BACKGROUND AND OBJECTIVES: A new wave of Covid-19 pandemic has worsened the epidemiological situation in Ukraine. This caused the need to tighten quarantine measures that have been introduced since 31.08.2020. The conducted analysis showed that there are 3 groups of technologies for digital contact tracing: from maximum (25%) to minimum (20%). Objective of the study is to develop an exchange platform to track the spread of COVID-19 in rural areas. METHODS: Factor analysis identified key factors of COVID-19 virus spread. Cluster analysis identified clusters of COVID-19 spread. Taxonomy method established the limits of using contact tracing methods. Discriminatory method makes it possible to change the applied contact tracing method. FINDINGS: The results showed that the identified factors (medico-demographic special features of Covid-19 virus spread; rural infrastructure to counteract the infection) describe in total 83.24% of the data processed. Specified 4 clusters differ in the level of susceptibility of the population to COVID-19 and infrastructure development: from minimum (33% of the united territorial communities) to maximum - 13% of the united territorial communities. The value of the integral indicator calculated provides means for establishing the maximum (8.5) and the minimum (2) limit of changes in the method of digital contact tracing. CONCLUSION: The developed methodology was implemented on the basis of the united territorial communities of Sumy region. Monitoring of changes in the epidemiological situation made it possible to justify the need to change the contact tracing model, which will reduce the epidemiological level in the region as a whole by 30%.
The coronavirus disease 2019 (COVID-19) has been identified as the main cause of the outbreak of the respiratory disease in Wuhan, Hubei Province of China in December 2019. Since then, the epidemic has spread rapidly throughout China and many other countries in the world. This study, therefore, examines the spatiotemporal distribution of the confirmed cases of COVID-19 and its effect on human development in China, and suggested social and non-pharmaceutical preventive interventions to help curb the further spread of the disease. The public open data available from January to February 2020, from the National Health Commission of the People’s Republic of China and a medical knowledge sharing website were used, and spatial analysis was performed to visualize the spatial distribution pattern of COVID-19 in China. The results showed among others that COVID-19 had entered a dispersed spatial pattern, resulting in increased pressure to control the spread of the disease. In early March, there was a significant reduction in the existing number of cases, and the number of deaths also decreased. At the provincial level, the spatial distribution of the number of cumulative confirmed cases in China was divided into four patterns: Hubei was the initial core region; the eastern provinces adjacent to Hubei formed the second concentrated pattern; the western provinces adjacent to Hubei and the northeastern and southeastern provinces which were separated from Hubei by one province belonged to the third distribution pattern; while the rest of the provinces in the north, south and west showing sporadic distribution patterns formed the fourth. It has been estimated that about 80% of students’ online learning at all schools were not effective due to lack of access to reliable and uninterrupted internet services especially in the rural areas of China.
Fipronil is a relatively new insecticide in agriculture with health and environmental effects. This is the first report studying effect of fipronil on fish administered via intraperitoneal route. Intraperitoneal LD50 of fipronil in 16.3 g Caspian kutum, Rutilus frisii kutum, fingerlings was determined using a total of 133 fish in 19 tanks (7 fish/tank) including one control and 6 treatment groups (300, 450, 550, 650, 750, 850 mg/kg). Fish were injected intraperitoneally and monitored at 96 h. The LD50 of fipronil was 632 mg/ kg in Caspian kutum. Sub-lethal test doses of 10, 20, and 30% of the LD50 at 96 h were used to assess the effect of fipronil on the fish's liver. The blood plasma of 90 fish were used (18 at each test dose and in controls) on days 7 and 14 for biochemistry. The hepatosomatic index (HSI) of the livers were obtained and histopathology done on the same days. Pyknosis, sinusoid dilation and vacuolization were common histological changes, and these changes became more severe in a time and dose dependent manner. This dependence was also observed for HSI and the liver biochemical test (alanine and aspartate transaminase). Liver histological alterations showed that fipronil can be a potential factor in liver carcinoma.
The increasing frequency and severity of flooding demands identification of flood hazard zones in Kalilangan, Bukidnon in response to the echoing need of better disaster preparedness via enhancing the understanding and awareness of the public on flood characteristics by integrating the use of two-dimensional hydrodynamic modeling and remote sensing. Flood simulation was carried out in a two-dimensional hydrodynamic model using hydrologic engineering centerriver analysis system to derive the flood inundation area and flood depth of Kalilangan, Bukidnon. Thus, it was preceded by pre-processing of the model using software packages of hydrologic engineering center-hydrologic modeling system and ArcGIS along with interferometric synthetic aperture radar-digital elevation model, Manning's roughness coefficient and precipitation data. Five different rain return flooding scenarios were simulated using rainfall intensity duration frequency data. Three zones of flood hazard were then set as low, medium and high. The result shows that most areas of Kalilangan are within the zones of medium to high hazard with residential buildings as the most flooded type of built-up structures. Flood hazard zone areas could be mapped at an accuracy of 79.51%. Thus, harnessing this potential approach offers cost-effective way of flood preparedness viewing hazard-prone areas with special attention and utmost importance.
A factorial experiment was conducted to evaluate the impact of super absorbents and organic wastes of rice, olive marc, vermicompost and farmyard manure on the soil water holding capacity and the growth of plant based on randomized complete block design with 13 treatments at two irrigation intervals 5 and 10 days. The olive saplings with same heights and better appearances were planted in an open space roofed with a plastic cover with a height of 3 m to avoid the effects of rainfall and snowfall on the results. Stockosorb superabsorbent and weighted zeolite and the rest of bulk materials were mixed. Results showed that the substrate containing 10 g per kg soil of zeolite and the substrate including 20% vermicompost + 15% rice wastes + 15% manure + 50% soil had the best yield and can modify the effect of 10 day irrigation interval compared to the 5 day.
The toxicity and corrosion potential of hydrogen sulfide in raw biogas underlines the need for biogas purification. Several techniques available for removal of hydrogen sulfide from biogas are out of the reach for common end users due to lack of knowledge, higher running costs, and insufficient operational skills. The present experimental study aims to propagate hydrogen sulfide removal techniques amongst the end users by using a low-cost chemical absorption technique and packed column reactors. Commercial grade chemicals like monoethanolamine, sodium hydroxide, calcium hydroxide, granular activated carbon, and steel wool were used for biogas purification in packed column reactors of 1.2 liters capacity. Hydrogen sulfide removal efficiency up to 92.41% was achievable using single purification columns. The efficiency achieved by using multiple purification column was up to 96.84%. Hydrogen sulfide removal efficiency was calculated for experimental variants like the use of a dedicated purification column, multiple purification columns, flow variations and pressure variations of raw biogas. The data for the frequency of regeneration/replacement of different chemicals was also determined. The simplicity of operation and the use of low-cost reagents in the present study can enable the use of these methods amongst end users of biogas technology for minimizing health hazards and corrosion problems.
In the present study, different activated carbons were prepared from carbonized African beech wood sawdust by potassium hydroxide activation. The activated carbons were characterized by brunauer–emmett–teller, scanning electron microscope, fourier transform infrared spectroscopy, and thermogravimetric analyzer. The phenol adsorption capacity of the prepared carbons was evaluated. The different factors affecting phenol’s removal were studied including: contact time, solution pH and initial phenol concentration. The optimum phenol removal was obtained after a contact time of 300 min. and at an initial phenol solution pH 7. The maximum removal percentages were determined at 5mg/l initial phenol concentration as 79, 93, 94 and 98% for AC0, AC1, AC2 and AC3; respectively. The adsorption of phenol on African beech sawdust activated carbons was found to follow the Lagergren first order kinetics and the intraparticle diffusion mechanism gave a good fit to the experimental data. The isothermal models applied fitted the experimental data in the order: Langmuir> Dubinin–Radushkevich> Freundlich and Temkin.
