Analysis of the Seasonal Variation of CO2 Concentration in China Based on GOSAT Satellite Data

2018 ◽  
Vol 46 (10) ◽  
pp. 1667-1675 ◽  
Author(s):  
Lanlan Zhang ◽  
Jinye Zhang
Keyword(s):  
Seasonal Variation ◽  
Satellite Data ◽  
Co2 Concentration ◽  
Gosat Satellite

scholarly journals Seasonal Variation Analysis Method of GHG at Municipal Solid Waste Incinerator

2020 ◽  
Vol 12 (18) ◽  
pp. 7425
Author(s):  
Seongmin Kang ◽  
Joonyoung Roh ◽  
Eui-chan Jeon
Keyword(s):  
Seasonal Variation ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Ghg Emissions ◽  
Co2 Concentration ◽  
Waste Incineration ◽  
Seasonal Effect ◽  
Waste Incinerator ◽  
Waste Composition

The greenhouse gas emissions of the waste incineration sector account for approximately 43% of the total GHG emissions and represent the majority of the CO2 emissions from waste in Korea. Improving the reliability of the GHG inventory of the waste incineration sector is an important aspect for the examination of global GHG emission management according to the Paris Agreement. In this study, we introduced a statistical approach to analyze seasonal changes through analysis of waste composition and CO2 concentration in Municipal Solid Waste incinerators and applied the methodology to one case study facility. The analysis results in the case study showed that there was no seasonal variation in waste composition and CO2 concentrations, except for wood. Wood is classified as biomass, and the GHG emissions caused by biomass incineration are reported separately, indicating that the effect of an MSW incinerator on GHG emissions is not significant. Therefore, the seasonal effect of CO2 concentration or waste composition may not be an impact when calculating GHG emissions from case study facilities’ MSW incinerators. This study proposed an approach for analyzing factors that affect the GHG inventory reliability by analyzing seasonal characteristics and variation through the statistical analysis, which are used for the calculation of the GHG emissions of an MSW incinerator.

scholarly journals Comparisons of CH<sub>4</sub> ground-based FTIR measurements near Saint Petersburg with GOSAT observations

2014 ◽  
Vol 7 (4) ◽  
pp. 1003-1010 ◽  
Author(s):  
N. M. Gavrilov ◽  
M. V. Makarova ◽  
A. V. Poberovskii ◽  
Yu. M. Timofeyev
Keyword(s):  
Fourier Transform ◽  
Greenhouse Gases ◽  
Satellite Data ◽  
Fourier Transform Infrared ◽  
Similar Data ◽  
Saint Petersburg ◽  
Spectroscopic Observations ◽  
Atmospheric Column ◽  
Standard Deviations ◽  
Gosat Satellite

Abstract. Atmospheric column-average methane mole fractions measured with ground-based Fourier-transform spectroscopy near Saint Petersburg, Russia (59.9° N, 29.8° E, 20 m a.s.l.) are compared with similar data obtained with the Japanese GOSAT (Greenhouse gases Observing SATellite) in the years 2009–2012. Average CH4 mole fractions for the GOSAT data version V01.xx are −15.0 ± 5.4 ppb less than the corresponding values obtained from ground-based measurements (with the standard deviations of biases at 13.0 ± 4.2 ppb). For the GOSAT data version V02.xx, the average values of the differences are −1.9 ± 1.8 ppb with standard deviations of 14.5 ± 1.3 ppb. This verifies that FTIR (Fourier transform infrared) spectroscopic observations near Saint Petersburg have similar biases with GOSAT satellite data as FTIR measurements at other ground-based networks and aircraft CH4 estimations.

Seasonal variation in particle contribution and aerosol types in Shanghai based on satellite data from MODIS and CALIOP

Particuology ◽  
2020 ◽  
Vol 51 ◽  
pp. 18-25 ◽  
Author(s):  
Qiong Liu ◽  
Xin Liu ◽  
Tongqiang Liu ◽  
Yanming Kang ◽  
Yonghang Chen ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Satellite Data ◽  
Aerosol Types

scholarly journals CO<sub>2</sub> column-averaged volume mixing ratio derived over Tsukuba from measurements by commercial airlines

2010 ◽  
Vol 10 (2) ◽  
pp. 3401-3421 ◽  
Author(s):  
M. Araki ◽  
I. Morino ◽  
T. Machida ◽  
Y. Sawa ◽  
H. Matsueda ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Observational Data ◽  
Meteorological Data ◽  
Co2 Concentration ◽  
Concentration Data ◽  
Climatological Data ◽  
Mixing Ratios ◽  
Least Squares Fit ◽  
Small Uncertainty ◽  
Using Data

Abstract. Column-averaged volume mixing ratios of carbon dioxide (XCO2) during the period from January 2007 to May 2008 over Tsukuba, Japan, were derived by using CO2 concentration data observed by Japan Airlines Corporation (JAL) commercial airliners, based on the assumption that CO2 profiles over Tsukuba and Narita were the same. CO2 profile data for 493 flights on clear-sky days were analysed in order to calculate XCO2 with an ancillary dataset: Tsukuba observational data (by rawinsonde and a meteorological tower) or global meteorological data (NCEP and CIRA-86). The amplitude of seasonal variation of XCO2 (Tsukuba observational) from the Tsukuba observational data was determined by least-squares fit using a harmonic function to roughly evaluate the seasonal variation over Tsukuba. The highest and lowest values of the obtained fitted curve in 2007 for XCO2 (Tsukuba observational) were 386.4 and 381.7 ppm in May and September, respectively. The dependence of XCO2 on the type of ancillary dataset was evaluated. The average difference between XCO2 (global) from global climatological data and XCO2 (Tsukuba observational), i.e., the bias of XCO2 (global) based on XCO2 (Tsukuba observational), was found to be -0.621 ppm with a standard deviation of 0.682 ppm. The uncertainty of XCO2 (global) based on XCO2 (Tsukuba observational) was estimated to be 0.922 ppm. This small uncertainty suggests that the present method of XCO2 calculation using data from airliners and global climatological data can be applied to the validation of GOSAT products for XCO2 over airports worldwide.

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