Evaluating the effectiveness of marine actinobacterial extract and its mediated titanium dioxide nanoparticles in the degradation of azo dyes

Aim of the present study was to synthesize titanium dioxide nanoparticles （YiO2 NPs） from marine actinobacteria and to develop an eco-friendly azo-dye degradation method. A total of five actinobacterial isolates were isolated from Chennai marine sediments, Tamilnadu, India and analyzed for the synthesis of TiO2 NPs using titanium hydroxide. Among these, the isolate PSV 3 showed positive results for the synthesis of TiO2 NPs, which was confirmed by UV analysis. Further characterization of the synthesized TiO2 NPs was done using XRD, AFM and FI＇-IR analysis. Actinobacterial crude extract and synthesized TiO2 NPs was found efficient in degrading azo dye such as Acid Red 79 （AR-79） and Acid Red 80 （AR-80）. Degradation percentage was found to be 81% for AR-79, 83% for AR-80 using actinobacterial crude extract and 84% for AR-79, 85% for AR-80 using TiO2 NPs. Immobilized actinobacterial ceils showed 88% for AR-79 and 81% for AR- 80, dye degrading capacity. Degraded components were characterized by FT-IR and GC-MS analysis. The phytotoxicity test with 500 μg/mL of untreated dye showed remarkable phenotypic as well as cellular damage to Tagetes erecta plant. Comparatively no such damage was observed on plants by degraded dye components. In biotoxicity assay, treated dyes showed less toxic effect as compared to the untreated dyes.     

An assessment of carbon stock for various land use system in Aravally mountains, Western India

Reducing carbon emissions from deforestation and degradation in developing countries is of the central importance in efforts to combat climate change. A study was conducted to measure carbon stocks in various land-use systems including forms and reliably estimates the impact of land use on carbon (C) stocks in the forest of Rajasthan, western India (23°3′–30°12′N longitude and 69°30′–78°17′E). 22.8% of India is forested and 0.04% is the deforestation rate of India. In Indian forest sector of western India of Aravally mountain range covered large area of deciduous forest and it’s very helpful in carbon sequestration at global level. The carbon stocks of forest, plantation (reforestation) and agricultural land in aboveground, soil organic and fine root within forest were estimated through field data collection. Results revealed that the amount of total carbon stock of forests (533.64?±?37.54 Mg·ha^?1, simplified expression of Mg (carbon) ·ha^?1) was significantly greater (P?<?0.05) than the plantation (324.37?±?15.0 Mg·ha^?1) and the agricultural land (120.50?±?2.17 Mg·ha^?1). Soil organic carbon in the forests (172.84?±?3.78 Mg·ha^?1) was also significantly greater (P?<?0.05) than the plantation (153.20?±?7.48 Mg·ha^?1) and the agricultural land (108.71?±?1.68 Mg·ha^?1). The differences in carbon stocks across land-use types are the primary consequence of variations in the vegetation biomass and the soil organic matter. Fine root carbon was a small fraction of carbon stocks in all land-use types. Most of the soil organic carbon and fine root carbon content was found in the upper 30-cm layer and decreased with soil depth. The aboveground carbon (ABGC): soil organic carbon (SOC): fine root carbon ratios (FRC), was 8:4:1, 4:5:1, and 3:37:1 for the forest, plantation and agricultural land, respectively. These results indicate that a relatively large proportion of the C loss is due to forest conversion to agricultural land.     

贝类资源过度开发对印度东北海岸的影响

引言 生物多样性是生态系统结构和功能的一项基本属性.它是一连串概念[1],包括从基因学和分子生物学到群落结构和生境的异质性等多个相互联系的方面.生态学家利用多个指数量测生物多样性,所有这些指数或多或少直接地将种的数量与丰度和/或数量优势相联系[3].     

