Suitable Distribution Research Articles

Projecting spatiotemporal dynamics of severe fever with thrombocytopenia syndrome in the mainland of China.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with increasing incidence and geographic extent. The extent to which global climate change affects the incidence of SFTS disease remains obscure. We use an integrated multi-model, multi-scenario framework to assess the impact of global climate change on SFTS disease in China. The spatial distribution of habitat suitability for the tick Haemaphysalis longicornis was predicted by applying a boosted regression tree model under four alternative climate change scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) for the periods 2030-2039, 2050-2059, and 2080-2089. We incorporate the SFTS cases in the mainland of China from 2010 to 2019 with environmental variables and the projected distribution of H. longicornis into a generalized additive model to explore the current and future spatiotemporal dynamics of SFTS. Our results demonstrate an expanded geographic distribution of H. longicornis toward Northern and Northwestern China, showing a more pronounced change under the RCP8.5 scenario. In contrast, the environmental suitability of H. longicornis is predicted to be reduced in Central and Eastern China. The SFTS incidence in three time periods (2030-2039, 2050-2059, and 2080-2089) is predicted to be increased as compared to the 2010s in the context of various RCPs. A heterogeneous trend across provinces, however, was observed, when an increased incidence in Liaoning and Shandong provinces, while decreased incidence in Henan province is predicted. Notably, we predict possible outbreaks in Xinjiang and Yunnan in the future, where only sporadic cases have been reported previously. These findings highlight the need for tick control and population awareness of SFTS in endemic regions, and enhanced monitoring in potential risk areas.

Statistical Analysis and Distribution Modeling of Rainfall Data in Flood-Prone Regions of Karnataka State

This research paper presents a comprehensive analysis of southwest monsoon rainfall data in flood-prone regions of Karnataka State, employing suitable statistical techniques and data distribution modeling. The detailed analysis of the dataset helped in understanding rainfall patterns, which is essential in identifying flood risks in Karnataka.The analysis includes the computation of descriptive statistics, exploration of data stationarity and the application of distribution models to characterize rainfall patterns. Maximum likelihood estimator has been used to estimate the parameters involved in the data distribution modelling. Further, hypothesis tests were conducted to assess the goodness-of-fit of these distribution models. These models are found to be suitable for the dataset in comparison with the Gaussian models.

Impacts of Climate Changes on Geographic Distribution of Primula filchnerae, an Endangered Herb in China.

Primula filchnerae, an endangered plant endemic to China, has drawn people's attention in recent years due to its ornamental value in flower. It was rarely recorded since being described in 1902, but it was rediscovered in 2009 and is now known from a limited number of sites located in Hubei and Shaanxi Provinces. Since the species is still poorly known, a number of unanswered questions arise related to it: How has P. filchnerae responded to past climate change and how might it respond in the future? Why was P. filchmerae so rarely collected during the past century? We assembled geographic coordinates for P. filchnerae through the field surveys and website searches, and then used a maximum entropy model (MaxEnt) to simulate its potential suitable distribution in six periods with varied carbon emission levels by combining bioclimatic and environmental factors. MaxEnt showed that Min Temperature of the Coldest Month (bio6) and Precipitation of the Coldest Quarter (bio19) affected P. filchnerae's distribution most, with an aggregate contribution >60% and suitable ranges above -5 °C and below 40 mm, respectively. We also analyzed potential habitat distribution in various periods with differing impacts of climate change compared to today's suitable habitats, and in most cases, Shaanxi and Sichuan remained the most stable areas and with possible expansion to the north under various carbon emission scenarios, but the 2050s SSP5-8.5 scenario may be an exception. Moreover, we used MaxEnt to evaluate population shifts, with various scenarios indicating that geometric center would be concentrated in Sichuan Province in China. Finally, conservation strategies are suggested, including the creation of protected areas, long-term monitoring, raising public awareness of plant conservation, situ conservation measures, assisted migration, and species introduction. This study demonstrates how P. filchnerae may have adapted to changes in different periods and provides a scientific basis for germplasm conservation and management.

