Climate change scenario | EPFL Graph Search

Climate change scenarios or socioeconomic scenarios are projections of future greenhouse gas (GHG) emissions used by analysts to assess future vulnerability to climate change. Scenarios and pathways are created by scientists to survey any long term routes and explore the effectiveness of mitigation and helps us understand what the future may hold this will allow us to envision the future of human environment system. Producing scenarios requires estimates of future population levels, economic activity, the structure of governance, social values, and patterns of technological change. Economic and energy modelling (such as the World3 or the POLES models) can be used to analyze and quantify the effects of such drivers. Scientists can develop separate international, regional and national climate change scenarios. These scenarios are designed to help stakeholders understand what kinds of decisions will have meaningful effects on climate change mitigation or adapta

What are the likely changes in mercury concentration in the Arctic atmosphere and ocean under future emissions scenarios?

Hélène Paule Angot

Arctic mercury (Hg) concentrations respond to changes in anthropogenic Hg emissions and environmental change. This manuscript, prepared for the 2021 Arctic Monitoring and Assessment Programme Mercury Assessment, explores the response of Arctic Ocean Hg concentrations to changing primary Hg emissions and to changing sea-ice cover, river inputs, and net primary production. To do this, we conduct a model analysis using a 2015 Hg inventory and future anthropogenic Hg emission scenarios. We model future atmospheric Hg deposition to the surface ocean as a flux to the surface water or sea ice using three scenarios: No Action, New Policy (NP), and Maximum Feasible Reduction (MFR). We then force a five-compartment box model of Hg cycling in the Arctic Ocean with these scenarios and literature-derived climate variables to simulate environmental change. No Action results in a 51% higher Hg deposition rate by 2050 while increasing Hg concentrations in the surface water by 22% and

2022

Dealing with Correlations in Discrete Choice Models

Anna Fernández Antolín

The focus of this thesis is to develop methods to address research challenges related to correlation patterns in discrete choice models. In the context of correlations within alternatives, we extend the novel methodology of the multiple indicator solution (MIS) to deal with endogeneity, and show, through its theoretical derivation, that it is applicable when there are interactions between observed and unobserved variables. In the context of correlations between alternatives, we discuss the importance of using models that can capture them, such as cross nested logit models. We show, through real world examples, that ignoring these correlation patterns can have severe impacts on the obtained demand indicators, and that this can lead to wrong decisions by practitioners. We also address the challenge of using revealed preference data, where the attributes of the non-chosen alternatives are unavailable, and propose a solution based on multiple imputations of their empirical distributions. In the thesis, we also contribute to the existing literature by gaining a better understanding of private motorized modes, in terms of modal split and purchases of new cars. Related to modal split, we use a mode choice case study in low density areas of Switzerland. We find that ignoring the car-loving attitude of individuals leads to incorrect value of time estimates and elasticities, which might have severe implications in the pricing schemes of public transportation, for example. Related to the purchase of new cars, we use data from new car acquisitions in France in 2014, and focus on hybrid and electric vehicles. We find elasticities to price that are in line with the literature, and willingness to pay values in line with the market conditions. We also study the impact of different future policy scenarios and find that the sales of new electric vehicles could reach around 1% as a result of a major technological innovation that would render electric vehicles less expensive. In the last part of the thesis, we propose the discrete-continuous maximum likelihood (DCML) framework, which consists in estimating discrete and continuous parameters simultaneously. This innovative idea, opens the door to new research avenues, where decisions that were usually taken by the analyst can now be data driven. As an illustration, we show that correlations between alternatives can be identified at the estimation level, and do not need to be assumed by the analyst. The DCML framework consists in a mixed integer linear program (MILP) in which the log-likelihood estimator is linearized. This linearization might be useful to estimate parameters of other discrete choice models for which the log-likelihood function is not concave (and therefore global optimality is not insured by the optimization algorithms), since for an MILP, a global optimum is guaranteed. We use a simple mode choice case study for the proof-of-concept of the DCML framework, and use it to investigate its strengths and limitations. The preliminary results presented in the thesis seem very promising. To summarize, we develop methods to deal with correlations in discrete choice models that are relevant to real world problems, and show their applicability by using transportation examples. The contributions are therefore both theoretical and applied. The new methods proposed open the door to new research directions in the discrete choice field.

EPFL2018

Cost and benefits of climate change in Switzerland

Anita Frehner, Wolfgang Knoke, Dario Stocker, Philippe Thalmann, Boris Thurm, Marc Vielle, Frank Vöhringer

Understanding the economic magnitude of climate change impacts is a prerequisite for developing adequate adaptation strategies. In Switzerland, despite new climate scenarios and impact studies, only few impacts have been monetized. Our objective is to assess costs and opportunities of climate change for Switzerland by 2060, while enhancing the assessment methods. Using inputs from bottom-up impact studies, we simulate the economic consequences of climate scenarios in a CGE framework. We cover health, buildings/infrastructure, energy, water, agriculture, tourism, the spill-overs to other sectors, and international effects. Due to data constraints, significant impacts have not been quantified, e.g. for heat waves and droughts more extreme than the 2060 average climate. For the considered impacts, welfare decreases by 0.37% to 1.37% in 2060 relative to a reference without climate change. Higher summer temperatures increase mortality and decrease productivity. Contrariwise, tourism benefits from extended summer seasons. Regarding energy, increased demand for cooling is overcompensated by savings in heating.

2019

Dealing with Correlations in Discrete Choice Models

Anna Fernández Antolín

EPFL2018