The present work was carried out to evaluate the removal of p-nitrophenol by adsorption onto olive cake based activated carbon having a BET surface area of 672 m²/g. The batch adsorption experimental results indicated that the equilibrium time for nitrophenol adsorption by olive cake-based activated carbon was 120min. The adsorption data was modeled by equilibrium and kinetic models. The pseudo- first and second order as well as the Elovichkinetic models were applied to fit the experimental data and the intraparticle diffusion model was assessed for describing the mechanism of adsorption. The data were found to be best fitted to the pseudo-second order model with a correlation coefficient (R2=0.986). The intraparticle diffusion mechanism also showed a good fit to the experimental data, showing two distinct linear parts assuming that more than one step could be involved in the adsorption of nitrophenol by the activated carbon. The equilibrium study was performed using three models including Langmuir, Freundlich and Temkin. The results revealed that the Temkin equilibrium model is the best model fitting the experimental data (R2=0.944). The results of the present study proved the efficiency of using olive cake based activated carbon as a novel adsorbent for the removal of nitrophenol from aqueous solution.
This study was investigated the efficiency of activated persulfate and in-vessel composting for removal of total petroleum hydrocarbons. Remediation by activated persulfate with ferrous sulfate as pre-treatment was done at batch system. In the chemical oxidation, various variables including persulfate concentrations (10-3000 mg/g as waste), pH (3-7), ferrous sulfate (0.5-4 mg/g as waste) and temperature (20-60°C) were studied. In the biological system, premature compost was added as an amendment. The filter cake to compost ratio were 1:0 (as control) and 1:5 to 15 (as dry basis). C: N: P ratio and moisture content were 100:5:1 and 45-60%, respectively. The results showed that acidic pH (pH=3) had high efficiency for the removal of total petroleum hydrocarbons by activated persulfate. Temperature had the significant effect during the persulfate oxidation. When ferrous sulfate was used as an activator for degradation at acidic condition and 60°C, removal efficiency increased to 47.32%. The results of biological process showed that the minimum total petroleum hydrocarbons removal in all reactors was 62 percent. The maximum and minimum removal efficiency was obtained at 1:5 (69.46%) and 1:10 (62.42%) mixing ratios, respectively. Kinetic study showed that second order kinetic model (R²>0.81) shows the best agreement with the experimental data and the rate of TPH degradation at low mixing ratio (1:3) was faster than high mixing ratio (1:15). Therefore, according to the results, in-vessel composting after pre-treatment by activated persulfate is suggested as an efficient process for degradation of total petroleum hydrocarbons.
Water is prime requirement for surviving of any living beings. The existence of surface water and groundwater sources are used for domestic, agriculture and industrial purposes in all over the world. Fresh water from both the water sources is highly contaminated in recent years because of rapid population growth, modern agriculture and industrial growth. Among them, contamination of water sources due to industrialization is high and it requires more attention to protect those water sources. In this study, nickel removal from electroplating industry wastewater was done with the help of bamboo activated carbon. The nickel removal from electroplating industry wastewater by bamboo activated carbon was done in this study at various adsorbent dosages (0.5, 1.0, 1.5 and 2.0 g/L), agitation speeds (25, 50, 75 and 100 rpm), particle sizes (2.36, 1.18, 0.6 and 0.3 mm), and concentration dilutions (0, 25, 50, 75 and 100%). The maximum removal percentage of nickel from electroplating industry wastewater using bamboo activated carbon was found to be 98.7 % at an optimum adsorption dosage 1.5 g/L, agitation speed 25 rpm, particle size 0.6 mm and concentration dilution 75 % with 110 min. contact time and 5.5 pH. Functional groups available in a bamboo activated carbon before and after treatment were determined by fourier-transform infrared spectroscopy analysis. Fourier-transform infrared spectroscopy analysis specified that alkanes, carboxylic acids, esters, amides, amines, aromatic compounds, alkyl halides, ethers, alcohols, carboxylic acids, aldehydes functional groups in bamboo activated carbon was contributed for removing nickel from the electroplating industry wastewater. Isotherm models were used to know the adsorption behaviour of bamboo activated carbon for removing nickel from electroplating industry wastewater. Isotherm results revealed that Langmuir model was best suited with the equilibrium data than Freundlich model. Finally, this study concluded that bamboo activated carbon was best suited for removing nickel from electroplating industry wastewater.
A risk assessment study was conducted to predict the expected hazardous influence on the ecosystem resulted from urbanization and industrialization activities at Helwan area, Egypt. To achieve these goals, soils, plants and water samples were collected from Helwan area, and their total concentrations of inorganic contaminants (Cd, Cr, Co, Cu, Fe, Mn, Ni, Pb, and Zn) and organic pollutants; such as Phenol and hydrocarbons were measured. The obtained results showed that, the concentrations of organic contaminants in water streams and surrounding soils recorded high concentration values than the permissible limits, while inorganic elements were within the safe limits for irrigation. In addition, soils irrigated with the effluents of industrial units recorded high values of inorganic and organic contaminants. Consequently, the levels of these contaminants were high in plant tissues grown thereon; especially the edible parts. Risk assessment based on available Predicted No Effect Concentration values for the aquatic and terrestrial environment was performed. Inorganic elements were expected to cause serious hazard problems for both aquatic organisms and soil microorganisms. The impact of these pollutants on human health was calculated using daily metals intake of inorganic metals via consumption of edible plants. Hazard index values proved that concentrations of Cr may cause serious hazard problems for humans in this area; especially, children.
Background and objectives: This paper focuses on the development of Czech laws of water resource protection. The presented research examines the statistical data of the number and type of legislative acts concerning to water protection issued in the Czech Republic during the period 1990-2019. Several types of legislative acts are followed in administrative law and statistically compared by the development in time and its type. The survey focuses on general water protection acts, water sewage management, agriculture sector, hygiene standards, and the protection of the basins of Czech rivers (e.g., blue water and gray water). METHODS: The analysis firstly concerns to the development of the number of legislative acts during 1990-2019 and secondly discusses a diversification of the legislative acts types (laws, decrees, resolutions, regulations, and strategic plans). A total of 12,272 legislative acts is analyzed during three phases of Czech modern history: 1990-1992 (Czechoslovakia), 1993-2003 (Czech Republic before its accession to the European Union), and 2004-2019 (Czech Republic in the European Union). FINDINGS: Statistical elaboration of legislative acts proves that it is possible to determine different types of water management over time. Protection of water resource management in the Czech Republic was forming from crisis management (1990-1992), via operational management (1993-2003) to strategic management (2004-2019). Current trends after 2020 show a new trend towards integral management. CONCLUSION: Findings provide better understanding of changeable importance of water protection and management attitudes in the Czech Republic in reaction to the development of society.
