A cost benefit analysis of retrofitting public policies on Atlanta residential housing

The residential building sector has a major share in carbon emission and energy consumption. In the US, around 60% of the housing stock belongs to the owner-occupied sector. Since more than half of the existing building stock was built before the modern energy efficiency standards are taken place, there is a potential to reduce the energy consumption and greenhouse gas emissions in this sector, only by retrofitting the existing buildings. However, this goal cannot be achieved without a larger scale Cost Benefit Analysis (CBA) to develop and demonstrate market ready retrofit solutions/policies from both the government and the homeowner’s standings. To this extend, the aim of the presented paper is to conduct a city-level CBA on the city of Atlanta which ranked 5th in producing GHG emissions among 100 US metropolitan areas while residential buildings sector is ranked 4th among other contributing sectors. To this end, a hypothetical public policy of retrofitting single-family residential buildings built before 1970s is proposed with the objective of reducing the regional energy consumption rate while calculating the upper bound of the tax to be proposed on the properties rejecting to renovate. The preliminary results of this CBA revealed that although retrofitting all the prior 1970s buildings won’t be beneficial comparing to the status quo, the numbers are highly sensitive to the proposed discount rate as well as the percentage of the homeowners practically decide to retrofit. The sensitivity analysis showed that if only 30-40% of participants decided not to renovate and pay the tax, the CBA could be a positive Net Present Value (NPV) with a relatively low tax rate (less than $0.5/sqft) implementation. Therefore, it is recommended to more accurately study the reaction of the homeowners to the policy before implementing the tax/subsidy rates while precisely observe the fluctuations of the market discount rate

Aeroservoelastic design definition of a 20 MW common research wind turbine model

Wind turbine upscaling is motivated by the fact that larger machines can achieve lower levelized cost of energy. However, there are several fundamental issues with the design of such turbines, and there is little public data available for large wind turbine studies. To address this need, we develop a 20 MW common research wind turbine design that is available to the public. Multidisciplinary design optimization is used to define the aeroservoelastic design of the rotor and tower subject to the following constraints: blade‐tower clearance, structural stresses, modal frequencies, tip‐speed and fatigue damage at several sections of the tower and blade. For the blade, the design variables include blade length, twist and chord distribution, structural thicknesses distribution and rotor speed at the rated. The tower design variables are the height, and the diameter distribution in the vertical direction. For the other components, mass models are employed to capture their dynamic interactions. The associated cost of these components is obtained by using cost models. The design objective is to minimize the levelized cost of energy. The results of this research show the feasibility of a 20 MW wind turbine and provide a model with the corresponding data for wind energy researchers to use in the investigation of different aspects of wind turbine design and upscaling. Copyright © 2016 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134256/1/we1970.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134256/2/we1970_am.pd

Outcomes of chronic total occlusion percutaneous coronary intervention from the RAIAN (RAjaie - Iran) registry

Objective: While most of the evidence in CTO interventions emerge from Western and Japanese studies, few data have been published up today from the Middle East. Objective of this study was to evaluate technical success rates and clinical outcomes of an Iranian population undergoing CTO PCI in a tertiary referral hospital. Moreover, we sought to evaluate the efficacy of our CTO teaching program. Methods: This is a retrospective single-center cohort study including 790 patients who underwent CTO PCI performed by operators with different volumes of CTOs PCI performed per year. According to PCI result, all patients have been divided into successful (n = 555, 70.3 %) and unsuccessful (n = 235, 29.7 %) groups. Study endpoints were Major Adverse Cardiovascular Events and Health Status Improvement evaluated using the Seattle Angina Questionnaire at one year. Results: A global success rate of 70 % for antegrade and 80 % for retrograde approach was shown despite the lack of some CTO-dedicated devices. During the enrollment period, the success rate increased significantly among operators with a lower number of CTO procedures per year. One-year MACE rate was similar in both successful and unsuccessful groups (13.5 % in successful and 10.6 % in unsuccessful group, p = 0.173). One year patients' health status improved significantly only in successful group. Conclusions: No significant differences of in-hospital and one-year MACE were found between the successful and unsuccessful groups. Angina symptoms and quality of life significantly improved after successful CTO PCI. The RAIAN registry confirmed the importance of operator expertise for CTO PCI success

