Effect of dairy production system, breed and co-product handling methods on environmental impacts at farm level

Internal causality in agri-food Life Cycle Assessments: Solving allocation problems based on feed energy utilization in egg production

Physical allocation in Life Cycle Assessment (LCA) should, ideally, be based on underlying causal relationships. While both cause-oriented and effect-oriented causality referred to in LCA literature are forms of external causality, internal causality addresses the actual flow of materials and inputs in a system - in other words, the real behaviour of the system under study. While a number or examples of allocation based on physical causality have been used in poultry LCAs, none of these represent the internal causality (the actual biological processes) in egg production. The current study remedies that gap by proposing such a method. Agri-food LCAs, in particular LCAs of livestock production, were used to identify existing physical allocation approaches consistent with internal causality. The most commonly used approach was found to be based on the allocation of feed energy to support the various physiological functions of the livestock species. A feed energy - Metabolizable Energy (ME) - utilization model for allocation in egg production LCAs is hence similarly proposed. Using the inventory of a previous LCA study of egg production in Canada, allocation ratios for eggs and spent hens were developed. Feed utilization models specific to each unit process were identified. The overall differences between ME utilization (∼95% eggs, 5% spent hens) and gross chemical energy content (92% eggs, 8% spent hens) for allocation were relatively small. Scenario analysis, however, showed that the allocation ratios can be considerably different if the causal relationship is interpreted differently. Differences over ∼20% was seen in a scenario which did not allocate between the co-products of each unit process in the system, but rather to the products at the end of a biological causal chain straddling multiple unit processes. The proposed approach is consistent with the interpretation of LCA as a natural sciences framework, and with the ISO 14044 multi-functionality hierarchy, because it reflects actual biological causality in egg production systems. The study results also underscore that practitioners should not only clearly justify their choice of allocation strategy, but also describe its application in detail, since small differences in methods can result in divergent outcomes.

Dairy Farms and Life Cycle Assessment (LCA): The Allocation Criterion Useful to Estimate Undesirable Products

In this study, the life cycle assessment (LCA) principle was performed to estimate the environmental impact of three dairy farms that operate using different farming systems, namely, conventional (CON), organic (ORG), and high-quality (HQ) modes. In Italy, the typical style of high-quality (HQ) farming is commonly included in the conventional system but is more strictly regulated by the Decree of the Italian Ministry of Health N° 185/1991. Although the farms are not fully representative of each conduct, they showed intrinsic peculiarities, e.g., the cow-culling rate of each system. This rate requires a quantification as it may be related to loss of income. Allocation criteria were applied to attribute the quantities of pollutants to the co-products: wheat, involved in the congruence and number of cows culled, the latter being undesirable and therefore necessary to quantify. Analysis of variance (ANOVA) highlighted that the no-dairy products significantly mitigated (p < 0.05) some of the impacts’ categories. The allocation of culled cows decreased the impacts of the CON and particularly those of the ORG farms when the mass mode was adopted. HQ showed values similar to the results without allocation. Overall, the objective of identifying a “marker” of undesirable products, estimated by the culling rate, was partially achieved.

Hydroponic fodder and greenhouse gas emissions: a potential avenue for climate mitigation strategy and policy development

This research explores the potential hydroponic systems have for contributing to climate mitigation in fodder agriculture. Using British Columbia (BC) and Alberta as case studies, the study compares greenhouse gas (GHG) emissions and carbon sequestration potential of hydroponically grown sprouted barley fodder to conventional barley grain fodder. GHG emissions were examined through scenarios that assumed Alberta to be the main barley producer, while exploring different situations of BC and Alberta as consumers, distributed/centralized hydroponic systems, and renewable/nonrenewable energy. Carbon sequestration opportunities were examined through scenarios that explored the land sparing potential of transitioning from conventional to hydroponic barley and shifts from tillage to no-tillage practices. Sensitivity analyses were done to examine how changes in hydroponic seed-to-fodder output and energy consumption affect the systems’ climate mitigation potential. The results indicated that incorporating hydroponic systems into barley production has the potential to reduce GHG emissions, given seed-to-fodder output and energy consumption are maintained at certain levels and the systems are powered by renewable energy. Results also showed that hydroponic farming can provide greater carbon sequestration opportunities than simply shifting to no-tillage farming. The research indicates that hydroponic fodder farming could contribute to climate mitigation objectives if complemented with effective energy and land use policies.

