Suspended Particulate Matter Distribution in Rural-Industrial Satna and in Urban-Industrial South Delhi

An air quality sampling program was designed and implemented to collect the baseline concentrations of respirable suspended particulates (RSP = PM₁₀), non-respirable suspended particulates (NRSP) and fine suspended particulates (FSP = PM_2.5). Over a three-week period, a 24-h average concentrations were calculated from the samples collected at an industrial site in Southern Delhi and compared to datasets collected in Satna by Envirotech Limited, Okhla, Delhi in order to establish the characteristic difference in emission patterns. PM_2.5, PM₁₀, and total suspended particulates (TSP) concentrations at Satna were 20.5 ± 6.0, 102.1 ± 41.1, and 387.6 ± 222.4 μg m⁻³ and at Delhi were 126.7 ± 28.6, 268.6 ± 39.1, and 687.7 ± 117.4 μg m⁻³. Values at Delhi were well above the standard limit for 24-h PM_2.5 United States National Ambient Air Quality Standards (USNAAQS; 65 μg m⁻³), while values at Satna were under the standard limit. Results were compared with various worldwide studies. These comparisons suggest an immediate need for the promulgation of new PM_2.5 standards. The position of PM₁₀ in Delhi is drastic and needs an immediate attention. PM₁₀ levels at Delhi were also well above the standard limit for 24-h PM₁₀ National Ambient Air Quality Standards (NAAQS; 150 μg m⁻³), while levels at Satna remained under the standard limit. PM_2.5/PM₁₀ values were also calculated to determine PM_2.5 contribution. At Satna, PM_2.5 contribution to PM₁₀ was only 20% compared to 47% in Delhi. TSP values at Delhi were well above, while TSP values at Satna were under, the standard limit for 24-h TSP NAAQS (500 μg m⁻³). At Satna, the PM₁₀ contribution to TSP was only 26% compared to 39% in Delhi. The correlation between PM₁₀, PM_2.5, and TSP were also calculated in order to gain an insight to their sources. Both in Satna and in Delhi, none of the sources was dominant a varied pattern of emissions was obtained, showing the presence of heterogeneous emission density and that nonrespirable suspended particulate (NRSP) formed the greatest part of the particulate load.     

Temporal Trends in the Spatial Distribution of Impervious Cover Relative to Stream Location

Use of impervious cover is transitioning from an indicator of surface water condition to one that also guides and informs watershed planning and management, including Clean Water Act (33 U.S.C. §1251 et seq.) reporting. Whether it is for understanding surface water condition or planning and management, impervious cover is most commonly expressed as summary measurement (e.g., percentage watershed in impervious cover). We use the National Land Cover Database to estimate impervious cover in the vicinity of surface waters for three time periods (2001, 2006, 2011). We also compare impervious cover in the vicinity of surface waters to watershed summary estimates of impervious cover for classifying the spatial pattern of impervious cover. Between 2001 and 2011, surface water shorelines (streams and water bodies) in the vicinity of impervious cover increased nearly 10,000 km. Across all time periods, approximately 27% of the watersheds in the continental United States had proximally distributed impervious cover, i.e., the percentage of impervious cover in the vicinity of surface waters was higher than its watershed summary expression. We discuss how impervious cover spatial pattern can be used to inform watershed planning and management, including reporting under the Clean Water Act.     

长江中游城市群经济与生态成本空间演化模式分析

综合运用变异系数、泰尔指数及ESDA-GIS多种方法,在充分考虑传统经济影响因子的基础上,尝试引入经济发展生态成本指标,分析长江中游城市群经济综合发展水平与生态成本的空间匹配及演化模式。研究表明:经济综合发展水平高低聚集特征明显,空间极化现象是导致区域经济发展不平衡的主要原因;生态成本空间集聚现象以高高集聚和低低集聚为主,且呈现出高高集聚减少、低低集聚增多的现象,生态成本消耗有所改善;2001~2012年长江中游城市群市域经济综合发展水平与生态成本表现出越来越显著的差异化空间格局,呈现出由低经济综合发展水平-低生态成本过渡到高经济综合发展水平-高生态成本,进而发展到高经济综合发展水平-低生态成本的空间匹配模式的阶段性特征;高经济综合发展水平-高生态成本的经济发展模式仍在大部分城市中存在,经济与生态空间协调发展的潜力仍然很大。     

