Although the concept of sustainable development has made certain achievements in many fields, airport sustainability (AS) has not yet formed a unified and comprehensive theory and evaluation method. According to the connotation of sustainable development, this paper proposes the definition of airport sustainability by considering China’s national conditions and airport characteristics. Secondly, this paper identifies four AS dimensions of economy, environment, society, and operation and selects and screens evaluation indicators for each dimension. Thirdly, a synthetic evaluation index model of AS is constructed based on the benefit of the doubt (BoD) model, and the process of evaluation method is planned according to a synthetic evaluation method. Finally, Guangzhou Baiyun International Airport (CAN) is selected as a case study to evaluate the AS from 2008 to 2017, and the influencing factors of AS are discussed to predict AS in 2018. The evaluation and prediction results are consistent with the actual operational characteristics of CAN.
Airport environmental carrying capacity (AECC) provides the fundamental conditions for airport development and operation activities. The prediction of AECC is a necessary condition for planning an appropriate development mode for the airport. This paper studies the dynamic prediction method of the AECC to explore the development characteristics of AECC in different airports. Based on the driving force-pressure-state-response (DPSR) framework, the method selects 17 main variables from economic, social, environmental and operational dimensions, and then combines the drawing of causal loop diagrams and the establishment of system flow diagrams to construct the system dynamics (SD) model of AECC. The predicted values of AECC are obtained through SD model simulation and accelerated genetic algorithm projection pursuit (AGA-PP) model calculation. Considering sustainable development needs, different scenarios are set to analyze the appropriate development mode of the airport. The case study of the Pearl River Delta airports resulted in two main conclusions. First, in the same economic zone, different airports with similar aircraft movements have similar development characteristics of AECC. Second, the appropriate development modes for different airports are different, and the appropriate development modes for the airport in different periods are also different. The case study also proves that the AECC prediction based on SD model and AGA-PP model can realize short-term policy formulation and long-term planning for the airport development mode, and provide decision-making support for relevant departments of airport.
In order to evaluate the airport's comprehensive service capabilities, this paper considers the impact of air quality and noise on the airport environment under the big data of air traffic activities. In this study, the concept of environmental traffic capacity and big data are applied to the air traffic field. Recently, the airport air and noise pollution has been widely investigated and has become one of the major concerns of the potentially exposed people. This study explores the usage of governmental ambient air quality and noise standards to evaluate the airport operation capacities in the context of the era of big data. The first step is to analyze the typical airport operation scenario as the evaluation scenario. The second step is to use the air and noise emission assessment model for calculating the airport maximum air pollutant concentration and noise level. The final step is to establish a complete airport environment traffic capacity (AETC) evaluation process. As a case study, the capacity evaluation of Nanjing Lukou international airport (NKG) is performed using the above steps. In this case, significant associations between the pollutant concentrations/noise level and the air traffic volume were observed. The AETC of NKG was calculated with the established evaluation process successfully. The results show that the NKG maximum hourly air traffic volume is 120, daily air traffic volume is 770, and annual air traffic volume is 365,805, meeting the China Ambient Air Quality and Noise Standards. Although different air pollutants were investigated in this research, only the NOx was found to be the species that approaching the China governmental standards in this case. Thus, the airport NOx concentration was selected as the AETC limitation factor.
In order to clarify the comprehensive operational capabilities of the airport and better plan the sustainable development mode of the airport, this paper studies the evaluation method of airport environmental carrying capacity. First, this paper proposes the concept of airport environmental carrying capacity by taking into account the complex characteristics of airports affected by multiple factors and then selects 16 representative evaluation indicators to construct an indicator system based on the Driving Force-Pressure-State-Response (DPSR) framework. Finally, the accelerated genetic algorithm-projection pursuit model is established to model a comprehensive evaluation index, which is used to calculate the airport environmental carrying capacity (AECC). The results of the case study show that the AECC of Guangzhou Baiyun International Airport (CAN) decreased year by year from 2008 to 2017, which is in line with the coordinated development level of CAN. By analysing the changing mechanism of AECC and indicators, we get 6 key influencing indicators that led to the continuous decline of AECC and put forward some political suggestions to improve the AECC.
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