Showing papers in "Environmental Monitoring and Assessment in 2018"

Groundwater potential mapping using C5.0, random forest, and multivariate adaptive regression spline models in GIS

Abstract: Ever increasing demand for water resources for different purposes makes it essential to have better understanding and knowledge about water resources. As known, groundwater resources are one of the main water resources especially in countries with arid climatic condition. Thus, this study seeks to provide groundwater potential maps (GPMs) employing new algorithms. Accordingly, this study aims to validate the performance of C5.0, random forest (RF), and multivariate adaptive regression splines (MARS) algorithms for generating GPMs in the eastern part of Mashhad Plain, Iran. For this purpose, a dataset was produced consisting of spring locations as indicator and groundwater-conditioning factors (GCFs) as input. In this research, 13 GCFs were selected including altitude, slope aspect, slope angle, plan curvature, profile curvature, topographic wetness index (TWI), slope length, distance from rivers and faults, rivers and faults density, land use, and lithology. The mentioned dataset was divided into two classes of training and validation with 70 and 30% of the springs, respectively. Then, C5.0, RF, and MARS algorithms were employed using R statistical software, and the final values were transformed into GPMs. Finally, two evaluation criteria including Kappa and area under receiver operating characteristics curve (AUC-ROC) were calculated. According to the findings of this research, MARS had the best performance with AUC-ROC of 84.2%, followed by RF and C5.0 algorithms with AUC-ROC values of 79.7 and 77.3%, respectively. The results indicated that AUC-ROC values for the employed models are more than 70% which shows their acceptable performance. As a conclusion, the produced methodology could be used in other geographical areas. GPMs could be used by water resource managers and related organizations to accelerate and facilitate water resource exploitation.

Microplastics in municipal wastewater treatment plants in Turkey: a comparison of the influent and secondary effluent concentrations.

Abstract: Wastewater treatment plants are one of the primary pathways through which microplastics enter aquatic environments. In this study, we have determined the microplastic concentrations of the influent and secondary effluent water of two wastewater treatment plants in Turkey. For this purpose, we have taken samples of the influent and effluent water of Seyhan and Yuregir wastewater treatment facilities for 6 days in August 2017 and determined their microplastics’ content both visually and using μ-Raman spectroscopy. The results showed that the influent of the wastewater treatment contained 1 million–6.5 million particles per day, while the effluent contained 220,000–1.5 million particles per day. The removal rate of microplastics was found to be between 73 and 79%. In total, seven different types of polymers were detected. The most frequently observed polymer type was polyester.

Real - time water quality monitoring using Internet of Things in SCADA

Abstract: Water pollution is the root cause for many diseases in the world It is necessary to measure water quality using sensors for prevention of water pollution However, the related works remain the problems of communication, mobility, scalability, and accuracy In this paper, we propose a new Supervisory Control and Data Acquisition (SCADA) system that integrates with the Internet of Things (IoT) technology for real-time water quality monitoring It aims to determine the contamination of water, leakage in pipeline, and also automatic measure of parameters (such as temperature sensor, flow sensor, color sensor) in real time using Arduino Atmega 368 using Global System for Mobile Communication (GSM) module The system is applied in the Tirunelveli Corporation (Metro city of Tamilnadu state, India) for automatic capturing of sensor data (pressure, pH, level, and energy sensors) SCADA system is fine-tuned with additional sensors and reduced cost The results show that the proposed system outperforms the existing ones and produces better results SCADA captures the real-time accurate sensor values of flow, temperature, and color and turbidity through the GSM communication

A study on the determination of the natural park's sustainable tourism potential.

Abstract: The surface site of Yesilyuva Nature Park encompasses natural, social, economic, and cultural characteristics and has become a marker of the region's natural and cultural heritage. To support the preservation of this site, promotional activities should be planned. In this study, because of tourism and related opinions of residents and visitors alike in terms of their natural determination, an important cultural and historical feature is aimed at evaluating the tourism potential of Yesilyuva Nature Park. This framework is designed to establish prospective tourism sustainability. As a result, Yesilyuva Nature Park's natural and cultural properties have been determined to be suitable for sustainable tourism activities using geographic information systems (GIS). This protection in the field, which balances sustainability and landscape design, will provide for the development of tourism activities. In the Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis and survey, residents and visitors reported that the most important feature of the Yesilyuva Nature Park was its natural beauty. Visitors often come to observe traditional and natural life and to engage in tourism activities. All the data, which includes maps derived from GIS, represents landscape planning for sustainable tourism areas in Yesilyuva Nature Park.

Monitoring soil for sustainable development and land degradation neutrality.

Abstract: The adoption of the 17 sustainable development goals (SDGs) listed in the 2030 Agenda for Sustainable Development by the United Nations urged the scientific community to generate information for planning and monitoring socioeconomic development and the underlying environmental compartments. SDGs 2, 3, 6, 11, 13, 14, and 15 have targets which commend direct consideration of soil resources. There are five groups of SDGs and assigned SDG indicators where soil plays a central role. Frameworks of soil-related sustainable development goals and related indicators which can be monitored in current monitoring schemes are proposed.

