Improving Building Energy Efficiency in India: State-level Analysis of Building Energy Efficiency

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Improving Building Energy Efficiency in India: State-level Analysis of Building Energy Efficiency Policies

Sha Yu^a [email protected]

Qing Tan^a [email protected]

Meredydd Evans^a [email protected]

Page Kyle^a [email protected]

Linh Vu^a [email protected]

Pralit L Patel^a [email protected]

a Joint Global Change Research Institute, Pacific Northwest National Laboratory

5825 University Research Court, Suite 3500, College Park, MD 20740, United States

Corresponding author

Sha Yu [email protected]

Joint Global Change Research Institute, Pacific Northwest National Laboratory

5825 University Research Court, Suite 3500, College Park, MD 20740, United States

Version of Record: https://www.sciencedirect.com/science/article/pii/S0301421517304469 Manuscript_297360a32cf5defc3f931681eb8b875c

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2 Journal: Energy Policy

Highlights

• We assess state-level impact of building energy policies in India using GCAM.

• We link bottom-up and top-down analyses to examine real-world building policies.

• Gujarat would experience rapid growth and electrification in building energy use.

• Building energy codes can generate significant energy and economic savings by 2050.

• A high code compliance rate is critical to achieving intended savings.

Abstract

India is expected to add 40 billion m² of new buildings till 2050. Buildings are responsible for one third of India’s total energy consumption today and building energy use is expected to continue growing driven by rapid income and population growth. The implementation of the Energy Conservation Building Code (ECBC) is one of the measures to improve building energy efficiency. Using the Global Change

Assessment Model, this study assesses growth in the buildings sector and impacts of building energy policies in Gujarat, which would help the state adopt ECBC and expand building energy efficiency programs. Without building energy policies, building energy use in Gujarat would grow by 15 times in commercial buildings and 4 times in urban residential buildings between 2010 and 2050. ECBC improves energy efficiency in commercial buildings and could reduce building electricity use in Gujarat by 20% in 2050, compared to the no policy scenario. Having energy codes for both commercial and residential buildings could result in additional 10% savings in electricity use. To achieve these intended savings, it is critical to build capacity and institution for robust code implementation.

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Keywords: Building energy efficiency, integrated assessment modeling, Energy Conservation Building Code, impact assessment

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Improving Building Energy Efficiency in India: State-level Analysis of Building Energy Efficiency Policies

Sha Yu, Qing Tan, Meredydd Evans, Page Kyle, Linh Vu, Pralit Patel

1. Introduction

The buildings sector is booming in India; the country foresees 40 billion m² of new construction through 2050 (Chaturvedi et al., 2014). Building energy use today accounts for 33% of India’s total final energy consumption, and is increasing at around 8% annually (Rawal et al., 2012). Driven by rapid income and population growth, this trend is expected to continue. How to curb the growth of building energy use while continuously improving people’s quality of life has become one of the key challenges for Indian policy makers. In its recently released climate plan, the Government of India has highlighted the

importance of building energy efficiency in its climate mitigation strategies (Government of India, 2015).

As more than half of India’s floorspace is yet to be built, policies targeting energy efficiency in new buildings would be particularly impactful. The Government of India launched the Energy Conservation Building Code (ECBC) in 2007, setting the minimum energy efficiency requirements for new, large commercial buildings. In 2009, the Government of India enacted the National Mission for Enhanced Energy Efficiency as part of the National Action Plan on Climate Change. The Mission launched national programs to improve energy efficiency across various sectors, and further emphasized the significance of building energy efficiency and relevant policies including ECBC (Government of India, 2009). To

Abbreviations: ECBC, Energy Conservation Building Code; BEE, Indian Bureau of Energy Efficiency;

HVAC, heating, ventilation, and air conditioning; GRIHA, Green Rating for Integrated Habitat Assessment; LEED, Leadership in Energy and Environmental Design; GCAM, Global Change Assessment Model; NSSO, Indian National Sample Survey Organization; OECD , Organization for Economic Cooperation and Development; WWR, window to wall ratio; O&M, operation and maintenance.

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achieve the intended energy savings, ECBC needs to be effectively implemented. ECBC was developed as a model code at the national level; it goes into effect and becomes mandatory when a state or local government adopts and implements it in the jurisdiction. Understanding the impacts and benefits of ECBC at the state level will greatly help states adopt the code and motivate them to implement it, and thus avoid locking in carbon-intensive infrastructure.

Although there are a few studies assessing the energy savings potential of ECBC, none of them provided a thorough analysis of ECBC impacts at the state level. Dhaka et al. and Tulsyan et al. used building energy simulation to assess energy saving opportunities through implementing energy conservation measures in ECBC, and found that implementing ECBC could result in up to 40% savings (Dhaka et al., 2012; Tulsyan et al., 2013). However, these studies only examined energy savings of a group of buildings for a given time; they did not consider long-term growth of the buildings sector nor long-term energy and economic savings of ECBC. Another group of studies estimated long-term building energy demand in India, but lacked detailed analysis of the impact of building energy policies (Chaturvedi et al., 2014; IEA, 2015; Ürge-Vorsatz et al., 2015). In addition, none of the previous studies assessed building energy use and policy impacts at the state level, although the state is often the jurisdiction to adopt and implement building energy policies. This study fills the gap in literature, using an integrated assessment approach to examine long-term evolution of the buildings sector and energy and economic impacts of ECBC at the state level.

This paper is structured as follows. Section 2 provides a comprehensive overview of building energy policies in India. Section 3 presents the methodology and the integrated assessment model used in this paper. Section 4 explains the design of scenario analysis. Section 5 discusses energy and economic savings of ECBC in comparison with other building energy policies, as well as strategies to improve ECBC implementation. Implications for future policy development and conclusions are presented in Section 6.

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6 2. Building Energy Policies in India

2.1 Energy Conservation Building Code and green building programs

The Government of India has taken steps to improve energy efficiency in buildings. The enactment of the Energy Conservation Act in 2001 has led to the establishment of the Bureau of Energy Efficiency (BEE) and the development of ECBC. ECBC, launched in 2007, is the first building energy code in India. It applies to new commercial buildings with a connected load of over 100 kilowatt-hours or a contract demand of over 120 kilovolt-amps. Buildings with a conditioned area of over 1,000 m² generally fall under this category (ECO-III, 2009). ECBC prescribes minimum energy performance standards for the building envelope, heating, ventilation, and air-conditioning (HVAC) system, interior and exterior lighting, and service hot water in each of the five climatic zones in India. It also sets energy efficiency requirements for building electric power and motors. ECBC allows buildings to comply through three methods: prescriptive, simple trade-off, and whole building performance. While the simple trade-off method allows for trade-offs among envelope components, the whole building performance method is meant for flexibility within the entire building system as long as its overall energy performance is equivalent to or better than a standard ECBC-compliant building (ECO-III, 2009). All large national public buildings are now required to comply with ECBC. ECBC has been adopted in 7 states and 16 states are in the process of adopting ECBC (Indian Bureau of Energy Efficiency, 2016).

