scholarly journals REMIND2.1: transformation and innovation dynamics of the energy-economic system within climate and sustainability limits

2021 ◽  
Vol 14 (10) ◽  
pp. 6571-6603
Author(s):  
Lavinia Baumstark ◽  
Nico Bauer ◽  
Falk Benke ◽  
Christoph Bertram ◽  
Stephen Bi ◽  
...  
Keyword(s):  
Economic System ◽  
New Technologies ◽  
Linear Optimization ◽  
Scale Up ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Innovation Dynamics ◽  
Transformation Pathways ◽  
Economic Developments ◽  
Decentralized Market

Abstract. This paper presents the new and now open-source version 2.1 of the REgional Model of INvestments and Development (REMIND). REMIND, as an integrated assessment model (IAM), provides an integrated view of the global energy–economy–emissions system and explores self-consistent transformation pathways. It describes a broad range of possible futures and their relation to technical and socio-economic developments as well as policy choices. REMIND is a multiregional model incorporating the economy and a detailed representation of the energy sector implemented in the General Algebraic Modeling System (GAMS). It uses non-linear optimization to derive welfare-optimal regional transformation pathways of the energy-economic system subject to climate and sustainability constraints for the time horizon from 2005 to 2100. The resulting solution corresponds to the decentralized market outcome under the assumptions of perfect foresight of agents and internalization of external effects. REMIND enables the analyses of technology options and policy approaches for climate change mitigation with particular strength in representing the scale-up of new technologies, including renewables and their integration in power markets. The REMIND code is organized into modules that gather code relevant for specific topics. Interaction between different modules is made explicit via clearly defined sets of input and output variables. Each module can be represented by different realizations, enabling flexible configuration and extension. The spatial resolution of REMIND is flexible and depends on the resolution of the input data. Thus, the framework can be used for a variety of applications in a customized form, balancing requirements for detail and overall runtime and complexity.

scholarly journals REMIND2.1: Transformation and innovation dynamics of the energy-economic system within climate and sustainability limits

2021 ◽  
Author(s):  
Lavinia Baumstark ◽  
Nico Bauer ◽  
Falk Benke ◽  
Christoph Bertram ◽  
Stephen Bi ◽  
...  
Keyword(s):  
Economic System ◽  
New Technologies ◽  
Linear Optimization ◽  
Scale Up ◽  
Regional Model ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Innovation Dynamics ◽  
Transformation Pathways ◽  
Economic Developments

Abstract. This paper presents the new and now open-source version 2.1 of the REgional Model of INvestments and Development (REMIND). REMIND, as an Integrated Assessment Model (IAM), provides an integrated view on the global energy-economy-emissions system and explores self-consistent transformation pathways. It describes a broad range of possible futures and their relation to technical and socio-economic developments as well as policy choices. REMIND is a multi-regional model incorporating the economy and a detailed representation of the energy sector implemented in the General Algebraic Modeling System (GAMS). It uses non-linear optimization to derive welfare-optimal regional transformation pathways of the energy-economic system subject to climate and sustainability constraints for the time horizon 2005 to 2100. The resulting solution corresponds to the decentral market outcome under the assumptions of perfect foresight of agents and internalization of external effects. REMIND enables analyses of technology options and policy approaches for climate change mitigation with particular strength in representing the scale-up of new technologies, including renewables and their integration in power markets. The REMIND code is organized into modules that gather code relevant for specific topics. Interaction between different modules is made explicit via clearly defined sets of input/output variables. Each module can be represented by different realizations enabling flexible configuration and extension. The spatial resolution of REMIND is flexible and depends on the resolution of the input data. The framework can thus be used for a variety of applications in a customized form balancing requirements for detail and overall run-time and complexity.

scholarly journals The role of biomaterials for the energy transition from the lens of a national integrated assessment model

