Farm Emissions Research Articles

Financial Barriers to Reducing Nitrogen Pollution in Dutch Dairy Farms

SummaryNitrogen fertiliser boosts agricultural yields, but its excessive use destabilises ecosystems. That is why Dutch policy makers want to reduce nitrogen pollution on dairy farms. Cleaner technologies and structural changes could reduce farm emissions. We benchmarked farms, organised an expert consultation, and reviewed the literature to determine the degree to which the lack of available internal and external finance is a barrier to reducing nitrogen pollution. Although the average dairy farm in our sample can finance these investments, a significant share of farmers cannot. We find that investments vastly drain the currently accessible finances available to dairy farmers. Subsidies to reduce the price of investments and measures to increase farm net cash flows could mitigate this problem, while equity funds or preferential interest rate systems would be ineffective. Farm management is not bound by access to finance. Our findings suggest that improved management could vastly reduce the accumulation of nitrogen surplus on farms. Interestingly, we estimate that this can be achieved while increasing profits. The wide‐scale adoption of best practices can be facilitated by establishing and financing advisory services and peer learning programmes to spread knowledge and awareness.

Comparative Study of Fatty Acid Composition of Muscles of Atlantic Cod (Gadus morhua Linnaeus, 1758) with Natural Diet and Feeding near Salmon Farms

Coastal aquaculture and local fisheries interact in shared marine environments, influencing each other synergistically and/or antagonistically. Salmon farming, notably with open-net sea cages along the Norwegian coast, attracts wild fish due to increased food availability from uneaten feed, but it also exposes wild fish to farm emissions like waste and toxic chemicals (de-lice treatments, antifouling and medical agents). The attraction behaviour of wild fish can impact fatty acid composition in fish tissues, influenced by the high terrestrial fat content in salmon aquafeed. We study how the Atlantic cod, aggregating around salmon farms in a subarctic fjord in Northern Norway, can be affected, potentially altering their natural diet and fatty acid profiles. Our study compares the muscle-tissue fatty acid compositions of cod caught near aquaculture facilities (impact) versus fish caught in neighbouring fjords (control), and we hypothesise decreased omega-3 fatty acids near farms. The analysis revealed no significant differences in the fatty acid concentrations or categories between the impacted and control fish, challenging our initial expectations. However, differences were found for C18:1(n9)t (elaidic acid), with a higher value in the impacted fish. These findings suggest that salmon farming’s influence on cod’s fatty acid profiles in the flesh (i.e., relevant for the nutritional quality of the fillets that consumers eat) may be limited or minimal despite their aggregative behaviours around farms. The threshold levels of salmon feed consumed by wild cod before it affects the quality and survival of, e.g., sperm or other life stages, are not known and require new investigations. This study underscores the complexity of interactions between aquaculture and wild fisheries, impacting both ecological dynamics and consumer perspectives on seafood quality and health benefits.

Strategizing emissions reduction investment for a livestock production farm amid power demand pattern: A path to sustainable growth under the carbon cap environmental regulation

Livestock production companies come under increasing responsibility to reduce their environmental impact, and thereby, the simultaneous decision-making of inventory replenishment and emissions reduction investment has become essential for ensuring sustainable development in the livestock farming business. This study investigates, for the first time, the best investment strategy for a livestock farming business under the carbon cap (CC) environmental legislation, taking into account both the edible and non-edible parts of slaughtering mature growing items (GIs) after procuring and feeding baby GIs. By fusing economic and environmental factors, this study aims to shed light on two crucial issues: (i) figuring out the appropriate level of investment needed for the farm to adhere to the CC environmental regulation; and (ii) evaluating the effect of the investment decision on the farm's expenses and emissions levels. To deal with these insights, a thorough analytical framework integrating mathematical modeling methodology, economic evaluation, and carbon accounting approaches is employed. By analyzing the interaction between the farm's emissions reduction investments and replenishment choices, the cost-effective investment level is determined that enables the farm to satisfy the carbon cap obligation while guaranteeing maximum operational efficiency. The results of this study have important ramifications for livestock farming businesses trying to make their way through the stringent CC emission law. The results indicate that in order to keep the business feasible when the cap of the CC guideline is low, the livestock-producing farm should give priority to investing in minimizing feed emissions and using cutting-edge manure treatment methods.

