Air Temperature for Sustainable Airport Infrastructure and Environment

Understanding the patterns of air temperature in the local area is essential to mitigate potential destructive impacts and develop strategies for climate-resilient infrastructure. The pilot study focuses on the analysis of air temperature at Soekarno Hatta International Airport (SHIA), Indonesia. The study utilizes air temperature data collected over a 30-month period, grouped into six-month intervals. To assess the significance of means and distributions of air temperature points, independent t-tests are employed. Data visualizations are provided to clarify the air temperature patterns during the observation period. The findings reveal that SHIA has experienced warm and stable air temperatures over the last 30 months. However, to comprehensively study the various impacts from climatology and meteorology perspectives on airport infrastructure and operations, it is essential for future research to address limitations related to access to certain variables and consider employing multivariable forecasting techniques. By addressing these aspects, further investigations are able to provide deeper insights into the implications of air temperature on airport operations and contribute to formulate a strategy for developing a climate-resilient airport infrastructure.


Introduction
The operational performance of aviation greatly benefits from climate-resilient airport infrastructure.In this context, Gallardo described that the fluctuations of air temperature play a major role in determining airport operation [1].By carefully examining the air temperature of the local area whether using internet of things infrastructure or citizen reports in social media [2,3], airports can enhance their operational efficiency and preparedness to withstand various air temperature challenges.In terms of aviation, air temperature fluctuations directly impact aircraft punctuality [4,5,6].The reduction in air density results in decreased lift during takeoff, causing slower acceleration and climbing rates on runways.In terms of airport infrastructure, the analysis of local air temperature holds significant 1324 (2024) 012010 IOP Publishing doi:10.1088/1755-1315/1324/1/012010 2 importance for several reasons.Voskaki, Budd and Mason highlighted climate-resilient airport design as an effective risk mitigation plan based on various studies caused by climate variables including flood, snow, wind, and temperature [7].Furthermore, according to Abdallah, Makram, and Nayel, an analysis to find suitable indoor temperature can solve passenger satisfaction and energy efficiency within airport terminal facilities at once [8].
The analysis of air temperature within an airport infrastructure serves as an essential initial step in comprehending the local temperature conditions.A thorough examination of air temperature provides valuable insights, particularly in the prediction of delay times.Wang et al. conducted an analysis of numerous flight delay cases at Beijing Capital International Airport.The investigation focused on the relationship between air temperature and average delay time.The findings revealed that as the air temperature ranged between 20 to 40 degrees Celsius, the average delay time increased [9].Schultz, Reitmann, and Alam identified that air temperature and wind speed play crucial roles as significant contributing factors leading to flight delays, particularly in the context of departure flights rather than arrival flights [10].Many studies have highlighted the significance of air temperature analysis as a critical aspect to consider in the assessment and management of air travel operations.It underscores the importance of incorporating air temperature assessments to optimize operational performance of an airport.
The study aims to conduct a pilot analysis of air temperature at Jakarta International Airport Soekarno Hatta.The study which was inspired by the mentioned temperature analyses involves a 30month collection of daily average air temperature data.This study employs statistical tests to determine the significance of air temperature means within the research site.The findings of this study offer valuable insights into the air temperature trend at the airport, which is essential for formulating strategies to manipulate air temperature in order to enhance airport operational management.By understanding the patterns and fluctuations in air temperature, airport authorities and aviation operators can implement effective measures to mitigate risks.