Heavy metals and dyes are major contributors in contamination of water streams. These contaminants enter into our eco- system, thus posing a significant threat to public health, ecological equilibrium and environment. Thus a combined discharge of these contaminants results in water pollution with high chemical oxygen demand, biological oxygen demand, color, particulate matter, suspended particles and odor. The mounting pollution of the water bodies has attracted attention of the researchers towards the development of novel techniques and materials for water pollution. The paper describes the use of such a material Parthenium hysterophorus, a weed, explored for water purification. The potential of the weed has been tested for several heavy metals and dyes as described in this paper. As per literature the weed is capable of showing adsorption tendency up to 90% in certain cases for some heavy metals and dyes. Powdered weed, activated carbon, ash etc. of Parthenium have been employed for the removal process.
Mesoporous pellet adsorbent developed from mixing at an appropriate ratio of natural clay, iron oxide, iron powder, and rice bran was used to investigate the optimization process of batch adsorption parameters for treating aqueous solution coexisting with arsenate and arsenite. Central composite design under response surface methodology was applied for optimizing and observing both individual and interactive effects of four main influential adsorption factors such as contact time (24-72 h), initial solution pH (3-11), adsorbent dosage (0-20 g/L) and initial adsorbate concentration (0.25-4.25 mg/L). Analysis of variance suggested that experimental data were better fitted by the quadratic model with the values of regression coefficient and adjusted regression coefficient higher than 95%. The model accuracy was supported by the correlation plot of actual and predicted adsorption efficiency data and the residual plots. The Pareto analysis suggested that initial solution pH, initial adsorbate concentration, and adsorbent dosage had greater cumulative effects on the removal system by contributing the percentage effect of 47.69%, 37.07% and 14.26%, respectively. The optimum values of contact time, initial solution pH, adsorbent dosage and initial adsorbate concentration were 52 h, 7, 10 g/L and 0.5 mg/L, respectively. The adsorption efficiency of coexisting arsenate and arsenite solution onto the new developed adsorbent was over 99% under the optimized experimental condition.
The expensive nature of metal ions detoxification from wastewater have restricted the use of conventional treatment technologies. Cheap, alternative measures have been adopted to eliminate metal contamination, and adsorptions using agricultural adsorbents seem to be the way forward. The use of agricultural adsorbents for cadmium (II), copper (II) and lead (II) ion removal has gained more interest in literature due to the level of contamination in water bodies. This review shed lights on the removal proficiency of various low-cost agricultural adsorbent for the elimination of cadmium (II), copper (II) and lead (II) ions, considering performance, surface modification, equilibrium adsorptive studies, kinetic characteristics, coefficient of correlation (R²) and reuse. Furthermore, these agricultural adsorbents have displayed better performance when rivaled with commercial/conventional adsorbent. Observations from different adsorptive capacities presented owe their performance to surface area improvement/modification, pH of the adsorbent, ionic potential of the solution, initial concentration and elemental component of the adsorbent. However, gaps have been identified to improve applicability, sorption performance, economic viability, optimization, and commercialization of suitable agricultural adsorbents.
Fertilizer plant waste carbon slurry has been investigated after some processing as an adsorbent for the removal of dyes and phenols using columns. The results show that the carbonaceous adsorbent prepared from carbon slurry being porous and having appreciable surface area (380 m2/g) can remove dyes both cationic (meldola blue, methylene blue, chrysoidine G, crystal violet) as well as anionic (ethyl orange, metanil yellow, acid blue 113), and phenols (phenol, 2-chlorophenol, 4-chlorophenol and 2,4-dichlorophenol) fruitfully from water. The column type continuous flow operations were used to obtain the breakthrough curves. The breakthrough capacity, exhaustion capacity and degree of column utilization were evaluated from the plots. The results shows that the degree of column utilization for dyes lies in the range 60 to 76% while for phenols was in the range 53-58%. The exhaustion capacities were quite high as compared to the breakthrough capacities and were found to be 217, 211, 104, 126, 233, 248, 267 mg/g for meldola blue, crystal violet, chrysoidine G, methylene blue, ethyl orange, metanil yellow, acid blue 113, respectively and 25.6, 72.2, 82.2 and 197.3 mg/g for phenol, 2-chlorophenol, 4-chlorophenol and 2,4-dichlorophenol, respectively
Heavy metal contamination in the environment could cause harmful effects both to human health and aquatic life. Numerous remediation methods had been developed to encounter with the contamination problem prior to degrade, decrease and to purify the contaminated water at minimal concentration as low as possible. Therefore, in current study, commercialized chicken eggshells and hybrid Akar Putra chicken eggshells were conducted in batch experiment to testify the capabilities of bio-sorbent materials in iron (II) ion removal from aqueous solution at optimized level of dosage and equilibrium contact time. The optimum condition for iron (II) removal for commercialized chicken eggshells and hybrid Akar Putra chicken eggshells bio-sorbents reached at 0.30 g with optimum contact time of 50 minutes and 91.83% and 91.07% of removal percentage with 0.60 g at 40 minutes. The final concentration from both bio-sorbents is achieved below than drinking water guideline (0.30 mg/L), 0.1635 mg/L and 0.1785 mg/L, respectively. The isotherm adsorption results showed it fitted better in Langmuir Isotherm Model than in Freundlich Isotherm Model, however with weak bonding, which could not held onto the heavy metal ions in long time period. In brief, commercialized chicken eggshells and hybrid Akar Putra chicken eggshells have considerable potential in removing heavy metal in aqueous solution. The selection of the bio-sorbent materials is more favorable as it reduces dependency towards chemical usage in water treatment which could have complied with drinking water guideline that can be obtained easily, abundance in amount, cheap and biodegradable.
The potential effect of invasive plant species on biodiversity is one of most important subject of inquiry at present. In many parts of the world, the alarming spread of these plants has been documented. Knowing that climate exerts a dominant control over the distribution of plant species, predictions can therefore be made to determine which areas the species would likely spread under a climate change scenario and that is what this study aims to tackle. In the current study, a total of 211 species occurrence points were used to model the current and projected suitability of Piper aduncum in Bukidnon, Philippines using Maxent. Results revealed that the suitability of the species was determined primarily by climatic factors with Bio 18 (precipitation of the warmest quarter) as the strongest influencing variable with a mean percent contribution of 22.1%. The resulting model was highly accurate based on its mean test Area Under Curve that is equal to 0.917. Current prediction shows that suitable areas for Piper are concentrated along the southern portion of Bukidnon. Only 9% of the province is suitable for the species at present but is predicted to increase to 27% because of climate change. The central and southwestern parts of the province are the areas of high threat for invasion by Piper.
The current study was carried out to evaluate the quantity and quality of rural domestic waste generation and to identify the factors affecting it in rural areas of Khodabandeh county in Zanjan Province, Iran. Waste samplings consisted of 318 rural households in 11 villages. In order to evaluate the quality and quantity of the rural domestic waste, waste production was classified into 12 groups and 2 main groups of organic waste and solid waste. Moreover, kriging interpolation technique in ARC-GIS software was used to evaluate the spatial distribution of the generated domestic waste and ultimately multiple regression analysis was used to evaluate the factors affecting the generation of domestic waste. The results of this study showed that the average waste generated by each person was 0.588 kilograms per day. with the share of organic waste generated by each person being 0.409 kilograms per day and the share of solid waste generated by each person being 0.179 kilograms per day. The results from spatial distribution of waste generation showed a certain pattern in three groups and a higher rate of waste generation in the northern and northwestern parts, especially in the subdistrict. The results of multiple regression analysis showed that the households' income, assets, age, and personal attitude are respectively the most important variables affecting waste generation. The housholds' attitude and indigenous knowledge on efficient use of materials are also the key factors which can help reducing waste generation.
