The Large Angle Spectrometric Coronagraph (LASCO) and Extreme-ultraviolet Imaging Telescope (EIT) onboard Solar and Heliospheric
Observatory (SOHO) provide us with unprecedented multi-wavelength observations helping us to understand different dynamic
phenomena on the Sun and in the corona. In this paper we discuss the association between post-eruptive arcades (PEAs) detected
by EIT and white-light coronal mass ejections (CMEs) detected by LASCO/C2 telescope. 相似文献
Strong motion data from various regions of India have been used to study attenuation characteristics of horizontal peak acceleration and velocity. The strong ground motion data base considered in the present work consists of various earthquakes recorded in the northern part of India since 1986 with magnitudes 5.7 to 7.2. Using these data, relations for horizontal peak acceleration and velocity, which are $$\begin{gathered} log_{10} a = 1.14 + 0.31M + 0.65log_{10} R \hfill \\ log_{10} v = 0.571 + 0.41M + 0.768log_{10} R \hfill \\ \end{gathered} $$ have been proposed wherea is the peak horizontal acceleration in cm/sec2,v is the peak horizontal velocity in mm/sec,M is body wave magnitude, andR is the hypocentral distance in km. The proposed relations are in reasonable agreement with the small amount of strong ground motion data available for the northern part of India. The present results will be useful in estimating strong ground motion parameters and in the earthquake resistant design in the Himalayan region. 相似文献
The carbon isotope measurements, carried out on subsurface carbonate samples from Oxfordian Jaisalmer Formation, western India, yield positive d13C values up to +3.17%. The most positive Oxfordian C-isotope value corresponds to the carbon isotope excursion measured in samples from from other late Jurassic basins of world. The latest Oxfordian C-isotope values of Jaisalmer Basin fluctuate around 2% while the C-isotope values of 1.50% mark the base of Kimmeridgian. The Oxfordian C-isotope excursion appears to correspond to a time of overall increased organic carbon burial triggered by increased nutrient transfer from continents to oceans during a time of rising global sea level. 相似文献
The Ganga River plays a major role in the transfer of materials from the Indian sub-continent to the Bay of Bengal, both in dissolved and particulate forms. To understand the present elemental dynamics of the Ganga River system, it is important to assess the hydrogeochemical contribution of its tributaries. In this paper, we present an updated database on dissolved and particulate fluxes and denudation rates of the Himalayan tributaries of the Ganga River (Ramganga, Ghaghara, Gandak and Kosi). Dissolved trace element concentrations, their fluxes and suspended sediment-associated elemental fluxes of the Himalayan tributaries have been reported for the first time. Total dissolved flux of the Ramganga, Ghaghara, Gandak and Kosi was estimated as 4, 19.1, 10.3 and 8.8 million tons year?1 accounting for ~?5.7, ~?27.3, ~?14.7 and ~?12.6%, respectively, of the total annual dissolved load carried by the Ganga River. The total particulate flux of the Ramganga, Ghaghara, Gandak and Kosi was computed as 8.2, 81.6, 30.9 and 19.5 million tons year?1, respectively. Compared to earlier studies, we have found a significant increase in the total dissolved flux and chemical denudation rate of the studied tributaries. The estimated particulate fluxes were found to be low in comparison to the previous studies. We suggest that a significant increase in the dissolved fluxes and a decrease in the particulate fluxes are an indication of the increasing anthropogenic disturbances in the catchment of these tributaries. 相似文献
Ambient air pollution, particularly in the urban environment of developing countries, has turned out to be a major health risk factor. We explore the compounded impact of age sensitivity, exposure, poverty, co-morbidity, etc., along with composite air pollution in determining morbidity and health burden of people in Lucknow, India. This cross-sectional study is confined to analyse respiratory health status across different socio-economic and geographic locations using n = 140 in-depth questionnaire method. We used mean daily ambient air pollution data of PM10, PM2.5, SO2, and NO2 for the 2008–2018 period. We used the ecological model framework to assess the risk at different hierarchical levels and compounded severity on a spatial scale. We also used Logistic regression model with log odds and odds ratio to analyze the association of risks outcomes with composite air pollution scores calculated using the principal component analysis method. There is a strong association of location-specific respiratory disease prevalence with an overall 32 percent prevalence. The prevalence of ecological model 1 (individual domain) is 4.3 percent, while ecological model 2 (community domain) has the highest prevalence at 32.4 percent. The logistic regression model shows that respiratory disease load is positively associated with age sensitivity (P < .001) and composite pollution level (P < .001). For another model with suffocation as the outcome variable, composite pollution level (P < .001) and exposure (P < .001) are positively associated. Optimum interventions are required at Ecological models 1, 2, and 3 levels for better respiratory health outcomes.