The Seasonal Variation of the Concentrations of Ozone, Sulfur Dioxide, and Nitrogen Oxides in Two Nigerian Cities

A combination of multivariate statistical methods including factor analysis, principal component analysis, principal component regression, and multiple linear regression (MLR) were employed to evaluate the influence of seasons on the concentrations of ozone, sulfur (IV) oxide, and oxides of nitrogen in ambient air of Nigerian cities of Lagos and Ilorin. The former city is located in the coastal area, and it is highly congested with a high intensity of marine, vehicular, and industrial activities, and the latter city is a medium size town, located in the central guinea savannah zone of Nigeria. Samples were collected using a high-volume sampler from near the ground at various sites of diverse human and industrial activities, during wet and dry seasons from 2003 to 2006. The PCA reveals three distinct groupings during the day for all data, which is a reflection of different factors contributing to the atmospheric chemistry of these cities. The predicted ozone concentration values by MLR agree fairly well with the measured data. The dependence of ozone on meteorological parameters including relative humidity, air temperature, and sun exposure and the precursor pollutants depends on weather and the anthropogenic activities. The results for the two cities indicate that reduction in the level of NO₂ is accompanied by an increase in the level of ozone, suggesting the interconversion between the two via photochemical activity.     

Evaluation of the interaction between soil and antibiotics

The aim of this study was to investigate the occurrence of tetracycline and sulfonamide antibiotics in 13 different soil samples collected from agricultural fields. As well as the antibiotic analysis 18 different physicochemical properties of the soil samples were determined in order to establish a relationship between the recovery rates of antibiotics from the samples and the characteristics of the samples that provide critical information for the reliability of an applied antibiotic analysis method. While the concentrations of tetracyclines were 0.025–0.105 mg kg^?1 sulfonamide antibiotics were not detected in any investigated soil samples. The mean recovery rates of tetracyclines and sulfonamides were 84.57 ± 14.92% and 65.88 ± 8.56%, respectively. Although, the organic carbon contents and cation exchange capacities of the soil samples exhibited a great variation the results of multivariate statistical analysis indicated that the metal content of soils was the major factor significantly influenced the recovery rates of the antibiotics. The sulfonamide recovery rates were positively influenced by the calcium and magnesium amounts in the soil samples, whereas tetracycline recovery rates were markedly diminished by increasing the amount of these polyvalent metals.     

Identification of trace element sources and associated risk assessment in vegetable soils of the urban-rural transitional area of Hangzhou, China

In the urban-rural transitional area of Hangzhou, China, 74 topsoil samples were collected from vegetable fields to measure the contents of arsenic (As), copper (Cu), cobalt (Co), cadmium (Cd), chromium (Cr), mercury (Hg), manganese (Mn), nickel (Ni), lead (Pb) and zinc (Zn). The combination of multivariate statistical and geostatistical methods successfully separated the contaminating elements (As, Cd, Cu, Hg, Pb and Zn) from uncontaminated elements (Co, Cr, Ni and Mn). A significant correlation was found between these uncontaminated elements and total Al2O3, Fe2O3, and SiO2 of the soils, indicating that the source of these elements was mainly controlled by soil-forming factors. On the other hand, these contaminating elements showed relatively weaker correlation and higher spatial variability, indicating that their enrichment and spatial heterogeneity were mostly affected by anthropic inputs. Through the pollution evaluation, it was found that only 30.8% of the study area did not suffer from moderate or severe pollution.     

Assessment of heavy metal pollution in wetland soils from the young and old reclaimed regions in the Pearl River Estuary, South China

Soils were sampled in three types of wetlands from the young (A) and old (B) reclaimed regions of the Pearl River Estuary. They were analyzed for total concentrations of heavy metals to investigate their distributions and pollution levels in both regions. Results showed that most heavy metals in ditch and riparian wetlands did not significantly differ from those in reclaimed wetlands in A region, while significantly lower for Cd, Cu, Pb, and Zn in reclaimed wetlands in B region, suggesting higher effects of long-term reclamation. Iron, Cr and Cu were identified as metal pollutants of primary concern and had higher contributions to the total toxic units compared to other metals. Almost all metals exceeded their lowest effect levels and Fe and Cr even exceeded the severe effect levels. Multivariate analysis shows that Fe and Mn are controlled by parent rocks and other metals mainly originate from anthropogenic source.     

Combining FAP,MAP and correlation analysis for multivariate alarm thresholds optimization in industrial process

In the real industrial process, alarm threshold optimization is an important part of alarm system rationalization. If the design of alarm threshold is unreasonable, it would result in nuisance alarms, among which the critical alarms are overwhelmed. In order to alleviate this phenomenon, we propose a method of multivariate alarm thresholds optimization to reduce the nuisance alarms. Firstly, causal relationship between process variables is constructed based on the time delay estimation method, thus we can determine the alarms propagation path and then select the optimized variables. Secondly, in order to guarantee both the process safety and correlation consistency, three factors - false alarm probability (FAP), missed alarm probability (MAP), and the correlation between the alarm information and process information – are combined to establish the objective function of the optimization process for the first time. Then, the optimal thresholds are obtained by the genetic algorithm. Finally, the validity and effectiveness of the developed method are illustrated by the Tennessee Eastman process.     

