a constant weight was reached, then allowing them to cool inside a closed bell jar for 2 h, and, finally, the dry weights were obtained. The ashes were determined at 505 °C in a muffle (Lab 1200C Muffle Alumina Ceramic Fiber Furnace, Livingston, MT, USA) [37]. All measurements were performed on 3 samples for control and testing.

Another investigated parameter was the total nitrogen (N), determined by digesting 2 g dry weight of silverskin with concentrated sulphuric acid, hydrogen peroxide, and selenium catalysis, as well as 0.5 g dry weight of manure, and then digesting sample 3 with sulphuric acid and selenium catalysis.

2.5. In-Field Applications

Samples were collected from an area of approximately 23 m², located in the central area of the barn (Figure 4). The selection of this location was based on the prolonged presence of the cows, which contributed to a considerable accumulation of manure.

The measurements of pH from manure were carried out in the following two conditions: the application of mitigation strategies and an undisturbed test control. To achieve this objective, the detected area of 23 m² in the feeding area was subdivided into two equal sections of 11.5 m² each, separated by steel bars:

One of the sections was dedicated to the storage of the effluents produced by the cattle, representing the control group (Control SL-A).

In the other section, both silverskin and acetic acid were spread in the feeding area according to the proportions established during the laboratory analysis, constituting the experimental group (Sample SL-B). The silverskin, manure, and acetic acid were mixed directly on field to simulate the ordinary operative conditions of the dairy barn management.

The pH of the manure was determined using a digital pH meter (Ehomfy, China), as described in Section 2.2. This was also utilised in the laboratory tests. Prior to each measurement session, the instrument was calibrated to ensure the accuracy and reliability of the results.

Six samples of manure were collected: three from the control section (1C, 2C, 3C) and three from the experimental section (1T, 2T, 3T). For each sample, ten pH measurements were taken at approximately fifteen-minute intervals.

The data acquired from the measurements were organised on a datasheet and statistical analyses were carried out. In detail, a two-way ANOVA with a level of significance p lower than 0.05 was conducted to statistically identify differences in pH between the two groups of samples (i.e., control vs. treated sample) and the number of replicates. When the test was significant (p < 0.05), the identification of statistical differences between the two groups was evaluated by applying the Tukey post hoc test.

2.6. Environmental Assessment of Silverskin Valorisation

The usual practice for coffee torrefaction waste disposal is spreading on landfills. The main problem associated with this practice is the anaerobic decomposition of the biomass, which produces greenhouse gas (GHG) emissions—mainly methane emissions. In view of a more sustainable use, coffee silverskin could instead be spread on barn floors to mitigate NH₃ emissions. The main aspect that differentiated the baseline scenario from the mitigation scenario was the silverskin transport to the barn. In this regard, weak acid was not considered since it is feasible that it could be derived from agro-industrial wastes. For instance, the feasibility of extracting acid from orange processing waste has been investigated in the scientific literature [38,39].

To analyse the environmental impact of biomass transport, the impact was compared to that of biomass spreading. To this purpose, it was necessary to quantify the coffee silverskin mass required for this mitigation strategy to be effective. Based on the daily mass required, the lorry type was selected in the database and the frequency of transportation was computed. Secondly, the methane emissions from the coffee wastes were estimated. The final step was to compute the maximum distance that could be travelled to move the biomass to the barn and compare this to the GHG emissions of waste spreading. The parameters that were identified to develop this analysis are displayed in Table 2.

The EcoInvent v 3.11 database was utilised to perform the environmental assessment of the coffee silverskin spread in the barn.

In the dairy barn analysed, the total surface involved in the coffee silverskin spreading would be 165 m², and it has to be spread with a surface density of 0.10 kg m⁻². Coffee silverskin density was measured by weighing a graduated container, and the value was found to be equal to about 70 kg m⁻³. Therefore, the coffee silverskin mass and volume that needed to be spread were calculated by Equations (1) and (2), respectively:

Mass = Sd × Stot(1)

Volume = Mass × Hd(2)

