Studied the content and distribution of 18 environmental hazardous trace elementsin the lignite, fatty coal, anthracite and its burnt products by combustion simulatingexpriment in the one-dismensinal boiler.The transf...Studied the content and distribution of 18 environmental hazardous trace elementsin the lignite, fatty coal, anthracite and its burnt products by combustion simulatingexpriment in the one-dismensinal boiler.The transformations and concentration of 18 traceelements during different coal combustion were discussed.The results show that there aresome content distribution of 18 hazardous trace elements in every burnt product, but thelaw of concentration and dispersion of every trace element during different coal combustionis very different.Experiment results indicate that the transformation and concentrationof trace elements during coal combustion are related to the element contents and occur-rencesof trace elements in raw coal, but are also affected by some man-made factorssuch as the combustion method of boiler, combustion temperature and atmosphere, thetype of precipitators and so on.展开更多
Landslides are abundant in mountainous regions.They are responsible for substantial damages and losses in those areas.The A1 Highway,which is an important road in Algeria,was sometimes constructed in mountainous and/o...Landslides are abundant in mountainous regions.They are responsible for substantial damages and losses in those areas.The A1 Highway,which is an important road in Algeria,was sometimes constructed in mountainous and/or semi-mountainous areas.Previous studies of landslide susceptibility mapping conducted near this road using statistical and expert methods have yielded ordinary results.In this research,we are interested in how do machine learning techniques help in increasing accuracy of landslide susceptibility maps in the vicinity of the A1 Highway corridor.To do this,an important section at Ain Bouziane(NE,Algeria) is chosen as a case study to evaluate the landslide susceptibility using three different machine learning methods,namely,random forest(RF),support vector machine(SVM),and boosted regression tree(BRT).First,an inventory map and nine input factors were prepared for landslide susceptibility mapping(LSM) analyses.The three models were constructed to find the most susceptible areas to this phenomenon.The results were assessed by calculating the receiver operating characteristic(ROC) curve,the standard error(Std.error),and the confidence interval(CI) at 95%.The RF model reached the highest predictive accuracy(AUC=97.2%) comparatively to the other models.The outcomes of this research proved that the obtained machine learning models had the ability to predict future landslide locations in this important road section.In addition,their application gives an improvement of the accuracy of LSMs near the road corridor.The machine learning models may become an important prediction tool that will identify landslide alleviation actions.展开更多
The current study aimed at evaluating the capabilities of seven advanced machine learning techniques(MLTs),including,Support Vector Machine(SVM),Random Forest(RF),Multivariate Adaptive Regression Spline(MARS),Artifici...The current study aimed at evaluating the capabilities of seven advanced machine learning techniques(MLTs),including,Support Vector Machine(SVM),Random Forest(RF),Multivariate Adaptive Regression Spline(MARS),Artificial Neural Network(ANN),Quadratic Discriminant Analysis(QDA),Linear Discriminant Analysis(LDA),and Naive Bayes(NB),for landslide susceptibility modeling and comparison of their performances.Coupling machine learning algorithms with spatial data types for landslide susceptibility mapping is a vitally important issue.This study was carried out using GIS and R open source software at Abha Basin,Asir Region,Saudi Arabia.First,a total of 243 landslide locations were identified at Abha Basin to prepare the landslide inventory map using different data sources.All the landslide areas were randomly separated into two groups with a ratio of 70%for training and 30%for validating purposes.Twelve landslide-variables were generated for landslide susceptibility modeling,which include altitude,lithology,distance to faults,normalized difference vegetation index(NDVI),landuse/landcover(LULC),distance to roads,slope angle,distance to streams,profile curvature,plan curvature,slope length(LS),and slope-aspect.The area under curve(AUC-ROC)approach has been applied to evaluate,validate,and compare the MLTs performance.The results indicated that AUC values for seven MLTs range from 89.0%for QDA to 95.1%for RF.Our findings showed that the RF(AUC=95.1%)and LDA(AUC=941.7%)have produced the best performances in comparison to other MLTs.The outcome of this study and the landslide susceptibility maps would be useful for environmental protection.展开更多
This study presents a calibration process of three-dimensional particle flow code(PFC3D)simulation of intact and fissured granite samples.First,laboratory stressestrain response from triaxial testing of intact and fis...This study presents a calibration process of three-dimensional particle flow code(PFC3D)simulation of intact and fissured granite samples.First,laboratory stressestrain response from triaxial testing of intact and fissured granite samples is recalled.Then,PFC3D is introduced,with focus on the bonded particle models(BPM).After that,we present previous studies where intact rock is simulated by means of flatjoint approaches,and how improved accuracy was gained with the help of parametric studies.Then,models of the pre-fissured rock specimens were generated,including modeled fissures in the form of“smooth joint”type contacts.Finally,triaxial testing simulations of 1 t 2 and 2 t 3 jointed rock specimens were performed.Results show that both elastic behavior and the peak strength levels are closely matched,without any additional fine tuning of micro-mechanical parameters.Concerning the postfailure behavior,models reproduce the trends of decreasing dilation with increasing confinement and plasticity.However,the dilation values simulated are larger than those observed in practice.This is attributed to the difficulty in modeling some phenomena of fissured rock behaviors,such as rock piece corner crushing with dust production and interactions between newly formed shear bands or axial splitting cracks with pre-existing joints.展开更多
Natural hazards are often studied in isolation.However,there is a great need to examine hazards holistically to better manage the complex of threats found in any region.Many regions of the world have complex hazard la...Natural hazards are often studied in isolation.However,there is a great need to examine hazards holistically to better manage the complex of threats found in any region.Many regions of the world have complex hazard landscapes wherein risk from individual and/or multiple extreme events is omnipresent.Extensive parts of Iran experience a complex array of natural hazards-floods,earthquakes,landslides,forest fires,subsidence,and drought.The effectiveness of risk mitigation is in part a function of whether the complex of hazards can be collectively considered,visualized,and evaluated.This study develops and tests individual and collective multihazard risk maps for floods,landslides,and forest fires to visualize the spatial distribution of risk in Fars Province,southern Iran.To do this,two well-known machine-learning algorithms-SVM and MARS-are used to predict the distribution of these events.Past floods,landslides,and forest fires were surveyed and mapped.The locations of occurrence of these events(individually and collectively) were randomly separated into training(70%) and testing(30%) data sets.The conditioning factors(for floods,landslides,and forest fires) employed to model the risk distributions are aspect,elevation,drainage density,distance from faults,geology,LULC,profile curvature,annual mean rainfall,plan curvature,distance from man-made residential structures,distance from nearest river,distance from nearest road,slope gradient,soil types,mean annual temperature,and TWI.The outputs of the two models were assessed using receiver-operating-characteristic(ROC) curves,true-skill statistics(TSS),and the correlation and deviance values from each models for each hazard.The areas-under-the-curves(AUC) for the MARS model prediction were 76.0%,91.2%,and 90.1% for floods,landslides,and forest fires,respectively.Similarly,the AUCs for the SVM model were 75.5%,89.0%,and 91.5%.The TSS reveals that the MARS model was better able to predict landslide risk,but was less able to predict flood-risk patterns and forest-fire risk.Finally,the combination of flood,forest fire,and landslide risk maps yielded a multi-hazard susceptibility map for the province.The better predictive model indicated that 52.3% of the province was at-risk for at least one of these hazards.This multi-hazard map may yield valuable insight for land-use planning,sustainable development of infrastructure,and also integrated watershed management in Fars Province.展开更多
