Optimal household refrigerator replacement policy for life cycle energy, greenhouse gas emissions, and cost

ARTICLE IN PRESS

Energy Policy 34 (2006) 2310–2323 www.elsevier.com/locate/enpol

Optimal household refrigerator replacement policy for life cycle energy, greenhouse gas emissions, and cost Hyung Chul Kim, Gregory A. Keoleian, Yuhta A. Horie Center for Sustainable Systems, School of Natural Resources and Environment, University of Michigan, 440 Church St., Dana Bldg., Ann Arbor, MI 48109-1041, USA Available online 23 May 2005

Abstract Although the last decade witnessed dramatic progress in refrigerator efficiencies, inefficient, outdated refrigerators are still in operation, sometimes consuming more than twice as much electricity per year compared with modern, efficient models. Replacing old refrigerators before their designed lifetime could be a useful policy to conserve electric energy and greenhouse gas emissions. However, from a life cycle perspective, product replacement decisions also induce additional economic and environmental burdens associated with disposal of old models and production of new models. This paper discusses optimal lifetimes of mid-sized refrigerator models in the US, using a life cycle optimization model based on dynamic programming. Model runs were conducted to find optimal lifetimes that minimize energy, global warming potential (GWP), and cost objectives over a time horizon between 1985 and 2020. The baseline results show that depending on model years, optimal lifetimes range 2–7 years for the energy objective, and 2–11 years for the GWP objective. On the other hand, an 18-year of lifetime minimizes the economic cost incurred during the time horizon. Model runs with a time horizon between 2004 and 2020 show that current owners should replace refrigerators that consume more than 1000 kWh/year of electricity (typical mid-sized 1994 models and older) as an efficient strategy from both cost and energy perspectives. r 2005 Elsevier Ltd. All rights reserved. Keywords: Replacement policy; Refrigerator; Life cycle energy and costs

1. Introduction Refrigerators–freezers (hereafter referred to as ‘‘refrigerators’’) are one of the most energy consuming home appliances accounting for 14% of electricity consumption of US households in 2001 (Energy Information Administration (EIA) 2004a). A series of efficiency standards were enacted between 1990 and 2001 to lower energy consumption associated with refrigerators and other home appliances. The 1990, 1993, and 2001 standards applied specifically to refrigerators. With the tightened standards, the average energy efficiency of new model refrigerators improved Corresponding author. Tel.: +1 734 764 3194; fax: +1 734 647 5841. E-mail address: [email protected] (G.A. Keoleian).

0301-4215/$ - see front matter r 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2005.04.004

more than 150% between 1980 and 2002 (Association of Home Appliance Manufacturers (AHAM) 2003). However, consumers are continuing to use existing lessefficient models mainly due to economic reasons, resulting in the average useful lifetime of over 14 years (National Family Opinion (NFO) 1996). Deterioration of refrigerator components is another source of energy waste, sometimes causing 40–60% higher energy consumption than labeled values (Bos, 1993). Degradation of efficiency is difficult to fix. Previous studies based on real measurements in the field show that simple repair of old refrigerators is unlikely to restore their original efficiencies (Bos, 1993; Meier et al., 1993). Incentives to accelerate replacement of old refrigerators with new ones may be a useful policy instrument to reduce unnecessary energy consumption associated with inefficient refrigerators. From the consumers’

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standpoint, replacement decisions depend on the tradeoffs between higher equipment costs for more efficient refrigerators vs. lower annual energy costs. Consequently, incentives or subsidies are commonly used to facilitate refrigerator replacement programs. For example, in 1993, the Sacramento Municipal Utility District offered a $100 compensation for replacing old refrigerators with new models (Bos, 1993). States including New York, Indiana, Wisconsin, and Iowa have been offering refrigerator replacement programs as a part of a weatherization program for low-income households (Kinney and Belshe, 2001; New York State, 1998; Pratt and Miller, 1998). Utilities have also supported replacement by participating in weatherization programs and, prior to deregulation, as a demand-side management strategy. These programs are producing positive outcomes achieving 50–70% electricity use reductions and more than $50/year of electricity cost savings (Kinney and Belshe, 2001). A similar approach was taken with vehicle scrappage programs that were primarily designed to reduce criteria pollutant emissions from a small fraction of high-emitting vehicles with malfunctioning emission controls. However, replacing old vehicles also creates negative environmental impacts mainly due to the additional greenhouse gas emissions and energy consumption associated with the production and disposal of vehicles (ECMT, 1999; Kim et al., 2003). An owner’s decision to replace a refrigerator poses economic and environmental tradeoffs: benefits from operating new, energy-efficient refrigerators vs. costs associated with retiring and producing additional refrigerators. A life cycle optimization (LCO) model that combines life cycle assessment (LCA) and dynamic programming was developed to study the environmental impacts of replacing old, inefficient vehicles with new models (Kim, 2003; Kim et al., 2003). LCA is an analytical tool for evaluating environmental burdens and impacts associated with a product life cycle (International Standards Organization (ISO) 1997). Dynamic programming is a mathematical tool used to analyze sequential decisions which best satisfies a decision-maker’s criteria. A recent study by the authors explored the optimal lifetimes of mid-sized generic cars between model years (MYs) 1985 and 2020 with 12,000 miles of annual mileage (Kim et al., 2003). The study shows that for regulated emissions (carbon monoxide, non-methane hydrocarbons, and oxides of nitrogen), automobile lifetimes ranging from 3 to 14 years are optimal depending on MY, while a lifetime of 18 years minimizes cumulative life cycle energy and CO2. LCO models have not yet been developed, however, to integrate life cycle energy and environmental objectives in replacement decision-making and policy for home appliances. The present research introduces a comprehensive framework for evaluating optimal lifetimes of refrig-

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erators and replacement policies considering both improvements in efficiencies of new refrigerator models and deteriorating efficiency with refrigerator age. To achieve this goal, the present study extends a novel method for optimizing vehicle replacement from a life cycle environmental standpoint (Kim, 2003; Kim et al., 2003). First, the LCA method was used to estimate environmental burdens from the entire life cycle of a baseline refrigerator model (MY 1997): materials production, manufacturing, use, maintenance, and end-of-life. In order to describe dynamically changing environmental performance based on MY and age of refrigerators, dynamic life cycle inventories (LCIs) were developed for MYs between 1985 and 2020. The life cycle costs (LCCs) were also developed for these MYs. Finally, the LCO model for refrigerator models was constructed based on a dynamic programming model. Model runs were conducted for a time horizon between 1985 and 2020 and the benefits of the optimal decisions were discussed. Sensitivity of the model run results was analyzed based on varying scenarios. Optimal replacement decisions from the perspective of households with refrigerators ranging in MY 1985–2003 were also analyzed over the time horizon between 2004 and 2020.