Spatially constrained clustering and upper level set scan hotspot detection in surveillance geoinformatics

We discuss upper level set (ULS) scan as a type of spatially constrained clustering in relation to two ways of imposing the spatial constraint, retrospectively versus progressively. We show that ULS scan produces the same results both ways; whereas two popular clustering techniques, single-linkage and K-means, can yield different results when spatial constraints are imposed retrospectively versus progressively. The ULS scan approach examines spatially connected components of a tessellation as a threshold is moved from the highest level (value) in the data to the lowest level. When the variable of interest on the tessellation is a rate of incidence, then a significance test is available based on binomial or Poisson null models and Monte Carlo techniques. This is a common context for detecting hotspots of diseases in epidemiological work. We also discuss an approach for extending the univariate methodology to accommodate multivariate contexts. Received: September 2005 / Revised: February 2006 This material is based upon work supported by (i) the National Science Foundation under Grant No. 0307010, (ii) the United States Environmental Protection Agency under Grant No. CR-83059301 and (iii) the Pennsylvania Department of Health using Tobacco Settlement Funds under Grant No. ME 01324. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the agencies.     

Geospatial Analysis of Climatic and Geomorphic Interactions Influencing Stream Discharge, Appalachian Mountains, USA

Streamflow values are commonly synthesized for locations where flow measurement stations are lacking or where only intermittent measurements are available. In an Appalachian Mountains dataset comprised of 29 watersheds, the most appropriate among geomorphic, geologic, and hydrogeologic datasets were selected for use in prediction of streamflow at watershed scale. A statistical model was developed using principal components analysis (PCA) and cluster analysis (CA) for. Using CA on variables derived from the PCA, an optimum set of variables was derived for predicting streamflow. Results indicate there are two categories of watersheds in the study area. The first is strongly correlated with climatic variables (precipitation, temperature, elevation, and groundwater recharge). The second is strongly correlated with two geomorphic variables (watershed slope and percentage of forested area). The spatial distribution of cluster classifications shows that watersheds dominated by the climatic component are located along the Allegheny Front while watersheds dominated by the geomorphic component are located in the Allegheny Plateau and Valley and Ridge physiographic provinces. These variations between the Allegheny Plateau and Valley and Ridge physiographic provinces suggest that, to accurately model streamflow, modeling needs be done based on natural physiographic boundaries rather than political boundaries. In this physiographic setting, elevation seems to be a major control.     

对美国格林威治湾底栖动物造成危害的潜在胁迫因子的诊断

格林威治湾是纳拉甘西特湾一处受到多种影响因子作用的城市化形成港湾。本研究鉴定了对于格林威治湾底栖动物的重要影响因素。首先利用现存数据与信息来验证水体受损情况。其次确定了影响来源,影响因素和具体影响的存在。继而探究了来源,影响因素和具体影响之间的关系。这使我们能够鉴定出最可能危害水体的影响因素。本研究评估了化学制品、营养物质和悬浮沉积物3类污染物。这种证据权重的方法表明格林威治湾主要受到富营养化相关的影响因素危害。格林威治湾的沉积物富含碳,低溶解氧浓度的情况十分常见,尤其在格林威治湾西部。底栖生物群落出现发育不良的情况,与在氧气不足情况下的预测结果吻合。尽管我们的分析表明环境中的污染物浓度可能导致有害结果的出现,我们并未在结果中检出毒性。这是由于沉积物中存在大量的有机物,这些有机物限制了污染物的生物可利用性。我们的分析还表明悬浮沉积物的影响对于湾区的大部分区域而言几乎不存在。本分析展示了诊断法步骤可以用于组织和评估影响格林威治湾生态健康的潜在影响因素。诊断法步骤对于管理受到多重因素影响的水体非常有用。
精选自Marguerite Pelletier, Kay Ho, Mark Cantwell, Monique Perron, Kenneth Rocha, Robert M. Burgess, Roxanne Johnson, Kenneth Perez, John Cardin, Michael A. Charpentier. Diagnosis of potential stressors adversely affecting benthic invertebrate communities in Greenwich Bay, Rhode Island, USA. Environmental Toxicology and Chemistry: Volume 36, Issue 2, pages 449–462, July 2017. DOI: 10.1002/etc.3562
详情请见http://onlinelibrary.wiley.com/wol1/doi/10.1002/etc.3562/full
     

A chemometric approach to the evaluation of atmospheric and fluvial pollutant inputs in aquatic systems: the Guadalquivir River estuary as a case study

To establish the quality of waters it is necessary to identify both point and non-point pollution sources. In this work, we propose the combination of clean analytical methodologies and chemometric tools to study discrete and diffuse pollution caused in a river by tributaries and precipitations, respectively.During a two-year period, water samples were taken in the Guadalquivir river (selected as a case study) and its main tributaries before and after precipitations. Samples were characterized by analysing nutrients, pH, dissolved oxygen, total and volatile suspended solids, carbon species, and heavy metals. Results were used to estimate fluvial and atmospheric inputs and as tracers for anthropic activities.Multivariate analysis was used to estimate the background pollution, and to identify pollution inputs. Principal Component Analysis and Cluster Analysis were used as data exploratory tools, while box-whiskers plots and Linear Discriminant Analysis were used to analyse and distinguish the different types of water samples.