Solar timber kilns: State of the art and foreseeable developments

Analysis of the evolution in solar heated drying kilns in recent decades shows that there have been a series of modifications to optimize their thermal and drying efficiency. Using an analysis method based on product design, we report on existing solar timber kilns. The dryers and their component units are studied, developments are noted, focusing on changing trends in technological systems. As a result of this analysis we suggest some future adaptations

Model and simulation of a solar kiln with energy storage

A solar kiln with energy storage can be used for continuous drying. This kiln consisted of several units which were modeled to simulate it in operation. A model was proposed for each unit, and another based on laboratory tests for drying a wooden board by passing air across. These models were combined to produce a global model. Simulation results were then analyzed and showed that the use of storage was justified to reduce drying time. Moreover, with the judicious use of storage and air renewal, drying schedules could be produced for a better quality of dried wood

Reply to comment of Legates et al.

In the previous comment, Legates et al. express concern about the statistical reliability of the positive runoff–temperature relationship presented by Labat et al. We are grateful for this opportunity to respond to these concerns. As Legates et al. correctly points out, the effect of temperature on runoff is a complex relationship, which involves precipitation, evaporation, anthropomorphic affects, among others. As such, the effect of increased temperature on runoff is strongly dependent on the identity of the watershed of interest. For example, a watershed located in a glaciated region, such as Iceland, exhibits a strong positive correlation between runoff and temperature, whereas a watershed located in a arid climate, such as the Sahara desert, exhibits a negative correlation; often there is no run off at all during the summer months in such watersheds

Evidence for global runoff increase related to climate warming

Ongoing global climatic change initiated by the anthropogenic release of carbon dioxide is a matter of intense debate. We focus both on the impact of these climatic changes on the global hydrological cycle and on the amplitude of the increase of global and continental runoff over the last century, in relation to measured temperature increases. In this contribution, we propose an original statistical wavelet-based method for the reconstruction of the monthly discharges of worldwide largest rivers. This method provides a data-based approximation of the evolution of the annual continental and global runoffs over the last century. A consistent correlation is highlighted between global annual temperature and runoff, suggesting a 4% global runoff increase by 1 C global temperature rise. However, this global trend should be qualified at the regional scale where both increasing and decreasing trends are identified. North America runoffs appear to be the most sensitive to the recent climatic changes. Finally, this contribution provides the first experimental data-based evidence demonstrating the link between the global warming and the intensification of the global hydrological cycle. This corresponds to more intense evaporation over oceans coupled to continental precipitation increase or continental evaporation decrease. This process finally leads to an increase of the global continental runoff

An oriented-design simplified model for the efficiency of a flat plate solar air collector

In systems design, suitably adapted physical models are required. Different modelling approaches for a solar air collector were studied in this paper. First, a classical model was produced, based on a linearization of the conservation of energy equations. Its resolution used traditional matrix methods. In order to improve the possibilities for use in design, the behaviour of the collector was next expressed in terms of efficiency. Lastly, simplified models constructed from the results obtained with the classical linearized model, and explicitly including the design variables of the collector, were proposed. These reduced models were then evaluated in terms of Parsimony, Exactness, Precision and Specialisation (PEPS). It was concluded that one of them (D2), using a low number of variables and of equations, is well suited for the design of solar air collector coupled with other sub-systems in more complex devices such as solar kiln with energy storag

Comparing population distributions from bin-aggregated sample data: An application to historical height data from France

This paper develops a methodology to estimate the entire population distributions from bin-aggregated sample data. We do this through the estimation of the parameters of mixtures of distributions that allow for maximal parametric flexibility. The statistical approach we develop enables comparisons of the full distributions of height data from potential army conscripts across France's 88 departments for most of the nineteenth century. These comparisons are made by testing for differences-of-means stochastic dominance. Corrections for possible measurement errors are also devised by taking advantage of the richness of the data sets. Our methodology is of interest to researchers working on historical as well as contemporary bin-aggregated or histogram-type data, something that is still widely done since much of the information that is publicly available is in that form, often due to restrictions due to political sensitivity and/or confidentiality concerns.Health, health inequality, aggregate data, 19th-century France, welfare

Polarization: Robust Multidimensional Poverty Comparisons

We investigate how to make poverty comparisons using multidimensional indicators of well-being, showing in particular how to check whether the comparisons are robust to aggregation procedures and to the choice of multidimensional poverty lines. In contrast to earlier work, our methodology applies equally well to what can be defined as "union", "intersection" or "intermediate" approaches to dealing with multidimensional indicators of well-being. When one of two indicators is discrete, our methods specialize to those that have previously been developed to deal with household composition heterogeneity. To make these procedures of some practical usefulness, the paper is also the first to derive the sampling distribution of various multidimensional poverty estimators, including estimators of the "critical" poverty frontiers outside which multidimensional poverty comparisons can no longer be deemed ethically robust. The results are illustrated using data from a number of developing countries.Multidimensional Poverty, Stochastic Dominance

Robust Multidimensional Spatial Poverty Comparisons in Ghana, Madagascar, and Uganda

We investigate spatial poverty comparisons in three African countries using multidimensional indicators of well-being. The work is analogous to the univariate stochastic dominance literature in that we seek poverty orderings that are robust to the choice of multidimensional poverty lines and indices. In addition, we wish to ensure that our comparisons are robust to aggregation procedures for multiple welfare variables. In contrast to earlier work, our methodology applies equally well to what can be defined as "union", "intersection", or "intermediate" approaches to dealing with multidimensional indicators of well-being. Further, unlike much of the stochastic dominance literature, we compute the sampling distributions of our poverty estimators in order to perform statistical tests of the difference in poverty measures. We apply our methods to two measures of well-being, the log of household expenditures per capita and children's height-for-age z-scores, using data from the 1988 Ghana Living Standards Survey, the 1993 Enquêtes Permanente auprès des Ménages i Madagascar, and the 1999 National Household Survey in Uganda. Bivariate poverty comparisons are at odds with univariate comparisons in several interesting ways. Most importantly, we cannot always conclude that poverty is lower in urban areas from one region compared to rural areas in another, even though univariate comparisons based on household expenditures per capita almost always lead to that conclusion.Multidimensional Poverty, Stochastic Dominance, Ghana, Madagascar, Uganda

Robust Multidimensional Poverty Comparisons

We investigate how to make poverty comparisons using multidimensional indicators of well-being, showing in particular how to check whether the comparisons are robust to the choice of poverty indices and poverty lines. Our methodology applies equally well to either of what can be defined as "union" and "intersection" approaches to dealing with multidimensional indicators of well-being. When one of two variables is discrete, our methods specialize to those that Atkinson (1991), Jenkins and Lambert (1993) and others have developed to deal with household composition heterogeneity. The results also extend the statistical results recently derived in Davidson and Duclos (2000) to cases where well-being is measured in two or more dimensions. We thus derive the sampling distribution of various multidimensional poverty estimators, including estimators of the "critical" frontiers of poverty lines above which multidimensional poverty comparisons are no longer ethically robust.Multidimensional Poverty, Stochastic Dominance

Robust Multidimensional Poverty Comparisons with Discrete Indicators of Well-being

This paper provides a method to make robust multidimensional poverty comparisons when one or more of the dimensions of well-being or deprivation is discrete. Sampling distributions for the statistics used in these poverty comparisons are provided. Several examples show that the methods are both practical and interesting in the sense that they can provide richer information than do univariate poverty comparisons.Multidimensional Poverty, Stochastic Dominance