2. Dynamic life cycle inventory (LCI) The dynamic LCI is a conceptual framework that measures environmental performance of a product, such as energy and materials inputs and outputs, based on a certain time segment of the product life cycle. The time segment is typically defined as a specific time of the production, use, or end-of-life of the product. The dynamic LCI method was developed to describe technology improvements over product MYs. The dynamic LCI is also useful to describe deterioration behaviors with product usage. The present study uses the dynamic LCI framework and method that was developed to optimize lifetimes of generic cars from a life cycle perspective (Kim, 2003; Kim et al., 2003). The study of generic cars defined three dynamic factors: regulatory/social factors, technology improvement, and component deterioration as primary determinants of optimal lifetimes. Dynamic parameters were used to characterize each factor between 1985 and 2020. In the present study, the same approach adopted for the vehicle dynamic LCIs—determining dynamic factors, parameters, and inventories—was used for a time series of refrigerator MYs. The dynamic LCI of generic mid-sized, top/bottom type refrigerators was determined for MYs between 1985 and 2020 with a maximum lifetime of 20 years for all refrigerator models. Energy consumption, CO2 emissions, and other global warming gas emissions during materials production, manufacturing, use, and

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the end-of-life stage of the refrigerator life cycle were inventoried. The maintenance phase of a refrigerator’s life cycle was omitted from the analysis because for most refrigerators, no major maintenance is required during a 20-year lifetime (Meier, 1995). A number of sources were used for emission factors and primary energy use associated with each life cycle stage of a refrigerator including government agencies, such as the US Department of Energy (DOE) and the US Environmental Protection Agency (EPA). A life cycle analysis tool called SimaPro 5.1 was used as data sources of energy consumptions and CO2 emissions. The major modeling characteristics of the dynamic LCIs for each life cycle stage of mid-sized refrigerator models are summarized as follows. 2.1. Materials production The LCIs of materials production stage were analyzed using the material composition of refrigerators. Inventory datasets from SimaPro 5.1 were used as the source for energy intensities and carbon dioxide emission factors for producing a unit mass of material. The material composition of top/bottom refrigerators was Non-Ferrous Metal 6%

2.2. Manufacturing

Plastic 28% Ferrous Metal 61%

Other 1%

provided by the AHAM. In 1997, the AHAM undertook a teardown analysis of refrigerators in conjunction with an appliance recycling project. Fig. 1 gives the materials composition of top/bottom refrigerators made in 1997 (Morris, 2004). Packaging materials used to deliver refrigerators from manufacturing plants to shops were also taken into account. It was assumed that the materials composition of a mid-sized, top-freezer type refrigerator remained unchanged between the MYs 1985 and 2020. This assumption can be justified since the overall design of refrigerators remains essentially unchanged; although there have been complete changes in refrigerants and blowing agents (BAs), which account for less than 1% of the materials and new features have been introduced. Addition of new features such as through-the-door ice-makers may slightly change the average materials composition of a mid-sized refrigerator, but this change would have a very limited impact on the simulation results. The BA used for insulation foams as well as the refrigerant in US refrigerators have been changing with MYs due to the ongoing phase-in of the Montreal Protocol. The past trends and future forecasts for the use of BA and refrigerant are summarized in Table 1.

Glass 4%

Fig. 1. Average materials composition of top/bottom refrigerator (total ¼ 84.5 kg) (Morris, 2004).

The manufacturing process of refrigerators primarily consists of door assembly, cabinet assembly, refrigeration cycle assembly, and plastic parts processing/ assembly (JEMAI, 1995). It was assumed that the manufacturing process remains unchanged between MYs 1985 and 2020. LCI databases included in SimaPro 5.1 were used to estimate the energy consumption and CO2 emissions associated with the manufacture of refrigerators. For modeling purposes, transportation of refrigerators from plants to customers was included in the manufacturing stage. The transportation LCIs are estimated based on the arithmetic average of the distances between a customer in Ann Arbor, MI and three Whirlpool plant locations: (1) Fort Smith, Arkansas, (2) Evansville, Indiana, and (3) Monterrey, Mexico.

Table 1 Chemicals used as blowing agent (BA) and refrigerant (American Plastics Council, 2000; EIA, 1996; Papasavva and Moomaw, 1998; US International Trade Commission, 1995) Model year

BA

Amount (kg)

GWPa

Refrigerant

Amount (kg)

GWPa

1985–1993 1994–2002 2003–2020

CFC-11 HCFC-141b HFC-245fa

1.08 1.21 1.17

4000 630 950

CFC-12 HFC-134a HFC-134a

0.17 0.16 0.16

8500 1320 1320

a

Integrated time horizon (ITH) ¼ 100 years.

