Integrated ecological hotspot identification of organic egg production

Ecological sustainability in agriculture is a concept that contains various environmental problems, which are caused by emission of compounds during different processes along the food chain. A precise ecological analysis of farming systems and food chains is needed in order to suggest and implement effective measures to improve sustainability. Life Cycle Assessment (LCA) assesses the environmental impact along the entire chain. In this research, LCA was used to locate environmental hotspots within the organic egg production chain and explore options that substantially improve ecological sustainability using sensitivity analysis. The environmental impact was expressed per kg of organic egg leaving the farm gate. Five environmental impact categories were included: 1) climate change i.e., emission of CO2, CH4 and N2O, 2) eutrophication i.e., emission of NH3, NOx, N2O and leaching of NO3 - and PO4 -, 3) acidification i.e., emission of NH3, NOx, and SOx, 4) fossil energy use i.e., oil, gas, uranium and coal and 5) land use. In case of a multifunctional process, economic allocation was used. We interviewed 20 out of 68 Dutch organic egg farmers to collect farm data for 2006. Data on transport, feed, rearing and hatching were gathered by the conduction of interviews with suppliers and from literature. The Life Cycle Inventories of electricity, natural gas, tap water, transport and cultivation originated from the Eco-Invent V2.0 dataset. A sensitivity analysis was executed for production parameters from the laying hen farm. To identify hotspots, the relative contribution of transportation, feed production, rearing and hatching and the laying hen farm, as well as the contribution of various compounds to each impact category was determined. We identified a chaincompound combination as a hotspot if it contributed to more than 40% of the total of the environmental impact category. Results showed four hotspots. First, 62% of climate change was caused by emission of N2O from soils during growing of feed. Second, 57% of acidification was caused by NH3 emission from the laying hen farm. Third, 47% of energy use was oil used for cultivation of feed and fourth, 95% of the land use was arable land required for feed production. We identified no hotspot for eutrophication, but feed production contributed most with 37% nitrogen leaching and 26% PO4 - leaching. From the sensitivity analysis it appeared that the most sensitive parameters on an organic laying hen farm are the number of produced eggs, the amount of feed consumed and the housing system. An increase in average egg production from 276 with a SD of 39 eggs per laying hen reduced climate change with 13%, acidification with 15%, eutrophication with 13%, energy use with 12% and land use with 12%. A reduction in average annual feed consumption from 42.9 kg with the SD of 7.2 kg per laying hen reduced climate change with 14%, acidification with 17%, eutrophication with 15%, energy use with 14% and land use with 13%. A shift from deep litter housing to an aviary housing with manure drying reduced climate change with 11%, acidification with 53%, eutrophication with 18% and had no effect on land use. The effect on energy use is still being assessed. We conclude that feed conversion and housing are effective ecological optimization options for organic laying hen farmers. However ecological sound feed production also needs attention

Potential of LCA for designing technological innovations – the case of organic eggs

Ecological sustainability in agriculture is a concept that contains various environmental problems, which are caused by emission of pollutants and unsustainable use of limited resources, during different processes along the food chain. Technological innovations may help to improve ecological sustainability of food products. Preceding to the development of ecological sustainable technological innovations three questions need to be answered; 1) how ecological sustainable is the current production process, 2) which processes in the chain causes the highest ecological impact and 3) which production parameters significantly affect the ecological impact of these processes? The aim of this research is to demonstrate Life Cycle Assessment to the designers of technological innovations Life Cycle Assessment as a method to answer these questions, by means of a case study of the organic egg. In this study the LCA of organic eggs was calculated and compared to equivalent egg products. Ecological hotspots within the production chain were identified and the effectiveness of production parameters from the laying hen farm were identified on the LCA using sensitivity analysis. This LCA case study showed that organic eggs score worse than equivalent eggs on acidification, eutrophication and land use. Technological innovators should focus on ammonia emission from the laying hen farm to reduce the impact of acidification. Another focus should be nitrate leaching during concentrate production to reduce eutrophication. Innovative organic laying hen farmers may focus on a high feed conversion to improve the LCA of organic eggs in a broader sense. A shift from single tiered housing of laying hens to multi tiered housing with manure drying on manure belts, can reduce acidification 53% and eutrophication with 18%, almost enough to level out the 60% higher acidification and the 25% higher eutrophication of organic eggs compared to equivalent egg products

Defining Medical Futility in Ethics, Law and Clinical Practice: An Exercise in Futility?

