Winter road maintenance in the Nordic climate is demanding due to challenging weather conditions, high precipitation, and icy conditions. As a leading country in the transition to low-emission transport, Norway must work to reduce their emissions while providing a safe level of service through winter maintenance operations. This article investigates the environmental impacts of winter road maintenance (WRM) in Norway both today and under a climate change scenario predicted for 2050.
MethodsLife cycle assessment (LCA) is used to evaluate the environmental impact of the functional unit “average winter road maintenance in Norway on national and county roads per km.lane.” The ReCiPe (hierarchy) method was used to identify and categorize emissions related to WRM to show how different factors affect the system and to reveal hidden emissions hotspots. Real-time data from WRM vehicles were used to determine how fuel consumption is affected by gradient and weather. Producers and operators provided other relevant information on WRM vehicles. Official reports supplied information on deicer quantities used and the total distance driven by WRM vehicles in Norway.
Results and discussionThe quantity of deicer used is the main source of emissions contributing toward all impact categories. The effect of deicer is likely to be even higher in certain impact categories. The environmental impact of the deicer after application is not included. The representation of WRM in existing emissions data is limited despite the considerable amount of deicer applied and the long distances that WRM vehicles travel. The results document how energy use throughout the system is another important source of emissions. Various parameters, such as road gradient, vehicle properties, driver behavior, and weather, affect the fuel consumption of WRM vehicles, with weather being the most important of these.
ConclusionsSignificant potential for emissions reductions from WRM was found, and WRM operations should be included in cold-climate road LCA studies. The environmental impacts of deicer application are especially high compared to the mechanical clearing of roads and contribute strongly to impact categories such as terrestrial, freshwater, and human toxicity and to the formation of particulate matter.
相似文献Purpose
The main goal of this study is to provide a thorough environmental sustainability analysis of the construction, traffic, and maintenance of a 45.6-km section of the ‘Manu Road’, an unpaved tropical road that is currently being built in the vicinity of Manu National Park, in the region of Madre de Dios, Peru.Methods
Life cycle assessment (LCA) using a set of 18 different impact categories was selected to conduct the environmental analysis. Modelling of machinery and vehicle emissions, as well as dust emissions, was performed to account for site-specific characteristics in terms of road construction and traffic. Similarly, direct land use changes were modelled with a particular emphasis on the decay of deforested biomass during construction. A set of different scenarios for the production system were considered to account for uncertainty regarding vehicle transit, amount of deforested biomass, and emission standards.Results and discussion
Construction, maintenance, and traffic of the Manu Road varied considerably depending on methodological assumptions. Deforestation due to direct land use changes appears to be the main environmental hotspot in terms of climate change, whereas in the remaining impact categories, traffic was the main carrier of environmental burdens.Conclusions
To the best of our knowledge, this study is the first LCA that focuses on the construction, maintenance, and traffic in a tropical rainforest environment. Despite the low requirements in terms of materials and technology to build this road, its derived environmental impacts are relevant in terms of climate change and particulate matter formation due to deforestation and dust emissions, respectively. Unpaved roads represent a relevant proportion of the entire road network worldwide, especially in developing tropical countries, playing a crucial role in the transportation of raw materials. Furthermore, road infrastructure is expected to expand explosively in the decades to come. Therefore, we suggest that LCA studies can and should improve the planning of road infrastructure in terms of life cycle inventories.Several models are available in the literature to estimate agricultural emissions. From life cycle assessment (LCA) perspective, there is no standardized procedure for estimating emissions of nitrogen or other nutrients. This article aims to compare four agricultural models (PEF, SALCA, Daisy and Animo) with different complexity levels and test their suitability and sensitivity in LCA.
MethodsRequired input data, obtained outputs, and main characteristics of the models are presented. Then, the performance of the models was evaluated according to their potential feasibility to be used in estimating nitrogen emissions in LCA using an adapted version of the criteria proposed by the United Nations Framework Convention on Climate Change (UNFCCC), and other relevant studies, to judge their suitability in LCA. Finally, nitrogen emissions from a case study of irrigated maize in Spain were estimated using the selected models and were tested in a full LCA to characterize the impacts.