Then, a lorry of 3.5 t with a cargo body inner size of 3.32 m³ was considered for the transport activity as the minimum lorry size capable of carrying the silverskin volume required. The Ecoinvent v 3.11 database provides data on the value service of 1 tkm (tonnes × km) freight transport in a lorry of the size class of 3.5–7.5 metric tons gross vehicle weight (GVW) and Euro VI emissions class. This database item indicates a carbon emission of 0.561 kgCO₂ eq./tkm. Then, the frequency of biomass transportation by the lorry to supply the barn with the required biomass quantity was calculated using Equation (3), given that the silverskin should be spread once a day in the dairy barn:

(3)$\mathrm{F}\mathrm{r}\mathrm{e}\mathrm{q}\mathrm{u}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{y}={\displaystyle \frac{\mathrm{V}\mathrm{o}\mathrm{l}\mathrm{u}\mathrm{m}\mathrm{e}}{\mathrm{I}\mathrm{s}\times 1\mathrm{w}\mathrm{e}\mathrm{e}\mathrm{k}}}$

Since there are no specific studies about coffee silverskin, the value considered in this analysis is a mean value of the anaerobic decomposition of agricultural waste carbon emissions, equal to 0.025 kg CH₄ kg⁻¹, as provided by the IPCC 2021 report. Moreover, this report shows a value of 29.80 kgCO₂ kgCH₄⁻¹ for the CH₄ characterisation in terms of GHGs. Therefore, GHG emissions from anaerobic decomposition over a week (GHGad) were obtained using the following expression:

GHGad = Mass × ADc × Mc × Frequency(4)

Finally, the distance in km that was considered, including a return tour, for transporting one tonne of biomass to balance the GHGad was calculated as follows:

(5)$\mathrm{D}\mathrm{i}\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{c}\mathrm{e}={\displaystyle \frac{\mathrm{G}\mathrm{H}\mathrm{G}\mathrm{a}\mathrm{d}}{\mathrm{L}\mathrm{c}}}{\displaystyle \frac{1}{2}}$

To assess the local availability of this material close to the area of possible application, a territorial analysis was carried out in Sicily using a Geographic Information System (GIS). In detail, coffee availability data were acquired from the coffee Italia 2024 database (Beverford web page [40], last accessed January 2025). Information from coffee companies and the case study barn were overlapped using GIS tools to define areas where the use of coffee waste facilitated a sustainable use of resources. A network analysis was developed to identify all coffee firms at a shorter distance than that calculated using Equation (5).

3. Results

3.1. Laboratory Results

From the experiments, it was found that the treated samples had a lower pH compared to the control. In detail, there was a significant difference (p < 0.001) between the pH in the control and that in the samples. Indeed, the pH of samples had a mean value and standard deviation (SD) of 5.81 ± 0.75, with a reduction of about 24% compared to the pH of the control. The results of the laboratory tests carried out on the different samples and control are reported in Table 3. The results showed that the treatments reduced the pH compared to that of the control. Based on the one-way ANOVA, there was a significant difference between the pH of the samples analysed, with p < 0.001. The Tukey post hoc test showed that both the control and treated samples represented groups with a different statistical significance. The pH of sample 0 (only coffee silverskin) was on average 6.14 ± 0.01, while the pH of the control (only manure) was on average 7.62 ± 0.01. Sample 1, consisting of manure and coffee silverskin without acid, was observed to reduce the pH of the manure to 6.65 ± 0.03. The performance of the samples improved with increasing quantities of acetic acid.

Sample 3 was the most effective in pH reduction, achieving the lowest pH value of approximately 4.74 ± 0.33. This outcome was more effective than sample 2 with a pH of approximately 5.70 ± 0.05.

Based on the analyses performed at the laboratory scale, the sample 3 treatment was the most effective in achieving the fixed target (between 4.7 and 5.5) and, consequently, it was the one utilised during the field application. In detail, the pH of sample 3 showed a reduction of 38% compared to the pH of the control.

Other preliminary analyses were related to the measurements of N in the manure and in sample 3, as shown in Table 4.

The results show comparable levels of N in both silverskin and manure, and consequently the mix of the two in sample 3 after the acidification. In this regard, it is important to highlight that the N content in silverskin might not be directly related to NH₃ volatilisation. However, its N content allows the use of silverskin as a soil amendment.

The determination of dry matter and moisture content in Table 5 demonstrated the potential for the practical application of silverskin in the barn to prevent animals from slipping.

