Case Study In Istanbul Research Articles

Multi-period planning of hydrogen refuelling stations using flow data: A case study for Istanbul

Decreasing energy resources is among the future concerns of almost all sectors, including transportation. Hydrogen is one of the major alternatives. Although the promotion of hydrogen fuel cell vehicles (HFCVs) is supported by the governments and automobile companies, hydrogen refuelling stations (HRSs) should be accessible in order for HFCV to become widespread. Therefore the location and the number of HRS play an essential role for the spread of the HFCVs. In this study, we aim to find the number and the location of HRSs to be operated in Istanbul by using a multi-period p-median model. The adaptation to hydrogen technology for each district of the city is modelled using human development index, a measure for life quality which is then used to determine the HFCVs’ demand based on traffic flow data. It turns out that ignoring the transition of adopting hydrogen technology may result in a significant loss. HRSs have a cluster-like structure which is due to the demographic structure of the city. One cluster of stations serves to the underpopulated region (at the peripherals) and the other cluster is located at the densely populated districts (the middle regions of the city). It turns out that instead of spreading from the center to the city boundary, the stations appear at both clusters from early periods of the 30 years planning horizon.

Prediction of Wind Speed by Using Chaotic Approach: A Case Study in Istanbul

Renewable energy sources have gained great popularity due to the increasing importance given to a sustainable environment and economic development. Because of the environmental friendliness of renewable energy compared to fossil fuels, the tendency and investments in this field have increased. Wind energy comes into prominence among renewable energy sources because of its potential power that is used in various areas currently. Wind energy having stochastic nature is more sensitive to the extreme values of wind speed. Therefore, in order to create wind energy effectively, an accurate wind speed forecast is needed. In this study, nonlinear dynamical system approaches have been implemented by using reconstructing of phase space based on specifying minimum embedded dimension and delay time. In order to find out performance, different error metrics (MSE, RMSE, MAE, and MAPE) have been implemented. According to results, RMSE has been found 0.47 and 0.85 in hourly and daily dataset, respectively. Also, the correlation coefficient between the measurement and the obtained data set was as high as 0.92 in the hourly wind variable. In addition, a lesser correlation coefficient of 0.62 was found in the daily wind speed.

A methodology to creating semi-artificial city driving cycle: case study of Istanbul

This study describes the methodology of creating Semi - Artificial City Cycle (SACC), which can be used for emission tests of road vehicles; sustainability of hybrid electric vehicle (HEV); or emission inventories of the city. This methodology uses the half-hour frequency traffic data of Istanbul to calculate the average speeds and travel distances of urban, rural and highway segments. Then, calculated average data convert into instantaneous time—velocity distribution by random time—speed values, which are appropriate for acceleration/deceleration of real-world driving. In addition, in this study, the obtained artificial cycles and the regulation cycle are modelled in the AVL Cruise software to compare, and the driving dynamics of the city are examined. The SACC has different acceleration/deceleration distribution, average driving speeds, trips and travel times than regulation tests. However, according to the simulation results, the same fuel consumption and CO2 emission factors are obtained with the regulation test, except for the highway segment.

Factors affecting utilization opportunity of wetlands and their immediate surroundings in abandoned mining sites: A case study for Istanbul

As in the whole world, abandoned mining sites and their immediate surroundings stands as a major environmental problem in Turkey. This study aims to reveal the factors affecting the utilization opportunities of the wetlands and their immediate surroundings in the abandoned mining sites in Istanbul through a multidimensional approach. In the study, a 34-variable factor analysis was performed, and approximately 75% of the respondents’ opinions were explained with seven factors by taking 24 variables as a basis at the end of the reliability analysis. These factors are listed according to their significance level: (1) utilization for recreational purposes, (2) utilization for functional purposes, (3) management and operation, (4) utilization as water reserve areas, (5) utilization as disposal sites, (6) legal framework, principles, and procedures, and (7) contribution to employment and economy. Afterwards, the nonparametric Kruskal-Wallis H and Mann-Whitney U tests were used to investigate whether there was a statistically significant and important difference between the various socio-economic variables (gender, occupation, workplace and experience) of the groups identified within the scope of the questionnaire. According to these results, thanks to the interdisciplinary and multi-functional planning of these sites after mining activities and their correct and effective management, the local people will be ensured to benefit from these sites at the highest level and the ecological balance will be re-established. The previous economic and ecological value of the abandoned mining sites should at least be restored and/or developed further. There are various criteria and indicators for this. In order to carry out and follow up the works in these areas in a successful way without interruption, it is important that legal arrangements to be made include not only forest areas but also all areas that require nature restoration such as agriculture, industry, solid waste, mines and quarries. In this sense, it should be ensured that all relevant persons and institutions cooperate with each other. As a result, in terms of sustainable land use, this study revealed an approach regarding the correct and effective management of damaged areas remaining after mining and its importance.