This investigation assessed the efficacy of 10 widely used machine learning algorithms(MLA)comprising the least absolute shrinkage and selection operator(LASSO),generalized linear model(GLM),stepwise generalized linea...This investigation assessed the efficacy of 10 widely used machine learning algorithms(MLA)comprising the least absolute shrinkage and selection operator(LASSO),generalized linear model(GLM),stepwise generalized linear model(SGLM),elastic net(ENET),partial least square(PLS),ridge regression,support vector machine(SVM),classification and regression trees(CART),bagged CART,and random forest(RF)for gully erosion susceptibility mapping(GESM)in Iran.The location of 462 previously existing gully erosion sites were mapped through widespread field investigations,of which 70%(323)and 30%(139)of observations were arbitrarily divided for algorithm calibration and validation.Twelve controlling factors for gully erosion,namely,soil texture,annual mean rainfall,digital elevation model(DEM),drainage density,slope,lithology,topographic wetness index(TWI),distance from rivers,aspect,distance from roads,plan curvature,and profile curvature were ranked in terms of their importance using each MLA.The MLA were compared using a training dataset for gully erosion and statistical measures such as RMSE(root mean square error),MAE(mean absolute error),and R-squared.Based on the comparisons among MLA,the RF algorithm exhibited the minimum RMSE and MAE and the maximum value of R-squared,and was therefore selected as the best model.The variable importance evaluation using the RF model revealed that distance from rivers had the highest significance in influencing the occurrence of gully erosion whereas plan curvature had the least importance.According to the GESM generated using RF,most of the study area is predicted to have a low(53.72%)or moderate(29.65%)susceptibility to gully erosion,whereas only a small area is identified to have a high(12.56%)or very high(4.07%)susceptibility.The outcome generated by RF model is validated using the ROC(Receiver Operating Characteristics)curve approach,which returned an area under the curve(AUC)of 0.985,proving the excellent forecasting ability of the model.The GESM prepared using the RF algorithm can aid decision-makers in targeting remedial actions for minimizing the damage caused by gully erosion.展开更多
Landslides influence the capacity for safe and sustainable development of mountainous environments.This study explores the spatial distribution of and the interactions between landslides that are mapped using global p...Landslides influence the capacity for safe and sustainable development of mountainous environments.This study explores the spatial distribution of and the interactions between landslides that are mapped using global positioning system(GPS) and extensive field surveys in Mazandaran Province,Iran.Point-pattern assessment is undertaken using several univariate summary statistical functions,including pair correlation,spherical-contact distribution,nearest-neighbor analysis,and O-ring analysis,as well as bivariate summary statistics,and a markcorrelation function.The maximum entropy method was applied to prioritize the factors controlling the incidence of landslides and the landslides susceptibility map.The validation processes were considered for separated 30%data applying the ROC curves,fourfold plot,and Cohen’s kappa index.The results show that pair correlation and O-ring analyses satisfactorily predicted landslides at scales from 1 to 150 m.At smaller scales,from 150 to 400 m,landslides were randomly distributed.The nearest-neighbor distribution function show that the highest distance to the nearest landslide occurred in the 355 m.The spherical-contact distribution revealed that the patterns were random up to a spatial scale of 80 m.The bivariate correlation functions revealed that landslides were positively linked to several linear features(including faults,roads,and rivers) at all spatial scales.The mark-correlation function showed that aggregated fields of landslides were positively correlated with measures of land use,lithology,drainage density,plan curvature,and aspect,when the numbers of landslides in the groups were greater than the overall average aggregation.The results of analysis of factor importance have showed that elevation(topography map scale:1:25,000),distance to roads,and distance to rivers are the most important factors in the occurrence of landslides.The susceptibility model of landslides indicates an excellent accuracy,i.e.,the AUC value of landslides was 0.860.The susceptibility map of landslides analyzed has shown that 35% of the area is low susceptible to landslides.展开更多
This study investigates the tensile failure mechanisms in granitic rock samples at different scales by means of different types of tests.To do that,we have selected a granitic rock type and obtained samples of differe...This study investigates the tensile failure mechanisms in granitic rock samples at different scales by means of different types of tests.To do that,we have selected a granitic rock type and obtained samples of different sizes with the diameter ranging from 30 mm to 84 mm.The samples have been subjected to direct tensile strength(DTS)tests,indirect Brazilian tensile strength(BTS)tests and to two fracture toughness testing approaches.Whereas DTS and fracture toughness were found to consistently grow with sample size,this trend was not clearly identified for BTS,where after an initial grow,a plateau of results was observed.This is a rather complete database of tensile related properties of a single rock type.Even if similar databases are rare,the obtained trends are generally consistent with previous scatter and partial experimental programs.However,different observations apply to different types of rocks and experimental approaches.The differences in variability and mean values of the measured parameters at different scales are critically analysed based on the heterogeneity,granular structure and fracture mechanics approaches.Some potential relations between parameters are revised and an indication is given on potential sample sizes for obtaining reliable results.Extending this database with different types of rocks is thought to be convenient to advance towards a better understanding of the tensile strength of rock materials.展开更多
The possibility of creating zero CO2 emissions residential buildings due to life cycle energy use in the island of Crete, Greece has been examined. In a typical residential building located in Crete, Greece, its annua...The possibility of creating zero CO2 emissions residential buildings due to life cycle energy use in the island of Crete, Greece has been examined. In a typical residential building located in Crete, Greece, its annual operating energy has been appraised at 170 KWh/m2 and its embodied energy at 30 KWh/m2. Various locally available renewable energies including solar energy, solid biomass and low enthalpy geothermal energy with heat pumps have been considered for generating the required heat and offsetting the grid electricity used. Their technologies are mature, reliable and cost-effective. Offset of the annual grid electricity use in the building with solar-PV electricity is allowed according to the net metering regulation. For zero carbon emissions due to embodied energy of the building, generation of additional solar electricity injected into the grid is required. A mathematical model has been developed for sizing the required solar-PV system installed in the building in order to offset the grid electricity use. For a residential building in Crete, Greece with a covered area of 100 m2, the power of the additional solar-PV system has been estimated at 1.6 KWp and its cost at 2400 €. In the current work, it is indicated that the creation of a zero CO2 emissions residential building due to life cycle energy use in Crete, Greece does not have major difficulties and it could be achieved relatively easily.展开更多