In addition to ECBC, there are voluntary programs to encourage the development of efficient and sustainable buildings, such as the Green Rating for Integrated Habitat Assessment (GRIHA), BEE Star Rating, and the Leadership in Energy and Environmental Design (LEED).

GRIHA is a building rating program that is widely implemented in India. It is applicable to new buildings with floorspace of over 2,500 m². Eligible buildings include offices, retail buildings, institutional

buildings, hotels, hospitals and healthcare facilities, and multi-family high-rise buildings. The rating system includes 34 criteria in site planning, resource utilization and conservation, building operation, as

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well as innovation designs. GRIHA evaluates a building’s performance throughout its life cycle based on nationally accepted energy and environmental principles, and aims to minimize the environmental impact of buildings and promote green building development (GRIHA India, 2016a). The program is executed by the GRIHA Council, which was founded by the Energy and Resources Institute with the support of the Indian Ministry of New and Renewable Energy (GRIHA India, 2016b). There are currently 700 projects on record that are registered with the GRIHA system (GRIHA India, 2016c).

BEE Star Rating is a voluntary program to assess and rate energy performance of existing commercial buildings. The buildings are rated on a 1- to 5-star scale based on their operational energy consumption (i.e. energy consumption per unit of floorspace per year), where 5-Star represents the most energy efficient buildings. Currently, there are about 150 buildings rated by the BEE Star Rating program (BEE, 2016).

LEED, the green building rating certification system, evaluates a building based on multiple aspects, including sustainability, water efficiency, energy, resources, indoor environmental quality, and innovation, and throughout the building’s planning, construction, maintenance, and operation. LEED certification can be applied to all types of buildings, ranging from homes to commercial office buildings. The number of LEED certified buildings increased rapidly in India in the past few years. In 2015, India ranked 4^th on the list of countries with LEED certified buildings (Gray, 2015).

Both ECBC and green building programs can help improve building energy efficiency, but they work in different ways. ECBC, a model building code, sets the minimum energy efficiency requirements for new commercial buildings and as such removes the inefficient buildings from the market. It helps push the buildings market to be energy efficient. Green building programs and BEE Star Rating system are voluntary programs that help pull the buildings market to reach higher efficiency levels. While ECBC applies to a broad set of buildings, voluntary programs target high-efficiency buildings which only make up a small share of the entire building stock. In other words, green building programs alone might result

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in a large number of inefficient buildings, although the number of high-efficiency buildings would increase. Given that India would add 40 billion m² of floorspace between now and 2050, having a robust building energy code is critical (Chaturvedi et al., 2014).

2.2 ECBC implementation in Gujarat

An assessment of ECBC impacts can inform policy makers and help relevant stakeholders understand the energy savings potential and economic benefits of ECBC, and motivate them to implement ECBC. Here we conduct an integrated assessment of ECBC impacts, using Gujarat as an example.

Gujarat is one of the fastest growing states in India, with rapid economic growth, urbanization, and building floorspace expansion. Gujarat’s per capita GDP was $2,100 in 2014¹, 45% higher than India’s national average (Indian Ministry of Statistics and Programme Implementation, 2016). The share of urban population in Gujarat increased from 37% in 2001 to 43% in 2011, higher than India’s average

urbanization rate of 31% in 2011 (Gujarat Directorate of Economics & Statistics, 2011). This rapid growth of urban centers also brings big demand for new construction (Gujarat Housing Board, 2008, 2016). In the long term, the floorspace to be built in India through 2050 would more than double that of today (Chaturvedi et al., 2014). New construction is the most cost-effective point in a building’s life cycle to integrate energy efficiency features. Developing energy efficient new buildings would help avoid locking in carbon-intensive infrastructure and set the path towards a sustainable future. The State of Gujarat is in the process of adopting ECBC, and understanding the impacts of ECBC is critical to policy development and implementation. In particular, how much savings would ECBC generate? How does ECBC interact with other building policies? And to what extent does the level of implementation matter?

This study examines the evolution of the buildings sector in Gujarat and addresses these questions through an integrated assessment approach.

3. Methodology and Data

1 Costs in this paper, if not specified, use the 2010 U.S. dollars.

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9 3.1 Global Change Assessment Model

We use the Global Change Assessment Model (GCAM) in this study. GCAM is a global integrated assessment model that links energy, economy, land use, water, and climate system. It has 32 energy- economy regions globally (Edmonds and Reilly, 1983; Kim et al., 2006). GCAM models regional energy supply and demand within a partial equilibrium framework with rich representations of energy production, transformation, and consumption technologies. The model is open source² and runs in 5-year time step through 2100. GCAM has been used to study climate mitigation policies at national and sub-national levels and to examine interactions between air pollutant emissions, climate policy, and climate change (Clarke et al., 2008; Wang et al., 2016).

We have extended the model by building GCAM-India and GCAM-Gujarat, which are fully global integrated assessment models with additional details for India and Gujarat. Compared with the core GCAM, GCAM-India has higher resolution for the buildings sector and includes more India-specific details. In particular, it has four improvements: 1) detailed representation of the buildings sector with more building types and services, 2) factoring in the impact of window-to-wall ratio (WWR) and solar heat gain coefficient on building energy use, 3) adding off-grid electricity generation technologies (e.g.

rooftop PV and diesel generator) for building and agricultural end-users, and 4) explicitly tracking production-driven agricultural energy use (Yu et al., 2017). The energy system in GCAM-India is represented in terms of electricity generation, other transformation, and end-use energy demands (i.e.

industrial, buildings, and transportation sectors). GCAM-Gujarat, the module used to assess the evolution of the buildings sector in Gujarat, is embedded in GCAM-India, so the energy system in Gujarat interacts with energy supply and demand in the rest of India (Figure 1).

Figure 1. Energy system of GCAM-India and GCAM-Gujarat

3.2 Buildings sector in GCAM-Gujarat

2 For details, see http://www.globalchange.umd.edu/models/gcam/.

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We use GCAM- Gujarat to assess the benefits of building energy policies in terms of energy and economic savings, as well as avoided electricity capacity additions. The model takes an integrated analysis approach, considering future population and GDP growth, increase in building floorspace and energy service demand, improvement in technologies, and constraint of energy supply in India.

The buildings sector in Gujarat is divided into urban residential, rural residential, and commercial sectors, as each of these buildings has different functions, characteristics, and fuel and energy-service profiles. For each building type, heating, cooling, ventilation, lighting, water heating, cooking, and appliances are explicitly represented with detailed technologies. Figure 2 shows the structure of the urban residential sector in Gujarat; rural residential and commercial buildings sectors have similar structures to the urban residential sector shown here.

