An assessment of coastal land-use and land-cover change from 1974–2008 in the vicinity of Mobile Bay,Alabama

The purpose of this research is to quantify and assess geospatial land-use and land-cover (LULC) changes in the coastal counties of Mobile and Baldwin, Alabama using nine Landsat images from 1974–2008. A study-specific classification scheme was devised comprising upland herbaceous, upland forest, non-woody and woody wetlands, open water, and urban categories. Upland forest was the most dominant terrestrial cover type. Wetlands averaged 17% and urban averaged 7%. A majority of the urban expansion occurred between 1974 and 1979 (26%). Thirty-four percent of the 2008 urban areas were upland forest in 1974. Watershed-scale analysis of Three Mile Creek and D’Olive Bay highlights the temporal and spatial differences of urbanization for watersheds found within the same region. This study is a Gulf of Mexico Alliance (GOMA) Application Pilot project that uses NASA data products to benefit coastal environmental managers and community members. Results have led to increased effectiveness of coastal conservation decision-making, increased understanding of post-hurricane LULC change, continued research on habitat change impacts, and contributed to timely conservation planning efforts. This study has benefited the development of watershed management plans by the Mobile Bay National Estuary Program, which is especially important given projected climate change.     

Selecting a binary Markov model for a precipitation process

This paper uses rth-order categorical Markov chains to model the probability of precipitation. Several stationary and non-stationary high-order Markov models are proposed and compared using BIC. The number of parameters increases exponentially by adding the Markov order. Several classes of high-order Markov models are proposed which their increase of number of parameters are modest. For example models that use the number of precipitation days in a period prior to date, temperature of the previous day and sines/cosines periodic functions (to model the seasonality) are considered. The theory of partial likelihood is used to estimate the parameters. Parsimonious non-stationary first order Markov models with few seasonal terms are found optimal using BIC and temperature does not turn out to be a useful covariate. However BIC seems to underestimate the number of seasonal terms. We have also compared the results with AIC in some cases which tends to pick parsimonious models with more seasonal terms and higher order. We also show that ignoring seasonal terms result in picking higher order Markov chains. Finally we apply the methods to build confidence intervals for the probability of periods with no precipitation or low number of precipitation days in Calgary using historical data from 1980 to 2000.     

Hierarchical space-time models for fire ignition and percentage of land burned by wildfires

Policy responses for local and global fire management as well as international green-gas inventories depend heavily on the proper understanding of the annual fire extend as well as its spatial variation across any given study area. Proper statistical models are important tools in quantifying these fire risks. We propose Bayesian methods to model jointly the probability of ignition and fire sizes in Australia and New Zeland. The data set on which we base our model and results consists of annual observations of several meteorological and topographical explanatory variables, together with the percentage of land burned over a grid with resolution of 1° across Austalia and New Zealand. Our model and conclusions bring improvements on the results reported by Russell-Smith et al. in Int J Wildland Fire, 16:361–377 (2007) based on a similar data set.     

Using data mining to predict soil quality after application of biosolids in agriculture

The amount of biosolids recycled in agriculture has steadily increased during the last decades. However, few models are available to predict the accompanying risks, mainly due to the presence of trace element and organic contaminants, and benefits for soil fertility of their application. This paper deals with using data mining to assess the benefits and risks of biosolids application in agriculture. The analyzed data come from a 10-yr field experiment in northeast France focusing on the effects of biosolid application and mineral fertilization on soil fertility and contamination. Biosolids were applied at agriculturally recommended rates. Biosolids had a significant effect on soil fertility, causing in particular a persistent increase in plant-available phosphorus (P) relative to plots receiving mineral fertilizer. However, soil fertility at seeding and crop management method had greater effects than biosolid application on soil fertility at harvest, especially soil nitrogen (N) content. Levels of trace elements and organic contaminants in soils remained below legal threshold values. Levels of extractable metals correlated more strongly than total metal levels with other factors. Levels of organic contaminants, particularly polycyclic aromatic hydrocarbons, were linked to total metal levels in biosolids and treated soil. This study confirmed that biosolid application at rates recommended for agriculture is a safe option for increasing soil fertility. However, the quality of the biosolids selected has to be taken into account. The results also indicate the power of data mining in examining links between parameters in complex data sets.     

