Methodological framework for urban sprawl control through sustainable planning of urban green infrastructure

Gavrilidis, Athanasios Alexandru; Niţă, Mihai Răzvan; Onose, Diana Andreea; Badiu, Denisa L.; Năstase, Irina Iulia

doi:10.1016/j.ecolind.2017.10.054

Cited by 130 publications

(60 citation statements)

References 70 publications

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“…Additionally, groups for the mode of transportation used by the respondents have generated accordingly: (car, carpool, airplane, bus, walk or bike, and others). Based on Reference [23], data screened for possible normality and linearity, possible outliers, and missing values. To implement research objective 3, researchers referred to scientific reports that utilized the greenhouse gases regulated emissions and energy use in transportation (GREET) model to calculate the quantity of CO 2 emissions generated by the travelers to the event based on the mode of transportation that they utilized [24,25] The GREET model is a reliable tool that can estimate the CO 2 emissions generated by personal automobiles, public transit (e.g., train and bus), and airplanes [26,27].…”

Section: Discussionmentioning

confidence: 99%

“…According to the United States Environmental Protection Agency (US EPA) reports, on average, the typical American car generates an average of 8.9 kg of CO 2 emissions per gallon of regular gasoline [22]. Given the amount that Reference [22] has provided, the average American car generates 0.40 kg of C 2019, 5, 49 7 of 10 CO 2 emissions per mile, and therefore, based on Reference [23], the carbon footprint of one person inside a given vehicle driving 1 mile was assumed to have a carbon footprint of 0.40. Table 3 shows the quantity of the CO 2 emissions generated by participants who traveled by car for each mileage group.…”

Section: Co 2 Emissions (Research Objective 3)mentioning

confidence: 99%

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Growing Cities and Mass Participant Sport Events: Traveling Behaviors and Carbon Dioxide Emissions

Triantafyllidis

Davakos

2019

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Fast-growing cities are expected to become a key contributor to the global climate crisis. A key characteristic of those urban districts is the accommodation of mass participant sport events. Sport entities, in collaboration with city governments, plan annually active participation sport events to promote their cities as tourism destinations. Mass participant sport events aim to attract more visitors to the cities and to establish a successful social and economically sustainable future to those places. Given the fact that transportation is a critical factor of the residents and the visitors’ behavior, it is crucial to research the quantity of CO2 emissions generated to those places in association with the travel behaviors of the active sport event participants. Data collected from an annual mass participant running event in a highly ranked growing city in the United States. Findings showed that most of the active sport event participants traveled more than 150 miles to participate in the race and they used their vehicles. The largest quantity of CO2 emissions derived from those participants who traveled a round trip of, on average, 500 miles. The long-distance travelers alone generated 338 million kg of CO2 emissions. The conclusions recommend that growing cities and sport events should target long-distance travelers for promotions concerning sustainable transportation. Consequently, mass participant sport events could play a crucial role in the development of growing cities, and, in turn, growing cities that control long-distance traveling behaviors can reduce the global amount of greenhouse gas emissions and their impact on the global environmental destruction.

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Section: Discussionmentioning

confidence: 99%

Section: Co 2 Emissions (Research Objective 3)mentioning

confidence: 99%

Growing Cities and Mass Participant Sport Events: Traveling Behaviors and Carbon Dioxide Emissions

Triantafyllidis

Davakos

2019

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“…Accessibility to environmental/neighborhood services is a major and fundamental tool for urban planning (Gavrilidis et al 2019). The minimum distance, transportation costs, streets networking and location of property are discussing in cases of accessibility (Belmeziti et al 2018).…”

Section: Review Literaturementioning

confidence: 99%

The impact of neighborhood services on land values: an estimation through the hedonic pricing model

2020

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A strong need exists to increase the knowledge and recognize the values of neighborhood services. This paper makes an attempt to examine the impact of neighborhood services on land values, through analysis based on results obtained from multi linear regression analysis. This case study was done in area of dense urban settlement to check the consequence of neighborhood services through the hedonic pricing model base variables which include the structural, locational, community and neighborhood services. The regression coefficient was checked at (p \ 0.05) level of significance for each variable. The primary data was collect through the questionnaire filling by random sampling and Punjab Urban Gazette was used for the verification of land values in study area. The results found a valuable potential on land and property values of neighborhood services through the regression analysis results express through R (0.926), R 2 (0.856) and coefficient tables to represent the effect of each individual variable on property and land values. Every individual variable play role in defining the values of land and property based upon its utilization such as larger the structure of a property, more the covered area, larger size of a property more the land area higher price. Similarly, for locational factor study in geography, a piece of land adjacent to the road have high land values 50-70% compare to those located at distance. Very less attention has been paid on such issues in the world due to lack of effective urban planning and research on such crucial issues. If empirical studies on such issue has been done, effective way can be obtained for urban planning.

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“…In [ 21 ], a comparison among the AQI and the different city contexts was estimated, and the study was limited to roadside and city background situations. The study realized in [ 22 ] defined a smart city divided in urban functional zones (agricultural, industrial, commercial, multi dwelling housing, individual housing) which were described and categorized in detail, though a correlation among each of them and the specific pollutants emitted and air quality estimation was missing. In [ 23 ], a study on AQI estimation was realized connected to the city morphological characteristics of a smart city, the study was mainly focused on density population, road graph, buildings, Point of Interest (POI), traffic data, vegetation, and meteorological data.…”

Section: Introductionmentioning

confidence: 99%

High Density Real-Time Air Quality Derived Services from IoT Networks

Badii

Bilotta

Cenni

et al. 2020

Sensors

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In recent years, there is an increasing attention on air quality derived services for the final users. A dense grid of measures is needed to implement services such as conditional routing, alerting on data values for personal usage, data heatmaps for Dashboards in control room for the operators, and for web and mobile applications for the city users. Therefore, the challenge consists of providing high density data and services starting from scattered data and regardless of the number of sensors and their position to a large number of users. To this aim, this paper is focused on providing an integrated solution addressing at the same time multiple aspects: To create and optimize algorithms for data interpolation (creating regular data from scattered), making it possible to cope with the scalability and providing support for on demand services to provide air quality data in any point of the city with dense data. To this end, the accuracy of different interpolation algorithms has been evaluated comparing the results with respect to real values. In addition, the trends of heatmaps interpolation errors have been exploited to detected devices’ dysfunctions. Such anomalies may often be useful to request a maintenance action. The solution proposed has been integrated as a Micro Services providing data analytics in a data flow real time process based on Node.JS Node-RED, called in the paper IoT Applications. The specific case presented in this paper refers to the data and the solution of Snap4City for Helsinki. Snap4City, which has been developed as a part of Select4Cities PCP of the European Commission, and it is presently used in a number of cities and areas in Europe.

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Methodological framework for urban sprawl control through sustainable planning of urban green infrastructure

Cited by 130 publications

References 70 publications

Growing Cities and Mass Participant Sport Events: Traveling Behaviors and Carbon Dioxide Emissions

Growing Cities and Mass Participant Sport Events: Traveling Behaviors and Carbon Dioxide Emissions

The impact of neighborhood services on land values: an estimation through the hedonic pricing model

High Density Real-Time Air Quality Derived Services from IoT Networks

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