APPLICATION AND ENHANCEMENT OF LIFE CYCLE ASSESSMENT AND WATER FOOTPRINT APPROACHES TO AGRICULTURAL MACHINERY AND CULTIVATION

La sostenibilit\ue0 ambientale delle produzioni agricole ha riscosso ampio interesse in tutto il mondo. Per la comunit\ue0 scientifica, comprendere i sistemi produttivi agricoli nell\u2019ottica dell\u2019impatto ambientale, che consente di realizzare analisi con una prospettiva olistica, e quantificare i benefici ambientali derivanti dalla selezione di una serie di operazioni o un'altra, comporta la possibilit\ue0 di identificare e suggerire l'introduzione di miglioramenti vantaggiosi per la societ\ue0 e le generazioni future. Questa Tesi di Dottorato \ue8 stata finalizzata a studiare come rendere adeguatamente affidabili gli inventari per le valutazioni di sostenibilit\ue0 ambientale relativi ai sistemi produttivi agricoli in cui si utilizzano macchine agricole per le operazioni di campo. Per esse, le caratteristiche locali pedo-climatiche e organizzativo-produttive influenzano considerevolmente i dati di inventario e, di conseguenza, i risultati degli studi di sostenibilit\ue0 ambientale, qui realizzati secondo la metodologia del Life Cycle Assessment (LCA). Nel dettaglio, utilizzando l\u2019LCA, nella Tesi sono stati quantificati gli impatti ambientali delle operazioni agricole di campo per la preparazione del letto di semina (lavorazione del terreno primaria e secondaria) e per la distribuzione di fertilizzanti organici; ci\uf2 \ue8 stato fatto studiando l'uso di diverse macchine operatrici in diverse condizioni di lavoro. Di conseguenza, si \ue8 evidenziato quanto possono essere diversi i risultati di impatto ambientale relativi alla medesima operazione, ma ottenuti utilizzando dati di inventario riguardanti condizioni di lavoro \u201cmedie\u201d che vengono adottati acriticamente. Ci\uf2 \ue8 necessario per rendere consapevoli i decisori politici e tutte le parti interessate dell'importanza di evitare semplificazioni eccessive e informazioni generiche. Le diverse operazioni che sono state studiate, rappresentative per il contesto produttivo della Pianura Padana, sono state analizzate con ENVIAM (ENVironmental Inventory of Agricultural Machinery operations). ENVIAM \ue8 un foglio di calcolo sviluppato per quantificare i dati di inventario delle operazioni agricole considerando le variabili di tipo meccanico di trattori e macchine operatrici, le scelte sulla tipologia di accoppiamento tra gli stessi, la ripartizione dei tempi di lavoro e le variabili pedo-climatiche locali. I risultati ottenuti dalla relativa valutazione di impatto ambientale hanno mostrato delle differenze non trascurabili. Pertanto, risulta evidente come la scelta delle macchine (trattori e macchine operatrici) influenzi profondamente la sostenibilit\ue0 ambientale delle produzioni agricole, principalmente in termini di consumo di combustibile, olio lubrificante e materiali, nonch\ue9 delle emissioni dei gas di scarico del motore e delle sostanze nutritive rilasciate in aria, suolo e acqua. Tra questi, l'attenzione \ue8 stata rivolta ai combustibili e ai gas di scarico del motore e, per approfondire la conoscenza sul sistema e migliorare l\u2019affidabilit\ue0 dello strumento di calcolo di inventario, sono state eseguite delle prove su molteplici operazioni di campo utilizzando un trattore equipaggiato con GPS, CAN-bus, software di registrazione dei dati Dewesoft\uae e analizzatore di emissioni Testo\uae. Ci\uf2 ha consentito di raccogliere dati durante le operazioni in campo ed elaborarli per ciascuno degli stati di lavoro identificati (lavoro effettivo, svolte in capezzagna, tempi di stop e trasporto). Inoltre, nella Tesi di Dottorato \ue8 stata eseguita un'analisi sull'indicatore Water Footprint (WF) poich\ue9 la risorsa idrica \ue8 fondamentale per le produzioni agricole e per le problematiche di sostenibilit\ue0 ambientale. Analizzando la letteratura sono emerse delle critiche metodologiche sull'approccio di calcolo adottato per il WF, principalmente in relazione alla quantificazione di WFblue e WFgrey. Pertanto, sono stati suggeriti alcuni miglioramenti, tra cui l\u2019introduzione del Pollution Water Indicator (PWI) che permette di valutare qualitativamente il WFgrey con il supporto delle categorie di impatto caratteristiche dell\u2019LCA che si riferiscono all\u2019impatto sulla risorsa idrica. I risultati ottenuti dall'analisi delle operazioni di campo e dalla valutazione sui dati per la compilazione degli inventari hanno permesso di identificare le combinazioni alternative di trattori e macchine operatrici che hanno un impatto ambientale pi\uf9 contenuto rispetto ad altri. Inoltre, sono state identificate le condizioni di lavoro che dovrebbero essere adottate positivamente quando si lavora con il trattore utilizzato durante le prove di campo e le misure in campo hanno anche permesso di avere dati affidabili per quantificare l'impatto ambientale delle operazioni analizzate. Infine, per quanto riguarda lo studio del