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An in-depth analysis of aviation route doses for the longest distance flight from Taiwan
Radiation Physics and Chemistry 168 (2020) 108548
Contents lists available at ScienceDirect
Radiation Physics and Chemistry journal homepage: www.elsevier.com/locate/radphyschem
An in-depth analysis of aviation route doses for the longest distance flight from Taiwan
T
Zi-Yi Yanga, Rong-Jiun Sheua,b,∗ a b
Institute of Nuclear Engineering and Science, National Tsing Hua University, 101, Sec. 2, Kuang-Fu Road, Hsinchu, Taiwan Department of Engineering and System Science, National Tsing Hua University, 101, Sec. 2, Kuang-Fu Road, Hsinchu, Taiwan
ARTICLE INFO
ABSTRACT
Keywords: Galactic cosmic rays Aviation route dose Flight route variation Great-circle approximation Correlation coefficients
This study investigated effective doses received on board an aircraft for the direct flight between Taipei and Houston, which is the longest distance flight from Taiwan with a flying distance of more than 13,000 km that takes approximately 13 h outbound and approximately 16 h inbound. Instead of choosing one representative flight, all 680 flights operated in 2017 were systematically analyzed by using a self-developed flight dose calculator, with an emphasis on effects of flight route variation and great-circle approximation. The average effective dose of 340 flights from Taipei to Houston was estimated to be 54.6 ± 7.8 μSv and that of 340 flights from Houston back to Taipei was estimated to be 64.4 ± 7.8 μSv, leading to a best dose estimate of 119.0 ± 11.0 μSv for a round-trip flight. The standard deviation associated with the mean value was approximately 10%, which offered a quantification of how daily flight routes may affect the resulting doses. As an alternative approach, the great-circle approximation predicted a round-trip dose value of 128.4 μSv, approximately 8% higher than that derived from actual fight routes. In addition, dose relationships of these flight routes with parameters including flight time, altitude, geomagnetic cutoff rigidity, and solar activity were identified using correlation coefficients and scatterplots.
1. Introduction Galactic cosmic rays, composed primarily of high-energy protons and heavier nuclei originating outside the Solar System, interact with the Earth’s atmosphere and produce cascade showers of secondary particles (Tanabashi et al., 2019). Radiation field at flight altitudes is a complex mixture of charged and neutral particles of various types and energies. The intensities, angular and energy distributions of primary and secondary particles in the atmosphere vary and depend on various solar, interplanetary, and geophysical conditions. Cosmic-ray induced radiation doses received on board an aircraft are substantially higher than those on the ground because of reduced protection of the atmosphere. Aircrew and frequent flyers are therefore exposed to elevated radiation levels from cosmic radiation on every flight, in particular for those flights with long distances, high altitudes, across polar regions, and under solar minimum conditions (ICRP, 2016). At present, the longest non-stop flight from Taiwan flies between Taipei and Houston, operated daily by EVA Airways with a flying distance of more than 13,000 km that takes approximately 13 h outbound from Taipei to Houston (flying from west to east) and approximately 16 h return from Houston to Taipei (flying from east to west). This flight
∗
is among the 25 longest flights in the world. In 2017, a total of 680 flights between Taipei and Houston were actually flown, including 340 outbound flights (flight number EVA52) and 340 inbound flights (flight number EVA51). Instead of choosing one or a few flight routes as representative, this study collected tracking data of all these flights, calculated individual route doses, and performed an in-depth analysis of these results to investigate the effect of flight route variation and check the appropriateness of great-circle approximation. In addition, for all outbound and inbound flights, correlation coefficients between influential parameters and the resulting route doses were calculated and discussed. The results provide a quantitative description and graphic demonstration of how the flight time, altitude, geomagnetic cutoff rigidity, and solar modulation affect the route dose calculations for this long-haul flight. The tool and approach used in this study can be useful for those who are interested in related topics and analyses. 2. Materials and methods 2.1. Route dose calculation High-energy cosmic rays penetrate into the atmosphere and induce
Corresponding author. Institute of Nuclear Engineering and Science, National Tsing Hua University, 101, Sec. 2, Kuang-Fu Road, Hsinchu, Taiwan. E-mail address: [email protected] (R.-J. Sheu).
https://doi.org/10.1016/j.radphyschem.2019.108548 Received 28 July 2019; Received in revised form 3 October 2019; Accepted 27 October 2019 Available online 31 October 2019 0969-806X/ © 2019 Elsevier Ltd. All rights reserved.
Radiation Physics and Chemistry 168 (2020) 108548
Z.-Y. Yang and R.-J. Sheu
Fig. 1. Flying trajectories and the route dose histograms for (a) 340 EVA52 flights from Taipei to Houston in 2017 and (b) 340 EVA51 flights from Houston back to Taipei.
parameters of the fitted sigmoid function. By observing the data dependencies, these interpolations are considered as reasonable approximations for flight dose estimation. Compared with the result of a direct simulation, the combined level of uncertainty resulting from interpolations of altitude, cutoff rigidity, and solar modulation parameter was estimated no more than 10%. The validity of the dose calculator (including the underlying database) has been demonstrated by comparing its predictions with the anonymous results of eleven similar codes summarized in EURADOS Report 2012–03 (Bottollier-Depois, 2012). For the selected 23 flight routes in the report, the route doses provided by our dose calculator show consistent and satisfactory agreement (within ~20%) with the median values of the predictions of other codes (Yang et al., 2019). After starting, the NTHU Flight Dose Calculator shows up an integrated interface with five main tabs for different application categories: User Specified, Orthodrome, Location, Personnel Dose, and Database. Two distinct features pertinent to this study are briefly described below. First, the dose calculator enables the user to perform automatic batch analysis of multiple flights, which is handy for the purpose of this study because 680 individual flights have to be analyzed. Second, the dose calculator by default can be run with a greatcircle path as an approximation to actual flight routes between airports. The flying altitude and speed of the aircraft along the great-circle path have default values but can be edited as desired. This function facilitates the comparison of route doses calculated according to an actual flight path and using great-circle approximation.
