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Holden, Nicholas M.
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Holden, Nicholas M.
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Holden, Nicholas M.
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Now showing 1 - 6 of 6
- PublicationEnvironmental impacts of animal-based food supply chains with market characteristicsAnimal-based food supply chains lead to significant environmental impacts, which can be influenced by production systems, distribution networks and consumption patterns. To develop strategy aimed at reducing the environmental impact of animal-based food supply chains, the common environmental hotspots among different types of food, the role of transport logistics and the consequence of end market need to be better understood. Life cycle assessment was adopted to model three types of animal-based food chains (beef, butter and salmon), with specific technologies, high spatial-resolution logistics and typical consumption patterns for three markets: local, regional (intra-European) and international. The results confirmed that the farm production stage usually had the greatest environmental impact, except when air transport was used for distribution. Potentially, the role of end market also can significantly influence the environmental impacts. To understand more, three improvement options were examined in detail with regard to hotspots for climate change: novel feed ingredients (farm production stage), sustainable aviation fuel (transport and logistics stage) and reduction of wasted food (consumption and end of life stage). Significant reduction was achieved in the salmon system by sustainable aviation fuel (64%) and novel feed (15%). Minimizing food waste drove the greatest reduction in the beef supply chain (23%) and the international butter supply chain can reduce 50% of GHG mission by adopting sustainable aviation fuel. Combined interventions could reduce GHG emission of animal-based food supply chains by 15% to 82%, depending on market, transport and food waste behaviour. The results show that eco-efficiency information of animal-based foods should include the full supply chain. The effective mitigation strategy to achieve the greatest reduction should not only consider the impacts on-farm, but also detail of the downstream impacts, such as food distribution network and consumption patterns.
26Scopus© Citations 10 - PublicationThe biosystems engineering design challenge at University College Dublin(American Society of Agricultural and Biological Engineers, 2007-01)
; ; ; ; The Biosystems Engineering Design Challenge has recently become an academic module open to all undergraduate students at University College Dublin. The focus of the module is on designing and building a working, bench-scale device that solves a practical problem relevant to Biosystems Engineering. The module provides an opportunity for students to learn about engineering design, project management and teamwork. Enrolled students are split into teams of up to seven and meet an assigned mentor each week during a semester (12 weeks) to solve a specified problem. The objectives thus far have focused on water-driven electricity generation, treatment of greywater from domestic buildings,and biofiltration of malodors from food waste. The assessment criteria include teamwork, minimisation of expenditure, device design, innovation, operational safety, system performance, report writing and appropriate use of biological and recycled materials. External experts evaluate each entry and substantial cash prizes are awarded to the top teams. Students receive individual academic grades based on their contribution. Feedback on the module has been very positive from both inside and outside the University. The most recent developments have been the introduction of an online project journal for each student and the involvement of biosystems engineering graduate students as mentors.212 - PublicationEnhancing the first year learning experience for Biosystems Engineering students at University College Dublin(American Society for Engineering Education, 2010-06)
; ; ; ; This paper outlines the development of a problem-based learning module called the Biosystems Engineering Design Challenge. The focus of the module is on designing and building a working, bench-scale device that solves a practical problem relevant to Biosystems Engineering. It provides an early opportunity for students to learn about engineering design, project management and teamwork. The module aligns well with the academic policy of University College Dublin to introduce alternative teaching and learning strategies compared to the conventional lecture. While the original aim of the module was to enhance the learning experience specifically for Biosystems Engineering students, it was considered beneficial to adopt a multi-disciplinary approach by allowing students from a wide variety of programs to participate. Students are split into teams and meet an assigned mentor each week during a 12-week semester to solve a specified problem with several design constraints. The projects thus far have focused on flood barrier construction, water-driven electricity generation, treatment of gray water from domestic buildings, and biofiltration of malodors from food waste. The student groups are formed in the first week when they meet their mentors and learn about the technical design constraints of the project and tips for good teamwork and time management. The second week provides a focus for literature research followed by brainstorming and evaluation of the key design solutions. A self-assessment is made of the teamwork in the sixth week and more guidance is provided on the requirements for the compilation of reports and posters. Weeks eight to ten focus on device assembly while technical performance is evaluated in the penultimate session. A panel of external technical experts visit the University in the final week to meet the students, mentors and faculty and to view a display of the devices and accompanying posters in the main Engineering building. The assessment criteria include teamwork, minimization of expenditure, device design, innovation, operational safety, system performance, project journal submission, report writing, poster presentation and appropriate use of biological and recycled materials. Prizes are awarded to the top teams. Students receive individual academic grades based on their contribution following a review by mentors and faculty at the end of the semester. Mentor assessment of students concentrates on meeting attendance, task completion and participation in the team. Student feedback has been very positive. They like a “hands-on” approach to learning while solving problems within a team environment. Awards for the recognition of teaching excellence have been received from UCD College of Life Sciences and from the American Society for Engineering Education.238 - PublicationWater footprinting of dairy farming in Ireland(Elsevier, 2017-01-01)