Literature Review
Air temperature analysis plays a significant role in various applications, particularly in addressing climate change, optimizing energy consumption, and gaining a comprehensive understanding of a particular territory [11].In several studies conducted by Bioinformatics and Data Science Research Center, air temperature positively correlates with particulate matter (PM) [12] and other climate variables such as ground level ozone [13] that influence local air quality [14,15].Ekwueme and Agunwamba have employed trend analysis approaches and statistical tests to investigate the influences of air temperature changes on other climatic aspects, such as rainfall, in Nigeria [16].Additionally, Qian et al. conducted air temperature analysis at Adelaide Airport to compare the impact of irrigation trials aimed at cooling the airport [17].
Air temperature analysis utilized time-series datasets that capture specific characteristics.These datasets are typically compiled from multiple weather stations and cover extended periods of time, allowing researchers to explore anomalies on an annual or seasonal basis.Additionally, time series forecasting techniques are frequently employed to generate accurate predictions in various cases.For example, Radhakrishnan's analysis highlights the trend of mean temperature in India.The findings reveal an increase of 0.86 degree Celsius in the annual mean temperature from the first two decades to the last two decades [18].Another example, Vincent et al. conducted an analysis of temperature trends across various observation locations in Canada, considering both annual and seasonal patterns.The results indicated an overall increase in temperatures at most of the observation spots.Specifically, the annual mean temperature averaged across the country displayed a positive trend of 1.5°C over the course of the past 61 years [19].

Research Methods
Figure 1 provides a comprehensive visual representation of the main processes.The study commenced with data acquisition, and subsequently, a thorough data pre-processing procedure was undertaken to 1324 (2024) 012010 IOP Publishing doi:10.1088/1755-1315/1324/1/0120103 ensure the dataset's readiness for analysis.The data analysis phase commenced with exploratory data analysis, which allowed for the identification and understanding of the characteristics of air temperature at the research site.The independent t-test was utilized to ascertain statistical significance within paired intervals.Data visualization techniques were employed to augment the understanding of the data analysis process through visual representations.Finally, the study concludes with a synthesis of the various analyses conducted, allowing for meaningful insights and conclusions to be drawn from the findings.Air temperature data from various airports is publicly available for download on weatherundergroud.com.The dataset was collected from Jakarta Soekarno-Hatta International Airport (SHIA) spanning a period from January 1 st , 2021, to June 30 th , 2023.The data was grouped into sixmonth intervals, and the temperatures were recorded using the Fahrenheit measurement scale.Table 1 shows the grouping of the data into five distinct six-month intervals.Intervals 2021_1, 2022_1, and 2023_1 commenced annually on January 1 st and concluded on June 30th each year.Conversely, intervals 2021_2 and 2022_2 initiated on July 1 st and terminated on December 31 st of each year.

Intervals Start Date End Date 2021_1
In the context of statistical analysis, independent t-test is employed to compute the means of two independent samples.Within the Python programming language, the SciPy library can be utilized to facilitate independent t-test computations.When employing independent t-test module, the "equal_var" parameter can be set to "True" if the assumption of equal population variances is met, thus conducting a default independent t-test.Alternatively, the parameter can be set to "False" in cases where population variances are not equal, thereby enabling the execution of Welch's t-test.A significance level (α) of 0.05 was applied to all pertinent analyses conducted within this study.

Air Temperature Analysis
Table 2 describes the characteristics of the acquired air temperature data.Overall, the analysis of the air temperature at the research site reveals a stable pattern with minor variations around mean and median values.The dataset consists of uniform sample sizes across all intervals.It is notable that the distribution of temperature points in 2021_1, 2022_1 and 2023_1 appears to be more distributed around the mean value rather than the period of 2021_2 to 2022_2 which shows a similar spread.In addition, Table 3 shows the results of the independent t-test.Several significant differences in temperature averages across certain time periods are detected.Specifically, statistically significant differences were found between the temperature averages of 2021_1 and 2021_2 (p-value: 0.001), 2021_2 and 2023_1 interval (p-value: 0.019), 2021_2 and 2022_1 interval (p-value: < 0.001), 2021_2 and 2022_2 interval (p-value: 0.002), 2022_1 and 2023_1 interval (p-value: 0.010), and 2022_2 and 2023_1 (p-value: 0.040).Independent t-test results suggest that these specific time intervals exhibit distinct temperature characteristics, possibly indicating climatic shifts or influences from the regional climate.However, no statistically significant differences were detected between the temperature averages of other group pairs, which described relatively stable temperature trends within those specific time periods.Figure 2 represents a boxplot with trendline visualization of the air temperature at SHIA according to chronological order.The visualization clarifies that the air temperature is relatively stable after a slight significant fluctuation to the mean temperature in 2021_2.