A description and assessment of a small renewable energy community located in Crete, Greece is presented. The community included private residential and agricultural activities without any involvement of the public se...A description and assessment of a small renewable energy community located in Crete, Greece is presented. The community included private residential and agricultural activities without any involvement of the public sector. Small-scale decentralized energy systems were used. Solar energy and solid biomass which are locally available covered most of the heat and electricity requirements in the community. Renewable energy technologies used include solar thermal energy, solar-PV and solid biomass burning utilizing olive tree wood and olive kernel wood. These technologies are mature, reliable, well proven in Crete and cost-effective. Existing energy systems were generating 857,877 kWh per year covering 94.46% of the current energy requirements in the community, significantly reducing its emissions at 278,494 kg CO2 per year. The addition of a new solar-PV system with nominal power of 33.6 kWp could cover all the remaining electricity needs in the community, transforming it to a zero-CO2 emission community due to energy use. The total installation cost of the existing renewable energy systems in the community was estimated at 0.16€ per total kWh of thermal and electric energy generated annually and at 0.50€ per ton of CO2 emissions saved annually. Results indicated that the creation of the above-mentioned small local energy community is economically viable, environmental friendly and socially accepted. Therefore it could be replicated in other territories with similar availability of renewable energies, increasing their energy autonomy and sustainability.展开更多
Over recent years, the population of Caspian cobra Naja oxiana has declined in its distribution range in Iran due to habitat destruction and overhunting. Consequently, their small and isolated populations in fragmente...Over recent years, the population of Caspian cobra Naja oxiana has declined in its distribution range in Iran due to habitat destruction and overhunting. Consequently, their small and isolated populations in fragmented landscapes are facing genetic and demographic threats. Evaluating the spatial distribution pattern of Naja oxiana, identifying core habitat patches and improving landscape connectivity among the patches have a significant role in the long-term survival of the species. This study predicts the spatial distribution map of the Caspian cobra considering the factors affecting the predictive power of the distribution models, including sampling bias in presence points, correct selection of background locations, and input model parameters. The sampling bias in presence points was removed using spatial filtering. Several models were run using 19 environmental variables that eventually led to the selection of the effective habitat variables and best MaxEnt distribution model. We also used an ensemble model(EM) of habitat suitability methods to predict the potential habitats of the species. Topographical roughness, shrublands, average annual precipitation, and sparse rangeland with a density of ≤ 20% had the most effect on the spatial distribution of Caspian cobra. The evaluation of models confirmed that the EM has more predictive performance than MaxEnt in predicting the distribution of Naja oxiana.展开更多
In numerical modelling,selection of the constitutive model is a critical factor in predicting the actual response of a geomaterial.The use of oversimplified or inadequate models may not be sufficient to reproduce the ...In numerical modelling,selection of the constitutive model is a critical factor in predicting the actual response of a geomaterial.The use of oversimplified or inadequate models may not be sufficient to reproduce the actual geomaterial behaviour.That selection is especially relevant in the case of aniso-tropic rocks,and particularly for shales and slates,whose behaviour may be affected,e.g.well stability in geothermal or oil and gas production operations.In this paper,an alternative anisotropic constitutive model has been implemented in the finite element method software CODE_BRIGHT,which is able to account for the anisotropy of shales and slates in terms of both deformability and strength.For this purpose,a transversely isotropic version of the generalised Hooke’s law is adopted to represent the stiffness anisotropy,while a nonuniform scaling of the stress tensor is introduced in the plastic model to represent the strength anisotropy.Furthermore,a detailed approach has been proposed to determine the model parameters based on the stressestrain results of laboratory tests.Moreover,numerical analyses are performed to model uniaxial and triaxial tests on Vaca Muerta shale,Bossier shale and slate from the northwest of Spain(NW Spain slate).The experimental data have been recovered from the literature in the case of the shale and,in the case of the slate,performed by the authors in terms of stress-strain curves and strengths.A good agreement can be generally observed between numerical and experi-mental results,hence showing the potential applicability of the approach to actual case studies.Therefore,the presented constitutive model may be a promising approach for analysing the anisotropic behaviour of rocks and its impact on well stability or other relevant geomechanical problems in aniso-tropic rocks.展开更多
The concentrations of two fresh Chinese coals (lignitie and fatty coal ) from dif-ferent geological origin and the corresponding fly and bottom ashes were determined us-ing inductively coupled plasma mass spectrometry...The concentrations of two fresh Chinese coals (lignitie and fatty coal ) from dif-ferent geological origin and the corresponding fly and bottom ashes were determined us-ing inductively coupled plasma mass spectrometry(ICP-MS). The ranges and means of concentrations of these elemennts were given. Based on the combustion simulating ex-periment in the one-dismensional boiler, the contents of REE (rare-earth element) of 18 samples in lignite, fatty coal and their fly and bottom ashes in different combustion condi-tion were determined, and geochemical feature of REE were analyzed.展开更多
Three fresh China coals （lignitie, bituminite and anthracite） from different geological origin and the corresponding fly and bottom ashes were studied by room temperature（RT） Mossbauer spectroscopy（MS）. The iron...Three fresh China coals （lignitie, bituminite and anthracite） from different geological origin and the corresponding fly and bottom ashes were studied by room temperature（RT） Mossbauer spectroscopy（MS）. The iron-bearing minerals were characterized to be mainly pyrite in all coal samples by the hyperfine parameters.Suphate（FeSO4·nH2O） was found in bituminite and anthracite coal.The MSssbauer spectra of the fly and bottom ashes as a result of pulverised coal combustion（PCC） in Xiaolongtan,Shuicheng and Luohuang Power Plants are comprised of superimposed sextets and doulets of oxides includes maghemite（γ-Fe2O3）, magnitite（Fe3O4）, haematite（α-Fe2O3）, magnesioferite （MgFe2O4）, Fe^3＋/Fe^2＋ -mullite, Fe^3＋ -glass silicate and metallic iron. The studies also show that iron-bearing minerals in coals are largely dependant on geological regions and coal rank, the composition of the corresponding fly and bottom ashes will not only depend on the type and mineralogy of the feed coal but also on the local nature of combustion.展开更多
The possibility of transforming Gavdos Island located south of Crete, Greece to a 100% renewable energies island has been investigated. Gavdos Island has few inhabitants but it hosts a large number of tourists during ...The possibility of transforming Gavdos Island located south of Crete, Greece to a 100% renewable energies island has been investigated. Gavdos Island has few inhabitants but it hosts a large number of tourists during the summer. Due to the small size of the island the use of vehicles is limited. It has abundant local energy resources, mainly solar and wind energy, which are currently underutilized. Electricity is locally generated with diesel oil and its electric grid is not interconnected with the grid of Crete. Energy demand in the island has been estimated as well as the availability of various renewable energy resources. The most reliable and cost effective of them, including solar thermal, solar and wind power, solid biomass burning and high efficiency heat pumps have been indicated for achieving a 100% renewable island. Electric vehicles must also replace conventional vehicles in order to zero carbon emissions in transport. Since the power grid in the island is isolated, electricity storage is required and it could be obtained either with electric batteries or with a small hydro-pump storage system. The nominal power of the required solar-PV system for covering all the electricity needs in Gavdos island has been estimated at 848 KWp and the required electricity storage capacity was at 19.2 MWh.展开更多
