To date, projections of European crop yields under climate change have been based almost entirely on the outputs of crop-growth models. While this strategy can provide good estimates of the effects of climatic factors, soil conditions and management on crop yield, these models usually do not capture all of the important aspects related to crop management, or the relevant environmental factors. Moreover, crop-simulation studies often have severe limitations with respect to the number of crops covered or the spatial extent. The present study, based on agroclimatic indices, provides a general picture of agroclimatic conditions in western and central Europe (study area lays between 8.5°W–27°E and 37–63.5°N), which allows for a more general assessment of climate-change impacts. The results obtained from the analysis of data from 86 different sites were clustered according to an environmental stratification of Europe. The analysis was carried for the baseline (1971–2000) and future climate conditions (time horizons of 2030, 2050 and with a global temperature increase of 5 °C) based on outputs of three global circulation models. For many environmental zones, there were clear signs of deteriorating agroclimatic condition in terms of increased drought stress and shortening of the active growing season, which in some regions become increasingly squeezed between a cold winter and a hot summer. For most zones the projections show a marked need for adaptive measures to either increase soil water availability or drought resistance of crops. This study concludes that rainfed agriculture is likely to face more climate-related risks, although the analyzed agroclimatic indicators will probably remain at a level that should permit rainfed production. However, results suggests that there is a risk of increasing number of extremely unfavorable years in many climate zones, which might result in higher interannual yield variability and constitute a challenge for proper crop management.

Incorporating undesirable outputs in the operational assessments through the integration of Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) has received great attention recently. There are many studies throughout literature that apply various methods to integrate LCA and DEA. In this case study, the six most common approaches were employed to assess the winter wheat cropping system in Poland. These six methods were: a) ignoring undesirable outputs, b) treating undesirables as inputs to the DEA model, c) data transformation, d) impact rate, e) ratio model, and f) slack based measurement DEA with undesirable outputs. The environmental impact of wheat production was assessed by determining its carbon footprint (CF). The mean CF equalled 0.45 kg CO2eq per kg wheat grain (ranging from 0.25 to 0.67). According to the model comparison results, a slack based measurement DEA with undesirable outputs could better reflect the performance of undesirable outputs, and was selected as the most appropriate method to maximize the efficiency of winter wheat production while minimizing undesirable outputs. The advantage of applying the slack based model with undesirable outputs was that the targets presented by this model were based on existing efficient farms, as opposed to theoretical results; thus achieving these targets are feasible. The average efficiency score equalled 0.43, whereby few farms were classified as efficient farms. The results of the proposed integrated model showed a high reduction potential for mineral fertilizers (up to 595 kg ha-1 y-1), seed (up to 37 kg ha-1 y-1), and fuel (up to 75 L ha-1 y-1) in winter wheat farms. These results help farmers to obtain a realistic and reliable usage pattern for inputs in a winter wheat production system, whereby the greatest production can be achieved in conjunction with the lowest possible environmental impact.