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Regionalized environmental impacts of construction machinery
Get PDFPURPOSE: This study aims to establish a regionalized environmental impact assessment of construction machinery equipped with diesel engines certified by the European emission standard Stage V, and operated in cold climatic zones in Europe. METHOD: The study quantifies potential environmental impacts associated with construction machinery over the entire lifecycle, from extraction of materials to the end-of-life. For the operation phase, a meso-level emission accounting method is applied to quantify tailpipe emissions for certain subcategories of construction machinery. This is achieved by determining the operational efficiency of each machine in terms of effective hours. The quantified emission data are then adjusted based on engine deterioration models to estimate the rate of increase in emissions throughout the lifetime of each machine. Finally, the CML impact assessment method is applied to inventory data to quantify potential environmental impacts. RESULTS: The study shows that tailpipe emissions, which largely depend on an engine’s fuel consumption, had the largest contribution to environmental impacts in most impact categories. At the same time, there was a positive correlation between the operation weight and the impacts of the machinery. Also, machinery with similar operation weight had relatively similar impact patterns due to similar driving factors and dependencies. In addition, network, sensitivity, and uncertainty analyses were performed to quantify the source of impacts and validate the robustness of the study. Results of the sensitivity analysis showed that the responsiveness of the studied systems is very sensitive to changes in the amount of fuel consumption. In addition, the uncertainty results showed that the domain of uncertainty increased as the operation weight subcategory of machinery increased. CONCLUSION: This study extends previous work on the life cycle assessment (LCA) of construction machinery, and the methodology developed provides a basis for future extension and improvement in this field. The use of effective hours as the unit of operational efficiency helps to resolve uncertainties linked to lifetime and annual operation hours. Also, the obtained results can be of use for decision support and for assessing the impacts of transition from fossil fuels to alternative fuel types.publishedVersio
Impact of late spring Siberian snow on summer rainfall in South-Central China
Get PDFLocated in the Yangtze River Valley and surrounded by mountains, South-Central China (SCC) frequently suffered from natural disasters such as torrential precipitation, landslide and debris flow. Here we provide corroborative evidence for a link between the late spring (May) snow water equivalent (SWE) over Siberia and the summer (July–August, abbr. JA) rainfall in SCC. We show that, in May, anomalously low SWE over Siberia is robustly related to a large warming from the surface to the mid-troposphere, and to a stationary Rossby wave train from Siberia eastward toward the North Atlantic. On the one hand, over the North Atlantic there exhibits a tripole pattern response of sea surface temperature anomalies in May. It persists to some extent in JA and in turn triggers a wave train propagating downstream across Eurasia and along the Asian jet, as the so-called Silk Road pattern (SRP). On the other hand, over northern Siberia the drier soil occurs in JA, accompanied by an overlying anomalous anticyclone through the positive feedback. This anomalous anticyclone favors the tropospheric cooling over southern Siberia, and the meridional (northward) displacement of the Asian jet (JMD) due to the change in the meridional temperature gradient. The combination of the SRP and the JMD facilitates less water vapor transport from the tropical oceans and anomalous descending motion over SCC, and thus suppresses the precipitation. These findings indicate that May Siberian SWE can be exploited for seasonal predictability of SCC precipitation.acceptedVersio
Can statistics of turbulent tracer dispersion be inferred from camera observations of SO2 in the ultraviolet? A modelling study.
Get PDFAtmospheric turbulence and in particular its effect on tracer dispersion may be measured by cameras sensitive to the absorption of ultraviolet (UV) sunlight by sulfur dioxide (SO2), a gas that can be considered a passive tracer over short transport distances. We present a method to simulate UV camera measurements of SO2 with a 3D Monte Carlo radiative transfer model which takes input from a large eddy simulation (LES) of a SO2 plume released from a point source. From the simulated images the apparent absorbance and various plume density statistics (centre-line position, meandering, absolute and relative dispersion, and skewness) were calculated. These were compared with corresponding quantities obtained directly from the LES. Mean differences of centre-line position, absolute and relative dispersions, and skewness between the simulated images and the LES were generally found to be smaller than or about the voxel resolution of the LES. Furthermore, sensitivity studies were made to quantify how changes in solar azimuth and zenith angles, aerosol loading (background and in plume), and surface albedo impact the UV camera image plume statistics. Changing the values of these parameters within realistic limits has negligible effects on the centre-line position, meandering, absolute and relative dispersions, and skewness of the SO2 plume. Thus, we demonstrate that UV camera images of SO2 plumes may be used to derive plume statistics of relevance for the study of atmospheric turbulent dispersion.publishedVersio
Arctic sea-ice loss intensifies aerosol transport to the Tibetan Plateau
No full textThe Tibetan Plateau (TP) has recently been polluted by anthropogenic emissions transported from South Asia, but the mechanisms conducive to this aerosol delivery are poorly understood. Here we show that winter loss of Arctic sea ice over the subpolar North Atlantic boosts aerosol transport toward the TP in April, when the aerosol loading is at its climatological maximum and preceding the Indian summer monsoon onset. Low sea ice in February weakens the polar jet, causing decreased Ural snowpack via reduced transport of warm, moist oceanic air into the high-latitude Eurasian interior. This diminished snowpack persists through April, reinforcing the Ural pressure ridge and East Asian trough, segments of a quasi-stationary Rossby wave train extending across Eurasia. These conditions facilitate an enhanced subtropical westerly jet at the southern edge of the TP, invigorating upslope winds that combine with mesoscale updrafts to waft emissions over the Himalayas onto the TP.acceptedVersio
Safe(r) by design implementation in the nanotechnology industry
No full textThe implementation of Safe(r) by Design (SbD) in industrial innovations requires an integrated approach where the human, environmental and economic impact of the SbD measures is evaluated across and throughout the nanomaterial (NM) life cycle. SbD was implemented in six industrial companies where SbD measures were applied to NMs, nano-enabled products (NEPs) and NM/NEP manufacturing processes.