Soil heavy metal pollution and risk assessment associated with the Zn-Pb mining region in Yunnan, Southwest China

Abstract: The environmental assessment and identification of sources of heavy metals in Zn-Pb ore deposits are important steps for the effective prevention of subsequent contamination and for the development of corrective measures. The concentrations of eight heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in soils from 40 sampling points around the Jinding Zn-Pb mine in Yunnan, China, were analyzed. An environmental quality assessment of the obtained data was performed using five different contamination and pollution indexes. Statistical analyses were performed to identify the relations among the heavy metals and the pH in soils and possible sources of pollution. The concentrations of As, Cd, Pb, and Zn were extremely high, and 23, 95, 25, and 35% of the samples, respectively, exceeded the heavy metal limits set in the Chinese Environmental Quality Standard for Soils (GB15618-1995, grade III). According to the contamination and pollution indexes, environmental risks in the area are high or extremely high. The highest risk is represented by Cd contamination, the median concentration of which exceeds the GB15618-1995 limit. Based on the combination of statistical analyses and geostatistical mapping, we identified three groups of heavy metals that originate from different sources. The main sources of As, Cd, Pb, Zn, and Cu are mining activities, airborne particulates from smelters, and the weathering of tailings. The main sources of Hg are dust fallout and gaseous emissions from smelters and tailing dams. Cr and Ni originate from lithogenic sources.

Indexing method for assessment of pollution potential of leachate from non-engineered landfill sites and its effect on ground water quality.

Abstract: Dumping of solid waste in a non-engineered landfill site often leads to contamination of ground water due to leachate percolation into ground water. The present paper assesses the pollution potential of leachate generated from three non-engineered landfill sites located in the Tricity region (one each in cities of Chandigarh, Mohali and Panchkula) of Northern India and its possible effects of contamination of groundwater. Analysis of physico-chemical properties of leachate from all the three landfill sites and the surrounding groundwater samples from five different downwind distances from each of the landfill sites were collected and tested to determine the leachate pollution index (LPI) and the water quality index (WQI). The Leachate Pollution Index values of 26.1, 27 and 27.8 respectively for landfill sites of Chandigarh (CHD), Mohali (MOH) and Panchkula (PKL) cities showed that the leachate generated are contaminated. The average pH values of the leachate samples over the sampling period (9.2 for CHD, 8.97 for MOH and 8.9 for PKL) show an alkaline nature indicating that all the three landfill sites could be classified as mature to old stage. The WQI calculated over the different downwind distances from the contamination sites showed that the quality of the groundwater improved with an increase in the downwind distance. Principal component analysis (PCA) carried out established major components mainly from natural and anthropogenic sources with cumulative variance of 88% for Chandigarh, 87.1% for Mohali and 87.8% for Panchkula. Hierarchical cluster analysis (HCA) identifies three distinct cluster types for the groundwater samples. These clusters corresponds to a relatively low pollution, moderate pollution and high pollution regions. It is suggested that all the three non-engineered landfill sites be converted to engineered landfill sites to prevent groundwater contamination and also new sites be considered for construction of these engineered landfill sites as the present dumpsites are nearing the end of their lifespan capacity.

Evaluation of surface water quality by using Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) method and discriminant analysis method: a case study Coruh River Basin

Abstract: In this study, the water quality of the Coruh River Basin, which is located in the Eastern Black Sea Region of Turkey, was evaluated. The water quality data measurement results obtained by the State Hydraulic Works 26th Regional Directorate from four different sites over a course of 4 years between the years 2011 and 2014 in the Coruh River Basin were used as the data. In this study, the water quality was evaluated by using the Canadian Council of Ministers of the Environmental Water Quality Index (CCME WQI) method and discriminant analysis (DA). The water quality of the Coruh River Basin was calculated as 30.4 and 71.35 by using the CCME WQI and classified as “poor,” “marginal,” and “fair”. These values show that the water of the Coruh River Basin is degraded and under threat and its overall quality is not close to natural or desired levels. The monitoring sites were divided into two groups by the cluster analysis (CA). DA is a multivariate analysis technique used to divide individuals or objects into different groups and assign them into predetermined groups. As a result of DA, calcium (Ca) and sulfate (SO4) were determined to be significant parameters in the determination of the water quality of the Coruh River Basin. The success of DA depends on the percentage of correct classification. As a result of the analysis, 23% of the parameters in the first measurement point, 69.2% of the parameters in the second and third measurement points, and 76.9% of the parameters in the fourth measurement point were classified correctly. Since the second measurement point is the discharge point of a copper mine, it can be said that the water quality parameters measured may provide accurate results in detecting pollution at this point.