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2.3. Use

2.4. End-of-life

Electricity consumption during the use phase is measured in several ways. The DOE procedure, also adopted by the AHAM, is known to accurately estimate real-world refrigerator energy consumption in the US households (Meier, 1995). According to this test procedure, the test chamber ambient temperature is maintained at 3270.6 1C and the annual electricity consumption with a freezer temperature of
15 1C is estimated. Other nations use test methods such as the ISO and the Japanese Industrial Standard (JIS) test procedures depending on climates and cultural variances. A detailed comparison of these test procedures is presented elsewhere (Meier, 1995). Historical energy efficiencies of refrigerator models in the present study were determined based on the AHAM Refrigerator Energy Survey and issues of Consumer Reports between 1985 and 2002 (AHAM, 2003; Consumers Union, 2002). Consumer Reports provide energy efficiencies of new refrigerator models measured in a slightly different test condition from the DOE test. Shipment weighted average efficiencies of generic midsized refrigerator models (including both top–bottom and side-by-side types) from the AHAM survey were used to estimate past trends in electricity use. The average adjusted volumes (AV) weighted by shipments between MYs 1985 and 2002 ranged from 19.5 ft3 (MY 1985) to 22.2 ft3 (MY 2002). In addition, average efficiencies of top–bottom type models from Consumer Reports with a capacity of 20–22 ft3 were selected to examine the effect of energy efficiency trends on the simulation results. ‘‘Adjusted volume’’ is defined as the volume of the refrigeration compartment plus 1.63 times the volume of the freezer compartment, while ‘‘capacity’’ is based on Consumer Reports’ definition excluding the ice-maker (AHAM, 2003; Consumers Union, 2002). For the future forecast of energy efficiencies, scenarios were developed using annual rates of efficiency improvement of 0%, 1%, and 2% of 2002 values. In addition, upstream energy consumption for electricity generation was added to the end-use energy consumption in households. The upstream CO2 emissions were also determined based on the end-use electricity consumption in households and emission factors of Franklin Associates (1998). The energy intensity to generate electricity (i.e. grid efficiency) was assumed to be constant between the calendar years 1985 and 2020. The thermal conversion factors for electricity generation and consumption have remained nearly unchanged for the last several decades (EIA, 2003) and the EIA forecasts only a 5.5% decrease in energy intensity over the period from 2002 to 2020 (EIA, 2004b). In addition, the EIA forecasts that fossil fuels such as coal and natural gas will remain as the dominant energy source for electricity generation until 2020.

On average in the US, 70% of refrigerator materials are recycled. In the present study, the energy consumption and CO2 emissions associated with the recycling process such as transporting, dismantling, and shredding old refrigerators were estimated using SimaPro 5.1 software. It was assumed that refrigerators are transported by a diesel truck to a recycling facility located 50 km away from the owner’s house. In the US, by law refrigerants must be recovered at the end of the refrigerator life cycle (EPA, 2003). The energy use for the recovery of refrigerant was modeled. Emissions of BAs at the end of the life cycle depend on the disposal scenarios. Less than half of the BA gases inside insulation foams are released instantaneously during the shredding process. The remaining gases escape from the shredded foam particles if those foams are disposed in landfills. Although BA gases near broken foam surfaces can escape to the environment in a few weeks, a significant fraction of gases may diffuse through unbroken foam and are released over the course of several years. Therefore, the escape rates primarily depend on the particle size of shredded foams (Kjeldsen and Jensen, 2001; Kjeldsen and Scheutz, 2003). Two extreme scenarios are developed to examine the importance of BA release from a life cycle environmental standpoint: (1) 0% and (2) 100% of BA releases at the time of the disposal.

3. Dynamic life cycle cost (LCC) The LCCs from purchase, use, and disposal of refrigerator models between 1985 and 2020 were determined based on historical data and future forecasts. Consumer Reports and the Annual Energy Review from the DOE were used as the sources for the historical refrigerator and electricity prices, respectively. The future forecast of electricity prices was based on the reference case forecasts of the residential sector from the Annual Energy Outlook 2004 (AEO2004) while the prices of new refrigerators were projected from the historical trends (EIA, 2004b). According to the AEO2004, the average US electricity price for the residential sector will decline by 5% between 2002 and 2008, and will remain stable until 2020. Other AEO2004 electricity price forecasts based on different economic growth rates and oil prices did not affect the results of the present study. Energy consumption data from Consumer Reports was used to determine the electricity cost during the refrigerator use phase. Energy efficiency reported in Consumer Reports may be more representative of actual values due to their more stringent test procedure than the AHAM test specification. Energy efficiency improvements and deterioration behaviors

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modeled for the dynamic LCIs were also applied to the LCC calculation. In addition, the refrigerant disposal fee of $25 was incorporated into the calculation. Maintenance costs were ignored due to the uncertainties and rare occurrences. The LCCs were determined over a 20-year lifetime assuming that no repair costs are required. The LCCs were adjusted to 1985 dollars using the consumer price indexes and an interest rate of 4%, which is the average return rate to government bonds and considered as a consumer interest rate without risk premium (Newell and Pizer, 2002).

4. Dynamic LCI and LCC results 4.1. Baseline LCI and LCC Fig. 2 presents the primary energy consumption of an MY 1997 refrigerator based on the first year of usage. The use phase will dominate the life cycle primary energy use as refrigerator age increases. Previous LCA studies regarding refrigerators also show that the use phase accounts for a major fraction (90%) of the life cycle energy use (BASF, 2002; Foley, 2004). The use

10000

Energy Use (MJ)

8000

6000

4000

2000

0 Materials Manufacturing Use (AHAM) Use (CR) 1st Year 1st Year

End-of-Life

Life Cycle Phase 700

600

Costs (1985 dollars)

500

400

300

200

100

0 Purchase

Use (AHAM) 1st Year

Use (CR) 1st Year

End-of-Life

Life Cycle Phase Fig. 2. Life cycle energy consumption and cost based on 1-year usage of mid-sized 1997 refrigerator model (CR ¼ Consumer Reports, AHAM ¼ Association of Home Appliance Manufacturers survey).