WF, i risultati ottenuti dall'introduzione del PWI hanno permesso di valutare l'inquinamento della risorsa idrica nelle produzioni agricole senza omettere importanti inquinanti. In conclusione, i risultati di questa Tesi di Dottorato possono essere adottati per avere una metodologia di analisi dei sistemi produttivi che consenta di valutare la variabilit\ue0 locale e di raggiungere una maggiore affidabilit\ue0 nei risultati e, inoltre, per aiutare i decisori politici a introdurre politiche e sistemi di incentivazione adeguati a supportare la sostenibilit\ue0 ambientale dei sistemi agro-alimentari.The environmental sustainability of agricultural productions has gained wide interest worldwide. For the scientific community, understanding the behaviour of agricultural production systems on the environmental impact perspective with a holistic view and quantifying the environmental benefits arising from the selection of a sequence of operations or another, permits to identify and suggest the introduction of beneficial improvements for society and future generations. This PhD Thesis was aimed to study how to make adequately reliable the inventories in view of performing environmental sustainability assessments about agricultural machinery production systems. For these, local pedo-climatic and work-specific characteristics affect considerably both the completion of inventories and the outcomes of Life Cycle Assessment (LCA) studies. In detail, in this Thesis are quantified with LCA the environmental impacts of agricultural field operations for seedbed preparation (i.e. primary and secondary soil tillage) and for organic fertilisers spreading techniques. This has been done by studying the use of different machinery in different working conditions and, consequently, highlighting how different environmental outcomes can be obtained when average inventory data are used uncritically. This makes policy makers and stakeholders aware of the importance of avoiding such simplifications and general information. The alternative operations that were studied, representative of the Italian Po Valley, were analysed with the tool ENVIAM (ENVironmental Inventory of Agricultural Machinery operations). ENVIAM was developed to quantify inventory data for agricultural field operations, considering the mechanical variability of machinery (i.e. of tractors and implements), the coupling choices between tractor and implement, the organisation of working time and the local pedo-climatic variables. The related environmental impact results showed not negligible differences. Accordingly, the choice of machinery greatly influences the environmental sustainability of agricultural productions, mainly in terms of fuel consumption, lubricating oil and materials consumption as well as of emissions of engine exhaust gases and of nutrients to air, soil and water. Among them, the focus was paid to fuel and engine exhaust gases. For deepening knowledge and improving the reliability of the inventory calculation tool, field tests on several field operations were carried out using a tractor equipped with GPS, CAN-bus, Dewesoft\uae data logger and Testo\uae emissions analyser. This allowed collecting data during field operations and processing them within the identified work states (i.e. effective work, turns at the headlands, stops and transport). In addition, in the PhD Thesis an analysis of the Water Footprint (WF) indicator was carried out, because water resource is crucial for agricultural productions and environmental sustainability issues. By reviewing the literature, methodological criticisms emerged about the Water Footprint Network approach, mostly in relation to the quantification of WFblue and WFgrey. Therefore, some improvements have been suggested, among which the introduction of the Pollution Water Indicator (PWI). It was proposed to qualitatively evaluate WFgrey with the support of LCA\u2019s impact categories that relate to the impact on water resources. The results got from the analysis of agricultural machinery operations and inventory data completion permitted to identify the alternatives for machinery that have a more restrained environmental impact respect to others. Moreover, the work conditions that should be adopted when working with the tractor used during the field trials were identified, which also allowed having reliable data for quantifying the environmental impact of the analysed field operations. Finally, regarding the WF study, the results that were obtained from the use of PWI permitted to assess water pollution of agricultural productions without omitting important pollutant sources. In conclusion, the outcomes of this PhD Thesis can be adopted to have a methodology for analysing local production systems that allows assessing local variability and achieving greater reliability in the results and, moreover, to help policy makers introduce policies and incentive systems appropriate to support the environmental sustainability of agri-food systems