complicated hadron-electromagnetic-muon cascades, producing a large number of secondary particles, including neutrons, protons, muons, electrons, positrons, photons, pions, and heavy ions. Although time consuming, Monte Carlo simulations are generally the most accurate and suitable approach to determine and characterize the complex radiation field at flight altitudes (Roesler et al., 2002). The self-developed NTHU Flight Dose Calculator was used in this study for assessing exposure to galactic cosmic radiation during long-haul flights (Yang et al., 2019). The dose calculator is a graphical user interface program with a comprehensive database that describes and characterizes the radiation field in the atmosphere from the sea level up to 70 km of altitude. The database was generated based on a series of FLUKA Monte Carlo simulations of atmospheric showers caused by galactic cosmic rays (Ferrari et al., 2005). The ion composition of the galactic flux in the FLUKA simulations was derived from the Badhwar-O’Neill (1996) model, which considered all elemental groups from Z = 1 to Z = 28. The geomagnetic field was considered in two stages of the FLUKA simulation: 1) The geomagnetic cutoff was used to modulate the primary spectrum at the top of the atmosphere; 2) The local geomagnetic field was considered during shower development in the atmosphere. The geomagnetic cutoff rigidities of various locations and epochs were adopted from various literature sources, including Smart and Shea (1997) and Finlay et al. (2010). The resulting database comprises information about energy spectra and effective dose rates of various radiation components (neutrons, protons, muons, electrons, positrons, photons, pions, and heavy ions) in the global atmosphere calculated at two solar modulation parameters (φ=465 and 1440 MV). The effective dose rates were evaluated based on the FLUKA built-in fluence-to-dose conversion coefficients mainly from ICRP-74 (1996). The terms of dose and dose rate hereinafter are considered to be effective dose and effective dose rate without further explanation. In parallel with the database, the NTHU Flight Dose Calculator was developed to estimate the effective dose and energy spectra of various particles accumulated along a given flight route (actual or great-circle route) by performing a series of interpolations and summations. The altitude and solar modulation parameter have simple linear interpolations, and the interpolations of cutoff rigidity are based on the stored
2.2. Flight route information The flight tracking data of 680 EVA flights between Taipei and Houston operated in 2017 was purchased from the website FlightAware (2018). The file downloaded from the website is a comma-separated values file that is suitable for storing tabular data in plain text. Each line of the file is a data record corresponding to a waypoint during a flight. Each record has several fields or columns separated by commas. Only four columns in the file are necessary for dose calculations: timestamp, latitude, longitude, and altitude that collectively pinpoint the route 2
Radiation Physics and Chemistry 168 (2020) 108548
Z.-Y. Yang and R.-J. Sheu
taken by the aircraft. For a single flight, the user can easily process the data and import it into the NTHU Flight Dose Calculator immediately for route dose evaluation. For multiple flights in a file, which is typical for data downloaded from FlightAware, the dose calculator comes with auxiliary Python scripts developed for supporting users in automatic batch processing and data post-processing (Yang and Sheu, 2019). The left-hand side of Fig. 1 shows the flying trajectories of 340 outbound EVA52 flights and 340 inbound EVA51 flights on the world map for easy visualization. Evidently, each flight was flying a particular route because weather and aircraft conditions at that time affected the route and altitude taken by the aircraft regardless of the original flight plan. For a long-haul flight such as the one considered here, the greatcircle path is usually a good approximation to actual flight routes in aviation dose assessment because the great-circle path is the most efficient way to get the aircraft from one airport to another on the Earth’s surface. The default flying altitude and cruising speed were set to 11,000 km and 900 km/h, respectively, in the NTHU Flight Dose Calculator. The two parameters were adjusted in this study to achieve a fair comparison with the results based on actual flight routes. According to the actual flight tracking data, the average flying altitude and speed were first estimated and then used in the program to estimate the greatcircle route doses. The solar wind modulates the flux of galactic cosmic rays reaching the top of the Earth’s atmosphere. Although the changes in solar modulation of the cosmic-ray flux within a year are small when compared with the 11-year solar cycle, the mean monthly values of the solar modulation parameters for the year 2017 were calculated and considered in route dose calculations. The solar modulation parameter for each month in 2017 was determined based on the reconstruction of the modulation potential reported by Usoskin et al. (2017) and the neutron monitor counting rates of Oulu Cosmic Ray Station (2018). The derived values were found to vary within a small range of 451–511 MV that is close to solar minimum conditions, this will yield dose estimates approaching the maximum values in terms of solar modulation effects.