Research on Environmental, Economic, and Social Sustainability in Dairy Farming: A Systematic Mapping of Current Literature

Dairy cows are able to convert fibrous materials, such as grass, roughage, and by-products from the food industry, into milk and meat, which justifies their role in food production. However, modern dairy farming is associated with major sustainability challenges, including greenhouse gas emissions. In order to develop sustainable future production, it is important to implement existing knowledge and fill knowledge gaps. The aim of this study was to systematically map the scientific literature on environmental, economic, and social sustainability at farm level in dairy farming. Literature published between January 2000 and March 2020 and with the geographical focus on Europe, North America, and Australia–New Zealand was included. In total, the literature search resulted in 169 hits, but after removing duplicates and papers outside the study scope only 35 papers remained. Of these, only 11 dealt with the three dimensions of sustainability, and several of these only mentioned one or two of the dimensions or set them in relation to that/those actually studied. Overall, the selected literature did not clearly explain how aspects of sustainability are interlinked, so possible negative or positive interactions between different aspects of sustainability dimensions remain unidentified.

Energy Consumption on Dairy Farms: A Review of Monitoring, Prediction Modelling, and Analyses

The global consumption of dairy produce is forecasted to increase by 19% per person by 2050. However, milk production is an intense energy consuming process. Coupled with concerns related to global greenhouse gas emissions from agriculture, increasing the production of milk must be met with the sustainable use of energy resources, to ensure the future monetary and environmental sustainability of the dairy industry. This body of work focused on summarizing and reviewing dairy energy research from the monitoring, prediction modelling and analyses point of view. Total primary energy consumption values in literature ranged from 2.7 MJ kg−1 Energy Corrected Milk on organic dairy farming systems to 4.2 MJ kg−1 Energy Corrected Milk on conventional dairy farming systems. Variances in total primary energy requirements were further assessed according to whether confinement or pasture-based systems were employed. Overall, a 35% energy reduction was seen across literature due to employing a pasture-based dairy system. Compared to standard regression methods, increased prediction accuracy has been demonstrated in energy literature due to employing various machine-learning algorithms. Dairy energy prediction models have been frequently utilized throughout literature to conduct dairy energy analyses, for estimating the impact of changes to infrastructural equipment and managerial practices.

Improving Policy Evidence Base for Agricultural Sustainability and Food Security: A Content Analysis of Life Cycle Assessment Research

Life cycle assessment is a widespread method for measuring and monitoring the environmental impacts of production processes, thereby allowing the comparison of business-as-usual with more ecological scenarios. Life cycle assessment research can support evidence-based policy making by comparing and communicating the environmental impacts of agricultural and food systems, informing about the impact of mitigating interventions and monitoring sectoral progress towards sustainable development goals. This article aims at improving the contribution of science to evidence-based policies for agricultural sustainability and food security, while facilitating further research, by delivering a content-analysis based literature review of life cycle assessment research in agricultural and food economics. Results highlight that demand-side and system-level approaches need further development, as policies need to support redesigned agricultural systems and newly conceived dietary guidelines, which combine environmental protection and health benefits, without reducing productivity. Similarly, more research effort towards consequential life cycle assessment and multidimensional assessment may benefit policy makers by considering the rebound effects associated with the large-scale implementation of impact-mitigating interventions. Promising interventions involve the promotion of waste circularization strategies, which could also improve the profitability of agriculture. For effective policy making towards agricultural sustainability and food security worldwide, countries with the greatest expected population growth and raise of urbanization rates need more attention by researchers.

