Search results for: demand multipliers

Authors: Jang-Hwan Jo

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Implementing sustainable island forest management policies requires categorizing islands into groups based on key indicators and establishing a consistent management system. Building on the results of previous studies, a typology of forested islands was established: Type 1 – connected islands with high natural vegetation cover; Type 2 – connected islands with moderate natural vegetation cover; Type 3 – connected islands with low natural vegetation cover; Type 4 – unconnected islands with high natural vegetation cover; Type 5 – unconnected islands with moderate natural vegetation cover; and Type 6 – unconnected islands with low natural vegetation cover. An AHP analysis was conducted with island forest experts to identify priority ecosystem services (ESs) for the sustainable management of each island type. In connected islands, provisioning services (natural resources, natural medicines, etc.) assumed greater importance than regulating (erosion control) and supporting services (genetic diversity). In unconnected islands, particularly those with a small proportion of natural vegetation, regulating services (erosion control) requires greater emphasis in management. Considering that Type 3 islands require urgent management as connectivity to the mainland makes natural vegetation-sparse island forest ecosystems vulnerable to anthropogenic activities, the land-use scoring method was carried out on Jin-do, a Type 3 forested island. Comparisons between AHP-derived expert demand for key island ESs and the spatial distribution of ES supply potential revealed mismatches between the supply and demand of erosion control, freshwater supply, and habitat provision. The framework developed in this study can help guide decisions and indicate where interventions should be focused to achieve sustainable island management.

Keywords: ecosystem service, sustainable management, forested islands, Analytic hierarchy process

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Authors: Alhaji M. H. Conteh, Xiangbin Yan, Issa Fofana, Brima Gegbe, Tamba I. Isaac

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Rice grain is Sierra Leone’s staple food and the nation imports over 120,000 metric tons annually due to a shortfall in its cultivation. Thus, the insufficient level of the crop's cultivation in Sierra Leone is caused by many problems and this led to the endlessly widening supply and demand for the crop within the country. Consequently, this has instigated the government to spend huge money on the importation of this grain that would have been otherwise cultivated domestically at a cheaper cost. Hence, this research attempts to explore the response of rice supply with respect to its demand in Sierra Leone within the period 1980-2010. The Nerlovian adjustment model to the Sierra Leone rice data set within the period 1980-2010 was used. The estimated trend equations revealed that time had significant effect on output, productivity (yield) and area (acreage) of rice grain within the period 1980-2010 and this occurred generally at the 1% level of significance. The results showed that, almost the entire growth in output had the tendency to increase in the area cultivated to the crop. The time trend variable that was included for government policy intervention showed an insignificant effect on all the variables considered in this research. Therefore, both the short-run and long-run price response was inelastic since all their values were less than one. From the findings above, immediate actions that will lead to productivity growth in rice cultivation are required. To achieve the above, the responsible agencies should provide extension service schemes to farmers as well as motivating them on the adoption of modern rice varieties and technology in their rice cultivation ventures.

Keywords: Nerlovian adjustment model, price elasticities, Sierra Leone, trend equations

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Authors: Montserrat Crespi-Vallbona; Oscar Mascarilla-Miró

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Mature destinations have different challenges trying to attract tourism and please its citizens. Hence, they have to maintain their touristic interest to standard demand and also not to undeceive those tourists with more advanced experiences. Second, they have to be concerned for the daily life of citizens and avoid the negative effects of touristification. This balance is quite delicate and often has to do with the sensitivity and commitment of the party in the local government. However, what is a general consensus is the need for destinations to differentiate from the homogeneous rest of regions and create new content, consumable resources or marketing events to guarantee their positioning. In this sense, the main responsibility of destinations is to satisfy users, tourists and citizens. Hence, its aim has to do with holistic experiences, which collect these wide approaches. Specifically, this research aims to analyze the volume and growth of tourist houses in the central touristic neighborhoods of Barcelona (this is Ciutat Vella) as the starting point to identify the behavior of tourists regarding their interests in searching for local heritage attractiveness and community atmosphere. Then, different cases are analyzed in order to show how Barcelona struggles to keep its attractive brand for the visitors, as well as for its inhabitants. Methodologically, secondary data used in this research comes from official registered tourist houses (Catalunya Government), Open Data (Barcelona municipality), the Airbnb tourist platform, from the Incasol Data and Municipal Register of Inhabitants. Primary data are collected through in-depth interviews with neighbors, social movement managers and political representatives from Turisme de Barcelona (local DMO, Destination Management Organization). Results show what the opportunities and priorities are for key actors to design policies to find a balance between all different interests.

Keywords: touristification, tourist houses, governance, tourism demand, airbnbfication

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Authors: Salah Hosseini, Hadi Ramezani, Bagher Shahbazi, Hossein Rabiei, Jafar Hooshmand, Hiwa Khaldi

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Diversity of energy portfolio and fluctuation of urban energy demand establish the need for more operational flexibility of combined Cooling, Heat, and Power Plants. Currently, the most common way to achieve these specifications is the use of heat storage devices or wet operation of gas turbines. The current work addresses using variable extraction steam turbine in conjugation with a gas turbine inlet cooling system as an alternative way for enhancement of a CCHP cycle operating range. A thermodynamic model is developed and typical apartments building in PARDIS Technology Park (located at Tehran Province) is chosen as a case study. Due to the variable Heat demand and using excess chiller capacity for turbine inlet cooling purpose, the mentioned steam turbine and TIAC system provided an opportunity for flexible operation of the cycle and boosted the independence of the power and heat generation in the CCHP plant. It was found that the ratio of power to the heat of CCHP cycle varies from 12.6 to 2.4 depending on the City heating and cooling demands and ambient condition, which means a good independence between power and heat generation. Furthermore, selection of the TIAC design temperature is done based on the amount of ratio of power gain to TIAC coil surface area, it was found that for current cycle arrangement the TIAC design temperature of 15 C is most economical. All analysis is done based on the real data, gathered from the local weather station of the PARDIS site.