Water is a unique natural resource among all sources available on earth. It plays an important role in economic development and the general well-being of the country. This study aimed at using the application of water quality index in evaluating the ground water quality innorth-east area of Jaipur in pre and post monsoon for public usage. Total eleven physico–chemical characteristics; total dissolved solids, total hardness,chloride, nitrate, electrical conductance, sodium, fluorideand potassium, pH, turbidity, temperature) were analyzed and observed values were compared with standard values recommended by Indian standard and World Health Organization. Most of parameter show higher value than permissible limit in pre and post monsoon. Water quality index study showed that drinking water in Amer (221.58,277.70), Lalawas (362.74,396.67), Jaisinghpura area (286.00,273.78) were found to be highly contaminated due to high value of total dissolved solids, electrical conductance, total hardness, chloride, nitrate and sodium.Saipura (122.52, 131.00), Naila (120.25, 239.86), Galta (160.9, 204.1) were found to be moderately contaminated for both monsoons. People dependent on this water may prone to health hazard. Therefore some effective measures are urgently required to enhance the quality of water in these areas.
Background and objectives: Open-pit mining is an important activity to obtain mineral resources that supply society with raw materials to improve people’s quality of life. However, this extractive activity causes negative environmental impacts and, it is therefore necessary to identify and evaluate these impacts in order to design preventive and control measures to reduce them and thus safeguard the environment and natural resources. In the Region of Murcia, in Spain, as well as other Mediterranean areas with similar climatic conditions, there is a great deal of mining activity linked to the building sector, in which mainly ornamental rock (marble and marble limestone) and limestone aggregates are used. All of this has given rise to numerous active and abandoned mines, where no restoration process has been carried out, generating strong impacts on the environment. Methods: In this study, 8 environmental impact assessments studies of ornamental rock and aggregate quarries in the Region of Murcia were analysed to identify the negative impacts on the abiotic and biotic environment, landscape, socio-economic and socio-cultural environment, and infrastructures and analysing preventive and control measures. Findings: According to the environmental impact assessment studies analysed, the importance of the most significant environmental impacts has been calculated, indicating whether the impacts are critical, severe, moderate or compatible, and based on it, preventive and corrective measures are proposed together in an impact mitigation management system based in flow charts that will serve to more easily apply and control these measures, in order to prevent them from causing significant or irreversible damage to the environment. Analysing these measures, it has been observed that 90% of the measures applied to control the different negative environmental factors in this type of quarry are the same. Conclusion: Open-pit mining extraction systems have a series of similar characteristics that allow a systematic approach to be established when analysing the impacts. With the use of flowcharts, it becomes easier to apply measures to reduce environmental impacts and in addition, these diagrams, allow at the same time the easy incorporation of updates due to changing regulations.
In this study, the quality of a treated wastewater for agricultural and irrigation purposes was investigated. 39 quality parameters were investigated at the entrance of an effluent channel to the destination plain in monthly time intervals during a year. The aim of this study was drawing an analogy between analyses results and the latest standards in the world (nationwide and internationally), the agricultural and irrigation usage indexes and the Wilcox diagram. The results showed that some parameters such as turbidity, total suspended solids, electrical conductivity, sodium, detergents, total coliform and focal coliform, ammonium, residual sodium carbonate, the Kelly's Ratio and the Wilcox diagram were exceeding the permissible limit and are not suitable for agriculture and irrigation. It was found that the aquifers in the study area were polluted by natural salinity and geogenic source. As a result, application of the treated wastewater from Qom for agriculture and irrigation purposes needs to be revised and monitored. An action plan is also needed to manage a huge source of water and to avoid further environmental and health risks.
The study provides a statistical trend analysis of different air pollutants using Mann-Kendall and Sen's slope estimator approach on past pollutants statistics from air quality index station of Varanasi, India. Further, using autoregressive integrated moving average model, future values of air pollutant levels are predicted. Carbon monoxide, nitrogen dioxide, sulphur dioxide, particulate matter particles as PM2.5 and PM10 are the pollutants on which the study focuses. Mann-Kendall and Sen's slope estimator tests are used on summer (February-May), monsoon (June-September) and winter (October-January) seasonal data from year 2013 to 2016 and trend results and power of the slopes are estimated. For predictive analysis, different autoregressive integrated moving average models are compared with goodness of fit statistics, and the observed results stated autoregressive integrated moving average (1,1,1) as the best-suited for forecast modeling of different pollutants in Varanasi. Autoregressive integrated moving average model (1,1,1) is also used on the annual concentration levels to predict forthcoming year's annual pollutants value. Study reveals that PM 10 shows a rising trend with predicted approximate annual concentration of 273 μg/m³ and PM2.5, carbon monoxide, nitrogen dioxide and sulphur dioxide show a reducing trend with approximate annual concentration of 139 μg/m³, 1.37 mg/ m³, 38 μg/m³ and 17 μg/m³, respectively, by the year 2030. The study predicted carbon monoxide, nitrogen dioxide and sulphur dioxide concentrations are lower and PM10 and PM2.5 concentrations are much higher to the standard permissible limits in future years also, and specific measures are required to control emissions of these pollutants in Varanasi.
During the last years, several exceedances of PM10 and benzo(a)pyrene limit values exceedances were recorded in Taranto, a city in southern Italy included in so-called areas at high risk of environmental crisis because of the presence of a heavy industrial district including the largest steel factory in Europe. A study of these critical pollution events showed a close correlation with the wind coming from the industrial site to the adjacent urban area. During 2011, at monitoring sites closes to the industrial area, at least the 65% of PM10 exceedances were related to wind day conditions (characterized by at least 3 consecutive hours of wind coming from 270-360±2deg with an associated speed higher than 7 m/s). For this reason, in 2012 an integrated environmental permit and a regional air quality plan were enacted to reduce pollutant emissions from industrial plants. A study of PM10 levels registered during windy days was performed during critical episodes of pollution highlighting that the difference between windy days and no windy days’ concentrations reduces from 2012 to 2014 in industrial site. False negative events (verified ex-post by observed meteorological data) not identified by the forecast model - did not show a significant influence on PM concentration: PM10 values were comparable and sometimes lower than windy days levels. It is reasonable that the new scenario with a relevant reduction emissions form Ilva plant reduced the pollutants contribution from industrial area, contributing to PM10 levels decrease, also in false negative events.
Indoor air pollution associated with cooking and heating biomass fuel burning is estimated to be responsible for 7 million deaths in 2016 and most of these deaths occur in low and middle income countries. In Côte d'Ivoire, 73% of the population is reported using biomass (charcoal or wood) for cooking. The active device 3M EVM-7 was used to measure PM 2.5 daily average concentrations inside and outside households in areas close (Andokoi) and far (Lubafrique) to an industrial zone in two popular neighborhoods of Yopougon, the largest and most populated municipality of the city of Abidjan (Côte d'Ivoire). PM 2.5 daily average concentrations indoors and outdoors are respectively 121±12 μg/m ³ and 117±8 μg/m ³ in Andokoi and 32±3 μg/m ³ and 41±4 μg/m ³ in Lubafrique well above the World Health Organization guideline value (25 μg/m ³ ) for air quality. Using multivariable models, the results were the number of windows in bedrooms and kitchens located outdoor were negatively correlated with the concentration of indoor PM 2.5 . The outdoor concentrations of PM 2.5 , were higher according to the cooking fuel type.