; ; ; ; ; In the context of global water scarcity, water footprints have become an important sustainability indicator for food production systems. To improve the water footprint of the dairy sector, insight into freshwater consumption of individual farms is required. The objective of this study was to determine the primary contributors to freshwater consumption (i.e. water use that does not return to the same watershed) at farm-gate level, expressed as a water footprint, for the production of one kg of fat-and-protein corrected milk (FPCM), on 24 Irish dairy farms. This is the first study that uses detailed farm level data to assess the water footprint of a large set of Irish dairy farms. The water footprint comprises of the consumption of soil moisture due to evapotranspiration (green water), and the consumption of ground and surface water (blue water), and includes freshwater used for cultivation of crops for concentrate production, on-farm cultivation of grass or fodder and water required for animal husbandry and farm maintenance. The related impact of freshwater consumption on global water stress from producing milk in Ireland was also computed. Over the 24 farms evaluated, the production of milk consumed on average 690 L water/kg FPCM, ranging from 534 L/kg FPCM to 1107 L/kg FPCM. Water required for pasture production contributed 85% to the water footprint, 10% for imported forage production (grass in the form of hay and silage), concentrates production 4% and on-farm water use ∼1%. The average stress weighted water footprint was 0.4 L/kg FPCM across the farms, implying that each litre of milk produced potentially contributed to fresh water scarcity equivalent to the consumption of 0.4 L of freshwater by an average world citizen. The variation of volumetric water footprints amongst farms was mainly related to the level of feed grown on-farm and levels of forages and concentrates imported onto the farm. Using farm specific data from a subset of Irish dairy farms allowed this variability in WF to be captured, and contributes to the identification of improvement options. The biggest contribution to the water footprint of milk was from grass grown with green water, which is a plentiful resource in Ireland. This study also indicates an opportunity for present and future milk production systems to source feed ingredients from non-water stressed areas to further reduce the burden on freshwater resources, especially in countries that utilise confinement systems that have a higher proportion of concentrate feed in the dairy cow's diet.826Scopus© Citations 40 - PublicationWater footprinting of pasture-based farms; beef and sheep(Cambridge University Press, 2018-05)
; ; ; In the context of water use for agricultural production, water footprints (WFs) have become an important sustainability indicator. To understand better the water demand for beef and sheep meat produced on pasture-based systems, a WF of individual farms is required. The main objective of this study was to determine the primary contributors to freshwater consumption up to the farm gate expressed as a volumetric WF and associated impacts for the production of 1 kg of beef and 1 kg of sheep meat from a selection of pasture-based farms for 2 consecutive years, 2014 and 2015. The WF included green water, from the consumption of soil moisture due to evapotranspiration, and blue water, from the consumption of ground and surface waters. The impact of freshwater consumption on global water stress from the production of beef and sheep meat in Ireland was also computed. The average WF of the beef farms was 8391 l/kg carcass weight (CW) of which 8222 l/kg CW was green water and 169 l/kg CW was blue water; water for the production of pasture (including silage and grass) contributed 88% to the WF, concentrate production – 10% and on-farm water use – 1%. The average stress-weighted WF of beef was 91 l H2O eq/kg CW, implying that each kg of beef produced in Ireland contributed to freshwater scarcity equivalent to the consumption of 91 l of freshwater by an average world citizen. The average WF of the sheep farms was 7672 l/kg CW of which 7635 l/kg CW was green water and 37 l/kg CW was blue water; water for the production of pasture contributed 87% to the WF, concentrate production – 12% and on-farm water use – 1%. The average stress-weighted WF was 2 l H2O eq/kg CW for sheep. This study also evaluated the sustainability of recent intensification initiatives in Ireland and found that increases in productivity were supported through an increase in green water use and higher grass yields per hectare on both beef and sheep farms.452Scopus© Citations 7 - PublicationPredicting freshwater demand on Irish dairy farms using farm data(Elsevier, 2017-11-10)
; ; ; ; ; Freshwater use in agriculture is a matter of discussion due to rising concerns over water scarcity, availability and pollution. To make robust predictions of freshwater demand, a large dataset of agricultural data is needed to discern the relationships between production parameters and water demand. The objective of this research was to predict freshwater demand (L yr−1) on Irish dairy farms based on a minimal set of farm data. A detailed water footprint (WF) was calculated for 20 dairy farms for 2014 and 2015, and the relationships between the WF and agricultural inputs explored via a mixed modelling procedure, to develop a minimal footprinting solution. The WF comprised of the consumption of soil moisture due to evapotranspiration (green water, GW) and ground and surface water (blue water, BW). The performance of the models was validated using an independent data set of five dairy farms. The GW model was applied to 221 dairy farms to establish the relationship between the GWF of milk and economic performance. The average total volumetric WF of the 20 farms was 778 L/kg fat and protein corrected milk (L/kg FPCM) (range 415¿1338 L/kg FPCM). Freshwater for pasture production made up 93% of the GW footprint. Grass grown, imported forages and concentrates fed were all significant predictors of GW. The relative prediction error (RPE) of the GW model was 11.3%. Metered on-farm water and concentrates were both significant predictors of BW. The RPE of the BW model was 3.4%. When applied to 221 dairy farms ranked by net margin per hectare, there was a trend (P < 0.05) towards higher profitability as the GWF decreased, indicating that the GWF of dairy farms can be improved by implementing good management practices aligned with improving profitability.362Scopus© Citations 4