Keywords: CCHP plant, GTG, HRSG, STG, TIAC, operational flexibility, power to heat ratio

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Authors: Shravani Itkelwar, Deepak Tewari, Bhaskar Natarajan

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The energy consumption data plays a vital role in energy efficiency policy design, implementation, and impact assessment. Any demand-side energy management intervention's success relies on the availability of accurate, comprehensive, granular, and up-to-date data on energy consumption. The Building sector, including residential and commercial, is one of the largest consumers of energy in India after the Industrial sector. With economic growth and increasing urbanization, the building sector is projected to grow at an unprecedented rate, resulting in a 5.6 times escalation in energy consumption till 2047 compared to 2017. Therefore, energy efficiency interventions will play a vital role in decoupling the floor area growth and associated energy demand, thereby increasing the need for robust data. In India, multiple institutions are involved in the collection and dissemination of data. This paper focuses on energy consumption data management in the building sector in India for both residential and commercial segments. It evaluates the robustness of data available through administrative and survey routes to estimate the key performance indicators and identify critical data gaps for making informed decisions. The paper explores several issues in the data, such as lack of comprehensiveness, non-availability of disaggregated data, the discrepancy in different data sources, inconsistent building categorization, and others. The identified data gaps are justified with appropriate examples. Moreover, the paper prioritizes required data in order of relevance to policymaking and groups it into "available," "easy to get," and "hard to get" categories. The paper concludes with recommendations to address the data gaps by leveraging digital initiatives, strengthening institutional capacity, institutionalizing exclusive building energy surveys, and standardization of building categorization, among others, to strengthen the management of building sector energy consumption data.

Keywords: energy data, energy policy, energy efficiency, buildings

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Authors: Jeaha Yang, Ahmed Khan, Donna L. Rodela, Mohammed A. Qaudeer

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Traditional supply chain silos still exist today due to the difficulty of establishing trust between various partners and technological barriers across industries. Companies lose opportunities and revenue and inadvertently make poor business decisions resulting in further challenges. Blockchain technology can bring a new level of transparency through sharing information with a distributed ledger in a decentralized manner that creates a basis of trust for business. Blockchain is a loosely coupled, hub-style communication network in which trading partners can work indirectly with each other for simpler integration, but they work together through the orchestration of their supply chain operations under a coherent process that is developed jointly. A Blockchain increases efficiencies, lowers costs, and improves interoperability to strengthen and automate the supply chain management process while all partners share the risk. Blockchain ledger is built to track inventory lifecycle for supply chain transparency and keeps a journal of inventory movement for real-time reconciliation. State design patterns are used to capture the life cycle (behavior) of inventory management as a state machine for a common, transparent and coherent process which creates an opportunity for trading partners to become more responsive in terms of changes or improvements in process, reconcile discrepancies, and comply with internal governance and external regulations. It enables end-to-end, inter-company visibility at the unit level for more accurate demand planning with better insight into order fulfillment and replenishment.

Keywords: supply chain management, inventory trace-ability, perpetual inventory system, inventory lifecycle, blockchain, inventory consignment, supply chain transparency, digital thread, demand planning, hyper ledger fabric

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Authors: Ruth Lorivi, Jianzheng Li, John J. Ambuchi, Kaiwen Deng

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Nitrogen removal from wastewater is accomplished by nitrification and denitrification processes. Successful denitrification requires carbon, therefore, if placed after biochemical oxygen demand (BOD) and nitrification process, a carbon source has to be re-introduced into the water. To avoid adding a carbon source, denitrification is usually placed before BOD and nitrification processes. This process however involves recycling the nitrified effluent. In this study wood chips were used as internal carbon source which enabled placement of denitrification after BOD and nitrification process without effluent recycling. To investigate the efficiency of a wood packed aerobic-anaerobic baffled reactor on carbon and nutrients removal from domestic wastewater, a three compartment baffled reactor was presented. Each of the three compartments was packed with 329 g wood chips 1x1cm acting as an internal carbon source for denitrification. The proposed mode of operation was aerobic-anoxic-anaerobic (OAA) with no effluent recycling. The operating temperature, hydraulic retention time (HRT), dissolved oxygen (DO) and pH were 24 ± 2 ℃, 24 h, less than 4 mg/L and 7 ± 1 respectively. The removal efficiencies of chemical oxygen demand (COD), ammonia nitrogen (NH₄⁺-N) and total nitrogen (TN) attained was 99, 87 and 83% respectively. TN removal rate was limited by nitrification as 97% of ammonia converted into nitrate and nitrite was denitrified. These results show that application of wood chips in wastewater treatment processes is an efficient internal carbon source. 

Keywords: aerobic-anaerobic baffled reactor, denitrification, nitrification, wood chip

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Authors: Pranab Kumar Das

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Vulnerability assessment of buildings with irregularity in the vertical direction has been carried out in this study. The constructions of vertically irregular buildings are increasing in the context of fast urbanization in the developing countries including India. During two reconnaissance based survey performed after Nepal earthquake 2015 and Imphal (India) earthquake 2016, it has been observed that so many structures are damaged due to the vertically irregular configuration. These irregular buildings are necessary to perform safely during seismic excitation. Therefore, it is very urgent demand to point out the actual vulnerability of the irregular structure. So that remedial measures can be taken for protecting those structures during natural hazard as like earthquake. This assessment will be very helpful for India and as well as for the other developing countries. A sufficient number of research has been contributed to the vulnerability of plan asymmetric buildings. In the field of vertically irregular buildings, the effort has not been forwarded much to find out their vulnerability during an earthquake. Irregularity in vertical direction may be caused due to irregular distribution of mass, stiffness and geometrically irregular configuration. Detailed analysis of such structures, particularly non-linear/ push over analysis for performance based design seems to be challenging one. The present paper considered a number of models of irregular structures. Building models made of both reinforced concrete and brick masonry are considered for the sake of generality. The analyses are performed with both help of finite element method and computational method.The study, as a whole, may help to arrive at a reasonably good estimate, insight for fundamental and other natural periods of such vertically irregular structures. The ductility demand, storey drift, and seismic response study help to identify the location of critical stress concentration. Summarily, this paper is a humble step for understanding the vulnerability and framing up the guidelines for vertically irregular structures.

