Detection, modelling and estimation of non-linear trends by using a non-homogeneous Vasicek stochastic diffusion. Application to CO2 emissions in Morocco

This paper proposes a new stochastic model, based on a Vasicek non-homogeneous diffusion process, in which the non-linear trend coefficient (drift) depends on deterministic functions that describe the dynamic evolution of certain exogenous variables. After studying its probabilistic characteristics, and in particular the transition probability density and trend function, the associated stochastic inference based on discrete sampling in time is established using maximum likelihood methodology. This model is applied to detect, estimate and model the non-linear trend present in data corresponding to CO₂ emissions in Morocco. Energy and financial variables that affect the behaviour of this trend are also detected, and substantial improvement provided by this non-homogeneous model with respect to its corresponding homogeneous version, is confirmed.     

Teleconnection between low flows and large-scale climate indices in Texas River basins

Understanding low flow variability is critical for assessing water quality and health of riverine ecosystems in a river basin. Low flows are dependent on human water abstraction as well as the climate variability. This paper investigates the changing nature of low flows and their association with large-scale climate variability for different watersheds in the State of Texas, USA. For this purpose, we employed trend, wavelet analysis and linear as well as nonlinear correlations to identify important changes in low flow characteristics for three stream-gauging stations selected from different (i.e. Brazos, Colorado and Trinity) river basins located in Texas for the time period of 1916–1959 and 1960–2003. We also investigated the teleconnections between low flow variables and the large-scale climate indices (NINO 3.4, SOI and PDO) using cross wavelet analysis as well as their linear and non-linear correlation relationship. Our results indicated that the low flow magnitudes have shown considerable different characteristics for selected river basins during two separate time periods (1916–1959 and 1960–2003). Based on cross wavelet analysis, we identified that the low flows in selected stations of Colorado and Trinity River basins are likely to be influenced by all three large-scale climate indices. In addition to that, we identified that low flows are more nonlinearly associated with climate indices. Among the selected River basins, the stronger association between low flows and large scale climate indices are observed for Trinity River basin. The results from this study can help in better understanding of low flow hydrology and their potential relationship with large scale indices.     

General correlation analysis: a new algorithm and application

Correlation associations have been detected using Pearson’s r which aims to analyze linear correlation between two variables. It should be noted here that associations between hydro-meteorological variables are usually nonlinear. In this sense, the classical correlation analysis method cannot truly reflect the inherent associations between variables characterized by nonlinear associations. In this case, a new algorithm has been proposed by using the ideas of local correlation, detrended cross-correlation analysis and multifractals, and this novel algorithm is called as the general detrended correlation analysis. The newly-proposed algorithm was evaluated for the validity with numerically-generated time series and the real world hydrological series. The results indicate that the newly-proposed algorithm can well reflect the nonlinear and non stationary associations between two hydrological series when compared to the classical relation detection method such as the Pearson correlation analysis method, and it is particularly the case under the condition that hydrological abrupt changes of the hydrological processes occur where the classical association analysis is not appropriate.     

Speciation leads to divergent methylmercury accumulation in sympatric whitefish

Central European lake whitefish (Coregonus spp.) colonized Swiss lakes following the last glacial retreat and have undergone rapid speciation and adaptive radiation. Up to six species have been shown to coexist in some lakes, and individual species occupy specific ecological niches and have distinct feeding and reproductive ecologies. We studied methylmercury (MeHg) accumulation in sympatric whitefish species from seven Swiss lakes to determine if ecological divergence has led to different rates of MeHg bioaccumulation. In four of seven lakes, sympatric species had distinctly different MeHg levels, which varied by up to a factor of two between species. Generally, species with greater MeHg levels were smaller in body size and planktivorous, and species with lower MeHg were larger and benthivorous. While modest disparities in trophic position between species might be expected a priori to explain the divergence in MeHg, δ¹⁵N of bulk tissue did not correlate with fish MeHg in five of seven lakes. Results of a nested ANCOVA analysis across all lakes indicated that only two factors (species, lake) explained substantial portions of the variance, with species accounting for more variance (52 %) than inter-lake differences (32 %). We suggest that differences in MeHg accumulation were likely caused by diverging metabolic traits between species, such as differences in energy partitioning between anabolism and catabolism, potentially interacting with species-specific prey resource utilization. These results indicate substantial variability in MeHg accumulation between closely related fish species, illustrating that ecological speciation in fish can lead to divergent MeHg accumulation patterns.     