Locating a disinfection facility for hazardous healthcare waste in the COVID-19 era: a novel approach based on Fermatean fuzzy ITARA-MARCOS and random forest recursive feature elimination algorithm.

Hazardous healthcare waste (HCW) management system is one of the most critical urban systems affected by the COVID-19 pandemic due to the increase in waste generation rate in hospitals and medical centers dealing with infected patients as well as the degree of hazardousness of generated waste due to exposure to the virus. In this regard, waste network flow would face severe problems without taking care of hazardous waste through disinfection facilities. For this purpose, this study aims to develop an advanced decision support system based on a multi-stage model that was combined with the random forest recursive feature elimination (RF-RFE) algorithm, the indifference threshold-based attribute ratio analysis (ITARA), and measurement of alternatives and ranking according to compromise solution (MARCOS) methods into a unique framework under the Fermatean fuzzy environment. In the first stage, the innovative Fermatean fuzzy RF-RFE algorithm extracts core criteria from a finite set of initial criteria. In the second stage, the novel Fermatean fuzzy ITARA determines the semi-objective importance of the core criteria. In the third stage, the new Fermatean fuzzy MARCOS method ranks alternatives. A real-life case study in Istanbul, Turkey, illustrates the applicability of the introduced methodology. Our empirical findings indicate that “Pendik” is the best among five candidate locations for sitting a new disinfection facility for hazardous HCW in Istanbul. The sensitivity and comparative analyses confirmed that our approach is highly robust and reliable. This approach could be used to tackle other critical multi-dimensional problems related to COVID-19 and support sustainability and circular economy.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10479-022-04822-0.

Recovery center selection for end-of-life automotive lithium-ion batteries using an integrated fuzzy WASPAS approach

With the emergence of battery-based electric vehicles, transportation systems gradually leave using fossil fuel-based combustion engines. Due to their reasonable performance, Lithium-ion batteries have become one of the major batteries used for electric vehicles. Although these batteries are being used in most companies, their high production cost, rare raw material, and short life cycle have raised important incentives for their recovery process. However, locating a recovery center for end-of-life Lithium-ion batteries is a multi-aspect decision making problem influenced by many criteria. For this purpose, a novel integrated decision-making model is developed based on Measuring Attractiveness by a Categorical Based Evaluation TecHnique (MACBETH) for calculating the criteria weights and Weight Aggregated Sum Product ASsessment (WASPAS) methods under the fuzzy environment with Dombi norms for evaluating the alternatives to address recovery center location selection problem considering technical as well as environmental, economic, and social aspects. To show the reliability and applicability of the developed method, a real-world case study in Istanbul is investigated. The developed method is used to evaluate six potential locations for the possible establishment of a recovery center. Results showed that Tuzla district is the most suitable location for opening a recovery center for end-of-life Lithium-ion batteries. Tuzla is in a very good position in terms of proximity to suppliers, transportation and location. To illustrate the robustness of the obtained results, extensive sensitivity analysis tests are performed.

A Novel Stochastic Optimization Model for Reverse Logistics Network Design of End-of-Life Vehicles: A Case Study of Istanbul