Research on a Multi-Species Combined Habitat Suitability Assessment Method for Various Fish Species

To reveal the evolution of habitat distribution for multiple fish species in the lower reaches of the Gongzui Hydropower Station, this study conducted a catch survey to determine the target species of the reach. Based on their suitability curves, a combined suitability assessment model for multiple fish species was constructed. The reliability of the model was verified by combining acoustic observations of flow fields and fish distribution in specific flow conditions. A two-dimensional hydrodynamic model was coupled to quantitatively analyze the distribution characteristics of fish habitat patches under different flow conditions. The results indicate that the correlation coefficient between the multi-species comprehensive suitability index and the number of fish is 0.676, which indicates that the model can better evaluate the distribution of multiple fish habitats in the study river reach; the weighted usable area (WUA) decreased as the discharge increased; from low flow condition (<800 m3/s) to high flow condition (>2000 m3/s), the patch area of suitable habitat decreased from 11,424 m2 to 1268 m2, and the connectivity between patches also showed a downward trend; and the habitat shifted to the near-shore area of the downstream wider and shallower section, which was highly correlated with the migration process of low-depth and low-velocity areas. The model proposed in this study can establish a rapid response between the suitable habitat distribution of multiple fish species and discharge conditions, which can provide a research method for quantitative evaluation of multi-species habitats in river, and make a significant contribution to the sustainable development of riverine fisheries resources and river water ecology.

Study on suitability and spatial distribution of human settlement environment in arid areas based on GIS and analytic hierarchy process

IntroductionScientific evaluation of the suitability of human settlement in arid areas and a grasp of their spatial differentiation characteristics are of great significance for the implementation of regional human settlement environment (HSE) improvement according to local conditions.MethodsIn this study, we took Gansu Province (GS), a typical arid area in China, as the research object. First, based on field research, we used the analytic hierarchy process to determine the weights of 12 evaluation indicators and build an HSE evaluation model from the two dimensions of nature and humanities. Then, we conduct a comprehensive evaluation of each factor based on the GIS spatial analysis module. Finally, we used the GIS natural breakpoint method and zoning statistics to understand the suitability of the HSE and its spatial distribution characteristics in GS Province.ResultsThe study findings can be summarized as follows: (1) The spatial distribution of the suitability of the natural environment in GS Province shows that the east-central part of the province is significantly higher than the northwestern, and there is a big difference between localities. (2) The comprehensive suitability of human settlement in GS Province appears as a spatial distribution characteristic, gradually decreasing from the central urban area to the surrounding areas. The suitability index of the living environment is between 0.26 and 0.71. (3) The area sizes of the five types of suitability are ranked as the following: low suitable (138,502 km2) > moderately suitable (133,761 km2) > critical suitable (97,244 km2) > high suitable (47,459 km2) > unsuitable (38,980km2); in 14 cities, the average value of habitat suitability index is more than 0.5 accounting for 42.9%.DiscussionOur research not only fills a gap in the research of human settlement in arid zones but also provides policy support for government departments to improve human settlement.

Potential Global Distribution of the Invasive Mosquito Aedes koreicus under a Changing Climate.

Invasive alien species are a growing threat to natural systems, the economy, and human health. Active surveillance and responses that readily suppress newly established colonies are effective actions to mitigate the noxious consequences of biological invasions. Aedes (Hulecoeteomyia) koreicus (Edwards), a mosquito species native to East Asia, has spread to parts of Europe and Central Asia since 2008. In the last decade, Ae. koreicus has been shown to be a competent vector for chikungunya virus and Dirofilaria immitis. However, information about the current and potential distribution of Ae. koreicus is limited. Therefore, to understand the changes in their global distribution and to contribute to the monitoring and control of Ae. koreicus, in this study, the MaxEnt model was used to predict and analyze the current suitable distribution area of Ae. koreicus in the world to provide effective information.