Keywords: ductility, stress concentration, vertically irregular structure, vulnerability

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Authors: Elham Fathi, Seyed Mohammad Kalantarkousheh, Abolfazl Hatami Varzane

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The present study aimed to determine predict capacity of the relationship among attachment styles, humor styles and communication patterns in female married students. Statistical population consisted of female married students from Allameh Tabataba’i University. The research sample consisted of 104 married students selected through convenience sampling. They responded to study instruments that consisted of attachment styles, humor styles and Communication patterns questionnaires. Data was analyzed by means of correlation method. The results indicated significant positive relationship between secure attachment styles with adaptive humor styles, and anxious attachment styles with maladaptive humor styles. Also a negative relationship between avoidant attachment with affiliative humor, and anxious attachment with self-enhancing humor was found. Furthermore, a negative relationship between self- enhancing humor styles with demand – withdraw communication pattern, and between affiliative humor with mutual avoidant communication pattern and a positive relationship between affiliative humor with mutual constructive communication pattern was observed. The relationship between secure attachment with mutual constructive communication pattern was positive, while relationship between avoidant attachment to mutual constructive communication pattern was negative and significant and its relation with mutual avoidant communication pattern was significantly positive. The result of regression analysis indicated that affliative humor style and secure attachment style, positively predicted mutual constructive communication pattern. Avoidant attachment style positively and affliative humor style negatively predicted the mutual avoidant communication pattern. And self-enhancing humor style negatively predicted the demand – withdraw communication pattern style.

Keywords: attachment styles, communication patterns, humor styles, female married students

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Authors: Dewan Hasin Mahtab, Farzana Sadia

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At present, wastewater treatment has become essential to maintain a constant supply of safe water as well as to protect the environment. Due to overpopulation and overconsumption, the water quality from various surface water sources is degrading every day. Being one of the megacities in the world, Dhaka City, is going through rapid industrialization and urbanization. The effluents from these industries and factories are mostly discharged directly into the rivers without any treatment. As such, the quality of water of Buriganga is being afflicted with a noisome problem of pollution. The water of the Buriganga River has become detrimental to humans, animals, and the environment. It has become crucial to conserve the environment so that we can save both ourselves and the environment. The first step towards it should be analyzing the wastewater to decide the further steps of the treatment process. Increased population and increased consumption both contribute to water pollution. Mohammadpur is a developing area of Dhaka City, and Kamrangirchar is one of the largest slum areas in Dhaka City. The total study area is 6.13 sq. Km of Dhaka city with a population of 4,73,310 people. Of them, 86.47% had their own latrine, 47% were directly connected to the drain, 55% had septic tanks, and 70.09% of them cleaned their septic tank once a year. The pH, Dissolved Oxygen, Chemical Oxygen Demand, Biochemical Oxygen Demand, Total Dissolved Solid, Total Suspended and total coliforms of wastewater from two samples of both Mohammadpur and Kamrangirchar was analyzed. The DO level from the water bodies of Kamrangirchar was found very low, making the water bodies inhabitable for aquatic plants and animals. The BOD and COD level was extremely high from samples collected from Mohammadpur. The total coliforms count was found too high during the wet season, making it a potential health concern in the wet season in these two areas.

Keywords: Dhaka, environmental conservation rule, sanitation, wastewater

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Authors: Vishnu Nagendra, Marten Van Der Veen, Stefania Giodini

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Effective humanitarian logistics operations are a cornerstone in the success of disaster relief operations. However, for effectiveness, they need to be demand driven and supported by adequate data for prioritization. Without this data operations are carried out in an ad hoc manner and eventually become chaotic. The current availability of geospatial data helps in creating models for predictive damage and vulnerability assessment, which can be of great advantage to logisticians to gain an understanding on the nature and extent of the disaster damage. This translates into actionable information on the demand for relief goods, the state of the transport infrastructure and subsequently the priority areas for relief delivery. However, due to the unpredictable nature of disasters, the accuracy in the models need improvement which can be done using remote sensing data from UAVs (Unmanned Aerial Vehicles) or satellite imagery, which again come with certain limitations. This research addresses the need for a framework to combine data from different sources to support humanitarian logistic operations and prediction models. The focus is on developing a workflow to combine data from satellites and UAVs post a disaster strike. A three-step approach is followed: first, the data requirements for logistics activities are made explicit, which is done by carrying out semi-structured interviews with on field logistics workers. Second, the limitations in current data collection tools are analyzed to develop workaround solutions by following a systems design approach. Third, the data requirements and the developed workaround solutions are fit together towards a coherent workflow. The outcome of this research will provide a new method for logisticians to have immediately accurate and reliable data to support data-driven decision making.

Keywords: unmanned aerial vehicles, damage prediction models, remote sensing, data driven decision making

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Authors: Suhas Kadam, Vishal Chandanshive, Niraj Rane, Sanjay Govindwar

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Fimbristylis dichotoma, Ammannia baccifera, and their co-plantation consortium FA were found to degrade methyl orange, simulated dye mixture, and real textile effluent. Wild plants of Fimbristylis dichotoma and Ammannia baccifera with equal biomass showed 91 and 89% decolorization of methyl orange within 60 h at a concentration of 50 ppm, while 95% dye removal was achieved by consortium FA within 48 h. Floating phyto-beds with co-plantation (Fimbristylis dichotoma and Ammannia baccifera) for the treatment of real textile effluent in a constructed wetland was observed to be more efficient and achieved 79, 72, 77, 66 and 56% reductions in ADMI color value, chemical oxygen demand, biological oxygen demand, total dissolve solid and total suspended solid of textile effluent, respectively. High performance thin layer chromatography, gas chromatography-mass spectroscopy, Fourier transform infrared spectroscopy, Ultra violet-Visible spectroscopy and enzymatic assays confirmed the phytotransformation of parent dye in the new metabolites. T-RFLP analysis of rhizospheric bacteria of Fimbristylis dichotoma, Ammannia baccifera, and consortium FA revealed the presence of 88, 98 and 223 genera which could have been involved in dye removal. Toxicity evaluation of products formed after phytotransformation of methyl orange by consortium FA on bivalves Lamellidens marginalis revealed less damage in the gills architecture when analyzed histologically. Toxicity measurement by Random Amplification of Polymorphic DNA (RAPD) technique revealed normal banding pattern in treated methyl orange sample suggesting less toxic nature of phytotransformed dye products.

