Fractional Order Environmental and Economic Model Investigations Using Artificial Neural Network

The motive of these investigations is to provide the importance and significance of the fractional order(FO)derivatives in the nonlinear environmental and economic(NEE)model,i.e.,FO-NEE model.The dynamics of the NEE model achieves more precise by using the form of the FO derivative.The investigations through the non-integer and nonlinear mathematical form to define the FO-NEE model are also provided in this study.The composition of the FO-NEEmodel is classified into three classes,execution cost of control,system competence of industrial elements and a new diagnostics technical exclusion cost.The mathematical FO-NEE system is numerically studied by using the artificial neural networks(ANNs)along with the Levenberg-Marquardt backpropagation method(ANNs-LMBM).Three different cases using the FO derivative have been examined to present the numerical performances of the FO-NEE model.The data is selected to solve the mathematical FO-NEE system is executed as 70%for training and 15%for both testing and certification.The exactness of the proposed ANNs-LMBM is observed through the comparison of the obtained and the Adams-Bashforth-Moulton database results.To ratify the aptitude,validity,constancy,exactness,and competence of the ANNs-LMBM,the numerical replications using the state transitions,regression,correlation,error histograms and mean square error are also described.

A container-based approach for sharing environmental models as web services

As researchers globally work towards a fully digital representation of the earth and its processes-i.e.a true Digital Earth-the need grows for software and systems to link disparate computer simulation models of various parts of the earth in a reliable and highly functional way.Web services have been demonstrated as an effective way to share and reuse models as they enable communication and interoperation among applications via the Internet.However,even using well-designed software tools,it remains a daunting process to publish heterogeneous environmental models as web services and provide long-term maintenance in response to changing computational environments.We present an approach that enables environmental models to be published as long-term functional web services on the same platform regardless of execution mode,programming language,and computational environment conflicts.The approach adopts the OpenGMS Wrapper System(OGMS-WS)for service publishing and Docker containers for model isolation.A streamflow prediction service is developed using this approach and is applied to analyze historical streamflow trends in Bangladesh.We demonstrate that this approach can lower the barrier to deploying heterogeneous environmental models as long-term functional web services,contributing to the development of a Digital Earth.

Ranking environmental projects model based on multicriteria decision-making and the weight sensitivity analysis

With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental quality and economic benefits is an important problem for the decision makers. The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria. A model for ranking the projects of municipal sewage treatment plants is proposed by using exports＇ information and the data of the real projects. And, the ranking result is given based on the PROMETHEE method. Furthermore, by means of the concept of the weight stability intervals （WSI）, the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed. The result shows that some criteria, such as “proportion of benefit to project cost”, will influence the ranking result of alternatives very strong while others not. The influence are not only from the value of criterion but also from the changing the weight of criterion. So, some criteria such as “proportion of benefit to project cost” are key critera for ranking the projects. Decision makers must be cautious to them.

Profiles and Source Apportionment of Nonmethane Volatile Organic Compounds in Winter and Summer in Xi’an, China, based on the Hybrid Environmental Receptor Model

Summer and winter campaigns for the chemical compositions and sources of nonmethane hydrocarbons(NMHCs)and oxygenated volatile organic compounds(OVOCs)were conducted in Xi’an.Data from 57 photochemical assessment monitoring stations for NMHCs and 20 OVOC species were analyzed.Significant seasonal differences were noted for total VOC(TVOC,NMHCs and OVOCs)concentrations and compositions.The campaign-average TVOC concentrations in winter(85.3±60.6 ppbv)were almost twice those in summer(47.2±31.6 ppbv).Alkanes and OVOCs were the most abundant category in winter and summer,respectively.NMHCs,but not OVOCs,had significantly higher levels on weekends than on weekdays.Total ozone formation potential was higher in summer than in winter(by 50%)because of the high concentrations of alkenes(particularly isoprene),high temperature,and high solar radiation levels in summer.The Hybrid Environmental Receptor Model(HERM)was used to conduct source apportionment for atmospheric TVOCs in winter and summer,with excellent accuracy.HERM demonstrated its suitability in a situation where only partial source profile data were available.The HERM results indicated significantly different seasonal source contributions to TVOCs in Xi’an.In particular,coal and biomass burning had contributions greater than half in winter(53.4%),whereas traffic sources were prevalent in summer(53.1%).This study’s results highlight the need for targeted and adjustable VOC control measures that account for seasonal differences in Xi’an;such measures should target not only the severe problem with VOC pollution but also the problem of consequent secondary pollution(e.g.,from ozone and secondary organic aerosols).

