Statistical evaluation of photon count rate data for nanoscale particle measurement in wastewaters

The dynamic light scattering (DLS) technique can detect the concentration and size distribution of nanoscale particles in aqueous solutions by analyzing photon interactions. This study evaluated the applicability of using photon count rate data from DLS analyses for measuring levels of biogenic and manufactured nanoscale particles in wastewater. Statistical evaluations were performed using secondary wastewater effluent and a Malvern Zetasizer. Dynamic light scattering analyses were performed equally by two analysts over a period of two days using five dilutions and twelve replicates for each dilution. Linearity evaluation using the sixty sample analysis yielded a regression coefficient R(2) = 0.959. The accuracy analysis for various dilutions indicated a recovery of 100 ± 6%. Precision analyses indicated low variance coefficients for the impact of analysts, days, and within sample error. The variation by analysts was apparent only in the most diluted sample (intermediate precision ~12%), where the photon count rate was close to the instrument detection limit. The variation for different days was apparent in the two most concentrated samples, which indicated that wastewater samples must be analyzed for nanoscale particle measurement within the same day of collection. Upon addition of 10 mg l(-1) of nanosilica to wastewater effluent samples, the measured photon count rates were within 5% of the estimated values. The results indicated that photon count rate data can effectively complement various techniques currently available to detect nanoscale particles in wastewaters.     

Spatial modeling of rat bites and prediction of rat infestation in Peshawar valley using binomial kriging with logistic regression

In this study, we propose to develop a geostatistical computational framework to model the distribution of rat bite infestation of epidemic proportion in Peshawar valley, Pakistan. Two species Rattus norvegicus and Rattus rattus are suspected to spread the infestation. The framework combines strengths of maximum entropy algorithm and binomial kriging with logistic regression to spatially model the distribution of infestation and to determine the individual role of environmental predictors in modeling the distribution trends. Our results demonstrate the significance of a number of social and environmental factors in rat infestations such as (I) high human population density; (II) greater dispersal ability of rodents due to the availability of better connectivity routes such as roads, and (III) temperature and precipitation influencing rodent fecundity and life cycle.     

郑州市 PM2．5和 PM10质量浓度变化特征分析

根据郑州市2013年PM2．5和PM10颗粒物连续自动监测数据,对郑州市各国控站点的PM2．5和PM10的达标情况、变化趋势等进行探讨分析。结果表明：2013年郑州市PM10和PM2．5的年均质量浓度均超过了新标准规定的年均值二级标准限值。 PM10和PM2．5月均值峰值出现在1月和10月,谷值出现在8月,各月PM2．5的超标天数都大于PM10。PM10和PM2．5冬季的日均值浓度明显高于其他季节,呈双峰型,夜晚浓度整体高于白天;PM2．5春、夏、秋三季日变化呈单峰型,PM10夏季和秋季呈单峰型,春季呈双峰型。 PM2．5和PM10日均值有着非常显著的线性相关关系,PM2．5和PM10浓度的比值（p）10月最高。     

Analysis of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China from 1982 to 2010

Drought is a complex natural phenomenon that can cause reduced water supplies and can consequently have substantial effects on agriculture and socioeconomic activities. The objective of this study was to gain a better understanding of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China. The Vegetation Condition Index (VCI) dataset calculated from NOAA/AVHRR images from 1982 to 2010 was used to analyse the spatial-temporal variation characteristics of vegetative drought in China. This study also examined the trends in meteorological factors and their influences on drought using monitoring data collected from 686 national ground meteorological stations. The results showed that the VCI appeared to slowly rise in China from 1982 to 2010. From 1982 to 1999, the VCI rose slowly. Then, around 2000, the VCI exhibited a severe fluctuation before it entered into a relatively stable stage. Drought frequencies in China were higher, showing a spatial distribution feature of “higher in the north and lower in the south”. Based on the different levels of drought, the frequencies of mild and moderate drought in four geographical areas were higher, and the frequency of severe drought was higher only in ecologically vulnerable areas, such as the Tarim Basin and the Qaidam Basin. Drought was mainly influenced by meteorological factors, which differed regionally. In the northern region, the main influential factor was sunshine duration, while the other factors showed minimal effects. In the southern region and Tibetan Plateau, the main influential factors were sunshine duration and temperature. In the northwestern region, the main influential factors were wind velocity and station atmospheric pressure.     