Keywords: constructed wetland, phyto-bed, textile effluent, phytoremediation

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Authors: Purnima Dhall, Rita Kumar

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Introduction: River Yamuna, in the national capital territory (NCT), and also the primary source of drinking water for the city. Delhi discharges about 3,684 MLD of sewage through its 18 drains in to the Yamuna. Water quality monitoring is an important aspect of water management concerning to the pollution control. Public concern and legislation are now a day’s demanding better environmental control. Conventional method for estimating BOD5 has various drawbacks as they are expensive, time-consuming, and require the use of highly trained personnel. Stringent forthcoming regulations on the wastewater have necessitated the urge to develop analytical system, which contribute to greater process efficiency. Biosensors offer the possibility of real time analysis. Methodology: In the present study, a novel rapid method for the determination of biochemical oxygen demand (BOD) has been developed. Using the developed method, the BOD of a sample can be determined within 2 hours as compared to 3-5 days with the standard BOD3-5day assay. Moreover, the test is based on specified consortia instead of undefined seeding material therefore it minimizes the variability among the results. The device is coupled to software which automatically calculates the dilution required, so, the prior dilution of the sample is not required before BOD estimation. The developed BOD-Biosensor makes use of immobilized microorganisms to sense the biochemical oxygen demand of industrial wastewaters having low–moderate–high biodegradability. The method is quick, robust, online and less time consuming. Findings: The results of extensive testing of the developed biosensor on drains demonstrate that the BOD values obtained by the device correlated with conventional BOD values the observed R2 value was 0.995. The reproducibility of the measurements with the BOD biosensor was within a percentage deviation of ±10%. Advantages of developed BOD biosensor • Determines the water pollution quickly in 2 hours of time; • Determines the water pollution of all types of waste water; • Has prolonged shelf life of more than 400 days; • Enhanced repeatability and reproducibility values; • Elimination of COD estimation. Distinctiveness of Technology: • Bio-component: can determine BOD load of all types of waste water; • Immobilization: increased shelf life > 400 days, extended stability and viability; • Software: Reduces manual errors, reduction in estimation time. Conclusion: BiosensorBOD can be used to measure the BOD value of the real wastewater samples. The BOD biosensor showed good reproducibility in the results. This technology is useful in deciding treatment strategies well ahead and so facilitating discharge of properly treated water to common water bodies. The developed technology has been transferred to M/s Forbes Marshall Pvt Ltd, Pune.

Keywords: biosensor, biochemical oxygen demand, immobilized, monitoring, Yamuna

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Authors: Erich Ryan, Benjamin McDaniel, Dragoljub Kosanovic

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Combined heat and power (CHP) plants are an efficient technology for meeting the heating and electric needs of large campus energy systems, but have come under greater scrutiny as the world pushes for emissions reductions and lower consumption of fossil fuels. The electrification of heating and cooling systems offers a great deal of potential for carbon savings, but these systems can be costly endeavors due to increased electric consumption and peak demand. Thermal energy storage (TES) has been shown to be an effective means of improving the viability of electrified systems, by shifting heating and cooling load to off-peak hours and reducing peak demand charges. In this study, we analyze the integration of an electrified heating and cooling system with thermal energy storage into a campus CHP plant, to investigate the potential of leveraging existing infrastructure and technologies with the climate goals of the 21st century. A TRNSYS model was built to simulate a ground source heat pump (GSHP) system with TES using measured campus heating and cooling loads. The GSHP with TES system is modeled to follow the parameters of industry standards and sized to provide an optimal balance of capital and operating costs. Using known CHP production information, costs and emissions were investigated for a unique large energy user rate structure that operates a CHP plant. The results highlight the cost and emissions benefits of a targeted integration of heat pump technology within the framework of existing CHP systems, along with the performance impacts and value of TES capability within the combined system.

Keywords: thermal energy storage, combined heat and power, heat pumps, electrification

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Authors: Ana L. Martins, Luis Orfão

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Healthcare systems have been subject to various research efforts aiming at process improvement under a lean approach. Another perspective, agility, has also been used, though in a lower scale, in order to analyse the ability of different hospital services to adapt to demand uncertainties. Both perspectives have a common denominator, the improvement of effectiveness and efficiency of the services in a healthcare setting context. Mixing the two approached allows, on one hand, to streamline the processes, and on the other hand the required flexibility to deal with demand uncertainty in terms of both volume and variety. The present research aims to analyse the impacts of the combination of both perspectives in the effectiveness and efficiency of an hospital service. The adopted methodology is based on a case study approach applied to the process of the ambulatory surgery service of Hospital de Lamego. Data was collected from direct observations, formal interviews and informal conversations. The analyzed process was selected according to three criteria: relevance of the process to the hospital, presence of human resources, and presence of waste. The customer of the process was identified as well as his perception of value. The process was mapped using flow chart, on a process modeling perspective, as well as through the use of Value Stream Mapping (VSM) and Process Activity Mapping. The Spaghetti Diagram was also used to assess flow intensity. The use of the lean tools enabled the identification of three main types of waste: movement, resource inefficiencies and process inefficiencies. From the use of the lean tools improvement suggestions were produced. The results point out that leagility cannot be applied to the process, but the application of lean and agility in specific areas of the process would bring benefits in both efficiency and effectiveness, and contribute to value creation if improvements are introduced in hospital’s human resources and facilities management.