Figure 2. Structure of GCAM-Gujarat

A number of studies have been using GCAM to examine the evolution of the buildings sector in both developing and developed countries (Chaturvedi et al., 2014; Eom et al., 2012; Kyle et al., 2010; Yu et al., 2014b). Income, climate, and the costs of energy services drive the demand for building energy services.

However, the building energy service demand would not experience unlimited growth; it will stabilize as income reaches a certain level. In other words, there is a sufficient level of building energy services for a given unit of floorspace. This study follows the approach taken by Eom et al. (Eom et al., 2012),

Chaturvedi et al. (Chaturvedi et al., 2014), and Yu et al. (Yu et al., 2014b) to estimate future demand for building energy services, which allows demands to reach a saturation level (see Appendix A).

3.3 Data and assumptions

The historical GDP and population data for Gujarat are from the Gujarat Directorate of Economics and Statistics and the Census of India (Census of India, 2016; Government of Gujarat, 2011). The average annual GDP growth rate in Gujarat was around 7% between 1990 and 2010; the GDP growth is expected to slow down in the next few decades, with an average annual growth rate of 5% between 2010 and 2050

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(Figure 3a). We assume that population growth will also slow down, and the annual growth rate would decrease from 1.3% between 1990 and 2010 to 0.87% between 2010 and 2050. In addition, similar to many developing regions, the state of Gujarat would experience rapid urbanization, and urban population would account for 55% and 70% of Gujarat’s total population in 2030 and 2050, respectively (Figure 3b).

Figure 3. GDP (a) and population (b) growth in Gujarat

Floorspace expansion drives building energy consumption. The Indian National Sample Survey Organisation (NSSO) conducted the Consumer Expenditure Survey and collected information on per capita floorspace in urban and rural residential buildings at the state level (NSSO, 2009). The ECO-III program compiled data on India’s commercial floorspace and estimated the growth of commercial floorspace until 2030. Here we assume that per capita commercial floorspace in Gujarat is the same as India’s national average per capita commercial floorspace. Per capita rural and urban floorspace increases by 2-3 times between 2010 and 2050, reaching 20 m² and 26 m², respectively. Per capita commercial floorspace increases by almost 6 times between 2010 and 2050 and reaches more than 4 m², but it is still much lower than the current level in Organization for Economic Cooperation and Development (OECD) countries (Enerdata, 2008) (Figure 4a). Future floorspace growth is driven by increasing income as well as demographic changes. We assume that total floorspace in Gujarat would increase by more than 4 times, and the growth rate differs across building types. Driven by strong urbanization and construction boom in urban areas, total floorspace in urban residential buildings and commercial buildings would grow by around 7 and 8 times, respectively (Figure 4b).

Figure 4. Per capita (a) and total (b) floorspace growth in Gujarat

Understanding the current pattern of building energy use in Gujarat is critical to estimating future building energy consumption. This would help understand consumers’ preferences for fuel uses and energy services and determine the changes in consumer preferences and the potential of fuel substitution in the future. Estimated from NSSO’s household surveys and the Gujarat Statistical Outline, Gujarat’s

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building energy consumption in 2010 is 0.37 EJ, accounting for 4.5% of India’s building final energy use.

Traditional biomass is still the major fuel used in Gujarat buildings, especially in rural households for water heating and cooking. Electricity, after biomass, is the second largest source of building energy use in Gujarat. ECBC and most green building programs require energy efficient air conditioning, lighting, and service hot water, which together make up around 63% of building electricity use in Gujarat, and could have significant impacts on curbing building energy consumption (Figure 5).

Figure 5. Share of building energy use by fuel and service in Gujarat (2010)

4. Scenario Development

We develop a set of scenarios to explore the evolution of the buildings sector in Gujarat and to assess the impacts of ECBC and other building energy programs (Table 1). We limit the scope of this study to the assessment of energy and economic savings through policies in new buildings because more than half of India’s building floorspace is yet to be built and policies improving energy efficiency in new buildings may generate more savings than retrofitting programs. Promoting energy efficiency in new buildings also avoids locking in carbon-intensive infrastructure. In addition, the Government of Gujarat is in the process of adopting ECBC, and understanding the benefits associated with ECBC can facilitate the policy

decision making.

In the reference scenario, we assume that there is no building energy policy in Gujarat. Currently, the Government of Gujarat has no policy in place to promote building energy efficiency, although it has initiated the process of adopting ECBC. The reference scenario assumes the continuation of the status quo and represents the natural growth of the buildings sector in Gujarat without any policy intervention. For urban residential and commercial buildings, the shell efficiency for the base year 2010 is 2.0 W/m²K, consistent with the assumptions used by BEE for developing design guidelines of energy efficient residential buildings (BEE, 2014). For rural residential buildings, the shell efficiency for 2010 is 2.5

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W/m²K. The reference scenario is a frozen efficiency scenario and assumes the building shell efficiency would remain the same throughout 2050.

Without building energy policies, energy efficiency of buildings may get worse over time. For example, there are an increasing number of buildings with curtain glass walls in India and elsewhere (Singh and Garg, 2011); without improvement in energy efficiency of building materials, the increasing WWR could increase solar heat gain in buildings and elevate the demand for cooling, especially in tropical regions like India. Therefore, we conduct a sensitivity analysis to assess how the increasing WWR influences building energy use. We apply an average annual growth rate of 2% to WWR in the Gujarat buildings, which is the same as growth rate of WWR in the U.S. office buildings between 1979 and 1986 weighted by energy consumption (U.S. Energy Information Administration, 2009). Base on BEE’s survey, WWR of typical Indian high-rise buildings is about 0.15 (BEE, 2014). With the 2% annual growth, WWR will reach around 0.3 by 2050. This would increase building electricity use in Gujarat by 8% in 2050.

Table 1. Description of scenarios

The ECBC scenarios consider both the stringency and implementation of the code. In the ECBC scenarios, we assume that the Government of Gujarat will adopt ECBC in 2016 and continue to improve the

stringency of ECBC. The current version of ECBC would be effective between 2016 and 2025 and then the code for new commercial buildings would improve continuously until approaching a technically achievable limit of 0.05 W/m²K in 2050 (Yu et al., 2014a). The annual efficiency improvement in lighting and HVAC systems is 0.16%, consistent with the assumptions used by the U.S. Building Energy Codes Program to assess benefits of building energy codes (Livingston et al., 2014). In terms of implementation, we create two scenarios with low and high compliance with ECBC. In the ECBC-Low scenario, the compliance rate would rise slowly from 0 in 2016 to 80% in 2050. In the ECBC-High scenario, we assume that the Government of Gujarat proactively promotes ECBC implementation and it would reach a 99% compliance rate within 10 years of adopting ECBC. Assessing the high compliance scenario can

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shed light on the full potential of energy and economic savings from ECBC and motivate policy makers to promote ECBC implementation.