A stock assessment for Illex argentinus in Southwest Atlantic using an environmentally dependent surplus production model

The southern Patagonian stock（SPS） of Argentinian shortfin squid, Illex argentinus, is an economically important squid fishery in the Southwest Atlantic. Environmental conditions in the region play an important role in regulating the population dynamics of the I. argentinus population. This study develops an environmentally dependent surplus production（EDSP） model to evaluate the stock abundance of I. argentines during the period of 2000 to 2010. The environmental factors（favorable spawning habitat areas with sea surface temperature of 16–18°C） were assumed to be closely associated with carrying capacity（K） in the EDSP model. Deviance Information Criterion（DIC） values suggest that the estimated EDSP model with environmental factors fits the data better than a Schaefer surplus model without environmental factors under uniform and normal scenarios.The EDSP model estimated a maximum sustainable yield（MSY） from 351 600 t to 685 100 t and a biomass from 1 322 400 t to1 803 000 t. The fishing mortality coefficient of I. argentinus from 2000 to 2010 was smaller than the values of F（0.1） and F（MSY）. Furthermore, the time series biomass plot of I. argentinus from 2000 to 2010 shows that the biomass of I.argentinus and this fishery were in a good state and not presently experiencing overfishing. This study suggests that the environmental conditions of the habitat should be considered within squid stock assessment and management.

Countermeasures for Solving the Environmental Problems and Accelerating the Model City Construction of Xi'an

Through careful study, it found that the key and difficult points of affecting and restricting Xi＇an to reach the model city construction standards in provincial and national levels were ＂urban air environment quality standards＂ and ＂water qualification rate of urban water environment function area＂. In order to tackle with the weak links, highlight the important points and focus on the difficult points to strengthen scientific and technological innovation, we actively explored new ideas and ways to resolve the dilemma in meeting the two standards of model city construction, and we managed to put forward the countermeasures to resolve the dilemma through innovating system and mechanism. ＂Place master system＂ should be carded out quickly to meet the ＂urban air environment quality standards＂, while ＂river master system＂ should be implemented as soon as possible to reach the ＂water qualification rate of urban water environment function area＂. The aim of this study was to enhance the qualification rates of the indicators for model city construction to make Xi＇an successfully pass the provincial and national assessment of model city construction through dealing with the weak links to accelerate the realization of becoming model environmental protection city.

Environmental input-output model and its analysis with a focus on the solid waste management sectors

An environmental input output model (EIOM) was introduced to the regional solid waste management sectors, which can reflect the direct and indirect relations between the environment and the regional economy development. Some details about how to use the EIOM was discussed. The EIOM was applied to the Changsha City in China. The example results indicate that much useful information related to the environment and the regional economy development can be gained from the solution of the EIOM. Thus, the EIOM can be used as a useful tool for the sustainable development planning including the solid waste management sectors.

Modelling Environmental Attitudes of the Users of Kilombero Valley Wetlands, Tanzania

Development policies have for a long time made it more profitable for people to degrade than to conserve environment. The adoption of these economic wide policies by Africa especially during colonial time and after independence has resulted into erosion of its communities’ conservation behaviour and attitude. Although many studies assess environmental attitudes, those focussing on African regions or countries using New Environmental Paradigm (NEP) scale are very limited. Such studies in the African context using NEP scale are very important, simply because many people depend on the environment for their livelihood, and in the process they destroy the world’s valued ecosystems including wetlands. This study is meant to fill in the gap using Kilombero valley wetlands in Tanzania as a case. The study used Structural Equation Modelling (SEM) to predict the behaviour of the users based on attitudes, environmental knowledge and awareness. The findings indicate that users of the Kilombero wetlands have a generally positive attitude towards the environment, despite a great degree of variability among the study participants. The study shows also that a certain level of environmental awareness is needed in order to increase people’s knowledge about environmental issues and change their environmental attitudes. The NEP scale does not fully fit into the Tanzanian context, thus suggesting that further research into the adaptation of the scale is needed.