Keywords: case study, healthcare systems, leagility, lean management

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Authors: Neda Nabid

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Friction-based supplemental devices have been extensively used for seismic protection and strengthening of structures, however, the conventional use of these dampers may not necessarily lead to an efficient structural performance. Conventionally designed friction dampers follow a uniform height-wise distribution pattern of slip load values for more practical simplicity. This can lead to localizing structural damage in certain story levels, while the other stories accommodate a negligible amount of relative displacement demand. A practical performance-based optimization methodology is developed to tackle with structural damage localization of RC frame buildings with friction energy dissipation devices under severe earthquakes. The proposed methodology is based on the concept of uniform damage distribution theory. According to this theory, the slip load values of the friction dampers redistribute and shift from stories with lower relative displacement demand to the stories with higher inter-story drifts to narrow down the discrepancy between the structural damage levels in different stories. In this study, the efficacy of the proposed design methodology is evaluated through the seismic performance of five different low to high-rise RC frames equipped with friction wall dampers under six real spectrum-compatible design earthquakes. The results indicate that compared to the conventional design, using the suggested methodology to design friction wall systems can lead to, by average, up to 40% reduction of maximum inter-story drift; and incredibly more uniform height-wise distribution of relative displacement demands under the design earthquakes.

Keywords: friction damper, nonlinear dynamic analysis, RC structures, seismic performance, structural damage

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Authors: Salma Maher, Ahmed Elseragy, Sally Eldeeb

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Nowadays, Urbanism and climate change lead to the rapid growth in energy consumption and the increase of using air-conditioning for cooling. In a hot climate area, there is a need for a new sustainable alternative that is more convenient for an existing situation. The Building envelope controls the heat transfer between the outside and inside the building. While the building façade is the most critical part, types of façade material play a vital role in influences of the energy demand for heating and cooling due to exposure to direct solar radiation throughout the day. Since the beginning of the twentieth century, the use of curtain walls in office buildings façades started to increase rapidly, which lead to more cooling loads in energy consumption. Integrating the living wall system in urban areas as a sustainable renovation and energy-saving method for the built environment will reduce the energy demand of buildings and will also provide environmental benefits. Also, it will balance the urban ecology and enhance urban life quality. The results show that the living wall systems reduce the internal temperature up to 4.0 °C. This research carries on an analytical study by highlighting the different types of living wall systems and verifying their thermal performance, energy-saving, and life potential on the building. These assessing criteria include the reason for using the Living wall systems in the building façade as well as the effect it has upon the surrounding environment. Finally, the paper ends with concluding the effect of using living wall systems on building. And, it suggests a system as long-lasting, and energy-efficient solution to be applied in curtain wall façades in a hot climate area.

Keywords: living wall systems, energy consumption, curtain walls, energy-saving, sustainability, urban life quality

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Anza-Vhudziki Mboyi, Ilunga Kamika, Maggy Momba

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The aim of this study was to ascertain the survival limit and capability of commonly found wastewater protozoan (Aspidisca sp, Trachelophyllum sp, and Peranema sp) and bacterial (Bacillus licheniformis, Brevibacillus laterosporus, and Pseudomonas putida) species to remove COD while exposed to commercial nanomaterials under varying pH conditions. The experimental study was carried out in modified mixed liquor media adjusted to various pH levels (pH 2, 7 and 10), and a comparative study was performed to determine the difference between the cytotoxicity effects of commercial zinc oxide (nZnO) and silver (nAg) nanomaterials (NMs) on the target wastewater microbial communities using standard methods. The selected microbial communities were exposed to lethal concentrations ranging from 0.015 g/L to 40 g/L for nZnO and from 0.015 g/L to 2 g/L for nAg for a period of 5 days of incubation at 30°C (100 r/min). Compared with the absence of NMs in wastewater mixed liquor, the relevant environmental concentration ranging between 10 µg/L and 100 µg/L, for both nZnO and nAg caused no adverse effects, but the presence of 20 g of nZnO/L and 0.65 g of nAg/L significantly inhibited microbial growth. Statistical evidence showed that nAg was significantly more toxic compared to nZnO, but there was an insignificant difference in toxicity between microbial communities and pH variations. A significant decrease in the removal of COD by microbial populations was observed in the presence of NMs with a moderate correlation of r = 0.3 to r = 0.7 at all pH levels. It was evident that there was a physical interaction between commercial NMs and target wastewater microbial communities; although not quantitatively assessed, cell morphology and cell death were observed. Such phenomena suggest the high resilience of the microbial community, but it is the accumulation of NMs that will have adverse effects on the performance in terms of COD removal.

Keywords: bacteria, biological treatment, chemical oxygen demand (COD) and nanomaterials, consortium, pH, protozoan

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Authors: Farhood Rismanchian, Seong Hyeon Park, Young Hoon Lee

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This paper proposes a method to optimize the layout of an emergency department (ED) based on real executions of care processes by considering several planning objectives simultaneously. Recently, demand for healthcare services has been dramatically increased. As the demand for healthcare services increases, so do the need for new healthcare buildings as well as the need for redesign and renovating existing ones. The importance of implementation of a standard set of engineering facilities planning and design techniques has been already proved in both manufacturing and service industry with many significant functional efficiencies. However, high complexity of care processes remains a major challenge to apply these methods in healthcare environments. Process mining techniques applied in this study to tackle the problem of complexity and to enhance care process analysis. Process related information such as clinical pathways extracted from the information system of an ED. A 0-1 goal programming approach is then proposed to find a single layout that simultaneously satisfies several goals. The proposed model solved by optimization software CPLEX 12. The solution reached using the proposed method has 42.2% improvement in terms of walking distance of normal patients and 47.6% improvement in walking distance of critical patients at minimum cost of relocation. It has been observed that lots of patients must unnecessarily walk long distances during their visit to the emergency department because of an inefficient design. A carefully designed layout can significantly decrease patient walking distance and related complications.

