A Statement on the Appropriate Role for Research and Development in Climate Policy

This statement is issued by a group of economists and scientists which met at Stanford University on October 18, 2008 to discuss the role of research and development (R&D) in developing effective policies for addressing the adverse potential consequences of climate change. We believe that climate change is a serious issue that governments need to address. We also believe that research and development needs to be a central part of governments’ strategies for responding to this challenge. Solutions to manage long-term risks will require the development and global deployment of a range of technologies for energy supply and end-use, land-use, agriculture and adaptation that are not currently commercial. A key potential benefit of focused scientific and technological research and development investment is that it could dramatically reduce the cost of restricting greenhouse gas emissions by encouraging the development of more affordable, better performing technologies.

Modeling coupled nitrification–denitrification in soil with an organic hotspot

The emission of nitrous oxide (N2O) from agricultural soils to the atmosphere is a significant contributor to anthropogenic greenhouse gas emissions. The recycling of organic nitrogen (N) in manure and crop residues may result in spatiotemporal variability in N2O production and soil efflux which is difficult to capture by process-based models. We propose a multi-species, reactive transport model to provide detailed insight into the spatiotemporal variability in nitrogen (N) transformations around such N2O hotspots, which consists of kinetic reactions of soil respiration, nitrification, nitrifier denitrification, and denitrification represented by a system of coupled partial differential equations. The model was tested with results from an incubation experiment at two different soil moisture levels (−30 and −100 hPa) and was shown to reproduce the recorded N2O and dinitrogen (N2) emissions and the dynamics of important carbon (C) and N components in soil reasonably well. The simulation indicated that the four different microbial populations developed in closely connected but separate layers, with denitrifying bacteria growing within the manure-dominated zone and nitrifying bacteria in the well-aerated soil outside the manure zone and with time also within the manure layer. The modeled N2O production within the manure zone was greatly enhanced by the combined effect of oxygen deficit, abundant carbon source, and supply of nitrogenous substrates. In the wetter soil treatment with a water potential of −30 hPa, the diffusive flux of nitrate (NO3-) across the manure–soil interface was the main source of NO3- for denitrification in the manure zone, while at a soil water potential of −100 hPa, diffusion became less dominant and overtaken by the co-occurrence of nitrification and denitrification in the manure zone. Scenarios were analyzed where the diffusive transport of dissolved organic carbon or different mineral N species was switched off, and they showed that the simultaneous diffusion of NO3-, ammonium (NH4+), and nitrite (NO2-) was crucial to simulate the dynamics of N transformations and N2O emissions in the model. Without considering solute diffusion in process-based N2O models, the rapid turnover of C and N associated with organic hotspots can not be accounted for, and it may result in the underestimation of N2O emissions from soil after manure application. The model and its parameters allow for new detailed insights into the interactions between transport and microbial transformations associated with N2O emissions in heterogeneous soil environments.</p

Preferences and skills of Indian public sector teachers

With a sample of 700 future public sector primary teachers in India, a Discrete Choice Experiment is used to measure job preferences, particularly regarding location. General skills are also tested. Urban origin teachers and women are more averse to remote locations than rural origin teachers and men respectively. Women would require a 26-73 percent increase in salary for moving to a remote location. The results suggest that existing caste and gender quotas can be detrimental for hiring skilled teachers willing to work in remote locations. The most preferred location is home, which supports decentralised hiring, although this could compromise skills

Do clinical guidelines reduce clinician dependent costs?

Clinician dependent costs are the costs of care that are under the discretion of the healthcare provider. These costs include the costs of drugs, tests and investigations, and discretionary outpatient visits and impatient stays. The purpose of this review was to summarize recent evidence, relevant to both developed and developing countries on whether evidence based clinical guidelines can change hospitals variable costs which are clinician dependent, and the degree of financial savings achieved at hospital level. Potential studies for inclusion were identified using structured searches of Econlit, J-Stor, and Pubmed databases. Two reviewers independently evaluated retrieved studies for inclusion. The methodological quality of the selected articles was assessed using the Oxford Centre for Evidence- Based Medicine (CEBM) levels of evidence. The results suggest that 10 of the 11 interventions were successful reducing financial costs. Most of the interventions, either in modeling studies or real interventions generate significant financial saving, although the former reported higher savings because the studies assumed 100 percent compliance

The Abisko Polar Prediction School

Polar regions are experiencing rapid climate change, faster than elsewhere on Earth with consequences for the weather and sea ice. This change is opening up new possibilities for businesses such as tourism, shipping, fisheries and oil and gas extraction, but also bringing new risks to delicate polar environments. Effective weather and climate prediction is essential to managing these risks, however our ability to forecast polar environmental conditions over periods from days to decades ahead falls far behind our abilities in the mid-latitudes. In order to meet the growing societal need for young scientists trained in this area, a Polar Prediction School for early career scientists from around the world was held in April 2016

Active learning and optimal climate policy

This paper develops a climate-economy model with uncertainty, irreversibility, and active learning. Whereas previous papers assume learning from one observation per period, or experiment with control variables to gain additional information, this paper considers active learning from investment in monitoring, specifically in improved observations of the global mean temperature. We find that the decision maker invests a significant amount of money in climate research, far more than the current level, in order to increase the rate of learning about climate change. This helps the decision maker make improved decisions. The level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations. As the uncertainty about climate change is smaller, active learning reduces the optimal carbon tax. The greater the risk, the larger is the effect of learning. The method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable, for instance, the precision at which we observe GDP, unemployment, or the quality of education