Assessing Flood Risk: LH-Moments Method and Univariate Probability Distributions in Flood Frequency Analysis

This study examines all of the equations necessary to derive the parameters for seven probability distributions of three parameters typically used in flood frequency research, namely the Pearson III (PE3), the generalized extreme value (GEV), the Weibull (W3), the log-normal (LN3), the generalized Pareto Type II (PG), the Rayleigh (RY) and the log-logistic (LL3) distributions, using the higher-order linear moments method (LH-moments). The analysis represents the expansion of previous research whose results were presented in previous materials, and is part of hydrological research aimed at developing a standard for calculating maximum flows based on L-moments and LH-moments. The given methods for calculating the parameters of the examined distributions are used to calculate the maximum flows on Romania’s Prigor River. For both methods, the criterion for selecting the most suitable distribution is represented by the diagram of the L-skewness–L-kurtosis and LH-skewness–LH-kurtosis. The results for Prigor River show that the PG distribution is the best model for the L-moments method, the theoretical values of the statistical indicators being 0.399 and 0.221. The RY distribution is the best model for the LH-moments technique, with values of 0.398 and 0.192 for the two statistical indicators.

Is dirt cheap? The economic costs of failing to meet soil health requirements on smallholder farms

AbstractAgricultural productivity is hindered in smallholder farming systems due to several factors, including farmers’ inability to meet crop‐specific soil requirements. This article focuses on soil suitability for maize production and creates multidimensional soil suitability profiles of smallholder maize plots in Uganda while quantifying forgone production due to cultivation on less‐than‐suitable land and identifying groups of farmers that are disproportionately impacted. The analysis leverages the unique socioeconomic data from a subnational survey conducted in Eastern Uganda, inclusive of plot‐level, objective measures of maize yields and soil attributes. Stochastic frontier models of maize yields are estimated within each soil suitability class to understand differences in returns to inputs, technical efficiency, and potential yield. Farmers cultivating highly suitable soil have the potential to increase their observed yields by as much as 86%, while those at the opposite end of the suitability distribution (i.e., with marginally suitable land) operate closer to the production frontier and can only increase yields by up to 59%, given the current technology set. There is heterogeneity in potential gains across the wealth distribution, with poorer households facing more heavily constrained potential.

Species catalogue of Drymaeus (Mesembrinus) Alberts, 1850 (Gastropoda: Bulimulidae) from Brazil and new data on morphology and distribution of Drymaeus (Mesembrinus) interpunctus (Martens, 1887).

Herein, we attempted to obtain detailed data on the distribution of the species of Drymaeus (Mesembrinus) in Brazil, using biodiversity databases, malacological collections and literature as sources of occurrence records. We provided a catalogue of species, along with distribution maps. We also estimated the suitable distribution of Drymaeus (Mesembrinus) interpunctus using the maximum entropy approach. A detailed description of the anatomy of the soft parts of this species was provided, with new data on the pallial system. For each species we provided information on the compiled data associated with museum collections and the literature. Distribution maps including geographic boundaries, Brazilian biomes and altitude were made with QGIS software 3.16.10 Hannover. For niche modelling, nineteen bioclimatic variables and a topographic variable were used as predictors. The models were performed with MaxEnt version 3.3.3k. Most of the species are represented by scarce material in malacological collections; for some species, these records correspond to type material, indicating that they have not been recollected. Most of the species were represented by shells making anatomical comparison and DNA analysis difficult, limiting our ability to provide new criteria for species delimitation. Our results allowed us to expand the known distribution area for three species, Drymaeus dutaillyi, D. gereti and D. oreades, with new occurrence records in Brazil. The MaxEnt model showed a thin area of high suitability to D. (M.) interpunctus in the Southeastern Brazil, corresponding to the Atlantic Forest. Minimum temperature of the coldest month and mean temperature of coldest quarter were the variables that most influenced the development of the model. Drymaeus interpunctus was described based on specimens collected in Brazil without mention to the exact localities. Herein the new records from databases allowed to expand the known geographic distribution for this species and to infer its potential distribution. Although the type locality of D. interpunctus is in Brazil, the anatomy of the soft parts of specimens from this country was not previously described. The anatomy of the reproductive system of the specimens analyzed herein mostly corresponds to a previous description for specimens from Paraguay, except for the absence of penial sheath and the relative length of the bursa copulatrix duct. The results of niche modeling showed a thin area of high suitability for D. interpunctus and a vast area of moderate suitability, indicating that this species present a niche breadth that favors its occurrence in a range of different biomes, including less suitable areas. The small number of records obtained for most of the species and their restricted ranges associated with habitat destruction may indicate that they are of conservation concern.