Keywords: healthcare operation management, goal programming, facility layout problem, process mining, clinical processes

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Authors: Iman Janghorban Esfahani

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Due to the increased use of irrigation in agriculture, the importance and need for highly reliable water pumping systems have significantly increased. The pumping of the groundwater is essential to provide water for both drip and furrow irrigation to increase the agricultural yield, especially in arid regions that suffer from scarcities of surface water. The most common irrigation pumping systems (IPS) consume conventional energies through the use of electric motors and generators or connecting to the electricity grid. Due to the shortage and transportation difficulties of fossil fuels, and unreliable access to the electricity grid, especially in the rural areas, and the adverse environmental impacts of fossil fuel usage, such as greenhouse gas (GHG) emissions, the need for renewable energy sources such as photovoltaic systems (PVS) as an alternative way of powering irrigation pumping systems is urgent. Integration of the photovoltaic systems with irrigation pumping systems as the Photovoltaic Powered-Irrigation Pumping System (PVP-IPS) can avoid fossil fuel dependency and the subsequent greenhouse gas emissions, as well as ultimately lower energy costs and improve efficiency, which made PVP-IPS systems as an environmentally and economically efficient solution for agriculture irrigation in every region. The greatest problem faced by integration of PVP with IPS systems is matching the intermittence of the energy supply with the dynamic water demand. The best solution to overcome the intermittence is to incorporate a storage system into the PVP-IPS to provide water-on-demand as a highly reliable stand-alone irrigation pumping system. The water storage tank (WST) is the most common storage device for PVP-IPS systems. In the integrated PVP-IPS with a water storage tank (PVP-IPS-WST), a water storage tank stores the water pumped by the IPS in excess of the water demand and then delivers it when demands are high. The Freshwater pinch analysis (FWaPA) as an alternative to mathematical modeling was used by other researchers for retrofitting the off-grid battery less photovoltaic-powered reverse osmosis system. However, the Freshwater pinch analysis has not been used to integrate the photovoltaic systems with irrigation pumping system with water storage tanks. In this study, FWaPA graphical and numerical tools were used for retrofitting an existing PVP-IPS system located in Salahadin, Republic of Iraq. The plant includes a 5 kW submersible water pump and 7.5 kW solar PV system. The Freshwater Composite Curve as the graphical tool and Freashwater Storage Cascade Table as the numerical tool were constructed to determine the minimum required outsourced water during operation, optimal amount of delivered electricity to the water pump, and optimal size of the water storage tank for one-year operation data. The results of implementing the FWaPA on the case study show that the PVP-IPS system with a WST as the reliable system can reduce outsourced water by 95.41% compare to the PVP-IPS system without storage tank.

Keywords: irrigation, photovoltaic, pinch analysis, pumping, solar energy

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Authors: David P. Horton, Gary Lynch-Wood

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Western populations are aging, prone to various lifestyle health problems, and increasing their demand for health and social care services. This demand has created enormous fiscal and regulatory challenges. In response, government institutions have deployed strategies of behavior modification to encourage people to exercise greater personal responsibility over their health and care needs (i.e., welfare responsibilisation). Policy strategies are underpinned by the assumption that people if properly supported, will make better health and lifestyle selections. Not only does this absolve governments of the responsibility for meeting all health and care needs, but it also enables government institutions to assert fiscal control over welfare spending. Looking at the regulation of health and social care in the UK, the authors identify and outline a suite of regulatory tools that are designed to extract and manage the resources of health and social care services users and to encourage them to make (‘better’) use of these resources. This is important for our understanding of how health and social care regulation is responding to ongoing social and economic challenges. It is also important because there has been a failure to systematically examine the relevance of resources for regulation, which is surprising given that resources are crucial to how and whether regulation succeeds or fails. In particular, drawing from the regulatory welfare state concept, the authors analyse the key legal and regulatory changes and mechanisms that have been introduced since the 2008 financial crisis, focusing on critical measures such as the Health and Social Care Act and regulations introduced under the National Health Service Act. The authors show how three types of user resources (i.e., tangible, labor, and data) are being used to assert fiscal control and increase welfare responsibilisation. Amongst other things, the paper concludes that service users have become more than rule followers and targets of behavioral modification; rather, they are producers of resources that regulatory systems have come to rely on.

Keywords: health care, regulation, resources, social care

Procedia PDF Downloads 73

Authors: Abdullah Al-Mamun, Md. Nuruzzaman, Md. Noor Salleh, Muhammad Abu Eusuf, Ahmad Jalal Khan Chowdhury, Mohd. Zaki M. Amin, Norlida Mohd. Dom

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Identification of pollution sources and determination of pollution loads from all areas are very important for sustainable rehabilitation of any contaminated river. Pusu is a small river which, flows through the main campus of International Islamic University Malaysia (IIUM) at Gombak. Poor aesthetics of the river, which is flowing through the entrance of the campus, gives negative impression to the local and international visitors. As such, this study is being conducted to find ways to rehabilitate the river in a sustainable manner. The point and non-point pollution sources of the river basin are identified. Upper part of the 12.6 km2 river basin is covered with secondary forest. However, it is the lower-middle reaches of the river basin which is being cleared for residential development and source of high sediment load. Flow and concentrations of the common pollutants, important for a healthy river, such as Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Suspended Solids (SS), Turbidity, pH, Ammoniacal Nitrogen (AN), Total Nitrogen (TN) and Total Phosphorus (TP) are determined. Annual pollution loading to the river was calculated based on the primary and secondary data. Concentrations of SS were high during the rainy day due to contribution from the non-point sources. There are 7 ponds along the river system within the campus, which are severely affected by high sediment load from the land clearing activities. On the other hand, concentrations of other pollutants were high during the non-rainy days. The main sources of point pollution are the hostels, cafeterias, sewage treatment plants located in the campus. Therefore, both pollution sources need to be controlled in order to rehabilitate the river in a sustainable manner.

