Igor Staritsky

Modelling the spatial distribution of livestock in Europe

Livestock remains the world’s largest user of land and is strongly related to grassland and feed-crop production. Assessments of environmental impacts of livestock farming require detailed knowledge of the presence of livestock, farming practices, and environmental conditions. The present Europe-wide livestock distribution information is generally restricted to a spatial resolution of NUTS 2 (province level). This paper presents a modelling approach to determine the spatial distribution of livestock at the landscape level. Location factors for livestock occurrence were explored and applied to consistent and harmonized EU-wide regional statistics to produce a detailed spatial distribution of livestock numbers. Both an expert-based and an empirical approach were applied in order to disaggregate the data to grid level. The resulting livestock maps were validated. Results differ between the two downscaling approaches but also between livestock types and countries. While both the expert-based and empirical approach are equally suited to modelling herbivores, in general, the spatial distribution of monogastrics can be better modelled by applying the empirical approach.

How much would it cost to monitor farmland biodiversity in Europe

To evaluate progress on political biodiversity objectives, biodiversity monitoring provides information on whether intended results are being achieved. Despite scientific proof that monitoring and evaluation increase the (cost) efficiency of policy measures, cost estimates for monitoring schemes are seldom available, hampering their inclusion in policy programme budgets. Empirical data collected from 12 case studies across Europe were used in a power analysis to estimate the number of farms that would need to be sampled per major farm type to detect changes in species richness over time for four taxa (vascular plants, earthworms, spiders and bees). A sampling design was developed to allocate spatially, across Europe, the farms that should be sampled. Cost estimates are provided for nine monitoring scenarios with differing robustness for detecting temporal changes in species numbers. These cost estimates are compared with the Common Agricultural Policy (CAP) budget (2014-2020) to determine the budget allocation required for the proposed farmland biodiversity monitoring. Results show that the bee indicator requires the highest number of farms to be sampled and the vascular plant indicator the lowest. The costs for the nine farmland biodiversity monitoring scenarios corresponded to 0·01%-0·74% of the total CAP budget and to 0·04%-2·48% of the CAP budget specifically allocated to environmental targets. Synthesis and applications. The results of the cost scenarios demonstrate that, based on the taxa and methods used in this study, a Europe-wide farmland biodiversity monitoring scheme would require a modest share of the Common Agricultural Policy budget. The monitoring scenarios are flexible and can be adapted or complemented with alternate data collection options (e.g. at national scale or voluntary efforts), data mobilization, data integration or modelling efforts.

Nutrient Recovery and Emissions of Ammonia, Nitrous Oxide, and Methane from Animal Manure in Europe: Effects of Manure Treatment Technologies

Animal manure contributes considerably to ammonia (NH3) and greenhouse gas (GHG) emissions in Europe. Various treatment technologies have been implemented to reduce emissions and to facilitate its use as fertilizer, but a systematic analysis of these technologies has not yet been carried out. This study presents an integrated assessment of manure treatment effects on NH3, nitrous oxide (N2O) and methane (CH4) emissions from manure management chains in all countries of EU-27 in 2010 using the MITERRA-Europe model. Effects of implementing 12 treatment technologies on emissions and nutrient recovery were further explored through scenario analyses; the level of implementation corresponded to levels currently achieved by forerunner countries. Manure treatment decreased GHG emissions from manures in EU countries by 0-17% in 2010, with the largest contribution from anaerobic digestion; the effects on NH3 emissions were small. Scenario analyses indicate that increased use of slurry acidification, thermal drying, incineration and pyrolysis may decrease NH3 (9-11%) and GHG (11-18%) emissions; nitrification-denitrification treatment decreased NH3 emissions, but increased GHG emissions. The nitrogen recovery (% of nitrogen excreted in housings that is applied to land) would increase from a mean of 57% (in 2010) to 61% by acidification, but would decrease to 48% by incineration. Promoting optimized manure treatment technologies can greatly contribute to achieving NH3 and GHG emission targets set in EU environmental policies.

Landscape level simulation of land use change

Land use changes are a result of decision making at the local level which is influenced by changes in the regional and global economy, demography, policies and other factors operating over a wide range of organisational levels and spatial scales. This chapter describes a methodology to integrate the demands for changes in land use as determined by global and national scale processes with local level conditions influencing land use conversions across the European Union. The approach enables an assessment of landscape level changes in land use and the analysis of policies specifically aimed at land use and landscape functioning. A baseline scenario is presented to illustrate the approach and results.

Assessment of uncertainties in greenhouse gas emission profiles of livestock sectors in Africa, Latin America and Europe

AbstractThe global animal food chain has a large contribution to the global anthropogenic greenhouse gas (GHG) emissions, but its share and sources vary highly across the world. However, the assessment of GHG emissions from livestock production is subject to various uncertainties, which have not yet been well quantified at large spatial scale. We assessed the uncertainties in the relations between animal production (milk, meat, egg) and the CO2, CH4, and N2O emissions in Africa, Latin America and the European Union, using the MITERRA-Global model. The uncertainties in model inputs were derived from time series of statistical data, literature review or expert knowledge. These model inputs and parameters were further divided into nine groups based on type of data and affected greenhouse gas. The final model output uncertainty and the uncertainty contribution of each group of model inputs to the uncertainty were quantified using a Monte Carlo approach, taking into account their spatial and cross-correlation. GHG emissions and their uncertainties were determined per livestock sector, per product and per emission source category. Results show large variation in the GHG emissions and their uncertainties for different continents, livestock sectors products or source categories. The uncertainty of total GHG emissions from livestock sectors is higher in Africa and Latin America than in the European Union. The uncertainty of CH4 emission is lower than that for N2O and CO2. Livestock parameters, CH4 emission factors and N emission factors contribute most to the uncertainty in the total model output. The reliability of GHG emissions from livestock sectors is relatively high (low uncertainty) at continental level, but could be lower at country level.