Attitudes and perceptions regarding entrepreneurship around the world : a cluster analysis approach

Nowadays it is believed that entrepreneurship could be a driving force in growth and development. For the achievement of a relevant national entrepreneurship rate the social and economic business environment can be crucial. However, despite the international attention given to entrepreneurship, it is not known if it is a global phenomenon or if there are particular regions where the entrepreneurial activity is specially recognized by society. Applying cluster analysis statistical techniques to a dataset gathered by the Global Entrepreneurship Monitor (GEM) and that includes, in 2010, 59 countries this paper intends to identify groups of countries with the same population attitude and perception regarding entrepreneurship

Attitudes and perceptions regarding entrepreneurship around the world : a cluster analysis approach

Nowadays it is believed that entrepreneurship could be a driving force in growth and develop-ment. For the achievement of a relevant national entrepreneurship rate the social and economic business environment can be crucial. However, despite the international attention given to entrepreneurship, it is not known if it is a global phenomenon or if there are particular regions where the entrepreneurial activity is specially recognized by society. Applying cluster analysis statistical techniques to a dataset gathered by the Global Entrepreneurship Monitor (GEM) and that includes, in 2010, 59 countries this paper intends to identify groups of countries with the same population attitude and perception regarding entrepreneurship

Embodied Life Cycle Assessment (LCA) comparison of residential building retrofit measures in Atlanta

© 2020 Elsevier Ltd Studies showed that up to 30% of a building's life cycle energy and emissions are associated with the embodied phase and this number could increase to 50% for energy efficient passive houses. The residential housing market alone has a significant impact on US emissions. This research targeted Atlanta as one of the growing metropolitan areas in the US and conducted an embodied Life Cycle Assessment (LCA) comparison of single-family residential retrofit measures considering the original construction year of the buildings. At first, the paper investigated the potential retrofit measurements to improve the operational energy consumption of the different building categories. The paper then calculated the embodied impacts associated with the retrofit measures and compared them against each other to find the most energy and environmentally efficient options in terms of the embodied impacts. The paper finally conducted a trade-off analysis to investigate the payback period of the retrofit options regarding their impact on the operational energy savings throughout the second phase of the building's life span. The main findings of this research showed that the highest environmental impacts are associated with the attic/knee insulation and heating, ventilation and air conditioning (HVAC) unit's replacement through retrofitting residential buildings. The findings also demonstrated the significant environmental impacts for foundation wall insulation and window upgrading through retrofitting dwellings built before the 1970s. The trade-off results revealed that the embodied energy payback period is generally around 3–5 years for before 1970s and 1.6–3.2 years for after 1970s buildings

Embodied life cycle assessment comparison of single family residential houses considering the 1970s transition in construction industry: Atlanta case study

20% of US energy consumption and their consequential environmental impacts are associated with building sector. Previous studies show that approximately 30% of a building's life cycle energy is attributed to its embodied energy. This study focuses on the residential buildings in the City of Atlanta and describes the trend of embodied energy and emissions of residential buildings in the city considering the 1970s transition in construction industry. The major objective of this research is to create a process-based Life Cycle Assessment (LCA) model to compare the embodied impacts of residential buildings constructed by two separate pre-1970s and post-1970s construction trends. For this purpose, the residential buildings have been categorized into two groups of buildings built before 1970s and built after 1970s. The 1-story and 2-story buildings have also been analyzed separately. The results indicated that residential buildings built before 1970s have lower embodied energy and impacts per square meter than residential buildings built after 1970s. This difference is in its highest for GWP which is 3.75–4.04 times higher for buildings built after 1970s. AP, ODP and SP come next with approximately 72%, 45% and 22% increase respectively for their 1-story models built after 1970s and with approximately 75%, 75% and 15% increase respectively for their 2-story models built after 1970s. Additionally, 2-story residential buildings have lower embodied energy and environmental impacts per square meter in comparison to 1-story residential buildings for all building scenarios and impacts

