Transient and spatial modeling and simulation of polybrominated diphenyl ethers reaction and transport in air, water and soil

The release of the wastes containing polybrominated diphenyl ethers into the environment is a worldwide major concern. Investigation of spatial and temporal variations of polybrominated diphenyl ethers concentrations due to different factors, especially the transport of these species between air and water as well as between air and soil is the purpose of present research. A model was developed and solved using the methods of finite difference and lines. Simulations were implemented for three dimensions of width, length, and height and also time for the air compartment, whereas for the soil and water compartments, variations were considered only with respect to height and time. Transport between water and soil was disregarded for simplicity at this stage. Vancouver’s landfill was considered as a case study. Lower concentrations in air and higher concentrations in water at the interface show that these pollutants tend to diffuse from air to water. Concentrations of all four pollutants decrease near the interface in soil as time passes, but they are predicted to be almost constant at other levels.     

Sedimentologic attributes of the Proterozoic siliciclastic packages of the Garhwal–Kumaun Lesser Himalaya,India: Implication for their relationship and palaeobasinal conditions

The present work addresses the long-standing issues on the characterization aspect of the Proterozoic siliciclastic successions exposed in the central part of the Lesser Himalaya, restricted between the Main Boundary Thrust (MBT) and the Main Central Thrust (MCT). Geologic, sedimentologic, and petrographic study divides the Lesser Himalaya in two zones- northern Palaeo- Mesoproterozoic Inner Lesser Himalayan (ILH) and southern Neoproterozoic Outer Lesser Himalayan (OLH) zones. The major lithofacies recognized from the zones are - (i) coarse grained siliciclastic (CGS), (ii) interbedded medium and fine-grained siliciclastic (IMFS), (iii) argillite (ARG), and (iv) siliciclastic–argillite rhythmites (SAR). Amongst all these facies, the nearshore IMFS facies shows consistent presence in both OLH and ILH zones. From the facies distribution pattern, a northwest–southeasterly trending palaeo- shoreline has been envisaged. The CGS facies in the ILH hints towards an alluvial fan setting during 1.8 Ga rifting phase associated with penecontemporaneous basic magmatism. Compositionally, the siliciclastics of both the zones (ILH and OLH) are arenite and wacke types with minimal variation in their detrital proportions, derived from the early Proterozoic (between 2.4-1.6Ga) Aravalli-Delhi Supergroup provenance. Nearly matching types and content of detrital modes and the lithofacies pattern of the ILH and OLH siliciclastics probably conclude the derivation from the rising (nearby) Aravalli-Delhi orogen and deposition in a foreland like situation.     

Implementing landslide path dependency in landslide susceptibility modelling

Landslide susceptibility modelling—a crucial step towards the assessment of landslide hazard and risk—has hitherto not included the local, transient effects of previous landslides on susceptibility. In this contribution, we implement such transient effects, which we term “landslide path dependency”, for the first time. Two landslide path dependency variables are used to characterise transient effects: a variable reflecting how likely it is that an earlier landslide will have a follow-up landslide and a variable reflecting the decay of transient effects over time. These two landslide path dependency variables are considered in addition to a large set of conditioning attributes conventionally used in landslide susceptibility. Three logistic regression models were trained and tested fitted to landslide occurrence data from a multi-temporal landslide inventory: (1) a model with only conventional variables, (2) a model with conventional plus landslide path dependency variables, and (3) a model with only landslide path dependency variables. We compare the model performances, differences in the number, coefficient and significance of the selected variables, and the differences in the resulting susceptibility maps. Although the landslide path dependency variables are highly significant and have impacts on the importance of other variables, the performance of the models and the susceptibility maps do not substantially differ between conventional and conventional plus path dependent models. The path dependent landslide susceptibility model, with only two explanatory variables, has lower model performance, and differently patterned susceptibility map than the two other models. A simple landslide susceptibility model using only DEM-derived variables and landslide path dependency variables performs better than the path dependent landslide susceptibility model, and almost as well as the model with conventional plus landslide path dependency variables—while avoiding the need for hard-to-measure variables such as land use or lithology. Although the predictive power of landslide path dependency variables is lower than those of the most important conventional variables, our findings provide a clear incentive to further explore landslide path dependency effects and their potential role in landslide susceptibility modelling.     

Land use change assessment in coastal mangrove forests of Iran utilizing satellite imagery and CA–Markov algorithms to monitor and predict future change

Mangrove forest stores large organic carbon stocks in a setting that is highly vulnerable to climate change and direct anthropogenic influences. As such there is a need to elucidate the causes and consequences of land use change on these ecosystems that have high value in terms of ecosystem services. We examine the areal pattern of land types in a coastal region located in southern Iran over a period of 14 years to predict future loss and gain in land types to the year 2025. We applied a CA–Markov model to simulate and predict mangrove forest change. Landsat satellite images from 2000 to 2014 were used to analyze the land cover changes between soil, open water and mangroves. Major changes during this period were observed in soil and water which could be attributed to rising sea level. Furthermore, the mangrove area in the more seaward position was converted to open water due to sea-level rise. A cellular automata model was then used to predict the land cover changes that would occur by the year 2025. Results demonstrated that approximately 21 ha of mangrove area will be converted to open water, while mangroves are projected to expand by approximately 28 ha in landward direction. These changes need to be delineated to better inform precise mitigation and adaptation measures.     