Modeling Biomass Logistics

This chapter will presents the current status and the main challenges of biomass logistics. Logistical aspects of the biomass supply chain will be delineated. It further provides a thorough description of different methodologies to design biomass value chains combined with relevant logistical assessment criteria. This includes also descriptions for how to integrate the various logistical components in modeling logistical tools that are currently available to implement the described methodologies. The chapter finishes with a set of case studies based on local data and made with these logistical tools.

Chapter 9 – Assessing the Potentials for Nonfood Crops

Given the ambitious EU targets to further decarbonize the economy, it can be expected that demand for lignocellulosic biomass will continue to grow. Provisioning of part of this biomass by dedicated biomass crops becomes an option. This chapter presents yields and cost levels that can be reached in Europe with different perennial crops in different climatic, soil, and management situations. The AquaCrop model developed by FAO was used and fed with phenological parameters per crop and detailed weather data to simulate the crop growth in all European NUTS3 regions. Yield levels were simulated for a maximum and a water limited yield situation and further converted to match with low, medium, and high input management systems. Low input systems are suitable for the lower quality soils often characterized as “marginal” because of their low suitability to be used for annual (rotational) cropping. In addition, suitability maps specific per crop were prepared according to important limiting factors such as killing frost, length of growing season, and slope. The cost productions were assessed with an activity-based costing (ABC) model, developed to assess the roadside Net Present Value (NPV) cost per ton of biomass. The yield, crop suitability, and cost simulation results were then combined to identify the best performing crop–management mix per region.

A framework with an integrated computer support tool to assess regional biomass delivery chains

Abstract In this paper, we first provide a brief overview of other decision support tools for bioenergy and assess to which extent the integrated tool central in this paper is different and novel. Next, a description is given of the tool, the different models used and the functionalities. The working of the tool is then illustrated with three case studies based in the northern part of The Netherlands. The computerised tool is meant to support the communication process between stakeholders to come to the implementation of regional biomass delivery chains. It helps to create a quick and common understanding of optimal biomass use in a region. Although the tool has been applied only to bioenergy chains, other biochemical and biomaterial chains are also suitable to be incorporated. The three case studies presented include a conventional sugar beet bioethanol production chain, an advanced Miscanthus bioethanol conversion chain and a straw-based electricity chain. The main conclusions are that optimal biomass use for non-food purposes from a sustainability and resource-efficient perspective depend on many different factors specific to the conversion chains. For example, the green house gas (GHG) emission and mitigation potential of a sugar beet-based bioethanol chain requires careful organisation particularly on the primary biomass production and transport, while in a straw-based electricity chain, the largest efficiency gains can be reached in the conversion part. Land use change (LUC) to sugar beet generally causes more negative environmental impacts than LUC to Miscanthus. This applies to both GHG efficiency, soil organic carbon content and emissions of nitrogen to surface waters. At the same time, it becomes clear that the different scenario assumptions can be very influential, particularly on the final economic performance of a chain. Overall, it is clear from the cases that the users understand much better under which circumstances and through which mechanisms the designed chains can become profitable and can become more environmentally sustainable.

Assessing Potentials for Agricultural Residues

Abstract Agricultural residues can be derived from both primary harvesting and pruning activities on field as well as by-products/residues from processing crops in the respective agricultural industries. In this chapter, they are defined as primary and secondary agricultural residues, respectively. The aim of the chapter is to present the key challenges, the methodologies, and relevant indicators for assessing potentials for agricultural residues. Detailed information on the use of data sources and methods are also included. The diversity of landscapes and related economic activities in Europe provide a big range of potential agricultural residues. To secure year-round sustainable supply, their mobilization should be linked to current practices and traditional agricultural markets within the respective regions. Future assessments should focus on bottom-up approaches and account for the soil, climatic, environmental, and socioeconomic profiles in the understudy regions.

Existing Modeling Platforms for Biomass Supply in Europe

Biomass availability is related to the prevailing land use patterns in a region as these deliver different types and quantities of feedstocks. Robust modeling frameworks are required to predict future land use changes and biomass availability for given demands in terms of the production of crops, livestock, timber, bioenergy, biochemical, and biomaterials. This chapter presents two important modeling frameworks, CAPRI, and GLOBIOM and explains how they are used respectively to assess cost supply of domestic biomass potential from agriculture and forestry in Europe and cost-supply potential for biomass imports from the rest of the world. Recent work demonstrates that both model structure and consistency in input data are imperative to ensure the validity of biomass assessments but there are also limitations deriving from the inconsistency of statistical databases, the increasingly complex assumptions, variable feedstock types, and geographical levels. Regular updates and model improvements will be necessary to internalize further the evolving key issues determining biomass supply for biobased economy in Europe.