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.     

Characteristics and driving factors of marsh changes in Zhalong wetland of China

Zhalong National Nature Reserve in the northeast of China is a large wetland and a habitat of hundreds species of fauna and flora. The rare red-crowned crane is one kind of endangered birds in it. Recently, Zhalong wetland is shrinking and it encounters many problems including occasional fires, bad water quality, human activities, etc. In order to find out a proper way to protect and restore the wetland, this study, using a geographic information system, the global positioning system and remote sensing techniques, analyses the spatial characteristics of the changes in marsh landscape pattern and examines the driving factors for these changes. Data sources include 8 Landsat Thematic Mapper satellite images of Zhalong area in the period of 1986–2002 and the investigation information on site. Based on the analysis of changes of marsh area and annual precipitation during the 16 years, it is found that there is a close correlation between annual precipitation and marsh area. It means that climate is one of driving factors of marsh pattern changes. To understand influences of other kinds of land uses on marsh spatial distribution in Zhalong wetland, this paper analyses the relationship between marsh and different kinds of land uses, such as water surface, residential area, farmland, salina land and grass land, respectively. According to the patch analysis theory, a fragmental index and a fractal dimension of the marsh are calculated with perimeter-area method. The results indicate that the marsh pattern is affected by human activities significantly. In addition, the location alteration of marsh centroid point over the 16 years is studied. The movement trace of marsh centroid point is concerned with different hydrological situation in different areas of the wetland. In summary the characteristics of the marsh landscape pattern evolution during the 16 years are affected by multiple driving factors. The main driving factors are climate, human activities, distribution of other kinds of land uses and hydrological situation in different areas.     

Using Spatial Pattern to Quantify Relationship Between Samples, Surroundings, and Populations

The need for accurate carbon budgeting, climate change modelling, and sustainable resource management has lead to an increase in the number of large area forest monitoring programs. Large area forest monitoring programs often utilize field and remotely sensed data sources. Sampling, via field or photo plots, enables the collection of data with the desired level of categorical detail in a timely and efficient manner. When sampling, the aim is to collect representative detailed data enabling the statistical reporting upon the characteristics of larger areas. As a consequence, approaches for investigating how well sample data represent larger areas (i.e., the sample neighbourhood and the population) are desired. Presented in this communication is a quantitative approach for assessing the nature of sampled areas in relation to surrounding areas and the overall population of interest. Classified Landsat data is converted to forest/non-forest categories to provide a consistent and uniform data set over a 130,000 km² study region in central British Columbia, Canada. From this larger study area 322 2 × 2 km photo plots on a 20 × 20 km systematic grid are populated with composition and configuration information for comparison to non-sampled areas. Results indicate that typically, within the study area, the spatial pattern of forest within a photo plot is representative of the forest patterns found within primary and secondary neighbourhoods and over the entire population of the study. These methods have implications for understanding the nature of data used in monitoring programs worldwide. The ability to audit photo and field plot information promotes an increased understanding of the results developed from sampling and provides tools identifying locations of possible bias.     

The application of generalized linear mixed models to multi-level sampling for insect population monitoring

Iwao's quadratic regression or Taylor's Power Law (TPL) are commonly used to model the variance as a function of the mean for sample counts of insect populations which exhibit spatial aggregation. The modeled variance and distribution of the mean are typically used in pest management programs to decide if the population is above the action threshold in any management unit (MU) (e.g., orchard, forest compartment). For nested or multi-level sampling the usual two-stage modeling procedure first obtains the sample variance for each MU and sampling level using ANOVA and then fits a regression of variance on the mean for each level using either Iwao or TPL variance models. Here this approach is compared to the single-stage procedure of fitting a generalized linear mixed model (GLMM) directly to the count data with both approaches demonstrated using 2-level sampling. GLMMs and additive GLMMs (AGLMMs) with conditional Poisson variance function as well as the extension to the negative binomial are described. Generalization to more than two sampling levels is outlined. Formulae for calculating optimal relative sample sizes (ORSS) and the operating characteristic curve for the control decision are given for each model. The ORSS are independent of the mean in the case of the AGLMMs. The application described is estimation of the variance of the mean number of leaves per shoot occupied by immature stages of a defoliator of eucalypts, the Tasmanian Eucalyptus leaf beetle, based on a sample of trees within plots from each forest compartment. Historical population monitoring data were fitted using the above approaches.     