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phase energy consumption of a mid-sized MY 1997 refrigerator based on Consumer Reports is slightly higher than that based on the AHAM survey due to the differences in the definition of ‘‘mid-sized’’ refrigerators and test procedures for electricity consumption. The life cycle CO2 emissions are distributed in a similar pattern as the primary energy use across the refrigerator life cycle stages since fossil fuels are the major energy source. On the other hand, Fig. 2 shows that the purchasing cost of a new refrigerator ($430–670 in 1985 dollars depending on MY) is the most significant element of the consumer’s LCC. Compared with the purchasing cost, the annual end-use electricity cost ($20–110 in 1985 dollars depending on MY and age) is considerably lower. Such contrasting patterns between the LCI and the LCC profiles are consistently observed throughout MYs.

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decrease from the 2002 electricity use. Electricity use from Consumer Reports tends to be greater than that from the AHAM survey perhaps because Consumer Reports adopts a more stringent test procedure than that of AHAM. However, for MY 2002, the value from the AHAM survey is greater than that from Consumer Reports. Note that the values from the AHAM survey are the shipment weighted averages of all types of refrigerators while the values from the Consumer Reports are averages of mid-sized top–bottom type refrigerators. Therefore, this trend indicates that more households are switching to more energy consuming large size refrigerators and side-by-side type refrigerators. It is also notable that the past trends based on the AHAM survey describe faster technology improvements than those based on Consumer Reports. 4.3. Use phase efficiency deterioration over age

4.2. Use phase efficiency improvements over model year In the US, improvements in refrigerator energy efficiencies have been primarily driven by the appliance efficiency standards. The federal minimum efficiency standards that took effect in 1990, 1993, and 2001 were believed to be the major milestones for guiding technology improvements in refrigerator efficiencies (Meier, 1997; Meyers et al., 2003). Fig. 3 shows the past trends and future scenarios of annual electricity use based on the data from the AHAM survey and Consumer Reports. Three future scenarios were developed for each data source—0%, 1%, and 2% annual

Performance of household refrigerators is expected to deteriorate over time. A field study regarding the energy usage of existing refrigerators found that nearly half of the monitored units consumed at least 20% more energy than their rated values (Cavallo and Mapp, 2000). An analysis of laboratory tests for the refrigerators turned in during California’s Residential Appliance Recycling Program also demonstrates degradation of refrigerator efficiency over time (Goldberg et al., 2004). However, the mechanism of deterioration is still uncertain. Dirty coils and worn-out gaskets may increase energy use. Yet, studies regarding the effect of refrigerator

16000 14000

Primary Energy Use (MJ/yr.)

12000 10000

1200

1000

800

8000 600 6000 400

Electricity Use (kWh/yr.)

Past trend (Consumer Reports) Past trend (AHAM survey) Forecast A: 0%/yr. from 2002 Forecast B: 1%/yr. from 2002 Forecast C: 2%/yr. from 2002

4000 200

2000 0

0 1990

2000

2010

2020

Model Year

Fig. 3. Past trends and future forecast scenarios of energy use during the 1st year of a new refrigerator model. Forecasts A, B, and C assume that the energy consumption for a new model refrigerator would decrease 0%/year, 1%/year, and 2%/year of 2002 model, respectively (AHAM, 2003; Consumers Union, 2002).

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maintenance reveal that energy savings are negligible or non-existent even after cleaning and replacing these parts (Bos, 1993; Meier, 1995; Meier et al., 1993). The efficiency deterioration from aging of insulation foam, on the other hand, has been relatively well studied. Studies measured the loss of BA gases over time from polyurethane insulation foam, in an effort to characterize energy use as a function of refrigerator lifetime (Johnson, 2000; Johnson, 2003; Wilkes et al., 2002). Also, energy efficiency changes of full refrigerators due to foam aging have been estimated in several models. According to those models, the annual energy increase caused by aging of insulation foam is closely related to the BAs used. However, it would be difficult to precisely estimate the deterioration characteristics without a large-scale experiment. For the present study, it was assumed that 0.5% of BAs escapes from insulation foams every year (Johnson, 2000). To calculate the annual efficiency deterioration, the present study used the following equation derived from an empirical analysis (Johnson, 2000):
 20
a c DE ¼ r , (1) 20 where DE is the annual increase in energy use, r the initial aging rate, a the age ( ¼ 0, 1, y, 19), and c a constant. Foams blown by HFC-245fa, which were assumed for MYs 2003–2020 in the present study, are known to age slower than foams blown by other BAs (Johnson, 2000; Wilkes et al., 2002). On the other hand, the diffusion properties of CFC-11 and HCFC-141b inside polyurethane foams are known to be very similar with each other (Hong and Duda, 1998). To examine the sensitivity of the results based on the deterioration rate, scenarios were developed by changing initial aging rate r and constant c (Table 2). Scenario A describes the most probable, baseline case and scenario B assumes no deterioration. According to Scenario A, refrigerators with foams blown by CFC-11/HCFC-141b (MY 1985–2002) consume 21% more electricity per year after 10 years, and those with foams blown by HFC-245fa (MY 2003–2020) consume 15% more electricity (Fig. 4). After 20 years, refrigerators with each type of foam consume 24% and 20% more electricity per year than

the first year, respectively. Scenario C assumes a slower deterioration for the early MYs between 1985 and 2002 than the baseline (Scenario A) while scenario D describes a faster deterioration of future MYs between 2003 and 2020 than the baseline.