Fast methods to solve the unloading problem of a cylindrical cavity or tunnel excavated in elasto-perfectly plastic, elasto-brittle or strain-softening materials under a hydrostatic stress feld can be derived based on...Fast methods to solve the unloading problem of a cylindrical cavity or tunnel excavated in elasto-perfectly plastic, elasto-brittle or strain-softening materials under a hydrostatic stress feld can be derived based on the self-similarity of the solution. As a consequence, they only apply when the rock mass is homogeneous and so exclude many cases of practical interest. We describe a robust and fast numerical technique that solves the tunnel unloading problem and estimates the ground reaction curve for a cylindrical cavity excavated in a rock mass with properties depending on the radial coordinate, where the solution is no longer self-similar. The solution is based on a continuation-like approach(associated with the unloading and with the incremental formulation of the elasto-plastic behavior), fnite element spatial discretization and a combination of explicit sub-stepping schemes and implicit techniques to integrate the constitutive law, so as to tackle the diffculties associated with both strong strain-softening and elasto-brittle behaviors. The developed algorithm is used for two practical ground reaction curve computation applications. The frst application refers to a tunnel surrounded by an aureole of material damaged by blasting and the second to a tunnel surrounded by a ring-like zone of reinforced(rock-bolted) material.展开更多
The residual strength of rocks and rock masses is an important parameter to be constrained for analysis and design purposes in many rock engineering applications.A residual strength envelope in principal stress space ...The residual strength of rocks and rock masses is an important parameter to be constrained for analysis and design purposes in many rock engineering applications.A residual strength envelope in principal stress space is typically developed using residual strength data obtained from compression tests on many different specimens of the same rock type.In this study,we examined the potential for use of the continuous-failure-state testing concept as a means to constrain the residual strength envelope using a limited number of specimens.Specifically,cylindrical specimens of three rock types(granodiorite,diabase,and Stanstead granite)were unloaded at the residual state such that a full residual strength envelope for each individual specimen was obtained.Using a residual strength model that introduces a single new strength parameter(the residual strength index,or RSI),the results of the continuous-failurestate unloading tests were compared to conventionally obtained residual strength envelopes.Overall,the continuous-failure-state residual strength data were found to be consistent with the conventional residual strength data.However,it was identified that the primary factor limiting an accurate characterization of the residual strength for a given rock type is not the amount of data for a given specimen,but the variety of specimens available to characterize the inherent variability of the rock unit of interest.Accordingly,the use of continuous-failure-state testing for estimation of the residual strength of a rock unit is only recommended when the number of specimens available for testing is very limited(i.e.<5).展开更多
Olive pomace plants process olive paste, a waste product of olive mills which produces crude olive kernel oil and olive kernel wood. Olive kernel wood has very good burning characteristics, high heat content, low cost...Olive pomace plants process olive paste, a waste product of olive mills which produces crude olive kernel oil and olive kernel wood. Olive kernel wood has very good burning characteristics, high heat content, low cost and it is used as a renewable solid fuel replacing liquid fuel and heating oil. Part of the produced olive kernel wood is consumed inside the factory for heat generation and the rest is sold to heat consumers. It has been estimated that a typical olive pomace plant located in Crete, Greece consumes 42.86% of the produced olive kernel wood for its own heat generation, while the remaining 57.14% is sold to various heat consumers. 99.1% of the energy used in these plants is consumed for heating and the rest, 0.9%, for lighting and the operation of various electric devices. Olive pomace plants utilize a renewable solid fuel, which is carbon neutral, for the production of thermal energy. Therefore their CO<sub>2</sub> emissions regarding energy utilization are due to electricity use. Installation of solar-PV panels in the plant could generate annually all the electricity needed for its operation. The current legal framework in Greece through net-metering allows the offsetting of grid electricity consumed in factories with PV electricity. The required capital cost of a solar-PV system installed in a typical olive pomace plant located in Crete, Greece in order to offset the grid electricity consumed annually has been estimated at 185,832€, the payback period of 5.33 years and the net present value at 555,671€. Since the plant could utilize only solid biomass for heat generation and could offset the grid electricity consumption with solar electricity, its total CO<sub>2</sub> emissions due to energy use would be zero contributing positively to climate stabilization.展开更多
Decrease of energy consumption in buildings and increase of the share of renewable energies in them are currently technologically and economically feasible and it is promoted by E.U. policies. After 2019, all the new ...Decrease of energy consumption in buildings and increase of the share of renewable energies in them are currently technologically and economically feasible and it is promoted by E.U. policies. After 2019, all the new public buildings in EU countries must be near zero energy buildings reducing their energy consumption and CO<sub>2</sub> emissions. Use of various renewable energies for heat and power generation in school buildings in Crete-Greece can result in zeroing their fossil fuels consumption and CO<sub>2</sub> emissions. Purpose of the current work is to investigate the possibilities of creating zero CO<sub>2</sub> emissions school buildings in Crete-Greece due to operational energy use in them. A methodology which allows the replacement of fossil fuels with renewable energies in school buildings is proposed. Solar energy, solid biomass and low enthalpy geothermal energy, which are abundant in Crete, can be used for that. School buildings in Greece consume significantly less energy, 68 KWh/m<sup>2</sup> year, and emit less CO<sub>2</sub>, 28 kgCO<sub>2</sub>/m<sup>2</sup> year, than the corresponding buildings in other countries. The installation cost of renewable energies systems in order to replace all fossil fuels used in school buildings in Crete-Greece and to zero their CO<sub>2</sub> consumption due to energy use in them has been estimated at 47.42 - 87.71 €/m<sup>2</sup>, which corresponds to 1.69 - 3.13 €/kg CO<sub>2</sub> saved.展开更多
The Chenyulan Stream in Central Taiwan follows the Chenyulan fault line which is a major boundary fault in Taiwan. In recent years, many destructive landslides have occurred in the Chenyulan Creek Basin after heavy ra...The Chenyulan Stream in Central Taiwan follows the Chenyulan fault line which is a major boundary fault in Taiwan. In recent years, many destructive landslides have occurred in the Chenyulan Creek Basin after heavy rainfall accompanied by several strong typhoons. Three examples of landslide distributions in the Chenyulan Creek Basin, before and after 1996 and after 2004 are analyzed. The box dimension and two-point correlation dimension are employed to describe the landslide area size distribution and distance distribution between every two landslides, respectively. It is found that the number of landslides increased in this period. However, the average landslide area decreased. The correlation dimension gradually increased from 1.15 to 1.32 during this period（before and after 1996 and after 2004）. This implies that the landslide distribution in the Chenyulan Creek Basin has become diffuse and extensive. The box dimension value shows the degree of the landslide density occupied in a space. The box dimension also increased from 0.3 to 0.69 during this period. The increasing box dimension means that the landslide presented in this creek basin has gradually increased. This indicates that the slopes of this creek basin have become more unstable and susceptible.展开更多
基金Supported by the National Natural Science Key Foundation of China(40133010)Natural Science Foundation of China of Anhui University of Science and Technology for ph.D to Research(DG414)
文摘Studied the content and distribution of 18 environmental hazardous trace elementsin the lignite, fatty coal, anthracite and its burnt products by combustion simulatingexpriment in the one-dismensinal boiler.The transformations and concentration of 18 traceelements during different coal combustion were discussed.The results show that there aresome content distribution of 18 hazardous trace elements in every burnt product, but thelaw of concentration and dispersion of every trace element during different coal combustionis very different.Experiment results indicate that the transformation and concentrationof trace elements during coal combustion are related to the element contents and occur-rencesof trace elements in raw coal, but are also affected by some man-made factorssuch as the combustion method of boiler, combustion temperature and atmosphere, thetype of precipitators and so on.
