Environmental Engineering
D. Fadhiliani; M. Ikhwan; M. Ramli; S. Rizal; M. Syafwan
Abstract
BACKGROUND AND OBJECTIVES: The hydrodynamic uncertainty of the ocean is the reason for testing marine structures as an initial consideration. This uncertainty has an impact on the natural structure of the topography as well as marine habitats. In the hydrodynamics laboratory, ships and offshore structures ...
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BACKGROUND AND OBJECTIVES: The hydrodynamic uncertainty of the ocean is the reason for testing marine structures as an initial consideration. This uncertainty has an impact on the natural structure of the topography as well as marine habitats. In the hydrodynamics laboratory, ships and offshore structures are tested using mathematical models as input to the wave marker. For large wavenumbers, Benjamin Bona Mahony's equation has a stable direction and position in the wave tank. During their propagation, the generated waves exhibit modulation instability and phase singularity phenomena. These two factors refer to Benjamin Bona Mahony as a promising candidate for generating extreme waves in the laboratory. The aim of this research is to investigate the distribution of energy in each modulation frequency change. The Hamiltonian formula that describes the phenomenon of phase singularity is used to observe energy. This data is critical in determining the parameters used to generate extreme waves. METHODS: The envelope of the Benjamin Bona Mahony wave group can be used to study the Benjamin Bona Mahony wave. The Benjamin Bona Mahony wave group is known to evolve according to the Nonlinear Schrodinger equation. The Hamiltonian governs the dynamics of the phase amplitude and proves the Nonlinear Schrodinger equation's singularity for finite time. The Hamiltonian is derived from the appropriate Lagrangian for Nonlinear Schrodinger and then transformed into the Hamiltonian with the displaced phase-amplitude variable. FINDINGS: Potential energy is related to wave amplitude and kinetic energy is related to wave steepness in the study of surface water waves. When , the maximum wave amplitude and steepness are obtained. When , extreme waves cannot be formed due to steepness. This is due to the possibility of breaking waves into smaller waves on the shore. In terms of position, the energy curve is symmetrical. CONCLUSION: According to Hamiltonian's description of the energy distribution, the smaller the modulation frequency, the greater the potential and kinetic energy involved in wave propagation, and vice versa. While the wave's amplitude and steepness will be greatest for a low modulation frequency, and vice versa. The modulation frequency considered as an extreme wave generator is , because the resulting amplitude is quite high and the energy in the envelope is also quite large.
Environmental Engineering
J. O. Castillo-Miranda; F. J. Rodríguez-Gómez; J. Genescá-Llongueras; L. G. Ruiz-Suárez; J. A. García-Reynoso
Abstract
BACKGROUND AND OBJECTIVES: Atmospheric zinc corrosion in the Mexico City Metropolitan area has long been attributed mainly to the effect of pollutants such as sulfur dipxide. There are changes in the urban atmosphere's chemical composition due to the implementation of air quality policies focused on ...
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BACKGROUND AND OBJECTIVES: Atmospheric zinc corrosion in the Mexico City Metropolitan area has long been attributed mainly to the effect of pollutants such as sulfur dipxide. There are changes in the urban atmosphere's chemical composition due to the implementation of air quality policies focused on reducing the emission of sulfur dipxide and other pollutants. This study's objectives were to estimate and map the contribution of nitric acid on zinc's atmospheric corrosion process METHODS: The impact of nitric acid on zinc is feasible to estimate using a function for a multi-pollutant situation. This function contemplates the sum of two contributions: one of nitric acid and another that includes sulfuric acid and climatic parameters. The multi-pollutant function is suitable to apply in areas without the strong influence of chlorides and tropical and subtropical climates, comparable to the Mexico City Metropolitan area. FINDINGS: The results showed that spatial and temporal estimation of corrosion rates in grams per square meter of zinc was made for 2015-2019, using data modeling in a geographic information system. The maps of corrosion rates allowed us to visualize that, in general, the "southwest" zone has the most significant effects and that the lowest corrosion rates were presented in 2019 as an outcome of the implementation of air quality programs. Furthermore, a contribution of nitric acid up to 32% to the zinc corrosion rate was estimated. CONCLUSION: The construction of corrosion rate maps provides a spatial and temporal estimate that allows visualizing areas where zinc materials are at risk corrosion due to the dispersion of atmospheric pollutants and climatic parameters. Likewise, it can represent a decision-making tool for the implementation of atmospheric corrosion studies of materials.