长光程大气自动监测中异常数据的分析及处置

长光程大气自动监测系统部件较多,结构复杂,中心站对子站监控通过在线方式完成,因此对系统中故障的判断和排除有一定难度。通过对中心站调出的异常数据进行诊断和分析,帮助操作者提升对系统的了解和对异常数据处理的技能。     

降雨对噪声自动监测数据的影响分析

选取北京市近5年夏半年(4—9月)的降雨数据及相关噪声自动监测小时等效声级,利用数学统计软件进行有雨-无雨声级差异性分析、声级-降雨相关性分析及平均声级-雨量变化趋势分析等,提出降雨确实对噪声自动监测小时数据有一定贡献,不同雨量对不同功能区噪声影响不同,建议噪声自动监测系统建设时应考虑雨噪声影响,以保证对声环境质量评价的科学性和准确性。     

Comparing the natural variation of oribatid mite communities with their changes associated with anthropogenic disturbance

Several organism communities serve as ecological and environmental indicators to detect changes in human-impacted habitats. However, the composition of indicator communities may vary because of natural variation in addition to the changes associated with human disturbances. This meta-analysis compared the natural variation of oribatid mite assemblages, a good indicator model group in soil ecosystems, with their deviations associated with disturbance using diversity and dissimilarity indices and three human disturbance types. Literature data were collected about oribatid mite assemblages from natural and disturbed habitats. Human disturbances consisted of agriculture, heavy metal pollution and forest management. Biodiversity indices (Shannon and Berger-Parker) and dissimilarity indices (Jaccard and Bray-Curtis) were calculated among natural habitats and between disturbed and control habitats at the species and genus level. We considered oribatid mite assemblages as effective community-level indicators when the methods separated the differences of assemblages between disturbed and control habitats from their varieties among natural habitats. In addition, the study analysed the correlation between these indices and environmental variables of the study sites. Oribatid mite assemblages performed high indication strength with Bray-Curtis index for agricultural disturbances since dissimilarity values between disturbed and control habitats were as high as between different natural habitats and higher than among the same types of natural habitats. Genus-level values showed similar results to the species level. This approach may be useful to test the effectiveness of other indicator groups and methods.     

A method to combine non-probability sample data with probability sample data in estimating spatial means of environmental variables

In estimating spatial means of environmental variables of a region from datacollected by convenience or purposive sampling, validity of the results canbe ensured by collecting additional data through probability sampling. Theprecision of the estimator that uses the probability sample can beincreased by interpolating the values at the nonprobability sample points tothe probability sample points, and using these interpolated values as anauxiliary variable in the difference or regression estimator. Theseestimators are (approximately) unbiased, even when the nonprobability sampleis severely biased such as in preferential samples. The gain in precisioncompared to the estimator in combination with Simple Random Samplingis controlled by the correlation between the target variable andinterpolated variable. This correlation is determined by the size (density)and spatial coverage of the nonprobability sample, and the spatialcontinuity of the target variable. In a case study the average ratio of thevariances of the simple regression estimator and estimator was 0.68for preferential samples of size 150 with moderate spatial clustering, and0.80 for preferential samples of similar size with strong spatialclustering. In the latter case the simple regression estimator wassubstantially more precise than the simple difference estimator.     

