The incentive gap: LULUCF and the Kyoto mechanism before and after Durban

To-date, forest resource-based carbon accounting in land use, land use change and forestry (LULUCF) under the United Nations Framework Convention on Climate Change (UNFCCC), Kyoto Protocol (KP), European Union (EU) and national level emission reduction schemes considers only a fraction of its potential and fails to adequately mobilize the LULUCF sector for the successful stabilization of atmospheric greenhouse gas (GHG) concentrations. Recent modifications at the 2011 COP17 meetings in Durban have partially addressed this basic problem, but leave room for improvement. The presence of an Incentive Gap (IG) continues to justify reform of the LULUCF carbon accounting framework. Frequently neglected in the climate change mitigation and adaptation literature, carbon accounting practices ultimately define the nuts and bolts of what counts and which resources (forest, forest-based or other) are favored and utilized. For Annex I countries in the Kyoto Mechanism, the Incentive Gap under forest management (FM) is significantly large: some 75% or more of potential forestry-based carbon sequestration is not effectively incentivized or mobilized for climate change mitigation and adaptation (Ellison etal. 2011a). In this paper, we expand our analysis of the Incentive Gap to incorporate the changes agreed in Durban and encompass both a wider set of countries and a larger set of omitted carbon pools. For Annex I countries, based on the first 2years of experience in the first Commitment Period (CP1) we estimate the IG in FM at approximately 88%. Though significantly reduced in CP2, the IG remains a problem. Thus our measure of missed opportunities under the Kyoto and UNFCCC framework - despite the changes in Durban - remains important. With the exception perhaps of increased energy efficiency, few sinks or sources of reduced emissions can be mobilized as effectively and efficiently as forests. Thus, we wonder at the sheer magnitude of this underutilized resource

Sustainable Phosphorus Loadings from Effective and Cost-Effective Phosphorus Management Around the Baltic Sea

Nutrient over-enrichment of the Baltic Sea, accompanied by intensified algal blooms and decreasing water clarity, has aroused widespread concern in the surrounding countries during the last four decades. This work has used a well-tested dynamic mass-balance model to investigate which decrease in total phosphorus loading would be required to meet the environmental goal to restore the trophic state in the Baltic Sea to pre-1960s levels. Furthermore, the extent to which various abatement options may decrease the phosphorus loading in a cost-effective manner has been studied. Upgrading urban sewage treatment in the catchment could, alone or in combination with banning phosphates in detergents, be sufficient to meet the set environmental goal, at an estimated annual basin-wide cost of 0.21–0.43 billion euro. Such a plan would potentially decrease the total phosphorus loading to the Baltic Sea with 6,650–10,200 tonnes per year

New Insights Into Legacy Phosphorus From Fractionation of Streambed Sediment

Streambed and lake sediment was studied in Savjaan, a eutrophic mesoscale catchment (722 km(2)) in central Sweden. Triplicate sediment cores from five lakes and nine streams, ranging from headwater to fourth order, were sampled. The sediment was analyzed with a sequential extraction method, where six different phosphorus (P) fractions were measured. The results showed that streambed sediments store considerable amounts of P and in some cases have comparable P contents (g/kg DW) to lake sediment. Land use, soil type, and drainage area (location in the catchment) had a significant effect on the different P fractions found in surficial sediments. Sediment from lakes and forested headwater streams generally had high proportions of organic P and iron bound P. In larger streams located in agricultural areas on clay soils closer to the catchment outlet, with dense sediment and a relatively low proportion of organic matter, P was to a larger extent bound to calcium. Streambed sediment may be an important catchment scale P store and should be considered when modeling catchment P dynamics. The large stores of streambed legacy P should also be considered when performing ditch maintenance to avoid unnecessary mobilization of bioavailable P

Capturing the heterogeneity of sub-national production in global trade flows

With increasingly complex and globalised supply chains, agricultural production and related impacts are often far removed from the point of final demand and difficult to trace. Accurately linking consumption to production is essential to understand drivers, key actors, and to facilitate actionable adaptation strategies to minimise negative impacts and guarantee food security. Here a hybridised multiregional input-output (MRIO) model, IOTA, is introduced. IOTA utilises sub-national and national level production, trade and environmental data, national scale commodity-use data, and a global economic MRIO, to link sub-national production and associated impacts to regional final consumption. In an example case-study, applying the model to Brazilian soy production and related land use for EU consumption, the relative levels of production in Brazilian states to meet EU demand differ from those of total production, and differ further still between the EU's constituent countries. Patterns can also vary considerably within a country's consumption profile depending on the sector of purchase. The linking of consumption to sub-national production and trade allows for more accurate and meaningful connections to be made between consumer behaviour and the associated impacts and risks. This enhanced understanding of consumption-driven impacts in turn informs, and allows for, more targeted and effective policy interventions to tackle the pressures and risks associated with agricultural commodity production for a global market

Calculating the optimal number of contaminant samples by means of data worth analysis

This is a study of Bayesian data worth analysis in environmental clean-up applications. Its focus is on calculatingthe worth of simultaneously taking several (soil) samples in a small homogeneous area and on finding the optimalnumber of samples to take, by relating the reduction in risk cost from sampling, that is, data worth, to the cost ofthe samples. Even though the cost of one sample may be higher than the risk cost reduction it provides, this studyshows that several samples may be cost-efficient. This is mainly due to two factors: one is that the unit sample costoften decreases as the number of samples increase; another, more important, factor is that the data worth of severalsamples typically is higher than the worth of fewer samples. Copyright # 2006 John Wiley & Sons, Ltd