Environmental Engineering
M. Ikhwan; R. Wafdan; Y. Haditiar; M. Ramli; Z. A. Muchlisin; S. Rizal
Abstract
BACKGROUND AND OBJECTIVES: El Niño - Southern Oscillation is known to affect the marine and terrestrial environment in Southeast Asia, Australia, northern South America, and southern Africa. There has been much research showing that the effects of El Niño - Southern Oscillation are extensive. ...
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BACKGROUND AND OBJECTIVES: El Niño - Southern Oscillation is known to affect the marine and terrestrial environment in Southeast Asia, Australia, northern South America, and southern Africa. There has been much research showing that the effects of El Niño - Southern Oscillation are extensive. In this study, a simulation of an El Niño event is carried out, which is ideal in the vertical layer of the Pacific Ocean (0-250 meters). The fast Fourier transform is used to process the vertical modeling data so that the results can accurately represent El Niño. METHODS: A non-hydrostatic 3-dimensional numerical model is used in this research. To separate the signal produced and obtain the quantitative difference of each sea layer, the simulation results are analyzed using the fast Fourier transform. Winds blow from the west to the east of the area in perfect El Niño weather, with a reasonably high wind zone near the equator (forming a cosine). Open fields can be found on the north and south sides, while closed fields can be found on the west and east sides. Density is uniform up to a depth of 100 meters, then uniformly increases by 1 kilogram per cubic meter from 100 to 250 meters. FINDINGS: The results of the model simulation show that one month later (on the 37th day), the current from the west has approached the domain's east side, forming a complete coastal Kelvin wave. The shape of coastal Kelvin waves in the eastern area follows a trend that is similar to the OSCAR Sea Surface Velocity plot data obtained from ERDDAP in the Pacific Ocean in October 2015. In this period, the density at a depth of 0-100 meters is the same, while the density at the depth layer underneath is different. CONCLUSION: Strong winds could mix water masses up to a depth of 100 meters, implying that during an ideal El Niño, the stratification of the water column is influenced by strong winds. The eastern domain has the highest sea level amplitude, resulting in perfect mixing up to a depth of 100 m, while wind effect is negligible in the lower layers. The first layer (0-50 m) and the second layer (50-100 m) have the same density and occur along the equator, according to FFT. The density is different and much greater in the third layer (100-150 m).
Environmental Engineering
N. Amani; F. Tirgar Fakheri; K. Safarzadeh
Abstract
BACKGROUND AND OBJECTIVES: According to the latest energy balance sheets, the average energy consumption in the residential sector of Iran is about 41% of the total energy consumption in the country. Increasing the energy efficiency of buildings can decrease the annual energy consumption in the residential ...
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BACKGROUND AND OBJECTIVES: According to the latest energy balance sheets, the average energy consumption in the residential sector of Iran is about 41% of the total energy consumption in the country. Increasing the energy efficiency of buildings can decrease the annual energy consumption in the residential sector and, thereby, the energy costs of families. The objectives of this study were to evaluate and prioritize the effective factors in reducing the energy consumption in residential buildings in the north of Iran using the climatic conditions analysis. METHODS: In the first step, the amount of energy consumption in the cooling and heating section was estimated in the base conditions, and in the next step, the amount of energy consumption was calculated. The obtained results were compared with each other with the help of optimization strategies for energy consumption using the Design Builder software. Finally, a set of effective factors were determined to be involved in decreasing the energy consumption. FINDING: The results showed that application of the LED lamps instead of the conventional fluorescent lamps could decrease the energy consumption by 980.4 kWh. Moreover, changing the materials of the walls and ceiling, using the polyurethane foam insulation with the thickness of 20 mm, and using the double-glazed UPVC windows reduced the energy consumption by 770 kWh. Energy reduction of about 101.5 kWh was also obtained after external movable awning and internal blind. CONCLUSION: The most commonly used materials were analyzed by the Design Builder software. The analysis was done by integrating building architecture engineering (the best form of orientation and facade) based on the reasonable costs of consuming common materials in the area. The obtained results can be used for both evaluating the energy efficiency in residential buildings and producing a comfortable living environment in a moderate and humid climate.
Environmental Engineering
G.R. Puno; R.A. Marin; R.C.C. Puno; A.G. Toledo-Bruno
Abstract
BACKGROUND AND OBJECTIVES: The study explored the capability of the geographic information system interface for the water erosion prediction project, a process-based model, to predict and visualize the specific location of soil erosion and sediment yield from the agricultural watershed of Taganibong. ...