The aim of this study is to evaluate the obstacles due to a DPSIR model combined with fuzzy analytic hierarchy process technique. Hence, to prioritize the responses regarding the driving forces, pressures, states and impacts, the hierarchy of the model is established. Evaluations and prioritization of model results of urban transport situation in Tehran have provided a number of necessary issues for strategic planning to reduce local air pollution and emission of greenhouse gases by prioritizing their effectiveness in the implementation, including; a) development and improvement of public transport (R1), b) improvement of fuel quality (R2), c) improvement of vehicle emission standards (R3), d) vehicle inspection (R4), f) traffic management (R5). In this study, responses to improve the factors of pressure, stimulus, the current state and the impacts were examined and compared hierarchically. Finally, their priority relative to each other was achieved. Development and improvement of public transport, improvement of the quality of fuel, improvement of vehicle emission standards, vehicle check-up and finally urban traffic management were identified respectively as practical steps to control and reduce air pollution in Tehran.
Different methods have been designed to calculate the air quality index in form of mathematical formula. But the formula designed by Central Pollution Control Board in 2014 is more robust to find out the air quality category. The index has been calculated based upon four parameters like particulate matters (PM10, PM2.5), sulfur oxide and nitrogen oxide. The study area has affected by different sources like point, line and volume. Presence of different industries and mining activities polluting the natural environment of nearby areas more, although the industries taking mitigative measures proactively. In the present research, monitoring of ambient air quality has been carried out for a period from March 2013 to February 2016 for three years. It has been revealed from the study that the air quality status of the area has been declining from 2013 to 2016 i.e. 78.9 to 157.8 in summer, 49.4 to 84.3 in monsoon and 86.9 to 183.9 in winter season. It has also been found that, PM10 and PM2.5 were responsible for maximum sub-index as well as air quality index. During the study period 2015-16, out of the eight stations most comes under moderately polluted category especially in winter season followed by summer season. Statistical and Duncan's multiple range test has been applied to the results with two-way and one-way analysis of variance based on different seasons and stations. In two-way analysis of variance, F-value was computed to be 30.105 based on seasons and stations and one-way analysis of variance test shows the F-values as 186.07 and 18.97 based on seasons and stations respectively which is found to be significant (P < 0.01).The present research is important to assess the environmental quality of a mining- industrial complex area and can be a reference for similar study in other areas.
Rapid urbanization and severe air quality deterioration in Pakistan have increased citizens's concern towards air pollution. The study aimed to develop relationship between degraded air quality and resident's willingness to pay for improved air quality in city of Lahore, Pakistan through contingent valuation method to quantify an individual's willingness to pay for improved air quality. Hypothetical market was created and 250 respondents, selected through random sampling, were asked to respond to pre tested questionnaire. Results revealed that 92.5% of respondents showed positive willingness to pay and average predicted willingness to pay by each person was $9.86 per month. Respondents were willing to pay $118 per year which was 1.27% of their mean monthly income. Stepwise Regression model was used to develop relationship between independent variables and willingness to pay. Most parameters accompanied by econometric analysis elaborated expected results. Results disclosed that annual household income, symptoms of respiratory diseases and self observed air pollution pointedly impact willingness to pay. It is concluded that despite of the fact that Pakistan is among the lower income countries with no rigid budget allocation for improvement in air quality, people of Pakistan are willing to pay to reduce air pollution load. One of the factor which effected the positivity of willingness to pay is that, a quite large number of people were suffering from pollution related respiratory disorders like asthma, chronic bronchitis, wheezing, cough, and chest congestion. Only 7.5% of respondents were not interested to pay for improved air quality which reported unconcerned attitude and lack of environmental awareness.
High concentrations of nitrogen compounds, such as ammonia observed in the petrochemical industry, are the major environmental pollutants. Therefore, effective and inexpensive methods are needed for its treatment. Biological treatment of various pollutants is a low cost and biocompatible replacement for current physico-chemical systems. The use of aquatic plants is an effective way to absorb the nutrient pollutants. In this study, the optimal operating conditions in the biological removal of ammonia from the urea-ammonia wastewater of Kermanshah Petrochemical Company by Lemna gibba were determined using the response surface methodology. Lemna gibba was collected from the ponds around Kermanshah and maintained in a nutrient medium. Effect of the main operational variables such as ammonia concentration, residence time and Lemna gibba to surface ratio on optimal conditions of ammonia removal from wastewater has been analyzed using the Box-Behnken model design of experiments. Model numerical optimization was performed to achieve the maximum amount of ammonia removal from wastewater. The ammonia removal percentage varied from 13% to 88%, but the maximum amount of ammonia removal was determined at ammonia concentration of 5 ppm and Lemna gibba residence time of 11 days in wastewater based on the quadratic model. Lemna gibba to surface ratio of 2:5 was measured at 96.449%. After optimization, validation of ammonia removal was performed under optimum conditions and measured at 92.07%. Based on the experimental design and the predicted under model conditions, the maximum amounts of ammonia removal percentage in the experiments were 82.84% and 88.33% respectively, indicating the high accuracy of the model to determine the optimum conditions for the ammonia removal from wastewater.
Environmental sustainability needs to use resources efficiently and effectively from macro to micro level with a systematic approach. The dualistic relationship between ecosystem and human beings require considering ecological and social systems as well as economic factors known as the three-legged approach. Individuals and their perceptions are also important in this approach because of the need of environmental awareness and behaviors. From this point of view, this study assesses the perceptions of local mine workers in the Göksu Valley about the environmental sustainability to understand the relationship between environmental, personal and organizational factors. Extroversion, conscientiousness, and agreeableness as the sub-dimensions of the personality have positive correlations with environmental sustainability. Also, working conditions and expert power of the leader have a significant relationship with environmental sustainability within the mine worker sample which has a high-level environmental sustainability mean. The perceptions of local workers or residents are important to gain specific information about areas which have a special ecosystem for agriculture and animals.
Environmental planning and management can have positive effects on development of some land uses including industrial areas that have a major effect on economic, social and environmental conditions. Considering the most important problems associated with modeling, the fundamental methods and functions of site-selection laid inside the geographical information system are not accounted for the multi-purpose experimental programs. The main purpose of this study is to present a systematic pattern for environmental management using genetic algorithm and fuzzy analytic hierarchy process in geographical information system in order to reduce uncertainty. Through fuzzy analytic hierarchy process, the weight of criteria was calculated after extracting the criteria by Delphi technique and identifying all the effective criteria and factors involved in site selection. After preparation of intended layers, each map was prepared in the form of raster layers on geographical information system. Information layers were combined after being valued and finally the map of suitable areas was prepared. Finally, the conformity of all the obtained maps was checked out with field conditions. In this study, the genetic algorithm was used as an optimization method applied for natural selection. It was also attempted to find better solutions among others. The results showed the best site for developing industries.