文摘Landslides are abundant in mountainous regions.They are responsible for substantial damages and losses in those areas.The A1 Highway,which is an important road in Algeria,was sometimes constructed in mountainous and/or semi-mountainous areas.Previous studies of landslide susceptibility mapping conducted near this road using statistical and expert methods have yielded ordinary results.In this research,we are interested in how do machine learning techniques help in increasing accuracy of landslide susceptibility maps in the vicinity of the A1 Highway corridor.To do this,an important section at Ain Bouziane(NE,Algeria) is chosen as a case study to evaluate the landslide susceptibility using three different machine learning methods,namely,random forest(RF),support vector machine(SVM),and boosted regression tree(BRT).First,an inventory map and nine input factors were prepared for landslide susceptibility mapping(LSM) analyses.The three models were constructed to find the most susceptible areas to this phenomenon.The results were assessed by calculating the receiver operating characteristic(ROC) curve,the standard error(Std.error),and the confidence interval(CI) at 95%.The RF model reached the highest predictive accuracy(AUC=97.2%) comparatively to the other models.The outcomes of this research proved that the obtained machine learning models had the ability to predict future landslide locations in this important road section.In addition,their application gives an improvement of the accuracy of LSMs near the road corridor.The machine learning models may become an important prediction tool that will identify landslide alleviation actions.
文摘The current study aimed at evaluating the capabilities of seven advanced machine learning techniques(MLTs),including,Support Vector Machine(SVM),Random Forest(RF),Multivariate Adaptive Regression Spline(MARS),Artificial Neural Network(ANN),Quadratic Discriminant Analysis(QDA),Linear Discriminant Analysis(LDA),and Naive Bayes(NB),for landslide susceptibility modeling and comparison of their performances.Coupling machine learning algorithms with spatial data types for landslide susceptibility mapping is a vitally important issue.This study was carried out using GIS and R open source software at Abha Basin,Asir Region,Saudi Arabia.First,a total of 243 landslide locations were identified at Abha Basin to prepare the landslide inventory map using different data sources.All the landslide areas were randomly separated into two groups with a ratio of 70%for training and 30%for validating purposes.Twelve landslide-variables were generated for landslide susceptibility modeling,which include altitude,lithology,distance to faults,normalized difference vegetation index(NDVI),landuse/landcover(LULC),distance to roads,slope angle,distance to streams,profile curvature,plan curvature,slope length(LS),and slope-aspect.The area under curve(AUC-ROC)approach has been applied to evaluate,validate,and compare the MLTs performance.The results indicated that AUC values for seven MLTs range from 89.0%for QDA to 95.1%for RF.Our findings showed that the RF(AUC=95.1%)and LDA(AUC=941.7%)have produced the best performances in comparison to other MLTs.The outcome of this study and the landslide susceptibility maps would be useful for environmental protection.
基金The University of Vigo is acknowledged for financing part of the first author’s PhD studiesthe Spanish Ministry of Economy and Competitiveness for funding of the project‘Deepening on the behaviour of rock masses:Scale effects on the stressestrain response of fissured rock samples with particular emphasis on post-failure’,awarded under Contract Reference No.RTI2018-093563-B-I00partially financed by means of European Regional Development Funds from the European Union(EU)。
文摘This study presents a calibration process of three-dimensional particle flow code(PFC3D)simulation of intact and fissured granite samples.First,laboratory stressestrain response from triaxial testing of intact and fissured granite samples is recalled.Then,PFC3D is introduced,with focus on the bonded particle models(BPM).After that,we present previous studies where intact rock is simulated by means of flatjoint approaches,and how improved accuracy was gained with the help of parametric studies.Then,models of the pre-fissured rock specimens were generated,including modeled fissures in the form of“smooth joint”type contacts.Finally,triaxial testing simulations of 1 t 2 and 2 t 3 jointed rock specimens were performed.Results show that both elastic behavior and the peak strength levels are closely matched,without any additional fine tuning of micro-mechanical parameters.Concerning the postfailure behavior,models reproduce the trends of decreasing dilation with increasing confinement and plasticity.However,the dilation values simulated are larger than those observed in practice.This is attributed to the difficulty in modeling some phenomena of fissured rock behaviors,such as rock piece corner crushing with dust production and interactions between newly formed shear bands or axial splitting cracks with pre-existing joints.
基金The study was supported by College of Agriculture,Shiraz University(Grant No.96GRD1M271143).
