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.      

Climate change mitigation policy paradigms—national objectives and alignments

The aim of this paper is to assess how policy goals in relation to the promotion of green growth, energy security, pollution control and greenhouse gas (GHG) emissions reductions have been aligned in policies that have been implemented in selected countries during the last decades as a basis for discussing how a multi objective policy paradigm can contribute to future climate change mitigation. The paper includes country case studies from Brazil, Canada, China, the European Union (EU), India, Japan, Mexico, Nigeria, South Africa, South Korea and the United States covering renewable energy options, industry, transportation, the residential sector and cross-sectoral policies. These countries and regions together contribute more than two thirds of global GHG emissions. The paper finds that policies that are nationally driven and that have multiple objectives, including climate-change mitigation, have been widely applied for decades in both developing countries and industrialised countries. Many of these policies have a long history, and adjustments have taken place based on experience and cost effectiveness concerns. Various energy and climate-change policy goals have worked together in these countries, and in practice a mix of policies reflecting specific priorities and contexts have been pursued. In this way, climate-change mitigation has been aligned with other policy objectives and integrated into broader policy packages, though in many cases specific attention has not been given to the achievement of large GHG emission reductions. Based on these experiences with policy implementation, the paper highlights a number of key coordination and design issues that are pertinent to the successful joint implementation of several energy and climate-change policy goals.     

Changes in earth’s dipole

The dipole moment of Earth’s magnetic field has decreased by nearly over the past 150 years and by about 30% over the past 2,000 years according to archeomagnetic measurements. Here, we explore the causes and the implications of this rapid change. Maps of the geomagnetic field on the core–mantle boundary derived from ground-based and satellite measurements reveal that most of the present episode of dipole moment decrease originates in the southern hemisphere. Weakening and equatorward advection of normal polarity magnetic field by the core flow, combined with proliferation and growth of regions where the magnetic polarity is reversed, are reducing the dipole moment on the core–mantle boundary. Growth of these reversed flux regions has occurred over the past century or longer and is associated with the expansion of the South Atlantic Anomaly, a low-intensity region in the geomagnetic field that presents a radiation hazard at satellite altitudes. We address the speculation that the present episode of dipole moment decrease is a precursor to the next geomagnetic polarity reversal. The paleomagnetic record contains a broad spectrum of dipole moment fluctuations with polarity reversals typically occurring during dipole moment lows. However, the dipole moment is stronger today than its long time average, indicating that polarity reversal is not likely unless the current episode of moment decrease continues for a thousand years or more.     

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.     

Impact of heavy metals on bacterial communities from mangrove soils of the Mahanadi Delta (India)

This study aimed to assess soil nutrient status and heavy metal content and their impact on the predominant soil bacterial communities of mangroves of the Mahanadi Delta. Mangrove soil of the Mahanadi Delta is slightly acidic and the levels of soil nutrients such as carbon, nitrogen, phosphorous and potash vary with season and site. The seasonal average concentrations (μg/g) of various heavy metals were in the range: 14 810–63 370 (Fe), 2.8–32.6 (Cu), 13.4–55.7 (Ni), 1.8–7.9 (Cd), 16.6–54.7 (Pb), 24.4–132.5 (Zn) and 13.3–48.2 (Co). Among the different heavy metals analysed, Co, Cu and Cd were above their permissible limits, as prescribed by Indian Standards (Co=17 μg/g, Cu=30 μ g/g, Cd=3–6 μ g/g), indicating pollution in the mangrove soil. A viable plate count revealed the presence of different groups of bacteria in the mangrove soil, i.e. heterotrophs, free-living N₂ fixers, nitrifyers, denitrifyers, phosphate solubilisers, cellulose degraders and sulfur oxidisers. Principal component analysis performed using multivariate statistical methods showed a positive relationship between soil nutrients and microbial load. Whereas metal content such as Cu, Co and Ni showed a negative impact on some of the studied soil bacteria.