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BACKGROUND AND OBJECTIVES: The study explored the capability of the geographic information system interface for the water erosion prediction project, a process-based model, to predict and visualize the specific location of soil erosion and sediment yield from the agricultural watershed of Taganibong. METHODS: The method involved the preparation of the four input files corresponding to climate, slope, land management, and soil properties. Climate file processing was through the use of a breakpoint climate data generator. The team had calibrated and validated the model using the observed data from the three monitoring sites. FINDINGS: Model evaluation showed a statistically acceptable performance with coefficient of determination values of 0.64 (probability value = 0.042), 0.85 (probability value = 0.000), and 0.69 (probability value = 0.001) at 95% level, for monitoring sites 1, 2, and 3, respectively. A further test revealed a statistically satisfactory model performance with root mean square error-observations standard deviation ratio, Nash-Sutcliffe efficiency, and percent bias of 0.62, 0.61, and 44.30, respectively, for monitoring site 1; 0.65, 0.56, and 25.60, respectively, for monitoring site 2; and 0.60, 0.65, and 27.90, respectively, for monitoring site 3. At a watershed scale, the model predicted the erosion and sediment yield at 89 tons per hectare per year and 22 tons per hectare per year, respectively, which are far beyond the erosion tolerance of 10 tons per hectare per year. The sediment delivery ratio of 0.20 accounts for a total of 126,390 tons of sediments that accumulated downstream in a year. CONCLUSION: The model generated maps that visualize a site-specific hillslope, which is the source of erosion and sedimentation. The study enables the researchers to provide information helpful in the formulation of a sound policy statement for sustainable soil management in the agricultural watershed of Taganibong.
Environmental Engineering
C. Turan
Abstract
The present study aims to predict the potential geographic distribution and future expansion of invasive alien lionfish (Pterois miles) with ecological niche modelling along the Mediterranean Sea. The primary data consisted of occurrence points of P. miles in the Mediterranean and marine climatic data ...
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The present study aims to predict the potential geographic distribution and future expansion of invasive alien lionfish (Pterois miles) with ecological niche modelling along the Mediterranean Sea. The primary data consisted of occurrence points of P. miles in the Mediterranean and marine climatic data layers were collected from global databases. All the used models run 100% success predictions, and true skill statistics and area under the receiver operating characteristic curve values ranged from 0.42 and 0.71 to 0.86 and 0.95 for current distribution modelling; and 0.0 and 0.0 to 0.83 and 0.94 for the future distribution modelling, respectively. The mean sea surface temperature and maximum bathymetry played an important role in the prediction of the model and explained relatively higher biological importance to the extension and adaptation of P. miles with extreme environmental factors. The predicted suitable habitats of P. miles under the current climate dominantly occurred in the east parts of coastal areas of the Mediterranean. The predicted future suitable habitats of P. miles revealed that P. miles increase its range of distribution dominantly to the central and west part of the Mediterranean in a spatial extent, indicating high suitability of these areas for its future distribution.
Environmental Engineering
R.E. Caraka; Y. Lee; R. Kurniawan; R. Herliansyah; P.A. Kaban; B.I. Nasution; P.U. Gio; R.C. Chen; T. Toharudin; B. Pardamean
Abstract
COVID-19 has a severe and widespread impact, especially in Indonesia. COVID-19 was first reported in Indonesia on March 03, 2020 then rapidly spread to all 34 provinces by April 09, 2020. Since then, COVID-19 is declared a state of national disaster and health emergency. This research analyzes ...
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COVID-19 has a severe and widespread impact, especially in Indonesia. COVID-19 was first reported in Indonesia on March 03, 2020 then rapidly spread to all 34 provinces by April 09, 2020. Since then, COVID-19 is declared a state of national disaster and health emergency. This research analyzes the difference of CO, HCHO, NO2, and SO2 density in Jakarta, West Java, Central Java, and South Sulawesi before and during the pandemic. Also, this study assesses the effect of large scale restrictions on the economic growth during COVID-19 pandemic in Indonesia. In a nutshell, the results on Wilcoxon and Fisher test by significance level α=5% as well as odds ratio showed that there are significant differences of CO density in all regions with highest odds ratio in East Java (OR=9.07), significant differences of HCHO density in DKI Jakarta, East Java, and South Sulawesi. There are significant differences of NO2 density before and during public activities limitation in DKI Jakarta, West Java, East Java, and South Sulawesi. However, the results show that there are no significant differences of SO2 density in all regions. In addition, this research shows that there are significant differences of retail, grocery and pharmacy, and residental mobility before and during the COVID-19 pandemic in Indonesia. This research also shows that during the COVID-19 pandemic there are severe economic losses, industry, companies, and real disruptions are severe for all levels of life due to large scale restrictions.