Research on the Theory of Governmental Environmental Regulatory Responsibility

In recent years,the environmental pollution caused by the rapid development of tourist attractions has increasingly become the focus of society,which has triggered scholars to think about the government's responsibility for environmental regulation,and has generated a variety of theories in the academic world.For example,the stakeholder theory extends corporate governance to the regulation of tourism scenic spots,and achieves the purpose of perfecting the environmental regulation of tourism scenic spots by continuously enriching the scope of stakeholders'subjects;the property rights theory analyzes the transaction costs generated by various economic activities in the regulation of tourism scenic spots from macro and micro perspectives,and the public goods theory clarifies the concept,types and characteristics of tourism scenic spots as public goods.Therefore,based on stakeholder theory,property rights theory and public goods theory,this paper explores and clarifies the content of the government's responsibility in the environmental regulation of tourism scenic spots,and tries to further enrich the theoretical results of the government's environmental regulation responsibility,in order to provide new ideas for the sustainable development of tourism scenic spots from the theoretical point of view.

Animal models of amyotrophic lateral sclerosis： a comparison of model validity

Animal models are necessary to investigate the pathogenic features underlying motor neuron degeneration and for therapeutic development in amyotrophic lateral sclerosis（ALS）. Measures of model validity allow for a critical interpretation of results from each model and caution from over-interpretation of experimental models. Face and construct validity refer to the similarity in phenotype and the proposed causal factor to the human disease, respectively. More recently developed models are restricted by limited phenotype characterization, yet new models hold promise for novel disease insights, thus highlighting their importance. In this article, we evaluate the features of face and construct validity of our new zebrafish model of environmentally-induced motor neuron degeneration and discuss this in the context of current environmental and genetic ALS models, including C9 orf72, mutant Cu/Zn superoxide dismutase 1 and TAR DNA-binding protein 43 mouse and zebrafish models. In this mini-review, we discuss the pros and cons to validity criteria in each model. Our zebrafish model of environmentally-induced motor neuron degeneration displays convincing features of face validity with many hallmarks of ALS-like features, and weakness in construct validity. However, the value of this model may lie in its potential to be more representative of the pathogenic features underlying sporadic ALS cases, where environmental factors may be more likely to be involved in disease etiology than single dominant gene mutations. It may be necessary to compare findings between different strains and species modeling specific genes or environmental factors to confirm findings from ALS animal models and tease out arbitrary strain-and overexpression-specific effects.

Flash flood susceptibility mapping using a novel deep learning model based on deep belief network,back propagation and genetic algorithm

Flash floods are responsible for loss of life and considerable property damage in many countries.Flood susceptibility maps contribute to flood risk reduction in areas that are prone to this hazard if appropriately used by landuse planners and emergency managers.The main objective of this study is to prepare an accurate flood susceptibility map for the Haraz watershed in Iran using a novel modeling approach(DBPGA)based on Deep Belief Network(DBN)with Back Propagation(BP)algorithm optimized by the Genetic Algorithm(GA).For this task,a database comprising ten conditioning factors and 194 flood locations was created using the One-R Attribute Evaluation(ORAE)technique.Various well-known machine learning and optimization algorithms were used as benchmarks to compare the prediction accuracy of the proposed model.Statistical metrics include sensitivity,specificity accuracy,root mean square error(RMSE),and area under the receiver operatic characteristic curve(AUC)were used to assess the validity of the proposed model.The result shows that the proposed model has the highest goodness-of-fit(AUC=0.989)and prediction accuracy(AUC=0.985),and based on the validation dataset it outperforms benchmark models including LR(0.885),LMT(0.934),BLR(0.936),ADT(0.976),NBT(0.974),REPTree(0.811),ANFIS-BAT(0.944),ANFIS-CA(0.921),ANFIS-IWO(0.939),ANFIS-ICA(0.947),and ANFIS-FA(0.917).We conclude that the DBPGA model is an excellent alternative tool for predicting flash flood susceptibility for other regions prone to flash floods.