Heavy metal concentrations in roadside soil and street dust from Petra region, Jordan.

Abstract: Concentrations of Cd, Cu, Fe, Pb, and Zn were measured in the samples of street dust and surface roadside soil before Jordan switched to unleaded fuel usage. The samples were collected from Petra, the most tourist-attractive site in Jordan. The samples were analyzed for heavy metals by atomic absorption spectrophotometry. Our results show that the distribution of metals in the soil samples is affected by wind direction in the investigated area. The highest level of metals was found in the eastern parts of the roads due to the westerly-dominant wind in the studied area. The contamination levels of metals decrease as the distance from the edge of the road increases. In the roadside soil samples, the means for the concentrations of the metals at 1 m from the east side of the main road are 1.0, 19.1, 3791.4, 177.0, and 129.0 mg kg-1 for Cd, Cu, Fe, Pb, and Zn, respectively. In the samples of street dust, the means of the concentrations of the metals in the investigated area are 9.7, 11.8, 4694.4, 31.6, and 24.8 mg kg-1 for Cd, Cu, Fe, Pb, and Zn, respectively. In conclusion, the lithogenic origins (traffic emissions) are responsible for the diffusion of these metals in the studied region.

Erodibility of calcareous soils as influenced by land use and intrinsic soil properties in a semiarid region of central Iran.

Abstract: The most important properties affecting the soil loss and runoff were investigated, and the effects of land use on the soil properties, together with the erodibility indices in a semiarid zone, central Iran, were evaluated. The locations of 100 positions were acquired by cLHS and 0–5-cm surface soil layer samples were used for laboratory analyses from the Borujen Region, Chaharmahal-Va-Bakhtiari Province, central Iran. To measure in situ runoff and soil erodibility of three different land uses comprising dryland, irrigated farming, and rangeland, a portable rainfall simulator was used. The results showed that the high variations (coefficient of variation, CV) were obtained for electrical conductivity (EC), mean weight diameter (MWD), soil organic carbon (SOC), and soil erodibility indices including runoff volume, soil loss, and sediment concentration (CV ~ 43.6–77.4%). Soil erodibility indices showed positive and significant correlations with bulk density and negative correlations with SOC, MWD, clay content, and soil shear strength in the area under investigation. The values of runoff in the dryland, irrigated farming, and rangeland were found 1.5, 28.9, and 58.7 cm3; soil loss in the dryland, irrigated farming, and rangeland were observed 0.25, 2.96, and 76.8 g; and the amount of sediment concentration in the dryland, irrigated farming, and rangeland were found 0.01, 0.11, and 0.15 g cm−3. It is suggested that further investigations should be carried out on soil erodibility and the potential of sediment yield in various land uses with varying topography and soil properties in semiarid regions of Iran facing the high risk of soil loss.

Identifying and assessing environmental awareness of hotel and restaurant employees' attitudes in the Amasra District of Bartin.

Abstract: Environmental damage occurring on individual, institutional, and societal levels is one of the major problems in the world and results from mostly unconscious human behavior. This damage poses serious threats to human health and other habitats. The aim of this study is to determine the level of environmental awareness of hotel and restaurant employees in the Amasra District of Bartin, Turkey. For this purpose, a descriptive survey method is used to measure 16 items with a 5-point Likert scale. Data are obtained from 200 employees in the hotels and restaurants as of 2015. The reliability coefficient is found to be 0.74. This data reveals that only 43% of hotels and 72% of restaurants in Amasra have recycling bins. Males and Bachelor's degree holders have more environmental awareness. Enterprises established after 2011 follow popular journals related to environment more than those before 2011. As a result, it is essential to organize educational meetings and seminars related to environmental awareness for hotel and restaurant employees in order to improve the tourism industry's environmental impact. The results show that the legislation has resulted in general environmental awareness and that the organizations are willing to change their business processes and environmental strategies. Nevertheless, despite their actions, there is little awareness of the benefits that can result from cost reductions resulting from environmentally friendly practices. Those affected by their suppliers act to reduce waste but do not deploy formal environmental management systems or use environmental messages to market their goods or services.

Assessment of ozone toxicity among 14 Indian wheat cultivars under field conditions: growth and productivity