Results and discussionAccording to the set of criteria, the models scored, from best to worst: Daisy (77%), SALCA (74%), Animo (72%) and PEF (70%), being Daisy the most suitable model to LCA framework. Regarding the case study, the estimated emissions agreed to literature data for the irrigated corn crop in Spain and the Mediterranean, except N2O emissions. The impact characterization showed differences of up to 56% for the most relevant impact categories when considering nitrogen emissions. Additionally, an overview of the models used to estimate nitrogen emissions in LCA studies showed that many models have been used, but not always in a suitable or justified manner.
ConclusionsAlthough mechanistic models are more laborious, mainly due to the amount of input data required, this study shows that Daisy could be a suitable model to estimate emissions when fertilizer application is relevant for the environmental study. In addition, and due to LCA urgently needing a solid methodology to estimate nitrogen emissions, mechanistic models such as Daisy could be used to estimate default values for different archetype scenarios.
相似文献0.352 3。结论 广西县级医疗卫生资源配置的公平性较好,其中人口分布优于地理分布,床位分布优于卫生人力资源分布。广西县级医疗卫生资源配置的公平性低于广西总体水平,但优于城区医疗卫生资源的配置。应进一步加大县级医疗卫生资源的投入,不断缩小城乡差距,提高县级医疗卫生资源在人口和地理配置的公平性。 相似文献
The main objective of this paper is to develop a model that will combine economic and environmental assessment tools to support the composite material selection of aircraft structures in the early phases of design and application of the tool for an aircraft elevator.
MethodsAn integrated life cycle cost (LCC) and life cycle assessment (LCA) methodology was used as part of the sustainable design approach for the laminate stacking sequence design. The model considered is the aircraft structure made of carbon fiber reinforce plastic prepreg and processed via hand layup-autoclave process which is the preferred method for the aircraft industry. The model was applied to a cargo aircraft elevator case study by comparing six different laminate configurations and two different carbon fiber prepreg materials across aircraft’s entire life cycle.
Results and discussionThe results show, in line with other studies using different methodologies (e.g., life cycle engineering, or LCE), that the combination of LCA with LCC is a worthwhile approach for comparing the different laminate configurations in terms of cost and environmental impact to support composite laminate stacking design by providing the best trade-off between cost and environment. Elevator LCC reduces 19% by changing the material type and applying different ply orientations. Elevator LCA score reduces 53% by selecting the optimum instead of best technical solution that minimizes the displacement. Improving the structural performance does not always lead to an increase in the cost.
相似文献California’s Central Valley produces more than 75% of global commercial almond supply, making the life cycle performance of almond production in California of global interest. This article describes the life cycle assessment of California almond production using a Scalable, Process-based, Agronomically Responsive Cropping System Life Cycle Assessment (SPARCS-LCA) model that includes crop responses to orchard management and modeling of California’s water supply and biomass energy infrastructure.
MethodsA spatially and temporally resolved LCA model was developed to reflect the regional climate, resource, and agronomic conditions across California’s Central Valley by hydrologic subregion (San Joaquin Valley, Sacramento Valley, and Tulare Lake regions). The model couples a LCA framework with region-specific data, including water supply infrastructure and economics, crop productivity response models, and dynamic co-product markets, to characterize the environmental performance of California almonds. Previous LCAs of California almond found that irrigation and management of co-products were most influential in determining life cycle CO2eq emissions and energy intensity of California almond production, and both have experienced extensive changes since previous studies due to drought and changing regulatory conditions, making them a focus of sensitivity and scenario analysis.
Results and discussionResults using economic allocation show that 1 kg of hulled, brown-skin almond kernel at post-harvest facility gate causes 1.92 kg CO2eq (GWP100), 50.9 MJ energy use, and 4820 L freshwater use, with regional ranges of 2.0–2.69 kg CO2eq, 42.7–59.4 MJ, and 4540–5150 L, respectively. With a substitution approach for co-product allocation, 1 kg almond kernel results in 1.23 kg CO2eq, 18.05 MJ energy use, and 4804 L freshwater use, with regional ranges of 0.51–1.95 kg CO2eq, 3.68–36.5 MJ, and 4521–5140 L, respectively. Almond freshwater use is comparable with other nut crops in California and globally. Results showed significant variability across subregions. While the San Joaquin Valley performed best in most impact categories, the Tulare Lake region produced the lowest eutrophication impacts.