Total and methylmercury in a Brazilian estuary,Rio de Janeiro

Guanabara Bay, in Rio de Janeiro state, is impacted by organic matter, oil and heavy metals. The present study evaluated the total mercury (THg) and methylmercury (MeHg) concentrations and the MeHg to THg ratio (%MeHg) in water samples from different points of the bay and in 245 organisms of three different trophic levels sampled between 1990 and 2000. Dissolved mercury concentration in estuarine water samples ranged from 0.72 to 5.23 ngl(-1). THg and MeHg in mussel, ranging from 11.6 to 53.5 microg THg kg(-1) wet wt. and 4.5-21.0 microg MeHg kg(-1) wet wt., varied according to sampling point and water quality. Planktivorous fish and mussel presented similar MeHg concentrations, meanwhile THg in planktivorous fish were lower than in mussel. Carnivorous fish showed higher THg and MeHg concentrations (199.5 +/- 119.3, 194.7 +/- 112.7 microg kg(-1) wet wt. respectively) than organisms from other feeding habits and lower trophic levels. There was a significant difference in the %MeHg among trophic levels: mussel presented lower MeHg percentage (33%) than planktivorous fish (54%) and carnivorous fish (98%).     

Speciation and Determination of Inorganic Mercury and Methylmercury by Headspace Single Drop Microextraction and Electrothermal Atomic Absorption Spectrometry in Water and Fish

In this study, headspace single drop microextraction (HS‐SDME) method in combination with electrothermal atomic absorption spectrometry (ETAAS) method was developed and validated for the speciation and determination of inorganic mercury (iHg) and methylmercury (MeHg). MeHg and iHg species were reduced to volatile methylmercury hydride (CH₃HgH) and elemental mercury, respectively, in the presence of NaBH₄ and trapped onto a drop of acceptor phase in the tip of a microsyringe. Thiourea and ammonium pyrrolydinedithiocarbamate (APDC) were tested as the acceptor phase. The experimental parameters of the method such as microextraction time, temperature, NaBH₄ concentration, acceptor phase concentration, and pH of the medium were investigated to obtain distinctive conditions for mercury species. Possible interference effects have also been investigated. In order to validation of the method, analytical figures of merits such as accuracy, precision, limit of detection (LOD), limit of quantitation (LOQ), and linear working range have been evaluated. Accuracy of the method has been verified by analyzing certified reference materials (BCR 453 Tuna fish) and spiked samples. The proposed method was applied for the speciation and determination of mercury species in water and fish samples. Mercury species (MeHg and iHg) have been determined in the real samples with a relative error less than 10%.     

Spatial variability in selenium and mercury interactions in a key recreational fish species: Implications for human health and environmental monitoring

Selenium’s (Se) protective effects against mercury (Hg) toxicity have been demonstrated; however, this is seldom considered in health assessments, where dietary exposure is still evaluated by Hg concentration alone. Se:Hg ratios and selenium health benefit values (Se HBVs) offer a more comprehensive seafood safety model. Here we describe total mercury (THg), methylmercury (MeHg) and Se concentrations in fish from a Hg-polluted estuary. Spatial variation in THg, MeHg and Se was evident, though all regions maintained Se:Hg ratio values >1. Se HBV varied between regions and in one region mean negative values (−5.17) were evident. This study provides the first evidence that quoting a single all-encompassing Se HBV is not appropriate when species demonstrate strong site fidelity. It highlights the need for research into Se–Hg relationships in environments with established Hg pollution and reinforces the assertion that Se concentration be considered in assessments of human health risk to Hg exposure.     

Associations between outdoor air quality and birth weight: a geostatistical sequential simulation approach in Coastal Alentejo,Portugal

Several environmental health studies suggest birth weight is associated with outdoor air pollution during gestation. In these studies, exposure assignments are usually based on measurements collected at air quality monitoring stations that do not coincide with health data locations. So, estimated exposures can be misleading if they do not take into account the uncertainty of exposure estimates. In this article we conducted a semi-ecological study to analyze associations between air quality during gestation and birth weight. Air quality during gestation was measured using a biomonitor, as an alternative to traditional air quality monitoring stations data, in order to increase spatial resolution of exposure measurements. To our knowledge this is the first time that the association between air quality and birth weight is studied using biomonitors. To address exposure uncertainty at health locations, we applied geostatistical simulation on biomonitoring data that provided multiple equally probable realizations of biomonitoring data, with reproduction of observed histogram and spatial covariance while matching for conditioning data. Each simulation represented a measure of exposure at each location. The set of simulations provided a measure of exposure uncertainty at each location. To incorporate uncertainty in our analysis we used generalized linear models, fitted simulation outputs and health data on birth weights and assessed statistical significance of exposure parameter using non-parametric bootstrap techniques. We found a positive association between air quality and birth weight. However, this association was not statistically significant. We also found a modest but significant association between air quality and birth weight among babies exposed to gestational tobacco smoke.     

