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The ‘4 per mille Soils for Food Security and Climate’ was launched at the COP21 with an aspiration to increase global soil organic matter stocks by 4 per 1000 (or 0.4 %) per year as a compensation for the global emissions of greenhouse gases by anthropogenic sources. This paper surveyed the soil organic carbon (SOC) stock estimates and sequestration potentials from 20 regions in the world (New Zealand, Chile, South Africa, Australia, Tanzania, Indonesia, Kenya, Nigeria, India, China Taiwan, South Korea, China Mainland, United States of America, France, Canada, Belgium, England & Wales, Ireland, Scotland, and Russia). We asked whether the 4 per mille initiative is feasible for the region. The outcomes highlight region specific efforts and scopes for soil carbon sequestration. Reported soil C sequestration rates globally show that under best management practices, 4 per mille or even higher sequestration rates can be accomplished. High C sequestration rates (up to 10 per mille) can be achieved for soils with low initial SOC stock (topsoil less than 30 t C ha− 1), and at the first twenty years after implementation of best management practices. In addition, areas which have reached equilibrium will not be able to further increase their sequestration. We found that most studies on SOC sequestration only consider topsoil (up to 0.3 m depth), as it is considered to be most affected by management techniques. The 4 per mille number was based on a blanket calculation of the whole global soil profile C stock, however the potential to increase SOC is mostly on managed agricultural lands. If we consider 4 per mille in the top 1m of global agricultural soils, SOC sequestration is between 2-3 Gt C year− 1, which effectively offset 20–35% of global anthropogenic greenhouse gas emissions. As a strategy for climate change mitigation, soil carbon sequestration buys time over the next ten to twenty years while other effective sequestration and low carbon technologies become viable. The challenge for cropping farmers is to find disruptive technologies that will further improve soil condition and deliver increased soil carbon. Progress in 4 per mille requires collaboration and communication between scientists, farmers, policy makers, and marketeers.

AbstractThe aim is to develop a catalysed water-based capture process, avoiding the energy intensive steam stripping steps necessary with amine solvents. The naturally occurring zinc metallo-enzyme carbonic anhydrase/hydratase (CAH) can concentrate CO2 using a reversible hydration/dehydration cycle at neutral pH and at ambient temperatures. Some tripodal complexes of zinc (II)–[zinc-itrilo-tris(2-benzimidazoyl-methyl-6-sulfonic acid, (zinc-L1S), and zinc-tris(2-benzimidazoylmethyl)-amine, (zinc-LI)], and also cadmium (II), cobalt (II) and other metals complexed to these tripodal ligands have been prepared, and show activity that mimics the CAH catalytic process–hydration of CO2 to bicarbonate followed by the reverse dehydration of the bicarbonate to regenerate CO2 in a pH dependent mechanism. The thermal stability of these complex catalysts has been demonstrated by Differential Thermo-Gravimetric (DTG) studies to above 200 °C. A process for fast absorption/desorption is proposed.

Developing causal loop diagrams (CLDs) involves identifying stakeholders and endogenous variables and formulating variable causal relationships. Traditionally, the CLDs are developed mainly using a qualitative approach such as literature review, observations and interviews with stakeholders. However, modellers may question which stakeholders should be approached, whether the relevant variables are selected, and what to do when stakeholders perceive different variable relationships in the CLDs differently. Applying in a case study, this research proposes a multi-method approach by combining both quantitative and qualitative methods to select stakeholders, identify endogenous/exogenous variables, and develop the CLDs. The proposed quantitative method is expected to provide modellers with a justifiable stakeholder and variable selection process. The method also highlights possible hidden variables and relationships, which were further explored with a traditional qualitative approach.

AbstractObjectiveTo assess the epidemiological evidence on the joint effects of climate variability and socioecological factors on dengue transmission.MethodsFollowing PRISMA guidelines, a detailed literature search was conducted in PubMed, Web of Science and Scopus. Peer‐reviewed, freely available and full‐text articles, considering both climate and socioecological factors in relation to dengue, published in English from January 1993 to October 2015 were included in this review.ResultsTwenty studies have met the inclusion criteria and assessed the impact of both climatic and socioecological factors on dengue dynamics. Among those, four studies have further investigated the relative importance of climate variability and socioecological factors on dengue transmission. A few studies also developed predictive models including both climatic and socioecological factors.ConclusionsDue to insufficient data, methodological issues and contextual variability of the studies, it is hard to draw conclusion on the joint effects of climate variability and socioecological factors on dengue transmission. Future research should take into account socioecological factors in combination with climate variables for a better understanding of the complex nature of dengue transmission as well as for improving the predictive capability of dengue forecasting models, to develop effective and reliable early warning systems.

This paper presents a comparative study in predicting the monthly average solar radiation for Darwin, Australia (latitude 12.46 deg S longitude 130.84 deg E). The city of Darwin, Northern Territory (NT), has the highest and most consistent sunshine duration among all the other Australian states. This unique climate presents an opportunity for photovoltaic (PV) applications. Reliable and accurate predictions of solar radiation enable potential site locations, which exhibit high solar radiations and sunshine hours, to be identified for PV installation. Three predictive models were investigated in this study—the linear regression (LR), Angstrom–Prescott–Page (APP), and the artificial neural network (ANN) models. The mean global solar radiation coupled with the climate data (mean minimum and maximum temperatures, mean rainfall, mean evaporation, and sunshine fraction) obtained from the Australian Bureau of Meteorology (BoM) formed the basis of the dataset. Using simple and easily obtainable climate data presents an added advantage by reducing model complexity. Predictive results showed the root mean square errors (RMSEs) obtained were 6.72%, 13.29%, and 8.11% for the LR, APP, and ANN models, respectively. The predicted solar exposure from the LR model was then compared with the satellite-derived data to assess the accuracy of the LR method.

A natural holm oak forest was selectively thinned to test thinning as a tool to reduce tree mortality, increase productivity, and reverse the recent regression of the dominant species (Quercus ilex) induced by climate change. Thinning increased aboveground productivity and reduced stem mortality in this Mediterranean forest during four years just after thinning, contributing to the maintenance of forest functioning under changing climatic conditions. Q. ilex was the only species positively affected by the thinning: stem growth increased for all stem sizes, and mortality was significantly lower in thinned plots. On the contrary, mortality rates of Phillyrea latifolia and Arbutus unedo were not significantly lower. Stem growth increased for P. latifolia only in the smallest stem-size class. Our results highlight the suitability of selective thinning for improving the forest productivity and ensuring the conservation of Mediterranean coppices. Other benefits of selective thinning, such as a decrease in the risk of fire dispersion and an increase in the water supply for human populations, are also discussed.