3.2. In-Field Applications

Based on the two-way ANOVA, there was a significant influence of the sample (p < 0.001), the number of repetitions (p < 0.001), and the interaction between the sample and the number of repetitions (p < 0.001) on the pH analysed. In detail, Figure 5 shows the influence of the interaction between samples (i.e., control and test) and repetitions (i.e., three) on the pH. The pH of manure had a reduction of about 31% after the treatment. The results showed that the pH values in the sample and control were 5.74 ± 0.37 and 8.30 ± 0.19, respectively. In addition, the boxplot in Figure 6 shows that the pH in the manure after the treatment was reduced from the first to the third measurements, together with a reduction in the standard deviation.

The comparison between the field and laboratory pH data shows that the values reduced on average (8.30 vs. 7.62 for control, and 5.74 vs. 4.74 for test) due to the time interval needed to transport the samples, thus suggesting how transportation influences pH.

As a consequence, the effect of pH reduction is higher in laboratory than in field conditions. The results from the in-field measurements show that the pH increased at a slow rate (about 0.5 after more than 2 h), proving that acidification was effective (Figure 7).

4. Territorial Level

Following the proposed methodology, the total silverskin weight and volume needed in a week, computed according to Equations (1) and (2), were mass = 115.5 kg and volume = 1.65 m³.

If we assume the means of transport is a lorry of a size of 3.5 t with a cargo body inner size of 3.32 m³, it could bring the necessary material for 2 weeks (Equation (3)). The total silverskin weight for 2 weeks is 131 kg.

The anaerobic decomposition of 2 weeks of coffee silverskin would result in carbon emissions with GHGad = 172.1 kgCO₂ eq, according to Equation (4).

According to Equation (5), a distance of 75 km was thus estimated by considering lorry emissions, balancing the environmental impact of methane emissions due to coffee waste decomposition on the ground without undergoing further treatment.

Figure 8 highlights the results of the GIS-based network analysis, showing those coffee firms (in green) at a distance lower than 75 km from the barn, which would fulfil the environmental sustainability criterion for the application of coffee residues in the considered barn.

5. Discussion

Silverskin is a residue from the coffee torrefaction process that is usually disposed as a waste in most coffee-consuming countries. This study investigated the opportunity to mix it with manure to mitigate the NH₃ concentration in livestock barns. Silverskin’s absorbing capacity proved to be a key advantage for the scope of this experiment, as it mitigates the risk of cow slippage on barn floors, where livestock are housed [41]. In addition to these features, silverskin is well known for its stability and low moisture content, which enable it to maintain its properties over extended periods, even upon desiccation. Another critical factor in selecting this material was its local availability, which facilitated collection and transport to the experimental site situated in south-eastern Sicily. Preliminary analyses indicated that the composition of sample 3 was the most effective in significantly reducing the pH of manure in laboratory conditions. In-field results confirmed that the chosen treatment proportion was suitable for reducing the pH of manure on the floor, with a final value of 5.74, which closely aligned with the intended target. The present study achieved the same target pH value of 5.5 observed by Kavanagh et al. [20], who investigated the effects of various chemical treatments on GHGs and NH₃ produced from cattle and swine manure at a dairy farm in Ireland. In this research, conducted in temperature-controlled chambers, several chemical additives were tested, including sulfuric acid (H₂SO₄), acetic acid, alum, and ferric chloride, highlighting the role of acidification in mitigating NH₃ emissions. The effectiveness of this strategy was further confirmed by the study of Park et al. [32], who evaluated the application of sulfuric acid during the storage and application phases of pig manure. The results demonstrated that lowering the pH to 5.5 significantly reduced NH₃ volatilisation, thus contributing to a more sustainable management of livestock effluents. Similarly, Sommer et al. [33] applied sulfuric acid to acidify liquid bovine manure, achieving a pH of 5.5. Therefore, the positive outcomes suggest that the tested treatment proportion could provide a solid foundation for future applications to assess the effect of bio-acidification on NH₃ emissions.

