Satellite- and ground-based measurements of CO2 over the Indian region: its seasonal dependencies,spatial variability,and model estimates

ABSTRACT

The present study demonstrates the distribution of carbon dioxide (CO₂) concentration over the Indian region and the surrounding oceanic regions during 2009–2012, using measurements from satellites viz., Greenhouse Gases Observing Satellite (GOSAT) and Atmospheric Infrared Sounder, Carbon Tracker (CT) model simulations and flask measurements from two Indian stations Sinhagad (SNG) (73°45′ E, 18°21′36″ N) and Cape Rama (CRI) (73°54′ E, 15°6′ N). The concentration of CO₂ is observed to be maximum during pre-monsoon and shows a decreasing phase during the post-monsoon season. In a regional scale, it is found that Indo-Gangetic Plain and northern India have relatively higher concentrations compared to the other regions. The probability distribution of the concentration differences shows that for most of the time, the differences lie between ±3 ppmv between GOSAT and CT. The comparison between the CO₂ flask measurements over SNG and CRI with respect to that of GOSAT and CT clearly reveals that the differences in CO₂ are as high as 10 ppmv between the ground- and satellite-based measurements. Further, we utilized the Lagrangian model FLEXible PARTicle (FLEXPART) to understand the source?receptor relationship over CRI, SNG, and over the equatorial Indian Ocean (IO). The source contributions from the northern and eastern continental regions of the Indian region are found to be more influential over SNG compared to CRI. It is also found from simulations that the equatorial IO has less influence from the continental source and therefore has a reduced seasonal variability compared to the other regions considered in the present study.     

Analyzing the Structure and Evolution of Massive Telecom Graphs

With the ever-growing competition in telecommunications markets, operators have to increasingly rely on business intelligence to offer the right incentives to their customers. Existing approaches for telecom business intelligence have almost solely focused on the individual behavior of customers. In this paper, we use the call detail records of a mobile operator to construct call graphs, that is, graphs induced by people calling each other. We determine the structural properties of these graphs and also introduce the Treasure-Hunt model to describe the shape of mobile call graphs. Moreover, we determine how the structure of these call graphs evolve over time. Finally, since short messaging service (SMS) is becoming a preferred mode of communication among many sections of the society, we study the properties of the SMS graph. Our analysis indicates several interesting similarities and differences between the SMS graph and the corresponding call graph. We believe that our analysis techniques can allow telecom operators to better understand the social behavior of their customers and potentially provide major insights for designing effective incentives.     

Local and Regional Secondary Organic Aerosol: Insights from a Year of Semi-Continuous Carbon Measurements at Pittsburgh

We present Scanning Mobility CCN Analysis (SMCA) as a novel method for obtaining rapid measurements of size-resolved cloud condensation nuclei (CCN) distributions and activation kinetics. SMCA involves sampling the monodisperse outlet stream of a Differential Mobility Analyzer (DMA) operated in scanning voltage mode concurrently with CCN and condensation particle counters. By applying the same inversion algorithm as used for obtaining size distributions with a scanning mobility particle sizer (SMPS), CCN concentration and activated droplet size are obtained as a function of mobility size over the timescale of an SMPS scan (typically 60–120 s). Methods to account for multiple charging, particle non-sphericity, and limited counting statistics are presented. SMCA is demonstrated using commercial SMPS and CFSTGC instruments with the manufacturer-provided control software. The method is evaluated for activation of both laboratory aerosol and ambient aerosol obtained during the 2004 NEAQS-ITCT2k4 field campaign. It is shown that SMCA reproduces the results obtained with a DMA operating in voltage “stepping” mode.     

Thermodynamics of nanoscale materials

Nanoscale materials have been considered for and been in use in a variety of industrial engineering applications. The surface tension of silver and copper were calculated at various temperatures using non-ideal or real solution characteristics. The surface concentration of individual components was also calculated. The surface concentration of silver in a binary silver copper system is higher in spite of its lower surface tension as a pure component. It is also shown that the melting temperature of individual elements decrease with decrease in particle size. This trend is true for most metallic elements and is pronounced below a particle size of 20 nm.     

Thermal diffusion in nanostructured porous InP

Nanostructured porous InP samples were prepared by electrochemical anodic dissolution of InP for various current densities and etching periods. The samples were characterized by SEM and photoluminescence (PL) where a blue shift was observed in PL. Thermal properties studied by photoacoustic (PA) spectroscopy revealed one order decrease in thermal conductivity of porous InP compared to the bulk. Further it is shown that the thermal conductivity of porous InP decreases with decrease in size of the particles.     

江苏德邦化工集团有限公司，江苏连云港 222023

1 简介 印度第一个纯碱厂始建于1932年，位于印度西部古吉拉特邦的Dhrangadhra，装置能力为50t/d。 作为基础无机化工产品，因为整个印度无天然碱矿，全部产品--包括轻灰和重灰只能以合成法生产。     

Sample size and error in the determination of mode shapes by principal components analysis

Principal components analysis (PCA) is a multivariate statistical technique that transforms a data set having a large number of inter-related variables to a new set of uncorrelated variables called the principal components, determined to allow the dimensionality of the data set to be reduced while retaining as much of the variation present as possible. PCA can be applied to dynamic structural response data to identify the predominant modes of vibration of the structure. Because PCA is a statistical technique, there are errors in the computed modes due to the use of a sample of finite size. The aim of this paper is to study the effect of sample size on the accuracy with which the modes of vibration can be computed. The paper focuses predominantly on elastic response data and examines the potential influence of various parameters such as the period of the structure, the input excitation, and the spatial distribution of mass over the structure. Issues relating to errors in the modes of nonlinear structures are also discussed.     

The coming of age of agroforestry

The success of modern agricultural and forestry production can be largely attributed to monoculture systems using a few select species. In the drive for maximizing yield and profit, the age‐old tradition of using combined farming systems was essentially avoided and in some cases this has resulted in environmental problems such as land and water degradation and increased land clearing. During the last 30 years, however, the positive benefits of agroforestry to the producer and the environment have been increasingly recognized. Combining trees and crops in spatial or temporal arrangements has been shown to improve food and nutritional security and mitigate environmental degradation, offering a sustainable alternative to monoculture production. By providing supportive and complimentary roles with a flexible approach, agroforestry can offer specific social and environmental benefits across a range of landscapes and economies. More research and effort is needed to explore the full potential of agroforestry applications and to fuel awareness. As the plethora of benefits of agroforestry are realized, modern land‐use systems are evolving towards a more sustainable and holistic approach to land management. Copyright © 2007 Society of Chemical Industry