Management of basiphilous dune slack communities in relation to carbonate accumulation and hydrological conditions

In dune slacks in The Netherlands, a decline of rare mesotrophic basiphilous plant species and their plant communities has been observed in combination with an increase of more productive systems with common, taller acidophilous plant species. This has been attributed to both natural and anthropogenic changes. In a humid climate with a precipitation surplus, as in The Netherlands, the calcium carbonate content of a calcareous soil increases with depth. However, soils in coastal dune slacks, may have a higher carbonate content in the topsoil horizon than in the underlying layers. Carbonates which buffer the pH can prolong the presence of mesotrophic basiphilous plant communities which are of high conservation value. To explain the occurrence of calcareous surface horizons in dune slacks, hydrological and micromorphological analyses were carried out in three dune slacks. Two slacks are situated on the Wadden Sea islands in the northern part of The Netherlands; one on Schiermonnikoog and one on Texel. The third slack is situated in the dunes on the island of Goeree in the southwestern part of The Netherlands. In all three slacks, carbonate occurs as mollusc and gastropod fragments (silt- or sand-sized) and as micritic nodules in the topsoil layer, due to aeolian deposition and sedimentation by water.In situ carbonate accumulation (calcitans and calcareous crusts) due to CO₂ release in inundated and/or capillary rise of calcareous groundwater near, or at the soil surface. Accumulation of carbonate also occurs as a result of biological activity by algae in the topsoil of the Goeree site. In general, hydrological processes maintaining high levels of calcareous groundwater are a prerequisite for the maintenance of high carbonate levels in topsoils. Such levels are necessary for the conservation and management of basiphilous pioneer vegetation.     

乌鲁木齐城市地表温度时空变化与贡献度研究

伴随着新疆首府乌鲁木齐市经济快速发展,人口持续增加、城市化进程不断加快,地表温度也发生极其显著的变化.以乌鲁木齐市中心城区为研究对象,利用1990—2018年的4期Landsat卫星影像和中国科学院土地利用/覆被分类数据,采用地表温度反演、重心转移模型、空间聚类分析以及计算贡献度指数等方法,定量研究乌鲁木齐市城市化进程...     

基于CA-Markov模型的艾比湖流域平原区景观格局动态模拟预测

利用“3S”技术及CA-Markov模型,按照是否实施跨流域调水工程2种预案情况,以2005年为起始时刻,对新疆艾比湖流域平原区2020年景观格局进行模拟预测。结果显示：在调水工程未实施的情况下,2020年研究区的生态环境将进一步恶化,其突出表现为艾比湖湖泊水面将持续萎缩、裸露湖底盐漠面积进一步扩大,水资源短缺及生态环境恶化的结果将严重制约研究区社会经济的发展;在调水工程实施的情况下,2020年研究区内艾比湖湖泊水面将稳定增加至800 km^2以上、裸露湖底盐漠面积相应有所减少,生态环境恶化趋势得到改善,区域水资源短缺问题将有所缓解,可有效地促进研究区内社会经济的发展。     

创新我国环境监测质量管理体系初探

在调研国内外环境监测质量管理模式的基础上,提出了强化环境监测统一监督管理,建立国家环境监测质量管理与技术中心、区域(流域)环境监测质量管理与技术中心,完善各级环境监测机构质量管理工作体系的设想.     

贵州草海湿地农田渠系水质空间分异特征及影响分析

为了解草海湿地农田渠系水质现状、空间分异特征及影响因素,于2011年秋季对草海湿地进行大空间尺度的采样,分析了氮磷等理化指标,采用单因子污染指数法和营养状态指数法分别对农田渠系水质和湖泊营养状态进行评价.结果表明,草海湿地农田渠系水质污染严重,多数水质为V类或劣V类,总氮和溶解氧是水体中的主要污染因子;上游水质劣于下游,尤其是上游靠近县城区域的水质最差;多等级排水渠系对氮磷具有一定的截留作用,干渠V级水质好于低级渠系水质;不同的土地利用方式对水质的影响不同,城镇用地>集中式村落>农田;草海湿地水体上、中、下游营养水平分别为中度富营养、轻度富营养和中营养,外源污染物的累积和湖泊营养水平的提高导致其沼泽化,而流域不合理的土地利用结构加剧了沼泽化的进程.