Environmental Engineering Reference
In-Depth Information
The vertical link from CAPRI to bio-physical simulation models and dis-aggregation
below the administrative regional level received more attention in the CAPRI-
Dynaspat project (FP6 Project, 2004-2007). These components of CAPRI are not
part of SEAMCAP since APES and FSSIM provide a bottom-up approach to assess
environmental externalities. To a large extent, this link applies a top-down approach,
where only limited bio-physical interactions are described in the regional supply
models but rather post-model analysis is used to capture impacts on the environment.
Given the non-linearities of bio-physical models, especially with respect to soil
parameters, and the need to analyse environmental impacts in a spatial context, a
methodology for spatial down-scaling from NUTS 2 level to about 150,000 clusters
of 1 × 1 km grid cells covering the EU-27 was developed (Leip et al. 2008) . This spatial
layer covers all crops in CAPRI, animal stocking densities, crop yields and organic
and mineral fertilizer application rates. As full simulations of all crop-site-farm
management combination with bio-physical models are too time consuming, a
statistical response surface from the bio-physical model DNDC was estimated.
It comprised, as explanatory variables soil and climate parameters, mineral and
organic fertilizer application and the so-called potential yield, a crop parameter
typically used for calibration purposes of DNDC (Britz and Leip 2008) . By inverting
the regression function so that it allows defining the potential yield to be equal to
the observed one, the statistical model is able to reproduce the results of CAPRI
and provide biophysical results consistent with the quantity framework
provided by the economic model. Following the general CAPRI principle, also
this downscaling approach covers all agricultural activities and the whole agricultural
area of the EU.
Baseline Generation for Forward Looking Impact Assessment
A further feature which CAPRI shares with other economic simulation models is
the need for forward looking impact assessment . Agricultural policies require time
to be developed and implemented, and their impact clearly depends on the state of
the system at the implementation stage. As technical progress, population growth,
changes in consumer behaviour and policies inside and outside the EU lead to
strong changes in the agricultural and market systems, analysing impacts based on
available and often outdated statistical data can provoke a serious bias. Accordingly,
there is a need for tools to project a most-likely future state of the system or to offer
a plausible range of future states. The projection capabilities of CAPRI, especially
at regional scale, led to specific applications e.g. for the European Environmental
Agency (Witzke et al. 2004) or for the prospects of agricultural markets and income
of the Directorate General of Agriculture and Rural Development (DG-AGRI) 2007
(European Commission 2007a) or DG-AGRI's Rural Development Outlook
2007 (European Commission 2007b) . For the projection, CAPRI integrates a-priori
information derived from trend analysis and knowledge from market experts at
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