Evidence of Market Power in the Atlantic Steam Coal Market Using Oligopoly Models with a Competitive Fringe

Before 2004 South Africa was the dominant steam coal exporter to the European market. However a new market situation with rising global demand and prices makes room for a new entrant: Russia. The hypothesis investigated in this paper is that the three incumbent dominant firms located in South Africa and Colombia reacted to that new situation by exerting market power and withheld quantities from the market in 2004 and 2005. Three market structure scenarios of oligopoly with a competitive fringe are developed to investigate this hypothesis: a Stackelberg model with a cartel, a Stackelberg model with a Cournot-oligopoly as leader and a Nash-bargaining model. The model with a Cournot oligopoly as leader delivers the best reproduction of the actual market situation meaning that the dominant players exert market power in a non-cooperative way without profit sharing. Furthermore some methodological clarifications regarding the modeling of markets with dominant players and a competitive fringe are made. In particular we show that the use of mixed aggregated conjectural variations can lead to outcomes that are inconsistent with the actions of rational profit-maximizing players

What Price Recreation in Finland?—A Contingent Valuation Study of Non-Market Benefits of Public Outdoor Recreation Areas

Basic services in Finnish national parks and state-owned recreation areas have traditionally been publicly financed and thus free of charge for users. Since the benefits of public recreation are not captured by market demand, government spending on recreation services must be motivated in some other way. Here, we elicit people’s willingness to pay (WTP) for services in the country’s state-owned parks to obtain an estimate of the value of outdoor recreation in monetary terms. A variant of the Tobit model is used in the econometric analysis to examine the WTP responses elicited by a payment card format. We also study who the current users of recreation services are in order to enable policymakers to anticipate the redistribution effects of a potential implementation of user fees. Finally, we discuss the motives for WTP, which reveal concerns such as equity and ability to pay that are relevant for planning public recreation in general and for the introduction of fees in particular

Delayed Action and Uncertain Targets: How Much Will Climate Policy Cost?

Despite the growing concern about actual on-going climate change, there is little consensus about the scale and timing of actions needed to stabilise the concentrations of greenhouse gases. Many countries are unwilling to implement effective mitigation strategies, at least in the short-term, and no agreement on an ambitious global stabilisation target has yet been reached. It is thus likely that some, if not all countries, will delay the adoption of effective climate policies. This delay will affect the cost of future policy measures that will be required to abate an even larger amount of emissions. What additional economic cost of mitigation measures will this delay imply? At the same time, the uncertainty surrounding the global stabilisation target to be achieved crucially affects short-term investment and policy decisions. What will this uncertainty cost? Is there a hedging strategy that decision makers can adopt to cope with delayed action and uncertain targets? This paper addresses these questions by quantifying the economic implications of delayed mitigation action, and by computing the optimal abatement strategy in the presence of uncertainty about a global stabilisation target (which will be agreed upon in future climate negotiations). Results point to short-term inaction as the key determinant for the economic costs of ambitious climate policies. They also indicate that there is an effective hedging strategy that could minimise the cost of climate policy under uncertainty, and that a short-term moderate climate policy would be a good strategy to reduce the costs of delayed action and to cope with uncertainty about the outcome of future climate negotiations. By contrast, an insufficient short-term effort significantly increases the costs of compliance in the long-term

Genetically Engineered Alginate Lyase-PEG Conjugates Exhibit Enhanced Catalytic Function and Reduced Immunoreactivity

Alginate lyase enzymes represent prospective biotherapeutic agents for treating bacterial infections, particularly in the cystic fibrosis airway. To effectively deimmunize one therapeutic candidate while maintaining high level catalytic proficiency, a combined genetic engineering-PEGylation strategy was implemented. Rationally designed, site-specific PEGylation variants were constructed by orthogonal maleimide-thiol coupling chemistry. In contrast to random PEGylation of the enzyme by NHS-ester mediated chemistry, controlled mono-PEGylation of A1-III alginate lyase produced a conjugate that maintained wild type levels of activity towards a model substrate. Significantly, the PEGylated variant exhibited enhanced solution phase kinetics with bacterial alginate, the ultimate therapeutic target. The immunoreactivity of the PEGylated enzyme was compared to a wild type control using in vitro binding studies with both enzyme-specific antibodies, from immunized New Zealand white rabbits, and a single chain antibody library, derived from a human volunteer. In both cases, the PEGylated enzyme was found to be substantially less immunoreactive. Underscoring the enzyme's potential for practical utility, >90% of adherent, mucoid, Pseudomonas aeruginosa biofilms were removed from abiotic surfaces following a one hour treatment with the PEGylated variant, whereas the wild type enzyme removed only 75% of biofilms in parallel studies. In aggregate, these results demonstrate that site-specific mono-PEGylation of genetically engineered A1-III alginate lyase yielded an enzyme with enhanced performance relative to therapeutically relevant metrics.Cystic Fibrosis Foundation (Research Development Program)National Center for Research Resources (U.S.) (P20RR018787-06