Abstract: Tropospheric ozone (O3) is a well-known threat to global agricultural production. Wheat (Triticum aestivum L.) is the second most important staple crop in India, although little is known about intra-specific variability of Indian wheat cultivars in terms of their sensitivity against O3. In this study, 14 wheat cultivars widely grown in India were exposed to 30 ppb elevated O3 above ambient level using open top chambers to evaluate their response against O3 stress. Different growth and physiological parameters, foliar injury and grain yield were evaluated to assess the sensitivity of cultivars and classified them on the basis of their cumulative stress response index (CSRI). Due to elevated O3, growth parameters, plant biomass, and photosynthetic rates were negatively affected, whereas variable reductions in yield were observed among the test cultivars. Based on CSRI values, HD 2987, DBW 50, DBW 77, and PBW 550 were classified as O3 sensitive; HD 2967, NIAW 34, HD 3059, PBW 502, HUW 213, and HUW 251 as intermediately sensitive, while HUW12, KUNDAN, HUW 55, and KHARCHIYA 65 were found to be O3-tolerant cultivars. Cultivars released after year 2000 were found to be more sensitive compared to earlier released cultivars. Path analysis approach showed that leaf area, plant biomass, stomatal conductance, net assimilation rate, and absolute growth rate were the most important variables influencing yield under O3 stress. Findings of the current study highlight the importance of assessing differential sensitivity and tolerance of wheat cultivars and response of different traits in developing resistance against elevated O3.

An assessment of commonly employed satellite-based remote sensors for mapping mangrove species in Mexico using an NDVI-based classification scheme.

Abstract: Optimizing the classification accuracy of a mangrove forest is of utmost importance for conservation practitioners. Mangrove forest mapping using satellite-based remote sensing techniques is by far the most common method of classification currently used given the logistical difficulties of field endeavors in these forested wetlands. However, there is now an abundance of options from which to choose in regards to satellite sensors, which has led to substantially different estimations of mangrove forest location and extent with particular concern for degraded systems. The objective of this study was to assess the accuracy of mangrove forest classification using different remotely sensed data sources (i.e., Landsat-8, SPOT-5, Sentinel-2, and WorldView-2) for a system located along the Pacific coast of Mexico. Specifically, we examined a stressed semiarid mangrove forest which offers a variety of conditions such as dead areas, degraded stands, healthy mangroves, and very dense mangrove island formations. The results indicated that Landsat-8 (30 m per pixel) had the lowest overall accuracy at 64% and that WorldView-2 (1.6 m per pixel) had the highest at 93%. Moreover, the SPOT-5 and the Sentinel-2 classifications (10 m per pixel) were very similar having accuracies of 75 and 78%, respectively. In comparison to WorldView-2, the other sensors overestimated the extent of Laguncularia racemosa and underestimated the extent of Rhizophora mangle. When considering such type of sensors, the higher spatial resolution can be particularly important in mapping small mangrove islands that often occur in degraded mangrove systems.

Index-based assessment of suitability of water quality for irrigation purpose under Indian conditions

Abstract: Agriculture is a major sector in India which contributes around 14% of country's gross domestic product (GDP). Being an agriculture-based country, good quality of water for irrigation has been a prime requisite. Highly growing population and accelerated industrial development are causing anthropogenic pollution to both surface and groundwater on one side and geogenic contamination like arsenic, fluoride, high dissolved solids, sodicity, and iron in groundwater on other side. As a result, ensuring safe water quality for the irrigation has become a major challenge to both the central and state governments. The present irrigation water quality standards being followed in India have been set by the Central Pollution Control Board (CPCB) and Central Ground Water Board (CGWB) in the year 2000. These standards are solely based on four parameters, namely electrical conductivity, sodium percentage, sodium absorption ratio, and residual sodium carbonate, which are quite subjective and many times are not capable to exactly decide the quality of irrigation water particularly when there are large variations in the source water quality. Therefore, in the present paper, an indices-based approach is presented for categorization of irrigation water quality. These indices are mathematical equations that transform water quality data into a numeric value, which describes the quality of irrigation water. The proposed irrigation water quality index (IWQI), which is based on 12 parameters, classifies the water into five categories, viz. excellent, good, medium, bad, and very bad in the same manner as given by the CPCB and CGWB. In order to give proper rating to various parameters of the index, weights are computed using Saaty's analytic hierarchy process (AHP)-based multiple criteria decision analysis (MCDA) approach. This approach minimizes the subjectivity in assessment of weights and improves understanding of water quality issues by generating an overall index to describe the status of water quality. The proposed index will be beneficial for the water management authorities in ensuring safe water to the stakeholders.

Unmanned aerial vehicle (UAV)-based monitoring of a landslide: Gallenzerkogel landslide (Ybbs-Lower Austria) case study.

Abstract: In the present study, UAV-based monitoring of the Gallenzerkogel landslide (Ybbs, Lower Austria) was carried out by three flight missions. High-resolution digital elevation models (DEMs), orthophotos, and density point clouds were generated from UAV-based aerial photos via structure-from-motion (SfM). According to ground control points (GCPs), an average of 4 cm root mean square error (RMSE) was found for all models. In addition, light detection and ranging (LIDAR) data from 2009, representing the prefailure topography, was utilized as a digital terrain model (DTM) and digital surface model (DSM). First, the DEM of difference (DoD) between the first UAV flight data and the LIDAR-DTM was determined and according to the generated DoD deformation map, an elevation difference of between − 6.6 and 2 m was found. Over the landslide area, a total of 4380.1 m3 of slope material had been eroded, while 297.4 m3 of the material had accumulated within the most active part of the slope. In addition, 688.3 m3 of the total eroded material had belonged to the road destroyed by the landslide. Because of the vegetation surrounding the landslide area, the Multiscale Model-to-Model Cloud Comparison (M3C2) algorithm was then applied to compare the first and second UAV flight data. After eliminating both the distance uncertainty values of higher than 15 cm and the nonsignificant changes, the M3C2 distance obtained was between − 2.5 and 2.5 m. Moreover, the high-resolution orthophoto generated by the third flight allowed visual monitoring of the ongoing control/stabilization work in the area.