文摘Natural hazards are often studied in isolation.However,there is a great need to examine hazards holistically to better manage the complex of threats found in any region.Many regions of the world have complex hazard landscapes wherein risk from individual and/or multiple extreme events is omnipresent.Extensive parts of Iran experience a complex array of natural hazards-floods,earthquakes,landslides,forest fires,subsidence,and drought.The effectiveness of risk mitigation is in part a function of whether the complex of hazards can be collectively considered,visualized,and evaluated.This study develops and tests individual and collective multihazard risk maps for floods,landslides,and forest fires to visualize the spatial distribution of risk in Fars Province,southern Iran.To do this,two well-known machine-learning algorithms-SVM and MARS-are used to predict the distribution of these events.Past floods,landslides,and forest fires were surveyed and mapped.The locations of occurrence of these events(individually and collectively) were randomly separated into training(70%) and testing(30%) data sets.The conditioning factors(for floods,landslides,and forest fires) employed to model the risk distributions are aspect,elevation,drainage density,distance from faults,geology,LULC,profile curvature,annual mean rainfall,plan curvature,distance from man-made residential structures,distance from nearest river,distance from nearest road,slope gradient,soil types,mean annual temperature,and TWI.The outputs of the two models were assessed using receiver-operating-characteristic(ROC) curves,true-skill statistics(TSS),and the correlation and deviance values from each models for each hazard.The areas-under-the-curves(AUC) for the MARS model prediction were 76.0%,91.2%,and 90.1% for floods,landslides,and forest fires,respectively.Similarly,the AUCs for the SVM model were 75.5%,89.0%,and 91.5%.The TSS reveals that the MARS model was better able to predict landslide risk,but was less able to predict flood-risk patterns and forest-fire risk.Finally,the combination of flood,forest fire,and landslide risk maps yielded a multi-hazard susceptibility map for the province.The better predictive model indicated that 52.3% of the province was at-risk for at least one of these hazards.This multi-hazard map may yield valuable insight for land-use planning,sustainable development of infrastructure,and also integrated watershed management in Fars Province.
基金supported by the College of Agriculture,Shiraz University(Grant No.97GRC1M271143)funding from the UK Biotechnology and Biological Sciences Research Council(BBSRC)funded by BBSRC grant award BBS/E/C/000I0330–Soil to Nutrition project 3–Sustainable intensification:optimisation at multiple scales。
文摘This investigation assessed the efficacy of 10 widely used machine learning algorithms(MLA)comprising the least absolute shrinkage and selection operator(LASSO),generalized linear model(GLM),stepwise generalized linear model(SGLM),elastic net(ENET),partial least square(PLS),ridge regression,support vector machine(SVM),classification and regression trees(CART),bagged CART,and random forest(RF)for gully erosion susceptibility mapping(GESM)in Iran.The location of 462 previously existing gully erosion sites were mapped through widespread field investigations,of which 70%(323)and 30%(139)of observations were arbitrarily divided for algorithm calibration and validation.Twelve controlling factors for gully erosion,namely,soil texture,annual mean rainfall,digital elevation model(DEM),drainage density,slope,lithology,topographic wetness index(TWI),distance from rivers,aspect,distance from roads,plan curvature,and profile curvature were ranked in terms of their importance using each MLA.The MLA were compared using a training dataset for gully erosion and statistical measures such as RMSE(root mean square error),MAE(mean absolute error),and R-squared.Based on the comparisons among MLA,the RF algorithm exhibited the minimum RMSE and MAE and the maximum value of R-squared,and was therefore selected as the best model.The variable importance evaluation using the RF model revealed that distance from rivers had the highest significance in influencing the occurrence of gully erosion whereas plan curvature had the least importance.According to the GESM generated using RF,most of the study area is predicted to have a low(53.72%)or moderate(29.65%)susceptibility to gully erosion,whereas only a small area is identified to have a high(12.56%)or very high(4.07%)susceptibility.The outcome generated by RF model is validated using the ROC(Receiver Operating Characteristics)curve approach,which returned an area under the curve(AUC)of 0.985,proving the excellent forecasting ability of the model.The GESM prepared using the RF algorithm can aid decision-makers in targeting remedial actions for minimizing the damage caused by gully erosion.
基金We would like to thank from Shiraz University for supporting us on this studyThe study was supported by College of Agriculture,Shiraz University(Grant No.96GRD1M271143).
文摘Landslides influence the capacity for safe and sustainable development of mountainous environments.This study explores the spatial distribution of and the interactions between landslides that are mapped using global positioning system(GPS) and extensive field surveys in Mazandaran Province,Iran.Point-pattern assessment is undertaken using several univariate summary statistical functions,including pair correlation,spherical-contact distribution,nearest-neighbor analysis,and O-ring analysis,as well as bivariate summary statistics,and a markcorrelation function.The maximum entropy method was applied to prioritize the factors controlling the incidence of landslides and the landslides susceptibility map.The validation processes were considered for separated 30%data applying the ROC curves,fourfold plot,and Cohen’s kappa index.The results show that pair correlation and O-ring analyses satisfactorily predicted landslides at scales from 1 to 150 m.At smaller scales,from 150 to 400 m,landslides were randomly distributed.The nearest-neighbor distribution function show that the highest distance to the nearest landslide occurred in the 355 m.The spherical-contact distribution revealed that the patterns were random up to a spatial scale of 80 m.The bivariate correlation functions revealed that landslides were positively linked to several linear features(including faults,roads,and rivers) at all spatial scales.The mark-correlation function showed that aggregated fields of landslides were positively correlated with measures of land use,lithology,drainage density,plan curvature,and aspect,when the numbers of landslides in the groups were greater than the overall average aggregation.The results of analysis of factor importance have showed that elevation(topography map scale:1:25,000),distance to roads,and distance to rivers are the most important factors in the occurrence of landslides.The susceptibility model of landslides indicates an excellent accuracy,i.e.,the AUC value of landslides was 0.860.The susceptibility map of landslides analyzed has shown that 35% of the area is low susceptible to landslides.
文摘This study investigates the tensile failure mechanisms in granitic rock samples at different scales by means of different types of tests.To do that,we have selected a granitic rock type and obtained samples of different sizes with the diameter ranging from 30 mm to 84 mm.The samples have been subjected to direct tensile strength(DTS)tests,indirect Brazilian tensile strength(BTS)tests and to two fracture toughness testing approaches.Whereas DTS and fracture toughness were found to consistently grow with sample size,this trend was not clearly identified for BTS,where after an initial grow,a plateau of results was observed.This is a rather complete database of tensile related properties of a single rock type.Even if similar databases are rare,the obtained trends are generally consistent with previous scatter and partial experimental programs.However,different observations apply to different types of rocks and experimental approaches.The differences in variability and mean values of the measured parameters at different scales are critically analysed based on the heterogeneity,granular structure and fracture mechanics approaches.Some potential relations between parameters are revised and an indication is given on potential sample sizes for obtaining reliable results.Extending this database with different types of rocks is thought to be convenient to advance towards a better understanding of the tensile strength of rock materials.
