Life Cycle Energy Consumption Research Articles

Sustainability: A new imperative in contaminated land remediation

Abstract Land is not only a critical component of the earth's life support system, but also a precious resource and an important factor of production in economic systems. However, historical industrial operations have resulted in large areas of contaminated land that are only slowly being remediated. In recent years, sustainability has drawn increasing attention in the environmental remediation field. In Europe, there has been a movement towards sustainable land management; and in the US, there is an urge for green remediation. Based on a questionnaire survey and a review of existing theories and empirical evidence, this paper suggests the expanding emphasis on sustainable remediation is driven by three general factors: (1) increased recognition of secondary environmental impacts (e.g., life-cycle greenhouse gas emissions, air pollution, energy consumption, and waste production) from remediation operations, (2) stakeholders’ demand for economically sustainable brownfield remediation and “green” practices, and (3) institutional pressures (e.g., social norm and public policy) that promote sustainable practices (e.g., renewable energy, green building, and waste recycling). This paper further argues that the rise of the “sustainable remediation” concept represents a critical intervention point from where the remediation field will be reshaped and new norms and standards will be established for practitioners to follow in future years. This paper presents a holistic view of sustainability considerations in remediation, and an integrated framework for sustainability assessment and decision making. The paper concludes that “sustainability” is becoming a new imperative in the environmental remediation field, with important implications for regulators, liability owners, consultants, contractors, and technology vendors.

Large-scale building simulation using cloud computing for estimating lifecycle energy consumption

The use of whole building simulation is increasing to support the design process. Often it is desirable to evaluate many scenarios, however the simulation time involved presents a significant barrier. Simulationists are forced to reduce the number of scenarios evaluated to meet time constraints. With cloud computing, simulationists can significantly reduce the total simulation time by allocating portions of the simulations to multiple processor cores. The benefit of cloud computing is demonstrated through a case study project, which computes the lifecycle energy consumption (LEC) of 1 080 000 single detached home design scenarios in Toronto, for a budget of CAN$2400. Code was written using Python to couple EnergyPlus and ATHENA IE to modify input files, process results and calculate LEC. The results of this study suggest that utilizing cloud computing to simulate large scenario studies represents an efficient method that is beginning to surface in mainstream building simulation.

LIFECYCLE ENERGY CONSUMPTION PREDICTION OF RESIDENTIAL BUILDINGS BY INCORPORATING LONGITUDINAL UNCERTAINTIES

Accurate prediction of buildings’ lifecycle energy consumption is a critical part in lifecycle assessment of residential buildings. Longitudinal variations in building conditions, weather conditions and building's service life can cause significant deviation of the prediction from the real lifecycle energy consumption. The objective is to improve the accuracy of lifecycle energy consumption prediction by properly modelling the longitudinal variations in residential energy consumption model using Markov chain based stochastic approach. A stochastic Markov model considering longitudinal uncertainties in building condition, degree days, and service life is developed: 1) Building's service life is estimated through Markov deterioration curve derived from actual building condition data; 2) Neural Network is used to project periodic energy consumption distribution for each joint energy state of building condition and temperature state; 3) Lifecycle energy consumption is aggregated based on Markov process and the state probability. A case study on predicting lifecycle energy consumption of a residential building is presented using the proposed model and the result is compared to that of a traditional deterministic model and three years’ measured annual energy consumptions. It shows that the former model generates much narrower distribution than the latter model when compared to the measured data, which indicates improved result.

Sensitivity of Energy Use to Factors in Pipe Replacement Planning for a Large Water Distribution System

Abstract A previous study completed by the authors used a life-cycle energy analysis approach to evaluate energy associated with pipe replacement schedules in a large distribution system, thereby identifying several factors that contributed to life cycle energy consumption. This paper examines the impact of parameters within the calculation of life cycle energy consumption with a sensitivity analysis. Leak duration, leak volume, break rate model coefficients, and pump efficiency were evaluated. The results of the analysis suggest that investments in improving pump efficiency are likely to yield greater energy savings than investments in leak detection or leakage volume quantification.