Environmental Engineering
F.M. Torres-Bejarano; A.C. Torregroza-Espinosa; E. Martinez-Mera; D. Castañeda-Valbuena; M.P. Tejera-Gonzalez
Abstract
Ciénaga de Mallorquín is a coastal lagoon designated as a RAMSAR site due to its ecological regional and international importance. In this work, the environmental fluid dynamics code explorer modeling system was implemented to determine the spatio-temporal distribution of temperature, dissolved ...
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Ciénaga de Mallorquín is a coastal lagoon designated as a RAMSAR site due to its ecological regional and international importance. In this work, the environmental fluid dynamics code explorer modeling system was implemented to determine the spatio-temporal distribution of temperature, dissolved oxygen, chemical oxygen demand and nutrient levels, and assess the trophic status of Ciénaga de Mallorquín. The model was set up with field measurement data taken during transition period and wet season, and secondary information obtained from local authorities and environmental agencies. The results of model simulations were calibrated and verified by the root mean square error method, achieving a consistent fit for all considered variables. Average velocities were between 0.006 m/s and 0.013 m/s during the analyzed periods. The temperature was higher in the wet season than in the transition period (29°C and 31.5°C, respectively). The dissolved oxygen was similar in both periods (6.6 and 6.7 mg/L). NO3 concentrations were higher during the transition period (3.28 mg/L), with a minimum of 1.76 mg/L and a maximum of 5.09 mg/L. The lowest NO3 concentrations were found in the area influenced by the connection with the Caribbean Sea. PO4 concentrations in the wet season were lower than in the transition period (0.20 mg/L). Finally, Ciénaga de Mallorquín exhibits high productivity levels with Trophic State Index > 50 and temporal variations of mesotrophic to eutrophic. The use of Trophic State Index is useful for the management of water body eutrophication and productivity, making it particularly important in aquatic ecosystems.
Environmental Engineering
M. Camara; N.R.B. Jamil; A.F.B. Abdullah; R.B. Hashim
Abstract
Predicting land use change is an indispensable aspect in identifying the best development and management of land resources and their potential. This study used certified land-use maps of 1997, 2006, and 2015 combined with ancillary data such as road networks, water bodies and slopes, obtained from the ...
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Predicting land use change is an indispensable aspect in identifying the best development and management of land resources and their potential. This study used certified land-use maps of 1997, 2006, and 2015 combined with ancillary data such as road networks, water bodies and slopes, obtained from the Department of Agriculture and the Department of Surveying and Mapping in Malaysia, respectively. The prediction of future land use changes in the Selangor River basin in Malaysia was performed using the Cellular Automata Markov model. The transition probability matrices were computed using the land use conditions of the periods 1997-2006, 2006-2015, 1997-2015. The performance of the model was very good in its overall ability to simulate the actual land use map of 2015, with the index values of 0.92% and 0.97%, respectively for Kappa for no information and Kappa for grid-cell level location which indicated the reliability of the model to successfully simulate land use changes in 2024 and 2033. Based on the expected results, the future urban area will grow faster (33%) over the next two decades, leading to a decline in forest area that is expected to lose 8% of its total space during these periods. Agricultural land will increase to 4%, while water bodies will change slightly increasing to 1%, and other areas of land use will likely become reservoirs of water, topsoil or new green spaces shrinking at 30%. Given the importance of knowledge of future land use in addressing the problems of uncontrolled development on environmental quality, this study could be valuable for land use planners of the river basin largely covered by natural forest. The study however, suggests future research to integrate geospatial techniques with biophysical and socio-economic factors in simulating land use trends.
Environmental Engineering
A. Masih
Abstract
In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single ...
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In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single base classifiers such as support vector machine, multilayer perceptron, linear regression and regression tree using M5 algorithm. The prediction of Sulphur dioxide was based on atmospheric pollutants and meteorological parameters. While, the model performance was assessed by using four evaluation measures namely Correlation coefficient, mean absolute error, root mean squared error and relative absolute error. The results obtained suggest that 1) homogenous ensemble classifier random forest performs better than single base statistical and machine learning algorithms; 2) employing single base classifiers within bagging as base classifier improves their prediction accuracy; and 3) heterogeneous ensemble algorithm voting have the capability to match or perform better than homogenous classifiers (random forest and bagging). In general, it demonstrates that the performance of ensemble classifiers random forest, bagging and voting can outperform single base traditional statistical and machine learning algorithms such as linear regression, support vector machine for regression and multilayer perceptron to model the atmospheric concentration of sulphur dioxide.