The debate as to the meaning of medical futility and what physicians should do in clinical practice dates back to the time of the writings of Hippocrates and Plato where it was said, "To attempt futile treatment is to display an ignorance that is allied to madness". In simpler times assertions regarding the obvious were sufficient to indicate what was thought "fitting" as a medical practitioner. In recent times, however, modern technology, professional values and power, patient autonomy, limited health care resources and societal expectations, make for a much more potent and potentially explosive mixture. In this article we argue that futility is a problem that will not go away, both because of increased health expectations and emerging technologies that keep making possible what was previously impossible. The problem of definition and its ramifications in terms of institutional policies is one in which the legal profession and its process (which often represents and reflects societal values) has a key role to play by way of critical reflection and appraisal

Rethinking Plato’s Theory of Art: Aesthetics and the Timaeus

The Timaeus presents a fascinating account of the cosmos. It includes a creation myth that introduces the figure known as the Demiurge who, despite the fact that he is the cause of the sensible world, is reverently attributed with reason, and whose creation – the cosmos – is actually beautiful and good. In this dialogue Plato offers his readers a panorama of the universe. But just what are his intentions for this? Is his approach a precursor to the methods of natural science,1 or does the Timaeus fall under the category of theology? This thesis will discuss the outcome Plato wished to achieve by finally writing on cosmology and how the methods used to accomplish these ends reveal a more existential attitude towards aesthetics

A mechanistic model for electricity consumption on dairy farms: Definition, validation, and demonstration

Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on dairy farms (MECD) capable of simulating total electricity consumption along with related CO2 emissions and electricity costs on dairy farms on a monthly basis; (2) validated the MECD using empirical data of 1 yr on commercial spring calving, grass-based dairy farms with 45, 88, and 195 milking cows; and (3) demonstrated the functionality of the model by applying 2 electricity tariffs to the electricity consumption data and examining the effect on total dairy farm electricity costs. The MECD was developed using a mechanistic modeling approach and required the key inputs of milk production, cow number, and details relating to the milk-cooling system, milking machine system, water-heating system, lighting systems, water pump systems, and the winter housing facilities as well as details relating to the management of the farm (e.g., season of calving). Model validation showed an overall relative prediction error (RPE) of less than 10% for total electricity consumption. More than 87% of the mean square prediction error of total electricity consumption was accounted for by random variation. The RPE values of the milk-cooling systems, water-heating systems, and milking machine systems were less than 20%. The RPE values for automatic scraper systems, lighting systems, and water pump systems varied from 18 to 113%, indicating a poor prediction for these metrics. However, automatic scrapers, lighting, and water pumps made up only 14% of total electricity consumption across all farms, reducing the overall impact of these poor predictions. Demonstration of the model showed that total farm electricity costs increased by between 29 and 38% by moving from a day and night tariff to a flat tariff

Effect of electricity tariffs and cooling technologies on dairy farm electricity consumption, related costs and greenhouse gas emissions

The aim of this study was to provide insight into the variations in dairy farm electricity costs across five electricity tariffs. The effect of four milk cooling scenarios is also simulated to illustrate the effect of technologies on the electricity consumption, related costs and CO2 emissions of a dairy farm. Helping dairy farmers to make informed business decisions when confronted with future options in the sphere of electricity tariffs and energy efficient cooling systems will contribute to optimum farm profitability and will help to improve the profitability and sustainability of the industry. A previously developed model capable of simulating electricity consumption, related costs and CO2 emissions of dairy farms was used to simulate five electricity tariffs (Flat, Day&Night, Time of Use Tariff 1 (TOU1), TOU2 and Real Time Pricing (RTP)) on a dairy farm with 195 milking cows. The Flat tariff consisted on one electricity price for all time periods, the Day&Night tariff consisted of two electricity prices, a high rate from 09:00 to 00:00 h and a low rate thereafter. The TOU tariff structure was similar to that of the Day&Night tariff except that a third peak price band was introduced between 17:00 and 19:00 h. The RTP tariff varied dynamically according to the electricity demand on the national grid. The model used in these simulations is a mechanistic mathematical representation of the electricity consumption that simulates farm equipment under the following headings; milk cooling system, water heating system, milking machine system, lighting systems, water pump systems and the winter housing facilities. Direct expansion, ice bank and pre-cooling milk cooling systems were simulated to determine how dairy farm electricity consumption, related costs and CO2 emissions vary according to the milk cooling system installed on the farm. Annual simulated electricity consumption of the farm was 32,670 kWh when a direct expansion milk cooling system without pre-cooling of milk was included in the model. The annual electricity consumption of the farm on the day & night tariff was €4,571. Adding precooling with ground water to the direct expansion milk cooling system reduced annual electricity consumption by 28% to 23,660 kWh and reduced annual electricity costs by 38% to €2,875. The addition of a pre-cooling system to the direct expansion milk cooling system saved 3,973 kg of CO2. Simulation of an ice bank milk cooling system without pre-cooling resulted in annual simulated electricity consumption of 34,777 kWh. The annual electricity consumption on the day & night tariff was €3,793. Adding pre-cooling with ground water to the ice bank milk cooling system reduced annual electricity consumption by 30% to 24,181 kWh and reduced annual electricity costs by 33% to €2,527. The addition of a pre-cooling system to the ice bank milk cooling system saved 5,044 kg of CO2

