scholarly journals Pathways limiting warming to 1.5°C: a tale of turning around in no time?

Author(s):  
Elmar Kriegler ◽  
Gunnar Luderer ◽  
Nico Bauer ◽  
Lavinia Baumstark ◽  
Shinichiro Fujimori ◽  
...  

We explore the feasibility of limiting global warming to 1.5°C without overshoot and without the deployment of carbon dioxide removal (CDR) technologies. For this purpose, we perform a sensitivity analysis of four generic emissions reduction measures to identify a lower bound on future CO 2 emissions from fossil fuel combustion and industrial processes. Final energy demand reductions and electrification of energy end uses as well as decarbonization of electricity and non-electric energy supply are all considered. We find the lower bound of cumulative fossil fuel and industry CO 2 emissions to be 570 GtCO 2 for the period 2016–2100, around 250 GtCO 2 lower than the lower end of available 1.5°C mitigation pathways generated with integrated assessment models. Estimates of 1.5°C-consistent CO 2 budgets are highly uncertain and range between 100 and 900 GtCO 2 from 2016 onwards. Based on our sensitivity analysis, limiting warming to 1.5°C will require CDR or terrestrial net carbon uptake if 1.5°C-consistent budgets are smaller than 650 GtCO 2 . The earlier CDR is deployed, the more it neutralizes post-2020 emissions rather than producing net negative emissions. Nevertheless, if the 1.5°C budget is smaller than 550 GtCO 2 , temporary overshoot of the 1.5°C limit becomes unavoidable if CDR cannot be ramped up faster than to 4 GtCO 2 in 2040 and 10 GtCO 2 in 2050. This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels’.

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3204
Author(s):  
Michał Sabat ◽  
Dariusz Baczyński

Transmission, distribution, and micro-grid system operators are struggling with the increasing number of renewables and the changing nature of energy demand. This necessitates the use of prognostic methods based on ever shorter time series. This study depicted an attempt to develop an appropriate method by introducing a novel forecasting model based on the idea to use the Pareto fronts as a tool to select data in the forecasting process. The proposed model was implemented to forecast short-term electric energy demand in Poland using historical hourly demand values from Polish TSO. The study rather intended on implementing the range of different approaches—scenarios of Pareto fronts usage than on a complex evaluation of the obtained results. However, performance of proposed models was compared with a few benchmark forecasting models, including naïve approach, SARIMAX, kNN, and regression. For two scenarios, it has outperformed all other models by minimum 7.7%.


Smart Cities ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 112-145
Author(s):  
Daniel Then ◽  
Johannes Bauer ◽  
Tanja Kneiske ◽  
Martin Braun

Considering the European Union (EU) climate targets, the heating sector should be decarbonized by 80 to 95% up to 2050. Thus, the macro-trends forecast increasing energy efficiency and focus on the use of renewable gas or the electrification of heat generation. This has implications for the business models of urban electricity and in particular natural gas distribution network operators (DNOs): When the energy demand decreases, a disproportionately long grid is operated, which can cause a rise of grid charges and thus the gas price. This creates a situation in which a self-reinforcing feedback loop starts, which increases the risk of gas grid defection. We present a mixed integer linear optimization model to analyze the interdependencies between the electricity and gas DNOs’ and the building owners’ investment decisions during the transformation path. The results of the investigation in a real grid area are used to validate the simulation setup of a sensitivity analysis of 27 types of building collectives and five grid topologies, which provides a systematic insight into the interrelated system. Therefore, it is possible to identify building and grid configurations that increase the risk of a complete gas grid shutdown and those that should be operated as a flexibility option in a future renewable energy system.


2012 ◽  
Vol 621 ◽  
pp. 352-355
Author(s):  
Zhong Fu Tan ◽  
Shu Xiang Wang ◽  
Chen Zhang ◽  
Li Qiong Lin ◽  
Yin Hui Zhao

This paper analyses multi influencing factors of energy demand, using energy demand forecast regression model reveals inner relations between each factor and energy demand. Establish simulation model of the relation between GDP, energy intense and energy demand. Under the change in population, urbanization and energy efficiency, this paper gives analysis model of energy demand change.


Science ◽  
1972 ◽  
Vol 175 (4027) ◽  
pp. 1279-1279
Author(s):  
K. K. Bertine ◽  
Edward D. Goldberg

Sign in / Sign up

Export Citation Format

Share Document