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Abstract: Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.

Using Acer platanoides annual rings to monitor the amount of heavy metals accumulated in air

Abstract: Annual rings are good indicators for determining the increase in the amount of heavy metals in the atmosphere from past to the present. Air pollution has rapidly increased in Ankara over the past 20 years. In particular, there is a serious increase in the concentration of heavy metals that adversely affect human health. In this study, the accumulation of Al, Zn, Cu, Co, Fe, Mn, Cr, Cd, Na, Ca, Ba, P, Mg, As, and B on Acer platanoides rings has been determined using the GBC Integra XL-SDS-270 ICP-OES instrument. Based on our experimental findings, we determined that the concentration of heavy metals accumulated on the rings over the past 20 years varied and that there was a significant correlation between heavy metal concentration in air and heavy metal accumulation on trees. The main reasons for this increase were an increase in the amount of exhaust emission gases and most importantly the transport of heavy metals by the prevailing winds from heavy industrial plants established after 1990 in Ankara. As a result, when the values were examined, we found that except for Na, all the elements, which showed differences at statistically significant levels, were in considerably high quantities in the bark. On average, the values obtained for bark were 6 times higher than those obtained for wood. In terms of elements that showed statistically significant level of differences, this difference was the lowest in P (1.61 times higher), Mg (2.52 times higher), and B (3.94 times higher) and the highest in Mn (23.87 times higher), Al (22.0 times higher), and Fe (14.27 times higher). In the case of Na, we found that the value obtained for wood was 1.64 times higher than that obtained for bark.

Detection and assessment of the phytotoxicity of residual organic pollutants in sediment contaminated with pulp and paper mill effluent.

Abstract: The safe disposal of pulp and paper mill effluent is still a threat to the environment due to the presence of several unknown organic pollutants. The comparative physico-chemical analysis of pulp and paper mill effluent-contaminated sediment (PPECS) of site 1 and site 2 showed that the sediment had an alkaline nature and was loaded with several organic pollutants and heavy metals. SEM-EDX examination showed a porous structure with a heterogeneous distribution of particles, allowing the adsorption of metal and other complex organic ions. FTIR analysis depicted the presence of a variety of functional groups, i.e., alkyl halides, phenolics, and lignin, in the contaminated sediment. GC-MS analysis showed the major presence of organic pollutants, i.e., 2-methyl-4-keto-2-pentan-2-ol and 3,7-dioxa-2,8-disilanonane,2,2,8,8-tetramethyl-5-[(trimethylsilyl)oxy], in the site 1 sediment contaminated with pulp and paper mill waste, while 2-methyl-4-keto-2-trimethylsiloxypentane, 4-ethyl-2-methoxyphenol, ethyl-2-octynoate, cis-9-hexadecenoic acid, and octadecenoic acid were detected in the site 2 sediment contaminated with pulp and paper mill waste. The genotoxicity of PPECS determined by examining Allium cepa root cell division showed chromosomal aberration. In this study, several compounds that have not been reported before were identified.

Climate type-related changes in the leaf micromorphological characters of certain landscape plants

Abstract: This research aimed to determine changes to some micromorphological characteristics of certain landscape plants grown in areas with different dominant climate types. Leaf samples were collected from eight woody plant species in areas with terrestrial, Black Sea, and Mediterranean climate types in Turkey. Then, scaled images of the collected leaf samples were obtained using SEM. StomaLength, StomaWidth, PoreLength, PoreWidth, and StomaDensity were determined using measurements made on the images. Data were statistically evaluated, and the changes to these characteristics by climate type and species were determined. The results show that the lowest values were for plants grown in the terrestrial climate, while the highest values were for plants grown in the Mediterranean climate for all characteristics except SDEN. For SDEN, the lowest value was for plants grown in the Mediterranean climate, while the highest value was obtained for plants grown in the terrestrial climate.