文摘The possibility of creating zero CO2 emissions residential buildings due to life cycle energy use in the island of Crete, Greece has been examined. In a typical residential building located in Crete, Greece, its annual operating energy has been appraised at 170 KWh/m2 and its embodied energy at 30 KWh/m2. Various locally available renewable energies including solar energy, solid biomass and low enthalpy geothermal energy with heat pumps have been considered for generating the required heat and offsetting the grid electricity used. Their technologies are mature, reliable and cost-effective. Offset of the annual grid electricity use in the building with solar-PV electricity is allowed according to the net metering regulation. For zero carbon emissions due to embodied energy of the building, generation of additional solar electricity injected into the grid is required. A mathematical model has been developed for sizing the required solar-PV system installed in the building in order to offset the grid electricity use. For a residential building in Crete, Greece with a covered area of 100 m2, the power of the additional solar-PV system has been estimated at 1.6 KWp and its cost at 2400 €. In the current work, it is indicated that the creation of a zero CO2 emissions residential building due to life cycle energy use in Crete, Greece does not have major difficulties and it could be achieved relatively easily.
文摘A description and assessment of a small renewable energy community located in Crete, Greece is presented. The community included private residential and agricultural activities without any involvement of the public sector. Small-scale decentralized energy systems were used. Solar energy and solid biomass which are locally available covered most of the heat and electricity requirements in the community. Renewable energy technologies used include solar thermal energy, solar-PV and solid biomass burning utilizing olive tree wood and olive kernel wood. These technologies are mature, reliable, well proven in Crete and cost-effective. Existing energy systems were generating 857,877 kWh per year covering 94.46% of the current energy requirements in the community, significantly reducing its emissions at 278,494 kg CO2 per year. The addition of a new solar-PV system with nominal power of 33.6 kWp could cover all the remaining electricity needs in the community, transforming it to a zero-CO2 emission community due to energy use. The total installation cost of the existing renewable energy systems in the community was estimated at 0.16€ per total kWh of thermal and electric energy generated annually and at 0.50€ per ton of CO2 emissions saved annually. Results indicated that the creation of the above-mentioned small local energy community is economically viable, environmental friendly and socially accepted. Therefore it could be replicated in other territories with similar availability of renewable energies, increasing their energy autonomy and sustainability.
文摘Over recent years, the population of Caspian cobra Naja oxiana has declined in its distribution range in Iran due to habitat destruction and overhunting. Consequently, their small and isolated populations in fragmented landscapes are facing genetic and demographic threats. Evaluating the spatial distribution pattern of Naja oxiana, identifying core habitat patches and improving landscape connectivity among the patches have a significant role in the long-term survival of the species. This study predicts the spatial distribution map of the Caspian cobra considering the factors affecting the predictive power of the distribution models, including sampling bias in presence points, correct selection of background locations, and input model parameters. The sampling bias in presence points was removed using spatial filtering. Several models were run using 19 environmental variables that eventually led to the selection of the effective habitat variables and best MaxEnt distribution model. We also used an ensemble model(EM) of habitat suitability methods to predict the potential habitats of the species. Topographical roughness, shrublands, average annual precipitation, and sparse rangeland with a density of ≤ 20% had the most effect on the spatial distribution of Caspian cobra. The evaluation of models confirmed that the EM has more predictive performance than MaxEnt in predicting the distribution of Naja oxiana.
文摘In numerical modelling,selection of the constitutive model is a critical factor in predicting the actual response of a geomaterial.The use of oversimplified or inadequate models may not be sufficient to reproduce the actual geomaterial behaviour.That selection is especially relevant in the case of aniso-tropic rocks,and particularly for shales and slates,whose behaviour may be affected,e.g.well stability in geothermal or oil and gas production operations.In this paper,an alternative anisotropic constitutive model has been implemented in the finite element method software CODE_BRIGHT,which is able to account for the anisotropy of shales and slates in terms of both deformability and strength.For this purpose,a transversely isotropic version of the generalised Hooke’s law is adopted to represent the stiffness anisotropy,while a nonuniform scaling of the stress tensor is introduced in the plastic model to represent the strength anisotropy.Furthermore,a detailed approach has been proposed to determine the model parameters based on the stressestrain results of laboratory tests.Moreover,numerical analyses are performed to model uniaxial and triaxial tests on Vaca Muerta shale,Bossier shale and slate from the northwest of Spain(NW Spain slate).The experimental data have been recovered from the literature in the case of the shale and,in the case of the slate,performed by the authors in terms of stress-strain curves and strengths.A good agreement can be generally observed between numerical and experi-mental results,hence showing the potential applicability of the approach to actual case studies.Therefore,the presented constitutive model may be a promising approach for analysing the anisotropic behaviour of rocks and its impact on well stability or other relevant geomechanical problems in aniso-tropic rocks.
基金Supported by the National Natural Science Key Foundation of China (40133010) Educational Natural Science Foundation of Anhui (2004kj114) Natural Science Foundation of Anhui University of Science and Technology for Ph.D to Research(DG414)
文摘The concentrations of two fresh Chinese coals (lignitie and fatty coal ) from dif-ferent geological origin and the corresponding fly and bottom ashes were determined us-ing inductively coupled plasma mass spectrometry(ICP-MS). The ranges and means of concentrations of these elemennts were given. Based on the combustion simulating ex-periment in the one-dismensional boiler, the contents of REE (rare-earth element) of 18 samples in lignite, fatty coal and their fly and bottom ashes in different combustion condi-tion were determined, and geochemical feature of REE were analyzed.
文摘Three fresh China coals （lignitie, bituminite and anthracite） from different geological origin and the corresponding fly and bottom ashes were studied by room temperature（RT） Mossbauer spectroscopy（MS）. The iron-bearing minerals were characterized to be mainly pyrite in all coal samples by the hyperfine parameters.Suphate（FeSO4·nH2O） was found in bituminite and anthracite coal.The MSssbauer spectra of the fly and bottom ashes as a result of pulverised coal combustion（PCC） in Xiaolongtan,Shuicheng and Luohuang Power Plants are comprised of superimposed sextets and doulets of oxides includes maghemite（γ-Fe2O3）, magnitite（Fe3O4）, haematite（α-Fe2O3）, magnesioferite （MgFe2O4）, Fe^3＋/Fe^2＋ -mullite, Fe^3＋ -glass silicate and metallic iron. The studies also show that iron-bearing minerals in coals are largely dependant on geological regions and coal rank, the composition of the corresponding fly and bottom ashes will not only depend on the type and mineralogy of the feed coal but also on the local nature of combustion.