Breast cancer is the most common cancer type among women all over the world. Chemotherapy is the use of anticancer medicines for treating cancer but it has many side effects and cells may become resistant to these chemical medicines. Therefore, finding new compounds of natural origin could be a promising solution to this problem. The aim of the current study was to evaluate anticancer activity of fucoxanthin which is the most important carotenoid found in the marine brown seaweeds and diatoms. fucoxanthin has many properties (antioxidant, antibacterial, anticancer, antiobesity, antiinflammatory and etc.) due to its unique structure. Samples with different concentrations (10, 25 and 50 μg/ ml) and at various incubation times were collected (6, 24 and 48 hours) from four different species (Padina tenuis, Colpomenia sinuosa, Iyengaria stellate and Dictyota indica) of brown seaweeds from Qeshm Island, Persian Gulf. Moreover, the anticancer activity of fucoxanthin-containing extracts on breast cancer cells line and normal human skin fibroblast cells line was assessed by MTT [3-(4,5-dimethylthiazolyl)-2,5-diphenyltetrazolium bromide] assay to specify the cytotoxic effects. The results showed that fucoxanthin extract from Dictyota. indica at 24-hour treatment and 50 μg/ml concentration has the most effective anticancer activity on the breast cancer cells line, without toxic effects to the normal cells. According to the obtained results, it seems that Dictyota. Indica is a good candidate for further analysis and can be introduced to the food and pharmaceutical industries.
Among the emerging environmental issues within Sub-Saharan Africa is the haphazard disposal of plastic waste, some of which end up downstream in the marine environment leading to negative effects. Notably there have been cases of humpback whales getting entangled in 'ghost' fishing nets, and endangered turtles ingesting plastic wastes in Watamu beach in Kenya. The aim of the current study was to assess the composition and management of plastic waste discarded by households in Watamu ward. Stratified random sampling was used to collect data from households in four sub-locations within Watamu ward. Data were analysed using descriptive and inferential statistics (the Freeman-Halton extension of the Fisher's Exact test). The composition of plastics usually discarded as waste by households in order of dominance were low density polyethylene, polyethylene terephthalate, high density polyethylene and polypropylene (FH=37.959, p = 0.000). From the results, only 0.7% of respondents recycled their plastic waste. The most preferred disposal method of household plastic waste was open dumpsites (61.4%) followed by burning (12.9%) and discards (6.4%). Majority of respondents (93.6%), re-use some plastic containers for food, water, and oil storage. There was a significant difference in terms of how the respondents re-used their plastic waste in the four sub-locations (FH=36.437, p=0.005). In conclusion, the current plastic waste disposal methods at Watamu are not environmentally friendly and recycling is still at a smaller scale despite its potential to generate income and clean the environment, and promote ecosystem services and human wellbeing.
Multivariate statistical techniques such as cluster analysis, multidimensional scaling and principal component analysis were applied to evaluate the temporal and spatial variations in water quality data set generated for two years (2008-2010) from six monitoring stations of Veli-Akkulam Lake and compared with a regional reference lake Vellayani of south India. Seasonal variations of 14 different physicochemical parameters analyzed were as follows: pH (6.42-7.48), water temperature (26.0-31.28°C), salinity (0.50-26.81 ppt), electrical conductivity (47-20656.31 µs/cm), dissolved oxygen (0.078-7.65 mg/L), free carbon-dioxide (3.8-51.8 mg/L), total hardness (27.20-2166.6 mg/L), total dissolved solids (84.66-4195 mg/L), biochemical oxygen demand (1.57-25.78 mg/L), chemical oxygen demand (5.35-71.14 mg/L), nitrate (0.012-0.321 µg/ml), nitrite (0.24-0.79 µg/ml), phosphate (0.04-5.88 mg/L), and sulfate (0.27-27.8 mg/L). Cluster analysis showed four clusters based on the similarity of water quality characteristics among sampling stations during three different seasons (pre-monsoon, monsoon and post-monsoon). Multidimensional scaling in conjunction with cluster analysis identified four distinct groups of sites with varied water quality conditions such as upstream, transitional and downstream conditions in Veli-Akkulam Lake and a reference condition at Vellayani Lake. Principal Component Analysis showed that Veli-Akkulam Lake was seriously deteriorated in water quality while acceptable water quality conditions were observed at reference lake Vellayani. Thus the present study could estimate the effectiveness of multivariate statistical approaches for assessing water quality conditions in lakes.
Surface waters are the most important economic resource for humans which provide water for agricultural, industrial and anthropogenic activities. Surface water quality plays vital role in protecting aquatic ecosystems. Unplanned urbanization, intense agricultural activities and deforestation are positively associated with carbon, nitrogen and phosphorous related water quality parameters. Multiple buffers give robust land use land cover and water quality model and highlight the impacts of land use land cover characteristics on water quality parameters at various scales which will guide watershed managers for particular application of best management practices to enhance stream health. Traditionally, water quality data collections are based on discrete sampling and were analyzed through statistical techniques which were designed for spatially isolated measurements. Traditional multivariate statistical approaches uncover hidden information in water quality data but they are unable to expose spatial relationship. The complexity of information in water quality data needs new statistical approaches which uncover spatiotemporal variability. This review briefly discusses influences of land use land cover characteristics on surface water quality, effects of spatial scale on land use land cover- water quality relationship, and water quality modeling using various statistical approaches. Every statistical method has unique purpose, application and solves different problems. This review article pinpoints that how statistical approaches in combination with spatial scale can be applied to develop statistically significant land use land cover- water quality relationship for better water quality evaluation.
In this study, adaptive neuro-fuzzy inference system, and feed forward neural network as two artificial intelligence-based models along with conventional multiple linear regression model were used to predict the multi-station modelling of dissolve oxygen concentration at the downstream of Mathura City in India. The data used are dissolved oxygen, pH, biological oxygen demand and water temperature at upper, middle and downstream of the river. To predict outlet of dissolved oxygen of the river in each station, considering different input combinations as i) 11 inputs parameters for all three locations except, dissolved oxygenat the downstream ii) 7 inputs for middle and downstream except dissolved oxygen, at the target location and lastly iii) 3 inputs for downstream location. To determine the accuracy of the model, root mean square error and determination coefficient were employed. The simulated results of dissolved oxygen at three stations indicated that, multi-linear regression is found not to be efficient for predicting dissolved oxygen. In addition, both artificial intelligence models were found to be more capable and satisfactory for the prediction. Adaptive neuro fuzzy inference system model demonstrated high prediction ability as compared to feed forward neural network model. The results indicated that adaptive neuro fuzzy inference system model has a slight increment in performance than feed forward neural network model in validation step. Adaptive neuro fuzzy inference system proved high improvement in efficiency performance over multilinear regression modeling up to 18% in calibration phase and 27% in validation phase for the best models.
The major aim of the present study was to investigate element (Fe, Ni, Pb, V, Zn) concentrations in sediment and different tissues of Phragmities australis and Typha latifolia in Hor al-Azim Wetland Southwest Iran. Sampling of sediments and aquatic plants was carried out during spring and summer 2014. Results showed that the mean concentrations of elements in Phragmities australis in root and stem-leaf were as follows: Iron:4448 mg/kg, Nickel: 28 mg/kg, Lead:8 mg/kg, Vanadium:10 mg/kg and Zinc 15.5 mg/kg in root and: Fe:645 mg/kg, Ni:15 mg/kg, Pb:4 mg/kg, V:4 mg/kg and Zinc 16 mg/kg respectively. Also, the mean concentrations of Fe, Ni, Pb, V and Zn in roots of Typha latifolia were 8696 mg/kg, 34 mg/kg, 5 mg/kg, 19 mg/kg and 27 mg/kg respectively. The mean concentrations of Fe, Ni, V, Pb, Zn in stem-leaves of Typha latifolia were as follows: 321 mg/kg, 3 mg/kg, 7 mg/kg, 2 mg/kg and 14 mg/kg respectively. The mean concentrations of Fe, Ni, V, Pb and zinc were as: 40991 mg/kg, 65 mg/kg, 60 mg/kg, 31 mg/kg, 60 mg/kg respectively in surface sediment of study area. Concentration pattern of elements in sediment were as: Fe>Ni>Zn>V>Pb. The highest concentration of elements in the plant was seen in the roots. Also, Typha latifolia can uptake more concentration of elements than Phragmities australis. Based on the enrichment factor, Ni in summer had the highest EF values among the elements studied and it has a moderate enrichment.