The analysis of monitoring data with the aid of time-series analysis

Methods derived from time-series analysis are proposed for processing monitoring data. The necessity for the use of these methods is demonstrated. In a case study time-series analysis was applied to assess the impact of the closure of the Grevelingen estuary (S. W. Netherlands) in 1971 on a local wintering population of Oystercatchers (Haematopus ostralegus) in the adjacent Oosterschelde estuary.Communication No. 328 of the Delta Institute for Hydrobiological Research.     

Estimation of nonpoint source loadings with data obtained from limited sampling programs

The feasibility of estimating nonpoint source loadings with data obtained from limited sampling programs was analyzed in conjunction with a study of sediment and nutrient loadings in a Swedish river basin. The study showed that different loading estimation methods can yield significantly different results, even if sampling during events (e.g. peak flows) occurs. This was particularly true for the temporal distribution of the estimated loadings. The estimated spatial distribution of loadings in the monitored subbasins was more independent of the applied estimation technique. Theoretical calculations showed that sampling strategies with evenly spaced sampling intervals may systematically over- or underestimate the true loading.The study basin was characterized by a pronounced snowmelt period and partly erosion-controlled nutrient loadings. Guidelines for the estimation of nonpoint loadings in such basins are summarized in a matrix. Factors influencing the choice of estimation method include the characteristics of the collected data, the relative influence of point sources, and the desired detail of loading estimates. Possible correlations between flow and concentration, and the presence of extreme events (and whether or not the events were sampled), also determine the appropriateness of the different methods.     

Seasonal variation of different microorganisms with nickel and cadmium in the industrial wastewater and agricultural soils

Wastewater and soil samples were collected from the industrial area of Ghaziabad City, India from January 2005 to December 2007 and were analyzed for the presence of heavy metals by atomic absorption spectrophotometry. Test samples revealed high levels of Fe, Cr, Cu, Ni, Zn, and Cd as 967.03, 34.63, 27.97, 19.7, 16.70, and 3.20 mg/L of wastewater, respectively. The concentrations of inorganic minerals were higher in the soil samples irrigated with wastewater. Total coliforms were found to be maximum (1,133 × 10⁴ most probable number per 100 mL) during spring and summer followed by winter and postmonsoon in the wastewater samples. The microbial count in soil as well as in wastewater decreases as the metal concentration increases. The concentration 200 μg/mL of nickel and cadmium inhibits majority of the population, while, at some points, it inhibits 100% of the population. The exponential decay model for microbial count at the increasing metal concentrations indicate that asymbiotic N₂ fixers were best fitted to the model. In all the seasons, the order of decline in terms of exponential decay of the population of different microbial groups in soil was asymbiotic N₂ fixers > actinomycetes > fungi > aerobic heterotrophic bacteria. The different microbial groups that have different values of slope in different seasons indicate that the resistant population of microorganisms was variable with seasons.     

Analysis of diazinon monitoring data from the Sacramento and Feather River watersheds: 1991-2001

