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2.7: Energy Efficiency - Biology

2.7: Energy Efficiency - Biology


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2.7: Energy Efficiency

New exterior doors often fit and insulate better than older types. If you have older doors in your home, replacing them might be a good investment, resulting in lower heating and cooling costs.

If you're building a new home, you should consider buying the most energy-efficient doors possible.

When selecting doors for energy efficiency, it's important to first consider their energy performance ratings in relation to the local climate and your home's design. This will help narrow your selection.

The National Fenestration Rating Council (NFRC) label helps you compare energy performance ratings of doors. Learn more about the NFRC label.

Note that ENERGY STAR considers glass doors to be a type of window.

The label shows the solar heat gain coefficient (SHGC) and U-factor for the door.

Look for a low SHGC in a climate that mainly requires cooling and a high SHGC in a climate that requires heating. The range is from 0 to 1. SHGC measures how well a product keeps out solar heat.

Look for a low U-factor the range is from 0.00-2.00. The lower the U-factor, the better the door keeps in heat.


Upcoming Meetings

There are no Building America meetings scheduled at this time. Please subscribe to Building America news and updates to receive notification of future meetings.

Past Technical and Stakeholder Meetings

Expert Meetings

Building America hosts several expert meetings each year on a variety of building energy efficiency topics, which are presented by research team members. This page provides links to past expert meetings proceedings, including presentations and related documents.

DateTeamExpert Meeting
9/29/14IBACOSCode Challenges with Multi-Family Area Separation Walls
10/12/12BSCRecommended Approaches to Humidity Control in High Performance Homes
9/28/12ARBIExploring the Disconnect Between Rated and Field Performance of Water Heating Systems
7/28/12BSCCladding Attachment over Exterior Insulation
6/28/12PARRCombustion Safety
2/8/12NAHB Research CenterKey Innovations for Adding Energy Efficiency to Maintenance Projects
11/15/11NorthernSTARFoundation Research Results
11/14/11NorthernSTARWindow Options for New and Existing Homes
10/31/11ARBIEnergy Savings You Can Bank On
10/25/11CARBRetrofit Implementation: A Neighborhood at a Time
10/13/11ARIESAdvanced Envelope Research Update
9/13/11BARATransforming Existing Buildings Through New Media: An Idea Exchange
7/31/11BSCRecommendations for Applying Water Heaters in Combination Space and Domestic Water Heating Systems
7/30/11BSCInterior Insulation of Masonry Structures
7/28/11PARRAchieving the Best Installed Performance from High-Efficiency Residential Gas Furnaces
7/13/11ARIESHydronic Heating in Multifamily Buildings
3/29/11IBACOSTransitioning Traditional HVAC Contractors to Whole House Performance
3/11/11IBACOSSimplified Space Conditioning Systems for Energy Efficient Houses
11/16/10BA-PIRCDelivering Better, Cheaper, and Faster Retrofits through Stakeholder-Focused Research
10/1-2/10NRELAdvanced Home Energy Management
4/26/10BSCDiagnostic Measurement and Performance Feedback for Residential Space Conditioning System Equipment

Keep current with upcoming events and news by subscribing to Building America updates.

Forrestal Building
1000 Independence Avenue, SW
Washington, DC 20585


Rules for Rounding Off Numbers

Rule 1: Determine what your rounding digit is and look at the digit to the right of it ( highlighted digit ).If the highlighted digit is 1, 2, 3, 4 simply drop all digits to the right of rounding digit.
Example:
3.42 3 may be rounded off to 3.42 when rounded off to the nearest hundredths place.
3.4 2 3 may be rounded off to 3.4 when rounded off to the nearest tenths place
3. 4 23 may be rounded off to 3 when rounded off to the nearest units place.

Rule 2: Determine what your rounding digit is and look at the digit to the right of it ( highlighted digit ).If the highlighted digit is 5, 6, 7, 8, 9 add one to the rounding digit and drop all digits to the right of rounding digit.
Example:
2.78 6 may be rounded off to 2.79 when rounded off to the nearest hundredths place.
2.7 8 6 may be rounded off to 2.8 when rounded off to the nearest tenths place.
2. 7 86 may be rounded off to 3 when rounded off to the nearest units place.
2.8 5 6 may be rounded off to 2.9 when rounded off to the nearest tenths place.

