Economic efficiency v energy efficiency

Horowitz, Marvin J.; Haeri, Hossein

doi:10.1016/0140-9883(90)90046-i

Cited by 28 publications

(9 citation statements)

References 14 publications

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“…The method is portable to cities in different climates, requiring solely data that are readily available for billing and urban planning purposes. This physical approach would benefit from the interaction with new advancement in materials design [46,47] and policy analyses to shed light on energy price-dependent [48], cost-effectiveness [49] and properties' tenure-dependent considerations [50] in various city-scale retrofit scenarios. Hence, from a practical view point, we consider mitigation of city-scale gas consumption and associated carbon emissions to be a multi-objective optimization problem characterized by a Pareto front in the space of technical, economical, legal and political aspects.…”

Section: Resultsmentioning

confidence: 99%

Data analytics for simplifying thermal efficiency planning in cities

Qomi

Noshadravan

Sobstyl³

et al. 2016

J. R. Soc. Interface.

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More than 44% of building energy consumption in the USA is used for space heating and cooling, and this accounts for 20% of national CO 2 emissions. This prompts the need to identify among the 130 million households in the USA those with the greatest energy-saving potential and the associated costs of the path to reach that goal. Whereas current solutions address this problem by analysing each building in detail, we herein reduce the dimensionality of the problem by simplifying the calculations of energy losses in buildings. We present a novel inference method that can be used via a ranking algorithm that allows us to estimate the potential energy saving for heating purposes. To that end, we only need consumption from records of gas bills integrated with a building's footprint. The method entails a statistical screening of the intricate interplay between weather, infrastructural and residents' choice variables to determine building gas consumption and potential savings at a city scale. We derive a general statistical pattern of consumption in an urban settlement, reducing it to a set of the most influential buildings' parameters that operate locally. By way of example, the implications are explored using records of a set of (N ¼ 6200) buildings in Cambridge, MA, USA, which indicate that retrofitting only 16% of buildings entails a 40% reduction in gas consumption of the whole building stock. We find that the inferred heat loss rate of buildings exhibits a power-law data distribution akin to Zipf's law, which provides a means to map an optimum path for gas savings per retrofit at a city scale. These findings have implications for improving the thermal efficiency of cities' building stock, as outlined by current policy efforts seeking to reduce home heating and cooling energy consumption and lower associated greenhouse gas emissions.

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Section: Resultsmentioning

confidence: 99%

Data analytics for simplifying thermal efficiency planning in cities

Qomi

Noshadravan

Sobstyl³

et al. 2016

J. R. Soc. Interface.

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“…(Dinan and Miranowski, 1989;Laquata, 1986;Johnson and Kaserman, 1983;Corgel et.al., 1982;Longstreth, 1986;Halvorsen and Pollakowski, 1981). Horowitz and Haeri (1990) found that home value reflects a rational trade-off between energy bills and after-tax mortgage interest expense, as demand for energy-efficient homes raises their price relative to other homes until that higher price results in higher after-tax mortgage costs that approximately offset energy bill savings. Nevin and Watson (1998) tested this "rational market" theory against [1991][1992][1993][1994][1995][1996] AHS data, and showed a consistent rise in home value of about $20 for every $1 reduction in annual energy bills, regardless of main heating fuel (gas, electric, or fuel oil), after controlling for other variables affecting home value.…”

Section: Summary Of Lead-safe Window Replacement Costs Benefits Andmentioning

confidence: 99%

Monetary benefits of preventing childhood lead poisoning with lead-safe window replacement

Nevin

Jacobs

Berg

et al. 2008

Environmental Research

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“…( Corgel et al, 1982;Johnson and Kaserman, 1983;Laquatra, 1986;Longstreth, 1986;Dinan & Miranowski, 1989;Horowitz & Haeri, 1990) Sub-sample analyses showed the same result for attached and detached homes, regardless of heating fuel used. Mortgage rates were near 7% from 1991-1996, and the mortgage interest deduction resulted in after-tax mortgage rates near 5%, so the efficient home value premium of $20 per $1 in annual energy savings reflected a rational trade-off between annual energy bill savings and after-tax mortgage interest expense clearance testing for lead dust.…”