Climate change may drive the distribution of tribe Zyginelline pests in China and the Indo-China Peninsula to shift towards higher latitude river-mountain systems.

Tribe Zyginelline leafhoppers can transmit plant viruses and are important pests that affect agriculture, forestry, and animal husbandry, causing serious economic losses. The potential distribution patterns of Zyginellini will change under climate change. Therefore, the best-performing random forest and maximum entropy models among 12 commonly used ecological niche models, alongside an ensemble model, were selected to predict the changes in habitat suitability distribution of Zyginellini under current and future climate scenarios [represented by two shared socio-economic pathways (SSPs), namely SSP126 and SSP585, for three periods (2050s, 2070s, and 2090s)] in China and the Indo-China Peninsula for the first time. The results revealed that the distribution of Zyginellini was mainly dominated by minimum temperature of coldest month. Under current and future climate scenarios, Zyginellini was mostly distributed southeast of the 400 mm equivalent precipitation line in China, and Vietnam. Under the future SSP126 scenario, the alert areas will mainly be concentrated in Hunan, Jiangxi, Zhejiang, Anhui, and Hebei in China, alongside Myanmar and Thailand in the Indo-China Peninsula. Meanwhile, in the SSP585 scenario, the alert areas in China will increase, whereas there will be little change in the Indo-China Peninsula. Interestingly, from the current to the future, the cores of Zyginelline distribution occurred around rivers and mountains, and shifted from Guizhou along the Yuanjiang River system to higher latitudes in Hunan. Zyginellini prefers higher latitude river-mountain systems under climate change. Our results will contribute to effective pest control strategies and biogeographical research for Zyginellini alongside other Cicadellidae insects. © 2023 Society of Chemical Industry.

Experimental study on low-altitude UAV-to-ground propagation characteristics in campus environment

In recent years, unmanned aerial vehicle (UAV)-to-ground wireless channels have become focused areas. Thus a better understanding of UAV-to-ground wireless channel characterizations is critical. The large-scale fading characterization is widely analyzed in many research works. Nevertheless, the small-scale fading characterization of low-altitude UAV-to-ground propagation has not been fully modeled. In this work, the close-in (CI) free space and floating-intercept (FI) path loss models are implemented to characterize large-scale fading. The large-scale parameters, i.e., path loss exponent (PLE), shadow fading standard deviation (STD), and shadow fading correlation coefficient, are carefully extracted, analyzed, and compared. Regarding small-scale fading, Akaike’s Information Criteria (AIC) is used to find the most suitable fading distribution. In addition, fade depth (FD), level crossing rate (LCR), and average fade duration (AFD) are also calculated. The quantitative results and comparisons show a noticeable difference with ground propagation. The parameterized models are helpful for further understanding and deployment of UAV-to-ground wireless communication systems.

Simulation and analysis of red-crowned crane habitat suitability using maximum entropy and information entropy models

The red-crowned crane (Grus japonensis) is a rare waterfowl species that is sensitive to environmental changes in its habitat selection; as such it effectively reflects the variation in wetland landscapes. Therefore, analysis of the habitat suitability for the red-crowned crane can be used to determine the species requirements and to predict its potential habitat distribution, thereby providing a basis for the protection of wetlands and endangered species. In this study, the Landsat satellite remote sensing data of Zhalong Wetland from 1996 to 2019 were used to simulate the nest coordinates of red-crowned cranes using a binary logistic model and to simulate the distribution of suitable habitat via a maximum entropy model. Moreover, an information entropy model was used to examine the yearly changes in habitat suitability and the underlying mechanisms and influencing factors. These two entropy models were combined to simulate the habitat suitability distribution and variation with high accuracy, determine the contribution rates of influencing factors, and provide data for analyzing interannual changes. The following results were obtained. First, the habitat suitability was highest in the center, core area and decreased towards the periphery of Zhalong Wetland. Second, the habitat suitability increased in some regions in the south, decreased in some areas in the north, and remained unchanged in the majority of the peripheral regions. Third, habitat suitability was primarily impacted by landscape patterns, distances to rivers and ditches, and vegetation. Red-crowned cranes preferred to reside far from human disturbance in wetlands near rivers with reeds (Phragmites australis) as the dominant species.

