印度空间研究组织

Delhi experiences severe air quality deterioration during the post-monsoon and winter seasons, driven by anthropogenic emissions and natural meteorological factors. This study investigates the atmospheric boundary layer (ABL) characteristics during heavy air pollution and fog conditions over Delhi from October 2023 to February 2024 using ground-based Lidar, satellite, and reanalysis data. Lidar measurements reveal a persistently shallow ABL (<1 km) from November to January, with nighttime boundary layer height (BLH) suppressed by strong radiative inversions. Elevated PM2.5 concentrations during this period show an inverse, power-law relationship with BLH. The ventilation coefficient (VC) remained below 800 m(2)s(-1) from November to January, indicating poor dispersion. INSAT-3D/3DR satellite data showed a peak fog occurrence of 75 % over Delhi, with the highest frequency in January. Analysis showed that the combined frequency of haze, fog, and low-level clouds reached 22.46 % during the study period, with the highest occurrences in November (45.10 %) and January (39.55 %). Ground-based Lidar observations captured fine-scale features such as shallow inversion layers, nighttime ABL collapse, and diurnal boundary layer development more accurately than reanalysis. These insights are crucial for enhancing urban weather models, air quality forecasts, and early warning systems in pollution-affected regions.

In space, materials used in spacecraft and satellites are exposed to extreme thermal fluctuations, radiation, and humidity, which can significantly affect the component’s structural integrity. In this work, high cycle fatigue (HCF) behavior of selective laser melting (SLM) AlSi10Mg alloy under simulated space environmental conditions is studied to ensure the structural integrity of components. To evaluate the mechanical performance of SLM AlSi10Mg alloy, fatigue and tensile tests were conducted on specimens subjected to thermoshock + thermovac and humidity + radiation conditions, alongside bare samples. Among the tested conditions, the humidity + radiation specimens exhibited the highest fatigue resistance, while the bare samples showed the lowest. This increased resistance to fatigue limit of humidity + radiation specimen among all conditions is primarily attributed to a decrease in grain size and higher geometrically necessary dislocation (GND) density during controlled environmental treatments. A strong correlation was observed between the grain size and fatigue limit: The fatigue limit increased from 59 MPa for bare (grain size, 32.66 ± 13.65 µm) to 76 MPa for humidity + radiation (grain size, 19.65 ± 11.43 µm) specimens. The results confirm the suitability of SLM AlSi10Mg alloy under space-relevant conditions, supporting its viability for structural use in space components.

India is the 3rd largest emitter of fossil fuel carbon dioxide (CO2), highlighting the critical need to understand CO2 dynamics for effective carbon management. This study investigates the CO2 variability and its dynamics over India using ground-based in situ measurements (11 sites), satellite observations and model simulations. The analyses reveal distinct diurnal and seasonal patterns, along with a consistent increasing trend with global-mean CO2 concentrations. The amplitude of seasonal cycles (SCAs) vary geographically, with deeper SCAs observed in northern India and shallower ones in the south, primarily influenced by the monsoon system and temperature-dependent vegetation dynamics. The lowest SCA is observed over the high-altitude site at Hanle in north India (7.4 ppm), followed by the coastal sites at Pondicherry (8.0 ppm) and Thumba (8.5 ppm) in south India. The deepest SCA of 26.7 ppm is observed at Mohali, with one of the peaks observed in November attributed to crop residue burning in the Indo-Gangetic Plain. We have used an Atmospheric Chemistry Transport Model (ACTM) to understand spatial and temporal variations in CO2. The model simulates the phase of the SCAs reasonably well at only a few sites, e.g., Thumba, Gadanki, and fails to capture details at most sites. Coarse horizontal resolution of ACTM (2.8o × 2.8°) limits the reproduction of observed diurnal pattern at the sites near strong fluxes. Satellite observations of total column CO2 (XCO2) anomalies (2014–2024) show negative values (indicative of sink) over India during post-monsoon season, and positive values (indicative of source) during premonsoon season. The regional mean XCO2 SCA (5.45–5.65 ppm), trend (2.44–2.51 ppm y−1) and interannual variability in growth rates (∼1.0–3.9 ppm y−1) are consistently estimated from two satellites during 2009–2024.

Modeling approaches are an effective way to simulate water balance components at spatially larger scales. The simulated components are validated against streamflow at a single or multiple sites to assess model's performance. While calibrating model parameters will identify only the key sensitive parameters, representing water storage structures will provide a realistic condition of catchment hydrology. In this study, the Srisailam Reservoir catchment of the River Krishna Basin is considered, and the inflow into the reservoir is simulated for the period 2010-2022 by incorporating the major reservoirs using Variable Infiltration Capacity reservoir module. The simulated inflows are corrected for other abstractions like waterbodies located in the upstream using correction factors derived from the regression model developed between catchment rainfall and its inflow. The estimated performance indicators such as correlation coefficient (r), Nash-Sutcliffe Efficiency and Kling-Gupta Efficiency are 0.7, 0.61 and 0.15, respectively, for a daily timestep. The performance criteria show good agreement with the observed inflow after the simulated inflows are corrected for upstream water storage structures. The findings of this study reinforce the message that water infrastructures and their operational settings play a key role in the reliability of simulation through hydrological modeling.

Cepstral analysis has become a widely recommended acoustic tool for voice assessment, yet its computational principles and clinical interpretation often remain unclear, particularly for nontechnical users. This review aims to present the concepts, methodological considerations, and clinical applications of cepstral analysis in a simplified and accessible format for voice clinicians, educators, students, and researchers. This narrative review is organized into two sections. The first introduces the theoretical foundations of cepstral analysis, highlighting its advantages over traditional perturbation measures, including its independence from fundamental frequency extraction and greater stability across voice types. Key parameter settings for the widely used Praat software are also outlined. The second section synthesizes available peer-reviewed studies and technical guidelines, categorizing empirical findings across multiple application domains. A comprehensive literature search was conducted across multiple scientific databases using defined inclusion and exclusion criteria to identify relevant studies. Where available, cutoff and normative values for cepstral measures are provided to guide clinical use and interpretation. This review offers a structured reference for clinicians, educators, and researchers, aiming to enhance consistent use of cepstral measures in voice assessment, improve clinical decision making, and highlight the need for ongoing methodological standardization across tasks, populations, and software platforms. https://doi.org/10.23641/asha.30764927