ConclusionWhile CO2eq and energy intensity of almond production increased over previous estimates, so too did credits to the system for displacement of dairy feed. These changes result from a more comprehensive model scope and improved assumptions, as well as drought-related increases in groundwater depth and associated energy demand, and decreased utilization of biomass residues for energy recovery due to closure of bioenergy plants in California. The variation among different impact categories between subregions and over time highlight the need for spatially and temporally resolved agricultural LCA.
相似文献Fuel economy and emissions of heavy-duty trucks greatly vary based on vehicular/environmental conditions. Large-scale infrastructure construction projects require a large amount of material/equipment transportation. Single-parameter generic hauling models may not be the best option for an accurate estimation of hauling contribution in life cycle assessment (LCA) involving construction projects; therefore, more precise data and parameterized models are required to represent this contribution. This paper discusses key environmental/operational variables and their impact on transportation of materials and equipment; a variable-impact transportation (VIT) model accounting for these variables was developed to predict environmental impacts of hauling.
MethodsThe VIT model in the form of multi-nonlinear regression equations was developed based on simulations using the U.S. Environmental Protection Agency (EPA)’s Motor Vehicle Emission Simulator (MOVES) to compute all the impact categories in EPA’s TRACI 2.1 and energy consumption of transportation. Considering actual driving cycles of hauling trucks recorded during a pavement rehabilitation project, the corresponding environmental impacts were calculated, and sensitivity analyses were performed. In addition, an LCA case study based on historical pavement reconstruction projects in Illinois was conducted to analyze the contribution of transportation and variability of its impacts during the pavements’ life cycle.
Results and discussionThe importance of vehicle driving cycles was realized from simulation results. The case study results showed that considering driving cycles using the VIT model could increase the contribution of hauling in total life cycle Global Warming Potential (GWP) and total life cycle GWP itself by 2–4 and 3–5%, respectively. In addition to GWP, ranges of other hauling-related impact categories including Smog, Ozone Depletion, Acidification, and Primary Energy Demand from fuel were presented based on the case study. Ozone Depletion ranged from 9 to 45%, and Smog ranged from 11 to 48% of the total relevant life cycle impacts. The GWP contribution of hauling in pavement LCA ranged between 5 and 32%. The results indicate that the contribution of hauling transportation can be significant in pavement LCA.
ConclusionsFor large-scale roadway infrastructure construction projects that need a massive amount of material transportation, high fidelity models and data should be used especially for comparative LCAs that can be used as part of decision making between alternatives. The VIT model provides a simple analytical platform to include the critical vehicular/operational variables without any dependence on an external software; the model can also be incorporated in those studies where some of the transportation activity data are available.
相似文献An estimation of the environmental impact of buildings by means of a life cycle assessment (LCA) raises uncertainty related to the parameters that are subject to major changes over longer time spans. The main aim of the present study is to evaluate the influence of modifications in the electricity mix and the production efficiency in the chosen reference year on the embodied impacts (i.e., greenhouse gas (GHG) emissions) of building materials and components and the possible impact of this on future refurbishment measures.
MethodsA new LCA methodological approach was developed and implemented that can have a significant impact on the way in which existing buildings are assessed at the end of their service lives. The electricity mixes of different reference years were collected and assessed, and the main datasets and sub-datasets were modified according to the predefined substitution criteria. The influence of the electricity-mix modification and production efficiency were illustrated on a selected existing reference building, built in 1970. The relative contribution of the electricity mix to the embodied impact of the production phase was calculated for four different electricity mixes, with this comprising the electricity mix from 1970, the current electricity mix and two possible future electricity-mix scenarios for 2050. The residual value of the building was also estimated.
Results and discussionIn the case presented, the relative share of the electricity mix GHG emission towards the total value was as high as 20% for separate building components. If this electricity mix is replaced with an electricity mix having greater environmental emissions, the relative contribution of the electricity mix to the total emissions can be even higher. When, by contrast, the modified electricity mix is almost decarbonized, the relative contribution to the total emissions may well be reduced to a point where it becomes negligible. The modification of the electricity mix can also influence the residual value of a building. In the observed case, the differences due to different electricity mixes were in the range of 10%.