The aim of this study was to evaluate the ability of microalgae Spirulina platensis and Chlorella vulgaris to remove nitrate and phosphate in aqueous solutions. Spirulina platensis and Chlorella vulgar is microalgae was collected in 1000 ml of municipal water and KNO3, K2HPO4 was added as sources of nitrate and phosphate in three different concentrations (0.25, 0.35 and 0.45g/L). During the growth period, the concentration of nitrate and phosphate was recorded at 1, 4, 6 and 8 days. The highest nitrate removal on the 8 day for Chlorella vulgaris was 89.80% at the treatment of 0.25g/L and for Spirulina platensis was 81.49% at the treatment of 0.25g/L. The highest phosphate removal for Spirulina platensis was 81.49% at the treatment of 0.45g/L and for Chlorella vulgaris was 88% at the treatment of 0.45g/L. The statistical results showed that the amount of phosphate and nitrate removal during different time periods by Chlorella vulgaris depicted a significant difference at P<0.01, while Spirulina platensis demonstrated a significant difference at P<0.05.Thus, Spirulina platensis and Chlorella vulgaris can be effectively used to remove nitrate and phosphate from effluent and waste water treatments, although it demands more research in different climatic conditions.
The current study aimed to examine the overall feasibility of the use of copper oxide nanoparticles as a catalyst in ozonation process for the removal of benzene from aqueous solutions under experimental conditions. This experimental study was conducted on a laboratory scale reactor in a semibatch mode. The effect of critical operating parameters such factors as pH, concentration of benzene, reaction time and nano-catalyst dose on the removal of benzene was investigated. The samples included with benzene concentrations (10-200 mg/L), pH (3-13), catalyst dose (0.1-0.5 mg), and ozonation time (5- 50 min). Findings indicated that the removal of benzene depended on various utilization parameters. The highest efficiency was achieved at reaction time of 50 min, pH of 12, initial benzene concentration of 10 mg/L and catalyst dose of 0.5 g. Among the studied factors, the maximum and the minimum contributions were made by the dose of nanoparticles (83%) and the reaction time (~73%). The software predicted that use of 0.13 g of the catalyst at pH of 12 and ozonation time of 5 min would lead to a removal efficiency of 68.4%. The catalytic ozonation process was able to remove benzene, and addition of copper oxide nanoparticles as a catalyst together with the ozonation process increased the benzene removal efficiency. The values of R² = 0.9972, adjusted R2= 0.9946, and predicted R² =0.9893 indicated that the model was acceptably predicted by the software and fitted the data obtained in the experiments.
In this study, the photocatalytic degradation of azo-dye acid orange 10 was investigated using titanium dioxide catalyst suspension, irradiation with ultraviolet-C lamp and bismuth vanadate under visible light of light-emitting diode lamp. Response surface methodology was successfully employed to optimize the treatment of acid orange 10 dye and assess the interactive terms of four factors. The characteristics of catalysts were determined by field emission scanning electron microscopes, X-ray diffraction and Fourier transform infrared spectroscopy. The optimum values of initial dye concentration, initial pH, irradiation time and catalyst dose were found 11.889 mg/L, 4.592, 12.87 min, and 0.178 g/100 mL for ultraviolet/titanium dioxide process, respectively, and 10.919 mg/L, 3.231, 320.26 min and 0.239 g/100 mL for visible/bismuth vanadate process, respectively. The removal efficiencies obtained for acid orange 10 were 100% and 36.93% after selecting the optimized operational parameters achieved for titanium dioxide and bismuth vanadate, respectively. The highest efficiency was achieved by the use of ultraviolet/titanium dioxide system, while a low acid orange 10 removal efficiency was obtained for the synthesized bismuth vanadate using the co-precipitation method. Thus, it seems necessary to increase the photocatalytic activity of bismuth vanadate in combination with titanium dioxide to remove acid orange 10 dye in subsequent studies.
Mapungubwe Cultural Landscape (MCL) woody vegetation was characterized to establish structural and compositional attributes. Stratified random sampling based on major soil types was used and nine plant variables were measured in 137(20x30) m² sampling plots; these being genera, species and family names; basal circumference; plant height; depth and diameter of tree canopy; number of stems per plant; plant life status; number of trees and shrubs; and number of saplings. A total of 3114 woody plants were sampled, comprising an assemblage of 28 families, 63 genera and 106 species. The results suggest alluvial floodplain flanking the Limpopo River is a biodiversity hotspot with high plant species diversity (H'=1.8-2.2) 1/ha, taller trees (P<0.05) with median height per plot ranging between 6.1-10 m, high canopy volume at 105783 (443155m³/ha) and basal area (16.9-111m²/ha). The Arenosols-Regosol stratum had significantly shorter trees (P<0.05) with median height per plot between 3-4 m, low species diversity (H'=0.8-2.3) 1/ha, low basal area (3.23-48.2m²/ha) and low canopy volume (6687.08(155965.00) m³/ha. The Cambisol-Luvisol stratum in the western section of MCL had high number of stems/plant at 1.65 (1.40), high woody plant density 483.33 (900.00) 1/ha, F3,137=19.07, P<0.05), high density of dead plants 16.67 (133.30) 1/ha and high sapling density 208.33 (850.00) 1/ha. The present study suggests soil type is a key determinant of woody vegetation structure and composition. The study recommends regular vegetation monitoring, periodic update of plant species inventories in protected areas, control of exotic invasive woody plant species found along the Limpopo river floodplain within the biodiversity management framework of Greater Mapungubwe Transfrontier Conservation Area initiative.
The proper use of natural resources can preserve these valuable assets. In line with the management of natural resources, land use optimization can be highly useful. The aim of the present study is to propose an appropriate integrative model for optimized allocation of lands for surface runoff and sediment load minimization and net income maximization in Bayg watershed, Iran. In this study, five categories of land uses, i.e. irrigated orchard, rangeland, irrigated farming, rainfed farming and almond orchard were spatially optimized to minimize surface runoff and sediment yield and to increase net income by integrating three approaches: weighted goal programming, analytic hierarchy process and multi-objective land allocation algorithm. To achieve the target levels in this work, the acreages of almond orchard and rainfed farming should be reduced by 100% and 37.32% respectively, and irrigated farming acreage should be increased by 138.53%. Through these alterations in the land use acreage, the sediment load will be reduced by 16.78% and net income will be improved by 72.52%. However, runoff volume will be increased by 0.22%. Results indicated that weighted goal programming satisfied 96% and 46% of the target levels of sediment load and net income respectively, but failed to reduce runoff volume. Therefore, it is necessary for managers to control runoff using the strategies related to runoff harvesting, especially on steep slopes. Generally, it can be concluded that a combination of the techniques weighted goal programming, analytic hierarchy process and multi-objective land allocation is highly capable to optimize land use and land covers based on the conflicting objectives.
