International News
LARGE UNCERTAINTIES IN TRENDS OF ENERGY DEMAND UNDER CLIMATE CHANGE
By Adrien Deroubaix , Inga Labuhn , Marie Camredon , Benjamin Gaubert , Paul-Arthur Monerie , Max Popp , Johanna Ramarohetra , Yohan Ruprich-Robert , Levi G . Silvers & Guillaume Siour
The energy demand for heating and cooling buildings is changing with global warming . Using proxies of climate-driven energy demand based on the heating and cooling Degree-Days methodology applied to thirty global climate model simulations , we show that , overall continental areas , the climate-driven energy demand trends for heating and cooling were weak , changing by less than 10 % from 1950 to 1990 , but become stronger from 1990 to 2030 , changing by more than 10 %.
With the multi-model mean , the increasing trends in cooling energy demand are more pronounced than the decreasing trends in heating . The changes in cooling , however , are highly variable depending on individual simulations , ranging from a few to several hundred percent in most of the densely populated midlatitude areas .
This work presents an example of the challenges that accompany future energy demand quantification as a result of the uncertainty in the projected climate .
INTRODUCTION In a warming world , most regions are expected to experience a reduction in the energy needed for heating , and an increase in the energy needed for cooling buildings . Anticipating those changes will help communities to adapt their buildings and energy systems to future climate .
The energy demand for heating and cooling buildings is driven by a climatic component , a socio-economic component ( population density and behaviour of people , gross domestic product , price of energy ) and by a technological component ( design and material determining the thermal properties of the building , efficiency of heating and cooling systems ).
In addition to long-term trends in these three components , there is a short-term variability in energy demand , and in related
CO 2 emissions , which is mostly linked to climate variability . Among the climate variables that influence the energy demand , ambient temperature is prominent , or more precisely its combination with humidity . The minimum and maximum daily temperatures are good predictors of the energy demand as they represent the diurnal cycle of ambient temperature .
The amplitude of this diurnal cycle is large in dry areas and small in wet areas . The day-to-day variability in energy demand depends on temperature following a V-shape curve with a minimum related to human thermal comfort as well as other socio-economic and technological factors .
This minimum is found for a similar daily mean temperature around 16 ° C for 35 countries in Europe . Therefore , a comprehensive analysis relating the trends in the projected temperature and its consequences on energy demand is possible .
The Degree-Days methodology is the historical method for estimating the heating and cooling energy demand of buildings ( cf . Methods section ). A key assumption of this method is that the average temperature of a day provides a good proxy for the human thermal discomfort , and thus of the daily energy demand .
Degree-Days represent the difference between the outside daily temperature and the range of comfortable indoor temperatures . In other words , Degree-Days are the cumulated temperature during one day below a base temperature , the so-called Heating Degree-Days ( HDD ); and above a base temperature , the so-called Cooling Degree-Days ( CDD ).
In the context of climate change , the estimation of energy demand of buildings in the coming decades should include changes in climate-driven energy demand , which are expected to become increasingly important in the future . The use of climate projections for this purpose is thus pivotal . Future changes in the energy demand for heating and cooling buildings through the twenty-first century have been estimated using Degree-Days calculated with the temperature output from climate model simulations for the US and Europe individually .
A vast amount of literature investigates climate change impacts on future energy demand together with implications for the society in terms of energy system capacity , regulations and mitigation , adaptation , or socio-economic developments . These studies consider the complexity of the socio-economic and technological components , but the climatic component is overly simplified .
For instance , the use of Multi-Model Mean ( MMM ) climate projections or a single scenario of greenhouse-gas emissions
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