Life Cycle Energy of Low Rise Residential Buildings in Indian Context

Life cycle energy of the building accounts for all energy inputs to the buildings during their intended service life. Buildings need to be constructed in such a way that energy consumption in their life cycle is minimal. Life Cycle Energy (LCE) consumption data of buildings is not available in public domain which is essentially required for building designers and policy makers to formulate strategies for reduction in LCE of buildings. The paper presents LCE of twenty (20) low rise residential buildings in Indian context. LCE of the studied buildings is varying from 160 - 380 kWh/m2 year (Primary). Based on the LCE data of studied buildings, an equation is proposed to readily reckon LCE of a new building.

Life-Cycle Greenhouse Gases and Energy Consumption for Material and Construction Phases of Pavement with Traffic Delay

This paper discusses an approach to life-cycle assessment (LCA) for pavement construction applications. The scope of the study included the material production and construction phases pertaining to the upper layers of pavement; the aim was to quantify energy consumption and greenhouse gases. Life-cycle inventory data were taken from literature sources and questionnaires, with system boundaries including upstream processes for the production of major materials and fuels. The use of regionalized data was necessary to ensure proper application of LCA. Thus, for the material production phase, this LCA included preliminary data collected from regional surveys and incorporated a localized life-cycle model for asphalt binder production. The impact of traffic delay was modeled in the construction phase with the U.S. Environmental Protection Agency's Motor Vehicle Emission Simulator. A case study was performed for a simulated two-lane reconstruction of an existing Interstate in northern Illinois. The energy consumption in the material phase [5,425 million (M) Btu/lane mile] was significantly higher than that of the construction phase (137 MBtu). The same pattern held for global warming potential [405 versus 12.0 tons of carbon dioxide equivalent (CO2e)]. With respect to traffic delay, the values of global warming potential (between 2.0 and 9.9 tons of CO2e) and energy consumption (between 22.5 and 116.8 MBtu) were comparable to those from the construction phase.

Impact of Hydrogen in the Road Transport Sector for Portugal 2010-2050

This paper presents an analysis of the potential economic-wide energy and CO2 emissions implications of hydrogen vehicle penetration into the Portuguese road transport over the time-horizon 2010-2050. The energy and emissions implications are obtained using PATTS (Projections for Alternative Transportation Technologies Simulation), an excel spreadsheet model based on forecast scenarios. Historical data and trends of gasoline versus diesel share, fleet scrappadge, representative light-duty vehicle technologies life cycle energy and emission factors, are used to estimate, on a yearly basis, the total fleet life cycle energy consumption, CO2 emissions and air quality related impact. The macroeconomic effects are assessed with a Computable General Equilibrium model that is solved as a non-linear optimization problem formulated in GAMS software capable of dealing with substitution between labour, capital stock, electric energy and non-electric energy factors of production. It integrates parameter inputs obtained from PATTS tool where the transportation sector becomes hydrogen driven and a wide hydrogen refuelling infrastructure is deployed. The simulation experiments show that “hydrogen technologies” are likely to become economically viable. Household consumption, real GDP and investment increase from baseline. The positive impact upon the economic variables is supplemented by energy costs reductions, of just -0.1 to -0.3 percent per annum, in both high-price and low-price cases. The economy grows faster in the low-price case where the reductions in energy costs are also more pronounced. CO2 avoided emissions due to hydrogen economy reach a maximum of 2 kton/km in 2050, if the natural gas steam reforming production method is adopted.

Life Cycle Energy and GHG Emission within the Turin Metropolitan Area Urban Water Cycle

Abstract This study analyze the urban water cycle in the Turin Metropolitan Area (Northwestern Italy), with a focus on quantifying the annual life cycle energy consumption and greenhouse gas emissions, using Material Flow Analysis and Life Cycle Assessment methods. The annual direct and indirect energy consumption and greenhouse gas emissions have been quantified as related to system-wide energy consumption and production and transportation of chemicals used in water/wastewater treatment plants. Results says that the wastewater treatment consumes the biggest share of the total energy (44%), but a significant part of this energy demand is provided by the energy in biogas produced from wastewater sludge.