Modeling land use/land cover change using remote sensing and geographic information systems: case study of the Seyhan Basin, Turkey

Abstract: Land use and land cover (LULC) changes affect several natural environmental factors, including soil erosion, hydrological balance, biodiversity, and the climate, which ultimately impact societal well-being. Therefore, LULC changes are an important aspect of land management. One method used to analyze LULC changes is the mathematical modeling approach. In this study, Cellular Automata and Markov Chain (CA-MC) models were used to predict the LULC changes in the Seyhan Basin in Turkey that are likely to occur by 2036. Satellite multispectral imagery acquired in the years 1995, 2006, and 2016 were classified using the object-based classification method and used as the input data for the CA-MC model. Subsequently, the post-classification comparison technique was used to determine the parameters of the model to be simulated. The Markov Chain analyses and the multi-criteria evaluation (MCE) method were used to produce a transition probability matrix and land suitability maps, respectively. The model was validated using the Kappa index, which reached an overall level of 77%. Finally, the LULC changes were mapped for the year 2036 based on transition rules and a transition area matrix. The LULC prediction for the year 2036 showed a 50% increase in the built-up area class and a 7% decrease in the open spaces class compared to the LULC status of the reference year 2016. About an 8% increase in agricultural land is also likely to occur in 2036. About a 4% increase in shrub land and a 5% decrease in forest areas are also predicted.

Development of GP and GEP models to estimate an environmental issue induced by blasting operation

Abstract: Air overpressure (AOp) is one of the most adverse effects induced by blasting in the surface mines and civil projects. So, proper evaluation and estimation of the AOp is important for minimizing the environmental problems resulting from blasting. The main aim of this study is to estimate AOp produced by blasting operation in Miduk copper mine, Iran, developing two artificial intelligence models, i.e., genetic programming (GP) and gene expression programming (GEP). Then, the accuracy of the GP and GEP models has been compared to multiple linear regression (MLR) and three empirical models. For this purpose, 92 blasting events were investigated, and subsequently, the AOp values were carefully measured. Moreover, in each operation, the values of maximum charge per delay and distance from blast points, as two effective parameters on the AOp, were measured. After predicting by the predictive models, their performance prediction was checked in terms of variance account for (VAF), coefficient of determination (CoD), and root mean square error (RMSE). Finally, it was found that the GEP with VAF of 94.12%, CoD of 0.941, and RMSE of 0.06 is a more precise model than other predictive models for the AOp prediction in the Miduk copper mine, and it can be introduced as a new powerful tool for estimating the AOp resulting from blasting.

Treatment technologies for PAH-contaminated sites: a critical review.

Abstract: To reduce environmental and human health risks of contaminated sites, having a comprehensive knowledge about the polycyclic aromatic hydrocarbon (PAH) removal processes is crucial. PAHs are contaminants which are highly recognized to pose threats to humans, animals, and plants. PAHs are hydrophobic and own two or more benzene rings, and hence are resistant to structural degradation. There are various techniques which have been developed to treat PAH-contaminated soil. Four distinct processes to remove PAHs in the contaminated soil, thought to be more effective techniques, are presented in this review: soil washing, chemical oxidation, electrokinetic, phytoremediation. In a surfactant-aided washing process, a removal rate of 90% was reported. Compost-amended phytoremediation treatment presented 58–99% removal of pyrene from the soil in 90 days. Chemical oxidation method was able to reach complete conversion for some PAHs. In electrokinetic treatment, researchers have achieved reliable results in removal of some specific PAHs. Researchers’ innovations in novel studies and advantages/disadvantages of the techniques are also investigated throughout the paper. Finally, it should be noted that an exclusive method or a combination of methods by themselves are not the key to be employed for remediation of every contaminated site but the field characteristics are also essential in selection of the most appropriate decontamination technique(s). The remedy for selection criteria is based on PAH concentrations, site characteristics, costs, shortcomings, and advantages.

Soil erodibility mapping using the RUSLE model to prioritize erosion control in the Wadi Sahouat basin, North-West of Algeria

Abstract: Soil losses must be quantified over watersheds in order to set up protection measures against erosion. The main objective of this paper is to quantify and to map soil losses in the Wadi Sahouat basin (2140 km2) in the north-west of Algeria, using the Revised Universal Soil Loss Equation (RUSLE) model assisted by a Geographic Information System (GIS) and remote sensing. The Model Builder of the GIS allowed the automation of the different operations for establishing thematic layers of the model parameters: the erosivity factor (R), the erodibility factor (K), the topographic factor (LS), the crop management factor (C), and the conservation support practice factor (P). The average annual soil loss rate in the Wadi Sahouat basin ranges from 0 to 255 t ha-1 year-1, maximum values being observed over steep slopes of more than 25% and between 600 and 1000 m elevations. 3.4% of the basin is classified as highly susceptible to erosion, 4.9% with a medium risk, and 91.6% at a low risk. Google Earth reveals a clear conformity with the degree of zones to erosion sensitivity. Based on the soil loss map, 32 sub-basins were classified into three categories by priority of intervention: high, moderate, and low. This priority is available to sustain a management plan against sediment filling of the Ouizert dam at the basin outlet. The method enhancing the RUSLE model and confrontation with Google Earth can be easily adapted to other watersheds.