Bayesian-based calibration for water quality model parameters.

To improve the efficiency and accuracy of water quality model parameter calibration and avoid local optima and the phenomenon in which different parameters have the same effect, this paper proposed a novel Bayesian-based water quality model parameter calibration method. Using Bayesian inference, the parameter calibration problem was converted into a posterior probability function sampling problem, which was sampled using the Markov Chain Monte Carlo algorithm. The convergence speed of the calibration was further improved by setting the optimized initial sampling value. The influences of the initial sampling value, Markov chain length, and proposal distribution form on the calibration effect were evaluated using four specific cases. The results indicate that (1) the mean relative error (MRE) of the parameter calibration results of this method is less than 10%, with the calibration MRE of Dx and Dy being 5.3% and 8.3%, respectively; (2) when the parameter sensitivity is low, the calibration effect of this method is relatively poor, with a calibration MRE of 46% for k; (3) the parameter calibration can be completed more efficiently by setting an optimized initial value for the MCMC, choosing a reasonable Markov chain length and a suitable proposal distribution form. PRACTITIONER POINTS: Bayesian-based water quality model parameter calibration method is proposed and posterior probability distribution was sampled using the MCMC algorithm. Parameter calibration can be completed more efficiently by setting an optimized initial value for the MCMC. As a result, efficient and accurate parameter calibration of water quality models was achieved. This method is widely applicable to various models, and the calibration speed depends on the calculation speed of the model.

Optimization of efficiency enhancement of TOPCon cells with boron selective emitter

Silicon solar cells with a tunnel oxide passivating contact (TOPCon) structure are the new mainstream products; however, emitter recombination has become the bottleneck for further improvement. The introduction of selective emitter (SE) technology becomes imperative to address this issue. In this study, the appropriate range of sheet resistance in the light-doped region (230–280 Ω/sq)and the reasonable interval of the diffusion junction depth in the heavy-doped region (1.2–1.3 μm) are presented. The selective emitter with a suitable doping distribution is realized using the mask and etch-back method. Compared to the homogeneous emitter with a sheet resistance of 150 Ω/sq, J0e of 16 fA/cm2, and J0metal-front of 500 fA/cm2, the optimum selective emitter results in a J0e-light doping of 8 fA/cm2, J0e-heavy doping of 45 fA/cm2 and J0metal-front of 213 fA/cm2. Finally, the boron SE-TOPCon cell samples UOC (726.5 mV), FF (84.01%), and efficiency (25.51%) are obtained, compared with the TOPCon cell with homogeneous emitter Uoc (717.6 mV), FF (83.77%) and efficiency (25.17%) of the reference. In addition, the efficiency potential of the boron SE-TOPCon cell (26.02%) at the optimal process conditions is determined based on device simulations. This study provides a feasible technical path for mass-produced TOPCon cells to increase the efficiency to more than 26%.

Application of landslide susceptibility towards urbanization suitability zonation in mountainous settings

Amplified susceptibility to landslides poses challenges to sustainable and equitable urban development. Thus, in this study, we introduce an artificial intelligence and geographic information system-based approach, urbanization suitability zonation (USZ), for spatial assessment of land suitability for urbanization, which accounts multiple factors, including a focus on landslide susceptibility. Further, the proposed USZ is tailored to assess health of current urbanization patterns, depicting the driving factors behind it by establishing a best-case urbanization suitability (BUS) and weighted urbanization suitability (WUS). The BUS portrays a hypothetically ideal land suitability scenario as a function of equally weighted factors, while the WUS portrays land suitability changes when factors are weighted hierarchically. An examination of current development against the BUS provides idealness of current urbanization patterns. The WUS aids in assessing the significance of factors in influencing the current urbanization pattern, and checks its resemblance with the BUS. The mountainous Indian township of Mussoorie is selected as the study area to exercise the USZ by considering seven factors with different weights, and subsequently generated a BUS map and 7 WUS maps (WUS–I to VII), which all display urbanization suitability distribution in five different classes. The BUS map shows that ∼98 % of current development falls in higher-suitability areas, indicating its preferability. Among the different WUS maps, the WUS-II aligns best with the BUS and current built-up, with slope gradient and transportation connectivity as key factors, and according to it, high-suitability areas are generally the central and south-facing slopes, while north-facing slopes are unsuitable, in general.