The collected evidence supports the idea that acidification is a useful method for managing NH₃ emissions in the livestock industry, as confirmed in a recent meta-analysis [42]. Nevertheless, conventional acidification methods depend entirely on adding chemical acids to decrease pH levels, whereas bio-acidification differentiates itself by using bio-acidifiers, which are natural and environmentally friendly substances. In contrast to chemical acidification, which could threaten the environment and soil health, bio-acidification permits the safe use of manure as a fertiliser without the degradation of soil quality.

Furthermore, the proposed solution to utilise coffee residues is embedded within a novel sustainable production cycle. The baseline scenario for the management of coffee waste is usually the spreading on landfills. The scenario proposed in the present study was to use silverskin as an NH₃ mitigation strategy. The aim of the sustainability assessment was to determine whether the proposed scenario decreased the environmental impact compared to the baseline scenario. This approach highlights how a by-product that could otherwise be considered waste can be repurposed within an alternative production process. The valorisation of agro-industrial wastes to reduce pollutant emissions is beneficial both for the dairy industry and for agro-industrial production. Indeed, mitigation strategies based on bio-acidification can reduce the environmental impacts of agro-industrial products by minimising waste disposal impacts. In this study, the sustainability of the proposed scenario was ascertained by equalling the environmental impact of the natural anaerobic decomposition of coffee waste to the environmental impact of waste transportation, thus achieving the maximum feasible distance of coffee industries from the barn.

In relation to the utilisation of acetic acid, the authors are conducting research on the utilisation of alternative, more sustainable bio-acidifiers. The most promising approach would be to obtain an acid from other very abundant agricultural, agro-industrial, or food wastes, as assessed by some authors [38,39]. For instance, in the region investigated, weak acids could be derived from the citrus residues of juice and marmalade production [43,44].

A proposed solution to be further investigated from a circular bioeconomy perspective would be the anaerobic digestion of the bio-acidified manure. In fact, technical and environmental analyses have been undertaken to study the anaerobic digestion potential of coffee waste [36]. The LCA-based study by De Oliveira Fernandes et al. [45], performed to compare the environmental impact of landfill practice with anaerobic digestion in a controlled industrial plant for energy production, showed that producing energy from the anaerobic digestion of coffee waste and then using the digestate as compost can reduce the environmental impact of this coffee biomass from 707.77 kgCO₂eq t⁻¹ to 22.35 kgCO₂eq t⁻¹. As anaerobic digestion is also a promising valorisation strategy for dairy cattle manure [46,47], the mixture of manure and coffee waste—after their application on site—could be conveyed to an anaerobic digestor in order to produce energy from alternative resources.

Moreover, the proposed methodology for calculating the maximum distance of agro-industrial firms from the barn can also be replicated for other biomass valorisation strategies. This approach would facilitate a more comprehensive investigation of transport in environmental impact analyses, thereby enhancing our ability to evaluate the ecological consequences of transportation-related activities. This methodology would offer a comprehensive strategy for addressing environmental impacts, including but not limited to acidification, Global Warming Potential (GWP), and cumulative energy demand.

6. Conclusions

In this study, preliminary analyses on the effectiveness and environmental impact of a novel bio-acidification treatment for manure were carried out by applying a multi-level approach that could be applied for any mitigation strategy. Indeed, the effects of using acetic acid and coffee residues for manure bio-acidification were examined, revealing a substantial reduction in pH in both laboratory and in-field conditions. In addition, preliminary territorial analyses also proved the feasibility of the sustainable reuse of coffee residues within a threshold distance from the barn. In light of these findings, this research could represent a promising solution for manure treatment on cattle barn floors, despite requiring further investigation in various directions, such as the sustainable production of acidifiers from agricultural wastes. Moreover, the positive outcomes regarding the use of silverskin to reduce pH in manure suggest that the next steps of this research should focus on the monitoring of gas concentrations under different climatic conditions, utilising the proposed mitigation strategy applied to livestock facilities. Future research could also investigate the methanogenic potential of the resulting product, assessing its applicability in anaerobic digesters and facilitating further resource recovery. Further research could also explore the potential use of the treated effluents, for instance, in biogas production, thereby contributing to renewable energy generation.

