I.J.M. de Boer

Comparing environmental consequences of anaerobic mono- and co-digestion of pig manure to produce bio-energy – A life cycle perspective

The aim of this work was to assess the environmental consequences of anaerobic mono- and co-digestion of pig manure to produce bio-energy, from a life cycle perspective. This included assessing environmental impacts and land use change emissions (LUC) required to replace used co-substrates for anaerobic digestion. Environmental impact categories considered were climate change, terrestrial acidification, marine and freshwater eutrophication, particulate matter formation, land use, and fossil fuel depletion. Six scenarios were evaluated: mono-digestion of manure, co-digestion with: maize silage, maize silage and glycerin, beet tails, wheat yeast concentrate (WYC), and roadside grass. Mono-digestion reduced most impacts, but represented a limited source for bio-energy. Co-digestion with maize silage, beet tails, and WYC (competing with animal feed), and glycerin increased bio-energy production (up to 568%), but at expense of increasing climate change (through LUC), marine eutrophication, and land use. Co-digestion with wastes or residues like roadside grass gave the best environmental performance.

Environmental consequences of processing manure to produce mineral fertilizer and bio-energy.

Liquid animal manure and its management contributes to environmental problems such as, global warming, acidification, and eutrophication. To address these environmental issues and their related costs manure processing technologies were developed. The objective here was to assess the environmental consequences of a new manure processing technology that separates manure into a solid and liquid fraction and de-waters the liquid fraction by means of reverse osmosis. This results in a liquid mineral concentrate used as mineral nitrogen and potassium fertilizer and a solid fraction used for bio-energy production or as phosphorus fertilizer. Five environmental impact categories were quantified using life cycle assessment: climate change (CC), terrestrial acidification (TA), marine eutrophication (ME), particulate matter formation (PMF), and fossil fuel depletion (FFD). For pig as well as dairy cattle manure, we compared a scenario with the processing method and a scenario with additional anaerobic digestion of the solid fraction to a reference situation applying only liquid manure. Comparisons were based on a functional unit of 1 ton liquid manure. System boundaries were set from the manure storage under the animal house to the field application of all end products. Scenarios with only manure processing increased the environmental impact for most impact categories compared to the reference: ME did not change, whereas, TA and PMF increased up to 44% as a result of NH3 and NO(x) emissions from processing and storage of solid fraction. Including digestion reduced CC by 117% for pig manure and 104% for dairy cattle manure, mainly because of substituted electricity and avoided N2O emission from storage of solid fraction. FFD decreased by 59% for pig manure and increased 19% for dairy cattle manure. TA and PMF remained higher compared to the reference. Sensitivity analysis showed that CH4 emission from manure storage, NH3 emission from processing, and the replaced nitrogen fertilizer by the mineral concentrate were important parameters affecting final results. It was concluded that processing fattening pig and dairy cattle manure to produce mineral fertilizer increased overall environmental consequences in terms of CC (except for dairy cattle manure), TA, PMF, and FFD compared to current agricultural practice. Adding the production of bio-energy reduced CC and FFD. Only when NH3 emission from processing was low and bio-energy was produced, overall equal or better environmental performance was obtained for TA and PMF. It was emphasized that real time measurements should be done to enhance the environmental assessment of manure processing technologies. Results of this study present the full environmental consequences of manure processing and key parameters affecting the environmental impact of manure management. Outcomes can be used for decision making and further tackling of environmental problems related to manure management.

On-farm quantification of sustainability indicators: an application to egg production systems

1. On-farm quantification of sustainability indicators (SI) is an effective way to make sustainable development measurable. The egg production sector was used as a case study to illustrate this approach. 2. The objective was to select SI for economic, ecological and societal issues, and to analyse the performance on selected SI of different production systems. 3. For the case study, we compared 4 egg production systems, characterised by differences in the housing systems which are most common in the Netherlands: the battery-cage system, the deep-litter system with and without outdoor run, and the aviary system with outdoor run. 4. Based on a clear set of criteria, we selected SI for animal welfare, economics, environmental impact, ergonomics and product quality. 5. We showed that on-farm quantification of SI was an appropriate method to identify the strengths and weaknesses of different systems. 6. From this analysis it appears that the aviary system with outdoor run is a good alternative for the battery-cage system, with better scores for the aviary system on animal welfare and economics, but with worse scores on environmental impact.