ECBC only addresses energy efficiency in new commercial buildings, leaving energy saving

opportunities in residential buildings untapped. Residential buildings constitute around 90% of Gujarat’s total building floorspace today and more than 80% of Gujarat’s building floorspace in 2050, which has significant opportunities for energy savings. Although there is no mandatory code to regulate energy efficiency in residential buildings, recognizing the importance of this issue, BEE launched the Design Guidelines for Energy Efficient Multi-Storey Residential Buildings to provide guidance on energy efficient design of residential buildings. To understand the impacts of energy efficiency improvement in the residential buildings, here we develop scenarios that expand the scope of energy codes to include both residential and commercial buildings. We assume that codes for residential buildings will be adopted in 2020, 5 years after the adoption of ECBC for commercial buildings. Similar to the ECBC scenarios, there are also low and high compliance codes scenarios (i.e. Codes-Low and Codes-High) to understand the impact of code enforcement.

In addition to energy codes, green building programs also help improve building energy efficiency in India. There are several voluntary green building programs (e.g. GRIHA, LEED, and Star Rating Scheme) and a growing number of green buildings in India. For example, India currently has over 13 million m² of LEED certified green building space and ranked the 4^th globally after the U.S., Canada, and China (Gray, 2015). Although green buildings often reach higher efficiency levels compared to code-compliant buildings, green building programs could not replace energy codes, given that the number of green buildings is relatively small compared to the total floorspace in India. Here we create green building scenarios to assess the impact of green building programs in lieu of mandatory energy codes. Energy efficiency of green buildings is assumed to be much higher than that of code-compliant buildings. Green buildings would be equipped with high efficiency envelope with a U-value of 0.05 W/m²K as early as year 2025, while the code-compliant buildings would reach this efficiency level in 2050. In addition,

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lighting and HVAC efficiency would also improve faster in green buildings, with an annual efficiency improvement rate of 1%. Based on estimates of the Indian Green Building Council, green buildings currently constitute around 1.6% of total floorspace in India (Indian Green Building Council, 2015). In the United States where there is a longer history of green building development, green buildings account for less than 2% of the total building floorspace in 2015 (Gray, 2015; GRIHA India, 2016a; U.S. Energy Information Administration, 2013, 2015). We assume low and high penetration of green building programs in Gujarat, and the shares of green building space in total building areas are 1.6% and 5% by 2025 and stay at these levels in the Green-Low and Green-High scenarios, respectively.

5. Results and Discussion

5.1 Evolution of the buildings sector in Gujarat

Without building energy policies in place, building energy consumption would grow rapidly in Gujarat and triple between 2010 and 2050. Energy consumption of rural households would decline as a result of fuel switching from traditional biomass to commercial fuels such as electricity and liquefied petroleum gas. Energy use in urban households would increase significantly and quadruple in the next four decades.

The strongest growth in building energy consumption is from the commercial sector; commercial building energy use would grow by around 15 times between 2010 and 2050, driven by the increase in floorspace and various energy services.

Despite the rapid growth, per capita building energy use in Gujarat would still be lower than that of OECD countries. However, energy intensity in commercial buildings would grow fast and be on a par with that of European countries. Energy intensity in residential buildings would decline, as households replace inefficient traditional biomass with modern fuels (Figure 6).

Figure 6. Energy use intensity in commercial (a) and residential (b) buildings across regions

The fuel profile of the buildings sector also changes over time (Figure 7a). The buildings sector in Gujarat would see a high electrification rate; the share of electricity use in total building energy consumption in

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Gujarat would increase from 13% in 2010 to around 60% in 2050. The rapid electrification is also accompanied by fuel switching in urban and rural buildings. Urban and rural households would gradually phase out traditional biomass for cooking and water heating, and use liquefied petroleum gas and

electricity instead. Electricity is the primary source of energy for commercial buildings, as most energy services in commercial buildings such as air conditioning, lighting, and appliances consume electricity.

As people become richer, demand for energy services also changes. Air conditioning and appliance use are the dominant energy services in commercial buildings in Gujarat. Energy use for air conditioning and ventilation in commercial buildings would increase by 16 times between 2010 and 2050, and make up around 40% of commercial building energy use in Gujarat by 2050. In residential buildings, although water heating and cooking still constitute a substantial share of energy use, the share would decrease significantly (dropping from 90% in 2010 to 60% in 2050 in rural residential buildings and from 80% to 40% in urban residential buildings). The use of air conditioning in the residential sector is expected to grow rapidly. In 2050, energy use for air conditioning accounts for 14% and 23% of energy use in rural and urban residential buildings, respectively (Figure 7b).

Figure 7. Building energy consumption by fuel (a) and service (b) in Gujarat (2010-2050)

Energy codes and green building programs set energy efficiency requirements for HVAC system, service hot water, building envelope, and lighting, which together account for 36% of building energy

consumption in Gujarat in 2050. Cooking and appliance energy use account for 39% and 24%, respectively. Since ECBC, energy codes, and green building programs will mostly affect building

electricity use, the following analyses will focus on the impact of these policies and programs on building electricity use.

5.2 Energy and economic savings from ECBC

ECBC, once adopted by the Government of Gujarat, has the potential to shape the energy landscape in the state. Effective implementation of ECBC with high compliance would reduce Gujarat’s building

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electricity use by around 20% in 2050, compared to the reference scenario. The cumulative electricity savings would be around 419,800 GWh. This in turn could help avoid 11,800 and 134,400 MW of cumulative electricity capacity additions from 2010 to 2030 and 2050, respectively. The avoided capacity additions between 2010 and 2050 are more than four times of Gujarat’s electricity generation capacity today (around 29,400 MW) (Central Electricity Authority, 2015).

Figure 8. Building electricity consumption in Gujarat under different scenarios

Energy savings from ECBC adoption and implementation can generate attendant economic savings, which come from avoided costs to build, finance, maintain, and operate power plants. Adding power generation capacities would require building new infrastructure, including power plants, transmission lines, and dispatching capabilities, as well as operating and maintaining power plants. With lower

electricity demand from implementing ECBC, costs associated with generation capacity additions are also reduced. Annual economic savings, estimated using modeled electricity price³ and electricity savings, are up to $8 billion⁴ by 2050. There are also other benefits of ECBC implementation. For example, a stringent building code and effective implementation often foster a market for energy efficient materials and products, which can contribute to the development of the local economy.

5.3 Energy and economic savings from energy codes in residential and commercial buildings

Although the current Indian building energy code only covers new commercial buildings, as the buildings sector evolves, Indian policy makers may also extend the code to improve energy efficiency in residential buildings. Given the volume of residential construction, this may have a significant impact.