Flood inundation mapping and monitoring in Kaziranga National Park, Assam using Sentinel-1 SAR data.

Abstract: Satellite-based flood assessment for extent and severity is very crucial input before, during, and after a flood event has occurred. Though optical remote sensing data has been widely used for flood hazard mapping, Synthetic Aperture Radar (SAR) data is preferred for detecting inundated areas and providing reliable information during a flood event due to its capability to operate in all weather and day/night time. Availability of cloud-free optical images during monsoon over north eastern India is a rarity. SAR data also has the advantage of detecting inundation under vegetated areas due to its penetration capabilities and sensitivity to soil moisture. The present study is an attempt to use SAR data for flood monitoring of the Kaziranga National Park (KNP) during monsoon, 2017. Every year, animals are washed away by floods and most of them migrate to higher grounds in order to escape from the rising water levels. Flooding events are common in the study area during the monsoon season due to high rainfall and its close proximity to the Brahmaputra River. Dual polarized (VV and VH) Sentinel-1 SAR images obtained for the entire monsoon period in 2017 were used to create inundation maps of the KNP. Two flood waves were observed in July and August, the second of which is considered to be one of the worst flooding events inundating most areas of the park. The use of SAR data for monitoring of flood events can be very crucial for identifying locations for building animal shelters and finding routes for rescue and relief operations during the disaster.

Monitoring and assessment of seasonal land cover changes using remote sensing: a 30-year (1987-2016) case study of Hamoun Wetland, Iran.

Abstract: The availability of Landsat data allows improving the monitoring and assessment of large-scale areas with land cover changes in rapid developing regions. Thus, we pretend to show a combined methodology to assess land cover changes (LCCs) in the Hamoun Wetland region (Iran) over a period of 30-year (1987–2016) and to quantify seasonal and decadal landscape and land use variabilities. Using the pixel-based change detection (PBCD) and the post-classification comparison (PCC), four land cover classes were compared among spring, summer, and fall seasons. Our findings showed for the water class a higher correlation between spring and summer (R2 = 0.94) than fall and spring (R2 = 0.58) seasons. Before 2000, ~ 50% of the total area was covered by bare soil and 40% by water. However, after 2000, more than 70% of wetland was transformed into bare soils. The results of the long-term monitoring period showed that fall season was the most representative time to show the inter-annual variability of LCCs monitoring and the least affected by seasonal-scale climatic variations. In the Hamoun Wetland region, land cover was highly controlled by changes in surface water, which in turn responded to both climatic and anthropogenic impacts. We were able to divide the water budget monitoring into three different ecological regimes: (1) a period of high water level, which sustained healthy extensive plant life, and approximately 40% of the total surface water was retained until the end of the hydrological year; (2) a period of drought during high evaporation rates was observed, and a mean wetland surface of about 85% was characterized by bare land; and (3) a recovery period in which water levels were overall rising, but they are not maintained from year to year. After a spring flood, in 2006 and 2013, grassland reached the highest extensions, covering till more than 20% of the region, and the dynamics of the ecosystem were affected by the differences in moisture. The Hamoun wetland region served as an important example and demonstration of the feedbacks between land cover and land uses, particularly as pertaining to water resources available to a rapidly expanding population.

Monitoring the response of vegetation dynamics to ecological engineering in the Mu Us Sandy Land of China from 1982 to 2014

Abstract: The Mu Us Sandy Land (MUSL) has undergone climate changes and shifts in human activities driven by a series of ecological restoration projects in recent decades. We analyze the spatiotemporal dynamics of vegetation in this region using the satellite-retrieved normalized difference vegetation index (NDVI) from the Global Inventory Modeling and Mapping Studies (GIMMS) and Moderate Resolution Imaging and Spectroradiometer (MODIS) datasets during the past 33 years. The results show that (1) the vegetation in 53.46% of the MUSL exhibited an upward trend, and 34.45% of the area displayed a large increase, mainly in the eastern part of the MUSL region, including most of Shenmu County, Yuyang District, Hengshan County, and Jingbian County. (2) By the end of 2014, the rapid increase in vegetation encompassed 16.85% of the total area of the study region due to the construction of ecological engineering projects. (3) Based on the residual regression method, the area of positive effects accounted for 55.07% of the total area, and the vegetation in the study area was positively affected by human activities. Our study suggests that these multiple ecological restoration programs contributed to the accelerated greening trend in the MUSL region and highlights the importance of human intervention in regional vegetation growth under climate change conditions.

Monitoring of meteorological and hydrological droughts in the Vistula basin (Poland).

