Soil degradation: a threat to developing-country food security by 2020?

Global population in the year 2020 will be a third higher than in 1995, but demand for food and fiber will rise by an even higher proportion, as incomes grow, diets diversify, and urbanization accelerates. However this demand is met, population and farming pressure on land resources will intensify greatly. There is growing concern in some quarters that a decline in long-term soil productivity is already seriously limiting food production in the developing world, and that the problem is getting worse. Sarah Sherr first focuses on the magnitude and effects of soil degradation. She then addresses soil degradation in the future and ends her brief with policy and research priorities.Soil degradation Developing countries., Food security Developing countries.,

Degradation modeling applied to residual lifetime prediction using functional data analysis

Sensor-based degradation signals measure the accumulation of damage of an engineering system using sensor technology. Degradation signals can be used to estimate, for example, the distribution of the remaining life of partially degraded systems and/or their components. In this paper we present a nonparametric degradation modeling framework for making inference on the evolution of degradation signals that are observed sparsely or over short intervals of times. Furthermore, an empirical Bayes approach is used to update the stochastic parameters of the degradation model in real-time using training degradation signals for online monitoring of components operating in the field. The primary application of this Bayesian framework is updating the residual lifetime up to a degradation threshold of partially degraded components. We validate our degradation modeling approach using a real-world crack growth data set as well as a case study of simulated degradation signals.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS448 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

The Thermal degradation of Bisphenol A Polycarbonate in Air

The thermal degradation of polycarbonate in air was studied as a function of mass loss using TGA/FTIR, GC/MS and LC/MS. In the main degradation region, 480–560 °C, the assigned structures of smaller molecules and linear molecules that evolved in air were very similar to those obtained from the degradation in nitrogen; the degradation of polycarbonate follows chain scission of the isopropylidene linkage, in agreement with the bond dissociation energies, and hydrolysis/alcoholysis of carbonate linkage. Compared to the degradation in nitrogen, some differences were observed primarily in the beginning stage of degradation. Oxygen may facilitate branching as well as radical formation via the formation of peroxides. These peroxides undergo further dissociations and combinations, producing aldehydes, ketones and some branched structures, mainly in the beginning stage of degradation. It is speculated that the intermediate char formed in the beginning due to branching reactions of peroxide interferes with the mass transfer through the surface of degrading polycarbonate in the main degradation. Thus, even though the mass loss begins earlier in air, a slower mass loss rate is observed

Analysis of Scarp Profiles: Evaluation of Errors in Morphologic Dating

Morphologic analysis of scarp degradation can be used quantitatively to determine relative ages of different scarps formed in cohesionless materials, under the same climatic conditions. Scarps of tectonic origin as well as wavecut or rivercut terraces can be treated as topographic impulses that are attenuated by surface erosional processes. This morphological evolution can be modelled as the convolution of the initial shape with erosion (or degradation) function whose width increases with time. Such modeling applies well to scarps less than 10m high, formed in unconsolidated fanglomerates. To a good approximation, the degradation function is Gaussian with a variance measuring the degree of rounding of the initial shape. This geometric parameter can be called the degradation coefficient. A synthetic experiment shows that the degradation coefficient can be obtained by least squares fitting of profiles levelled perpendicular to the scarp. Gravitational collapse of the free face is accounted for by assuming initial scarp slopes at the angle of repose of the cohesionless materials (30°–35°). Uncertainties in the measured profiles result in an uncertainty in degradation coefficient that can be evaluated graphically. Because the degradation coefficient is sensitive to the regional slope and to three-dimensional processes (gullying, loess accumulation, stream incision, etc.), a reliable and accurate determination of degradation coefficient requires several long profiles across the same scarp. The linear diffusion model of scarp degradation is a Gaussian model in which the degradation coefficient is proportional to numerical age. In that case, absolute dating requires only determination of the propotionality constant, called the mass diffusivity constant. For Holocene scarps a few meters high, in loose alluvium under arid climatic conditions, mass diffusivity constants generally range between 1 and 6 m^2/kyr. Morphologic analysis is a reliable method to compare ages of different scarps in a given area, and it can provide approximate absolute ages of Holocene scarplike landforms

Degradation effects in sc-Si PV modules subjected to natural and induced ageing after several years of field operation

This paper presents ageing effects observed in sc-Si PV modules operating in field conditions for 18 and over 22 years. The effects of both natural ageing processes and induced ageing by external agents, causing partial or total shading of cells for a prolonged period of time, are examined. Optical degradation effects observed through visual inspection include discoloration of the EVA, degradation of the AR coating, degradation of the interface between the cell and encapsulant, corrosion of busbars and fingers, and tears, bubbles and humidity ingress at the back surface of the modules. Thermal degradation effects examined via IR thermography reveal the existence of hot cells, hotspots on the busbars, and colder bubbles. Modules' power and performance degradation is assessed through I-V curve analysis. Results show naturally aged modules to exhibit milder ageing effects than modules subjected to induced ageing, an outcome also supported by their power degradation ratio

Broad activation of the ubiquitin-proteasome system by Parkin is critical for mitophagy

Parkin, an E3 ubiquitin ligase implicated in Parkinson's disease, promotes degradation of dysfunctional mitochondria by autophagy. Using proteomic and cellular approaches, we show that upon translocation to mitochondria, Parkin activates the ubiquitin–proteasome system (UPS) for widespread degradation of outer membrane proteins. This is evidenced by an increase in K48-linked polyubiquitin on mitochondria, recruitment of the 26S proteasome and rapid degradation of multiple outer membrane proteins. The degradation of proteins by the UPS occurs independently of the autophagy pathway, and inhibition of the 26S proteasome completely abrogates Parkin-mediated mitophagy in HeLa, SH-SY5Y and mouse cells. Although the mitofusins Mfn1 and Mfn2 are rapid degradation targets of Parkin, we find that degradation of additional targets is essential for mitophagy. These results indicate that remodeling of the mitochondrial outer membrane proteome is important for mitophagy, and reveal a causal link between the UPS and autophagy, the major pathways for degradation of intracellular substrates

Statistical modeling, parameter estimation and measurement planning for PV degradation

Photovoltaics (PV) degradation is a key consideration during PV performance evaluation. Accurately predicting power delivery over the course of lifetime of PV is vital to manufacturers and system owners. With many systems exceeding 20 years of operation worldwide, degradation rates have been reported abundantly in the recent years. PV degradation is a complex function of a variety of factors, including but not limited to climate, manufacturer, technology and installation skill. As a result, it is difficult to determine degradation rate by analytical modeling; it has to be measured. As one set of degradation measurements based on a single sample cannot represent the population nor be used to estimate the true degradation of a particular PV technology, repeated measures through multiple samples are essential. In this chapter, linear mixed effects model (LMM) is introduced to analyze longitudinal degradation data. The framework herein introduced aims to address three issues: 1) how to model the difference in degradation observed in PV modules/systems of a same technology that are installed at a shared location; 2) how to estimate the degradation rate and quantiles based on the data; and 3) how to effectively and efficiently plan degradation measurements