A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.     

Capturing market impacts of farm level policies: a statistical extrapolation approach using biophysical characteristics and farm resources

Technical change at the farm level or changes in input prices often have an impact on the firm's supply function, which in turn affect their economic and environmental performance. These changes can take place in numerous ways. This paper presents a methodology that increases the consistency of supply responses across various sets of agricultural products and most representative farm typologies in Europe, with a market model based on a statistical response function approach. Since most farm simulation models are limited to a subset of regions and farm types, the linkage to an aggregated model requires a procedure for expanding these results to non-sample regions to achieve full regional coverage. This paper addresses theoretical aspects related to the consistency between micro and market level models. The proposed approach is applied using a consistent set of simulation results from farm models in seven European regions. Our results show a fairly stable behaviour of the farm models considered for the analysis and quite good fit of the estimated response surface. As results are still preliminary we critically reflect on the applicability of this method in addressing further needs on up-scaling of other economic as well as environmental indicators.     

Carbonyl compounds in the urban environment of Athens,Greece

The concentration levels of 15 selected carbonyl compounds in 62 samples were determined at two sites in Athens basin from June to December 2000. Formaldehyde was the most abundant species (0.05-39 microg m(-3)), which comprised from 22% to 37% of the total measured compounds, followed by acetaldehyde (4.32-49 microg m(-3)), acetone/acrolein (0.64-198 microg m(-3)) and butanal (0.79-140 microg m(-3)). The mean formaldehyde/acetaldehyde and acetaldehyde/propanal molar ratios were calculated. No significant seasonal differences were observed for all the carbonyls. Photochemical production was found to weigh upon atmospheric levels for 83-93% in summer days, dropping below 33% in the winter. The importance of formaldehyde and acetaldehyde as a source of hydroxyl radicals in Athens was also assessed.     

The role of farmers’ objectives in current farm practices and adaptation preferences: a case study in Flevoland,the Netherlands

The diversity in farmers’ objectives and responses to external drivers is usually not considered in integrated assessment studies that investigate impacts and adaptation to climate and socio-economic change. Here, we present an approach to assess how farmers’ stated objectives relate to their currently implemented practices and to preferred adaptation options, and we discuss what this implies for assessments of future changes. We based our approach on a combination of multi-criteria decision-making methods. We consistently assessed the importance of farmers’ objectives and adaptation preferences from what farmers say (based on interviews), from what farmers actually do (by analysing current farm performance) and from what farmers want (through a selected alternative farm plan). Our study was performed for six arable farms in Flevoland, a province in the Netherlands. Based on interviews with farmers, we reduced the long list of possible objectives to the most important ones. The objectives we assessed included maximization of economic result and soil organic matter, and minimization of gross margin variance, working hours and nitrogen balance. In our sample, farmers’ stated preferences in objectives were often not fully reflected in realized farming practices. Adaptation preferences of farmers largely resembled their current performance, but generally involved a trend towards stated preferences. Our results suggest that in Flevoland, although farmers do have more objectives, in practical decision-making they focus on economic result maximization, while for strategic decision-making they account for objectives influencing long-term performance and indicators associated with sustainability, in this case soil organic matter.