Environmental impacts and resource use of milk production on the North China Plain, based on life cycle assessment

Life cycle assessment methodology was used to quantify the environmental impacts and resource use of milk production on the North China Plain, the largest milk production area in China. Variation in environmental burden caused by cow productivity was evaluated, as well as scenario analysis of the effects of improvement practices. The results indicated that the average environmental impact potential and resource use for producing 1kg of fat and protein corrected milk was 1.34kgCO₂eq., 9.27gPO₄^3-eq., 19.5gSO₂eq., 4.91MJ, 1.83m² and 266L for global warming potential (GWP), eutrophication potential (EP), acidification potential (AP), non-renewable energy use (NREU), land use (LU) and blue water use (BWU; i.e. water withdrawal), respectively. Feed production was a significant determinant of GWP, NREU, LU and BWU, while AP and EP were mainly affected by manure management. Scenario analysis showed that reducing use of concentrates and substituting with alfalfa hay decreased GWP, EP, AP, NREU and LU (by 1.0%-5.5%), but caused a significant increase of BWU (by 17.2%). Using imported soybean instead of locally-grown soybean decreased LU by 2.6%, but significantly increased GWP and NREU by 20% and 6.9%, respectively. There was no single perfect manure management system, with variable effects from different management practices. The environmental burden shifting observed in this study illustrates the importance of assessing a wide range of impact categories instead of single or limited indicators for formulating environmental policies, and the necessity of combining multiple measures to decrease the environmental burden. For the North China Plain, improving milking cow productivity and herd structure (i.e. increased proportion of milking cows), combining various manure management systems, and encouraging dairy farmers to return manure to nearby crop lands are promising measures to decrease multiple environmental impacts.

Milk production Life Cycle Assessment: A comparison between estimated and measured emission inventory for manure handling

Measuring emissions from manure management operations (from the barns to the land) is a challenging task, subject to different uncertainties related to the spatial-temporal variability in the process leading to gaseous release. At the same time, emissions inventory is a prerequisite of Life Cycle Assessment (LCA) studies. Manure management emissions are usually estimated using equations developed by Intergovernmental Panel on Climate Change (IPCC, in the case of greenhouse gases emissions) and European Environmental Agency (EEA) for Nitrogen-related emissions. In the present study, the environmental impacts associated to three Italian dairy farms were calculated through a comparative LCA using two different approaches for complying the emission inventory. In the "estimated" approach (E) the commonly adopted IPCC and EEA equations were used, while in the "measured" approach (M) emissions actually measured were taken as input data to quantify the emissions associated to manure management. The results showed that the IPCC equation underestimates the manure management emissions, leading to a 10-42% lower global warming potential comparing E to M approach. On the other hand, ammonia related impact categories showed higher values if they were calculated using the estimated approach, underling that a safer level of estimation is maintained.

A review of whole farm-system analysis in evaluating greenhouse-gas mitigation strategies from livestock production systems

Recognition is increasingly given to the need of improving agricultural production and efficiency to meet growing global food demand, while minimising environmental impacts. Livestock forms an important component of global food production and is a significant contributor to anthropogenic greenhouse-gas (GHG) emissions. As such, livestock production systems (LPS) are coming under increasing pressure to lower their emissions. In developed countries, LPS have been gradually reducing their emissions per unit of product (emissions intensity; EI) over time through improvements in production efficiency. However, the global challenge of reducing net emissions (NE) from livestock requires that the rate of decline in EI surpasses the productivity increases required to satisfy global food demand. Mechanistic and dynamic whole farm-system models can be used to estimate farm-gate GHG emissions and to quantify the likely changes in farm NE, EI, farm productivity and farm profitability as a result of applying various mitigation strategies. Such models are also used to understand the complex interactions at the farm-system level and to account for how component mitigation strategies perform within the complexity of these interactions, which is often overlooked when GHG mitigation research is performed only at the component level. The results of such analyses can be used in extension activities and to encourage adoption, increase awareness and in assisting policy makers. The present paper reviews how whole farm-system modelling has been used to assess GHG mitigation strategies, and the importance of understanding metrics and allocation approaches when assessing GHG emissions from LPS.