these values were then adopted as representative and used in correlation analyses. 3. Results and discussion 3.1. Route dose distribution On the basis of the collected flight tracking data, the right-hand side of Fig. 1 presents the estimated route doses of 340 outbound EVA52 flights and 340 inbound EVA51 flights in two separate histograms, which show the number of flights in a series of dose intervals and give a sense of the route dose distributions. For the outbound flight from Taipei to Houston, the route doses of 340 flights ranged from 37.8 to 71.7 μSv due to the variation in daily flight routes. The mean value was estimated to be 54.6 μSv with a standard deviation of 7.8 μSv. For the return flight from Houston to Taipei, the 340 flights exhibited a broader range of route doses from 37.1 to 83.1 μSv with a mean value of 64.4 and the associated standard deviation of 7.8 μSv. The mean route dose of return flights was approximately 18% higher than that of outbound flights because of relatively longer flight time. The average flight time of 340 outbound flights was calculated to be 787 ± 25 min. By contrast, the average flight time of 340 return flights was 934 ± 36 min, approximately 19% longer than that of outbound flights, proportional to the increase of the mean route dose. Adding two dose results together leads to a best estimate of the effective dose of 119.0 ± 11.0 μSv received on board an aircraft for a round-trip Taipei-Houston flight in 2017. In addition of actual flight routes, the thick red line in Fig. 1 depicts the great-circle path between Taipei and Houston for comparison. Under the same conditions of average flying altitude and speed, the great-circle route doses flying between Taipei and Houston were estimated to be 59.6 and 68.8 μSv for the outbound and return flights, respectively. Compared with the mean values estimated based on actual flight routes, the great-circle route doses appeared conservative with a margin of 7% to 9%. The term conservative here means that an analysis based on the great-circle approximation tends to overestimate the actual value of the effective dose for the purpose of crew radiation protection. For the same great-circle path, the route dose flying from Houston back to Taipei was observed approximately 15% higher than that flying from Taipei to Houston. The difference was primarily due to the different settings of flying speed in outbound and return flights in order to reflect their respective flight times as mentioned in the previous paragraph. By summing the results of outbound and return flights, the great-circle approximation predicted a round-trip dose value of 128.4 μSv, approximately 8% higher than that derived from actual fight routes. Publicly accessible literature and numerical models related to aviation dose assessment is abundant. For example, the EPCARD program (Mares et al., 2009), which was developed according to the results of extensive FLUKA simulations, is being used for routine dose assessment of aircraft crew by many European airline companies. Mishev and Usoskin (2015) also proposed a numerical model for dose assessment of cosmic rays at commercial aircraft altitudes. For the purpose of comparison, both EPCARD and Mishev’s model were employed to estimate the great-circle route doses flying between Taipei and Houston. The round-trip effective dose estimated by the EPCARD online1 was 132 μSv, very close to the aforementioned result of 128.4 μSv. Another estimate of 108 μSv for a round-trip Taipei-Houston flight was obtained through interpolations from the dose rate curves reported in the paper of Mishev and Usoskin (2015). The difference, approximately 16% lower than that estimated by our dose calculator, was considered to be
2.3. Pearson correlation coefficient and scatterplot matrix Pearson correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. It is a measure of the strength of a possible linear association between two variables (Witte and Witte, 2017). It takes a range of values from -1 (perfect negative association) through 0 (no association) to +1 (perfect positive association). General guidelines to interpreting Pearson's correlation coefficient are: 0.1 < r < 0.3 small association; 0.3 < r < 0.5 medium association; and 0.5 < r < 1.0 large association. For a system involving multiple variables, a correlation coefficient table or matrix can be generated to explore how these variables relate to each other by calculating the strength of the linear relationships between each pair of participating variables. On the other hand, a scatterplot matrix (Witte and Witte, 2017), which is a collection of pairwise scatterplots arranged in a square grid, can help one visualize the correlations between each pair of variables. Both the correlation coefficient matrix and scatterplot matrix are symmetric about its diagonal; therefore, one can combine two matrixes into one to avoid redundancy. This study simulated 680 flights between Taipei and Houston in 2017 according to their flight tracking data, applying the NTHU Flight Dose Calculator to estimate the route dose associated with each individual flight. From the characteristics of secondary cosmic rays in the atmosphere, the most influential parameters affecting route dose evaluation are flight time, flying altitude, geomagnetic cutoff rigidity, and solar activity. Among these variables and the resulting route doses, a correlation coefficient matrix was established to quantify how they relate to each other. In addition, a scatterplot matrix was created to visualize pairwise distributions and dependencies. For each of 680 flights, the mean flying altitude and mean geomagnetic cutoff rigidity were calculated by averaging over the flight route under consideration;
1 An online version of EPCARD is available free of charge, but not certified. The calculated dose is only given roughly and is therefore not suitable for routine aviation personnel dose calculation!.
3
Radiation Physics and Chemistry 168 (2020) 108548
Z.-Y. Yang and R.-J. Sheu
Fig. 2. Route-by-route variations of flying altitudes, geomagnetic cutoff rigidities, and the resulting effective dose rates on aircrafts as function of flight time for (a) 340 EVA52 flights from Taipei to Houston in 2017 and (b) 340 EVA51 flights from Houston back to Taipei.
maximum effective dose rates during these flights in 2017 were at levels of approximately 9 μSv/h, occurred in the proximity of the geomagnetic north pole. The areas under these dose rate curves are the accumulated effective doses for individual flight routes. Summarizing these route doses yields the two dose histograms presented in Figs. 1(a) and (b) respectively for 340 outbound EVA52 flights and 340 inbound EVA51 flights.
caused by relatively smaller effective dose conversion coefficients in ICRP-116 (2010) in comparison with ICRP-74 (1996) for neutrons and protons. 3.2. Flight route variation To help visualize the flight route effect on the estimated effective doses, Fig. 2 shows the route-by-route variations of flying altitudes, geomagnetic cutoff rigidities, and the resulting effective dose rates as function of flight time for all flights between Taipei and Houston in 2017. The thick red lines in the figure correspond to the values along the great-circle path. First, the mean flying altitude and duration for 340 outbound EVA52 flights were estimated to be 9.95 ± 0.16 km and 787 ± 25 min (Fig. 2a), respectively, and those for 340 inbound EVA51 flights were 9.87 ± 0.20 km and 934 ± 36 min (Fig. 2b), respectively. According to the flight times, the average flying speed of aircrafts with respect to the ground for outbound flights was calculated to be 1022 ± 59 km/h and that for return flights was at a relatively slow speed of 863 ± 46 km/h. Second, based on the latitudes and longitudes of waypoints along each flight route, the second row of Fig. 2 shows their corresponding geomagnetic cutoff rigidities as a function of flight time. The cutoff rigidity is a crucial factor affecting the cosmicray induced dose rates in planes. The lower the cutoff rigidities, the higher the estimated dose rates. For a long-haul flight between Taipei and Houston, the geomagnetic cutoff rigidities vary significantly, from low to high ranging from zero to 15 GV. Most of the cutoff rigidity curves following actual flight routes were observed higher than that along the great-circle path, in particular for those outbound EVA52 flights. This is why the great-circle route doses tend to be conservative when compared with the mean route doses estimated from actual flight data, as reported in the previous section. The last row of Fig. 2 shows the estimated dose rate profiles of 340 outbound EVA52 flights and 340 inbound EVA51 flight. These profiles largely reflect the influence of flight altitude and geomagnetic shielding. To a large extent, the dose rate profiles at flight altitudes vary inversely with the profiles of geomagnetic cutoff rigidities. The
3.3. Correlation analysis This study performed a correlation analysis on the estimated route doses of 680 flights between Taipei and Houston to explore how four influencing factors (flight time, altitude, geomagnetic cutoff rigidity, and solar modulation parameter) and the resulting route doses relate to each other. The duration of each flight is obvious as part of the flight tracking data. For each flight, a representative flight altitude and a representative geomagnetic cutoff rigidity were used in the correlation analysis, they were obtained by averaging the values along the flight route under consideration. The solar modulation parameter of each flight was determined by the month the flight was flown. The analysis results are summarized in Fig. 3, where the correlation coefficients indicate the strength of the linear relationships between each pair of variables. The 5×5 correlation coefficient matrix is apparently a symmetric matrix with all diagonal elements equal to one; therefore, Fig. 3 combines the correlation coefficient matrix and the corresponding scatterplots to help visualize pairwise data distributions and dependencies. Note that the diagonal elements of the matrix have been replaced by the histograms of individual variables, showing the respective distributions of flight times, altitudes, cutoff rigidities, solar modulation parameters, and the estimated route doses of 680 flights. The scatterplots in the first column of Fig. 3 essentially show patterns of two clusters because of the difference in flight time between outbound and return flights, and the scatterplots involving the solar modulation parameter exhibit discretized horizontal or vertical lines because only twelve discrete values of the solar modulation parameter were assigned to all the flights in 2017 (January to December). Among 4
Radiation Physics and Chemistry 168 (2020) 108548
Z.-Y. Yang and R.-J. Sheu
Fig. 3. A combined matrix of correlation coefficients and scatterplots between four influential parameters (flight time, altitude, geomagnetic cutoff rigidity, and solar activity) and the estimated route doses for 680 flights between Taipei and Houston in 2017. The diagonal elements of the matrix are the histograms of individual variables.
