کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8864282 | 1620301 | 2018 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Characterisation of methane variability and trends from near-infrared solar spectra over Hefei, China
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موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
علم هواشناسی
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چکیده انگلیسی
This study presents the characterization of XCH4 (averaged-column dry air mole fraction) variability and trends using the near-infrared (NIR) solar spectra recorded by the ground-based high-resolution Fourier transform spectrometer (FTS) over Hefei, China. An annual increase of 10.55 ± 2.87 ppb yrâ1 (0.56 ± 0.15% yrâ1) in CH4 concentrations was deduced from the three years' worth of FTS measurements. Seasonal cycles and three typical diurnal variation modes were captured. The maximum CH4 concentration occurred in late summer or early autumn, while the minimum CH4 concentration occurred in winter. CH4 concentrations in August were 30-55 ppb higher than those in January. In most cases, the diurnal variability exhibited an increasing trend in summer or early autumn, while it exhibited a decreasing trend or remained relatively constant in other seasons. We compared the FTS data with the GOSAT data and the GEOS-Chem model data. The average difference between the GOSAT and FTS data (GOSAT minus FTS) was 1.60 ppb (0.09%) ±13.0 ppb (0.70%), and between the smoothed GEOS-Chem model data and FTS data (GEOS-Chem minus FTS) was â8.09 ppb (0.45%) ±17.83 ppb (0.95%). The differences between GOSAT and FTS were season-independent; however, obvious season-dependent differences were observed between GEOS-Chem and FTS. The GOSAT and GEOS-Chem models could reproduce the seasonal cycle observed by FTS with correlation coefficients (r) of 0.77 and 0.86, respectively.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Atmospheric Environment - Volume 173, January 2018, Pages 198-209
Journal: Atmospheric Environment - Volume 173, January 2018, Pages 198-209
نویسندگان
Yuan Tian, Youwen Sun, Cheng Liu, Wei Wang, Changgong Shan, Xingwei Xu, Qihou Hu,