Invited review: Associations between variables of routine herd data and dairy cattle welfare indicators

As farm animal welfare is high on the political and societal agendas of many countries, considerable pressure exists to establish audit programs in which farm animal welfare is routinely monitored. On-farm assessment of animal welfare, however, is time-consuming and costly. A promising strategy to monitor animal welfare more efficiently is to first estimate the level of animal welfare on a farm based on routine herd data that are available in national databases. It is not currently known which variables of routine herd data (VRHD) are associated with dairy cattle welfare indicators (WI). Our aim was to identify VRHD that are associated with WI in a literature review. The 27 VRHD used in this review included the main types of data that are currently collected in national herd databases of developed countries, and related to identification and registration, management, milk production, and reproduction of dairy herds. The 34 WI used in this review were based on the Welfare Quality Assessment Protocol for Cattle. The search yielded associations in 146 studies. Twenty-three VRHD were associated with 16 WI. The VRHD that related to milk yield, culling, and reproduction were associated with the largest number of WI. Few associations were found for WI that referred to behavioral aspects of animal welfare, nonspecific disease symptoms, or resources-based indicators. For 18 WI, associations with VRHD were not significant (n=5 WI) or no studies were found that investigated associations with VRHD (n=13 WI). It was concluded that many VRHD have potential to estimate the level of animal welfare on dairy farms. As strengths of associations were not considered in this review, however, the true value of these VRHD should be further explored. Moreover, associations found at the animal level and in an experimental setting might not appear at the farm level and in common practice and should be investigated. Cross-sectional studies using integrated welfare scores at the farm level are needed to more accurately determine the potential of VRHD to estimate levels of animal welfare on dairy farms.

Prediction of additive and dominance effects in selected or unselected populations with inbreeding.

SummaryA genetic model with either 64 or 1,600 unlinked biallelic loci and complete dominance was used to study prediction of additive and dominance effects in selected or unselected populations with inbreeding. For each locus the initial frequency of the favourable allele was 0.2, 0.5, or 0.8 in different alternatives, while the initial narrow-sense heritability was fixed at 0.30. A population of size 40 (20 males and 20 females) was simulated 1,000 times for five generations. In each generation 5 males and 10 or 20 females were mated, with each mating producing four or two offspring, respectively. Breeding individuals were selected randomly, on own phenotypic performance or such yielding increased inbreeding levels in subsequent generations. A statistical model containing individual additive and dominance effects but ignoring changes in mean and genetic covariances associated with dominance due to inbreeding resulted in significantly biased predictions of both effects in generations with inbreeding. Bias, assessed as the average difference between predicted and simulated genetic effects in each generation, increased almost linearly with the inbreeding coefficient. In a second statistical model the average effect of inbreeding on the mean was accounted for by a regression of phenotypic value on the inbreeding coefficient. The total dominance effect of an individual in that case was the sum of the average effect of inbreeding and an individual effect of dominance. Despite a high mean inbreeding coefficient (up to 0.35), predictions of additive and dominance effects obtained with this model were empirically unbiased for each initial frequency in the absence of selection and 64 unlinked loci. With phenotypic selection of 5 males and only 10 females in each generation and 64 loci, however, predictions of additive and dominance effects were significantly biased. Observed biases disappeared with 1,600 loci for allelic frequencies at 0.2 and 0.5. Bias was due to a considerable change in allelic frequency with phenotypic selection. Ignoring both the covariance between additive and dominance effects with inbreeding and the change in dominance variance due to inbreeding did not significantly bias prediction of additive and dominance effects in selected or unselected populations with inbreeding.

Methods for uncertainty propagation in life cycle assessment

Life cycle assessment (LCA) calculates the environmental impact of a product over its entire life cycle. Uncertainty analysis is an important aspect in LCA, and is usually performed using Monte Carlo sampling. In this study, Monte Carlo sampling, Latin hypercube sampling, quasi Monte Carlo sampling, analytical uncertainty propagation and fuzzy interval arithmetic were compared based on e.g. convergence rate and output statistics. Each method was tested on three LCA case studies, which differed in size and behaviour. Uncertainty propagation in LCA using a sampling method leads to more (directly) usable information compared to fuzzy interval arithmetic or analytical uncertainty propagation. Latin hypercube and quasi Monte Carlo sampling provide more accuracy in determining the sample mean than Monte Carlo sampling and can even converge faster than Monte Carlo sampling for some of the case studies discussed in this paper. Display Omitted

Inter- and intra-observer reliability of experienced and inexperienced observers for the Qualitative Behaviour Assessment in dairy cattle

Qualitative Behaviour Assessment (QBA) is part of the Welfare Quality® protocol for dairy cattle, although its inter- and intra-observer reliability have not been reported. This study evaluated inter- and intra-observer reliability of the QBA for dairy cattle in experienced and inexperienced observers using videos. Eight experienced observers performed the QBA (20 descriptors) twice for 16 video clips (60 s per clip; series 1) showing 4-17 animals. They assessed another 11 video clips showing herds (4 shots of 30 s per clip; series 2). Ten inexperienced observers performed the QBA on both video series one time. Inter-observer reliability of experienced observers ranged from slight to moderate (both assessments of series 1), and from low to high (series 2) for descriptors, and from slight to moderate for the QBA score. Inter-observer reliability of inexperienced observers ranged from low to moderate (series 1), and from low to high (series 2) for descriptors, and was moderate (both series) for the QBA score. Intra-observer correlations varied largely per descriptor and observer. They were both negative and positive, and ranged from low to very high. High correlations, however, were not necessarily associated with low paired differences. Values of half of the descriptors and the QBA score differed amongst experienced and inexperienced observers. The QBA appears insufficiently reliable as a tool for welfare assessment in dairy cattle.

