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7. Global Evaluation and Intercomparison of XCO 2 Retrievals from GOSAT, OCO-2, and TANSAT with TCCON.

Author

Fang, Junjun, Chen, Baozhang, Zhang, Huifang, Dilawar, Adil, Guo, Man, Liu, Chunlin, Liu, Shu'an, Gemechu, Tewekel Melese, and Zhang, Xingying

Subjects
STANDARD deviations, GOVERNMENT policy on climate change, CARBON dioxide, GREENHOUSE gases, MOLE fraction
Abstract

Accurate global monitoring of carbon dioxide (CO2) is essential for understanding climate change and informing policy decisions. This study compares column-averaged dry-air mole fractions of CO2 (XCO2) between ACOS_L2_Lite_FP V9r for Japan's Greenhouse Gases Observing Satellite (GOSAT), OCO-2_L2_Lite_FP V10r for the USA's Orbiting Carbon Observatory-2 (OCO-2), and IAPCAS V2.0 for China's Carbon Dioxide Observation Satellite (TANSAT) collectively referred to as GOT, with data from the Total Carbon Column Observing Network (TCCON). Our findings are as follows: (1) Significant data quantity differences exist between OCO-2 and the other satellites, with OCO-2 boasting a data volume 100 times greater. GOT shows the highest data volume between 30–45°N and 20–30°S, but data availability is notably lower near the equator. (2) XCO2 from GOT exhibits similar seasonal variations, with lower concentrations during June, July, and August (JJA) (402.72–403.74 ppm) and higher concentrations during December, January, and February (DJF) (405.74–407.14 ppm). XCO2 levels are higher in the Northern Hemisphere during March, April, and May (MAM) and DJF, while slightly lower during JJA and September, October, and November (SON). (3) The differences in XCO2 (ΔXCO2) reveal that ΔXCO2 between OCO-2 and TANSAT are minor (−0.47 ± 0.28 ppm), whereas the most significant difference is observed between GOSAT and TANSAT (−1.13 ± 0.15 ppm). Minimal differences are seen in SON (with the biggest difference between GOSAT and TANSAT: −0.84 ± 0.12 ppm), while notable differences occur in DJF (with the biggest difference between GOSAT and TANSAT: −1.43 ± 0.17 ppm). Regarding latitudinal variations, distinctions between OCO-2 and TANSAT are most pronounced in JJA and SON. (4) Compared to TCCON, XCO2 from GOT exhibits relatively high determination coefficients (R2 > 0.8), with GOSAT having the highest root mean square error (RMSE = 1.226 ppm, <1.5 ppm), indicating a strong relationship between ground-based observed and retrieved values. This research contributes significantly to our understanding of the spatial characteristics of global XCO2. Furthermore, it offers insights that can inform the analysis of differences in the inversion of carbon sources and sinks within assimilation systems when incorporating XCO2 data from satellite observations. [ABSTRACT FROM AUTHOR]

Published
2023
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10. Research of aircraft ground service scheduling problems

Author

Liu Shu'an and Tang Fei

Subjects
Engineering, 021103 operations research, Optimization problem, Job shop scheduling, Aviation, business.industry, Quality of service, Industrial production, 0211 other engineering and technologies, Scheduling (production processes), ComputerApplications_COMPUTERSINOTHERSYSTEMS, 02 engineering and technology, Aircraft ground handling, Automotive engineering, Transport engineering, Rush hour, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, business
Abstract

Due to the development of science and technology and the progress of the society, commercial service and daily travel of air transport is gradually increasing in industrial production. With the growing demand of the flight numbers and types and corresponding increasingly tense of aviation resources, the shortening of flight cycle and a drop in the quality of service at the airport need to be fixed rapidly. Aims to those problems, we studied the on time landing airport service vehicle optimization problem with the consideration service demand in a rush hour, to optimize the ground service vehicles resources via the establishment of a novel mathematical model. Through the experimental analysis and solution based on the actual flight data, we can see improvements on the effective scheduling of the ground service and ground vehicle.

Published
2016

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