Exception to Rule 2: When the first digit dropped is 5 and there are no digits following or the digits following are zeros, make the preceding digit even (i.e., round off to the nearest even digit).
Example:
2.31 5 and 2.32 5 are both 2.32 when rounded off to the nearest hundredths place.


Examples and tips regarding the EGEE 102 Home Activities:

a. Avoid rounding off small whole numbers

b. While rounding small numbers involving decimals don’t round off before the nearest hundredths place.

• 45.67844 should be rounded off preferably to 45.68 or 45.678 or 45.6784 and not to 45.7 or 46 to avoid errors.

• This tip need not be used for numbers >100 because the error involved is small.

c. 2. 9 8 4 may be rounded off to 3 if the rounding is done either to the nearest units or tenths.


Most U.S. wind capacity built since 2011 is located in the center of the country

Wind capacity in the United States has increased significantly over the past decade, from 40.1 gigawatts (GW) in January 2011 to 118.3 GW at the end of 2020. This wind capacity growth was mostly concentrated in the middle of the country.

The Texas, Midwest, and Central regions&mdashhome to some of the country’s most prolific wind resources&mdashcombined accounted for the largest share of U.S. wind capacity growth from 2011 to 2020 with 73% of additions. At the beginning of 2011, the Texas region (which covers the area served by ERCOT) had 9.4 GW of wind capacity by the end of 2020, capacity had grown to 27.9 GW. Wind capacity in the Midwest region tripled, rising from 8.6 GW in 2011 to 26.9 GW in 2020. In 2011, the Central region had about half the wind capacity of the Texas and Midwest regions. After adding more wind capacity (20.5 GW) in the last decade than any other region, the Central region is now one of the top U.S. wind capacity regions.

Despite having similar wind capacity as the Texas and Midwest regions in 2011, the Northwest region installed far less new wind capacity (8.6 GW) between 2011 and 2020 than those regions.

The California region (which includes all but the northernmost part of the state) added 3.0 GW of wind capacity between 2011 and 2020, accounting for 4% of national wind capacity growth. Although California was an early adopter of utility-scale wind turbines, it has not had the high wind capacity growth in the last decade that some other regions have had.

The United States added a record amount (14.2 GW) of annual wind capacity in 2020. Previously, the most wind capacity added in a single year in the United States was 13.2 GW installed in 2012.

Both the California and Mid-Atlantic regions had their highest annual wind capacity additions in 2012. The Central region also had significant wind capacity growth in 2012, at 3.3 GW, which was slightly less than its regional high of 3.5 GW added in 2016.

In 2020, the Midwest and Northwest regions experienced their largest annual wind capacity additions, adding 5.7 GW and 2.7 GW, respectively. Many of the capacity additions in recent years have been driven by declining construction costs for wind farms and increases in state-level renewable portfolio standards (RPS).


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Homes and buildings

We spend the majority of our lives in buildings. Our houses, offices, and community centres require heating, cooling, and lighting. In Canada, buildings produce 12 percent of our national emissions, mostly for space and water heating. If you add indirect emissions from using electricity, that share jumps to 17 percent. And in making them more energy efficient, they represent a big economic opportunity.

Construction is a multi-billion-dollar industry in Canada. When we make our homes and buildings more energy efficient – we also create more jobs. In Canada, every dollar the government spends on energy-efficiency programs can save Canadians as much as $3 to $5.

Our buildings will become much more energy efficient, use clean electricity, and even generate their own electricity. Well-designed, efficient buildings are comfortable and healthy – and they save Canadians money on energy bills.

The federal government will support improving the energy efficiency of our homes and buildings.

First, the Government of Canada will provide tools to make new buildings more energy efficient. It is feasible to design buildings that use as much energy as they could produce using renewable energy. These are known as “net-zero energy ready” buildings. Working with the provinces and territories, the federal government will develop a building code that, when adopted by provinces and territories and used by builders, could enable all new buildings to be built “net-zero energy ready” by 2030.

We will also work with the provinces and territories to develop a retrofit code for existing buildings and work towards energy labeling to support retrofits. A code for existing buildings will help guide energy efficiency improvements that can be made when Canadians renovate their homes and buildings. In 2030, 75 percent of Canada’s buildings will be buildings standing today, so we must work to improve their energy efficiency.

Energy use labeling will allow homeowners to increase the value of their homes by showing the improvement in energy performance that results from investing in better insulation and more efficient heating and cooling systems.