The objectives of this study were to: (1) analyzehistorical diazinon water column monitoring data frominconsistent monitoring programs in mainstem and tributary sitesin the Sacramento and Feather River watersheds from 1991 to 2001to assess possible spatial and temporal trends and (2) determinethe probability of measured diazinon concentrations by site orsimilar pooled sites exceeding various proposed effectsbenchmarks such as Water Quality Criteria and 10th centilesderived from species sensitivity distributions proposed as targetconcentrations for Total Maximum Daily Loads (TMDLs). An analysisof diazinon monitoring data from both fixed and rain eventsampling from the Sacramento/Feather River watersheds from 1991to 2001 showed that 90th centiles for 27 different mainstemand tributary sites ranged from 12 to 14,897 ng L^-1. The 90th centiles were generally higher at tributary sites (as compared to mainstem sites) during rain event sampling prior to 1995. A comparison of rain event samples for similar sites sampled in 1994 and 2000 showed that 90th centiles were lower in seven of eight sites in 2000. A comparison of pooled mainstemsites between 1994 and 2000 for rain event data showed a lower90th centile value for 2000; 90th centiles were alsolower in 2000 at all pooled tributary sites and all sites whendata from a highly influential site was removed. For varioussite designations (all sites, pooled mainstem sites etc.) theprobability of exceeding the acute and chronic diazinon targetsdeveloped by California Department of Fish and Game decreasedfrom 1994 to 2000. These data clearly show progress in the 6 yrperiod in reducing environmental concentrations of diazinon.Probability of exceeding the 10th centile targets based onspecies sensitivity distributions for arthropods (the mostsensitive taxa to diazinon exposure) was similar and fairly lowbetween years; the highest percent probability of exceedance forany site designation was 20%.Results from a two-way ANOVA using individual measurementsfrom all sites sampled showed a significant decrease during rainevents between 1994 and 2000, although the decrease was notequivalent for all sites. Sources of uncertainty identified inthe analysis of rain event data from 1994 and 2000 wereinconsistent frequency of sampling during rain events for eachyear, unknown definition of rain events between the two years andnon-defined measurement point within the hydrograph of rainevents sampled in each year. Analysis of diazinon trends fromfixed sampling was limited due to lack of yearly data by site;therefore, only parametric analysis could be conducted. Based onparametric analysis of diazinon monitoring data from fixedsampling sites, the percent detected concentrations were greaterthan 20% for 12 tributary sites and 5 mainstem sites fromsamples collected during January-March. On the average over allsites and months, diazinon concentrations have decreased at fixedsampling sites in the Sacramento/Feather River watershed from1991 to 2001.     

Delineating the spatial-temporal variation of air pollution with urbanization in the Belt and Road Initiative area

The rapid urbanization in the Belt and Road Initiative (BRI) area has aggravated the cross-regional pollution of PM_2.5 and aroused concern about the conflicts between urban development and air quality. This study aims to examine the spatial-temporal PM_2.5 variations in the BRI region, in which area many countries are undergoing rapid urbanization and the main field of future urbanization, to delineate the driving mechanism of PM_2.5 accumulation or dissipation. Previous studies have analyzed the PM_2.5 distribution at the national level, providing limited information regarding regional heterogeneity in urbanization and PM_2.5 concentrations within each country. Additionally, the regional differences in the driving mechanisms of urbanization factors on PM_2.5 concentrations have not been thoroughly investigated within the BRI areas. In this study, remote sensing raster data was combined with geographic grid units to examine variations in urbanization and PM_2.5 within the BRI region, identifying “typical regions” where urbanization could enhance PM_2.5 accumulation. The main results are as follows: i) The spatial autocorrelation of urbanization and PM_2.5 concentrations has gradually strengthened, showing consistent high-value distributions in the North China Plain, Ganges Plain and indicating a synergistic growth among emerging developing regions such as China, India, and the Persian Gulf Coast. ii) The correlation between urbanization and PM_2.5 concentrations exhibited a distinct trend of differentiation within the BRI regions. The influence of urbanization on PM_2.5 changed from agglomeration to dispersion, forming a “typical region” category composed of ten countries, including China, India, and Morocco. iii) The three main urbanization-related factors for PM_2.5 accumulation in the “typical regions” for 2005–2016 were energy pollution emission, economic activities, and human activities. By 2023, the effects of energy pollution and economic activities are expected to converge in some “typical region” countries. Targeted urban strategies and governance actions based on the different driving-types of “typical regions” in BRI have been proposed to coordinate relationship between urban construction and atmospheric environmental protection.     