various pairs of variables, the results in Fig. 3 indicate only two meaningful correlations: a strong negative correlation (r = 0.87 ) between the geomagnetic cutoff rigidity and route dose, and a moderate positive correlation (r = 0.62 ) between the flight time and route dose. However, the effects of flying altitude and solar modulation on the estimated route doses in this case were found insignificant with almost zero correlation coefficients because values of the two parameters were limited in rather small ranges. For flights with the same destination and operated by the same type of aircraft (Boeing 777-300 ER), the flying altitudes of 680 flight routes formed a narrow Gaussian distribution with mean 9.91 km and standard deviation 0.18 km, as shown in Fig. 3. Meanwhile, the solar modulation parameters only varied within 451 to 511 MV because all these flights were flown in the same year of 2017. Apparently, if we can have flight tracking data covering short-, medium-, and long-haul flights from various airlines in different years, this correlation analysis will be more meaningful and capture more insights about the variability and relationship of route doses with influential parameters. Considering the time and resources needed to collect more comprehensive data, this is left as a topic for future studies.
predicted a round-trip dose value of 128.4 μSv, indicating that the great-circle path is appropriate and conservative to be used in evaluating cosmic radiation doses for this long-haul flight. According to a correlation analysis on the estimated route doses of 680 flights between Taipei and Houston, this study summarizes the results in a 5×5 mixed matrix showing the correlation coefficients of pairwise variables together with their corresponding scatterplots. The matrix quantifies and illustrates how the flight time, altitude, geomagnetic cutoff rigidity, solar modulation parameter, and the resulting route doses relate to each other in this long-haul flight. The present study highlights the tool and approach used in assessing cosmic radiation exposure during air transportation, and suggests future research to include flight data spanning various years and covering a wide range of routes in correlation analysis. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References
4. Conclusions
Badhwar, G.D., O'Neill, P.M., 1996. Galactic cosmic radiation model and its applications. Adv. Space Res. 17, 7–17. Bottollier-Depois, J.F., Beck, P., Latocha, M., Mares, V., Matthiä, D., Rühm, W., Wissmann, F., 2012. Comparison of Codes Assessing Radiation Exposure of Aircraft Crew Due to Galactic Cosmic Radiation. EURADOS Report 2012-03, Braunschweig, Germany. Ferrari, A., Sala, P.R., Fassò, A., Ranft, J., 2005. FLUKA: a Multi-Particle Transport Code. CERN-2005-10, INFN/TC_05/11, SLAC-R-773. Finlay, C.C., Maus, S., Beggan, C.D., Bondar, T.N., Chambodut, A., Chernova, T.A., Chulliat, A., Golovkov, V.P., Hamilton, B., Hamoudi, M., Holme, R., Hulot, G., Kuang, W., Langlais, B., Lesur, V., Lowes, F.J., Lühr, H., Macmillan, S., Mandea, M., McLean, S., Manoj, C., Menvielle, M., Michaelis, I., Olsen, N., Rauberg, J., Rother, M., Sabaka, T.J., Tangborn, A., Tøffner-Clausen, L., Thébault, E., Thomson, A.W.P., Wardinski, I., Wei, Z., Zvereva, T.I., 2010. International geomagnetic reference field: the eleventh generation. Geophys. J. Int. 183, 1216–1230. FlightAware Flight tracker/Flight status/Flight tracking. website. https://flightaware.com/. International Commission on Radiological Protection (ICRP), 1996. Conversion coefficients for use in radiological protection against external radiation. ICRP Publication
The longest distance non-stop flight from Taiwan is EVA Airways’ daily flights between Taipei and Houston. Among all commercial flights from and to Taiwan, this is the flight route exposes one to the maximum amount of cosmic radiation. Focusing on this route, the tracking data of 680 flights flown in 2017 was collected, half outbound and half return flights. These actual flight routes were analyzed by using the NTHU Flight Dose Calculator to estimate individual route doses caused by galactic cosmic rays. Two dose histograms for outbound and return flights were constructed to quantify the changes in the estimated route doses as a result of flight route variation. Accordingly, the best estimate of the effective dose received on board an aircraft flying from Taipei to Houston in 2017 was 54.6 ± 7.8 μSv and that of the return trip was 64.4 ± 7.8 μSv, which amounted to 119.0 ± 11.0 μSv for a round-trip flight. As an alternative approach, the great-circle approximation 5
Radiation Physics and Chemistry 168 (2020) 108548
Z.-Y. Yang and R.-J. Sheu 74. Ann. ICRP 26 (3–4). International Commission on Radiological Protection (ICRP), 2010. Conversion coefficients for radiological protection quantities for external radiation exposures. ICRP Publication 116. Ann. ICRP 40 (2–5). International Commission on Radiological Protection (ICRP), 2016. Radiological Protection from Cosmic Radiation in Aviation, vol. 132 ICRP Publication. Mares, V., Maczka, T., Leuthold, G., Rühm, W., 2009. Air crew dosimetry with a new version of EPCARD. Radiat. Prot. Dosim. 136, 262–266. Mishev, A., Usoskin, I., 2015. Numerical model for computation of effective and ambient dose equivalent at flight altitudes. J. Space Weather Space Clim. 5, A10. Oulu Cosmic Ray Station http://cosmicrays.oulu.fi/. Roesler, S., Heinrich, W., Schraube, H., 2002. Monte Carlo calculation of the radiation field at aircraft altitudes. Radiat. Prot. Dosim. 98, 367–388. Smart, D.F., Shea, M.A., 1997. World grid of calculated cosmic ray vertical cutoff