Spatial variations of human health risk associated with exposure to chlorination by-products occurring in drinking water

During disinfection, chlorine reacts with organic matter present in drinking water and forms various undesirable chlorinated by-products (CBPs). This paper describes a study of the spatial variability of human health risk (i.e., cancer effects) from CBP exposure through drinking water in a specific region. The region under study involves nine drinking water distribution systems divided into several zones based on their characteristics. The spatial distribution of cancer risk (CR) was estimated using two years of data (2006-2008) on various CBP species. In this analysis, trihalomethanes (THMs) and haloacetic acids (HAAs) served as surrogates for CBPs. Three possible routes of exposure (i.e., via ingestion, inhalation and dermal contact) were considered for each selected compound. The cancer risk assessment involved estimating a unit risk (R(T)) in each zone of the selected distribution systems. A probabilistic analysis based on Monte Carlo simulations was employed. Risk assessment results showed that cancer risk varied between systems, but also within individual systems. As a result, the population of the same region was not exposed to the same risk associated with CBPs in drinking water. Unacceptable levels (i.e., R(T) > 10(-4)) for the estimated CR were determined for several zones in the studied region. This study demonstrates that a spatial-based analysis performed to represent the spatial distribution of risk estimates can be helpful in identifying suitable risk management strategies. Suggestions for improving the risk analysis procedure are also presented.     

舟山近海水体和沉积物中多环芳烃分布特征

2012年,每两个月采集1次浙江省舟山近海水样及表层沉积物样品,检测16种多环芳烃(PAHs)含量.结果表明,舟山近海水体和沉积物中PAHs均存在显著的时空差异性,水体ΣPAHs浓度范围为382.3~816.9 ng·L-1,平均值为552.5ng·L-1;沉积物ΣPAHs含量范围为1017.9~3047.1 ng·g-1,平均值为2022.4 ng·g-1.空间分布上,水体ΣPAHs最大值和最小值分别出现在小洋山和燕窝山海域,而沉积物中分别出现在小洋山和朱家尖南沙海域.时间变化上,水体ΣPAHs最大值和最小值出现在10月和6月,而沉积物中分别出现在8月和6月.PAHs污染来源主要是油类排放和木柴、煤燃烧的共同叠加作用.结合PAHs的生物阈值,利用超标系数法评价舟山近海PAHs的生态风险,结果表明,ΣPAHs存在较低几率的潜在风险,但苊单体存在较高几率的潜在风险,二氢苊和芴可能存在生态风险.对水-沉积物界面PAHs的富集研究表明,舟山近海沉积物中富集了大量PAHs,富集系数(Kd值)岱山岛大于舟山本岛,并与沉积物的PAHs含量分布一致.     

MBR处理腈纶废水的效能及微生物群落结构分析

采用序批式膜生物反应器(SBMBR)处理腈纶聚合废水和丙烯腈废水,考察了不同废水比例和运行条件下反应器的运行效果,并采用PCR-DGGE技术分析了反应器内微生物群落结构的变化.结果表明,SBMBR对腈纶废水具有较好的处理效果,碳源和碱度不足是影响脱氮效果的两个主要因素;在水力停留时间为24 h,90 min缺氧/150 min好氧交替运行的条件下,COD、NH+4-N和TN的平均去除率分别为82.5%、98.7%和74.6%,出水水质可以稳定达到国家污水综合排放标准(GB8978-1996)的一级标准;PCR-DGGE分析结果表明,反应器内微生物多样性与进水水质和运行条件密切相关,微生物群落呈现出较明显的演替过程;通过克隆测序,从9个污泥样品中成功鉴定获得22种微生物的16S r DNA序列,并筛选出7种降解腈纶废水的优势菌种.     

电芬顿反应原理研究进展

电芬顿法作为一种新型电化学氧化技术,因其强氧化能力以及环境友好的特性引起了国内外的广泛关注.电芬顿反应通过电极产生H2O2和（或）Fe2＋,进行一系列反应生成具有强氧化能力的羟基自由基·OH.为了提高电子传递速度,产生更多芬顿试剂,国内外学者研发出不同类型的电芬顿反应器.通过分析电芬顿反应中·OH浓度与有机物浓度间的关系,大多数学者在准一级反应动力学基础上确定了反应常数,然而,目前其应用仍只停留在实验室阶段,电芬顿技术的效率及机理仍需要进一步研究改进.     

鱼腥藻在满江红-鱼腥藻共生体系去除水中铀时的作用

通过分离有藻满江红中的鱼腥藻,获得无藻满江红和鱼腥藻.采用水培试验的方法分别研究了无藻满江红、有藻满江红和鱼腥藻对水中铀的去除行为,并采用红外光谱技术分析了它们富集铀前后化学基团的变化.结果表明,对于初始浓度分别为2.5和5.0 mg·L-1的铀溶液,在有藻满江红的作用下,分别经过27和36 d生物富集后浓度能降低至GB 23727-2009规定的0.05 mg·L-1排放标准以下,而在无藻满江红和鱼腥藻的作用下,铀浓度无法达到排放标准.相对于无藻满江红,鱼腥藻提高了有藻满江红对水中铀的富集量、富集系数及对铀的抗胁迫能力,从而提高了有藻满江红对水中铀的去除效率.红外分析表明,在富集铀后,与无藻满江红相比,有藻满江红体内出现了芳环和醇类或苷类化合物,而这些新的物质是鱼腥藻在富集铀的过程中产生的,其可能促进了有藻满江红对铀的富集.