Waste management is gaining crucial importance as recycling aims at transforming produced waste into value for the economy. As the automotive industry is growing fast worldwide, recycling end-of-life vehicles (ELVs) attracts great research attention. Due to the promulgated regulations, multiple players like the last owners, manufacturers, treatment centres, and municipalities require a more cooperative engagement. The participation of multiple actors in the recycling process of ELVs brings various uncertainties. Additionally, parameters of the recycling process, like the number of vehicles withdrawn per year, cost items, and material composition tend to change due to technological, social, and economic developments. The automotive industry has crucial importance in the Turkish economy, which is highly affected by socio-political and economic issues. Furthermore, the Istanbul metropolitan area has the highest rate of vehicle ownership in Turkey. For that purpose, this paper proposes a scenario-based real-life stochastic optimization model to improve ELV supply chain network management in Istanbul. Sensitivity analyses to changes in scenario occurrence probabilities and changes in the amount of collected ELVs are performed to question the consistency of the study. The results of the mathematical model highlight that the operational cost items have the greatest ratio comparing the other cost items in the model. Furthermore, the results of the sensitivity analysis underline that the operational costs and selling prices of the materials from the ELVs have a significant impact on the profitability of ELVs’ recycling process. In addition, uncertainty in the number of ELVs has a significant effect on both operational and strategical decision-making processes. This research can be extended in the direction of examining the effectiveness of ELV management in Turkey since Istanbul could represent the whole of Turkey with its economic and cultural characteristics. Further works can also try to implement the novel concept of a “socially resilient supply chain” in the ELVs’ management.

Applying robust optimization to the shelter location–allocation problem: a case study for Istanbul

Applying robust optimization to the shelter location–allocation problem: a case study for Istanbul

Multi-criteria decision making for city-scale infrastructure of post-earthquake assembly areas: Case study of Istanbul

Assembly areas are first gathering places after earthquakes, and provide temporary sheltering. However if these areas have greater risks after earthquakes, they become more deadly. Current studies commonly look for evacuation shelter and temporary housing location models but most of them are not suited to assembly areas. This study aims to determine safe post-earthquake assembly areas by using the multi-criteria decision-making approach through an analytical hierarchy process using a geographical information system. 15 criteria were defined to evaluate the suitability in terms of spatial, natural structure and accessibility of each potential open space for emergency gathering. Following these criteria, possible areas were mapped, evaluated and scored with thematic hazard maps by using geographic information system in a case study to demonstrate the model. Finally, suitability layers were superimposed to estimate the safe assembly areas index and produce the city-scale infrastructure map. As a result, 107 assembly areas were designated for seven neighborhoods in Istanbul. Study results show that not every open area is safe to be a post-earthquake assembly area. The proposed method can provide useful information that could assist in earthquake disaster mitigation, and help government decisionmakers support further location allocation optimization of safe assembly areas.

Comparison of incineration and autoclave methods in the treatment of medical wastes through life cycle assessment: A case study for Istanbul

Medical waste management has always been an important topic due to its infectious status. Recently, more care has been given to it due to the COVID-19 pandemic throughout the world. Several methods are applied to handle medical wastes. Incineration and sterilization with autoclave are among the most common medical waste treatment methods. Among all methods, incineration serves the ultimate method of waste destruction since the waste is exposed to high temperatures (~800 °C) for about 2 hours. Because of the pandemic or some other reasons, administrations may want to shift their technology to incineration from autoclave. Therefore, in this study, we aimed to prepare a comparison of both technologies in terms of life cycle perspective. We used OpenLCA for calculations. Two different calculations were conducted. In the first one, the actual treatment methods and the waste amount were used. In the second one, a scenario was formed that included the treatment of the whole medical waste of Istanbul by only incineration process. The results indicated a higher mid-category life cycle impact for the combustion method. The highest contribution was for human toxicity with 3.8e4 kg 1,4-DB eq and 1.7e5 kg 1,4-DB eq for the current operation and scenario, respectively. The environmental impact of the sterilization process remained negligible relative to the combustion process.

Does environmental quality and weather induce COVID-19: Case study of Istanbul, Turkey

The coronavirus pandemic has infected more than 100 million people worldwide with COVID-19, with millions of deaths across the globe. In this research, we explored the effects of environmental and weather variables with daily COVID-19 cases and COVID-19 fatalities in Istanbul, Turkey. Turkey has the 8th highest number of COVID-19 cases globally, with the highest infections and deaths in Istanbul. This may be the first study to conduct a comprehensive investigation for environmental quality (air quality pollutants, e.g., PM2.5 and PM10, ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide, etc.), weather parameters (temperature, humidity) and COVID-19 in Turkey. The authors collected meteorological data from 11 March 2020 to 8 February 2021 and COVID-19 data from Istanbul and other regions. The results from empirical estimations, correlation analysis, and quantile on quantile techniques support that air quality and temperature significantly influence COVID-19 deaths in Istanbul. This research may help policymakers and health scientists to take specific measures to reduce the spread of coronavirus across different global cities. The effects of air quality on COVID-19 in Istanbul was investigated. The study applied correlation and quantile on quantile techniques over daily data. Temperature significantly induces the spread of COVID-19 in Istanbul at all quantiles. Air quality and Nitrogen are positively linked with COVID-19 new cases.