Synthesis of biochar from sugarcane filter-cake and its impacts on physiological performance of lettuce (<Emphasis Type="Italic">Lettuce sativa</Emphasis>) grown on cadmium contaminated soil

Soil contamination with cadmium has become major concern all over the world because of its adverse impacts on ecosystem health and agricultural land. Soil amendment with biochar may have varied effects on physical and chemical properties of soil. The objective of the study was to explore the impact of sugarcane filter-cake biochar on physiological performance and growth of lettuce in an aged soil. Four different doses (0, 1.5%, 3%, and 5%) of biochar were used in the soil and conditioned for 1 month. After this, lettuce seedlings were grown in the soil. The results showed that the biochar treatment improved the fresh and dry biomass of leaves and roots as well as plant height while diminished the bioavailability of cadmium from the soil. As compared to control, biochar significantly enhanced the chlorophyll content in lettuce leaves. Due to the biochar amendment, the oxidative stress decreased in lettuce shoots over the control. As compared to control, concentration of cadmium in lettuce significantly decreased after the application of biochar. It was concluded that biochar could mitigate the toxicity of cadmium in lettuce by altering the biochemical and physiological processes in cadmium contaminated soil.     

Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory

Landslides are a major category of natural disasters, causing loss of lives, livelihoods and property. The critical roles played by triggering (such as extreme rainfall and earthquakes), and intrinsic factors (such as slope steepness, soil properties and lithology) have previously successfully been recognized and quantified using a variety of qualitative, quantitative and hybrid methods in a wide range of study sites. However, available data typically do not allow to investigate the effect that earlier landslides have on intrinsic factors and hence on follow-up landslides. Therefore, existing methods cannot account for the potentially complex susceptibility changes caused by landslide events. In this study, we used a substantially different alternative approach to shed light on the potential effect of earlier landslides using a multi-temporal dataset of landslide occurrence containing 17 time slices. Spatial overlap and the time interval between landslides play key roles in our work. We quantified the degree to which landslides preferentially occur in locations where landslides occurred previously, how long such an effect is noticeable, and how landslides are spatially associated over time. We also investigated whether overlap with previous landslides causes differences in landslide geometric properties. We found that overlap among landslides demonstrates a clear legacy effect (path dependency) that has influence on the landslide affected area. Landslides appear to cause greater susceptibility for follow-up landslides over a period of about 10  years. Follow-up landslides are on average larger and rounder than landslides that do not follow earlier slides. The effect of earlier landslides on follow-up landslides has implications for understanding of the landslides evolution and the assessment of landslide susceptibility.     

Modified consecutive modal pushover procedure for seismic investigation of one-way asymmetric-plan tall buildings

The effects of higher modes and torsion have a significant impact on the seismic responses of asymmetric-plan tall buildings.A consecutive modal pushover(CMP) procedure is one of the pushover methods that have been developed to consider these effects.The aim of this paper is to modify the(CMP) analysis procedure to estimate the seismic demands of one-way asymmetric-plan tall buildings with dual systems.An analysis of 10-,15-and 20-story asymmetric-plan buildings is carried out,and the results from the modified consecutive modal pushover(MCMP) procedure are compared with those obtained from the modal pushover analysis(MPA) procedure and the nonlinear time history analysis(NLTHA).The MCMP estimates of the seismic demands of one-way asymmetric-plan buildings demonstrate a reasonable accuracy,compared to the results obtained from the NLTHA.Furthermore,the accuracy of the MCMP procedure in the prediction of plastic hinge rotations is better than the MPA procedure.The new pushover procedure is also more accurate than the FEMA load distribution and the MPA procedure.     

Estimating the Shapes of Gravity Sources through Optimized Support Vector Classifier (SVC)

In gravity interpretation methods, an initial guess for the approximate shape of the gravity source is necessary. In this paper, the support vector classifier (SVC) is applied for this duty by using gravity data. It is shown that using SVC leads us to estimate the approximate shapes of gravity sources more objectively. The procedure of selecting correct features is called feature selection (FS).In this research, the proper features are selected using inter/intra class distance algorithm and also FS is optimized by increasing and decreasing the number of dimensions of features space. Then, by using the proper features, SVC is used to estimate approximate shapes of sources from the six possible shapes, including: sphere, horizontal cylinder, vertical cylinder, rectangular prism, syncline, and anticline. SVC is trained using 300 synthetic gravity profiles and tested by 60 other synthetic and some real gravity profiles (related to a well and two ore bodies), and shapes of their sources estimated properly.