Abstract: The article presents the course of meteorological droughts in Vistula subcatchments in years 1981–2010 and their influence on the occurrence of hydrological droughts. Using the Standardized Precipitation Index (SPI) as an indicator of meteorological drought on the one hand and the Standardized Water-level Index (SWI) and Standardized Runoff Index (SRI) as indicators of hydrological drought on the other, the mutual relationships between precipitation conditions and hydrological conditions were evaluated, as well as the relationships between the two drought types. Studies were conducted for three cumulative periods of these indices, of 12, 24, and 48 months. It was determined that meteorological droughts occurred earliest in the north-western and central part of the basin, and latest in areas lying above 300 m a.s.l. and in the south of Poland. Total duration, depending on the cumulative period, for SPI comprised from 38 to 41% of the analyzed period and for SWI (35–47%) and SRI (24–51%). The strongest relationships were identified in the central part of the Vistula (0.8 < r < 0.85), while the weakest relationships were recorded in the foothill region (r < 0.5). There were also indicated non-climate-related factors influencing those relationships (underground reservoirs, diverse Vistula water resource usage for municipal and industrial intake).

Vehicular stress a cause for heavy metal accumulation and change in physico-chemical characteristics of road side soils in Pahalgam.

Abstract: In an effort to determine vehicular impact on soil quality, soil samples were collected from three different zones (Pahalgam, Batakote, and Chandanwari) in Pahalgam forest ecosystem. Results showed that a significant decrease in moisture content, organic carbon, available nitrogen, and potassium was observed in nearby road side soils. However, pH was observed to be on neutral side and available phosphorus recorded high concentration. The concentration of heavy metals Pb2+, Cu2+, Zn2+, Ni2+, and Cd2+ estimated was also significantly high. Furthermore, concentration of Pb2+ at high vehicular load subzones was observed to be highest (1.168 mg/Kg) followed by Zn2+ (0.896 mg/Kg), Ni2+ (0.649 mg/Kg), Cu2+ (0.415 mg/Kg), and Cd2+ (0.079 mg/Kg). An inter-zone analysis revealed that the concentration of the heavy metals (Pb2+ > Ni2+ > Cd2+) was observed to follow the trend, Z-I > Z-II > Z-III. Variation along the temporal gradient and the impact on soil qualities were notably higher in summer. Vehicular pollution to a great extent impacts physico-chemical characteristics and more interestingly adds substantial concentration of heavy metals in soils.

Heavy metal accumulation in vegetable species and health risk assessment in Serbia

Abstract: Continuous monitoring of heavy metal content in vegetables is of high priority for population nutrition control, as well as risk assessment for human health. The chemical composition of plants is a reliable indicator of their contamination by hazardous substances accumulated in the environment as a consequence of inadequately applied agro-technology. The main goal of this study was to examine the quality of vegetables that reach consumer markets as a function of growth location. Samples of 11 of the most common vegetable species used in the human diet were collected during a 4-year survey. Vegetables originated from local farm producers who cultivated them at different locations in Vojvodina Province, Serbia. Many vegetable samples contained disturbingly high levels of the investigated metals: cadmium, lead, nickel, and chromium. The plant species with the highest Cd accumulation was spinach, where Cd leaves exceeded the maximum permissible concentrations (MPCs) in more than half of the analyzed samples from different localities (54%). Pb concentrations in spinach were also higher than MPC values (according to Serbian law 3.0 μg/g) in 46% of all analyzed samples. Results showed that Cr levels in all tested vegetable species were below MPC values recommended by the FAO/WHO organization. The largest chromium accumulator was spinach, with average values of 2.3 μg/g, followed by beetroot and parsnips with an average concentration of 1.4 μg/g. The highest average content of Ni in all analyzed vegetable species was also recorded in spinach leaves, with an average value of 2.2 μg/g, followed by broccoli (1.7 μg/g) and tomatoes (1.5 μg/g).

Bioaccumulation of cadmium, lead, and zinc in agriculture-based insect food chains

Abstract: Globally, the metal concentration in soil is increasing due to different anthropogenic and geogenic factors. These metals are taken up by plants and further transferred in the food chain through different routes. The present study was designed to assess the transfer and bioaccumulation of the heavy metals, cadmium (Cd), lead (Pb), and zinc (Zn), in food chains from soil to berseem plants (Triofolium alexandrinum), to insect herbivores (the grasshopper Ailopus thalassinus and the aphid Sitobion avenae) and to an insect carnivore (the ladybird beetle Coccinella septempunctata). The soil of studied berseem fields were slightly alkaline, silty loam in texture and moderate in organic matter. In soil, the concentration of Zn and Pb were under permissible level while Cd was above the permissible level. The accumulation of metals in T. alexandrinum were found in the order Zn > Cd > Pb. Grasshoppers showed higher accumulation of Pb than of Cd and Zn. In the soil-berseem-aphid-beetle food chain, metal enrichment was recorded. However, aphids did not show bioaccumulation for Cd. Metals accumulation in beetles showed that translocation of Zn, Cd, and Pb was taking place in the third trophic level. Our study highlights the mobility of metals in insect food chains and showed that insect feeding style greatly influenced the bioaccumulation. However, different metals showed variable bioaccumulation rates depending on their toxicity and retention.