Prediction of the potentially suitable areas of Leonurus japonicus in China based on future climate change using the optimized MaxEnt model.

Leonurus japonicus Houtt. is a traditional Chinese medicinal plant with high medicinal and edible value. Wild L. japonicus resources have reduced dramatically in recent years. This study predicted the response of distribution range of L. japonicus to climate change in China, which provided scientific basis for the conservation and utilization. In this study, 489 occurrence points of L. japonicus were selected based on GIS technology and spThin package. The default parameters of MaxEnt model were adjusted by using ENMeva1 package of R environment, and the optimized MaxEnt model was used to analyze the distribution of L. japonicus. When the feature combination in the model parameters is hing and the regularization multiplier is 1.5, the MaxEnt model has a higher degree of optimization. With the AUC of 0.830, our model showed a good predictive performance. The results showed that L. japonicus were widely distributed in the current period. The maximum temperature of warmest month, the min temperature of coldest month, the precipitation of wettest month, the precipitation of driest month, and altitude were the main environmental factors affecting the distribution of L. japonicus. Under the three climate change scenarios, the suitable distribution area of L. japonicus will range shift to high latitudes, indicating that the distribution of L. japonicus has a strong response to climate change. The regional change rate is the lowest under the SSP126-2090s scenario and the highest under the SSP585-2090s scenario.

A multi-step approach to evaluate the sustainable use of groundwater resources for human consumption and agriculture

The rapid decline in both quality and availability of freshwater resources on our planet necessitates their thorough assessment to ensure sustainable usage. The growing demand for water in industrial, agricultural, and domestic sectors poses significant challenges to managing both surface and groundwater resources. This study tests and proposes a hybrid evaluation approach to determine Groundwater Quality Indices (GQIs) for irrigation (IRRI), seawater intrusion (SWI), and potability (POT), finalized to the spatial distribution of groundwater suitability involving water quality indicator along with hydrogeological and socio-economic factors. Mean Decrease Accuracy (MDA) and Information Gain Ratio (IGR) were used to state the importance of chosen factors such as level of groundwater above the sea, thickness of the aquifer, land cover, distance from coastline, silt soil content, recharge, distance from river and lagoons, depth to water table from ground, distance from agricultural wells, hydraulic conductivity, and lithology for each quality index, separately. The results of both methods showed that recharge is the most important parameter for GQIIRRI and GQIPOT, while the distance from the coastline and the rivers, are the most important for GQISWI. The spatial modelling of GQIIRRI and GQIPOT in the study area has been achieved applying three machine learning (ML) algorithms: the Boosted Regression Tree (BRT), the Random Forest (RF), and the Support Vector Machine (SVM). Validation results showed that RF has the highest prediction for GQIIRRI, while the SVM model has the highest prediction for the GQIPOT index. It is worth to mention that the future utilization and testing of new algorithms could produce even better results. Finally, GQIIRRI and GQIPOT were combined and compared using two combine and overlay methods to prepare a hybrid map of multi-GQIs. The results showed that 69% of the study area is suitable for irrigation and potable use, due to both geogenic and anthropogenic activities which contribute to make some water resources unsuitable for either use. Specifically, the northern, western, and eastern portions of the study area are in the “very high and high quality” classes while the southern portion shows “very low and low quality” classes. In conclusion, the developed map and approach can serve as a practical guide for enhancing groundwater management, identifying suitable areas for various uses and pinpointing regions requiring improved management practices.