Environmental Engineering
G.C.B. Paclibar; E.R. Tadiosa
Abstract
Non-native plants that can cause adverse effects are otherwise known as invasive alien plant species which pose a major threat to plant biodiversity conservation and sustainability. This study is dedicated to determine the plant diversity and to assess the vulnerability of Quezon Protected Landscape, ...
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Non-native plants that can cause adverse effects are otherwise known as invasive alien plant species which pose a major threat to plant biodiversity conservation and sustainability. This study is dedicated to determine the plant diversity and to assess the vulnerability of Quezon Protected Landscape, Southern Luzon, the Philippines to invasive alien plant species. Data from 90 10x10 m randomly established plots using the quadrat method showed that there are 318 plant species wherein 208 are native, 100 are non-native, and 10 are invasive. Results from the association of the physicochemical factors and the presence of invasive alien plant species through Spearman rho test revealed that most of the physicochemical factors have significant association except percent slope and hill shade. Soil pH, aspect and number of non-native plants show positive association while soil moisture, leaf litter thickness, elevation, species richness, species evenness, plot species diversity index, and the number of native plants signify negative association. Differences between the plots of with and without invasive alien plant species in physicochemical factors indicate that most of the physicochemical factors have a significant difference between plots of with and without invasive alien plant species except percent slope, hill shade, and aspect. Lastly, the MaxEnt model exemplifies that the most suitable predicted conditions for invasive alien plant species are at the edges of boundary and buffer zones. This study implies that most of the physicochemical factors are linked to the presence of invasive alien plant species and Quezon Protected Landscape has a low vulnerability to invasive alien plant species invasion.
Environmental Engineering
G. Elkiran; V. Nourani; S.I. Abba; J. Abdullahi
Abstract
ABSTRACT: 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 ...
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ABSTRACT: 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 oxygen at 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 multi-linear regression modeling up to 18% in calibration phase and 27% in validation phase for the best models.
Environmental Engineering
S.M. Tajbakhsh; H. Memarian; K. Moradi; A.H. Aghakhani Afshar
Abstract
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 ...
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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 processsimulation 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%.
Environmental Engineering
M. Rafiei; P.J. Sturm
Abstract
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, ...
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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.
Environmental Engineering
S.M. Tajbakhsh; H. Memarian; A. Kheyrkhah
Abstract
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 ...
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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.
Environmental Engineering
J.C. Paquit; R.I.P. Rama
Abstract
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 ...
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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.
Environmental Engineering
M. Tajbakhsh; H. Memarian; Y. Shahrokhi
Abstract
Mashhad City, according to the latest official statistics of the country is the second populated city after Tehran and is the biggest metropolis in the east of Iran. Considering the rapid growth of the population over the last three decades, the city’s development area has been extended, significantly. ...
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Mashhad City, according to the latest official statistics of the country is the second populated city after Tehran and is the biggest metropolis in the east of Iran. Considering the rapid growth of the population over the last three decades, the city’s development area has been extended, significantly. This significant expansion has impacted natural lands on suburb and even some parts e.g. rangelands and agricultural area have been transited to urban land uses. The study was aimed at analyzing and simulating land use changes in Mashhad, Iran. The work needs a model to simulate land use changes among multiple categories and combine spatial and temporal changes during the projection period. Thus, Cellular Automata-Markov model was chosen to meet this target. In this work, the projected time period corresponded to the final 20-year vision period of all-round development of Iran for the target point of 2025 based on a long-term plan. Multi criteria evaluation approach integrated along with analytic hierarchy process were employed for preparing suitability maps for the five land uses, i.e. urban continuous patches, urban discontinuous patches, rural patches, agricultural lands, and range lands. Having applied the matrices utilized in model calibration, the best kappa coefficient proved to be associated with the land use maps dated 1996 and 2002. The Kappa index of quantity and allocation agreement was determined to be 0.9189 and 0.9529, respectively, which established an almost perfect agreement between simulated and observed land uses according to the year 2015. Change detection results showed that with the physical expansion of urban continuous patches, range lands and agricultural lands mostly transited to urban discontinuous patches and eventually were promoted to urban continuous texture. These developments or gains in urbanized patches will lead to some loses in agricultural lands and rangelands of the suburb in 2025. In addition, the analysis of projected land use map indicated that over the upcoming years, the development of the city in northern front, especially in northwestern region will be more intense with a higher speed in comparison with the other regions.
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