Energy consumption and intensity of toll highway transport in Spain

We estimate the energy consumption of toll highway transport on a number of Spanish roads. Regression parameters are balanced according to coefficients from an empirical analysis based on survey data by vehicle type. The mean energy consumption and subsequent CO2 emissions on the toll highway sections are estimated as 1895MJ/h/lane-km and 0.15tCO2eq./h/lane-km, values that increase to 2644 and 0.22 when energy and carbon emissions of transport infrastructure are considered based on the life cycle energy consumption for toll highway construction and use. If the energy intensity of infrastructure construction is allocated to the users according to traffic, it is much higher for motorcycles than for cars, and is significantly lower for articulated trucks than for vans.

A Modular Design Approach to Improve Product Life Cycle Performance Based on the Optimization of a Closed-Loop Supply Chain

As environmental concerns have grown in recent years, the interest in product design for the life cycle (DFLC) has exhibited a parallel surge. Modular design has the potential to bring life cycle considerations into the product architecture decision-making process, yet most current modular design methods lack the capability for assessing module life cycle consequences in a supply chain. This paper proposes a method for product designers, called the architecture and supply chain evaluation method (ASCEM), to find a product modular architecture with both low life cycle costs and low energy consumption at the early design stages. ASCEM expands the assessment scope from the product's architecture to its supply chain network. This work analyzes the life cycle costs (LCCs) and energy consumption (LCEC) of two products designated within the European Union's directive on waste of electric and electronic equipment (WEEE) within a closed-loop supply chain to identify the most beneficial modular structure. In addition, data on 27 theoretical cases representing various products are analyzed to show the broader applicability of the proposed methodology. Our analysis shows that ASCEM can efficiently identify a good-quality modular structure having low LCC and LCEC in a closed-loop supply chain for both the two tested products and the hypothetical cases.

A rule-based approach for determining the plausible universe of electric vehicle buyers in the Lisbon Metropolitan Area

The electric vehicle (EV) presents many advantages when compared to the internal combustion engine vehicle (ICEV): lower lifecycle energy consumption, operating costs, air and noise emissions. Conversely, it also has disadvantages: high purchase price, reduced driving range and insufficient charging system (long charging time and low network coverage). Car purchase behaviour is a well-studied process where explanatory models estimate the discrete choice probability of each alternative of the choice set based on car and consumers (socioeconomic) attributes.Differently, few studies have focused on the identification of the most plausible choice set depending on the individuals’ characteristics. This study aimed to evaluate the market potential of EV when such surveys are lacking, by identifying the households to whom the EV would be a plausible choice when buying a new car, despite its current cost and technological limitations. We developed a rule-based screening methodology where alternatives are eliminated from the consumer’s choice set using simple non-compensatory rules. In the end, we aim to obtaining a choice set that is closer to the real consumer’s choice set based on his socioeconomic traits and mobility patterns.After characterising households according to a set of 19 indicators (e.g., ‘Home location’, ‘Activity time’, ‘Daily trips’, etc.), they are classified according to 5 profiles that correspond to increasing probability of including an EV in their choice set. The latter two profiles delimit the potential market of EV. To accommodate the uncertainty regarding the future of EV related policies, four scenarios concerning different incentive policies were considered. This method was implemented in a case study in Lisbon Metropolitan Area, Portugal.Results suggest that, currently, the diffusion of EV in LMA is very restricted, ranging from 2% to 6.2% of the households, depending on the incentive policies. Even if the price of the EV was not a barrier, it would still be suitable only to 10.4% of the LMA households.