Section: Home Energy Efficiency Impact On Home Valuementioning

confidence: 57%

“…(Corgel et al, 1982;Johnson and Kaserman, 1983;Laquatra, 1986;Longstreth, 1986;Dinan & Miranowski, 1989;Horowitz & Haeri, 1990) This hypothesis was later tested against very large American Housing Survey (AHS) datasets, including separate analysis of 1991, 1993, and 1995 national AHS data and merged 1992-1996 AHS metropolitan statistical area (MSA) data. (Nevin & Watson, 1998) Source: Nevin & Watson, 1998 Homebuyers do not calculate the present value of energy savings, but many buyers do ask to see utility bills before they make an offer (Long & Foster, 2009), to evaluate their ability to pay their total housing costs.…”

Section: Home Energy Efficiency Impact On Home Valuementioning

confidence: 99%

Energy-efficient housing stimulus that pays for itself

Nevin¹

2010

Energy Policy

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This paper describes an energy efficient housing stimulus strategy that can: (1) quickly provide large-scale job creation; (2) reduce home energy bills by 30% to 50% with associated reductions in emissions and energy assistance spending; (3) stabilize home values and reduce foreclosure inventory; (4) help to eliminate childhood lead poisoning; and (5) implement regulatory reforms that highlight market incentives for cost effective energy efficiency and alternative home energy investments. These benefits, far in excess of costs, can be achieved by combining "lead-safe window replacement" with other weatherization activities and simple regulatory and market reforms. This strategy can help to coordinate American Recovery and Reinvestment Act funding for energy efficiency, the $75 billion Making Home Affordable plan to reduce foreclosures, and the recently announced partnership between the Departments of Energy (DOE) and Housing and Urban Development (HUD) to streamline weatherization efforts and spur job creation. Energy Efficient Housing Stimulus that Pays for ItselfPresident Obama has charged his economic team with finding "areas where we can get a twofer, where we're getting both a short-term stimulus and we're also laying the groundwork for long-term economic growth." (CQ Transcriptswire, 2008) This paper presents a strategy that can yield a fiver: (1) provide large-scale job creation; (2) reduce home energy bills by 30% to 50% with associated reductions in emissions and federal spending for energy assistance; (3) stabilize home values and reduce the foreclosure inventory; (4) help to eliminate childhood lead poisoning; and (5) implement regulatory reforms that highlight market incentives for cost effective energy efficiency and alternative energy investments. These benefits, far in excess of costs, can be achieved by combining "lead-safe window replacement" with other weatherization activities and simple regulatory and market reforms. This strategy can provide a critical connection between American Recovery and Reinvestment Act funding for energy efficiency, the $75 billion Making Home Affordable plan to reduce foreclosures, and the recently announced partnership between the Departments of Energy (DOE) and Housing and Urban Development (HUD) to streamline weatherization efforts and spur job creation. Large-Scale Job CreationWindow replacement is a labor intensive activity that can quickly create millions of jobs with window manufacturers and their suppliers and, importantly, for housing renovation workers, especially hard hit by the housing market decline. Secondary, economic multiplier effects would include increased demand for light trucks from workers employed by this initiative. The 2008 spike in gas prices has (belatedly) discouraged the use of light trucks in rush hour commutes, but Nevin -Energy Efficient Housing Stimulus that Pays for Itself -4/9/2009 -Page 2 of 30 the light truck market has also been hard hit by the decline in housing construction and renovation work, where trucks are essenti...

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Economic efficiency v energy efficiency

Cited by 28 publications

References 14 publications

Data analytics for simplifying thermal efficiency planning in cities

Data analytics for simplifying thermal efficiency planning in cities

Monetary benefits of preventing childhood lead poisoning with lead-safe window replacement

Energy-efficient housing stimulus that pays for itself

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