The change of land use/land cover has been known as an imperative force in environmental alteration, especially in arid and semi-arid areas. This research was mainly aimed to assess the validity of two major types of land change modeling techniques via a three dimensional approach in Birjand urban watershed located in an arid climatic region of Iran. Thus, a Markovian approach based on two suitability and transition potential mappers, i.e. fuzzy analytic hierarchy process and artificial neural network-multi layer perceptron was used to simulate land use map. Validation metrics, quantity disagreement, allocation disagreement and figure of merit in a three-dimensional space were used to perform model validation. Utilizing the fuzzy-analytic hierarchy process simulation of total landscape in the target point 2015, quantity error, the figure of merit and allocation error were 2%, 18.5% and 8%, respectively. However, Artificial neural network-multi layer perceptron simulation led to a marginal improvement in figure of merit, i.e. 3.25%.
The aim of this study is to investigate the problems caused by discharge of polluted air from tunnels into the environment with a specific focus on residential areas. In city tunnels, portal or stacks, pollutant management is a big challenge. Nowadays, air quality management, particularly in urban tunnels, is considered as a part of the ventilation system design. The goal is to see the environmental impacts beforehand. From environmental aspects, preventive measures are required either inside or outside the tunnel in some cases. Niayesh tunnel in Tehran is taken as a case for proving the objectives presented in this study. Concentration of carbon monoxide at the vicinity of the portals is calculated using the proper dispersion simulation. The results of dispersion modeling for the assumed worst case of ventilation can help to understand the environmental impact of ventilation. The worst traffic emissions for a congested traffic scenario,are selected as an emission source for dispersion modeling. According to the traffic condition and fleet composition, the crucial emission extracted from the tunnel is carbon monoxide. Therefore, the performed simulation only focuses on carbon monoxide dispersion modeling. From the other side, carbon monoxide is taken as a demonstration pollutant, because it is inert and chemical reactions can be neglected in short-term considerations. A lagrangian model composed of Graz Lagrangian Model and Graz Mesoscale Model is used for flow-field and dispersion calculations.
Most parts of the urban areas are faced with the problem of floating fine particulate matter. Therefore, it is crucial to estimate the amounts of fine particulate matter concentrations through the urban atmosphere. In this research, an artificial neural network technique was utilized to model the PM2.5 dispersion in Tehran City. Factors which are influencing the predicted value consist of weather-related and air pollutionrelated data, i.e. wind speed, humidity, temperature, SO2, CO, NO2, and PM2.5 as target values. These factors have been considered in 19 measuring stations (zones) over urban area across Tehran City during four years, from March 2011 to March 2015. The results indicate that the network with hidden layer including six neurons at training epoch 113, has the best performance with the lowest error value (MSE=0.049438) on considering PM2.5 concentrations across metropolitan areas in Tehran. Furthermore, the "R" value for regression analysis of training, validation, test, and all data are 0.65898, 0.6419, 0.54027, and 0.62331, respectively. This study also represents the artificial neural networks have satisfactory implemented for resolving complex patterns in the field of air pollution.
Giant bamboo Dendrocalamus asper is recommended in environmental and livelihood programs in the Philippines due to its various ecological, economic and social benefits. However, there are limited data on the ecology of giant bamboo litterfall production, which contributes to soil nutrient availability. Bamboo also contributed in carbon sequestration. The study was conducted within the Taganibong Watershed in Bukidnon, Philippines. Nine litterfall traps measuring 1mx1m were established within the giant bamboo stand in the study area. Results show that giant bamboo litterfall is dominated by leaves. Biological characteristics of bamboo litterfall do no not influence litterfall production but temperature, wind speed and humidity correlate with the amount of litterfall. Findings of the study further revealed that fresh giant bamboo tissue contains high carbon content and the soil in the bamboo stand has higher organic matter than the open clearing. These data indicate the role of giant bamboo in carbon sequestration and soil nutrient availability.
As wind energy is one of the most important renewable energy sources over the globe, need for increasing safety for this type of energy is gaining importance. Although this sector is not suffering an excessive amount of fatal injury accidents, there are many aspects open for improvements in occupational health and safety management. The construction and operation processes of wind turbines include several hazards that must be reduced. This study aims to present a risk assessment for the construction and operation period of wind tribunes using a new fuzzy based method. Fuzzy analytical hierarchy process, a common used multi criteria decision making method, is applied to assign weights to the parameters of Fine-Kinney risk analysis method. Then, fuzzy VIKOR method is used to prioritize hazards. A case study is carried out for an onshore wind turbine in Turkey by using occupational health and safety experts in weighting risk parameters and evaluating compromised rankings of the hazards. Results reveal the most important hazards both for construction and operation period of the wind tribune. On conclusion of the current study, control measures for those risks and possible corrective-preventive actions for improvement are also provided.
Eutrophication is considered as a serious problem in water reservoirs. Awareness about the eutrophic status of each reservoir could help in providing a better understanding of the problem in a global scale. The present study was conducted to assess temporal and spatial eutrophication index in a water reservoir (Sahand dam) in the northwest of Iran. Physico-chemical parametres that are effective on eutrphic condition occurrence were analyzed, and trophic state index was calculated on a scale of 0-100 by measuring Secchi disk depth, chlorophyll a, total phosphorus, total nitrogen, total suspended solids, and phosphorus P/N ratio. Moreover, using the overlapping, the reservoir was mapped based on the mentioned index. Seasonal variation of dissolved solids in the reservoir was recorded due to precipitation and subsequent dilution and evaporation. Thermal stratification was observed during the summer months. The total trophic state index value was calculated as 55.5-58.07, with minimum value belonging to P/N and maximum value belonging to suspended solids for individual parameters. There were some spatial and temporal differences for trophic state index in the reservoir. It was found that the whole area of the reservoir was in almost moderately upper-mesotrophic condition and in some target stations it was very close to eutrophic condition. The worst condition was observed in Qaranqu River as the main input to the reservoir. Due to the significant impact of suspended particles resulting from erosion of the surrounding lands on TSI value, there is an urgent need for mitigation measures to intercept eutrophication.
Economic evaluation of 12 MW grid-connected wind farms and PV power plants in two regions in Northern Cyprus for electricity generation was investigated. The wind speed, sunshine duration, and solar global radiation characteristics were analyzed using monthly data collected over 17 years (2000- 2016) for Girne and nine years (2008-2016) for Lefkosa, which were measured at various heights. The result showed that during 2000-2016, the mean wind speed at Girne was 2.505 m/s and during 2008-2016, the mean wind speed at Lefkosa was 2.536 m/s. The result showed that both regions had annual mean wind speed greater than 2 m/s at 10 m height. Moreover, the annual mean sunshine duration and global solar radiation were higher than seven h/day and 15 MJ./m²/day at a height of 2 m for all studied regions, respectively. In this study, eight distribution functions were used to analyze the wind speeds and global solar radiation data in each region. The results indicated that Weibull and Logistic were the best distributions for analyzing the wind speeds and global solar radiation data of the studied regions, respectively. Furthermore, the capacity factors of the selected regions ranged between 1.92% and 48.53%. Based on the renewable energy cost results, it is found that the generation costs of the wind farm were between 0.023 and 0.04 Euro/ kWh, while the PV plant was between 0.08 and 0.098 Euro/kWh.