A Distribution Network Planning Method Considering the Distributed Energy Resource Flexibility of Virtual Power Plants

To solve the overload problem caused by the high proportion of renewable energy into the power system, it is particularly important to find a suitable distribution network planning scheme. Existing studies have effectively reduced the planning cost by incorporating virtual power plants into the distribution planning process, but there is no quantitative analysis of the flexible resources inside the virtual power plant. At the same time, the traditional planning process does not pay much attention to the acquisition of photovoltaic and load data. Therefore, in this paper, we propose a distribution network planning method considering the flexibility of distributed energy resources in virtual power plants. Firstly, taking the distribution network planning including the virtual power plant as the research object, the flexibility of the distributed energy resource of the virtual power plant was quantified. Then, in order to achieve the goal of minimizing the operating cost of system planning, a distribution network planning model considering the flexibility of distributed energy resources in the virtual power plant is established. In this model, the impact of virtual power plants flexibility on the distribution network planning process is mainly considered. Secondly, this paper uses the improved k-means clustering algorithm to obtain the typical data of PV and load. The algorithm effectively overcomes the impact of PV and load output fluctuations on the planning process. Finally, the simulation results show that the proposed planning model can effectively reduce the operation cost of system planning by using distributed energy storage system and distributed energy resource flexibility. At the same time, the PV absorption rate of the PV power station inside the distribution network is improved.

A Geospatial Analysis Model for the Selection of Post-Mining Land Uses in Surface Lignite Mines: Application in the Ptolemais Mines, Greece

Among the procedures included in surface mines’ closure, the determination of post-mining land uses constitutes one of the early but primary steps. This research aims to develop an algorithm for the selection of the most suitable land use spatial distribution in the post-mining area of a surface lignite mine in northern Greece. Considering the already reclaimed areas and the local socioeconomic conditions, six distinct criteria that concern physical local characteristics were selected and, in turn, spatially combined with parameters affecting the mining area. Mining experts attributed weights to the criteria regarding their importance for the examined land uses. The six criteria concerned physical local characteristics (slope, elevation, and distance from villages, rivers, roads, and transmission lines), while the parameters affecting the mining area referred to the type of ground (undisturbed or graded areas), existing infrastructure, and mine closure planning, emphasizing the final landscape of the mining area. The investigated land uses encompassed agricultural, forest, industrial (including buildings, infrastructure, and photovoltaic parks), and recreational parks. Through the application of a fuzzification algorithm within a geographical information system (GIS) environment, four land use suitability maps were generated, which were subsequently overlaid to derive a comprehensive suitability map. The final suitability map was derived from the integration of the mining parameters as spatial information into the algorithm. The findings indicate that, even though the land use suitability analysis could be derived from a mathematical model, the integration of qualitative information related to the mining specifications is necessary to produce more reliable results. The proposed algorithm can be used as a useful tool by decision-makers in the mining industry to plan post-mining reclamation based on suitable criteria.

Proton-blocking tadpole-type anion exchange membranes for acid recovery by electrodialysis

Three kinds of long-side-chain-modified tadpole-type anion exchange membranes (AEMs) named QPEK-DMODAs with microphase separated structures designed for electrodialysis (ED) acid recovery were fabricated from N,N-dimethyloctadecylamine (DMODA) as quaternization agent and poly(arylene ether ketone) (PEK) as skeleton, which is the copolymer of 2,2′,6,6′-tetramethyl biphenol (TMBP) and 4,4′-difluorobenzophenone (DFBP). QPEK-DMODAs were characterized systematically including basic structures and properties, ED recovery performance of H2SO4 solutions without or with metal impurities, and corrosive acid stability. The well-defined microphase separation structure of QPEK-DMODA-3 is formed by the suitable distribution of tadpole ionic groups at the highest IEC of 2.09 mmol g−1. The aggregate structure offers the membrane competent mechanical stability, ion conductivity and permselectivity, as well as low energy consumption and water transport ratio at the ED process. QPEK-DMODA-3 exhibits higher current efficiency (54.58 %) and recovery H+ concentration (1.74 M) than those of QPEK-DMODA-1, QPEK-DMODA-2 and commercial AMX with comparable energy consumption to that of AMX under the ED conditions of Fe2+ absence. Moreover, the Fe2+ removal rate (88.74 %) and ion selectivity (S = 57.32) of QPEK-DMODA-3 are remarkably higher than those of AMX (67.10 % and 17.32) without the scarce of recovery efficiencies in the ED recovery tests of 0.50 M H2SO4 solution containing 0.10 M of Fe2+. The combination of the comparable tolerance to strong acid to that of AMX and the confirmed good ED recovery performances declares a strong potential of tadpole-type QPEK-DMODA-3 in waste acid recovery by electrodialysis.