Livelihoods after land reform in South Africa

Over the past few decades, Zimbabwe, Namibia and South Africa have pursued redistributive land reform as a means to address rural poverty. The Livelihoods after Land Reform (LaLR) study was carried out between 2007 and 2009, to understand the livelihood and poverty reduction outcomes of land reform in each of the three countries. The South African component focused on Limpopo province, and investigated land reform processes, trajectories of change and outcomes in thirteen detailed case studies. This paper summarizes some of the main findings from the South African study, and briefly compares them with findings from Namibia and Zimbabwe. The paper argues that a fundamental problem affecting land reform in both South Africa and Namibia is the uncritical application of the Large-Scale Commercial Farming (LSCF) model, which has led to unworkable project design and/or projects that are irrelevant to the circumstances of the rural poor. Nevertheless, some ‘beneficiaries’ have experienced modest improvements in their livelihoods, often through abandoning or amending official project plans.Web of Scienc

A stochastic model of integrating occupant behaviour into energy simulation with respect to actual energy consumption in high-rise apartment buildings

Apartment buildings have evolved to be self-sufficient for occupants. Thus, energy use is individually controlled in apartment units, which can be considered as independent thermal zones within buildings. However, this has been disregarded in conventional energy modelling which is mainly applicable for reducing energy demands of buildings with standardised conditions, rather than reflecting actual consumption. This approach has been questioned due to the high levels of uncertainty formed with real buildings. In this study, a model considering occupant random behaviour consuming heating and electricity is developed to reflect variations in actual energy consumption in apartments. Moreover, the effects of various parameters of occupant behaviour in relation to the model were examined. In total 96 apartment blocks in Seoul were used as samples. Gaussian Process Classification was applied to modify occupant random behaviours corresponding to the probability of energy consumption. As a result, it has been found that occupants’ general heating controls (25% deviation) are between three and eight hours, with 17–20 °C set temperatures. Moreover, the operating hours of electric appliances and lighting are also approximated with the probabilities. This methodology could reduce uncertainties in building simulations, and provide a broader application in buildings with similar development stages