Energy demand on dairy farms in Ireland

Reducing electricity consumption in Irish milk production is a topical issue for 2 reasons. First, the introduction of a dynamic electricity pricing system, with peak and off-peak prices, will be a reality for 80% of electricity consumers by 2020. The proposed pricing schedule intends to discourage energy consumption during peak periods (i.e., when electricity demand on the national grid is high) and to incentivize energy consumption during off-peak periods. If farmers, for example, carry out their evening milking during the peak period, energy costs may increase, which would affect farm profitability. Second, electricity consumption is identified in contributing to about 25% of energy use along the life cycle of pasture-based milk. The objectives of this study, therefore, were to document electricity use per kilogram of milk sold and to identify strategies that reduce its overall use while maximizing its use in off-peak periods (currently from 0000 to 0900 h). We assessed, therefore, average daily and seasonal trends in electricity consumption on 22 Irish dairy farms, through detailed auditing of electricity-consuming processes. To determine the potential of identified strategies to save energy, we also assessed total energy use of Irish milk, which is the sum of the direct (i.e., energy use on farm) and indirect energy use (i.e., energy needed to produce farm inputs). On average, a total of 31.73 MJ was required to produce 1 kg of milk solids, of which 20% was direct and 80% was indirect energy use. Electricity accounted for 60% of the direct energy use, and mainly resulted from milk cooling (31%), water heating (23%), and milking (20%). Analysis of trends in electricity consumption revealed that 62% of daily electricity was used at peak periods. Electricity use on Irish dairy farms, therefore, is substantial and centered around milk harvesting. To improve the competitiveness of milk production in a dynamic electricity pricing environment, therefore, management changes and technologies are required that decouple energy use during milking processes from peak periods.

Economic, ecological, and social performance of conventional and organic broiler production in the Netherlands

1. In this study, we compared a conventional broiler production system keeping fast growing broilers with an organic broiler production system keeping slow growing broilers in the Netherlands, both managed by one person working a full time year (Full Time Equivalent, FTE). This comparison was based on a quantification of economic, ecological and social indicators. Indicators were quantified using scientific literature and national data sets. 2. The organic system performed better for the economic indicator net farm income per FTE than the conventional system. 3. Regarding ecological indicators, calculations showed a higher on-farm emission of ammonia per kg live weight for the organic system. Moreover, an organic system includes a higher risk for eutrophication per ha due to outdoor access. Emission of green house gasses, use of fossil fuels and use of land required for the production of one kg of live weight is higher for an organic than for a conventional system. This is mainly due to a lower feed conversion in organic production and use of organic feed. 4. The organic system performed better than the conventional system for the social indicators related to animal welfare time spent on walking, footpad lesions, mortality, and sound legs. Regarding the social indicator food safety was found that meat from an organic system contained less antibiotic residues and Salmonella contaminations but more Campylobacter contaminations than meat from a conventional system. 5. Changing from a conventional to an organic broiler production system, therefore, not only affects animal welfare, but also affects economic, ecological and other social issues. In this study, we ran into the situation that some information needed was lacking in literature and quantifications had to be based upon several sources. Therefore, an integrated on-farm assessment is needed, which can be used to develop a broiler production system that is economically profitable, ecologically sound, and acceptable for society.

Life cycle assessment of segregating fattening pig urine and feces compared to conventional liquid manure management

Gaseous emissions from in-house storage of liquid animal manure remain a major contributor to the environmental impact of manure management. Our aim was to assess the life cycle environmental consequences and reduction potential of segregating fattening pig urine and feces with an innovative V-belt system and to compare it to conventional liquid manure management, that is, the reference. Moreover, we aimed at analyzing the uncertainty of the outcomes related to applied emission factors. We compared a reference with two scenarios: segregation with solid, aerobically, stored feces and with liquid, anaerobically, stored feces. Results showed that, compared to the reference, segregation reduced climate change (CC) up to 82%, due to lower methane emission, reduced terrestrial acidification (TA) and particulate matter formation (PMF) up to 49%, through lower ammonia emission, but increased marine eutrophication up to 11% through nitrogen oxide emission from storage and nitrate leaching after field application. Fossil fuel depletion did not change. Segregation with liquid feces revealed lower environmental impact than segregation with solid feces. Uncertainty analysis supported the conclusion that segregating fattening pig urine and feces significantly reduced CC and additionally segregation with liquid feces significantly reduced TA and PMF compared to the reference.