The federal government will also set advanced efficiency standards for new heating equipment and other appliances, so homeowners save energy and money over time.

The $2 billion Low Carbon Economy Fund and the government’s green infrastructure investments will support the transformation of our buildings sector. Through these funds, we will work with interested provinces and territories to support their efforts to help homeowners and businesses become more energy efficient.

Finally, we will work in partnership with Indigenous Peoples to enhance efficiency and combat climate change as we address the housing challenges in Indigenous communities. Together, we will make new buildings more efficient through improved building standards, while also increasing the efficiency of existing buildings. Indigenous Peoples have also identified the need to incorporate Traditional Knowledge and culture into building designs.

These actions will create good jobs, drive the development of new technologies, save Canadians money and help make homes, businesses and other buildings more comfortable, healthy and environmentally friendly. For Canada to thrive in the clean growth century, we need efficient and resilient buildings.


Background

Dietary carbohydrate provides both an energy source and, through its effects on insulin and other hormones, regulatory control of metabolism. In the context of obesity, diabetes and related pathologic states, it is argued by many researchers that the level of carbohydrate, by its hormonal effects, controls the disposition of nutrient intake beyond simple caloric balance [1–11]. From this point of view, fat plays a relatively passive role and the deleterious effects of high dietary fat are expected only if there is sufficient dietary carbohydrate to provide the hormonal state in which the fat will be stored rather than oxidized. In its practical application, the principle has given rise to several forms of popular diet strategies which have in common some degree of carbohydrate restriction [12–14] or effective glycemic level [3, 15]. Experimentally, protocols based on carbohydrate restriction do as well or better than fat reduction for weight loss (reviews: [16–18]), but because they are somewhat iconoclastic with respect to official dietary recommendations and because they derive from the popular diets where discourse is heated, they remain controversial. The extent to which carbohydrate restriction is successful as a strategy for control of obesity or diabetes can be attributed to two effects. The strategy frequently leads to a behavioral effect, a spontaneous reduction in caloric intake as seen in ad lib comparisons. There is also a metabolic effect, an apparent reduction in energy efficiency seen in isocaloric comparisons, popularly referred to as metabolic advantage. The two are not necessarily independent: an association between thermogenesis, a reflection of inefficiency, and satiety has been established by Westerterp, et al., for example [19].

Experimental demonstrations of energy inefficiency in humans have recently been summarized [16, 17, 20] and the phenomenon has been demonstrated in animal models (e.g., ref. [21] and, most dramatically ref. [22]). This metabolic effect, however, is not universally accepted as a major component in human experiments, oddly even by investigators who have provided experimental support [23–26]. Variable energy efficiency, however, is known in many contexts: hormonal imbalance [27, 28], intensive insulin therapy [29], studies of weight regain [30, 31] and particularly knock-out experiments in animals [32–34]. Experiments demonstrating variable energy efficiency in the context of weight loss, however, remain controversial because of the difficulty in validating compliance in dietary interventions and because of a resistance to what is perceived as a violation of thermodynamics, that is, an intuitive feeling that, in the end, everything must even out. Thus, progress in this field still depends on a proper understanding of caloric efficiency and a description of how energy balance can account for differences in weight loss in isocaloric comparisons.

We have previously described how different isocaloric diets are actually expected to have different effects on metabolism and therefore on body mass [16, 35, 36]. Our previous arguments were largely based on equilibrium thermodynamics because this is most familiar. However, living systems, and in particular, TAG stores in adipocytes, are maintained far from equilibrium and the rates of breakdown of such high energy compounds are regulated by the kinetics of the enzymes that catalyze hydrolysis and re-synthesis. Because the system is maintained far from equilibrium, energy measurements provide values of (∂G/∂ξ)T,P where ξ is the reaction progress coordinate and the path-independence of state variables, that is, ΔG values measured in a calorimeter do not necessarily apply [37]. In essence, then, the problem is as much one of rates as of free energy. Much progress has been made in the development of nonequilibrium thermodynamics for the study of metabolism although there is no universally accepted approach ([38–40] and references therein) and the current work is intended to provide a first step towards developing the problem of energy efficiency in response to dietary macronutrients.