Seasonal variation of nonylphenol concentrations and fluxes with influence of flooding in the Daliao River Estuary, China

Nonylphenol is an endocrine disruptor with harmful effects including feminization and carcinogenesis on various organisms. This study aims to investigate the distribution and ecological risks of nonylphenol in the Daliao River Estuary, China. Nonylphenol, together with other phenolic endocrine disruptors (bisphenol A, 4-t-butylphenol, 4-t-octylphenol, and 2,4-dichlorophenol), was detected in surface water and sediment on three cruises in May 2009, June 2010, and August 2010, respectively. A large flooding occurred during our sampling campaign in August and its effect on nonylphenol concentrations and fluxes in the estuary was therefore evaluated. The results showed that nonylphenol with a concentration range between 83.6–777 ng l^?1 and 1.5–456 ng?g^?1 dw in surface water and sediment was the most abundant among the phenolic compounds, accounting for 59.1–81.0 and 79.9–92.1 % of the total phenolic concentration in surface water and sediment, respectively. The concentrations recorded in May and June were comparable, whereas those in August were considerably higher, mainly due to the flush of flooding. The flooding also caused a 50 times increase in nonylphenol flux from the estuary into the adjacent Bohai Sea. Nonylphenol concentrations in the estuary have exceeded the threshold level of undesirable effects with a potential risk of harm to local species, especially benthic organisms.     

Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/MODIS satellite data

The most commonly used normalized difference vegetation index (NDVI) from remote sensing often fall short in real-time drought monitoring due to a lagged vegetation response to drought. Therefore, research recently emphasized on the use of combination of surface temperature and NDVI which provides vegetation and moisture conditions simultaneously. Since drought stress effects on agriculture are closely linked to actual evapotranspiration, we used a vegetation temperature condition index (VTCI) which is more closely related to crop water status and holds a key place in real-time drought monitoring and assessment. In this study, NDVI and land surface temperature (T _s) from MODIS 8-day composite data during cloud-free period (September–October) were adopted to construct an NDVI–T _s space, from which the VTCI was computed. The crop moisture index (based on estimates of potential evapotranspiration and soil moisture depletion) was calculated to represent soil moisture stress on weekly basis for 20 weather monitoring stations. Correlation and regression analysis were attempted to relate VTCI with crop moisture status and crop performance. VTCI was found to accurately access the degree and spatial extent of drought stress in all years (2000, 2002, and 2004). The temporal variation of VTCI also provides drought pattern changes over space and time. Results showed significant and positive relations between CMI (crop moisture index) and VTCI observed particularly during prominent drought periods which proved VTCI as an ideal index to monitor terminal drought at regional scale. VTCI had significant positive relationship with yield but weakly related to crop anomalies. Duration of terminal drought stress derived from VTCI has a significant negative relationship with yields of major grain and oilseeds crops, particularly, groundnut.     

Statistical modeling of restricted pollutant data sets to assess compliance with air quality criteria

Three statistical models are used to predict the upper percentiles of the distribution of air pollutant concentrations from restricted data sets recorded over yearly time intervals. The first is an empirical quantile-quantile model. It requires firstly that a more complete date set be available from a base site within the same airshed, and secondly that the base and restricted data sets are drawn from the same distributional form. A two-sided Kolmogorov-Smirnov two-sample test is applied to test the validity of the latter assumption, a test not requiring the assumption of a particular distributional form. The second model represents the a priori selection of a distributional model for the air quality data. To demonstrate this approach the two-parameter lognormal, gamma and Weibull models and the one-parameter exponential model were separately applied to all the restricted data sets. A third model employs a model identification procedure on each data set. It selects the best fit model.     

Seasonal variation in physicochemical properties of coastal waters of Kalpakkam, east coast of India with special emphasis on nutrients

A study pertaining to the seasonal variation in physicochemical properties of the coastal waters was carried out at Kalpakkam coast for a period of 1 year (February 2006 to January 2007). It revealed that the coastal water was significantly influenced by freshwater input during North East (NE) monsoon and post-monsoon periods. Concentration of all the nutrients and dissolved oxygen (DO) was relatively high during the NE monsoon, whereas, salinity and chlorophyll-a (chl-a) were at their minimum level during this period. Phytoplankton production peak was observed in summer during which a typical marine condition prevailed. The present observed values of nitrate, phosphate, silicate, and turbidity are significantly high (five to ten times) compared to that of the pre-Tsunami period from this coast. Relatively low DO and chl-a concentration was noticed during the post-Tsunami period. A notable feature of this study is that though nutrient concentration in the coastal waters during post-Tsunami period has increased significantly, turbidity, the most single dominating factor, was found to adversely affect the phytoplankton production during post-Tsunami period as reflected by relatively low chl-a concentration. Thus, the post-Tsunami period may result in a change in coastal biodiversity pattern concomitant with change in coastal water quality.     