As shown in Figure 8, in the Codes-High scenario, having energy codes for both residential and commercial buildings would generate around 30% of electricity savings in 2050, compared to the reference scenario. This would translate into 165,900 MW of avoided electricity generation capacity

3 Electricity price in GCAM is estimated based on levelized electricity generation cost, reflecting costs to construct, maintain, and operate power plants.

4 Economic savings are estimated in 2010 USD.

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additions between 2010 and 2050. The associated economic savings from avoided capacity additions between 2010 and 2050 would be around $123 billion, around 40% more than savings in the ECBC-High scenario. The impact might be even more significant in the second half of the century, when households become richer and use more energy services.

5.4 Energy and economic savings from green building programs

Green building programs go beyond minimum energy codes requirements. Green building programs alone would not replace codes; instead, they often serve as a complementary measure to codes. Green building programs and energy codes target different market segments; energy codes make sure that the buildings on the market reach certain energy efficiency levels, and green building programs can further pull the market and increase the number of high-efficiency buildings. In addition, green building

programs include the elements beyond the scope of energy codes, such as water and resource efficiency.

Green building programs alone, although can increase the number of high-efficiency buildings, could only generate limited amount of savings, given that the percentage of green buildings is relatively small in the entire building stock. We conducted a sensitivity analysis to assess energy savings from green

building programs with high market penetration rate. The result shows that if green buildings account for 5% of new constructions in 2025 and maintain this 5% market share afterwards, energy savings between 2010 and 2050 from green building programs alone would still be lower than those of codes programs.

Green building programs alone (with 5% market share) would save around 10,000 GWh of electricity in 2050 compared to the reference scenario, while building electricity savings in the Codes-High scenario is around 50,000 GWh. Green buildings can work together with energy codes and encourage further development of energy efficiency standards and market. Green buildings can also serve as a proving ground for future codes development and spur technology innovation and the development of more efficient materials.

5.5 Impact of code compliance and mechanisms to improve compliance rate

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The effectiveness of building energy efficiency policies is contingent upon the extent of compliance.

Compared to the ECBC-Low scenario, high compliance with ECBC (i.e. ECBC-High) would save up to 11,300 GWh of electricity in 2050. The cumulative electricity consumption between 2010 and 2050 in the ECBC-High scenario would be 180,500 GWh less than that in the ECBC-Low scenario (Figure 9). The impact of compliance would be even more evident when there are comprehensive building energy codes in place. Building electricity use in 2050 in the Codes-Low scenario is around 18,500 GWh higher than that in the Codes-High scenario. The difference in cumulative building electricity use from 2010 to 2050 would be around 280,400 GWh between the Codes-Low and Codes-High scenarios.

Figure 9. Building electricity use in ECBC-Low and ECBC-High Scenarios Compared with Reference Scenario

To achieve the intended energy and economic savings from ECBC and other possible building energy efficiency policies in the future, a robust implementation system is critical to ensuring compliance. A strong institutional framework is needed to successfully implement ECBC. ECBC adoption is the first step toward effective implementation. The Government of Gujarat is currently in the process of adopting ECBC. Once ECBC is adopted, it is also important to establish an institutional framework that enables implementation. Some crucial elements of this framework include incorporating ECBC into the building permitting process, developing capacity of local code officials to conduct plan review and construction inspection, training professionals on designing and constructing ECBC-compliant buildings, and creating a market with certified and labeled energy efficient building materials.

Various mechanisms are used in other countries to improve code compliance. For example, China has two mechanisms to significantly enhance code compliance in a short time frame. One is the Code for

Acceptance of Energy Efficient Building Construction, which is a step-by-step guide on construction inspection. The other is the wide use of certified third-party inspectors to assist code officials in

compliance checking (Evans et al., 2010). The United States has various training programs at the national

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and regional levels to improve compliance capacity of code officials, architects, and engineers and raise awareness of other stakeholders. In addition, the U.S. Building Energy Codes Program initiated

systematic compliance evaluation to identify gaps in code compliance and inform future code

development and implementation (Yu et al., 2014c). Experience and lessons learned in other countries can help Indian policy makers to design effective policy mechanisms to improve code implementation and enhance compliance.

6. Conclusion and Policy Implications

India is experiencing a construction boom and strong building energy efficiency policies are key to avoiding excessive growth in electricity use and greenhouse gas emissions. Energy codes and green building policies are often used to encourage energy efficient designs of buildings and set an efficient path for new constructions. The government of India has developed an energy code, ECBC, to regulate energy efficiency in new commercial buildings, and there are several green building programs working in parallel with ECBC. Implementation of these policies depends on efforts at the state and local levels, and therefore, understanding the benefits of these policies would help state and local stakeholders adopt building energy policies and motivate effective policy implementation. This paper takes the State of Gujarat as an example and assesses the impacts of ECBC and other building energy programs at the state level.

ECBC could help generate up to 419,800 GWh savings in building electricity use in Gujarat between now and 2050, which would also help avoid around 134,400 MW of electricity capacity additions. Extending ECBC beyond the commercial sector and having energy codes for both commercial and residential buildings can achieve additional savings and result in around 193,700 GWh additional electricity savings and $32 billion additional economic savings from avoided capacity additions between 2010 and 2050.

However, fulfilling these savings potential heavily relies on good policy implementation, which requires training and capacity building as well as improvement in institutional set-up.

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21

Developing and implementing energy efficiency policies in the buildings sector extend the benefits beyond the buildings sector. In Gujarat and India, this means slower growth in electricity demand while meeting the same level of comfort and quality of life. The avoided electricity capacity additions also translate into a lower level of greenhouse gas and air pollutant emissions, especially when the majority of electricity generation comes from coal in India. There are also implicit benefits of implementing energy codes. For example, savings from the buildings and power sectors could be used to improve other social goals, such as poverty alleviation and quality education.

The results of this study should be interpreted as diagnostic rather than deterministic. This study

contributes to the literature by linking the bottom-up analysis and top-down analysis and introducing real- world policies under the integrated assessment framework. It sheds light on the evolution of buildings sector in Gujarat and various growth trajectories under different policies. The key findings on the importance of ECBC and its implementation will hold notwithstanding the assumptions made in this study. However, there are some limitations of this study. First, this study only considers policies affecting the design of new buildings. There are several other policies that also affect building energy use, such as appliance standards, retrofit policies, and incentives for rooftop PVs. Future studies can assess the impact of a full set of building energy policies. These policies could interact with energy codes and green

building programs discussed in this paper and shape the energy landscape of the buildings sector. Second, the estimate of economic benefits is not comprehensive. There are several other types of economic indicators that could be considered, such as improved demand of energy efficiency products and changes in household income and expenditure associated with job changes (e.g. job increase in the buildings sector, job loss from the power sector, and job increase in the sectors that investments are redirected to).

Future work could consider the full feedback to the economy due to development and implementation of the buildings sector policy. Finally, there are uncertainties in future population and GDP growth, as well as the rate of technology changes; the future work could conduct uncertainty analysis to assess how the buildings sector evolves and how policies affect energy use under different circumstances.