Here we review the basic ideas of nonequilibrium thermodynamics and provide an approach to the problem of maintenance and change in body mass following these ideas. The emphasis is on flux of metabolites in adipose tissue since, in the end, this is the major reflection of energy balance and obesity. The work has several goals:

To recast the problem of TAG accumulation and breakdown in the adipocyte in the language of nonequilibrium thermodynamics. In particular, we want to describe adipocyte physiology in terms of cycling between an efficient storage mode and a dissipative mode. Experimentally, this is reflected in the rate of fatty acid flux and fatty acid oxidation.

To provide a plausible mechanism for how different efficiencies of isocaloric diets can be accounted for by changes in kinetics. To show that hormonal levels controlled by changes in carbohydrate intake determine the relative contributions of the efficient and dissipative parts of the TAG-FA cycle.

Overall, the model is intended to provide a conceptual framework for energy efficiency in nutrition and to point the way to future research. We feel that the approach has general implications as well and is tied to the philosophical position espoused by Prigogine and followers in emphasizing the dynamic nature of physical processes, that is, the need to consider kinetics as well as thermodynamics [39, 41–44].

We emphasize that metabolic efficiency is not always seen in diet comparisons. A thermodynamic analysis, however, shows that inefficiency is to be expected and it is the cases where "a calorie is a calorie" that need to be explained: it is the unique characteristics of living systems – maintenance of a steady-state through tightly controlled feed-back systems – not general physical laws that accounts for energy balance when it is found. Practically speaking, the importance of obesity and other metabolic disorders makes it important to see what the requirements are to break out of these stable states.

Nonequilibrium thermodynamics

It is traditional to separate thermodynamics and kinetics but such a division applies strictly only to equilibrium systems [41, 45]. Systems that are far from equilibrium may undergo chemical reactions that never attain equilibrium and are characterized by the flux of material as well as energy. In a dietary intervention, the flux of material must be integrated over time to determine the total change in weight or fat loss. Thus, accumulated changes may be controlled by the presence of a catalyst or other factors that affect the rate of reaction.

In the case at hand, adipocytes cycle between states of greater or lower net breakdown of fat (lipolysis and reesterification) depending on the hormonal state which, in turn, is dependent on the macronutrient composition of the diet. A hypothetical scheme for changes in adipocyte TAG and a proposal for how TAG gain or loss could be different for isocaloric diets with different levels of insulin is shown in Figure 1. Under normal control conditions of weight maintenance, the breakdown and utilization of TAG by lipolysis and oxidation is balanced by the re-synthesis from food intake. Assuming, for simplicity. an instantaneous spike in food at meals, the curves represent the net flow of material (possibly through several TAG-FA cycles) within the adipocyte. In a coarse-grained analysis, the integral over time of the fluctuations between different states, measures the change in stored TAG in the time of a dietary experiment. The average is stable, that is, appears as weight maintenance. If now each meal is maintained at constant calories but there is an increase in the percentage of carbohydrate leading to higher insulin levels, the lipases may be reduced in activity (blue line in Figure 1). The rate of re-synthesis of TAG is less perturbed by the elevated insulin [46] and indeed may go the other way. The system may cycle between states, which, while they never come to equilibrium, have the net affect of producing changes in the direction of accumulation of TAG.

Hypothetical kinetics of fat storage and hydrolysis. Model for the effect of insulin on efficiency of storage. Black line indicates response under conditions of weight maintenance. Blue line shows the effect of added insulin on hormone sensitive lipase activity.

In carbohydrate restriction, the decrease in carbohydrate may be accompanied by an increase in dietary fat and the relative effect on rate of TAG accumulation due to disinhibition of lipolysis vs the effect of increased substrate will determine the efficiency. As noted below, experiments in the literature [47] show that after chronic exposure to a low carbohydrate diet (higher dietary TAG), the plasma levels of TAG following a high fat meal are reduced compared to controls. Of course, replacing dietary carbohydrate with dietary protein at constant lipid will be consistent with the model in the absence of compensating effects.

In these cases, the integrated change in TAG over the course of a day (or several days) will no longer be zero. In this way, two diets may lead to different weight gain (as indicated by accretion of fat), even though they have the same number of calories, simply because they affect hormonal levels differently. An analysis based on rates suggests further that a new steady state may be obtained in which TAG may be maintained at a higher or lower level even if the hormonal state returns to one that does not lead to further change. The cell may then relax from one steady state to another, the observed macroscopic weight gain or loss. The goal here is to ask what would it take to produce behavior like that in Figure 1.