rigidities for epoch 1990. In: 25th International Cosmic Ray Conference, Conference Papers, vol. 2. pp. 401–404. Particle Data GroupTanabashi, M., et al., 2019. The review of particle physics: 29. Cosmic rays. Phys. Rev. D 98, 030001 (2018) and 2019 update. Usoskin, I.G., Gil, A., Kovaltsov, G.A., Mishev, A.L., Mikhailov, V.V., 2017. Heliospheric modulation of cosmic rays during the neutron monitor era: calibration using PAMELA data for 2006-2010. J. Geophys. Res. Space Phys. 122, 3875–3887. Witte, R.S., Witte, J.S., 2017. Statistics, eleventh ed. Wiley, New Jersey. Yang, Z.Y., Sheu, R.J., 2019. Effects of flight route variation and great-circle approximation on aviation dose assessment for popular flights from Taiwan. Radiat. Prot. Dosim. 184, 79–89. Yang, Z.Y., Lai, P.C., Sheu, R.J., 2019. Update and new features of NTHU Flight Dose Calculator: a tool for estimating aviation route doses and cumulative spectra of cosmic rays in atmosphere. IEEE Trans. Nucl. Sci. 66, 1931–1941.
6
Contents lists available at ScienceDirect
Radiation Physics and Chemistry journal homepage: www.elsevier.com/locate/radphyschem
An in-depth analysis of aviation route doses for the longest distance flight from Taiwan
T
Zi-Yi Yanga, Rong-Jiun Sheua,b,∗ a b
Institute of Nuclear Engineering and Science, National Tsing Hua University, 101, Sec. 2, Kuang-Fu Road, Hsinchu, Taiwan Department of Engineering and System Science, National Tsing Hua University, 101, Sec. 2, Kuang-Fu Road, Hsinchu, Taiwan
ARTICLE INFO
ABSTRACT
Keywords: Galactic cosmic rays Aviation route dose Flight route variation Great-circle approximation Correlation coefficients
This study investigated effective doses received on board an aircraft for the direct flight between Taipei and Houston, which is the longest distance flight from Taiwan with a flying distance of more than 13,000 km that takes approximately 13 h outbound and approximately 16 h inbound. Instead of choosing one representative flight, all 680 flights operated in 2017 were systematically analyzed by using a self-developed flight dose calculator, with an emphasis on effects of flight route variation and great-circle approximation. The average effective dose of 340 flights from Taipei to Houston was estimated to be 54.6 ± 7.8 μSv and that of 340 flights from Houston back to Taipei was estimated to be 64.4 ± 7.8 μSv, leading to a best dose estimate of 119.0 ± 11.0 μSv for a round-trip flight. The standard deviation associated with the mean value was approximately 10%, which offered a quantification of how daily flight routes may affect the resulting doses. As an alternative approach, the great-circle approximation predicted a round-trip dose value of 128.4 μSv, approximately 8% higher than that derived from actual fight routes. In addition, dose relationships of these flight routes with parameters including flight time, altitude, geomagnetic cutoff rigidity, and solar activity were identified using correlation coefficients and scatterplots.
1. Introduction Galactic cosmic rays, composed primarily of high-energy protons and heavier nuclei originating outside the Solar System, interact with the Earth’s atmosphere and produce cascade showers of secondary particles (Tanabashi et al., 2019). Radiation field at flight altitudes is a complex mixture of charged and neutral particles of various types and energies. The intensities, angular and energy distributions of primary and secondary particles in the atmosphere vary and depend on various solar, interplanetary, and geophysical conditions. Cosmic-ray induced radiation doses received on board an aircraft are substantially higher than those on the ground because of reduced protection of the atmosphere. Aircrew and frequent flyers are therefore exposed to elevated radiation levels from cosmic radiation on every flight, in particular for those flights with long distances, high altitudes, across polar regions, and under solar minimum conditions (ICRP, 2016). At present, the longest non-stop flight from Taiwan flies between Taipei and Houston, operated daily by EVA Airways with a flying distance of more than 13,000 km that takes approximately 13 h outbound from Taipei to Houston (flying from west to east) and approximately 16 h return from Houston to Taipei (flying from east to west). This flight
∗
is among the 25 longest flights in the world. In 2017, a total of 680 flights between Taipei and Houston were actually flown, including 340 outbound flights (flight number EVA52) and 340 inbound flights (flight number EVA51). Instead of choosing one or a few flight routes as representative, this study collected tracking data of all these flights, calculated individual route doses, and performed an in-depth analysis of these results to investigate the effect of flight route variation and check the appropriateness of great-circle approximation. In addition, for all outbound and inbound flights, correlation coefficients between influential parameters and the resulting route doses were calculated and discussed. The results provide a quantitative description and graphic demonstration of how the flight time, altitude, geomagnetic cutoff rigidity, and solar modulation affect the route dose calculations for this long-haul flight. The tool and approach used in this study can be useful for those who are interested in related topics and analyses. 2. Materials and methods 2.1. Route dose calculation High-energy cosmic rays penetrate into the atmosphere and induce
Corresponding author. Institute of Nuclear Engineering and Science, National Tsing Hua University, 101, Sec. 2, Kuang-Fu Road, Hsinchu, Taiwan. E-mail address: [email protected] (R.-J. Sheu).
https://doi.org/10.1016/j.radphyschem.2019.108548 Received 28 July 2019; Received in revised form 3 October 2019; Accepted 27 October 2019 Available online 31 October 2019 0969-806X/ © 2019 Elsevier Ltd. All rights reserved.