Discussion
Air temperature of SHIA that ranges from 81.8 to 82.4 °F is considered warm for airport operation.
The temperature range has the potential to cause aircraft operational challenges, particularly for aircraft equipped with C-MAPSS40k engines [20].These engines, which are engineered to withstand air temperatures within the range of -30 to +50 degrees Fahrenheit, may exhibit diminished performance characteristics when subjected to temperatures that surpass the upper threshold of this designated range.Also, the temperature range might cause several damages that affect the operation of an airport include cracks on the runway, corrosions on fuel tanks, and compromising the structural integrity of terminal buildings [21].Several investigations have addressed potential factors contributing to the rise in air temperature and its associated implications.The increase of air temperatures can be attributed to several sources, including the release of hot exhaust gases from jet engines during aircraft take-off and landing 1324 (2024) 012010 IOP Publishing doi:10.1088/1755-1315/1324/1/0120105 procedures [22].Additionally, ground operations at airports, particularly those involving auxiliary power units (APUs), can generate substantial heat as well [23].Organizing independent t-test outcomes and arranging them chronologically reveals that each sequential interval pairing demonstrates statistical significance, except for the comparison between 2022_1 and 2022_2 (p-value: 0.544).This finding signifies a consistent and stable air temperature pattern during that specific period.A significant increase in air temperature was also observed during the interval 2021_2.According to a report by PricewaterhouseCoopers (PwC), this rise coincided with a significant surge in both passenger numbers and flight routes, commencing from 2021_1 [24].This trend was associated with the relaxation of travel regulations by the Indonesian government, which were previously implemented to mitigate the spread of COVID-19 [25].The rising demand is potentially influencing the local air temperature due to increased airport activity and operational demands.As air travel continues to recover, further investigation into the interplay between passenger traffic, flight routes, and air temperature may provide valuable insights for sustainable factor in terms of aviation and airport environment management.
The stability of warm temperature in SHIA is supported by eco-building, which was implemented in SHIA rest area that connects Terminal 1 and 2. The concept of eco-building aims to safeguard the natural environment through the incorporation of energy-efficient technologies and sustainable materials to minimize resource wastage.This initiative not only does contribute to the climatology aspect of the airport infrastructure but also significantly aligns with environmental considerations [26].Considering the energy consumption observed in SHIA Terminal 3 [27], it is highly recommended to explore the utilization of the warm temperature at SHIA for the installation of solar panels.This strategic approach holds the potential to harness renewable energy sources and contribute to the airport's energy sustainability efforts, thereby mitigating the environmental impact of its operations.

Conclusion
The findings of this study indicate that the last 30 months, the air temperature at SHIA has remained relatively warm and stable, ranging from 81.8 to 82.4 °F.Despite the stability, each observed interval shows statistically different means and distributions of air temperature points.However, further investigation is required to determine the implications of the constant warm air temperature on SHIA and to address the prediction of climatological and meteorological impacts on airport infrastructure and operations.The limitation of this study is various supporting datasets such as flight departure, arrival, climate and meteorology were not included due to limited access to the data source.Since many studies recommended combining air temperature data with various meteorological variables and departure-arrival records to predict delay time with machine learning methods, future directions of this

Figure 1 .
Figure 1.Five main processes in the study.

Figure 2 .
Figure 2. Boxplots and trendline visualization of air temperature at SHIA.

Table 2 .
The characteristics of air temperature at SHIA grouped in six-month interval.

Table 3 .
Independent t-test results.