Clinical management of Duchenne muscular dystrophy in the Netherlands: barriers to and proposals for the implementation of the international clinical practice guidelines

Background: In order to successfully implement the international clinical care guidelines for Duchenne muscular dystrophy (DMD) in the Netherlands, it is essential to know what barriers are experienced by healthcare practitioners regarding guideline adherence and organization of care. In the Netherlands, academic medical centers provide follow up visits and work together with peripheral hospitals, rehabilitation centers, centers for home ventilation and primary care centers for treatment.Objective: To investigate perceived barriers to international clinical DMD guideline adherence and identify potential areas of improvement for implementation in the Dutch 'shared care' organization.Methods: Semi-structured in-depth interviews with healthcare practitioners of academic medical hospitals and questionnaires for healthcare practitioners of rehabilitation centers, based on the framework of Cabana.Results: The analyses identified 4 barriers for non-adherence to the DMD guideline: (i) lack of familiarity/awareness, (ii) lack of agreement with specific guideline, (iii) lack of outcome expectancy, (iv) external barriers.Conclusions: A heterogeneous set of barriers is present. Therefore, a multifaceted intervention strategy is proposed to overcome these barriers, including a clear division of roles, allowing for local (Dutch) adaptations per specialism by local consensus groups, and the facilitation of easy communication with experts/opinion leaders as well as between care professionals.Neurological Motor Disorder

Compliance to DMD care considerations in the Netherlands

Background and objective: To optimize care for patients with DMD, it is essential to know to what extent current care complies with the recommended monitoring frequencies suggested by the DMD care considerations. The objective of this study was to investigate the current care for patients with DMD in the Netherlands and to what extent the care complies with the international care considerations.Methods: A cross-sectional questionnaire was carried out among the Dutch DMD patients and caregivers about the patients' functional and health status, visits to healthcare professionals, clinical tests and assessments, therapy, medication use and access to medical aids and devices. Compliance to guidelines was defined by comparing the frequency of visits to health care providers and clinical tests with the recommended frequencies derived from the care considerations of 2010.Results: Eighty-four participants completed the questionnaire. The majority of participants met the recommended visit frequencies to a neuromuscular specialist and cardiologist. Compliance was suboptimal for respiratory assessments in the non-ambulatory phase, monitoring of side effects of corticosteroid use and neuromuscular assessments. Disease specific information supply was perceived as sufficient and participants were satisfied with the received care.Conclusions: This study identifies areas in which compliance is lacking. Countries, such as the Netherlands, working according to a shared care system require easy and low-threshold communication between health care centers and a clear division of roles and responsibilities to reach optimal compliance. In the Netherlands the Duchenne Center Netherlands has the coordinating role.Neurological Motor Disorder

Association of elbow flexor MRI fat fraction with loss of hand-to-mouth movement in patients with Duchenne muscular dystrophy

Background and Objectives To study the potential of quantitative MRI (qMRI) fat fraction (FF) as a biomarker in nonambulant patients with Duchenne muscular dystrophy (DMD), we assessed the additive predictive value of elbow flexor FF to age at loss of hand-to-mouth movement. Methods Nonambulant patients with DMD (age >= 8 years) were included. Four-point Dixon MRI scans of the right upper arm were performed at baseline and at the 12-, 18-, or 24-month follow-up. Elbow flexor FFs were determined from 5 central slices. Loss of hand-to-mouth movement was determined at study visits and by phone calls every 4 months. FFs were fitted to a sigmoidal curve by use of a mixed model with random slope to predict individual trajectories. The added predictive value of elbow flexor FF to age at loss of hand-to-mouth movement was calculated from a Cox model with the predicted FF as a time-varying covariate, yielding a hazard ratio. Results Forty-eight MRIs of 20 patients with DMD were included. The hazard ratio of a percent-point increase in elbow flexor FF for the time to loss of hand-to-mouth movement was 1.12 (95% confidence interval 1.04-1.21; p = 0.002). This corresponded to a 3.13-fold increase in the instantaneous risk of loss of hand-to-mouth movement in patients with a 10-percent points higher elbow flexor FF at any age. Discussion In this prospective study, elbow flexor FF predicted loss of hand-to-mouth movement independently of age. qMRI-measured elbow flexor FF can be used as a surrogate endpoint or stratification tool for clinical trials in nonambulant patients with DMD. Classification of Evidence This study provides Class II evidence that qMRI FF of elbow flexor muscles in patients with DMD predicts loss of hand-to-mouth movement independently of age.Neuro Imaging Researc