ConclusionsIt was found that those parameters that are subject to a major change during the reference service period of the building should be treated dynamically in order to obtain reliable results. Future research is foreseen to provide additional knowledge concerning the influence of dynamic parameters on both the use phase and the end-of-life phase of buildings, and these findings will also be important when planning future refurbishment measures.
相似文献Background, aim, and scope
According to some recent studies, noise from road transport is estimated to cause human health effects of the same order of magnitude as the sum of all other emissions from the transport life cycle. Thus, ISO 14′040 implies that traffic noise effects should be considered in life cycle assessment (LCA) studies where transports might play an important role. So far, five methods for the inclusion of noise in LCA have been proposed. However, at present, none of them is implemented in any of the major life cycle inventory (LCI) databases and commonly used in LCA studies. The goal of the present paper is to define a requirement profile for a method to include traffic noise in LCA and to assess the compliance of the five existing methods with this profile. It concludes by identifying necessary cornerstones for a model for noise effects of generic road transports that meets all requirements. 相似文献Microalgae biodiesel has attracted considerable attention as a potential substitute for fossil fuels and biodiesel from food crops. Nevertheless, its reported climate impacts in the scientific literature vary significantly. This article describes and synthesizes the range of results found in the life cycle assessment (LCA) literature regarding microalgae biodiesel studies to investigate whether particular parameters, e.g. technologies, were associated with higher or lower greenhouse gas (GHG) emissions so that a best practice can be inferred from currently available LCA data and thereby recommended.
MethodsA systematic literature review and meta-regression analysis (MRA) of 36 LCA studies that report on the GHG emissions of microalgae biodiesel was conducted. An assessment of key aspects, including modelling choices and technologies, was performed. Furthermore, MRA models were formulated considering several variables of interest describing both technical and modelling choices to identify the main causes for the variability in GHG emissions per MJ of biodiesel. Variables chosen include: microalgae species; culture medium; cultivation system; source of CO2; extraction technology; conversion technology; system boundary; geographical scope; inclusion or exclusion of capital goods; and how multifunctionality was handled.
Results and discussionThe reviewed studies altogether reported 308 results ranging from ?0.7 to 3.8 kg CO2 eq. MJ?1biodiesel, portraying 19 different system configurations. Despite the comprehensive range of variables assessed, the models generated could not plausibly explain that the variability in GHG emissions depends either on the technologies considered or on the methodological choices adopted. However, the following relationships could be observed: location in Europe and high oil productivity were associated with lower emissions, whilst dry extraction should be avoided for leading to higher GHG emissions, on average.
ConclusionsThere is a large degree of variability within the technologies considered, as well as the methodological choices adopted, so that no robust conclusions could be drawn from the MRA. Notwithstanding, average GHG emissions reported were more than twice as high as fossil diesel and, while there are some studies showing large benefits, none of the various algae technologies performed consistently better than fossil diesel, questioning the climate-mitigation potential of microalgae biodiesel.
相似文献The majority of LCA studies begin with the drawing of a process flow diagram, which then needs to be translated manually into an LCA model. This study presents an initial image processing pipeline, implemented in an open-source software package, called lcopt-cv, which can be used to identify the boxes and links in a photograph of a hand-drawn process flow diagram and automatically create an LCA foreground model.
MethodsThe computer vision pipeline consists of a total of 15 steps, beginning with loading the image file and conversion to greyscale. The background is equalised, then the foreground of the image is extracted from the background using thresholding. The lines are then dilated and closed to account for drawing errors. Contours in the image are detected and simplified, and rectangles (contours with four corners) are identified from the simplified contours as ‘boxes’. Links between these boxes are identified using a flood-filling technique. Heuristic processing, based on knowledge of common practice in drawing of process flow diagrams, is then performed to more accurately identify the typology of the identified boxes and the direction of the links between them.
Results and discussionThe performance of the image processing pipeline was tested on four flow diagrams of increasing difficulty: one simple computer drawn diagram and three photographs of hand-drawn diagrams (a simple diagram, a complex diagram and a diagram with merged lines). A set of default values for the variables which define the pipeline was developed through trial and error. For the two simple flow charts, all boxes and links were identified using the default settings. The complex diagram required minor tweaks to the default values to detect all boxes and links. An ‘unstacking’ heuristic allowed the diagram with merged lines to be correctly processed. After some manual reclassification of link directions and process types, the diagrams were turned into LCA models and exported to open-source LCA software packages (lcopt and Brightway) to be verified and analysed.