文摘The possibility of transforming Gavdos Island located south of Crete, Greece to a 100% renewable energies island has been investigated. Gavdos Island has few inhabitants but it hosts a large number of tourists during the summer. Due to the small size of the island the use of vehicles is limited. It has abundant local energy resources, mainly solar and wind energy, which are currently underutilized. Electricity is locally generated with diesel oil and its electric grid is not interconnected with the grid of Crete. Energy demand in the island has been estimated as well as the availability of various renewable energy resources. The most reliable and cost effective of them, including solar thermal, solar and wind power, solid biomass burning and high efficiency heat pumps have been indicated for achieving a 100% renewable island. Electric vehicles must also replace conventional vehicles in order to zero carbon emissions in transport. Since the power grid in the island is isolated, electricity storage is required and it could be obtained either with electric batteries or with a small hydro-pump storage system. The nominal power of the required solar-PV system for covering all the electricity needs in Gavdos island has been estimated at 848 KWp and the required electricity storage capacity was at 19.2 MWh.
基金the Spanish Ministry of Science and Technology for fnancial support awarded under Contract Reference Numbers BIA2009-09673 and MTM2010-21235-C02-02
文摘Fast methods to solve the unloading problem of a cylindrical cavity or tunnel excavated in elasto-perfectly plastic, elasto-brittle or strain-softening materials under a hydrostatic stress feld can be derived based on the self-similarity of the solution. As a consequence, they only apply when the rock mass is homogeneous and so exclude many cases of practical interest. We describe a robust and fast numerical technique that solves the tunnel unloading problem and estimates the ground reaction curve for a cylindrical cavity excavated in a rock mass with properties depending on the radial coordinate, where the solution is no longer self-similar. The solution is based on a continuation-like approach(associated with the unloading and with the incremental formulation of the elasto-plastic behavior), fnite element spatial discretization and a combination of explicit sub-stepping schemes and implicit techniques to integrate the constitutive law, so as to tackle the diffculties associated with both strong strain-softening and elasto-brittle behaviors. The developed algorithm is used for two practical ground reaction curve computation applications. The frst application refers to a tunnel surrounded by an aureole of material damaged by blasting and the second to a tunnel surrounded by a ring-like zone of reinforced(rock-bolted) material.
文摘The residual strength of rocks and rock masses is an important parameter to be constrained for analysis and design purposes in many rock engineering applications.A residual strength envelope in principal stress space is typically developed using residual strength data obtained from compression tests on many different specimens of the same rock type.In this study,we examined the potential for use of the continuous-failure-state testing concept as a means to constrain the residual strength envelope using a limited number of specimens.Specifically,cylindrical specimens of three rock types(granodiorite,diabase,and Stanstead granite)were unloaded at the residual state such that a full residual strength envelope for each individual specimen was obtained.Using a residual strength model that introduces a single new strength parameter(the residual strength index,or RSI),the results of the continuous-failurestate unloading tests were compared to conventionally obtained residual strength envelopes.Overall,the continuous-failure-state residual strength data were found to be consistent with the conventional residual strength data.However,it was identified that the primary factor limiting an accurate characterization of the residual strength for a given rock type is not the amount of data for a given specimen,but the variety of specimens available to characterize the inherent variability of the rock unit of interest.Accordingly,the use of continuous-failure-state testing for estimation of the residual strength of a rock unit is only recommended when the number of specimens available for testing is very limited(i.e.<5).
文摘Olive pomace plants process olive paste, a waste product of olive mills which produces crude olive kernel oil and olive kernel wood. Olive kernel wood has very good burning characteristics, high heat content, low cost and it is used as a renewable solid fuel replacing liquid fuel and heating oil. Part of the produced olive kernel wood is consumed inside the factory for heat generation and the rest is sold to heat consumers. It has been estimated that a typical olive pomace plant located in Crete, Greece consumes 42.86% of the produced olive kernel wood for its own heat generation, while the remaining 57.14% is sold to various heat consumers. 99.1% of the energy used in these plants is consumed for heating and the rest, 0.9%, for lighting and the operation of various electric devices. Olive pomace plants utilize a renewable solid fuel, which is carbon neutral, for the production of thermal energy. Therefore their CO<sub>2</sub> emissions regarding energy utilization are due to electricity use. Installation of solar-PV panels in the plant could generate annually all the electricity needed for its operation. The current legal framework in Greece through net-metering allows the offsetting of grid electricity consumed in factories with PV electricity. The required capital cost of a solar-PV system installed in a typical olive pomace plant located in Crete, Greece in order to offset the grid electricity consumed annually has been estimated at 185,832€, the payback period of 5.33 years and the net present value at 555,671€. Since the plant could utilize only solid biomass for heat generation and could offset the grid electricity consumption with solar electricity, its total CO<sub>2</sub> emissions due to energy use would be zero contributing positively to climate stabilization.
文摘Decrease of energy consumption in buildings and increase of the share of renewable energies in them are currently technologically and economically feasible and it is promoted by E.U. policies. After 2019, all the new public buildings in EU countries must be near zero energy buildings reducing their energy consumption and CO<sub>2</sub> emissions. Use of various renewable energies for heat and power generation in school buildings in Crete-Greece can result in zeroing their fossil fuels consumption and CO<sub>2</sub> emissions. Purpose of the current work is to investigate the possibilities of creating zero CO<sub>2</sub> emissions school buildings in Crete-Greece due to operational energy use in them. A methodology which allows the replacement of fossil fuels with renewable energies in school buildings is proposed. Solar energy, solid biomass and low enthalpy geothermal energy, which are abundant in Crete, can be used for that. School buildings in Greece consume significantly less energy, 68 KWh/m<sup>2</sup> year, and emit less CO<sub>2</sub>, 28 kgCO<sub>2</sub>/m<sup>2</sup> year, than the corresponding buildings in other countries. The installation cost of renewable energies systems in order to replace all fossil fuels used in school buildings in Crete-Greece and to zero their CO<sub>2</sub> consumption due to energy use in them has been estimated at 47.42 - 87.71 €/m<sup>2</sup>, which corresponds to 1.69 - 3.13 €/kg CO<sub>2</sub> saved.
文摘The Chenyulan Stream in Central Taiwan follows the Chenyulan fault line which is a major boundary fault in Taiwan. In recent years, many destructive landslides have occurred in the Chenyulan Creek Basin after heavy rainfall accompanied by several strong typhoons. Three examples of landslide distributions in the Chenyulan Creek Basin, before and after 1996 and after 2004 are analyzed. The box dimension and two-point correlation dimension are employed to describe the landslide area size distribution and distance distribution between every two landslides, respectively. It is found that the number of landslides increased in this period. However, the average landslide area decreased. The correlation dimension gradually increased from 1.15 to 1.32 during this period（before and after 1996 and after 2004）. This implies that the landslide distribution in the Chenyulan Creek Basin has become diffuse and extensive. The box dimension value shows the degree of the landslide density occupied in a space. The box dimension also increased from 0.3 to 0.69 during this period. The increasing box dimension means that the landslide presented in this creek basin has gradually increased. This indicates that the slopes of this creek basin have become more unstable and susceptible.
