Discounting investments in mitigation and adaptation: a dynamic stochastic general equilibrium approach of climate change

We use a dynamic stochastic general equilibrium model to determine efficient discount rates for climate (mitigation and adaptation) and non-climate investment in the face of climate change. Our main result is that the non-diversifiable risk in the economy may be related to both shocks in aggregate wealth and shocks in global average temperature. Therefore, both aggregate wealth and global average temperature will carry a risk premium reflecting their contribution to the total amount of non-diversifiable risk. We characterize both climate and non-climate investments by means of a contingent claim and show that climate and non-climate investments will in general be discounted at different rates. We discuss the conditions under which the discount rates of climate investments will be lower than the discount rate of non-climate investments. September 2013 : There is an�updated version of this paper availlable, read CPB Discussion Paper 257 .

Optimal regulation under unknown supply of distributed generation

As distributed generation (DG) continues to expand, larger low-voltage networks will be required in the future. However, regulated distribution network operators (DNOs) need to invest in new infrastructure without knowing a relevant determinant of network costs, the future amount of DG. Due to uncertainty, optimal network capacity needs to reflect the expected demand for capacity over all possible DG states. Therefore, not all capacity will be used if a low level of DG occurs. Optimal regulation that is set under asymmetric information about future DG needs to create incentives for the DNO to invest in this 'excess capacity' and also encourage optimal network utilization. In this case, an option menu that includes fixed fees and positive network charges on DG-producers fulfills these requirements and implements the first-best optimum. On the contrary, price-cap and revenue-cap regulation lead to either underinvestment or high information rents to the DNO.

Oxidoreductase fusions:engineering enzymes for coupled reactions and stability

Enzymes are the core of biological life. These tiny molecular machines can transform molecules, which enables organisms to grow. Aside from their biological role, enzymes are also used for various applications, such as: brewing of beer, making cheese, and removing dirt from clothes.There is great interest in the application of enzymes for the production of useful compounds, such as: (bio)materials, (bio)fuels, medicine, and food additives. Compared to chemical processes, a process with enzymes is greener and more sustainable. However, enzymes from nature are often not stable enough for large-scale industrial application; they rapidly fall apart. Aside from this lack of stability, it is also difficult and costly to produce enzymes.In this thesis, we studied the approach of producing two enzymes together, as one: enzyme fusion. Not only does this make the production of enzymes more favorable, in some cases the enzymes can directly work together in a 2-step process.In the final research chapter, we used another approach to improve enzyme application: mutagenesis through computational predictions. Enzymes are composed of hundreds of amino acids, and single amino acids can be exchanged by mutagenesis. Each amino acid interacts with all neighbouring amino acids. By swapping an amino acid with another one of different shape and property, such that it can make more and better interactions with the neighbouring amino acids, we can fortify the enzyme’s structure. The mutated enzyme could nearly resist boiling water, while the original enzyme fell apart around 40 °C

Dark matter search with XENON1T

Most matter in the universe consists of 'dark matter' unknown to particle physics. Deep underground detectors such as XENON1T attempt to detect rare collisions of dark matter with ordinary atoms. This thesis describes the first dark matter search of XENON1T, how dark matter signals would appear in the detector, and the statistical techniques used in the search. The final chapters set world-leading constraints on the cross-section with which dark and normal matter interact