在围压条件下岩体模型应力应变关系的实验研究

含切口岩体模型在差应力作用下的应力应变关系表明:岩体不同部位的应力应变曲线按斜率变化特征可以划分为四个发展阶段。根据对切口岩石破裂过程的对比,各阶段的变形机制分别与岩体内原微裂纹闭合、孔隙和颗粒弹性变形、宏观张裂剪裂以及剪切、张-剪主破裂相对应,但各阶段的发展进程在时间、空间上却不一致,这一差异均与切口分布和岩性变化相关。最后讨论了应力应变特征与发震断层孕震过程的关系,对地震预报可能有实际意义     

Inorganic and methylmercury: do they transfer along a tropical coastal food web?

Methylmercury (MeHg) and inorganic mercury (Hg_inorg) were evaluated in the water of a Brazilian estuary, with two size classes of plankton and seven fish species of different feeding habits. Water partition coefficients (PCs) in microplankton were fourfold higher for MeHg than for Hg_inorg; and water PCs in mesoplankton were 26 times higher for MeHg than Hg_inorg. Difference between microplankton and mesoplankton MeHg bioaccumulation factor (BAF) was higher (0.60 log units) than Hg_inorg BAF (0.24 log units), indicating that trophic transfer of MeHg between planktonic organisms is more efficient than Hg_inorg transference. MeHg concentrations, proportion of mercury as MeHg and its biotransference factors (BTFs) in the microplankton, mesoplankton and fish increased with increasing trophic level while biotic concentrations of Hg_inorg and proportion of mercury as Hg_inorg decreased thus indicating that MeHg was indeed the biomagnified species of mercury. MeHg reflected the vertical trophic guilds distribution, due to the fact that the top predator fish presented the highest concentration (0.77 μg g⁻¹ d.w.), followed by the less voracious species (0.43 μg g⁻¹ d.w.); while planktivorous fish presented the lowest concentrations (0.044 μg g⁻¹ d.w.). Hg_inorg did not present the same behavior. Results suggest that feeding habits and trophic guild are important parameters, influencing biotransference and biomagnification processes.     

钢筋混凝土梁非线性动力特性试验研究

对钢筋混凝土梁非线性动力特性及其损伤程度之间关系做了试验研究。混凝土梁的非线件动力特性通过对冲击振动位移反应信号的时频分析和共振试验获得。把时频分析和共振试验两种方法结合在一起，通过分析得到合适的时频分析所用窗口宽度，再结合时频分析方法，得到各级加载后混凝土梁的振幅与频率关系曲线。通过分析混凝土梁在各级损伤加载后的振幅与频率关系曲线族，总结了损伤钢筋混凝土梁的非线性动力特性，并分析了用钢筋混凝土梁的非线性动力特性做损伤检测的可行性。     

Estimation of petrophysical parameters by linearized inversion of angle domain pre-stack data

We describe a linear Bayesian inversion method to estimate the relevant petrophysical properties of the media forming a reflecting interface from the observations of amplitude variation with incidence angle. Three main steps characterize the proposed approach:
– information from borehole logs are statistically analysed to estimate the empirical models that describe the functional relationship between petrophysical (e.g. porosity, saturation, pressure or depth) and seismic variable(P and S velocities and density);
– the pure-mode (PP) reflection coefficient is parameterized in terms of the relevant petrophysical variables and is linearized in order to implement the linear inversion;
– the sought petrophysical parameters are estimated from the seismic reflected amplitudes by applying the linearized inversion where a priori information, data and model errors and solutions are described by probability density functions.
We test the method on synthetic and real data relative to reflections from a shale/gas-sand interface where the amplitude versus angle response, besides the lithological contrast, is mainly controlled by the saturation and porosity of the sand layer. The outcomes of the linearized inversion are almost identical to those obtained by a previously developed non-linear inversion method demonstrating the applicability of the linear inversion. It turns out that the gas-sand saturation in the range 0%–95% is a poorly resolved parameter while the porosity is the best resolved parameter. The issues of robustness and resolution of the inversion are discussed either through singular value decomposition analysis or the observation of the a posteriori probability density functions.
The linear inversion algorithm, compared with the previously developed non-linear method, reduces significantly the computation time allowing for more extensive applications.     