An analysis on how switching to a more balanced and naturally improved milk would affect consumer health and the environment

This study compares a premium brand of UHT milk, Unicla, characterised by an improved nutritional composition, to conventional milk, in terms of health effects and environmental impacts. Unlike enriched milks, in which nutrients are added to the final product, Unicla is obtained naturally by improving the diet of the dairy cows. Health effects have been analysed based on literature findings, while the environmental analysis focused on those spheres of the environment where milk is expected to cause the higher impacts, and thus carbon (CF) and water footprints (WF) have been determined. Five final products have been compared: 3 conventional (skimmed, semi-skimmed, whole) and 2 Unicla (skimmed, semi-skimmed) milks. As a functional unit, one litre of packaged UHT milk entering the regional distribution centre has been chosen. The improved composition of Unicla milk is expected to decrease the risk of cardiovascular disease and to protect consumers against oxidative damage, among other health benefits. Concerning the environmental aspect, CF of Unicla products are, on average, 10% lower than their conventional equivalents, mainly due to the lower enteric emissions of caused by the Unicla diet. No significant differences were found between the WF of Unicla and conventional milk. Raw milk is the main contributor to both footprints (on average, 83.2 and 84.3% of the total CF of Unicla and conventional milk, respectively, and 99.9% of WF). The results have been compared to those found in literature, and a sensitivity analysis has been performed to verify their robustness. The study concludes that switching to healthier milk compositions can help slowing down global warming, without contributing to other environmental issues such as water scarcity. The results should encourage other milk companies to commit to the development of healthier, less environmentally damaging products, and also to stimulate consumers to bet on them.

Mitigating the environmental impacts of milk production via anaerobic digestion of manure: case study of a dairy farm in the Po Valley

This work analyzes the environmental impacts of milk production in an intensive dairy farm situated in the Northern Italy region of the Po Valley. Three manure management scenarios are compared: in Scenario 1 the animal slurry is stored in an open tank and then used as fertilizer. In scenario 2 the manure is processed in an anaerobic digestion plant and the biogas produced is combusted in an internal combustion engine to produce heat (required by the digester) and electricity (exported). Scenario 3 is similar to scenario 2 but the digestate is stored in a gas-tight tank. In scenario 1 the GHG emissions are estimated to be equal to 1.21 kg CO2 eq.kg(-1) Fat and Protein Corrected Milk (FPCM) without allocation of the environmental burden to the by-product meat. With mass allocation, the GHG emissions associated to the milk are reduced to 1.18 kg CO2 eq.kg(-1) FPCM. Using an economic allocation approach the GHG emissions allocated to the milk are 1.13 kg CO2 eq.kg(-1) FPCM. In scenarios 2 and 3, without allocation, the GHG emissions are reduced respectively to 0.92 (-23.7%) and 0.77 (-36.5%) kg CO2 eq.kg(-1) FPCM. If land use change due to soybean production is accounted for, an additional emission of 0.53 kg CO2 eq. should be added, raising the GHG emissions to 1.74, 1.45 and 1.30 kg CO2 eq kg(-1) FPCM in scenarios 1, 2 and 3, respectively. Primary energy from non-renewable resources decreases by 36.2% and 40.6% in scenarios 2 and 3, respectively, with the valorization of the manure in the biogas plant. The other environmental impact mitigated is marine eutrophication that decreases by 8.1% in both scenarios 2 and 3, mostly because of the lower field emissions. There is, however, a trade-off between non-renewable energy and GHG savings and other environmental impacts: acidification (+6.1% and +5.5% in scenarios 2 and 3, respectively), particulate matter emissions (+1.4% and +0.7%) and photochemical ozone formation potential (+41.6% and +42.3%) increase with the adoption of a biogas plant. The cause of the increase is mostly emissions from the CHP engine. These impacts can be tackled by improving biogas combustion technologies to reduce methane and NOx emissions. Freshwater eutrophication slightly increases (+0.8% in both scenarios 2 and 3) because of the additional infrastructures needed. In conclusion, on-farm manure anaerobic digestion with the production of electricity is an effective technology to significantly reduce global environmental impacts of dairy farms (GHG emissions and non-renewable energy consumption), however local impacts may increase as a consequence (especially photochemical ozone formation).