2021 ◽  
Vol 167 (3-4) ◽  
Author(s):  
Camilla C. N. de Oliveira ◽  
Gerd Angelkorte ◽  
Pedro R. R. Rochedo ◽  
Alexandre Szklo
Keyword(s):  
Integrated Assessment ◽  
Energy Transition ◽  
Integrated Assessment Model ◽  
Assessment Model

scholarly journals What matters to patients? A mixed method study of the importance and consideration of oncology patient demands

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mathias WAELLI ◽  
Etienne Minvielle ◽  
Maria Ximena Acero ◽  
Khouloud Ba ◽  
Benoit Lalloué
Keyword(s):  
Cancer Patients ◽  
Mixed Method ◽  
New Technologies ◽  
Care Pathway ◽  
Scale Up ◽  
Healthcare Delivery ◽  
Delivery Systems ◽  
Breast Cancer Patients ◽  
Structured Interviews ◽  
Oncology Patient

Abstract Background A patient-centred approach is increasingly the mandate for healthcare delivery, especially with the growing emergence of chronic conditions. A relevant but often overlooked obstacle to delivering person-centred care is the identification and consideration of all demands based on individual experience, not only disease-based requirements. Mindful of this approach, there is a need to explore how patient demands are expressed and considered in healthcare delivery systems. This study aims to: (i) understand how different types of demands expressed by patients are taken into account in the current delivery systems operated by Health Care Organisations (HCOs); (ii) explore the often overlooked content of specific non-clinical demands (i.e. demands related to interactions between disease treatments and everyday life). Method We adopted a mixed method in two cancer centres, representing exemplary cases of organisational transformation: (i) circulation of a questionnaire to assess the importance that breast cancer patients attach to every clinical (C) and non-clinical (NC) demand identified in an exploratory inquiry, and the extent to which each demand has been taken into account based on individual experiences; (ii) a qualitative analysis based on semi-structured interviews exploring the content of specific NC demands. Results Further to the way in which the questionnaires were answered (573 answers/680 questionnaires printed) and the semi-structured interviews (36) with cancer patients, results show that NC demands are deemed by patients to be almost as important as C demands (C = 6.53/7 VS. NC = 6.13), but are perceived to be considered to a lesser extent in terms of pathway management (NC = 4.02 VS C = 5.65), with a significant variation depending on the type of non-clinical demands expressed. Five types of NC demands can be identified: demands relating to daily life, alternative medicine, structure of the treatment pathway, administrative and logistic assistance and demands relating to new technologies. Conclusions This study shows that HCOs should be able to consider non-clinical demands in addition to those referring to clinical needs. These demands require revision of the healthcare professionals’ mandate and transition from a supply-orientated system towards a demand-driven approach throughout the care pathway. Other sectors have developed hospitality management, mass customisation and personalisation to scale up approaches that could serve as inspiring examples.

MITIGATION COST AND CLIMATE DAMAGE VERSUS INCENTIVE SHIFTS OF CLIMATE COALITION

2016 ◽  
Vol 07 (04) ◽  
pp. 1650011
Author(s):  
ZILI YANG
Keyword(s):  
Climate Change ◽  
Bargaining Game ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Policy Implications ◽  
Good Representation ◽  
Ghg Mitigation ◽  
Mitigation Cost ◽  
The Core ◽  
Cooperative Bargaining

Climate damage and greenhouse gas (GHG) mitigation cost plays important roles in a region’s willingness and incentives to join the global climate coalition. Negotiation of climate treaty can be modeled as a cooperative bargaining game of externality provision. The core of this game is a good representation of incentives of the participants. In this paper, we examine the relationship between the shocks of mitigation cost/climate damage and the shifts of the core of cooperative bargaining game of climate negotiation within the framework of RICE [Nordhaus and Yang, 1996. A regional dynamic general equilibrium model of alternative climate change strategies. American Economic Review, 86, 741–765], a widely used integrated assessment model (IAM) of climate change. Constructing a method that maps the core allocations onto a convex hull on the simplex of social welfare weights, we describe the scope of the core in simple metrics and capture the shifts of the core representation on the simplex in response to the shocks of mitigation cost and climate damage. A series of simulations are conducted in RICE to demonstrate the usefulness of the approach explored here. In addition, policy implications of methodological results are indicated.