Assessment of bioenergy plant locations using a GIS-MCDA approach based on spatio-temporal stability maps of agricultural and livestock byproducts: A case study

Addressing the global challenge of energy sustainability and global directives on farming emissions, the United Nations, the European Union, and China have led with strict targets for clean energy, renewable share growth, and carbon neutrality, highlighting a commitment to collective sustainability. This work is situated within the ambit of the Sustainable Development Goals (SDGs), advocating for a transition towards renewable energy sources. With substantial and accessible bioenergy resources, notably in Hubei Province, China, biogas technology has emerged as an emission-cutting solution. This research, focused on the Jianghan Plain, employs an integrated approach combining spatial analyses with machine learning tools to evaluate crop yield stability over two decades, with the aim of maximising the biogas yield from agricultural byproducts, i.e., crop straw and livestock manure. Using Multi-Criteria Decision Analysis (MCDA), which is informed by grey-based DEMATEL, 9 constraints and 13 environmental, social, and economic criteria were assessed to identify optimal sites for biogas facilities. The findings underscore the significant bioenergy potential of agricultural byproducts from the plain of 6.3 × 1012 kJ/year at an 11.4 kJ/m2 density. Stability analyses revealed consistent biomass availability, with rice in Gongan and Shayang and wheat in Jiangling being the primary contributors. Through the MCDA, 45–66 optimal biogas plants were identified across 4 critical counties (Zhongxiang, Shangyang, Jingshan, and Yichen), balancing the energy supply and demand under various stable scenarios. Furthermore, this study demonstrated the criticality of moderate biomass stability for stakeholder consensus and identified areas of high stability essential for energy demand fulfilment. Theoretically, this study offers a practical model for bioenergy resource exploitation that aligns with global sustainability and carbon neutrality goals to address the urgent need for renewable energy solutions amidst the global energy crisis. Practically, this study sets a precedent for policy and planning in environmental, agricultural, and renewable sectors, signifying a step forwards in achieving environmental sustainability and an energy-efficient future.

Citizens' willingness to support farmers’ adoption of low crude protein diet in pig production

Livestock farming has a detrimental effect on the environment since it generates a lot of gas emissions. In pig farming, the use of feed is among the substantial sources of animal farm emissions among the European Union. Nevertheless, the use of Low Dietary Crude Protein (LCP) may reduce the environmental impacts of pig farming and provide diverse ecosystem services (ESs). Concurrently, these pig diets alternatives may result more expensive than the conventional ones, which may negatively affect farmers' intention to adopt these alternatives. Citizens’ payment for ESs may be a viable strategy to motivate farmers to implement more sustainable pig diets. The primary objective of this study is to assess the extent to which citizens of Catalonia (Spain) are willing to pay for the ESs generated by the implementation of a LCP diet in pig production. In pursuit of this goal, we conducted an online survey among 501 citizens, including a Discrete Choice Experiment. Participants evaluated three feed scenarios, and their choices were scrutinized using conditional logit model. Results revealed that citizens prefer the new pig diets, including both LCP and Very LCP (VLCP) diets, over the conventional pig diet. However, there is a clear preference toward the VLCP diet justified by their willingness to pay (WTP) of €67/year/adult.

Innovative Strategies for Sustainable Dairy Farming in Canada amidst Climate Change

In recent years, the Canadian dairy sector has faced escalating challenges due to its significant contribution to greenhouse gas emissions, particularly methane. This paper critically examines a spectrum of innovative techniques aimed at mitigating methane emissions within this sector, scrutinizing their cost-effectiveness, efficiency, compatibility with animal welfare standards, and adherence to both existing and prospective Canadian environmental legislations. The discourse begins with an exhaustive overview of contemporary methane reduction methodologies relevant to dairy farming, followed by a rigorous analysis of their economic feasibility. This includes a detailed cost-benefit analysis, juxtaposed with the efficiency and technological advancements these techniques embody. A pivotal aspect of this examination is the alignment of animal welfare with emission reduction objectives, ensuring that the strategies employed do not compromise the health and well-being of dairy cattle. Furthermore, the paper delves into the legislative landscape of Canada, evaluating the congruence of these techniques with current environmental laws and anticipating future regulatory shifts. Performance indicators for emission reduction are critically assessed, establishing benchmarks tailored to the Canadian context. This is complemented by an exploration of the market potential of these innovations, including factors influencing their adoption and scalability in the market. The analysis culminates with a synthesis of case studies and best practices within Canada, offering insights into successful implementations and drawing lessons for future endeavors. This comprehensive approach not only addresses the immediate environmental and health impacts associated with dairy farming emissions but also significantly contributes to the overarching goal of sustainable development in the agricultural sector. The research presented in this paper holds significant implications for the future of sustainable dairy farming, offering a model for addressing environmental challenges while maintaining economic viability and animal welfare.