5. Life cycle optimization model construction The LCO model in the present study is constructed using dynamic programming tool. Dynamic programming is a mathematical used to find an optimal sequential decision (or optimal path) that best satisfies a decision-maker’s objective, such as economic cost. In the present study, the optimal path of decisions minimizes the cumulative LCIs (or costs) incurred from producing (or purchasing), using, and disposing a series of refrigerator MYs. In a typical dynamic programming model, a set of system characteristics is defined in the state of the system for each time epoch. Decisions are made at each time epoch throughout the time horizon of optimization. In the present study, a state is defined by a vector ði; jÞ that represents MY i and age j of a refrigerator. The dynamic LCIs and costs are characterized for each state of the system. The LCO model to find optimal refrigerator lifetimes for environmental criteria is constructed using the following notations and equations: n: N: M: BM ðiÞ:

First year. Last year. Maximum physical life. Environmental burden (hereafter called burden) from the materials production of MY i. BA ðiÞ: Burden of the manufacturing of MY i. BU ði; jÞ: Burden of the use phase during year j of MY i. BE ði; jÞ: Burden of the end-of-life stage of MY i retired at the end of year j. uði; jÞ: Cumulative burden of purchasing (producing) a new refrigerator at the start of year i and keeping it for j years. For any MY i, uði; 0Þ ¼ 0. f ðiÞ: Minimum possible burden accumulated from the start of year i through the end of year N given that a purchase is made at the start of year i.

Table 2 Deterioration scenarios of refrigerator efficiencies based on Eq. (1) (Johnson, 2000) Scenario

Scenario Scenario Scenario Scenario

A (baseline) B (no deterioration) C (slower deterioration between 1985 and 2002) D (faster deterioration between 2003 and 2020)

CFC-11/HCFC-141b (MY 1985–2002)

HFC-245fa (MY 2003–2020)

r

c

r

c

0.045 0 0.025 0.045

2.5 — 1.4 2.5

0.025 0 0.025 0.045

1.4 — 1.4 2.5

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130 CFC-11/HCFC-141b, r=0.045, c=2.5 HFC-254fa, r=0.025, c=1.4

Energy Use (%)

120

110

100

90 0

10

5

15

20

Age (years) Fig. 4. Deterioration of full refrigerator efficiencies based on Scenario A.

xi:

Number of years owning refrigerator of MY i.

uði; jÞ ¼

8 j P > < BM ðiÞ þ BA ðiÞ þ BE ði; i þ j
1Þ þ BU ði; kÞ

if j40;

> :

if j ¼ 0;

k¼1

0

ð2Þ ( f ðiÞ ¼

min

fuði; xi Þ þ f ði þ xi Þg 8 i ¼ n; . . . ; N;

xi 2f1;2;...;Mg

0

8 i4N: (3)

For each criterion, this model seeks to minimize the burden from the life cycle of MYs n to N by deciding xi, the number of years before purchasing a new refrigerator. A computer program to find the optimal path of sequential replacement decisions was coded using C language. A similar LCO model was also constructed for the cost criterion considering the LCCs from purchasing, using, and disposing refrigerator models.

6. Model results The optimal lifetimes of refrigerator MYs between 1985 and 2020 (n ¼ 1985 and N ¼ 2020) are determined for the objectives of energy, cost, and global warming

potential (GWP) on the basis of the dynamic LCI datasets developed for the present study assuming a 20year maximum physical lifetime (M ¼ 20). Table 3 shows the optimal lifetimes and cumulative LCIs and costs from the model runs assuming that a consumer purchases a new refrigerator at the beginning of 1985. For example, the energy optimization policy based on the electricity use data from Consumer Reports requires seven refrigerators of MYs 1985, 1987, 1992, 1996, 2002, 2007, and 2014. In other words, this policy would state ‘‘keep the model year 1985 refrigerator for 2 years and then replace it with a model year 1987, keep the model year 1987 for 5 years and then replace it with a model year 1992, y, and keep the model year 2014 refrigerator for 6 years, in order to minimize the cumulative energy usage over the time horizon between 1985 and 2020’’. As can be seen, optimal refrigerator lifetimes for energy and GWP objectives are significantly shorter than those for cost objective and the real-world average. Similar results for the energy and GWP objectives may be due to with the fact that the energy-related CO2 emissions from electricity generation and refrigerator production are the most dominant global warming gases. However, from a consumer’s perspective, such frequent replacements would be impractical considering the 36–50% additional cost to the cost optimal policy (lifetime of 18 years). On the other hand, the cost optimal policies incur 22–24% additional energy consumption compared to the energy optimal policies. For comparison, the average useful lifetime of a top-mount type refrigerator is 14 years

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Table 3 Optimal lifetimes of refrigerators and cumulative life cycle inventories for the time horizon between 1985 and 2020 with the baseline assumptions: 1%/year increase of efficiency between 2002 and 2020 and deterioration scenario A Objective

Electricity use data source (1985–2002)

Optimal lifetime (years)a

Cumulative energy use or GWPb

Cost (1985 dollars)

Energy

CR AHAM

2, 5, 4, 6, 5, 7, 7 4, 4, 9, 5, 7, 7

357,558 MJ 335,618 MJ

$3793 $3186

Cost

CR AHAM

18, 18 18, 18

444,503 MJ 407,907 MJ

$2534 $2350

GWP

CR AHAM

2, 7, 3, 5, 8, 11 4, 5, 8, 5, 7, 7

22,197 kg CO2-eq 20,956 kg CO2-eq

$3633 $3211

CR, Consumer Reports; AHAM, Association of Home Appliance Manufacturers survey. a Replacement intervals for 36 year time horizon. b Integrated time horizon (ITH) ¼ 100 years.