ConclusionsThis study demonstrates that it is possible to generate a fully functional LCA model from a picture of a flow chart. This has potentially important implications not only for LCA practitioners as a whole, but in particular for the teaching of LCA. Skipping the steep learning curve required by most LCA software packages allows teachers to focus on important LCA concepts, while participants maintain the benefits of experiential learning by doing a ‘real’ LCA.
相似文献Changes in the production of Australian cotton lint are expected to have a direct environmental impact, as well as indirect impacts related to co-product substitution and induced changes in crop production. The environmental consequences of a 50% expansion or contraction in production were compared to Australian cotton production’s current environmental footprint. Both were then assessed to investigate whether current impacts are suitable for predicting the environmental impact of a change in demand for cotton lint.
MethodsA consequential life cycle assessment (LCA) model of Australian cotton lint production (cradle-to-gin gate) was developed using plausible scenarios regarding domestic regions and technologies affected by changes in supply, with both expansion (additional cotton) and contraction (less cotton) being modelled. Modelling accounted for direct impacts from cotton production and indirect impacts associated with changes to cotton production, including co-product substitution and changes to related crops at regional and global scales. Impact categories assessed included climate change, fossil energy demand, freshwater consumption, water stress, marine and freshwater eutrophication, land occupation and land-use change.
Results and discussionFor both the expansion and contraction scenarios, the changes to climate change impacts (including iLUC) and water impacts were less than would be assumed from current production as determined using attributional LCA. However, the opposite was true for all other impact categories, indicating trade-offs across the impact categories. Climate change impacts under both scenarios were relatively minor because these were largely offset by iLUC. Similarly, under the contraction scenario, water impacts were dominated by indirect impacts associated with regional crops. A sensitivity analysis showed that the results were sufficiently robust to indicate the quantum of changes that could be expected.
ConclusionsA complex array of changes in technologies, production regions and related crops were required to model the environmental impacts of a gross change in cotton production. Australian cotton lint production provides an example of legislation constraining the direct water impacts of production, leading to a contrast between impacts estimated by attributional and consequential LCA. This model demonstrated that indirect products and processes are important contributors to the environmental impacts of Australian cotton lint.
相似文献This paper presents the implementation of O-LCA by a Brazilian cosmetics manufacturer. The case study was developed within the framework of the road testing of the “Guidance on organizational LCA” of the UNEP/SETAC Life Cycle Initiative. The aim is to illustrate methodological choices and implementation challenges encountered by the company, i.e., related to the broad product portfolio. The study demonstrates that O-LCA allows quantifying and managing environmental impacts throughout global supply chains and for every individual product.
MethodsO-LCA provides the methodological framework for applying LCA to organizations, and a set of application options based on the structure and experience of organizations. The reporting organization is NATURA Brazil in 2013. The 2600 products in the portfolio are modeled in this first exercise of the company through the bestsellers at each of its ten product category groups. A hybrid approach is considered for data collection: top-down approach for modeling corporate activities and bottom-up approach for upstream and downstream life cycle phases. The data sources are NATURA’s recordings, data gathered from suppliers, estimates from mass and energy balances, and life cycle inventory databases. The approach to acquire direct data or use life cycle databases depends on the representativeness of each raw material or packaging.
Results and discussionThe results show that major impacts could be detected during use phase that demands water and energy to use rinse-off products (the use phase of NATURA’s products contributed over 41% to most impact categories), and in the supply chain, and generated during the obtaining of plant origin ingredients and materials for packaging. Overall, the whole NATURA had in 2013 a potential impact on climate change of 1.4 million tonnes of CO2 eq, a natural land transformation of 1.3 million m2, and a fossil depletion of 0.23 million tonnes of oil eq, among other impacts. Apart from the results at the organizational level, individual results for product bestsellers were calculated and are presented here.
ConclusionsThe study confirmed the applicability of the O-LCA model at NATURA, addressed operational issues related to broad product portfolios, considering several dimensions such as data quality and availability, LCA software, and data management. Despite NATURA’s existing practices and previous knowledge in modeling environmental impacts of products and corporate activities, managing the large amount of data involved prove being a complex task. The company identified gaps and opportunities able to guide future method implementation and LCA-based management.
相似文献