SCALE AND TIME EFFECTS ON MATHEMATICAL MODELS FOR TRANSPORT IN THE ENVIRONMENT

The purpose of this paper is to analyse mathematical models used in environmental modelling. Following a brief survey of the development in modelling scale- and time-dependent dispersion processes in the environment, this paper compares three similarity solutions, one of which is a solution of the generalized Feller equation （GF） with fractal parameters, and the other two for the newly-developed generalized Fokker-Planck equation （GFP）. The three solutions are derived with parameters having physical significance. Data from field experiments are used to verify the solutions. The analyses indicate that the solutions of both GF and GFP represent the physically meaningful natural processes, and simulate the realistic shapes of tracer breakthrough curves.

Unsuspected implications arising from assumptions in simulations: insights from recasting a forest growth model in system dynamics

Background:Familiarity with a simulation platform can seduce modellers into accepting untested assumptions for convenience of implementation.These assumptions may have consequences greater than commonly suspected,and it is important that modellers remain mindful of assumptions and remain diligent with sensitivity testing.Methods:Familiarity with a technique can lead to complacency,and alternative approaches and software can reveal untested assumptions.Visual modelling environments based on system dynamics may help to make critical assumptions more evident by offering an accessible visual overview and empowering a focus on representational rather than computational efficiency.This capacity is illustrated using a cohort-based forest growth model developed for mixed species forest.Results:The alternative model implementation revealed that untested assumptions in the original model could have substantial influence on simulated outcomes.Conclusions:An important implication is that modellers should remain conscious of all assumptions,consider alternative implementations that reveal assumptions more clearly,and conduct sensitivity tests to inform decisions.

Study on the Emission Reduction Effect of Environmental Protection Tax—An Empirical Study Based on the Change of Pollution Charge Standard in China?

This paper reflects the actual effect of China’s environmental protection tax by empirically analyzing the environmental effect of the emission fee, in order to provide reference for China’s environmental tax reform. Based on the traditional environmental “Kuznets” model, the factor of environmental tax is added to verify the effect of environmental governance of environmental tax. The results show that: 1) the improvement of sulfur dioxide emission charge standard can effectively inhibit industrial sulfur dioxide emission, which verifies the existence of environmental effect of pollution levy policies. 2) The improvement of sewage charge standard has better inhibitory effect on sulfur dioxide emission per unit GDP than on sulfur dioxide emission. 3) There is regional heterogeneity in the “emission reduction” effect of sulfur dioxide emission charges in the eastern, central and western regions of China. Pollutants should be taxed differently according to regional differences. 4) Economic growth and sulfur dioxide emission show an inverted “U” shape, China is still in the stage before the inflection point of EKC. Economic growth still takes environmental damage as the cost, and the “emission reduction” effect of technological progress is not ideal, which reveals the urgency of increasing technological development in the field of green environmental protection under the current situation.

A New model to forecast fishing ground of Scomber japonicus in the Yellow Sea and East China Sea

The pelagic species is closely related to the marine environmental factors, and establishment of forecasting model of fishing ground with high accuracy is an important content for pelagic fishery. The chub mackerel（Scomber japonicus） in the Yellow Sea and East China Sea is an important fishing target for Chinese lighting purse seine fishery. Based on the fishery data from China＇s mainland large-type lighting purse seine fishery for chub mackerel during the period of 2003 to 2010 and the environmental data including sea surface temperature（SST）, gradient of the sea surface temperature（GSST）, sea surface height（SSH） and geostrophic velocity（GV）, we attempt to establish one new forecasting model of fishing ground based on boosted regression trees. In this study, the fishing areas with fishing effort is considered as one fishing ground, and the areas with no fishing ground are randomly selected from a background field, in which the fishing areas have no records in the logbooks. The performance of the forecasting model of fishing ground is evaluated with the testing data from the actual fishing data in 2011. The results show that the forecasting model of fishing ground has a high prediction performance, and the area under receiver operating curve（AUC） attains 0.897. The predicted fishing grounds are coincided with the actual fishing locations in 2011, and the movement route is also the same as the shift of fishing vessels, which indicates that this forecasting model based on the boosted regression trees can be used to effectively forecast the fishing ground of chub mackerel in the Yellow Sea and East China Sea.