Table 4 Sensitivities of the results depending on the scenarios and assumptions regarding energy efficiencies and BA disposal based on the electricity use trends of Consumer Reports Objective

Scenarios and assumptions

Optimal lifetime (years)a

Cumulative energy use or GWPb

Cost (1985 dollars)

Energy

0%/year efficiency improvement between 2002 and 2020 2%/year efficiency improvement between 2002 and 2020 Deterioration Bc Deterioration Cc Deterioration Dc

2, 2, 2, 2, 2,

363,622 MJ 350,133 MJ 331,860 MJ 351,469 MJ 359,930 MJ

$3616 $3782 $3190 $3567 $3774

Cost

0%/year efficiency improvement between 2002 and 2020 2%/year efficiency improvement between 2002 and 2020 Deterioration Bc Deterioration Cc Deterioration Dc

18, 18, 18, 18, 17,

445,696 MJ 443,310 MJ 385,017 MJ 432,757 MJ 439,236 MJ

$2537 $2533 $2321 $2489 $2540

GWP

100% release of BA at the time of disposal

2, 7, 3, 5, 8, 11

22,204 kg CO2-eq

$3633

5, 5, 7, 5, 5,

4, 4, 8, 4, 4,

6, 7, 12 6, 5, 7, 7 10, 9 6, 10, 9 6, 7, 6, 6

18 18 18 18 19

a

Replacement intervals for 36 year time horizon. Integrated time horizon (ITH) ¼ 100 years. c 1%/year efficiency improvement between 2002 and 2020. b

while that of a one-door type refrigerator is 19 years (NFO, 1996). The results are particularly dependent on use phase electricity consumption data and trends. The optimal lifetimes based on electricity use from Consumer Reports are shorter than those based on electricity use from the AHAM survey. As discussed before, the electricity consumption trend from Consumer Reports describes a more rapid improvement than that based on the AHAM survey. The faster improvement in refrigerator efficiencies was a significant factor in determining optimal lifetimes for the energy objective. On the other hand, optimal lifetimes for the cost objective remained unchanged between the two data sources perhaps because the electricity cost difference between the two data sources was insignificant compared with purchase costs. In order to examine the sensitivity of the results, optimizations were conducted for a range of scenarios

and assumptions regarding efficiency improvement, deterioration, and BA releases. Table 4 gives the results from the model runs based on the electricity use data from Consumer Reports. Optimal lifetimes are affected by scenarios and assumptions, along with life cycle environmental and cost profiles. Nonetheless, the overall trends—short optimal lifetimes for energy and GWP objective and long optimal lifetimes for the cost objective—were similar to the baseline results in Table 3. As can be seen, efficiency improvement forecasts for future MYs partially affect the optimal lifetimes of future models for the energy objective (compare the first row of Tables 3 and 4). The benefits of replacing old models with new models would grow in parallel with improving efficiencies over MYs. However, optimal lifetimes for the cost objective were unresponsive to the efficiency improvement scenarios probably because the efficiency changes have a relatively small impact on the LCCs. Deterioration is also an important factor that

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influences optimal lifetimes. The benefits of frequent replacement of refrigerators would also grow with rapid deterioration of efficiencies over age of refrigerators. As shown from the results in Table 4, more frequent replacements are required for the energy objective with increasing deterioration rates. However, optimal lifetimes for the cost objective were consistent requiring only two refrigerators during the time horizon. The release of BA gases during the disposal stage is found to be an unimportant factor in deciding optimal lifetimes. This result indicates that the GWP from indirect sources such as CO2 emissions from electricity generation or the materials production phase of refrigerators are far more dominant than from direct releases of global warming gases. Unlike the model runs in Tables 3 and 4, an owner typically faces a decision regarding whether to dispose or continue to use an existing old refrigerator. In such a condition, the decision-maker needs information regarding only future MYs. Model runs were conducted that optimize the decisions at the beginning of 2004 with an existing model. Such model runs are implemented by assuming BM ð2004Þ ¼ 0, BA ð2004Þ ¼ 0, BE ð2004; 2003þ jÞ ¼ BE ði ; i þ j
1Þ, and BU ð2004; kÞ ¼ BU ði ; kÞ in Eqs. (2) and (3), where i denotes the MY of the existing old refrigerator. Table 5 gives the optimal environmental and economic decisions depending on the MY of an existing refrigerator. For example, at the beginning of 2004, a decision-maker should immediately replace the MY 2001 refrigerator with an MY 2004 to minimize cumulative energy consumption during the time horizon (2004–2020). The owner should then use the 2004 model for 8 years, and 2012 model for 9 years consecutively. The optimal decisions for the MYs 2001

Table 5 Optimal refrigerator lifetimes based on a 17-year time horizon (2004–2020) beginning with an existing model based on use data from Consumer Reports and the baseline assumptions: 1% (of MY 2002)/ year increase of efficiency and deterioration scenario A Objective Model year of Optimal lifetime existing model (years)a

Energy (MJ)

Cost (1985 dollars)

Energy

1985–2001 2002 2003

0, 8, 9 3, 7, 7 8, 9

111,253 109,789 107,089

$1260 $1164 $730

Cost

1985–1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

0, 17 2, 15 3, 14 4, 13 4, 13 4, 13 4, 13 17 17 17

115,591 122,575 125,422 128,341 129,044 129,622 127,961 155,620 119,277 112,360

$908 $906 $899 $893 $889 $887 $878 $536 $400 $377

a

Replacement intervals for 36 year time horizon.

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and before are identical for the energy objective. However, the optimal decision for the energy objective for the MY 2001 refrigerator incurs a significant cost increase ($1260 vs. $536) compared with the cost optimal decision of keeping the 2001 model 17 more years. On the other hand, for the cost optimization, the MYs 1994 and before should be immediately retired. Sensitivity analysis using a 0% and 2% (of MY 2002) annual efficiency increase shows similar outcomes with the replacement of any pre-2000 MY being the optimal decision for the energy objective and mid-1990s MY for the cost objective (Appendix A). These results again demonstrate that there exists a tradeoff between the optimal decision for the energy objective and cost objective. Although replacing old, inefficient refrigerators with new, efficient ones provides environmental benefits, it may be economically unfavorable from an owner’s standpoint. While replacing inefficient refrigerators would reduce the external cost of electricity (Hohmeyer, 1992; Stirling, 1997), this positive impact would not result in direct economic savings to the owner. It would also be useful to predict the environmental benefits of applying these policies to a fleet of refrigerators in designing a larger-scale replacement project. As shown in Table 5, environmental benefits of a replacement are quite different depending on the existing MYs. An MY distribution (age distribution) of household refrigerators was developed based on the 2001 Residential Energy Consumption Survey (Fig. 5). The energy savings from the optimal policy for the energy objective in Table 5, compared with the energy use from the optimal policy for the cost objective, are determined based on the following equation: S¼