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22

ECBC, energy codes, and green building programs would generate energy savings, reduce electricity capacity additions, and create economic savings. They can also help alleviate local air pollution and provide health benefits. These policies together can serve as strategies to implement India’s Nationally Determined Contribution, and thus achieve climate change mitigation.

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23 Appendix A Representation of Energy Service Demand

Eq. (A.1) describes the demand for building energy services. It considers consumers’ preferences in energy service and changes in income and price elasticities. It has been used in earlier studies of Eom et al., Chaturvedi et al., and Yu et al (Chaturvedi et al., 2014; Eom et al., 2012; Yu et al., 2014a).

)]

/ /

2 ln exp(

1

[ I

_t

P

_t

S k

d = × − − µ ×

Eq. (A.1)

where d is the demand for the energy service under consideration. S is the level of demand satiation, is satiation impedance representing preference for the service, is service cost at time t, is per capita GDP at time t, and k is a calibration parameter. Satiation impedance helps define the degree of service penetration given a particular affordability of the service, or / .

Eq. (A.2) lays out how space heating and cooling services are derived. Heating and cooling degree days, building designs and characteristics, and internal gains would affect the demand for space heating and cooling.

t H t

t

H

HDD r IG

S = × η × − λ ×

t C t

t

C

CDD r IG

S = × η × − λ ×

Eq. (A.2)

where SH and SC arethe saturated service levels per unit of floorspace for space heating and cooling [GJ/m²]. HDDt and CDDt are heating and cooling degree days at time t [day ^oC]; η^t is shell conductance (or U-value) at time t [GJ/m² day ^oC] indicating the extent to which indoor temperature is susceptible to outdoor weather; and r is building floor-to-surface area ratio representing the size of building shell exposed to outdoor temperature. IGt is the amount of building internal gains at time t [GJ/m²], calculated endogenously in the model based on the demand for other building services such as lighting, and λ^H and λ^C are internal-gain scalars accounting for the potential mismatch of the time when space heating and cooling are required and the time when the internal gains are produced.

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24 Acknowledgements

The authors are grateful for research support provided by the Office of Energy Efficiency and Renewable Energy of U.S. Department of Energy (DOE). The authors acknowledge long-term support for Global Change Assessment Model development from the Integrated Assessment Research Program in DOE’s Office of Science. We also would like to thank Rajendra Pandya from the Gujarat Energy Development Agency, Rajan Rawal from the Center for Environmental Planning and Technology (CEPT) University, Ashu Gupta from Design2Occupancy Services Limited Liability Partnership (LLP), Sheila Moynihan from DOE, and Mark Halverson and Rahul Athalye from the Pacific Northwest National Laboratory (PNNL) for their inputs and thoughtful suggestions. The authors also want to thank Kerry Burgott for her help on data collection. PNNL is operated for DOE by Battelle Memorial Institute under contract DE- AC05-76RL01830. The views and opinions expressed in this paper are those of the authors alone.

Funding: This work was supported by U.S. Department of Energy.

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India

Gujarat oil

imports

oil production

oil

liquid fuels

MSW ag waste

bioenergy

gas imports

gas production

natural gas coal

production

coal imports

gas

nuclear hydro wind solar coal

distributed PV

diesel generators

retail electricity

whole-sale electricity

electricity generation

agriculture transportation buildings industry buildings

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Gujarat

India

grid electricity

distributed PV

diesel generators

buildings electricity

bioenergy gas coal liquid

fuels

residential urban ventilation

residential urban air conditioning

residential urban televisions

residential urban refrigerators

residential urban other appl.

residential urban cooking

residential urban lighting

commercial residential rural

residential

urban

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0 100 200 300 400 500 600 700 800 900

2000 2010 2020 2030 2040 2050

billion 2010 USD historical projection

0 10000 20000 30000 40000 50000 60000 70000 80000

2000 2010 2020 2030 2040 2050

thousand

urban rural historical projection

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2000 2005 2010 2015 2020 2025

Gujarat GDP 30.56687 61.96449 107.8065 148.0558 205.7382 277.5075 billion 2010$

2025 2030 2035 2040 2045 2050

Gujarat GDP (cont'd) 277.5075 360.2551 454.4182 562.2038 682.0739 812.6669billion 2010$

population 2000 2005 2010 2015 2020 2025 2030

Gujarat 50671 52156 53684 57337 60850 64080 thousand

urban 18931 20226 21756 25356 29363 33359 thousand

rural 31740 31930 31928 31981 31487 30721 thousand

2025 2030 2035 2040 2045 2050

Gujarat (cont'd) 64080 67010 69721 72152 74286 76005 thousand

urban (cont'd) 33359 37633 41789 46154 50222 54306 thousand

rural (cont'd) 30721 29377 27932 25998 24064 21699 thousand

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0 5 10 15 20 25 30

2010 2020 2030 2040 2050

m2

commercial rural residential urban residential

0 0.5 1 1.5 2 2.5

2010 2015 2020 2025 2030 2035 2040 2045 2050

billion m2

urban residential rural residential commercial

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Gujarat floorspace (billion m²) 2010 2015 2020 2025 2030 2035 2040 2045 2050

commercial 0.041 0.060318 0.08734 0.119935 0.156075

rural residential 0.318 0.372924 0.437889 0.505341 0.564306 urban residential 0.155 0.217456 0.302954 0.403394 0.514563

2035 2040 2045 2050

commercial (cont'd) 0.195505 0.238612 0.284119 0.33086

rural residential (cont'd) 0.620468 0.668161 0.704926 0.728076 urban residential (cont'd) 0.632608 0.759916 0.891971 1.02574

Gujarat per capita floorspace (m²) 2010 2015 2020 2025 2030 2035 2040 2045 2050

commercial 0.763728 1.051996 1.435329 1.871645 2.32913 2.804105 3.307074 3.824664 4.353135 rural residential 8.463427 9.671011 11.19735 12.83315 14.41669 16.00118 17.59474 19.00223 20.34214 urban residential 9.621014 11.5816 13.93306 16.33027 18.46466 20.44324 22.23475 23.98482 25.50736

2035 2040 2045 2050

commercial (cont'd) 2.804105 3.307074 3.824664 4.353135

rural residential (cont'd) 16.00118 17.59474 19.00223 20.34214 urban residential (cont'd) 20.44324 22.23475 23.98482 25.50736