Historical variation of elements with respect to different geochemical fractions in recent sediments from Pigeon Lake, Alberta, Canada

Geochemical analysis of elements and organic matter were conducted on vertical profiles of the recent sediments from Pigeon Lake, Alberta, Canada, to determine historical variations in elemental content of the sediments as related to their geochemical fractions. The elements are grouped according to their affinity with different geochemical fractions, by using cluster analysis and sequential extraction experiments. As a result, four elemental fractions were identified: clastic mineral detritus; carbonate; organic; and elements that show less similarity to the previous groups perhaps due to anthropogenic input or the influence of other fractions, such as oxyhydroxides. Following the identification of geochemical fractions in the sediments, a three-step normalizing method was applied using parameters that represent each geochemical fraction. These normalizing techniques appear to be important in verifying whether the variation of elements is indeed the result of anthropogenic and/or natural activities. The normalized data are correlated with the recent history of human activity and natural events near Pigeon Lake. Given the age of the lake sediments, this correlation indicates that the depth profiles of elements after being normalized to the organic and carbonate fractions reflect the variation of detrital input into the lake. However, the former mainly corresponds to the coarse-grained clastic minerals originating from high-energy erosion as the result of natural events (e.g., flooding), whereas the latter corresponds to the low-energy erosion of the fine particles (enriched in lithophile elements) due to deforestation in the drainage basin. Normalizing to the clastic mineral detritus fraction results in the increase of heavy metals in the uppermost part of the sediment profiles, which coincides with industrial activities during the past two decades in central Alberta. However, the concentration of these elements is negligible, as compared to the quantities released by geogenic processes (erosion).     

Phytoplankton variation and its relationship with the environment in Xiangxi Bay in spring after damming of the Three-Gorges, China

Following the completion of the Three-Gorges Dam, there was a strong spring phytoplankton bloom in Xiangxi Bay of Three-Gorges Reservoir. However, our knowledge of relationship between spring phytoplankton bloom and environmental factors was still limited. In this study, phytoplankton species composition, biomass, chlorophyll a concentration and environmental factors at two sampling sites in Xiangxi Bay were investigated during 25 March to 18 May 2007. The Xiangxi Bay was eutrophic with the lowest values of total nitrogen and total phosphorus being 0.80 and 0.07?mg/L, respectively. A total of 66 algal taxa belonging to seven phyla and 45 genera were identified. Peridiniopsis niei Liu was the most abundant species which preferred standing water. Canonical correspondence analysis and correlation analysis revealed that nitrate was significantly associated with phytoplankton growth. The phytoplankton chlorophyll a concentration was correlated significantly negatively with nitrate concentration, and nitrate concentration was very low during bloom periods. Heavy rainfall was the main reason of phytoplankton chlorophyll a concentration and biomass decreasing and blooms disappearing. In addition, heavy rainfall also brought more nitrate into the Bay which provided sufficient nitrogen source for blooms occurring again.     

Lichen biomonitoring of metals in the San Rossore park: Contrast with previous pine needle data

The epiphytic lichen Parmelia caperata collected in San Rossore park was analyzed for trace elements. Metal deposition in the park was found to be low throughout the year. A slight increase in Cu, Co, and Ni occurred at the east-southeastern edge of the park adjacent to Pisa. Lichens ware not affected by the sea-spray which has destroyed the coastal vegetation. The contrast with the results of previous pine needle biomonitoring is discussed.