Remote sensing of the atmospheric greenhouse gases, methane (CH4) and carbon dioxide (CO2), contributes to the understanding of global warming and climate change. A portable ground-based instrument consisting of a commercially available desktop optical spectrum analyzer and a small sun tracker has been applied to measure the column densities of atmospheric CH4 and CO2 at Yanting observation station in a mountainous paddy field of the Sichuan Basin from September to November 2013. The column-averaged dry-air molar mixing ratios, XCH4/XCO2, are compared with those retrieved by satellite observations in the Sichuan Basin and by ground-based network observations in the same latitude zone as the Yanting observation station.
Satellite observations and model simulations are of two important data sources to study atmospheric carbon dioxide concentration. For analyzing and evaluating the bias correction method of ACOS dry-air column averaged CO2 (Xco2) product, the GEOS-Chem Xco2 simulations are selected according to observing time and locations of the ACOS product. The GEOS-Chem simulations of CO2 profiles are transformed to Xco2 data by convolving with satellite averaging kernels and pressure weighting functions. The GEOS-Chem Xco2 data are then compared with both bias uncorrected and bias corrected satellite retrievals of ACOS. The comparisons show that the bias uncorrected ACOS retrievals are on average 1.12ppm higher than the model Xco2 data, while the corrected ACOS retrievals are only on average 0.06ppm lower than the model Xco2 data. By assuming consistency between model Xco2 simulations and true atmospheric Xco2, this study indicates that the bias can be obvious decreased through the bias correction method, and the correction is effective and necessary for satellite Xco2 retrievals.
CO2 is one of the most important greenhouse gases due to its selective absorption of long wave radiation from the Earth’s surface. In this paper, we use the column average dry air mole fraction of CO2 (XCO2) data from the Japanese GOSAT satellite to conduct a comprehensive and systematic analysis of temporal and spatial distribution of XCO2. This includes: (1) analysis of seasonal change characteristics of XCO2 data; and (2) comparative analysis of the northern and southern hemispheres carbon dioxide concentration at different latitudes. The results show that (1) from 2010 to 2013, atmospheric XCO2 significantly increased each year. The southern hemisphere's annual averages of XCO2 from 2010 to 2012 were 385.2 ppm, 387.3 ppm, and 389.1 ppm, while the average annual values for the northern hemisphere from 2010 to 2012 were 387.8 ppm, 390.0 ppm, and 391.7 ppm. The annual XCO2 in northern and southern hemispheres exhibited growth rates of 1-2 ppm per year. (2) The results show seasonal change trends: winter months displayed higher XCO2. Regarding the global spatial distribution of XCO2, the results show that the total XCO2 in the northern hemisphere is higher than that in the southern hemisphere. (3) The growth of global XCO2 in 2011 and 2012 was 1.9 ppm/yr and 2.1 ppm/yr. These values are in accordance with the growth rates of 1.9 ppm/yr and 2.2 ppm/yr reported in the World Meteorological Organization's greenhouse gas bulletin.
The Qinghai-Tibetan Plateau has been experiencing a distinct warming trend, and climate warming has a direct and quick impact on the alpine grassland ecosystem. We detected the greenness trend of the grasslands in the plateau using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2009. Weather station data were used to explore the climatic drivers for vegetation greenness variations. The results demonstrated that the region-wide averaged normalized difference vegetation index (NDVI) increased at a rate of 0.036 yr −1 . Approximately 20% of the vegetation areas, which were primarily located in the northeastern plateau, exhibited significant NDVI increase trend (p -value <0.05 ). Only 4% of the vegetated area showed significant decrease trends, which were mostly in the central and southwestern plateau. A strong positive relationship between NDVI and precipitation, especially in the northeastern plateau, suggested that precipitation was a favorable factor for the grassland NDVI. Negative correlations between NDVI and temperature, especially in the southern plateau, indicated that higher temperature adversely affected the grassland growth. Although a warming climate was expected to be beneficial to the vegetation growth in cold regions, the grasslands in the central and southwestern plateau showed a decrease in trends influenced by increased temperature coupled with decreased precipitation.
The spatial variation of collapsing houses caused by the earthquake may be used to assess the earthquake damage
intensity, and support the emergency decision-making process in rescue and recovery operations. We monitored the
spatial variation of house collapse ratio in the 5.12 Wenchuan Earthquake by the aerial images, and analyzed the
relationship with the earthquake intensity and assessed the afflicted population from the population and house collapse
ratio. The house collapse ratio was derived based on the results of visual interpretation of the collapsed houses and noncollapsed
houses by ADS40 airborne images acquired from May 15 to May 28, 2008. The results show that the houses
were widely damaged in earthquake-damaged region; especially the counties of Wenchuan, Beichuan, Qinchuan,
Mianzhu, Shifang and Pengzhou experienced the severest damage. The house collapse ratios, which are above 50%,
mainly distributed along the surface rupture in a SW to NE direction from Yinxiu to Beichuan. When analyzing the
spatial variation of the house collapse ratio and its relationship with the earthquake intensity, it was found the house
collapse ratio and the earthquake intensity presented positive correlation. An index called the afflicted population which
was derived by the house collapse ratio multiplying the population density showed a correlation with the actual fatalities
population, which will be available to provide the reference information for the decision-making of rescue areas where
the life of peoples may be urgently needed to rescue.
Collapsing houses are one of the indicators to assess earthquake damage intensity. We monitored and analyzed the house collapse ratio and its spatial distribution in the Wenchuan Earthquake of May 12, 2008 by interpreting the aerial images. The results show that the houses were widely damaged, especially in Wenchuan County, Mianzhu City, Shifang City, and Pengzhou City in which Wenchuan County experienced the severest damage. We analyzed the spatial variation of the house collapse ratio and its relationship with earthquake intensity, geological structure, and stratum lithology. The results demonstrate that the house collapse ratio and the earthquake intensity have a positive relationship, which is controlled by the geological structure, stratum lithology, and building structure. Analysis of the collapsed houses over an extensive earthquake-damaged region using aerial images provides not only an effective assessment for the damages and losses, but also the foundation data for the analysis of earthquake intensity.
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