Short-term residential exposure to endotoxin emitted from livestock farms in relation to lung function in non-farming residents

BackgroundEvidence on the public health relevance of exposure to livestock farm emissions is increasing. Research mostly focused on chemical air pollution, less on microbial exposure, while endotoxins are suggested relevant bacterial components in farm emissions. Acute respiratory health effects of short-term exposure to livestock-related air pollution has been shown for NH3 and PM10, but has not yet been studied for endotoxin. We aimed to assess associations between lung function and short-term exposure to livestock farming emitted endotoxin in co-pollutant models with NH3 and PM10. MethodsIn 2014/2015, spirometry was conducted in 2308 non-farming residents living in a rural area in the Netherlands. Residential exposure to livestock farming emitted endotoxin during the week prior to spirometry was estimated by dispersion modelling. The model was applied to geo-located individual barns within 10 km of each home address using provincial farm data and local hourly meteorological conditions. Regional week-average measured concentrations of NH3 and PM10 were obtained through monitoring stations. Lung function parameters (FEV1, FVC, FEV1/FVC, MMEF) were expressed in %-predicted value based on GLI-2012. Exposure-response analyses were performed by linear regression modelling. ResultsWeek-average endotoxin exposure was negatively associated with FVC, independently from regional NH3 and PM10 exposure. A 1.1% decline in FVC was estimated for an increase of endotoxin exposure from 10th to 90th percentile. Stratified analyses showed a larger decline (3.2%) for participants with current asthma and/or COPD. FEV1 was negatively associated with week-average endotoxin exposure, but less consistent after co-pollutant adjustment. FEV1/FVC and MMEF were not associated with week-average endotoxin exposure. ConclusionsLower lung function in non-farming residents was observed in relation to short-term residential exposure to livestock farming emitted endotoxin. This study indicates the probable relevance of exposure to microbial emissions from livestock farms considering public health besides chemical air pollution, necessitating future research incorporating both.

Assessing the carbon footprint in dairy cattle farms in the northern temperate region of Spain

The availability of models constitutes a key factor when selecting a decision support tool aimed at improving the production and environmental aspects of farms. There is a need for robust models that are user-friendly, facilitating the estimation of farm emissions and the analysis of their temporal fluctuations. The objectives of this study were i) to calculate both the partial (PCF) and total carbon (TCF) footprints of 212 dairy farms, distinguishing those with and without maize cultivation; ii) to identify critical variables related to feed, nutrition, productivity and environmental efficiency; and iii) to formulate and validate prediction equations based on available data from dairy farms. The database encompasses information from 212 dairy cattle farms situated in the temperate-humid zone of northern Spain, spanning the period from 2014 to 2018. Farm classification was based on the presence (CcMz) or absence (ScCMz) of maize cultivation for silage production, resulting in 96 farms in the CcMz category and 116 farms in the ScCMz category.Among the variables considered, the variable herd N-use efficiency (NUECR) for (PCF) showed the lowest root mean square error of prediction at 0.39% and the correspondingly lowest root men. The root mean squared percentage error (RMSPE): standard deviation ratio (RSR) at 0.52. In the case of total carbon footprint (TCF), herd N-use efficiency (NUECR) again showed the lowest root mean square error of prediction at 0.52%. Regarding TCF, herd feed efficiency (EACR) was the variable with the lowest both RMSPE and RSR, with 0.65 and 0.64, respectively. Consequently, the estimation of the PCF and TCF of 1 ​kg of milk from the temperate-humid zone of northern Spain at the farm gate can be feasibly accomplished utilizing NUECR and EACR, respectively.

