Generating better energy indicators: Addressing the existence of multiple scales and multiple dimensions

High energy prices and the growing concern for “Peak Oil” have put energy analysis, once again, on the front burner. However, before speculating about possible roadmaps regarding our energy future, it would be wise to develop better quantitative analyses. This paper flags the existence of systemic epistemological flaws in the current use of aggregate energy indicators and presents an alternative approach capable of dealing with the issue of multiple dimensions and multiple scales. Starting from a critical appraisal of the aggregate indicator “Economic Energy Intensity” it shows that economic and biophysical variables are often correlated and that their value is determined by characteristics which can only observed across different levels and scales. Complex metabolic systems (systems that use energy to maintain and reproduce themselves) are operating simultaneously at different scales. This implies that changes in the characteristics of parts, defined at the local scale, and changes in the characteristics of the whole, defined at the large scale can only be obtained after establishing a scaling mechanism in the analysis. In order to deal with the issue of scale in energy accounting, we propose to make a distinction between three different categories: (i) primary energy sources (PES) - establishing a link between energy quantities and the associated requirement of biophysical gradients, at the large scale, on the interface black-box/context; (ii) energy carriers (EC) - defining the set of energy inputs required by technical devices for expressing useful functions, at the local scale, within the parts operating inside the black-box; (iii) end uses (EU) the set of functions to be expressed by society across hierarchical levels for reproducing itself. Finally, the paper presents examples of quantitative results obtained using an innovative method of analysis - Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM). We conclude that by using this new accounting method it is possible to generate a better understanding of external and internal constraints determining the desirability and viability of the metabolic pattern of societies.     

Modelling radiative balance in a row-crop canopy: Cross-row distribution of net radiation at the soil surface and energy available to clusters in a vineyard

Distribution of energy at the soil surface in a row-crop influences mainly soil temperature and water content, and therefore root activity, nitrogen mineralization and within canopy air temperature, which all affect plant physiology. In the case of a vineyard, it is also closely related to the energy available to the berries and therefore most influential for fruit quality. The aim of this study was to develop a simplified model of available energy distribution at the soil surface and at the bottom of the rows, where most of the clusters are located. Such a model would be helpful for optimising some aspects of row-crop management like training system choice, row geometry, leaf area density, and soil surface maintenance practices.The model simulated radiation balance at the soil surface, split up into downward and upward short- and long-wave fluxes. Row shadows were calculated at any point of the inter-row space, in interaction with actual row geometry and simplified porosity distribution within row volume. All hemispheric radiations (long-wave and diffuse solar radiation) were calculated according to view factors between the row and soil surfaces. Input variables were therefore incoming solar radiation over the canopy, air temperatures near the row walls and soil surface temperatures. Parameters were row geometry, dimensions and porosities.The model was validated in a 7 years old Merlot vineyard in the Médoc area, by comparing model predictions to measured net radiation (Rns) at five positions above the inter-row soil surface. Along the row sampling was achieved by a moving device carrying the net-radiometers. Structure of the vegetation was kept constant during the experiment and gap fraction parameters were derived from pictures of shadows at the soil surface. Since Rns measurements are impracticable directly at the soil surface and horizontal distribution of Rns is heterogeneous, comparison was performed by calculating net radiation at the actual measurement height which was close to average cluster height.Model prediction agreed with field measurement in most conditions, which suggests that all short- and long-wave radiation fluxes, as well as interactions with the canopy structure, were well described. Rns, energy available to clusters, and soil surface temperature variations were all mainly driven by shading due to the rows. Coupling the model to soil heat transfer and convective fluxes to the atmosphere models will help forecasting soil temperature distribution at the surface and in depth as well as canopy microclimate. The model will also be an essential part of a more elaborate model of cluster microclimate, a key determinant of berry quality.