20 X

½ðOE i
CE i Þ  N i ,

(4)

i¼1

where S is the energy savings, OE the energy consumption of energy optimization policy (optimal energy consumption), CE the energy consumption of cost optimization policy, N the number of refrigerators, and i the age ( ¼ 1, 2, y, 20). The environmental benefits calculated based on Eq. (4) are considerably different than the benefits based on the previous model runs beginning with a purchase. On the basis of Eq. (4) and the 17-year time horizon between 2004 and 2020, the energy savings of applying the optimal energy policies to the refrigerator fleet described in Fig. 5 is only 12% from implementing the cost optimization polices over the time horizon. On the other hand, the optimal energy policies accrued 53% more cost over the time horizon compared with the cost optimization policies. This indicates that implementing the entire set of energy optimization policies in Table 5 is even more impractical from the cost perspective. Note

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2320

10

Fraction (%)

8

6

4

2

0 0

5

10

15

20

Age Fig. 5. A hypothetical age distribution of refrigerator models based on the EIA’s 2001 Residential Energy Consumption Survey (EIA, 2004a).

that this calculation, however, does not include pre-1985 models, which are expected to be a lot more energy consuming, thus incurring high-energy costs. Also, in this calculation, cost optimization policies are closer to the optimal energy policies in cumulative energy consumption. This similarity may stem from the fact that, in Table 5, replacing pre-1995 MYs is an effective strategy for both cost and energy saving purposes. Note that based on the modeling of the present research, the average electricity use for a mid-sized MY 1994 refrigerator is 800 kWh/year at the first year of use and consumes 960 kWh/year after 10 years of operation (see Figs. 3 and 4). Therefore, replacing refrigerators with an annual energy use of around 1000 kWh would be an equivalently effective strategy for the life cycle energy and cost perspective.

7. Discussion The present study demonstrates the application of LCO to refrigerator replacement decisions and policy. An earlier paper details a methodology for optimizing life cycle environmental burdens based on the dynamic LCIs of a series of automobile MYs (Kim et al., 2003). For both automobile and refrigerator cases the driving forces toward a replacement decision include technology improvement with MY and deteriorating efficiencies with product age. The life cycle profile that illustrates the distribution of environmental burdens across life cycle stages is also an important factor influencing optimal replacement strategies. The ratio between the

‘‘fixed’’ and ‘‘marginal’’ burdens is an important determinant of optimal lifetimes. The ‘‘fixed’’ burdens are from the materials production, manufacturing, and end-of-life stage while the ‘‘marginal’’ burdens are from the use and maintenance stages of a product life cycle. Although the use phase is the most dominant source of environmental burdens for both automobiles and refrigerators, the characteristics of energy efficiency improvement and deterioration are quite different between the case of automobile and refrigerator. The fuel economy standards for automobiles have remained nearly unchanged since the mid-1980s and fuel economy deterioration with vehicle age is known to be negligible. In the case of refrigerators, on the other hand, major efficiency improvements were achieved in the last decade, primarily due to the series of federal energy efficiency standards enacted in 1990, 1993, and 2001. Also, deterioration is likely to be a significant factor for electricity consumption. Therefore, the optimal lifetimes for the energy objective were considerably shorter in the case of refrigerators (2–7 years for the baseline scenario) than in the case of automobiles (18 years) if optimized over MYs between 1985 and 2020. From the results of the model runs, it is clear that replacing old model refrigerators are beneficial to society from an environmental perspective but may be uneconomical for a consumer. A subsidy program for switching to more efficient new refrigerators is a possible device to solve this problem. There have been a number of refrigerator replacement programs mainly as a form of low-income weatherization programs. For example, from 1996, the New York Power Authority (NYPA), a

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state-owned utility organization, replaced 180,000 refrigerators in the apartments managed by the New York City Housing Authority (NYCHA). In 1999, the replaced refrigerators were, on average, 12.9 years old and consumed 1013 kWh/year. This replacement project saved, on average, 587 kWh/year of electric energy and 74 W of peak power demand per refrigerator (Kinney and Belshe, 2001). In 2002, the State of Indiana also began a state-wide refrigerator replacement program for low-income households. Funded by a utility company and the state government, the program measured energy efficiencies of high-energy user refrigerators and replaced them with Energy Star models to maximize energy savings through the program. On average, the program saved 1260 kWh per year of electricity use for each refrigerator and 0.373 kW of peak demand during the summer (York and Kushler, 2003). These programs were proven to be cost-effective over the expected lifetime of replacing refrigerators, sometimes resulting in savings-to-investment ratios over 2.5 using a 20-year time horizon. In particular, utilities support the idea of retiring outdated refrigerators since modern refrigerators serve to relieve electric loads to the grid by reducing peak demand. Also, the power factor—the true power measured by a wattmeter divided by apparent power determined by the product of voltage and current—is closer to one for new refrigerator models. Utilities prefer electric equipment with a higher power factor since power factors close to unity allow more efficient power transfer from generators to electric equipment (Kinney and Belshe, 2001). However, as shown in the present study, the net primary energy savings associated with replacing older refrigerators with new ones would be significantly lower than the explicit savings if considering the life cycle energy use associated with producing new refrigerators and recycling old refrigerators (6000 MJ per refrigerator). Surveys show that customers are shifting toward larger-size, more fashionable, but less-efficient refrigerators such as side-by-side type refrigerators (AHAM, 2003; EIA, 2004a). Thus, caution needs to be practiced in applying the findings of the present study. Obviously, use phase energy and cost savings associated with replacement decisions would be expected to decrease as replacement units become less efficient. The results presented here were based on industry average data and forecasts. Further investigations based on refrigerator model options ranging from lowest to highest efficiencies can be conducted using the LCO model.