A Survey of Dairy Cattle Behavior in Different Barns in Northern Italy

Due to its increasing pressure on dairy cows, studies that investigate how to cope with heat stress are needed. The heat stress affects multiple aspects of cows' lives, among which their behavior and welfare. In this study, a survey was carried out in eight farms located in Northern Italy to monitor and evaluate the environmental aspects of the barns and the behavioral responses of dairy cows. For one year, three periods were monitored: thermoneutral (T_S), hot (H_S) and cold (C_S) seasons. Temperature and relative humidity were measured by environmental sensors, and lying vs. standing time, number of lying bouts and their average duration were collected by accelerometers. The temperature-humidity index (THI) was quantified inside and outside of the barn. Results show that at the increase of the THI, behavioral adaptations occurred in all the farms, especially with a reduction of lying time and an increase of respiration rate. Four of the eight farms need interventions for improving the cows' welfare. Here, environmental problems should be solved by introducing or improving the efficacy of the forced ventilation or by modifying the barn structure. Monitoring dairy barns with sensors and Precision Livestock Farming techniques can be helpful for future livestock farming to alert farmers on the need for their interventions to respond immediately to unwanted barn living conditions

Improving the Sustainability of Dairy Slurry by A Commercial Additive Treatment

Ammonia (NH3), methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2) emissions from livestock farms contribute to negative environmental impacts such as acidification and climate change. A significant part of these emissions is produced from the decomposition of slurry in livestock facilities, during storage and treatment phases. This research aimed at evaluating the eectiveness of the additive \u201cSOP LAGOON\u201d (made of agricultural gypsum processed with proprietary technology) on (i) NH3 and Greenhouse Gas (GHG) emissions, (ii) slurry properties and N loss. Moreover, the Life Cycle Assessment (LCA) method was applied to assess the potential environmental impact associated with stored slurry treated with the additive. Six barrels were filled with 65 L of cattle slurry, of which three were used as a control while the additive was used in the other three. The results indicated that the use of the additive led to a reduction of total nitrogen, nitrates, and GHG emissions. LCA confirmed the higher environmental sustainability of the scenario with the additive for some environmental impact categories among which climate change. In conclusion, the additive has beneficial eects on both emissions and the environment, and the nitrogen present in the treated slurry could partially displace a mineral fertilizer, which can be considered an environmental credit

Technical, economic, and environmental assessment of a collective integrated treatment system for energy recovery and nutrient removal from livestock manure

The aim of this 5-year study was to evaluate the technical, economic, and environmental performances of a collective-based integrated treatment system for bioenergy production and nutrients removal to improve the utilization efficiency and reduce the environmental impact of land applied livestock manure. The study involved 12 livestock production units located in an intensive livestock area designated as nitrate vulnerable zone with large N surplus. The treatment system consisted of an anaerobic digestion unit, a solid-liquid separation system, and a biological N removal process. Atmospheric emissions and nutrient losses in water and soil were examined for the environmental assessment, while estimated crop removal and nutrient utilization efficiencies were used for the agronomic assessment. The integrated treatment system achieved 49% removal efficiency for total solids (TS), 40% for total Kjeldahl nitrogen (TKN), and 41% for total phosphorous (TP). A surplus of 58kWh/t of treated manure was achieved considering the electricity produced by the biogas plant and consumed by the treatment plant and during transportation of raw and treated manure. A profit of 1.61 \ubf/t manure treated and an average reduction of global warming potential by 70% was also achieved. The acidification potential was reduced by almost 50%. The agronomic use of treated manure eliminated the TKN surplus and reduced the TP surplus by 94%. This collective integrated treatment system can be an environmentally and economically sustainable solution for farms to reduce N surplus in intensive livestock production areas

Improvements to dairy farms for environmental sustainability in Grana Padano and Parmigiano Reggiano production systems