Radiation Physics and Chemistry 168 (2020) 108548
Z.-Y. Yang and R.-J. Sheu
Fig. 1. Flying trajectories and the route dose histograms for (a) 340 EVA52 flights from Taipei to Houston in 2017 and (b) 340 EVA51 flights from Houston back to Taipei.
parameters of the fitted sigmoid function. By observing the data dependencies, these interpolations are considered as reasonable approximations for flight dose estimation. Compared with the result of a direct simulation, the combined level of uncertainty resulting from interpolations of altitude, cutoff rigidity, and solar modulation parameter was estimated no more than 10%. The validity of the dose calculator (including the underlying database) has been demonstrated by comparing its predictions with the anonymous results of eleven similar codes summarized in EURADOS Report 2012–03 (Bottollier-Depois, 2012). For the selected 23 flight routes in the report, the route doses provided by our dose calculator show consistent and satisfactory agreement (within ~20%) with the median values of the predictions of other codes (Yang et al., 2019). After starting, the NTHU Flight Dose Calculator shows up an integrated interface with five main tabs for different application categories: User Specified, Orthodrome, Location, Personnel Dose, and Database. Two distinct features pertinent to this study are briefly described below. First, the dose calculator enables the user to perform automatic batch analysis of multiple flights, which is handy for the purpose of this study because 680 individual flights have to be analyzed. Second, the dose calculator by default can be run with a greatcircle path as an approximation to actual flight routes between airports. The flying altitude and speed of the aircraft along the great-circle path have default values but can be edited as desired. This function facilitates the comparison of route doses calculated according to an actual flight path and using great-circle approximation.
complicated hadron-electromagnetic-muon cascades, producing a large number of secondary particles, including neutrons, protons, muons, electrons, positrons, photons, pions, and heavy ions. Although time consuming, Monte Carlo simulations are generally the most accurate and suitable approach to determine and characterize the complex radiation field at flight altitudes (Roesler et al., 2002). The self-developed NTHU Flight Dose Calculator was used in this study for assessing exposure to galactic cosmic radiation during long-haul flights (Yang et al., 2019). The dose calculator is a graphical user interface program with a comprehensive database that describes and characterizes the radiation field in the atmosphere from the sea level up to 70 km of altitude. The database was generated based on a series of FLUKA Monte Carlo simulations of atmospheric showers caused by galactic cosmic rays (Ferrari et al., 2005). The ion composition of the galactic flux in the FLUKA simulations was derived from the Badhwar-O’Neill (1996) model, which considered all elemental groups from Z = 1 to Z = 28. The geomagnetic field was considered in two stages of the FLUKA simulation: 1) The geomagnetic cutoff was used to modulate the primary spectrum at the top of the atmosphere; 2) The local geomagnetic field was considered during shower development in the atmosphere. The geomagnetic cutoff rigidities of various locations and epochs were adopted from various literature sources, including Smart and Shea (1997) and Finlay et al. (2010). The resulting database comprises information about energy spectra and effective dose rates of various radiation components (neutrons, protons, muons, electrons, positrons, photons, pions, and heavy ions) in the global atmosphere calculated at two solar modulation parameters (φ=465 and 1440 MV). The effective dose rates were evaluated based on the FLUKA built-in fluence-to-dose conversion coefficients mainly from ICRP-74 (1996). The terms of dose and dose rate hereinafter are considered to be effective dose and effective dose rate without further explanation. In parallel with the database, the NTHU Flight Dose Calculator was developed to estimate the effective dose and energy spectra of various particles accumulated along a given flight route (actual or great-circle route) by performing a series of interpolations and summations. The altitude and solar modulation parameter have simple linear interpolations, and the interpolations of cutoff rigidity are based on the stored
2.2. Flight route information The flight tracking data of 680 EVA flights between Taipei and Houston operated in 2017 was purchased from the website FlightAware (2018). The file downloaded from the website is a comma-separated values file that is suitable for storing tabular data in plain text. Each line of the file is a data record corresponding to a waypoint during a flight. Each record has several fields or columns separated by commas. Only four columns in the file are necessary for dose calculations: timestamp, latitude, longitude, and altitude that collectively pinpoint the route 2
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taken by the aircraft. For a single flight, the user can easily process the data and import it into the NTHU Flight Dose Calculator immediately for route dose evaluation. For multiple flights in a file, which is typical for data downloaded from FlightAware, the dose calculator comes with auxiliary Python scripts developed for supporting users in automatic batch processing and data post-processing (Yang and Sheu, 2019). The left-hand side of Fig. 1 shows the flying trajectories of 340 outbound EVA52 flights and 340 inbound EVA51 flights on the world map for easy visualization. Evidently, each flight was flying a particular route because weather and aircraft conditions at that time affected the route and altitude taken by the aircraft regardless of the original flight plan. For a long-haul flight such as the one considered here, the greatcircle path is usually a good approximation to actual flight routes in aviation dose assessment because the great-circle path is the most efficient way to get the aircraft from one airport to another on the Earth’s surface. The default flying altitude and cruising speed were set to 11,000 km and 900 km/h, respectively, in the NTHU Flight Dose Calculator. The two parameters were adjusted in this study to achieve a fair comparison with the results based on actual flight routes. According to the actual flight tracking data, the average flying altitude and speed were first estimated and then used in the program to estimate the greatcircle route doses. The solar wind modulates the flux of galactic cosmic rays reaching the top of the Earth’s atmosphere. Although the changes in solar modulation of the cosmic-ray flux within a year are small when compared with the 11-year solar cycle, the mean monthly values of the solar modulation parameters for the year 2017 were calculated and considered in route dose calculations. The solar modulation parameter for each month in 2017 was determined based on the reconstruction of the modulation potential reported by Usoskin et al. (2017) and the neutron monitor counting rates of Oulu Cosmic Ray Station (2018). The derived values were found to vary within a small range of 451–511 MV that is close to solar minimum conditions, this will yield dose estimates approaching the maximum values in terms of solar modulation effects.
