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Home » Large uncertainties in trends of energy demand under climate change

Large uncertainties in trends of energy demand under climate change

EnergyDemand1

By Adrien Deroubaix, Inga Labuhn, Marie Camredon, Benjamin Gaubert, Paul-Arthur Monerie, 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 mid-latitude 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 CO2 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 neglects the full range of possible future temperatures. A recent global analysis of numerous factors involved in the energy demand predictions showed a weak agreement in these projections for hot and cold days. To go further, the future temperature being highly variable among climate projections, the uncertainties related to climate need to be quantified and included in estimates of future energy demand. A consistent global analysis of these uncertainties is still missing.

This new study focuses on proxies of the climate-driven energy demand for heating and cooling buildings and presents a global analysis of future trends together with a comprehensive analysis of uncertainties linked to temperature projections.

To this end, the proxies of the climate-driven energy demand derived from the Degree-Days methodology are calculated using the simulated surface air temperatures of 30 CMIP5 (Coupled Model Inter-comparison Project phase 5) general circulation models (GCMs) and two pathways of future greenhouse-gas concentrations.

We show that the increasing trends in cooling energy demand are stronger than the decreasing trends in heating with the MMM of all 30 models. However, where the trends in cooling are the strongest, the variability of the trends between individual models is high, making estimates of future energy demand uncertain in these regions.

Results

  • Proxies of climate-driven energy demand
    HDD and CDD calculated with the temperature of historical climate simulations have been validated against observations. We define our heating and cooling—climate-driven energy demand—proxies as the annual HDD and CDD sums calculated from daily mean, minimum and maximum temperatures following the UK Met Office methodology for each of the 30 CMIP5 climate simulations.

    The advantage of HDD or CDD annual sums is that they can be compared on a global scale, regardless of the timing and length of local heating and cooling seasons. The heating and cooling proxies are presented for the MMM as averages over three 20-year periods 1941–1960, 1981–2000 and 2021–2040 (Supplementary Fig. 1).

    The spatial patterns of the MMM of the heating and cooling proxies are closely linked to the MMM of temperature on a global scale (comparing Supplementary Fig. 1 and Supplementary Fig. 2). The decrease in HDD and the increase in CDD between the three studied time periods are also consistent with the underlying temperature increase.

    Our results show typical values of the heating proxy over land areas between 0 and 1 500 HDD in inter-tropical regions (from 30°N to 30°S), between 1500 and 5000 HDD in mid-latitude regions (from 60°N to 30°N; or from 60°S to 30°S) and above 5000 HDD in polar regions (above 60°N or 60°S).

    Values of the cooling proxy are between 400 and 2 000 CDD in inter-tropical regions, and between 0 and 400 CDD in mid-latitudes. These values change in a warming world. However, the magnitude of the changes is not globally uniform (Supplementary Fig. 1).

  • Heating and cooling changes in the past and in the future
    To quantify the magnitude of past and future changes, we use the absolute differences in the heating and cooling proxies between 1981–2000 and 1941–1960, henceforth referred to as past changes, and between 2021–2040 and 1981–2000, henceforth referred to as future changes.

    Fig. 1: Global climate-driven changes in energy demand for heating and cooling buildings. Image credit: Nature Communications

    EnergyDemand2Fig. 2: Global climate-driven trends in energy demand for heating and cooling buildings. Image credit: Nature Communications

    We estimate the heating and cooling proxies from the CMIP5 historical simulations for the past and from the projections using the Representative Concentration Pathway 8.5 (RCP8.5; unless otherwise stated) for the future. The MMM heating proxy decreased and the MMM cooling proxy increased over the course of both the past and the future time periods.

    In the past, the most important changes in the heating proxy (below −200 HDD) occurred over polar regions (Fig. 1a), while, in the future, a decrease in the heating proxy of at least this magnitude occurs over the entire Northern Hemisphere (Fig. 1b). The increase in the cooling proxy was small in the past, below +100 CDD, everywhere except in some (semi-)arid parts of West Africa (Fig. 1c).

    The projected future increase in the cooling proxy, on the other hand, exceeds +100 CDD in most of the mid-latitude regions, exceeds +300 CDD in large parts of the tropics, and exceeds +400 CDD in Amazonia, in parts of the Sahel and in the Arabian Peninsula (Fig. 1d).

    Changes in the heating and cooling proxies have similar spatial patterns in the past and the future, with an overall extension of the areas with significant changes projected for the future (Fig. 1a, c compared to Fig. 1b, d). Mid-latitude regions present significant changes in both the heating and the cooling proxies.

    Areas with non-significant changes in the heating proxy are projected to reduce to tropical ocean regions, including tropical islands, as well as Amazonia in the future (Fig. 1b). Conversely, areas with non-significant changes in the cooling proxy are projected to reduce to the northern (above 40°N) and southern (below 40°S) oceans, whereas there is a significant change over all continental areas (except Greenland and Antarctica) in the future (Fig. 1d).

  • Comparing trends in heating and cooling
    Even when the absolute differences in some regions are small from one period to another, they could lead to significant changes in societal behaviour, such as widespread acquisition of cooling systems, as people feel a difference in thermal comfort relative to the past. We quantify trends in climate-driven energy demand for heating and cooling buildings by computing the relative differences in our proxies for the past and the future (cf. Methods section), which leads to important trends in the surroundings of the areas with non-significant changes (grey shaded areas in Fig. 1).

    Over continental areas, the decreasing trend in the MMM heating proxy was weak, ranging from −20 to 0% in the past (Fig. 2a). This trend is projected to become clearly negative everywhere in the future, reaching at least −5% (Fig. 2b).

    The increasing trend in the MMM cooling proxy was weak in the past, ranging between 0 and +20% over continental areas (Fig. 2c). This trend is also projected to be more pronounced in the future, exceeding +10% everywhere, reaching at least +20% over mid-latitude regions, and more than +60% in many northern hemisphere regions (Fig. 2d).

    Over mid-latitude oceans, the projected trend in the cooling proxy is to exceed +100%, which leads to strong gradients close to the coastlines, where an important part of the population lives.

 

 Notes: This is an extract of the full paper available on nature.com

 – Article number: 5197 (2021). Re-published under creative commons license. 


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