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biomass 69%

coal 7%

gas less than 1%

oil 11%

HVAC 36%

lighting 25%

TVs 9%

refrigerators 8%

water heaters 2%

cooking less than 1%

other appliances electricity 20%

13%

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final energy use by fuel 2010

biomass 0.25620 EJ

coal 0.02526 EJ

gas 0.00004 EJ

electricity 0.04953 EJ

oil 0.04208 EJ

electricity use by service 2010 share

HVAC 0.01772 EJ 35.77%

lighting 0.01268 EJ 25.60%

TVs 0.00432 EJ 8.73%

refrigerators 0.00393 EJ 7.93%

water heaters 0.00093 EJ 1.87%

cooking 0.00008 EJ 0.17%

other appliances 0.00987 EJ 19.92%

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Gujarat (2010-50) #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! GJ/m2 0

0.5 1 1.5 2 2.5 3

0 10 20 30 40 50 60

Final Energy Use per Unit of Floorspace (GJ/m2 )

Per Capita GDP (thousand 2010 USD at PPPs) Commercial

Gujarat Reference (2010-50) UK (1994-2004) Sweden (1983-2007) Germany (1995, 2001-07) France (1983,1986-2007) Denmark (1985-2007) Norway (1990-2007) US (80,90,00,06)

0 0.2 0.4 0.6 0.8 1 1.2 1.4

0 10 20 30 40 50 60

Final Energy Use per Unit of Floorspace (GJ/m2)

Per Capita GDP (thousand 2010 USD at PPPs) Residential

Gujarat Reference (2010-50) UK (1989-2006) Sweden (1983-2007) Germany (1990-2007) France (1980-2007) Denmark (1980-2007) Norway (1980-2007) US (80,84,87,90,97,01,05)

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GDP per capita PPP 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

UK 20.55251 20.27097 20.71939 21.46074 21.99753 22.73098 23.58886 24.61289 25.80055 26.31519 26.44568 25.98573 25.95786 26.47537 27.53796 28.2988 29.04574 29.9292 30.9233 31.88317 33.01793 33.7007 34.2856 35.10991 35.97143 36.51391 37.33923 38.05112 thous2010US$/per Sweden 24.78477 24.70492 24.98466 25.42461 26.48513 27.02293 27.72965 28.59265 29.22283 29.83339 29.90242 29.36812 28.84395 28.08516 28.98752 29.98214 30.37187 31.10151 32.26947 33.7257 35.15372 35.42971 36.16613 36.72206 38.08455 39.18386 40.61838 41.34688 thous2010US$/per Germany 22.25358 22.33855 22.27392 22.68585 23.40896 24.0088 24.55101 24.88628 25.67771 26.48769 27.63828 28.82493 29.24351 28.79987 29.47688 29.94628 30.15717 30.64297 31.27388 31.88024 32.86311 33.20919 33.15202 33.06475 33.47177 33.73899 34.84815 35.75201 thous2010US$/per France 22.86913 22.951 23.36936 23.52269 23.75677 24.04356 24.50909 24.98398 25.98413 26.90715 27.47 27.61238 27.85334 27.48202 27.98905 28.48107 28.69798 29.23898 30.15435 31.01091 32.00629 32.36612 32.46413 32.58809 33.1509 33.52864 34.04266 34.62874 thous2010US$/per Denmark 23.96323 23.75997 24.66167 25.33546 26.40632 27.45828 28.77786 28.82189 28.76395 28.91746 29.33656 29.6834 30.12344 29.99204 31.54588 32.36363 33.07861 33.98807 34.60449 35.37046 36.50196 36.62888 36.66945 36.71456 37.46734 38.27015 39.43831 39.93692 thous2010US$/per Norway 27.26108 27.58845 27.52225 28.49648 30.08862 31.60034 32.76578 33.18972 32.95916 33.14617 33.67355 34.54794 35.56483 36.33546 37.95087 39.34911 41.1387 43.12091 44.00802 44.59766 45.75129 46.43434 46.86186 47.06723 48.6091 49.60564 50.31256 51.19237 thous2010US$/per US 28.59337 29.02947 28.18382 29.1906 31.01813 32.0075 32.8055 33.54302 34.60248 35.49897 35.7544 35.18957 35.90759 36.46219 37.50522 38.00924 38.9907 40.26341 41.5488 43.07697 44.38454 44.4167 44.79482 45.49354 46.70357 47.69562 48.51482 49.07249 thous2010US$/per

2010 2015 2020 2025 2030 2035 2040 2045 2050

Gujarat 6.352803 8.16875 10.69595 13.6999 17.00731 20.61851 24.64964 29.04622 33.82483 thous2010US$/per

commercial building energy intensity 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

UK (1994-2004) 1.078106 1.073403 1.091753 1.029422 1.023774 1.003367 0.979067 0.966765 0.881864 0.885862 0.909448 GJ/m2

Sweden (1983-2007) 1.236208 1.277132 1.412652 1.325152 1.368962 1.357173 1.295258 1.28816 1.385032 1.300658 1.298973 1.313294 1.267768 1.306098 1.240426 1.212761 1.205302 0.992848 1.100625 1.117428 1.065061 1.021384 1.019503 1.05942 1.070044 GJ/m2

Germany (1995, 2001-07) 1.056787 0.753573 0.753911 0.760178 0.793942 0.699415 0.791592 0.711093 GJ/m2

France (1983,1986-2007) 2.030123 1.303953 1.311886 1.196396 1.103575 1.131335 1.257394 1.292129 1.262322 1.254811 1.114228 1.226289 1.201811 1.163669 1.149407 1.122812 1.148936 1.156138 1.141863 1.283701 1.308664 1.213494 1.1131 GJ/m2 Denmark (1985-2007) 0.983046 0.951168 0.952694 0.864832 0.797071 0.790931 0.80252 0.777612 0.79444 0.770875 0.78522 0.839768 0.790527 0.775644 0.760055 0.736205 0.75206 0.749613 0.760443 0.75793 0.737464 0.742657 0.717655 GJ/m2

Norway (1990-2007) 1.057801 1.03127 1.052249 1.009407 0.980503 0.956571 1.074849 1.05945 1.0492 1.049811 0.953154 1.061693 1.044575 0.995146 1.004434 0.958909 0.938998 0.989157 GJ/m2

US (80,90,00,06) 2.36404 2.358737 2.848423 2.722434 GJ/m2

2010 2015 2020 2025 2030 2035 2040 2045 2050

Gujarat Reference (2010-50) 0.649881 0.761561 0.858183 0.948551 1.018833 1.072892 1.119022 1.155013 1.182677 GJ/m2

residential building energy intensity 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

UK (1989-2006) 0.921398 0.919883 0.995985 0.957755 0.969193 0.91063 0.861598 0.9523 0.872145 0.887052 0.874064 0.872674 0.900192 0.865828 0.863176 0.867593 0.831877 0.780002 GJ/m2

Sweden (1983-2007) 0.966894 0.949295 1.046373 0.992079 0.995568 0.904471 0.845381 0.853615 0.862523 0.830473 0.858169 0.861887 0.86859 0.913422 0.867557 0.881119 0.856317 0.834398 0.865723 0.838868 0.830184 0.828421 0.832667 0.795944 0.822499 GJ/m2