For minor perturbations, there will be compensating effects of competing pathways (increase in insulin secretion due to fatty acid production [48, 49], for example) and one can expect, insofar as the model corresponds to reality, there may be a threshold effect. This is reflected in the emphasis on extreme carbohydrate reduction in the early phases of popular weight loss diets [12–14]. We emphasize that all of the potential sources of metabolic inefficiency – increased reliance on gluconeogenesis and consequent increased protein turnover, up-regulation of uncoupling proteins – described previously [16, 36] may still be operative but the net change in fat stores must be the final common output if body mass is to undergo change.

Formalism of nonequilibrium thermodynamics

For systems that are not at equilibrium, changes in entropy will drive the system towards equilibrium. If the system is close to equilibrium or, as in the case here, there is a small change in the total free energy – only a small fraction of TAG is actually hydrolyzed in the course of a day – then the change in entropy will be due to dSe, the flux of entropy that is exchanged with the environment and dSi, that due to the irreversible effect of the chemical reaction [41, 50, 51]. We are then interested in the rate of entropy production, Φ, due to chemical reactions at constant T and P:Φ = dSi/dt = - (1/T) Σ N μk dnk/dt

In nonequilibrium thermodynamics, overall flux of entropy is considered as a product of forces (derivative of the potential), Xk and flows Jk, all forces and flows vanishing at equilibrium. In a chemical system, the force Xk is defined as the negative of the chemical potential of the kth reaction, sometimes referred to as the affinity A = - (∂G/∂ξ)T,P where ξ is the extent of chemical reaction. In other words, a positive sign of × indicates spontaneous forward driving force. The force, then, depends on the concentration of reactants and products, the standard free energy and the extent of reaction. It is worth noting that for the systems like the adipocyte that are maintained far from equilibrium the distinction between ΔG values and (∂G/∂ξ)T,P noted by other authors [37] is important, that is, the simple additivity of state variables that underlies the idea that all calories are equivalent, is not valid.

The flows, Jk, are identified with the flux of the kth reaction. The flux of fatty acid in an adipocyte, for example, J1 = vlipolysis + vsynthesis, the sum of breakdown and synthesis rates for TAG. In the phenomenologic approach of nonequilibrium thermodynamics, the forces and flows may be the sum of several individual processes.

In applying the principles of nonequilibrium thermodynamics, the analysis will be simplified if we make the assumption that the fluxes are linear functions of the forces, in analogy with similar linear equations such as Fick's law of diffusion (diffusion is a linear function of the concentration gradient), or Ohm's law (current is a linear function of the potential). The proportionality constant Lkj is called the phenomenological coefficient.Jk = Σ n LkjXj

Although the general requirement that condition (2) hold is that the system be close to equilibrium, the linear approximation is often observed to be appropriate for systems very far from equilibrium, subject to stabilizing feedback and in enzymatic systems operating in the range of substrate concentrations that are close to KM [52, 53]. Further discussion is found in references [54–56]. Whereas the assumption of linearity is reasonable for the current model where small perturbations far from equilibrium occur in a region of high substrate, in the end, it is a working assumption and experimental tests of the model will ultimately determine if the assumption is justified.

Qualitative features of the adipocyte model and comparison to glycolysis

F igure 2 shows a simple model that is proposed for adipose tissue metabolism under conditions bearing on changes in body mass. The flux of TAG (1) represents the net accumulation or output with respect to the cell itself. This process driven by (2) the input of glycerol-3-phosphate from glycolysis or glyceroneogenesis and (3) fatty acid (FA) from plasma FA. The high energy form of the cycle, TAG, is stored. From the point of view of the organism, it is the FA output that provides fuel for oxidation and cell metabolism. This output may be taken as analogous to the system load as it is usually described in nonequilibrium thermodynamics. Oxidation and FA uptake are largely controlled independently, that is, the adipocyte system has high output conductance and low input conductance, that is, by analogy with an electronic system, is an ideal amplifier. Because there is effectively no load on the system and overall metabolic effect is simply to reduce the affinity of fatty acid, the analysis is greatly simplified. The flux of FA, J3 is of general physiologic importance and is the most experimentally accessible of the relevant parameters.