珠三角地区大气PM_(2.5)理化特性季节规律与成因

基于珠三角大气超级站2013年8月至2014年3月PM2.5、PM2.5中主要水溶性无机离子组分及其重要气态前体物等参数的逐时在线监测结果,揭示当地大气PM2.5中二次无机组分与其气态前体物的相互作用,以及PM2.5理化特性与成因的季节差异。结果表明,观测期间,PM2.5、PM10的年平均质量浓度分别为64.2、105.1μg/m3,PM2.5在PM10中所占比例(PM2.5/PM10)平均为61.1%。SO2-4、NO-3、NH+4的年平均质量浓度分别为16.6、9.0、10.2μg/m3,3者之和(SNA)占PM2.5的比例(SNA/PM2.5)平均为55.8%,体现了二次转化对珠三角地区PM2.5污染的重要影响;不同季节,SNA/PM2.5为46.0%~64.3%,夏季最低,冬季最高,其中SO2-4、NH+4对PM2.5的贡献相对稳定,NO-3贡献的季节差异较大;秋、冬季各项观测参数浓度的日变化规律相对明显,夏季除HNO3和NH3外,多项观测参数在低浓度水平波动,日变化规律不明显;珠三角大气中具有足量气态NH3以中和硫酸盐和硝酸盐,PM2.5中NH+4、SO2-4、NO-3主要以(NH4)2SO4和NH4NO3形式存在;本研究站点夏季的硫氧化率和氮氧化率均高于广州市,这充分体现了该站点的区域性特征。     

基于GIS的乌梁素海水体富营养化状况的模糊模式识别

利用基于MATLAB 7.0实现的模糊模式识别交叉迭代模型对2006年5—10月分布于乌梁素海各水体功能区的21个水质监测点的富营养化等级进行了模糊模式识别,并在GIS技术支持下,用Arcview的空间分析功能绘制富营养化等级识别结果、对富营养化状态影响权重最大的评价指标总氮(TN)含量和富营养化状态控制元素总磷(TP)含量对应的富营养化等级水体和地表水质等级水体的空间分布月变化Grid专题图.将富营养化状态变化及其分布区域与乌梁素海同期水质监测指标浓度变化及其分布区域进行对比分析及验证.结果表明,富营养化等级识别结果的时空分布与实际情况相符,能够比较准确地反映富营养化等级定量的时空变化趋势.      

北方农牧交错带土地利用及景观格局变化特征

基于1988,1995和2000年3期Landsat TM数据,采用遥感,GIS和景观生态学方法,运用土地利用转移矩阵、景观格局分析软件Fragstats3.3,对北方农牧交错带土地利用及景观格局变化进行了动态研究.结果表明:①减少的耕地主要转为草地,增加的耕地也主要源于开垦草地;②耕地转为草地的空间分布较均匀,草地转为耕地的区域差异明显;③1988—1995年和1995—2000年2个时段参加变化的土地数量差异显著;④增加的沙地主要源于草地退化;⑤景观异质性上升,结构趋向均衡化,稳定性增强,受人类干扰程度在加大.      

染料浓度和盐度对白腐真菌同工酶的电泳分析

应用聚丙烯酰胺凝胶电泳技术分析,并比较了染料废水的两大因子(染料浓度和盐度)对黄孢原毛平革菌过氧化物同工酶谱带的影响程度,结果表明:在染料或盐胁迫下,黄孢原毛平革菌均表现出应急产酶的响应,虽然过氧化物同工酶谱带数量未发生增加或减少,但谱带强度受到较大影响,活性艳红X-3B浓度≤200mg/L或NaCl浓度≤15g/L时均能诱导过量产酶,继续提高染料浓度或盐度将导致产酶抑制,染料浓度对酶带的影响作用高于盐度。     

城市景观水污染现状及处理技术

城市景观水体由于水质恶化而渐渐影响附近居民的正常生活,要从根本上保证水质需采取一定的水源保护和水处理措施。在景观水处理中,适用于景观水处理的工艺有很多,但工程实施中需要对其进行选择、优化、组合。随着社会不断发展和人们生活质量要求不断提高,景观水处理也必将成为继生活用水处理、工业用水处理后的又一给水处理新领域。     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

Assessing Impacts of Typhoons and the Chi-Chi Earthquake on Chenyulan Watershed Landscape Pattern in Central Taiwan Using Landscape Metrics

The Chi-Chi earthquake (M_L = 7.3) occurred in the central part of Taiwan on September 21, 1999. After the earthquake, typhoons Xangsane and Toraji produced heavy rainfall that fell across the eastern and central parts of Taiwan on November 2000 and July 2001. This study uses remote sensing data, landscape metrics, multivariate statistical analysis, and spatial autocorrelation to assess how earthquake and typhoons affect landscape patterns. It addresses variations of the Chenyulan watershed in Nantou County, near the earthquake’s epicenter and crossed by Typhoon Toraji. The subsequent disturbances have gradually changed landscape of the Chenyulan watershed. Disturbances of various types, sizes, and intensities, following various tracks, have various effects on the landscape patterns and variations of the Chenyulan watershed. The landscape metrics that are obtained by multivariate statistical analyses showed that the disturbances produced variously fragmented patches, interspersed with other patches and isolated from patches of the same type across the entire Chenyulan watershed. The disturbances also affected the isolation, size, and shape-complexity of patches at the landscape and class levels. The disturbances at the class level more strongly affected spatial variations in the landscape as well as patterns of grasslands and bare land, than variations in the watershed farmland and forest. Moreover, the earthquake with high magnitude was a starter to create these landscape variations in space in the Chenyulan watershed. The cumulative impacts of the disturbances on the watershed landscape pattern had existed, especially landslides and grassland in the study area, but were not always evident in space and time in landscape and other class levels.