Forecasting Ratio of Low Bid to Owner\u27s Estimate for Highway Construction

Several state departments of transportation (state DOTs) have encountered significant challenges to accurately estimate costs of their highway projects. It is not uncommon that states\u27 DOT estimates (owner\u27s estimates) are significantly different from contractors\u27 submitted bids. This is a critical problem for state highway agencies that strive to develop more accurate cost estimates, deliver projects within the budget, and optimize constrained funds for their highway programs. This inaccuracy problem is a temporal issue since the engineer\u27s estimate is developed ahead of time before the project is advertised and bids are received. The question that transportation agencies are interested in finding an answer to is: are there any significant risk factors in the construction market indicating to the increased likelihood of the deviation between owner\u27s estimate and the submitted low bid? In this research, a temporal perspective is selected to answer this question through identifying risk factors affecting the accuracy of the owner\u27s estimate. The ratio of low bid to owner\u27s estimate is examined using time-series analysis. The objectives of this research are to (1) examine several variables representing local highway construction market, overall construction market, macroeconomic conditions, and energy market, to identify the leading indicators of ratio of low bid to owner\u27s estimate; and (2) use the identified leading indicators to develop an appropriate time-series model to forecast the ratio of low bid to owner\u27s estimate. Four variables are identified as the major leading indicators: (1) number of projects awarded in the same month at the state level; (2) average number of bidders last month; (3) producer price index for steel mill products (PPISM); and (4) construction cost index (CCI). Several seasonal autoregressive integrated moving average with explanatory variable (ARIMAX) models are developed that are capable of forecasting the ratio of low bid to owner\u27s estimate with a high accuracy. This research contributes to the state of knowledge of analyzing the difference between owner\u27s estimate and low bid through: (1) identification of leading indicators of ratio of low bid to owner\u27s estimate that convey the extent of risk and uncertainty associated with construction projects at the cost estimation phase; and (2) development of appropriate multivariate time-series models (i.e., ARIMAX models) to predict the ratio of low bid to owner\u27s estimate. It is anticipated that the results will help cost estimating professionals in transportation agencies better understand the variability between their estimates and submitted bids by highway contractors, and thus, prepare more accurate cost estimates and develop appropriate risk management strategies for enhanced decision-making

A real options approach to evaluating investment in solar ready buildings

Sustainable building technologies such as Photovoltaics (PV) have promising features for energy saving and greenhouse gas (GHG) emissions reduction in the building sector. Nevertheless, adopting these technologies generally requires substantial initial investments. Moreover, the market for these technologies is often very vibrant from the technological and economic standpoints. Therefore, investors typically find it more attractive to delay investment on the PV panels. Nevertheless, they can prepare \u93Solar Ready Buildings\u94 that can easily adopt PV panels later in future at the optimal time; when their prices are lower, energy price are higher, or stricter environmental regulations are in place. The conventional valuation methods such as Net Present Value (NPV) are unable to identify the optimal timing for investing in the PV panels. Hence, in order to avoid over- and under-investment, the decision makers should be equipped with proper financial valuation models that help them identify the optimal investment timing. We apply Real Options Theory from finance/decision science to create an investment valuation framework for finding the optimal time for investing in PV technologies. Our proposed investment analysis model uses experience curve concept to model the changes in price and efficiency of the PV technologies over time. It also has an energy price modeling component that characterizes the uncertainty about future retail price of energy as a stochastic process. Finally, the model incorporates the information concerning specific policy and regulatory instruments that may affect the investment value. Using our mode, investors\u92 financial risk profiles of investment (i.e. Cumulative Distribution Function of the Investment Value) in the \u93fixed\u94 Solar Building and \u93flexible\u94 Solar Ready Buildings will be developed. This will determine the Financial Value (if any) of investing in the Solar ready building and identify the optimal time for installing the PV panels

Applying the shuffled frog-leaping algorithm to improve scheduling of construction projects with activity splitting allowed

In situation of contractors competing to finish a given project with the least duration and cost, acquiring the ability to improve the project quality properties seems essential for project managers. Evolutionary Algorithm (EAs) have been applied as suitable algorithms to develop the multi-objective Time-Cost trade-off Optimization (TCO) and Time-Cost-Resource Optimization (TCRO) in the past few decades ; however, by improving EAs, the Shuffled Frog Leaping Algorithm (SFLA) has been introduced as an algorithm capable of achieving a better solution with faster convergence. Furthermore, considering splitting in execution of activities can make models closer to approximating real projects. One example has been used to demonstrate the impact of SFLA and splitting on the results of the model and to compare with previous algorithms. Current research has elucidated that SFLA improves final results and splitting allows the model find suitable solutions