Keywords: river pollution, rehabilitation, point pollution source, non-point pollution sources, pollution loading

Procedia PDF Downloads 335

Authors: Michele Catalano, Jacopo Di Domenico, Luca Riccetti, Andrea Teglio

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We develop a data-driven agent based model (ABM) for the Italian economy. We calibrate the model for the initial condition and parameters. As a preliminary step, we replicate the Monte-Carlo simulation for the Austrian economy. Then, we evaluate the dynamic properties of the model: the long-run equilibrium and the allocative efficiency in terms of disequilibrium patterns arising in the search and matching process for final goods, capital, intermediate goods, and credit markets. In this perspective, we use a randomized initial condition approach. We perform a robustness analysis perturbing the system for different parameter setups. We explore the empirical properties of the model using a rolling window forecast exercise from 2010 to 2022 to observe the model’s forecasting ability in the wake of the COVID-19 pandemic. We perform an analysis of the properties of the model with a different number of agents, that is, with different scales of the model compared to the real economy. The model generally displays transient dynamics that properly fit macroeconomic data regarding forecasting ability. We stress the model with a large set of shocks, namely interest policy, fiscal policy, and exogenous factors, such as external foreign demand for export. In this way, we can explore the most exposed sectors of the economy. Finally, we modify the technology mix of the various sectors and, consequently, the underlying input-output sectoral interdependence to stress the economy and observe the long-run projections. In this way, we can include in the model the generation of endogenous crisis due to the implied structural change, technological unemployment, and potential lack of aggregate demand creating the condition for cyclical endogenous crises reproduced in this artificial economy.

Keywords: agent-based models, behavioral macro, macroeconomic forecasting, micro data

Procedia PDF Downloads 48

Authors: Aicha Assal, El Mostapha Lotfi

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Rapid industrialization and population growth are currently the main causes of energy and environmental problems associated with wastewater treatment. Wastewater treatment plants (WWTPs) aim to treat wastewater before discharging it into the environment, but they are not yet capable of treating non-biodegradable contaminants such as heavy metals. Toxic heavy metals can disrupt biological processes in WWTPs. Consequently, it is crucial to combine additional physico-chemical treatments with WWTPs to ensure effective wastewater treatment. In this study, the authors examined the pretreatment process for urban wastewater generated by the El Jadida WWTP in order to assess its treatment efficiency. Various physicochemical and spatiotemporal parameters of the WWTP's raw and treated water were studied, including temperature, pH, conductivity, biochemical oxygen demand (BOD5), chemical oxygen demand (COD), suspended solids (SS), total nitrogen, and total phosphorus. The results showed an improvement in treatment yields, with measured performance values of 77% for BOD5, 63% for COD, and 66% for TSS. However, spectroscopic analyses revealed persistent coloration in wastewater samples leaving the WWTP, as well as the presence of heavy metals such as Zn, cadmium, chromium, and cobalt, detected by inductively coupled plasma optical emission spectroscopy (ICP-OES). To remedy these staining problems and reduce the presence of heavy metals, a new low-cost, environmentally-friendly eggshell-based solution was proposed. This method eliminated most heavy metals such as cobalt, beryllium, silver, and copper and significantly reduced the amount of cadmium, lead, chromium, manganese, aluminium, and Zn. In addition, the bioadsorbent was able to decolorize wastewater by up to 84%. This adsorption process is, therefore, of great interest for ensuring the quality of wastewater and promoting its reuse in irrigation.

Keywords: WWTP, wastewater, heavy metals, decoloration, depollution, COD, BOD5

Procedia PDF Downloads 48

Authors: N. Ali, S. Nakayama, H. Yamaguchi, M. Nadeem

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Traffic congestion is a matter of prime concern in developing countries. This can be primarily attributed due to poor design practices and biased allocation of resources based on political will neglecting the technical feasibilities in infrastructure design. During the last decade, Lahore has expanded at an unprecedented rate as compared to surrounding cities due to more funding and resource allocation by the previous governments. As a result of this, people from surrounding cities and areas moved to the Lahore city for better opportunities and quality of life. This migration inflow inherited the city with an increased population yielding the inefficiency of the existing infrastructure to accommodate enhanced traffic demand. This leads to traffic congestion on major arterial roads of the city. In this simulation study, a major arterial road was selected to evaluate the performance of the five intersections by changing the geometry of the intersections or signal control type. Simulations were done in two software; Highway Capacity Software (HCS) and Synchro Studio and Sim Traffic Software. Some of the traffic management strategies that were employed include actuated-signal control, semi-actuated signal control, fixed-time signal control, and roundabout. The most feasible solution for each intersection in the above-mentioned traffic management techniques was selected with the least delay time (seconds) and improved Level of Service (LOS). The results showed that Jinnah Hospital Intersection and Akbar Chowk Intersection improved 92.97% and 92.67% in delay time reduction, respectively. These results can be used by traffic planners and policy makers for decision making for the expansion of these intersections keeping in mind the traffic demand in future years.

Keywords: traffic congestion, traffic simulation, traffic management, congestion problems

Procedia PDF Downloads 452

Authors: Rene Jimenez, Sonia E. Ruiz, Miguel A. Orellana

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On 09/19/2017, a Mw = 7.1 intraslab earthquake occurred in Mexico causing the collapse of about 40 buildings. Many of these were 5- or 6-story buildings with soft first story; so, it is desirable to perform a structural fragility analysis of typical structures representative of those buildings and to propose a reliable structural solution. Here, a typical 5-story building constituted by regular R/C moment-resisting frames in the first story and confined masonry walls in the upper levels, similar to the collapsed structures on the 09/19/2017 Mexico earthquake, is analyzed. Three different structural solutions of the 5-story building are considered: S1) it is designed in accordance with the Mexico City Building Code-2004; S2) then, the column dimensions of the first story corresponding to S1 are reduced, and S3) viscous dampers are added at the first story of solution S2. A number of dynamic incremental analyses are performed for each structural solution, using a 3D structural model. The hysteretic behavior model of the masonry was calibrated with experiments performed at the Laboratory of Structures at UNAM. Ten seismic ground motions are used to excite the structures; they correspond to ground motions recorded in intermediate soil of Mexico City with a dominant period around 1s, where the structures are located. The fragility curves of the buildings are obtained for different values of the maximum inter-story drift demands. Results show that solutions S1 and S3 give place to similar probabilities of exceedance of a given value of inter-story drift for the same seismic intensity, and that solution S2 presents a higher probability of exceedance for the same seismic intensity and inter-story drift demand. Therefore, it is concluded that solution S3 (which corresponds to the building with soft first story and energy dissipation devices) can be a reliable solution from the structural point of view.