22 Greenhouse Gas Emission Measurement and Modeling in Complex Beef Production Systems

Abstract Measuring and modeling gas emissions from cattle production pose unique challenges due to the complex nature of these systems. Several methods exist for measuring gas emissions including chambers, tracers, open path lasers, and eddy covariance systems. Each method comes with challenges and benefits. Accurate measurements are crucial for accounting and model development. Simple emission factor methods of accounting require less data but fail to represent dynamic factors that drive emissions. Whole farm emissions will vary depending on several factors including region, cattle breed and age, diet, climate, and manure management. Dynamic models provide more representative emissions, but require far more data, sophisticated software, and are not always user friendly.

Life cycle assessment of greenhouse gas emission from the dairy production system - review.

Climate change is altering ecological systems and poses a serious threat to human life. Climate change also seriously influences on livestock production by interfering with growth, reproduction, and production. Livestock, on the other hand, is blamed for being a significant contributor to climate change, emitting 8.1 gigatonnes of CO2-eq per year and accounting for two-thirds of global ammonia emissions. Methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2) are three major greenhouse gases (GHG) that are primarily produced by enteric fermentation, feed production, diet management, and total product output. Ruminants account for three-quarters of total CO2-equivalent (CO2-eq) emissions from the livestock sector. The global dairy sector alone emits 4.0% of global anthropogenic GHG emissions. Hence, dairy farming needs to engage in environmental impact assessment. Public concern for a sustainable and environmentally friendly farming system is growing, resulting in the significant importance of food-based life cycle assessment (LCA). Over the last decade, LCA has been used in agriculture to assess total GHG emissions associated with products such as milk and manure. It includes the production of farm inputs, farm emissions, milk processing, transportation, consumer use, and waste. LCA studies on milk production would assist us in identifying the specific production processes/areas that contribute to excessive greenhouse gas emissions when producing milk and recommending appropriate mitigation strategies to be implemented for a clean, green, and resilient environment.

Data-driven agent-based modelling of incentives for carbon sequestration: The case of sown biodiverse pastures in Portugal

Sown biodiverse permanent pastures rich in legumes (SBP) offset animal farming emissions due to their potential to sequester carbon. From 2009 to 2014 Portugal implemented a programme that provided payments to incentivize the adoption of SBP. However, no proper evaluation of its outcome was conducted. To address this gap, we develop an agent-based model (ABM) at the municipality level to study the adoption of SBP in Portugal and assess the outcome of the programme. We applied the first pure data-driven approach in agricultural land-use ABM, which relies on machine learning algorithms to define the agents’ behavioural rules and capture their interaction with biophysical conditions. The ABM confirms that the program effectively expanded the adoption of SBP. However, our estimates indicate that the adoption rate in the absence of payments would have been higher than originally predicted. Furthermore, the existence of the program decreased the adoption rate after its conclusion. These findings underscore the importance of using reliable models and considering residual effects to properly design land use policies. The ABM developed in this study provides a basis for future research aimed at supporting the development of new policies to further promote the adoption of SBP.

Residential exposure to livestock farms and lung function in adolescence – The PIAMA birth cohort study

BackgroundThere is a growing interest in the impact of air pollution from livestock farming on respiratory health. Studies in adults suggest adverse effects of livestock farm emissions on lung function, but so far, studies involving children and adolescents are lacking. ObjectivesTo study the association of residential proximity to livestock farms and modelled particulate matter ≤10 μm (PM10) from livestock farms with lung function in adolescence. MethodsWe performed a cross-sectional study among 715 participants of the Dutch prospective PIAMA (Prevention and Incidence of Asthma and Mite Allergy) birth cohort study. Relationships of different indicators of residential livestock farming exposure (distance to farms, distance-weighted number of farms, cattle, pigs, poultry, horses and goats within 3 km; modelled atmospheric PM10 concentrations from livestock farms) with forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) at age 16 were assessed by linear regression taking into account potential confounders. Associations were expressed per interquartile range increase in exposure. ResultsHigher exposure to livestock farming was consistently associated with a lower FEV1, but not with FVC among participants living in less urbanized municipalities (<1500 addresses/km2, N = 402). Shorter distances of homes to livestock farms were associated with a 1.4% (0.2%; 2.7%) lower FEV1. Larger numbers of farms within 3 km and higher concentrations of PM10 from livestock farming were associated with a 1.8% (0.8%, 2.9%) and 0.9% (0.4%,1.5%) lower FEV1, respectively. ConclusionsOur findings suggest that higher exposure to livestock farming is associated with a lower FEV1 in adolescents. Replication and more research on the etiologic agents involved in these associations and the underlying mechanisms is needed.