The approach considers human and environmental risks, functionality of the NM/NEP and costs as early as possible in the innovation process, continuing throughout the innovation progresses. Based on the results of the evaluation, a decision has to be made on whether to continue, stop or re-design the NM/NEP/process or to carry out further tests/obtain further data in cases where the uncertainty of the human and environmental risks is too large. However, SbD can also be implemented at later stages when there is already a prototype product or process available, as demonstrated in some of the cases.
The SbD measures implemented in some of the case studies did not result in a viable solution. For example the coating of silicon nanoparticles with amorphous carbon increased the conductivity, the stability and reduced the dustiness of the particles and therefore the risk of explosion and the exposure to workers. However the socioeconomic assessment for their use in lithium-ion batteries for cars, when compared to the use of graphite, showed that the increase in performance did not overcome the higher production costs.
This work illustrates the complexities of selecting the most appropriate SbD measures and highlights that SbD cannot be solely based on a hazard and exposure assessment but must include other impacts that any SbD measures may have on sustainability including energy consumption and waste generation as well as all associated monetary costs.acceptedVersio
Concentration Fluctuations from Localized Atmospheric Releases
Get PDFWe review the efforts made by the scientific community in more than seventy years to elucidate the behaviour of concentration fluctuations arising from localized atmospheric releases of dynamically passive and non-reactive scalars. Concentration fluctuations are relevant in many fields including the evaluation of toxicity, flammability, and odour nuisance. Characterizing concentration fluctuations requires not just the mean concentration but also at least the variance of the concentration in the location of interest. However, for most purposes the characterization of the concentration fluctuations requires knowledge of the concentration probability density function (PDF) in the point of interest and even the time evolution of the concentration. We firstly review the experimental works made both in the field and in the laboratory, and cover both point sources and line sources. Regarding modelling approaches, we cover analytical, semi-analytical, and numerical methods. For clarity of presentation we subdivide the models in two groups, models linked to a transport equation, which usually require a numerical resolution, and models mainly based on phenomenological aspects of dispersion, often providing analytical or semi-analytical relations. The former group includes: large-eddy simulations, Reynolds-averaged Navier–Stokes methods, two-particle Lagrangian stochastic models, PDF transport equation methods, and heuristic Lagrangian single-particle methods. The latter group includes: fluctuating plume models, semi-empirical models for the concentration moments, analytical models for the concentration PDF, and concentration time-series models. We close the review with a brief discussion highlighting possible useful additions to experiments and improvements to models.publishedVersio
Mot bedre utnyttelse av satellittdata for overvåkning av luftkvalitet i Norge ved hjelp av nedskaleringsteknikker (SAT4AQN)
Get PDFThe main goal for the “Towards better exploitation of Satellite data for monitoring Air Quality in Norway using downscaling techniques” (Sat4AQN) project was to evaluate the potential of spatially downscaling satellite data using a high-resolution Chemical Transport Model (CTM) to spatial scales that are more relevant for monitoring air quality in urban areas and regional background sites in Norway. For this demonstration project, we focused on satellite aerosol optical density (AOD) and particulate matter (PM) estimates.Hovedmålet for prosjektet "Mot bedre utnyttelse av satellittdata for overvåking av luftkvalitet i Norge ved hjelp av nedskaleringsteknikker" (Sat4AQN) var å evaluere potensialet for romlig nedskalering av eksisterende satellittprodukter med støtte fra en høyoppløselig kjemisk transportmodell (CTM) til romlige skalaer som er mer relevante for å overvåke luftkvaliteten i urbane områder og regionale bakgrunnssteder i Norge. For dette demonstrasjonsprosjektet fokuserte vi på satellitt-aerosol-optisk tykkelse (AOD) og svevestøv (PM) estimater.publishedVersio
Homology modeling to screen for potential binding of contaminants to thyroid hormone receptor and transthyretin in glaucous gull (Larus hyperboreus) and herring gull (Larus argentatus)
Get PDFThyroid hormone disrupting chemicals (THDCs) are of major concern in ecotoxicology. With the increased number of emerging chemicals on the market there is a need to screen for potential THDCs in a cost-efficient way, and in silico modeling is an alternative to address this issue. In this study homology modeling and docking was used to screen a list of 626 compounds for potential thyroid hormone disrupting properties in two gull species. The tested compounds were known contaminants or emerging contaminants predicted to have the potential to reach the Arctic. Models of transthyretin (TTR) and thyroid hormone receptor α and β (TRα and TRβ) from the Arctic top predator glaucous gull (Larus hyperboreus) and temperate predator herring gull (Larus argentatus) were constructed and used to predict the binding affinity of the compounds to the thyroid hormone (TH) binding sites. The modeling predicted that 28, 4 and 330 of the contaminants would bind to TRα, TRβ and TTR respectively. These compounds were in general halogenated, aromatic and had polar functional groups, like that of THs. However, the predicted binders did not necessarily have all these properties, such as the per- and polyfluoroalkyl substances that are not aromatic and still bind to the proteins.publishedVersio