Germany (1990-2007) 0.903617 0.926343 0.886984 0.940617 0.90334 0.92852 1.00209 0.981118 0.948672 0.881307 0.863647 0.937789 0.900633 0.89016 0.860858 0.825001 0.828448 0.697195 GJ/m2

France (1980-2007) 1.183448 1.077534 0.98914 0.998665 0.974083 1.024038 0.980418 0.989031 0.887591 0.875475 0.865923 0.986 0.927754 0.923282 0.836427 0.859767 0.920344 0.831821 0.866547 0.844293 0.807705 0.83063 0.776088 0.815213 0.81653 0.79439 0.750451 0.704482 GJ/m2 Denmark (1980-2007) 0.914011 0.828793 0.806159 0.768172 0.731539 0.833956 0.822101 0.831595 0.756009 0.692671 0.670437 0.723136 0.692171 0.74598 0.716782 0.726299 0.770464 0.716476 0.707994 0.684504 0.651796 0.684623 0.664807 0.67429 0.667062 0.662855 0.65386 0.644407 GJ/m2 Norway (1980-2007) 0.883475 0.833921 0.808268 0.779928 0.779621 0.827279 0.853445 0.852306 0.808245 0.771725 0.761984 0.770984 0.748155 0.753243 0.772059 0.772296 0.79712 0.756495 0.755694 0.748775 0.71176 0.726593 0.71023 0.666012 0.649502 0.667975 0.641878 0.642688 GJ/m2

US (80,84,87,90,97,01,05) 1.262095 1.253436 1.181769 1.143992 1.281909 1.126194 1.023055 GJ/m2

2010 2015 2020 2025 2030 2035 2040 2045 2050

Gujarat Reference (2010-50) 0.732485 0.657784 0.57838 0.516211 0.469498 0.433639 0.405329 0.383862 0.367741 GJ/m2

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0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

commercial rural residential urban residential commercial rural residential urban residential commercial rural residential urban residential commercial rural residential urban residential commercial rural residential urban residential

2010 2020 2030 2040 2050

EJ

biomass electricity oil coal gas

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

2010 2020 2030 2040 2050

EJ

cooking and water heating appliances HVAC lighting

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building energy use by sector and fuel

oil 0.0110273 0.009244343 0.021809557 0.0269025 0.021412066 0.04844454 0.0496287 0.038798984 0.081123599 0.0731251 0.052558981 0.10943184 0.0954575 0.058454831 0.131220077 EJ

gas 4.07431E-05 0 3.30096E-06 0.000104458 0 7.70528E-06 0.000191694 0 1.27887E-05 0.000271178 0 1.64982E-05 0.000321015 0 1.78679E-05 EJ

electricity 0.01557709 0.01791053 0.016038155 0.04794661 0.034042742 0.039396802 0.10919404 0.058799655 0.083038982 0.1936159 0.086586647 0.142184509 0.29552207 0.110024054 0.215034196 EJ

coal 0 0.00893292 0.0163263 0 0.0106452 0.0172024 0 0.0102316 0.0148008 0 0.00814449 0.0114991 0 0.00562858 0.0084228 EJ

biomass 0 0.2251638 0.03103667 0 0.2293814 0.02795574 0 0.1981068 0.02161332 0 0.1522114 0.01620796 0 0.10436945 0.011779053 EJ

building energy use by sector and service

cooking and water heating 0.0111 0.2427 0.0693 0.0270 0.2610 0.0942 0.0498 0.2474 0.1192 0.0734 0.2148 0.1407 0.0958 0.1725 0.1578 EJ

HVAC 0.0086 0.0049 0.0043 0.0260 0.0097 0.0114 0.0572 0.0182 0.0266 0.0972 0.0290 0.0501 0.1410 0.0399 0.0835 EJ

lighting 0.0039 0.0065 0.0038 0.0113 0.0101 0.0071 0.0238 0.0143 0.0123 0.0391 0.0166 0.0176 0.0560 0.0158 0.0212 EJ

appliances 0.0031 0.0072 0.0078 0.0106 0.0146 0.0202 0.0282 0.0260 0.0424 0.0573 0.0391 0.0710 0.0985 0.0502 0.1040 EJ

2010 2020 2030 2040 2050

(39)

0 20 40 60 80 100 120 140 160 180 200

2010 2015 2020 2025 2030 2035 2040 2045 2050

TWh

Reference ECBC-High Codes-High Green-High

(40)

electricity use 2010 2015 2020 2025 2030 2035 2040 2045 2050 Reference 13.75716 22.09260714 33.71838 50.22059 69.7313 92.00664 117.3297 144.4116 172.3834 TWh ECBC-High 13.75716 21.81970089 32.80033 47.19559 63.09258 79.99018 99.57038 119.7255 139.772 TWh Codes-High 13.75716 21.74317878 32.5276 46.11305 60.47435 74.86352 91.50926 107.8149 123.0718 TWh Green-High 13.75716 22.01943617 33.47074 49.47067 68.10494 89.04887 112.6109 137.4601 162.7135 TWh

0 20 40 60 80 100 120 140 160 180 200

2010 2015 2020 2025 2030 2035 2040 2045 2050

TWh

Reference ECBC-High Codes-High Green-High

(41)

0 20 40 60 80 100 120 140 160 180

2010 2020 2030 2040 2050

TWh

ECBC-High ECBC-Low Reference

21.3 TWh 32.6 TWh

(42)

building electricity use 2010 2020 2030 2040 2050 2050 savings ECBC-High 13.75716 32.80033 63.09258 99.57038 139.772 TWh 32.61142728 TWh ECBC-Low 13.75716 33.33015 66.58199 107.5189 151.049 TWh 21.33439314 TWh Reference 13.75716 33.71838 69.7313 117.3297 172.3834 TWh

(43)

Table 1. Description of scenarios Policy

Assessed

Scenario

Name Description

No building

policy Reference No building energy policy

ECBC

ECBC-Low

ECBC adoption and implementation for commercial buildings in 2016; low compliance with ECBC, reaching 80%

compliance in 2050 ECBC-High

ECBC adoption and implementation for commercial buildings in 2016; high compliance with ECBC, reaching 99%

compliance in 2025

Energy codes for all buildings

Codes-Low

ECBC adoption and implementation in 2016; adoption of energy codes for residential buildings in 2020; low compliance with codes, reaching 80% compliance in 2050

Codes-High

ECBC adoption and implementation in 2016; adoption of energy codes for residential buildings in 2020; high compliance with codes, reaching 99% compliance in commercial and residential buildings in 2025 and 2030 respectively

Green building programs

Green-Low

No mandatory building energy code in place; 1.6% of buildings meeting green building requirements in both residential and commercial sectors

Green-High

No mandatory building energy code in place; 5% of buildings meeting green building requirements in both residential and commercial sectors