Decisions Decisions – A Farmer's Mitigation Dilemma

Livestock producers are under rising pressure to nourish a growing population while simultaneously reducing the impact of meat/milk production on the planets’ climate. Decision Support Tools (DST) provide a valuable evidence-based decision-making framework in agriculture to improve productivity and environmental outputs. Decision Support Tools are often developed and designed by local stakeholders and tend to represent their national system. While current DSTs may be used to examine the impact of management choices on farm emissions, there are relatively few tools available for Irish farms that take into account both the environmental and financial aspects of decision-making. This research will improve existing farm scale descision support systems designed to cost effectively mitigate Green House Gas emissions from livestock production systems.

Implications of large‐scale miscanthus cultivation in water protection areas: A Life Cycle Assessment with model coupling for improved policy support

AbstractTwo major global challenges related to agriculture are climate change and the unbalanced nitrogen cycle. For both, national and international reduction targets have been defined to catalyse policy support for more sustainable farming systems. Miscanthus cultivation in water protection areas has been proposed as a contribution to achieving these targets. However, a thorough understanding of the underlying system dynamics at various spatial levels is required before recommendations for policy development can be provided. In this study, a model framework was established to provide economic and environmental indicator results at regional and sub‐regional levels. It presents a consequential Life Cycle Assessment coupled with an agro‐economic supply model (Economic Farm Emission Model) that simulates crop and livestock production, and an agricultural hydrology model (DAISY) that assesses effects on the nitrogen cycle. The framework is applied to Baden‐Württemberg, a federal state in southwest Germany with eight agro‐ecological regions. Scenarios investigating the differences between mandatory and voluntary miscanthus cultivation were also explored. While the results show the high potential of miscanthus cultivation for the reduction of greenhouse gas emissions (−16% to −724%), the potential to reduce nitrate leaching (−4% to −44%) is compromised in some sub‐regions and scenarios (+4% to +13%) by substantial effects on the crop rotation. Furthermore, the cultivation of miscanthus reduces gross margins in most sub‐regions (−0.1% to −9.6%) and decreases domestic food production (−1% to −50%). However, in regions with low livestock density and high yields, miscanthus cultivation can maintain or increase farmers' income (0.1%–5.8%) and improve environmental protection. The study shows that the heterogeneity of arable land requires a flexible promotion programme for miscanthus. Voluntary cultivation schemes were identified as most suitable to capture sub‐regional differences. Policies should address the demand for miscanthus, for example, support the development of regional value chains, including farmers, water suppliers and the biobased industry.

Oil tank farm emission trends of Russian refineries

The oil refining industry has an important position in the Russian economy. However, most of the country’s oil refineries have outdated production capacities of tank farms for storing oil, and the issue of emissions from Russian refineries is a research gap in this area. The aim of this study was to identify the dynamics of changes in the amounts of emissions from tank farms for oil storage in Russian refineries. A study period from 2008 to 2018 was considered. The contributions of this study include the development of methods for estimating emissions for the regions. In this study, an approach was developed that, based on the existing expressions of the unified methodology, allows us to estimate the emissions of tank farms at a regional scale.The results showed that the greatest emissions occurred in the Volga Federal District. The volume of emissions from that region exceeded the total emissions of the next three districts: the Central, Siberian, and Northwestern Federal Districts of Russia. The largest growth rate of emissions was demonstrated by the refineries of the Southern Federal District, exceeding those of the Central, Siberian, and Northwestern Federal Districts during the study period. In the Far Eastern and Ural federal districts of the country, annual emissions were much lower. During the study period, the total accumulated emissions exceeded 2.5 million tons; therefore, the country needs to carry out work to modernize the tank farms of oil refineries in accordance with the proposed direction.