Grana Padano (GP) and Parmigiano Reggiano (PR) are the two most important Italian PDO cheeses. To improve the environmental sustainability of their production, a Life Cycle Assessment (LCA) was completed on 84 dairy farms located in the province of Mantova (Northern Italy). In particular, 33 farms delivered milk for GP production, whereas 51 farms to dairies for PR production. In GP farms, maize silage represented 33.7% of total farmland and alfalfa represented 28.1%. While in PR farms, alfalfa represented 63.6% of total farmland. Fat and Protein Corrected Milk (FPCM) and Dairy Efficiency (DE, calculated as kg of produced FPCM per kg of DM intake) were different in the two production system: FPCM was 30.2 +/- 4.32 kg/d in GP farms and 25.0 +/- 4.71 kg/d in PR farms; DE was 1.35 +/- 0.26 in GP farms, and 1.15 +/- 0.22 in PR farms. Mitigation strategies to improve both environmental and economic sustainability were suggested focussing on forage crop production, milk production, herd management and off-farm purchased feed. From the preliminary results, there is evidence that improvements are needed. Climate Change (kg CO2 eq/kg FPCM) and Land Use (kg Carbon deficit/kg FPCM) were similar (1.38 +/- 0.33 and 19.3 +/- 7.08 for GP system; 1.46 +/- 0.37 and 21.8 +/- 11.4 for PR system). The most efficient farms in terms of milk production and DE generally showed the best environmental and economic sustainability, while the others show worse outcomes, mainly due to poor DE, livestock-management issues, feed purchase and ration composition

Smart Dairy Farming: Innovative Solutions to Improve Herd Productivity

Among the most straining trends that farmers have to face there are: on one side, to guarantee welfare and adequate life conditions for animals and to reduce the environmental footprint, on the other side, to develop new strategies to improve farm management reducing costs. The current conditions and the expected developments of the dairy sector highlight a strong need for more efficient and sustainable farming systems. Studying heat stress, herd management and housing and animals\u2019 productive and reproductive performances is fundamental for the economic and environmental sustainability of the dairy chain. New and effective tools to cope with these challenges have been provided by Precision Livestock Farming (PLF), which is nowadays increasingly applied and makes possible to control quali-quantitative parameters related to production, health, behaviour, and real-time locomotion per animal. The research key challenge is to turn these data into knowledge to provide real-time support in farming optimisation. This research focuses specifically on different systems to collect, process and derive useful information from data on animal welfare and productivity. A multi-disciplinary approach has been adopted to generate a decision support system for farmers

Life cycle assessment of European anchovy (Engraulis encrasicolus) landed by purse seine vessels in northern Spain

Purpose: The main purpose of this article is to assess the environmental impacts associated with the fishing operations related to European anchovy fishing in Cantabria (northern Spain) under a life cycle approach. Methods: The life cycle assessment (LCA) methodology was applied for this case study including construction, maintenance, use, and end of life of the vessels. The functional unit used was 1 kg of landed round anchovy at port. Inventory data were collected for the main inputs and outputs of 32 vessels, representing a majority of vessels in the fleet. Results and discussion: Results indicated, in a similar line to what is reported in the literature, that the production, transportation, and use of diesel were the main environmental hot spots in conventional impact categories. Moreover, in this case, the production and transportation of seine nets was also relevant. Impacts linked to greenhouse gas (GHG) emissions suggest that emissions were in the upper range for fishing species captured with seine nets and the value of global warming potential (GWP) was 1.44 kg CO2 eq per functional unit. The ecotoxicity impacts were mainly due to the emissions of antifouling substances to the ocean. Regarding fishery-specific categories, many were discarded given the lack of detailed stock assessments for this fishery. Hence, only the biotic resource use category was computed, demonstrating that the ecosystems' effort to sustain the fishery is relatively low. Conclusions: The use of the LCA methodology allowed identifying the main environmental hot spots of the purse seining fleet targeting European anchovy in Cantabria. Individualized results per port or per vessel suggested that there are significant differences in GHG emissions between groups. In addition, fuel use is high when compared to similar fisheries. Therefore, research needs to be undertaken to identify why fuel use is so high, particularly if it is related to biomass and fisheries management or if skipper decisions could play a role.The authors thank the Ministry of Economy and Competitiveness of the Spanish Government for their financial support via the project GeSAC-Conserva: Sustainable Management of the Cantabrian Anchovies (CTM2013-43539-R) and to Pedro Villanueva-Rey for valuable scientific exchange. Jara Laso thanks the Ministry of Economy and Competitiveness of Spanish Government for their financial support via the research fellowship BES-2014-069368 and to the Ministry of Rural Environment, Fisheries and Food of Cantabria for the data support. Dr. Ian Vázquez-Rowe thanks the Peruvian LCA Network for operational support. Reviewers are also thanked for the valuable and detailed suggestions. The work of Dr. Rosa M. Crujeiras has been funded by MTM2016-76969P (AEI/FEDER, UE)