these values were then adopted as representative and used in correlation analyses. 3. Results and discussion 3.1. Route dose distribution On the basis of the collected flight tracking data, the right-hand side of Fig. 1 presents the estimated route doses of 340 outbound EVA52 flights and 340 inbound EVA51 flights in two separate histograms, which show the number of flights in a series of dose intervals and give a sense of the route dose distributions. For the outbound flight from Taipei to Houston, the route doses of 340 flights ranged from 37.8 to 71.7 μSv due to the variation in daily flight routes. The mean value was estimated to be 54.6 μSv with a standard deviation of 7.8 μSv. For the return flight from Houston to Taipei, the 340 flights exhibited a broader range of route doses from 37.1 to 83.1 μSv with a mean value of 64.4 and the associated standard deviation of 7.8 μSv. The mean route dose of return flights was approximately 18% higher than that of outbound flights because of relatively longer flight time. The average flight time of 340 outbound flights was calculated to be 787 ± 25 min. By contrast, the average flight time of 340 return flights was 934 ± 36 min, approximately 19% longer than that of outbound flights, proportional to the increase of the mean route dose. Adding two dose results together leads to a best estimate of the effective dose of 119.0 ± 11.0 μSv received on board an aircraft for a round-trip Taipei-Houston flight in 2017. In addition of actual flight routes, the thick red line in Fig. 1 depicts the great-circle path between Taipei and Houston for comparison. Under the same conditions of average flying altitude and speed, the great-circle route doses flying between Taipei and Houston were estimated to be 59.6 and 68.8 μSv for the outbound and return flights, respectively. Compared with the mean values estimated based on actual flight routes, the great-circle route doses appeared conservative with a margin of 7% to 9%. The term conservative here means that an analysis based on the great-circle approximation tends to overestimate the actual value of the effective dose for the purpose of crew radiation protection. For the same great-circle path, the route dose flying from Houston back to Taipei was observed approximately 15% higher than that flying from Taipei to Houston. The difference was primarily due to the different settings of flying speed in outbound and return flights in order to reflect their respective flight times as mentioned in the previous paragraph. By summing the results of outbound and return flights, the great-circle approximation predicted a round-trip dose value of 128.4 μSv, approximately 8% higher than that derived from actual fight routes. Publicly accessible literature and numerical models related to aviation dose assessment is abundant. For example, the EPCARD program (Mares et al., 2009), which was developed according to the results of extensive FLUKA simulations, is being used for routine dose assessment of aircraft crew by many European airline companies. Mishev and Usoskin (2015) also proposed a numerical model for dose assessment of cosmic rays at commercial aircraft altitudes. For the purpose of comparison, both EPCARD and Mishev’s model were employed to estimate the great-circle route doses flying between Taipei and Houston. The round-trip effective dose estimated by the EPCARD online1 was 132 μSv, very close to the aforementioned result of 128.4 μSv. Another estimate of 108 μSv for a round-trip Taipei-Houston flight was obtained through interpolations from the dose rate curves reported in the paper of Mishev and Usoskin (2015). The difference, approximately 16% lower than that estimated by our dose calculator, was considered to be
2.3. Pearson correlation coefficient and scatterplot matrix Pearson correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. It is a measure of the strength of a possible linear association between two variables (Witte and Witte, 2017). It takes a range of values from -1 (perfect negative association) through 0 (no association) to +1 (perfect positive association). General guidelines to interpreting Pearson's correlation coefficient are: 0.1 < r < 0.3 small association; 0.3 < r < 0.5 medium association; and 0.5 < r < 1.0 large association. For a system involving multiple variables, a correlation coefficient table or matrix can be generated to explore how these variables relate to each other by calculating the strength of the linear relationships between each pair of participating variables. On the other hand, a scatterplot matrix (Witte and Witte, 2017), which is a collection of pairwise scatterplots arranged in a square grid, can help one visualize the correlations between each pair of variables. Both the correlation coefficient matrix and scatterplot matrix are symmetric about its diagonal; therefore, one can combine two matrixes into one to avoid redundancy. This study simulated 680 flights between Taipei and Houston in 2017 according to their flight tracking data, applying the NTHU Flight Dose Calculator to estimate the route dose associated with each individual flight. From the characteristics of secondary cosmic rays in the atmosphere, the most influential parameters affecting route dose evaluation are flight time, flying altitude, geomagnetic cutoff rigidity, and solar activity. Among these variables and the resulting route doses, a correlation coefficient matrix was established to quantify how they relate to each other. In addition, a scatterplot matrix was created to visualize pairwise distributions and dependencies. For each of 680 flights, the mean flying altitude and mean geomagnetic cutoff rigidity were calculated by averaging over the flight route under consideration;
1 An online version of EPCARD is available free of charge, but not certified. The calculated dose is only given roughly and is therefore not suitable for routine aviation personnel dose calculation!.
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Fig. 2. Route-by-route variations of flying altitudes, geomagnetic cutoff rigidities, and the resulting effective dose rates on aircrafts as function of flight time for (a) 340 EVA52 flights from Taipei to Houston in 2017 and (b) 340 EVA51 flights from Houston back to Taipei.
maximum effective dose rates during these flights in 2017 were at levels of approximately 9 μSv/h, occurred in the proximity of the geomagnetic north pole. The areas under these dose rate curves are the accumulated effective doses for individual flight routes. Summarizing these route doses yields the two dose histograms presented in Figs. 1(a) and (b) respectively for 340 outbound EVA52 flights and 340 inbound EVA51 flights.