Techno‐economic management of daily Volt/Var planning considering reactive power contribution of high penetrated‐PV solar farms utilized as STATCOM : A case study in Istanbul, Turkey

Techno‐economic management of daily Volt/Var planning considering reactive power contribution of high <scp>penetrated‐PV</scp> solar farms utilized as <scp>STATCOM</scp> : A case study in Istanbul, Turkey

Safety in Schools and Their Surroundings: A Case Study in Istanbul

This work proposes school safety be considered in terms of the wider perspective of urban safety in general, taking a totalitarian approach and presenting the basic problems and possible solutions inherent within the issue of safeguarding schools. School safety should not merely lie within the boundaries of any one school. School safety must be considered as one aspect of urban safety as a whole. Data presented in this article was collected by the International Strategic Research Organization (ISRO) as part of the four year, 2008–2012, Istanbul Urban Safety Project. The article does not consider threats to safety inside the school and its environs as matters to be dealt with by the police, but rather takes a holistic approach in the context of wider social problems to which the solutions lie in the implementation of comprehensive policies that include the school, the family, the social environment and policing in that order.

A triangulation process of street music in public spaces: a case study of Istanbul's Istiklal Avenue

Purpose This paper aims to discuss the spatial interactions of street music in public spaces. It proposes to clarify why relationship between street music and people in public spaces is important and how street music evokes an external stimulus on people. Design/methodology/approach The conceptual framework of this paper is based on the triangulation process of Whyte and the qualities of public spaces, forming a relationship between space and people produced from the seminal literature of the paper. Accordingly, a case study based on the qualitative research method was conducted in Istiklal Avenue, where street music performances can be observed for long term. During the field work which spans a period of 12 months, 10 spots of street music performances have been observed and photo–video documentation was collected. Findings This paper provides empirical insights on how the triangulation process reflects social interactions in public spaces. This also suggests the triangulated position of street music as an external stimulus relating with the people as actors of daily urban flux. Research limitations/implications Regarding to the chosen research approach which is based on deeper understanding, this paper interrelates the interactions of street music and people in public space. Social implications This paper includes qualitative research steps of data collection and disaggregates findings with a “Cross Matrix Table” proposed at the end of the study. Originality/value The proposed disaggregating “Cross Matrix Table” and case study fulfil an architectural need to research how everyday street art activity can reflect the qualities of public space.

Black carbon and size-segregated elemental carbon, organic carbon compositions in a megacity: a case study for Istanbul

In this study, black carbon (BC), particulate matter (PM), nitrogen oxides (NOx), and sulphur dioxide (SO2) were monitored between May 2019 and February 2020. During this sampling period, size-segregated particle samples were collected by a high-volume cascade impactor, once a week. Elemental carbon (EC) and organic carbon (OC) were investigated on the size-segregated particles. The study was carried out at Esenler district of Istanbul. Main sources in the vicinity of the sampling area are Central Coach Station of Istanbul, residential buildings, small-scale industrial facilities, and O-1 and O-2 highway connection. The average BC concentration was 2763 ± 1974 ng/m3. PM10 and PM2.5 concentrations were 38.2 ± 17.4 and 21.5 ± 12.4 μg/m3, respectively. BC comprised 12.8% and 7.2% of PM2.5 and PM10, respectively. Diurnal variation of BC had a similar trend with NO2 concentrations, which showed peak concentrations during rush hours. BC had high Pearson correlation coefficients with NO, NO2, and PM2.5. The geographical position of possible emission sources was estimated through conditional probability function. The Central Coach Station of Istanbul had the highest geographical possibility for BC sources. EC and OC exhibited bimodal size distribution. The coarse mode peak was at 0.95–1.5-μm size bin for OC, whilst it was at 1.5–3-μm size bin for EC. Since EC and BC exhibit the same origin with different measurement principles, we concluded that resuspension of road dust also contributed ambient BC concentrations.