Methane emissions from five Danish pig farms: Mitigation strategies and inventory estimated emissions

This study investigated whole-farm methane emissions from five Danish pig farms with different manure management practices and compared measured emission rates to international and national greenhouse gas inventory emission models. Methane emissions were quantified by using the tracer gas dispersion method. Farms were measured between five and eight times throughout a whole year. One of the farms housed sows and weaners (P1) and the others focused on fattening pigs (P2–P5). The farms had different manure treatment practices including biogasification (P3), acidification (P4–P5) and no manure treatment (liquid slurry) (P1–P2). Quantified methane emissions ranged from 0.2 to 20 kg/h and the highest rates were seen at the farms with fattening pigs and with no manure treatment (P2), while the lowest emissions were detected at farms with manure acidification (P4 and P5). Average methane emission factors (EFs), normalised based on livestock units, were 14 ± 6, 18 ± 9, 8 ± 7, 2 ± 1 and 1 ± 1 g/LU/h, for P1, P2, P3, P4 and P5, respectively. Emissions from fattening pig farms with biogasification (P3) and acidification (P4–P5) facilities were 55% and 91–93% lower, respectively, than from farm with no manure treatment (P2). Inventory models underestimated farm-measured methane emissions on average by 51%, across all models and farms, with the Danish model performing the worst (underestimation of 64%). A revision of model parameters related to manure emissions, such as the estimation of volatile solids excreted and methane conversion factor parameters, could improve model output, although more data needs to be collected to strengthen the conclusions. As one of the first studies assessing whole-pig farm emissions, the results showed the potential of the applied measuring method to identify mitigation strategy efficiencies and highlighted the necessity to investigate inventory model accuracy.

LASAM Model: An Important Tool in the Decision Support System for Policymakers and Farmers

Today’s global food system (including production, transportation, processing, packing, storage, retail sale, consumption, losses and waste) provides income to more than a billion people all over the world and makes up a significant part of many countries’ economies. The 21st century’s food systems that bring food from “farm to fork” face various challenges, including a shortage of agricultural land and water, competition with the energy industry, changes in consumption preferences, a rising global population, negative effects of climate change, etc. Therefore, many countries are working on creating various models to function as an important decision support system tool for policymakers, farmers and other stakeholders. Various agricultural sector models see particularly extensive use in the European Union (EU), determining the impact of the Common Agricultural Policy (CAP) and helping to create future development scenarios. This is why a special model adapted to the national conditions, called LASAM (Latvian Agricultural Sector Analysis Model), was created in Latvia, making it possible to use historical data on the development of agricultural sectors, medium-term price projections for agricultural products in the EU, changes in support policy, as well as the necessity for the resources used to project the long-term (up to 2050) development of agriculture. The LASAM model covers the crop sector, the animal sector and the overall socioeconomic development, as well as the growth of organic farming and greenhouse gas (GHG) emissions. This paper discusses the main objectives achieved in developing a decision support tool and presenting the research results: LASAM was used to prepare projections of the possible development of Latvia’s principal sectors of agriculture until 2050, considering the necessity to reduce GHG emissions, made available through the LASAM web application. Given that the projection data obtained by LASAM are public, they can be used (1) for national policy making in rural business development, which affects the development of the economy as a whole; and (2) internationally, to compare the projections made in Latvia with those obtained through various agricultural sector models and projected development trends.

Farm-level emission intensities of smallholder cattle (Bos indicus; B. indicus–B. taurus crosses) production systems in highlands and semi-arid regions

Ruminants are central to the economic and nutritional life of much of sub-Saharan Africa, but cattle are now blamed for having a disproportionately large negative environmental impact through emissions of greenhouse gas (GHG). However, the mechanism underlying excessive emissions occurring only on some farms is imperfectly understood. Reliable estimates of emissions themselves are frequently lacking due to a paucity of reliable data. Employing individual animal records obtained at regular farm visits, this study quantified farm-level emission intensities (EIs) of greenhouse gases of smallholder farms in three counties in Western Kenya. CP was chosen as the functional unit to capture the outputs of both milk and meat. The results showed that milk is responsible for 80–85% of total CP output. Farm EI ranged widely from 20 to >1 000 kg CO2-eq/kg CP. Median EIs were 60 (Nandi), 71 (Bomet), and 90 (Nyando) kg CO2-eq/kg. Although median EIs referenced to milk alone (2.3 kg CO2-eq/kg milk) were almost twice that reported for Europe, up to 50% of farms had EIs comparable to the mean Pan-European EIs. Enteric methane (CH4) contributed >95% of emissions and manure ∼4%, with negligible emissions attributed to inputs to the production system. Collecting data from individual animals on smallholder farms enabled the demonstration of extremely heterogeneous EI status among similar geographical spaces and provides clear indicators on how low EI status may be achieved in these environments. Contrary to common belief, our data show that industrial-style intensification is not required to achieve low EI. Enteric CH4 production overwhelmingly drives farm emissions in these systems and as this is strongly collinear with nutrition and intake, an effort will be required to achieve an “efficient frontier” between feed intake, productivity, and GHG emissions.