caused by relatively smaller effective dose conversion coefficients in ICRP-116 (2010) in comparison with ICRP-74 (1996) for neutrons and protons. 3.2. Flight route variation To help visualize the flight route effect on the estimated effective doses, Fig. 2 shows the route-by-route variations of flying altitudes, geomagnetic cutoff rigidities, and the resulting effective dose rates as function of flight time for all flights between Taipei and Houston in 2017. The thick red lines in the figure correspond to the values along the great-circle path. First, the mean flying altitude and duration for 340 outbound EVA52 flights were estimated to be 9.95 ± 0.16 km and 787 ± 25 min (Fig. 2a), respectively, and those for 340 inbound EVA51 flights were 9.87 ± 0.20 km and 934 ± 36 min (Fig. 2b), respectively. According to the flight times, the average flying speed of aircrafts with respect to the ground for outbound flights was calculated to be 1022 ± 59 km/h and that for return flights was at a relatively slow speed of 863 ± 46 km/h. Second, based on the latitudes and longitudes of waypoints along each flight route, the second row of Fig. 2 shows their corresponding geomagnetic cutoff rigidities as a function of flight time. The cutoff rigidity is a crucial factor affecting the cosmicray induced dose rates in planes. The lower the cutoff rigidities, the higher the estimated dose rates. For a long-haul flight between Taipei and Houston, the geomagnetic cutoff rigidities vary significantly, from low to high ranging from zero to 15 GV. Most of the cutoff rigidity curves following actual flight routes were observed higher than that along the great-circle path, in particular for those outbound EVA52 flights. This is why the great-circle route doses tend to be conservative when compared with the mean route doses estimated from actual flight data, as reported in the previous section. The last row of Fig. 2 shows the estimated dose rate profiles of 340 outbound EVA52 flights and 340 inbound EVA51 flight. These profiles largely reflect the influence of flight altitude and geomagnetic shielding. To a large extent, the dose rate profiles at flight altitudes vary inversely with the profiles of geomagnetic cutoff rigidities. The
3.3. Correlation analysis This study performed a correlation analysis on the estimated route doses of 680 flights between Taipei and Houston to explore how four influencing factors (flight time, altitude, geomagnetic cutoff rigidity, and solar modulation parameter) and the resulting route doses relate to each other. The duration of each flight is obvious as part of the flight tracking data. For each flight, a representative flight altitude and a representative geomagnetic cutoff rigidity were used in the correlation analysis, they were obtained by averaging the values along the flight route under consideration. The solar modulation parameter of each flight was determined by the month the flight was flown. The analysis results are summarized in Fig. 3, where the correlation coefficients indicate the strength of the linear relationships between each pair of variables. The 5×5 correlation coefficient matrix is apparently a symmetric matrix with all diagonal elements equal to one; therefore, Fig. 3 combines the correlation coefficient matrix and the corresponding scatterplots to help visualize pairwise data distributions and dependencies. Note that the diagonal elements of the matrix have been replaced by the histograms of individual variables, showing the respective distributions of flight times, altitudes, cutoff rigidities, solar modulation parameters, and the estimated route doses of 680 flights. The scatterplots in the first column of Fig. 3 essentially show patterns of two clusters because of the difference in flight time between outbound and return flights, and the scatterplots involving the solar modulation parameter exhibit discretized horizontal or vertical lines because only twelve discrete values of the solar modulation parameter were assigned to all the flights in 2017 (January to December). Among 4
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Fig. 3. A combined matrix of correlation coefficients and scatterplots between four influential parameters (flight time, altitude, geomagnetic cutoff rigidity, and solar activity) and the estimated route doses for 680 flights between Taipei and Houston in 2017. The diagonal elements of the matrix are the histograms of individual variables.
various pairs of variables, the results in Fig. 3 indicate only two meaningful correlations: a strong negative correlation (r = 0.87 ) between the geomagnetic cutoff rigidity and route dose, and a moderate positive correlation (r = 0.62 ) between the flight time and route dose. However, the effects of flying altitude and solar modulation on the estimated route doses in this case were found insignificant with almost zero correlation coefficients because values of the two parameters were limited in rather small ranges. For flights with the same destination and operated by the same type of aircraft (Boeing 777-300 ER), the flying altitudes of 680 flight routes formed a narrow Gaussian distribution with mean 9.91 km and standard deviation 0.18 km, as shown in Fig. 3. Meanwhile, the solar modulation parameters only varied within 451 to 511 MV because all these flights were flown in the same year of 2017. Apparently, if we can have flight tracking data covering short-, medium-, and long-haul flights from various airlines in different years, this correlation analysis will be more meaningful and capture more insights about the variability and relationship of route doses with influential parameters. Considering the time and resources needed to collect more comprehensive data, this is left as a topic for future studies.
predicted a round-trip dose value of 128.4 μSv, indicating that the great-circle path is appropriate and conservative to be used in evaluating cosmic radiation doses for this long-haul flight. According to a correlation analysis on the estimated route doses of 680 flights between Taipei and Houston, this study summarizes the results in a 5×5 mixed matrix showing the correlation coefficients of pairwise variables together with their corresponding scatterplots. The matrix quantifies and illustrates how the flight time, altitude, geomagnetic cutoff rigidity, solar modulation parameter, and the resulting route doses relate to each other in this long-haul flight. The present study highlights the tool and approach used in assessing cosmic radiation exposure during air transportation, and suggests future research to include flight data spanning various years and covering a wide range of routes in correlation analysis. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References
4. Conclusions
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The longest distance non-stop flight from Taiwan is EVA Airways’ daily flights between Taipei and Houston. Among all commercial flights from and to Taiwan, this is the flight route exposes one to the maximum amount of cosmic radiation. Focusing on this route, the tracking data of 680 flights flown in 2017 was collected, half outbound and half return flights. These actual flight routes were analyzed by using the NTHU Flight Dose Calculator to estimate individual route doses caused by galactic cosmic rays. Two dose histograms for outbound and return flights were constructed to quantify the changes in the estimated route doses as a result of flight route variation. Accordingly, the best estimate of the effective dose received on board an aircraft flying from Taipei to Houston in 2017 was 54.6 ± 7.8 μSv and that of the return trip was 64.4 ± 7.8 μSv, which amounted to 119.0 ± 11.0 μSv for a round-trip flight. As an alternative approach, the great-circle approximation 5
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