In the comparison of different diets, an additional component is (4) input of fatty acid from TAG-containing lipoproteins. Our treatment of the problem is to consider fluxes in the absence of this input since that is how it is usually described in the literature and then to consider the effect of input from lipoproteins as a perturbation. Focusing on the reaction in the absence of lipoprotein input, the overall relations of fluxes and flows:J1 = L11X1 + L12X2J2 = L21X1 + L22X2J3 = L13X1 + L33X3

As an example of the application of these principles, Aledo, et al. addressed the negative correlation between glycolytic flux and intracellular ATP concentration in yeast, the so-called ATP paradox [54, 57, 58]. The paradox was resolved by showing that if ATP-consuming pathways are more sensitive to glucose than the glycolytic pathway, the cell can switch from an efficient (ATP-conserving) to a dissipative (ATP-utilizing) regime [54, 58]. The dissipative regime offers higher output at high glucose cost, whereas the efficient regime has higher accumulation of ATP but lower glycolytic flux.

In the adipocyte model, periodic switching between dissipative and conservative regimes is meant to describe the dynamic cycling of TAG. The goal in development of the model is to show the constraints on the system for conservation of fat mass, and conversely, how isocaloric dietary inputs of different composition might plausibly bring about weight gain or loss, that is, how efficiency is regulated in the TAG-FA cycle and the activity of the reactants. In essence, we want to know what it would take for the blue line in Figure 1 to occur.

The major controlling variables will be the Lij, the phenomenologic constants which depend on hormonal levels, and the thermodynamic activity of plasma triglyceride (supplying fatty acid). Looking ahead, the simplest application will be the effect of replacing dietary carbohydrate with dietary protein at constant lipid where a semi-quantitative prediction can be made. In the most general case, however, we also want to know the relative impact of insulin reduction on the Lij (reduced lipolysis rate) compared to the increase in thermodynamic activity (X4) due to increased dietary fat.

The variables as they apply to the adipocyte model are as follows:

X1 = the output force is the affinity of the lipolysis-TAG synthesis cycle. The analysis can be simplified by the assumption that lipolysis of available TAG (and possibly re-synthesis) in an adipocyte occurs at a heterogeneous interface. We can therefore take the thermodynamic activity of TAG as 1, that is, although other concentrations may influence X1, the amount of TAG will not. (The contribution of TAG activity is unlikely to change in any case since perturbations in TAG concentrations are extremely small compared to the total stored TAG).X1 = -RT (ln (Keq) FA-TAG - ln ([FA] 3 [glyc-3-P]/[TAG]) = - 3 RT ln (([FA] [glyc-3-P]/K')

X2 = the driving force for supply of glycerol-3-phosphate whose major term is normally the availability of carbohydrate. Under conditions of carbohydrate restriction, however, there is also an increase in glyceroneogenesis from protein [59, 60].

X3 = = the driving force for supply of fatty acid from cellular TAG.

X4 = the force due to the supply of fatty acid from lipoproteins (chylomicrons and VLDL).

In the approach taken here,

L11, L12 are the sensitivities of the flux of TAG to the levels of TAG and the levels of substrate (glycerol-3-phosphate) which depend primarily on the hormonal levels (via phosphorylation of the lipases and other enzymes). It is generally assumed on theoretical grounds (Onsager relation) that L12 = L21 although this has to actually be established for systems that are not close to equilibrium.

L22 is the sensitivity of the glycerol-3-phosphate flux to the availability of carbohydrate (or other sources) which may also be controlled by hormonal levels.

Although somewhat beyond the level of analysis presented here, it is worth noting some of the derived parameter that are traditional in a NET analysis. The degree of coupling, q = L12 /√L11L22 is a dimensionless parameter that indicates how tightly the output process is coupled to the driver process [55] and takes on values from 0 to 1 in the forward direction. In the model in Figure 2, q will vary with different subjects and different metabolic states, in particular, is strongly under the control of insulin.


2.7: Energy Efficiency - Biology

The world is not on track to meet the energy-related components of the Sustainable Development Goals (SDGs). The IEA’s Sustainable Development Scenario (SDS) outlines a major transformation of the global energy system, showing how the world can change course to deliver on the three main energy-related SDGs simultaneously.

Based on existing and announced policies – as described in the IEA Stated Policies Scenario (STEPS) – the world is not on course to achieve the outcomes of the UN SDGs most closely related to energy: to achieve universal access to energy (SDG 7), to reduce the severe health impacts of air pollution (part of SDG 3) and to tackle climate change (SDG 13).