Ecosystem accounting to support the Common Agricultural Policy

The System of Environmental-Economic Accounting - Ecosystem Accounting (SEEA EA) provides an integrated statistical framework which organizes spatially explicit data on environmental quality, natural capital and ecosystem services and links this information to economic activities such as agriculture. In this paper we assess how the SEEA EA can support the monitoring and evaluation of environmental objectives of the Common Agricultural Policy (CAP). We focus on the Netherlands, for which an elaborate set of SEEA EA accounts has been published, and the themes of nitrogen pollution and farmland biodiversity. We studied the completeness of indicators included in the accounts, their quality and analysed how the accounts could support agri-environmental reporting, agri-environmental measures effectiveness assessments, and results-based payments to farmers. As a reference we used the Driving forces – Pressures – State – Impacts - Responses (DPSIR) framework. The Dutch SEEA EA accounts only include half of the indicators which we considered essential to assess the effects of farming on natural capital and ecosystem services for the two studied environmental themes. However, most gaps in the accounts could be filled with other publicly available environmental monitoring data. Regarding N pollution, the availability and reliability of indicators at landscape and farm scales are not sufficient to support the assessment of agri-environmental measures effectiveness and results-based payments to decrease N pollution. The accounts have a higher potential to support the assessment of measures to conserve farmland biodiversity, in particular due to high resolution maps of ecosystem extent and ecosystem services flows. The potential of the SEEA EA accounts may be more limited in other countries where ecosystem accounting has only recently started. However, the SEEA EA is also implemented at the European Union scale, so that SEEA EA indicators will gradually become available for all European countries. To enhance the relevance of the SEEA EA in the agri-environmental policy area, we recommend to integrate information on farming emissions (externalities) recorded in the SEEA Central Framework with SEEA EA accounts and evaluate the applicability of SEEA EA accounts for case studies at landscape and farm scales. Our research shows that the Dutch SEEA EA accounts, complemented with other data sources, have potential to strongly enhance the CAP monitoring and evaluation framework but further steps need to be taken to fill data gaps.

Economic and environmental analyses of incorporating guar into the American southwest

CONTEXTPersistent drought is affecting the livelihood of American farmers in arid climates. Adopting drought-tolerant crops, such as guar (Cyamopsis tetragonoloba L.), is one potential solution for improving economic revenue and reducing the effect of drought on farms. Guar produces guar gum, which is a thickening and stabilizing agent in fluids used most recently in the hydraulic fracking of shale oil and gas recovery. OBJECTIVEThis study was performed to investigate the economic and environmental feasibility of cultivating guar in the American Southwest and transporting it to a domestic processing facility for the primary product of guar gum. METHODSAn integrated techno-economic (TEA) and life cycle analysis (LCA) was performed on the cradle-to-gate process of producing guar gum for domestic supply in the United States. TEA was performed to investigate the economic performance on the farm and downstream for the guar gum production facility. Similarly, the LCA investigated the environmental impact to the farm and the primary product of guar gum. RESULTS AND DISCUSSIONBaseline results indicate a minimum selling price of $1.44 per kg-guar gum, driven largely by irrigation, herbicides and associated equipment use. A best case economic scenario where irrigation and fertilizers were removed, low-cost herbicides were used and less intensive land management practices were adopted, highlights the feasibility of guar gum being produced for as low as $0.45 per kg-guar gum, which is lower than the five-year average U.S. import price of $0.99 per kg-guar gum. Environmental impacts of guar gum are largely attributed to irrigation and agricultural equipment use. The indicator, global warming potential, resulted in farm-level emissions of 1160 per hectare of guar grown. The combined farm, transportation and downstream processing production processes results in 2.67 kg CO2eq per kg-guar gum, or 806 kg CO2eq per hectare, which is lower than the farm emissions due to a co-product credit for animal feed. SIGNIFICANCEThe economic results indicate that guar gum can be produced for less than average U.S. import prices. The environmental impact results indicate that growing guar would lead to lower emissions than existing crops when cultivated in the American Southwest.