Author Contributions

G.C. (Grazia Cinardi) and S.V. contributed equally to this paper. Conceptualization, G.C. (Grazia Cinardi), S.V. and P.R.D.; methodology: G.C. (Grazia Cinardi), S.V. and P.R.D.; validation, C.A., A.B. and G.C. (Giovanni Cascone); formal analysis: G.C. (Grazia Cinardi), S.V., P.R.D. and C.A.; investigation: G.C. (Grazia Cinardi), S.V., P.R.D., L.M.S., A.F., G.C. (Giovanni Cascone), F.F. and E.L.B.; resources, C.A.; data curation: G.C. (Grazia Cinardi), S.V. and P.R.D.; writing—original draft preparation, G.C. (Grazia Cinardi), S.V. and P.R.D.; writing—review and editing, P.R.D., C.A., A.B. and G.C. (Giovanni Cascone); visualization, G.C. (Grazia Cinardi), S.V. and P.R.D.; supervision, C.A., A.B. and G.C. (Giovanni Cascone); project administration, C.A.; funding acquisition, C.A. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Data will be available on request.

Acknowledgments

The authors would like to express their gratitude to the farm Alpa s.r.l. for the opportunity to carry out the experiments.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

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Figures and Tables

Figure 1 Structure of a coffee drupe.

Figure 2 Location of the case study.

Figure 3 Example of manure samples and laboratory setting.

Figure 4 Schemes of the area utilised for silverskin spreading and manure sampling.

Figure 5 Interaction plot between sample and repetitions, considering impact on pH. In detail, the figure showed field conditions where sample 3 treatment was applied.

Figure 6 Boxplot of the comparison between pH of control and sample: In detail, the figure showed field conditions where sample 3 treatment was applied.

Figure 7 Durability of the acidification effect.

Figure 8 GIS-based network analysis of the coffee firms around the case study barn.

Table 1

Consistency of livestock farming in Sicily (source: National Zootechnical Registry of the Italian Ministry of Health). Data are related to cows for milk and meat production.

Province	Number ofLivestock Farms	Number of Cows	Livestock Farm Density	Cow Density
Agrigento	418	8846	0.1374	2.9081
Caltanissetta	224	7166	0.1053	3.3672
Catania	750	28,191	0.2111	7.9362
Enna	1321	39,913	0.5156	15.5781
Messina	2334	43,957	0.7187	13.5363
Palermo	2507	72,992	0.5022	14.6211
Ragusa	1537	75,443	0.9523	46.7423
Syracuse	882	31,275	0.4182	14.8307
Trapani	228	3965	0.0893	1.5532
Total	10,201	311,748	0.3954	12.0834

Table 2

Parameters utilised for environmental assessment.

Parameters	Symbol	Values	Source
Total surface	Stot	165 m2	Measured
Surface density	Sd	0.10 kg × m−2	Calculated
Coffee silverskin density	Hd	70 kg × m−3	Measured
Lorry inner size	Is	3.32 m3	https://www.tkingauto.com/medium-duty-truck/3-5-ton-medium-truck.html (accessed on 14 February 2025)
Lorry carbon emission	Lc	0.561 kgCO₂eq.× tkm−1	EcoInvent v3.11
Anaerobic decomposition of agricultural waste carbon emission	ADc	0.025 kgCH4 × kg−1	IPCC 2021
Methane characterisation as GHG	Mc	29.80 kgCO2 × kgCH4−1	IPCC 2021

Table 3

Results of the one-way ANOVA (p < 0.001) for pH values of experimental samples analysed in laboratory conditions. Samples that do not share a letter in the Tukey post hoc test are significantly different.

Sample	Mean of pH Value	SD	Tukey Post Hoc Test
Control	7.62	0.01	A
Sample 0	6.14	0.01	C
Sample 1	6.65	0.03	B
Sample 2	5.70	0.05	D
Sample 3	4.74	0.33	E

Table 4

Laboratory results regarding nitrogen (N) measurements.

Sample	% Total N	SD%
Silverskin	2.88	±0.13
Manure	2.02	±0.21
Sample 3	2.74	±0.16

Table 5

Moisture content, dry matter, and organic dry matter of manure and sample 3.

Sample	Moisture Content %	Dry Matter %	Organic Dry Matter %
Manure	84.28	15.72	72.7
Silverskin	5.21	94.79	90.6

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