8. Conclusion Replacing older, less-efficient refrigerators with newer, more-efficient models is an important strategy for reducing household energy consumption. The LCO

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model developed here provides a comprehensive framework to guide replacement decisions from energy, emissions, and economic perspectives. This model accounts for burdens and costs associated with the production, use, and end-of-life management phases of each refrigerator’s life cycle. Life cycle profiles that represent overall performance based on parameters such as the energy efficiency and deterioration behavior of each refrigerator, determine the timing of replacement decisions over a specified time horizon. Two time horizons were explored in this study: 1985–2020 which considered historical and future decisions and 2004–2020 which examined decisions of current owners. Over the 1985–2020 timeframe, the optimal refrigerator life from an energy and greenhouse gas emissions perspective varied from 2 to 12 years. The simulation results show that the optimal refrigerator lifetimes of 17–19 years for cost objectives are considerably longer than those for environmental objectives. Technology and design improvements leading to use phase efficiency gains can more easily offset production and disposal burdens in the case of energy and GHG. On the other hand, cost savings from electricity conservation is less significant relative to the purchase price of new refrigerators. The average lifetime of a typical household refrigerator is 14 years for top-mount type and 19 years for one-door type, which is similar to the cost optimization results (NFO, 1996). Model results over 2004–2020 timeframe for current owners, however, signal a different replacement strategy than current marketplace behavior. For example, replacing the existing mid-1990s and previous models (with over 1000 kWh per year energy use) at the beginning of 2004 is beneficial from both cost and energy perspectives. Optimal replacement policy can be rationalized from a societal perspective when the refrigerator owner takes a long term, life cycle perspective, as is the case of this investigation. Other factors, however, can influence consumer behavior such as residence time which is approximately 8 years for the average US household (Hansen, 1998). Homeowners that move more frequently may be less interested in new, more efficient appliances. In addition, whether a consumer owns or rents a house (and appliances) could also determine refrigerator lifetime. Improving operating efficiency and reducing efficiency deterioration are both important factors that affect optimal refrigerator replacement policy. The effects of rates of improvement in operating efficiency and deterioration on replacement policy were substantial when optimizing for the energy objective. These factors affected both the cumulative energy use over the time horizon and replacement frequency. However, these factors have little impact on the optimal lifetime (17–19 years) for the economic cost objective primarily because of the dominance of initial purchase cost over

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electricity costs. Given the long refrigerator lifetime, enhancing durability by developing new insulation materials will also achieve significant savings in energy and greenhouse gases from old refrigerator models. Government programs for replacing old, inefficient refrigerators with new, efficient refrigerators are currently being implemented mostly as part of weatherization for low-income households. The replacement policy analysis framework developed in the present study can serve to evaluate these incentive programs and develop new programs that could lead to broader participation of customers currently using old, inefficient refrigerators. For example, the present model could predict the economically optimal lifetime of existing old refrigerators based on a level of incentive or subsidy awarded for purchasing efficient refrigerators, and estimate energy and greenhouse gas savings associated with these programs. In addition, the present model can be used to guide refrigerator efficiency standards. Since efficiency improvements and deterioration behaviors are both crucial factors for cumulative energy consumption over time, not only initial refrigerator efficiency standards that are currently enacted, but also durability standards, if created, would save substantial energy and reduce greenhouse gas emissions. However, as presented in this analysis, these standards would have only a limited impact on refrigerator replacement decisions due to the relatively high purchasing cost compared with electricity costs, which were presumed to be stable. The LCO model results for refrigerators provided useful insights for key stakeholders including manufacturers, regulators, and consumers. Future application and extension of this research can enhance the life cycle management of household refrigerators by guiding product design, regulatory efficiency standards, market based accelerated retirement program, and consumers’ decisions.

Table A1 Optimal refrigerator lifetimes based on a 17-year time horizon (2004–2020) beginning with an existing model based on use data from Consumer Reports and the baseline assumptions: 0% (of MY 2002)/ year increase of efficiency and deterioration scenario A Objective

Model year of existing model

Optimal lifetime (years)a

Energy (MJ)

Cost (1985 dollars)

Energy

1985–2002 2003

0, 17 17

117,837 112,360

$915 $377

Cost

1985–1995 1996 1997 1998 1999 2000 2001 2002 2003

0, 17 2, 15 3, 14 4, 13 4, 13 4, 13 17 17 17

117,837 125,835 129,343 134,106 134,684 133,023 155,620 119,277 112,360

$915 $913 $907 $904 $901 $893 $536 $400 $377

a

Table A2 Optimal refrigerator lifetimes based on a 17-year time horizon (2004–2020) beginning with an existing model based on use data from Consumer Reports and the baseline assumptions: 2% (of MY 2002)/ year increase of efficiency and deterioration scenario A Objective

Model year of existing model

Optimal lifetime (years)a

Energy (MJ)

Cost (1985 dollars)

Energy

1985–2001 2002 2003

0, 8, 9 3, 7, 7 5, 6, 6

104,548 102,364 100,630

$1242 $1142 $1086

Cost

1985–1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

0, 17 2, 15 2, 15 3, 14 3, 14 4, 13 4, 13 6, 11 17 17 17

113,345 119,283 122,575 120,854 120,210 123,982 124,560 130,333 155,620 119,277 112,360

$902 $899 $906 $884 $879 $876 $873 $863 $536 $400 $377

Acknowledgements This work was partially supported by National Science Foundation under the Technology for a Sustainable Environment (TSE) program Grant No. BES-9985625. The authors gratefully acknowledge the contributions to the present study from Robert Johnson and Karel Czanderna of Whirlpool Corporation, and Wayne Morris of the Association of Home Appliance Manufacturers.

Replacement intervals for 17 year time horizon.

a

Replacement intervals for 17 year time horizon.

0% and 2%, respectively. These results can be compared to the baseline results (1% improvement rate) which were reported in Table 5.

References Appendix A Tables A1 and A2 present optimal refrigerator lifetimes for annual efficiency improvement rates of

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