Reduced Emissions from Deforestation and Forest Degradation in Developing Countries (REDD+) is a policy mechanism now agreed under the United Nations Framework Convention on Climate Change (UNFCCC). It aims to reduce carbon dioxide emissions from developing countries through the sustainable management of forests, while providing co-benefits of biodiversity conservation and livelihood support. Implementation challenges include linking remote sensing and national forest inventories of carbon stocks, to local implementation and measuring carbon loss from forest degradation. Community-based forest monitoring can help overcome some of these challenges. We show that local people can collect forest condition data of comparable quality to trained scientists, at half the cost. We draw on our experience to propose how and where local REDD+ monitoring can be established. Empowering communities to own and monitor carbon stocks could provide a rapid and cost-effective way of absorbing carbon dioxide emissions, while potentially contributing to local livelihoods and forest biodiversity conservation.

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The available data on climate change over the past century indicate that the Earth is warming. Important biological events, including changes in plant phenology, have been reported in many parts of the world. We have explored some of these phenological changes in more than 650 temperate species, which have indicated the average advancement of 1.9 days per decade in spring events and average delay of 1.4 days per decade in autumnal events. Thus the average length of the growing season has extended by 3.3 days per decade.

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CO2, being a linear and centrosymmetric molecule, is very stable, and the electrochemical reduction of CO2 requires energy. However, the salen complexes are found to be very efficient to minimize overpotential as compared to their metal counterparts.

This paper aims to determine the optimal capacitors required for maximum output power of a single-phase self-excited induction generator (SEIG), using a three-phase machine feeding inductive as well as capacitive loads. The generator consists of a three-phase star-connected induction machine with three capacitors and a single-phase load. The algorithm, which gives directly the values of the optimal capacitors for the maximum power output and the maximum power available, has been developed using the steady-state model of the SEIG and sequential unconstrained minimization technique (SUMT). The variations of the maximum power output with power factor (pf) of loads (both inductive and capacitive) and speed of the SEIG have been presented. The voltage regulation of the generator is small due to the effect of the two series capacitors. Experimental results have shown the effectiveness and accuracy of the developed algorithm.