Selection of New Energy Vehicle Fuels and Life Cycle Assessment

Life cycle energy consumption and environment emission assessment model of vehicle new energy fuels is established. And life cycle energy consumption and environmental pollutant emissions of new energy fuels are carried out. Results show that the full life cycle energy consumption of alcohol fuels is highest, and the full life cycle energy consumption of the fuel cell is lowest, and the fuel consumption is mainly concentrated in the use stage, and that is lowest in the raw material stage. And the full life cycle CO2 emission of methanol is highest, and the full life cycle CO2 emission of Hybrid is lowest. The full life cycle VOCHCNOXPM10 and SOX emissions of alcohol fuels is highest, and the fuel cell is lowest.

Cost, energy, and greenhouse gas analysis of fly ash stabilised cold in-place recycled asphalt pavement

The purpose of this study is to evaluate the performance, costs, energy, and greenhouse gas emission of cementitious high-carbon fly ash (CHCFA)-stabilised recycled pavement materials (RPMs) as base course. Three test road cells were built in Minnesota. These cells have the same pavement structure except different base courses: conventional crushed aggregates, untreated RPM, and CHCFA-stabilised RPM. Results of laboratory and field tests were used in the Mechanistic-empirical pavement design guide (MEPDG) to predict the pavement performance. MEPDG performance prediction indicated that Cell 79 containing CHCFA-stabilised RPM had the longest service life in the three cells. The life-cycle analysis indicated that the usage of the CHCFA-stabilised RPM as the base of the flexible pavement can significantly reduce the life-cycle cost, energy consumption, and greenhouse gas emission.

Assessment of Life Cycle Energy Consumption and Emissions for Conventional and Advanced Powertrain Vehicles

In this study, an environmental comparison of hybrid, fuel cell and gasoline passenger vehicles is performed with the application of life cycle assessment (LCA) methodology. Unlike in a classic LCA, the vehicle cycle and fuel cycle of vehicles have both been modeled to cover vehicles with the full life time.According to the assumptions, the total energy consumption of the hybrid and fuel cell vehicles are respectively 27% and 37% lower than that of the gasoline vehicle. The GHG emission of the hybrid and fuel cell vehicles are respectively 27% and 44% lower than that of the gasoline vehicle. The results of the study show that the FCV is the one that presents the lower LCA energy consumption and GHG emission compared with the HEV.

Electric Urban Delivery Trucks: Energy Use, Greenhouse Gas Emissions, and Cost-Effectiveness

We compare electric and diesel urban delivery trucks in terms of life-cycle energy consumption, greenhouse gas (GHG) emissions, and total cost of ownership (TCO). The relative benefits of electric trucks depend heavily on vehicle efficiency associated with drive cycle, diesel fuel price, travel demand, electric drive battery replacement and price, electricity generation and transmission efficiency, electric truck recharging infrastructure, and purchase price. For a drive cycle with frequent stops and low average speed such as the New York City Cycle (NYCC), electric trucks emit 42-61% less GHGs and consume 32-54% less energy than diesel trucks, depending upon vehicle efficiency cases. Over an array of possible conditions, the median TCO of electric trucks is 22% less than that of diesel trucks on the NYCC. For a drive cycle with less frequent stops and high average speed such as the City-Suburban Heavy Vehicle Cycle (CSHVC), electric trucks emit 19-43% less GHGs and consume 5-34% less energy, but cost 1% more than diesel counterparts. Considering current and projected U.S. regional electricity generation mixes, for the baseline case, the energy use and GHG emissions ratios of electric to diesel trucks range from 48 to 82% and 25 to 89%, respectively.