2015年10月南京霾污染过程分析

为探讨南京秋季霾污染过程发生的主要影响因素,利用南京信息工程大学太阳光度计观测霾污染发生天气下AOD（aerosol optical depth,气溶胶光学厚度）数据,计算AE_440-1020（?ngstr?m Exponent,波长指数）以及a₂（光谱曲率）,结合CALIPSO（Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations）卫星气溶胶组分分析以及MODIS（Moderate Resolution Imaging Spectroradiometer）火点数据,对2015年10月南京霾污染过程进行分析.结果表明:2015年10月出现的两次霾污染过程期间南京地区AE_440-1020均高于1.0并且a₂呈负值,其中10月16日AQI达到峰值（201）,AOD₅₀₀达1.51,AE_440-1020达1.37,a₂达-0.77;这两次较为严重的霾污染过程均主要由人为因素（工业污染、城市建设、生物质燃烧、汽车尾气排放等）产生的细粒子所致.后向轨迹分析发现,2015年10月16日南京地区霾污染天气发生的主要原因是区域型污染,同时受长距离输送影响,大量携带人为因素产生的细粒子以及少量沙尘等污染物的空气团途经内蒙古、山东等地到达南京,加剧了当日的污染程度;2015年10月23日南京地区霾污染天气的发生则主要受长距离输送影响,同时也受到区域型污染影响,加剧了当日的污染程度.研究显示,在稳定的气象条件下,较高的相对湿度、较低的地表风速、低混合层高度以及贴地逆温的出现是诱发霾污染天气产生的有利气象条件.      

Real<Emphasis Type="Bold">-</Emphasis>time water quality monitoring using Internet of Things in SCADA

Water pollution is the root cause for many diseases in the world. It is necessary to measure water quality using sensors for prevention of water pollution. However, the related works remain the problems of communication, mobility, scalability, and accuracy. In this paper, we propose a new Supervisory Control and Data Acquisition (SCADA) system that integrates with the Internet of Things (IoT) technology for real-time water quality monitoring. It aims to determine the contamination of water, leakage in pipeline, and also automatic measure of parameters (such as temperature sensor, flow sensor, color sensor) in real time using Arduino Atmega 368 using Global System for Mobile Communication (GSM) module. The system is applied in the Tirunelveli Corporation (Metro city of Tamilnadu state, India) for automatic capturing of sensor data (pressure, pH, level, and energy sensors). SCADA system is fine-tuned with additional sensors and reduced cost. The results show that the proposed system outperforms the existing ones and produces better results. SCADA captures the real-time accurate sensor values of flow, temperature, and color and turbidity through the GSM communication.     

The probabilistic tsunami hazard assessment along Karnataka Coast from Makran Subduction Zone,west coast of India

Coastal tsunami amplitudes were calculated to identify areas susceptible to tsunami hazard at selected locations of the coast of Karnataka, west of India, due to earthquakes in the Makran Subduction Zone. This is the first time that the probabilistic tsunami hazard assessment along this study area has been attempted. A series of earthquake source scenarios with magnitudes of Mw 8.0, Mw 8.5, and a mega thrust of Mw 9.1 were modeled by using the Community Model Interface for Tsunami interface with the MOST model of Titov and Synolakis (J. Waterway, Port, Coastal and Ocean Engineering, 121(6), 308–316, 1995). As per the previous occurrences, the two least magnitudes are probable, while Mw 9.1 is a worst-case scenario as described by Heidarzadeh et al. (Ocean Engineering, 36(5), 368–376, 2009) and the same is reported by Burbidge et al. (Geoscience Australia Professional Opinion No. 2009/11) as high magnitude. These are not at all historical earthquakes or specifically from historical catalogues. The results of modeling show that all the seven coastal locations are inundated barely in our worst-case scenario with maximum water levels in the range of 100–200 cm. The first tsunami wave strikes the coast within 4–5 h of earthquake occurrence.     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.     

Community structure of zooplankton across environmental variables in a high-altitude lake of central Himalayas,India

We determined seasonal and spatial variation of zooplankton and their correlation with environment variables in a subtropical lake of the Himalayas. Thirty-eight species of zooplankton were identified, of which, 38.0% belonged to rotifera, 26.3% to cladocera, and 15.7% to copepoda. Nitrogen nutrients, total organic matter (TOM), and clay particles significantly influenced on the distribution pattern of zooplankton. Non-metric multidimensional scaling analysis showed homogeneous assemblages of dominant zooplankton species except Chydorus gibbus which has wider range of niche partitioning. Turbidity formed by suspended materials facilitated better avoidance of larger zooplankton like Daphnia similis from predators. Sedimentary silt particles influenced on the assemblages of sensitive species such as Tropocyclops prasinus, Asplanchna priodonta and Colurella obtuse. Changes within the land-use pattern in the catchment of the central Himalayan lakes either directly or indirectly impact on the distribution of zooplankton community.