Discovering Activity Patterns in the City by Social Media Network Data: a Case Study of Istanbul

With the rapid developments in internet and communication technologies, activities take within the city create a reflection in virtual environments and these traces make visible the relation ties of the city’s dynamic structure. The data generated by mobile devices that take part in everyday life and become integrated with the user’s activities gives valuable information about users’ behavioural trends in the city. This new type of data, called ‘Big Data’ that consist of huge amounts of information with a fine-grained resolution, also help people to make reasoning about the activity pattern formations within the city, with a bottom-up approach. This approach also paves the way for developing a holistic approach. This study aims to discover and analyse the activity patterns of the parts of historical districts of Istanbul by evaluating the data generated from location-based social networks. Foursquare API database is utilised to collect activity data that consist of location, venue, category, and visitor counts (check-in) features. The data mapped and weighted with the check-in counts and spatial statistics analyses held in GIS to discover hotspot and cluster patterns of the activities within the study area. The main finding of the paper is that the spatial distribution of citizens’ demand for products and services creates patterns of emerging urban areas of activity.

Groundwater budget rationale, time, and regional flow: a case study in Istanbul, Turkey

The groundwater balance is based on the principle that the water entering and leaving any aquifer is considered to be equal over a certain time-interval, taking into account the change in storage. However, in reality, determining a groundwater balance is complicated by the fact that it may take a very long time-interval to achieve a water balance in an aquifer and circulating groundwater may vary greatly in age, and may have been recharged under different climatic conditions in the past. Accounting for all of the inflows and outflows from a groundwater flow system including changes in the future is called a groundwater budget. Until the 1950s, sustainable groundwater management was made with the understanding that groundwater abstraction should not exceed the natural recharge, and the permission for groundwater abstraction is still given with the same approach in Turkey. This approach has globally been declared archaic since the 1980s, and the calculation of water captured from discharge, and recharge has come to an approach that ignores the recharge. Not fully understanding the overlapping groundwater communicating time and regional fast-flow pathways are the main reason for the water budget controversy and modeling mistakes. Estimating the groundwater budget correctly is crucial to controlling global groundwater depletion and floods. It is imperative to revisit the groundwater budget discussions due to these two major environmental problems seeming to be in opposition.

A fuzzy Full Consistency Method-Dombi-Bonferroni model for prioritizing transportation demand management measures

The selection and prioritization of appropriate Transportation Demand Management (TDM) measures is a common problem faced by transport planners and decision makers. The problem involves many uncertainties due to changing economic conditions, uncertainty in project success, changes in mobility and population characteristics etc. In this study, the multi-criteria decision making (MCDM) based fuzzy Full Consistency Method-Dombi-Bonferroni (fuzzy FUCOM-D’Bonferroni) model is proposed for a case study in Istanbul’s urban mobility system. Istanbul’s historical peninsula is considered to be a pilot area for the implementation of TDM projects by the local government. The proposed model is compared with other well-known four MCDM methods in order to show its validity and consistency. The results show that public transport capacity improvements is the best alternative among the other TDM measures.

The assessment of smart city projects using zSlice type-2 fuzzy sets based Interval Agreement Method

Cities are facing many urban challenges such as traffic congestion, air pollution, energy consumption and urban sprawl. Smart city concept is proposed to cope with these challenges. However, current smart city initiatives require a comprehensive decision-making framework. In this study, in order to capture individual and multiple opinions from decision makers over repeated surveys, the Interval Agreement Approach (IAA) is utilized to prioritize and evaluate the smart city dimensions for Istanbul's recent smart city project. The validity of the suggested approach is tested with a case study of Istanbul, the largest city in Turkey with many urban problems such as chronic traffic gridlock, rapid urban growth and environmental pollution. The results from the experiments show that IAA can be a useful approach for researchers who theoretically study smart city dimensions, concepts and decision-making methods. It can also help practitioners who deal with implementing smart city projects.

Multi-Step Approach to Improving Accuracy of Incident Duration Estimation: Case Study of Istanbul

Multi-Step Approach to Improving Accuracy of Incident Duration Estimation: Case Study of Istanbul