Interaction of European Carbon Trading and Energy Prices

This paper addresses the economic impact of the EU Emission Trading Scheme for carbon on wholesale electricity and gas prices. Specifically, we analyse the mutual relationships between electricity, gas and carbon prices in the daily spot markets in the United Kingdom. Using a structural co-integrated VAR model, we show how the prices of carbon and gas jointly influence the equilibrium price of electricity. Furthermore, we derive the dynamic pass-trough of carbon into electricity price and the response of electricity and carbon prices to shocks in the gas price.Carbon Emission Trading, Energy Markets, Structural VECM

A Pragmatic Approach to Wastewater Treatment Modelling: The Källby Wastewater Treatment Plant as a Case Study

A wastewater treatment plant prediction in your computer The Källby wastewater treatment plant was set-up in a mathematical model reflecting its actual behaviour. Are the commonly available measurements good enough to perform a simulation? What kind of outcomes can we expect? After you have read the heading and the introduction, I guess that two proper questions swirling around in your head might be: what is wastewater treatment and what is a model? First wastewater treatment is the process that allows the return of sewerage and industrial wastewater to water cycle with minimal environmental impact and in accordance with existing discharge limits. There are three main reasons why this is performed: protect people from waterborne diseases that may be originated by contact with untreated wastewater, safeguard water environment from pollution that may arise from discharge of untreated wastewater and support of relevant life and economic systems. Secondly I would answer that a model is the representation of a system of interest, that is something important to be studied. It often simplifies reality in order to describe only the relevant processes and makes use of software solutions to perform the required computations. Modelling applied to wastewater treatment allows to simulate the actual physical, biological and chemical processes taking place in a wastewater treatment plant. Now, why do we need to model a wastewater treatment plant? Nowadays modelling is used as a design tool, instead of traditional design procedures. It is the most feasible and maybe less costly way to attain a process optimisation and it can also help the plant operators to test some corrective actions without expensive and environmentally risky full scale tests...wow! Let's get to the point: The present work achieved to simulate the Källby wastewater treatment plant of Lund, Sweden. The work focused on the wastewater treatment lines, especially on carbon, nitrogen and phosphorus removal. The sludge treatment lines, necessary to dispose of sewage sludge produced during sewage treatment, were not included in the model. Only available real data from the database of the company managing the plant were used to feed the model, without performing any additional measurement campaign. A relevant part of the work regarded the data treatment concerning the influent concentration to generate the input file for the model. After that it was possible to perform the simulation. At this point comparison between real measurements and model outputs was allowed. The reasons causing the main mismatches between the model outputs and real data were investigated and a troubleshooting step was performed in order to try to fix them. Annual variations of nitrogen and phosphorus were shown by the model, meaning that, even with the limitation of poor data, modelling can still be a valuable tool to understand the behaviour of treatment plants and to predict the response of the plant to influent variations. The result of this thesis is a deeper understanding of the actual behaviour of the plant. It also allows evaluations of new scenarios and possible future changes of the operation. Knowledge achieved in this work could also be used by plant operator to troubleshoot or to find better control strategies. Enjoy the reading

ANALIZING WATER FRAMEWORK DIRECTIVE IMPACTS USING A MULTINOMIAL LOGIT LAND USE MODEL

We develop a two-stage, multinomial logit model of UK land use to investigate the impact of policy changes upon agriculture. The model utilizes a large panel database covering the entirety of England and Wales for 14 years between 1969 and 2004 integrated with the economic and physical environment determinants of all major agricultural land use types. Our model performs well in out-of-sample prediction of current land use and we use it to assess a proposed implementation of the Water Framework Directive via a tax on fertilizer. Results indicate that such policy change would generate substantial switching from arable to grassland systems, reducing significantly the amount of nitrate leaching into UK water-bodies.Water Framework Directive, Land use models, Discrete choice models, Multinomial logit, Agricultural and Food Policy, Land Economics/Use, Research Methods/ Statistical Methods, Resource /Energy Economics and Policy,

Spatially explicit integrated modeling and economic valuation of climate driven land use change and its indirect effects

We present an integrated model of the direct consequences of climate change on land use, and the indirect effects of induced land use change upon the natural environment. The model predicts climate-driven shifts in the profitability of alternative uses of agricultural land. Both the direct impact of climate change and the induced shift in land use patterns will cause secondary effects on the water environment, for which agriculture is the major source of diffuse pollution. We model the impact of changes in such pollution on riverine ecosystems showing that these will be spatially heterogeneous. Moreover, we consider further knock-on effects upon the recreational benefits derived from water environments, which we assess using revealed preference methods. This analysis permits a multi-layered examination of the economic consequences of climate change, assessing the sequence of impacts from climate change through farm gross margins, land use, water quality and recreation, both at the individual and catchment scale

Comunicazione elettorale e costruzione del consenso: considerazioni sul Petitionis (64 A.C.)

Lo scopo di questo articolo è tracciare alcuni paralleli tra i sistemi elettorali della Roma della tarda repubblica e quelli attualmente in uso nelle democrazie occidentali. Le similitudini sono mol t e, e ci ò per di verse ragioni. Tra queste l'influenza del modello romano sulle democrazie occidentali (in primo luogo su quella degli  Stati Uniti d’America) e la diminuzione del l'importanza dei partiti politici, grazie all'emergere della leadership e della copertura mediatica che hanno accorciato, almeno apparentemente, la distanza trai  politici e il popolo. L’antica città di Roma, con i suoi di battiti che avevano luogo nel Foro, sotto gli occhi di tutti, presenta molti punti in comune con il global village, dove ognuno, grazie proprio alla copertura mediatica, ha l’impressione di essere in grado di seguire il candidato e di conoscerlo. Contesti politici simili producono strategie elettorali simili; per questo motivo, le istruzioni date da Quinto al suo più famoso fratello Marco Tullio Cicerone nel Commentariolum petitionis potrebbero costituire fonte di ispirazione per gli spin-doctors di oggi

Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data

This is the final version. Available from Springer via the DOI in this record. In response to the COVID-19 emergency, many countries have introduced a series of social-distancing measures including lockdowns and businesses’ shutdowns, in an attempt to curb the spread of the infection. Accordingly, the pandemic has been generating unprecedented disruption on practically every aspect of society. This paper demonstrates that high-frequency electricity market data can be used to estimate the causal, short-run impacts of COVID-19 on the economy, providing information that is essential for shaping future lockdown policy. Unlike official statistics, which are published with a delay of a few months, our approach permits almost real-time monitoring of the economic impact of the containment policies and the financial stimuli introduced to address the crisis. We illustrate our methodology using daily data for the Italian day-ahead power market. We estimate that the 3 weeks of most severe lockdown reduced the corresponding Italian Gross Domestic Product (GDP) by roughly 30%. Such negative impacts are now progressively declining but, at the end of June 2020, GDP is still about 8.5% lower than it would have been without the outbreak.Università degli Studi di Trent