scholarly journals Energy Production from Biogas: Competitiveness and Support Instruments in Latvia

2016 ◽  
Vol 53 (5) ◽  
pp. 43-53
Author(s):  
G. Klāvs ◽  
A. Kundziņa ◽  
I. Kudrenickis
Keyword(s):  
New Technologies ◽  
Local Economic Development ◽  
Renewable Energy Sources ◽  
Distribution Network ◽  
Scale Up ◽  
Electricity Production ◽  
Small Scale ◽  
Gas Distribution ◽  
Ex Post ◽  
The Impact

Abstract Use of renewable energy sources (RES) might be one of the key factors for the triple win-win: improving energy supply security, promoting local economic development, and reducing greenhouse gas emissions. The authors ex-post evaluate the impact of two main support instruments applied in 2010-2014 – the investment support (IS) and the feed-in tariff (FIT) – on the economic viability of small scale (up to 2MWel) biogas unit. The results indicate that the electricity production cost in biogas utility roughly corresponds to the historical FIT regarding electricity production using RES. However, if in addition to the FIT the IS is provided, the analysis shows that the practice of combining both the above-mentioned instruments is not optimal because too high total support (overcompensation) is provided for a biogas utility developer. In a long-term perspective, the latter gives wrong signals for investments in new technologies and also creates unequal competition in the RES electricity market. To provide optimal biogas utilisation, it is necessary to consider several options. Both on-site production of electricity and upgrading to biomethane for use in a low pressure gas distribution network are simulated by the cost estimation model. The authors’ estimates show that upgrading for use in a gas distribution network should be particularly considered taking into account the already existing infrastructure and technologies. This option requires lower support compared to support for electricity production in small-scale biogas utilities.

scholarly journals Evaluation of Integrated Assessment Model hindcast experiments: A case study of the GCAM 3.0 land use module

2017 ◽  
Author(s):  
Abigail C. Snyder ◽  
Robert P. Link ◽  
Katherine V. Calvin
Keyword(s):  
Integrated Assessment ◽  
Structural Changes ◽  
Spatial Scales ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Land Allocation ◽  
Time Period ◽  
Skill Scores ◽  
Performance Benchmarks

Abstract. Hindcasting experiments (conducting a model forecast for a time period in which observational data is available) are rarely undertaken in the Integrated Assessment Model (IAM) community. When they are undertaken, the results are often evaluated using global aggregates or otherwise highly aggregated skill scores that mask deficiencies. We select a set of deviation based measures that can be applied at different spatial scales (regional versus global) to make evaluating the large number of variable-region combinations in IAMs more tractable. We also identify performance benchmarks for these measures, based on the statistics of the observational dataset, that allow a model to be evaluated in absolute terms rather than relative to the performance of other models at similar tasks. This is key in the integrated assessment community, where there often are not multiple models conducting hindcast experiments to allow for model intercomparison. The performance benchmarks serve a second purpose, providing information about the reasons a model may perform poorly on a given measure and therefore identifying opportunities for improvement. As a case study, the measures are applied to the results of a past hindcast experiment focusing on land allocation in the Global Change Assessment Model (GCAM) version 3.0. We find quantitative evidence that global aggregates alone are not sufficient for evaluating IAMs, such as GCAM, that require global supply to equal global demand at each time period. Additionally, the deviation measures examined in this work successfully identity parametric and structural changes that may improve land allocation decisions in GCAM. Future work will involve implementing the suggested improvements to the GCAM land allocation system identified by the measures in this work, using the measures to quantify performance improvement due to these changes, and, ideally, applying these measures to other sectors of GCAM and other land allocation models.

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