Impact of Spanish electricity mix, over the period 2008–2030, on the Life Cycle energy consumption and GHG emissions of Electric, Hybrid Diesel-Electric, Fuel Cell Hybrid and Diesel Bus of the Madrid Transportation System

In spite of the advanced research in automotive technology, and the improvement of fuels, the road transport sector continues to be an environmental concern, since the increase in transport demand is offsetting the effects of these technological improvements. Therefore, this poses the following question: what combination of technology and fuel is more efficient in terms of energy consumption and green house gas (GHG) emissions? To fully address this question it is necessary to carry out a Life Cycle Assessment (LCA). This paper presents a global LCA of 4 buses that run on the following fuel types and technologies: (1) Fuel Cell- Hybrid Bus, (2) Hybrid Diesel-Electric Bus (series configuration), (3) Battery Electric Bus and (4) Combustion Ignition Engine Bus. The impact categories assessed are: primary energy consumption, fossil energy and GHG emissions. Among the principal results, we can conclude that the Global LCA of buses (3) and (1) (which are the more sensitive pathways to the electricity mix variation) have for the 2008–2030 period a room for improvement of 25.62% and 28.16% in terms of efficiency of fossil energy consumption and a potential GHG emission reduction of 28.70% and 30.88% respectively.

Integration of BIM and Intelligence Algorithm for BLC Energy Consumption Evaluation and Optimization: Principles and Framework

Because of the emergence and development of life-cycle assessment (LCA) theory, the concept of building energy efficiency has been re-evaluated. In this paper, leveraged on the advantages and features of BIM and swarm intelligence algorithms, a methodology for the assessment and optimization of BLCEC is proposed to combine the advantage of both paradigms. Based on existing research in optimization algorithms for BLCEC, the key points of framework in this paper are as follows: (1) the principle and approach of N-dimensional model for Building Life Cycle Energy Consumption (BLCEC) evaluation, and (2) the principle and approach of integrating of BIM and swarm intelligence algorithms.

Development of electric vehicles use in China: A study from the perspective of life-cycle energy consumption and greenhouse gas emissions

China has promoted the use of electric vehicles vigorously since 2009; the program is still in its pilot phase. This study investigates the development of electric vehicle use in China from the perspectives of energy consumption and greenhouse-gas (GHG) emissions. Energy consumption and GHG emissions of plug-in hybrid electric vehicles (PHEVs) and pure battery electric vehicles (BEVs) are examined on the level of the regional power grid in 2009 through comparison with the energy consumption and GHG emissions of conventional gasoline internal combustion engine vehicles. The life-cycle analysis module in Tsinghua-LCAM, which is based on the GREET platform, is adopted and adapted to the life-cycle analysis of automotive energy pathways in China. Moreover, medium term (2015) and long term (2020) energy consumption and greenhouse-gas emissions of PHEVs and BEVs are projected, in accordance with the expected development target in the Energy Efficient and Alternative Energy Vehicles Industry Development Plan (2012–2020) for China. Finally, policy recommendations are provided for the proper development of electric vehicle use in China.

Sustainable construction: life cycle energy analysis of construction on sloping sites for residential buildings

In 2010, the Australian residential construction sector contributed about 28% of the value of all construction and was responsible for 8% of the total energy consumption. Residential construction will continue to increase to cope with the demand due to population growth. Owing to land scarcity, construction on sloping sites has become a common construction method for residential development in Australia. This method has economic benefits but poses environmental issues as it damages topsoil, disturbs natural drainage and groundwater pathways and imposes additional stress on soil under fill. The life cycle energy consumption of the construction process is examined in relation to residential projects on sloping sites on a range of slopes and soil types in New South Wales, Australia. Forty-one detached dwellings were selected and a service life of 60 years assumed for the study. The research findings reveal that the slope for each type of soil has a positive correlation with life cycle energy consumption. As part of the onsite construction process, the results also show that the energy consumption of construction on sloping sites plays a significant factor in the life cycle energy analysis of a building.

Timber and Chinese Architecture

Timber, a traditional construction material that was almost forgotten. Timber structure building got a qualitative leap in structure form, mechanized producing craftmanship and matching products, along with social progress and technology improvement. This paper will summarize modern timber structure forms by comparison with popular constructional material, like concrete and steel, in five aspects including life-cycle energy consumption, structure form, construction cost, construction period, seismic performance. Timber's advantages and disadvantages in architectural design will be listed, which may provide theoretical basis for diversified choice of construction materials in architectural design.