RESEARCH AND PRACTICE FOR MANUFACTURING ENVIRONMENT MODELLING TECHNOLOGY OF CIMS

An abstract model and representation method for manufacturing environment is presented based on analysis of process planning tasks and factory configuration capable of handling the process plans. This model has been proved to be applicable to the generative process planning and to shopflow control information integration. A general manufacturing environment modelling tool has been developed under the X-window support to verity the mentioned model and modelling technology.

Meteoroid and Space Debris Risk Assessment for Satellites Orbiting the Earth/Moon

Interplanetary meteoroids and space debris can impact satellites orbiting the Earth or spacecraft traveling to the Moon.Targeting China Space Station(CSS),7 satellites selected from the constellation of Beidou Navigation Satellite System Phase III(BDS-3),and 3 spacecraft orbiting the Moon,we have adopted in the paper the Meteoroid Engineering Model 3,Divine-Staubach meteoroid environment model,and Jenniskens-McBride meteoroid steam model to analyze the meteoroid environment with the mass range of 10–6~10 g.Orbital Debris Engineering Model 3.1 space debris model is used to analyze the orbital debris environment faced by these satellites.The flux of space debris with a size larger than 100μm is compared with that of the meteoroids.The results show that the space debris flux encountered by China Space Station is much higher than that of the meteoroids with sizes in the above range.And quite the opposite,the meteoroids flux impacting the 7 satellites from the BDS-3 is higher.Upon adopting the double-layer Whipple protection measure,the catastrophic collision flux of these satellites encountering meteoroids is about 10–6 times of that without protection,or even less,implying that the Whipple protection effectively guarantees the safety of the satellites in orbit.Besides,it is also found that the flux of the high-density meteoroid population encountered by each satellite is greater than that of the low-density population,whereas the impact velocity is lower for each satellite.These results can aid the orbit selection and the protection design for satellites and spacecraft.

Water Quality Index Using Modified Random Forest Technique: Assessing Novel Input Features

Water quality analysis is essential to understand the ecological status of aquatic life.Conventional water quality index(WQI)assessment methods are limited to features such as water acidic or basicity(pH),dissolved oxygen(DO),biological oxygen demand(BOD),chemical oxygen demand(COD),ammoniacal nitrogen(NH3-N),and suspended solids(SS).These features are often insufficient to represent the water quality of a heavy metal–polluted river.Therefore,this paper aims to explore and analyze novel input features in order to formulate an improved WQI.In this work,prospective insights on the feasibility of alternative water quality input variables as new discriminant features are discussed.The new discriminant features are a step toward formulating adaptive water quality parameters according to the land use activities surrounding the river.The results and analysis obtained from this study have proven the possibility of predicting WQI using new input features.This work analyzes 17 new input features,namely conductivity(COND),salinity(SAL),turbidity(TUR),dissolved solids(DS),nitrate(NO3),chloride(Cl),phosphate(PO4),arsenic(As),chromium(Cr),zinc(Zn),calcium(Ca),iron(Fe),potassium(K),magnesium(Mg),sodium(Na),E.coli,and total coliform,in predicting WQI using machine learning techniques.Five regression algorithms-random forest(RF),AdaBoost,support vector regression(SVR),decision tree regression(DTR),and multilayer perception(MLP)-are applied for preliminary model selection.The results show that the RF algorithm exhibits better prediction performance,with R2 of 0.974.Then,this work proposes a modified RF by incorporating the synthetic minority oversampling technique(SMOTE)into the conventional RF method.The proposed modified RF method is shown to achieve 77.68%,74%,69%,and 71%accuracy,precision,recall,and F1-score,respectively.In addition,the sensitivity analysis is included to highlight the importance of the turbidity variable in WQI prediction.The results of sensitivity analysis highlight the importance of certain water quality variables that are not present in the conventional WQI formulation.