The SDS sets out an ambitious and pragmatic vision of how the global energy sector can evolve in order to achieve these critical energy-related SDGs. It starts with the SDG outcomes and then works back to set out what would be needed to deliver these goals in a realistic and cost-effective way. In the WEO-2020, the Sustainable Development Scenario also integrates the stimulus packages required for a global sustainable recovery from Covid-19. Investments in the 2021-2023 period are therefore aligned with the Sustainable Recovery depicted in the World Energy Outlook Special Report.

An integrated approach to energy and sustainable development

The Paris Agreement has an objective of “holding the increase in the global average temperature to well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C above pre-industrial levels”. Energy production and use is the largest source of global greenhouse-gas (GHG) emissions, meaning that the energy sector is crucial for achieving this objective.

To achieve the temperature goal, the Paris Agreement calls for emissions to peak as soon as possible and reduce rapidly thereafter, leading to a balance between anthropogenic emissions by sources and removals by sinks (i.e. net-zero emissions) in the second half of this century. These conditions are all met in the SDS.

The SDS holds the temperature rise to below 1.8 °C with a 66% probability without reliance on global net-negative CO2 emissions this is equivalent to limiting the temperature rise to 1.65 °C with a 50% probability. Global CO2 emissions from the energy sector and industrial processes fall from 35.8 billion tonnes in 2019 to less than 10 billion tonnes by 2050 and are on track to net zero emissions by 2070.

The SDS is fully aligned with the Paris Agreement

Compare the new SDS 2020 to IPCC scenarios with a temperature rise in 2100

Source: IAMC 1.5°C Scenario Explorer hosted by IIASA release 1.1, https://data.ene.iiasa.ac.at/iamc-1.5c-explorer, https://doi.org/10.5281/zenodo.3363345

The IPCC Special Report on Global Warming of 1.5°C, published in 2018, assessed a large number of scenarios that led to at least a 50% chance of limiting the temperature rise to 1.5 °C. As the figure above makes clear, the SDS trajectory is well within the envelope of these scenarios.

Almost all of these IPCC scenarios (88 out of 90) assume some level of net negative emissions. The Sustainable Development Scenario does not rely on net negative emissions, but if the requisite technologies became available at scale, warming could be further limited. A level of net negative emissions significantly smaller than that used in most scenarios assessed by the IPCC would provide the Sustainable Development Scenario with a 50% probability of limiting the rise in global temperatures to 1.5°C.

How does SDS relate to the pursuit of a 1.5°C outcome?

Cumulative net-negative CO2 emissions between 2018 and 2100 in 1.5°C scenarios assessed by the IPCC

However, as frequently highlighted in the WEO, there are reasons to limit reliance on early-stage technologies for which future rates of deployment are highly uncertain: that is why the SDS emphasises the importance of early action on reducing emissions.

In the light of concern surrounding negative emissions technologies, it would be possible to construct a scenario that goes further than the Sustainable Development Scenario and delivers a 50% chance of limiting warming to 1.5 °C without any reliance on net-negative emissions. These conditions would require achieving net zero emissions globally by around 2050.

Eliminating the 10 Gt CO2 energy-sector emissions remaining in SDS in 2050 would not amount to a simple extension of the changes to the energy system described in the SDS. The additional changes involved – particularly those surrounding rates of technological change, infrastructure constraints, social acceptance and behavioural changes, and capital stock replacement – would pose challenges that would be very difficult and very expensive to surmount. This is not something that is within the power of the energy sector alone to deliver. Change on a massive scale would be necessary across a very broad front, and would impinge directly on the lives of almost everyone.

The Paris Agreement is also clear that climate change mitigation objectives should be fulfilled in the context of sustainable development and efforts to eradicate poverty. The Sustainable Development Scenario explicitly supports these broader development efforts (in contrast to most other decarbonisation scenarios), in particular through its energy access and cleaner air dimensions.

In the Sustainable Development Scenario, strong policy support and international co-operation are an integral part of national and international recovery plans, and this enables a ramping up of progress on expanding access programmes to achieve universal access to electricity and clean cooking by 2030, despite the near-term slowdown caused by the health crisis and economic downturn. This scenario requires $40 billion of annual investment between 2021 and 2030 to reach universal access, making full use of decentralised solutions. Achieving universal access will transform the lives of hundreds of millions, and reduce the severe health impacts of indoor air pollution, overwhelmingly caused by smoke from cooking.


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