Keywords: demand hazard analysis, fragility curves, incremental dynamic analyzes, soft-first story, structural capacity

Procedia PDF Downloads 159

Authors: Abdulla Rahil, Rupert Gammon, Neil Brown

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The rapid growth of renewable energy sources and their integration into the grid have been motivated by the depletion of fossil fuels and environmental issues. Unfortunately, the grid is unable to cope with the predicted growth of renewable energy which would lead to its instability. To solve this problem, energy storage devices could be used. Electrolytic hydrogen production from an electrolyser is considered a promising option since it is a clean energy source (zero emissions). Choosing flexible operation of an electrolyser (producing hydrogen during the off-peak electricity period and stopping at other times) could bring about many benefits like reducing the cost of hydrogen and helping to balance the electric systems. This paper investigates the price of hydrogen during flexible operation compared with continuous operation, while serving the customer (hydrogen filling station) without interruption. The optimization algorithm is applied to investigate the hydrogen station in both cases (flexible and continuous operation). Three different scenarios are tested to see whether the off-peak electricity price could enhance the reduction of the hydrogen cost. These scenarios are: Standard tariff (1 tier system) during the day (assumed 12 p/kWh) while still satisfying the demand for hydrogen; using off-peak electricity at a lower price (assumed 5 p/kWh) and shutting down the electrolyser at other times; using lower price electricity at off-peak times and high price electricity at other times. This study looks at Derna city, which is located on the coast of the Mediterranean Sea (32° 46′ 0 N, 22° 38′ 0 E) with a high potential for wind resource. Hourly wind speed data which were collected over 24½ years from 1990 to 2014 were in addition to data on hourly radiation and hourly electricity demand collected over a one-year period, together with the petrol station data.

Keywords: hydrogen filling station off-peak electricity, renewable energy, off-peak electricity, electrolytic hydrogen

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Authors: Fikre Belay Tekulu

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This thesis presents the socio-economic and environmental impacts of urban sprawl in the case of Adigrat city, Tigray Region, Ethiopia. The main objective of this research is to assess major causes, trends and socio-economic and environmental impacts of the urban sprawl of Adigrat city. The study employed both quantitative and qualitative methods as questionnaires, interviews and observation used for data collection. Simple random sampling has been used to select the participants. The land use and land cover change for agricultural land and forest and grassland resource analysis is done with the aid of GIS. Urban sprawl is mainly caused by the rapid population growth, increase in the living and property cost in the core of the city, land demand and land speculation and the growth of transport and an increase in income of people and demand of more living space. The study indicates 15726.24 hectares (515.49 per cent) of new land added to the city jurisdiction from its adjacent Gantafeshum Wereda between 1986 and 2018. The population of Adigrat city increased by 9.045 per cent per year, while the city expanded 16.01 per cent per annum and the LCR was 0.0233 hectares per person between 1986 and 2018.Built-up area increased by 35.27 per cent per annum, while agricultural land, forests and grassland cover decreased by 1.68 per cent and 1.26 per cent per annum respectively in the last thirty three years. This rapid growth of urban sprawl brought social-economic and environmental change in the city that has been observed by the city residents. Therefore, the city administration should need strong, integrated, effective and efficient work, with its neighbor rural area and also done timely preparation, implementation, supervision, and evaluation of the structural plan of the city to bring out sustainable development of the city.

Keywords: cause, , trends, urban sprawl, land use land cover, GIS

Procedia PDF Downloads 113

Authors: Fei Chen, Wei Lu, Jun Cai

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During the Twelve Five period, China promulgated industrial policies promoting the relocation of energy-intensive industries to coastal areas in order to utilize marine shipping resources. Consequently, some major state-owned steel and gas enterprises have relocated and resulted in a large-scale coastal area development. However, some land may have been over-exploited with seamless coastline projects. To balance between employment and housing, new industrial coastal towns were constructed to support the industrial-led development. In this paper, we adopt a case-study approach to closely examine the development of several new industrial coastal towns of Liaoning Province situated in the Bohai Bay area, which is currently under rapid economic growth. Our investigations reflect the common phenomenon of long distance commuting and a massive amount of vacant residences. More specifically, large plant relocation caused hundreds of kilometers of daily commute and enterprises had to provide housing subsidies and education incentives to motivate employees to relocate to coastal areas. Nonetheless, many employees still refuse to relocate due to job stability, diverse needs of family members and access to convenient services. These employees averaged 4 hours of commute daily and some who lived further had to reside in temporary industrial housing units and subject to long-term family separation. As a result, only a small portion of employees purchase new coastal residences but mostly for investment and retirement purposes, leading to massive vacancy and ghost-town phenomenon. In contrast to the low demand, coastal areas tend to develop large amount of residences prior to industrial relocation, which may be directly related to local government finances. Some local governments have sold residential land to developers to general revenue to support the subsequent industrial development. Subject to the strong preference of ocean-view, residential housing developers tend to select coast-line land to construct new residential towns, which further reduces the access of marine resources for major industrial enterprises. This violates the original intent of developing industrial coastal towns and drastically limits the availability of marine resources. Lastly, we analyze the co-existence of over-exploiting residential areas and massive vacancies in reference to the demand and supply of land, as well as the demand of residential housing units with the choice criteria of enterprise employees.

Keywords: coastal industry town, commuter traffic, employment-housing space, outer suburb industrial area

Procedia PDF Downloads 200