The effect of magnetite particle size on paleointensity determinations of the geomagnetic field

The Thellier method for paleointensity determinations has been applied to prepared samples containing magnetites whose mean particle sizes range from single domain, SD, to multidomain, MD. Linear (ideal) PNRM-PTRM curves are obtained for samples containing SD and submicron magnetite particles. However, for MD particles non-linear (concave-up) PNRM-PTRM curves are observed such that a linear approximation to the lower blocking-temperature data leads to apparent paleointensities that are higher than the actual paleofield; however, the ratio of the end-points, NRM/TRM, yields the correct (laboratory) intensity. The non-linear (concave-up) PNRM-PTRM curves for the MD particles are explained in terms of the lack of symmetry of the domain-wall movements during the two heatings of the Thellier experiment. Low stabilities with respect to alternating fields and with respect to temperature cycles below magnetite's isotropic temperature are diagnostic in detecting samples most likely to exhibit non-linearities due to the MD effect.     

BURGER'S EQUATION AS A MODEL FOR THE IP PHENOMENON1

The dynamic response characterizing the induced-polarization (IP) phenomenon is modelled by a non-linear diffusion equation (Burger's equation) supplemented by relevant initial and boundary values. The analysis of the model yields a voltage step response and an impedance curve in the frequency domain which agree qualitatively with experimental measurements. Curve fits based on the model have been made in the case of electrochemical cell measurements. The diffusion coefficients estimated by means of these curves are of the same order of magnitude as those calculated using experimental measurements. The normalized transient with these diffusion coefficients agrees with observations, but probably has a shorter discharge time. We have also carried out a comparison with predictions obtained from a linear, finite diffusion layer model, thus showing that for most practical situations the nonlinear term modelling the migration effect can be neglected.     

Evaluation of seismic site factors in the Mississippi Embayment. I. Estimation of dynamic properties

Deep deposits of the Mississippi Embayment, overlying the New Madrid Seismic Zone, present unique challenges for the estimation of local site effects on propagated ground motion. Limited information is available on the dynamic properties of these deposits. This paper develops generalized depth dependent modulus degradation and damping curves specific to the embayment deposits. Depth dependent small strain damping is estimated using weak motion recordings during the Enola earthquake, 2001. Modulus degradation and damping curves are further constrained using limited laboratory test data of embayment soils at low confining pressure. At high confining pressures embayment specific data is unavailable and test data from outside the embayment is used in developing the dynamic properties. The representative modulus degradation and damping curves are used in non-linear and equivalent linear one-dimensional site response analyses. A companion paper describes a large-scale probabilistic seismic hazard analysis study in the Mississippi Embayment that integrates non-linear site effects.     

System parameters of soil foundations for time domain dynamic analysis

Soil-structure interaction analysis is usually carried out in the frequency domain, because the compliance functions of the half-space are known only in the frequency domain. Since non-linear analysis cannot be carried out in the frequency domain, a system with frequency independent parameters is used to represent the half-space soil medium so that a nonlinear analysis in the time domain becomes possible. The objective of this paper is to propose a system with lumped parameters, which are independent of frequency, to represent the half-space soil medium. The proposed frequency independent system consists of a number of real discrete structure elements; thus the existing dynamic analysis programs may be adoptable with little modification. In this paper, the parameters are found by minimizing the sum of the squares of deviations between the steady-state responses of the theoretical half-space model and those of the lumped parameter system over a specified frequency range. Once the parameters have been found, the lumped parameter system can be used in practical applications for time domain dynamic analysis of either linear or non-linear structures. In comparison with the dynamic response of the theoretical half-space model, the lumped parameter system yields satisfactory results.     

Non-crossing nonlinear regression quantiles by monotone composite quantile regression neural network,with application to rainfall extremes

The goal of quantile regression is to estimate conditional quantiles for specified values of quantile probability using linear or nonlinear regression equations. These estimates are prone to “quantile crossing”, where regression predictions for different quantile probabilities do not increase as probability increases. In the context of the environmental sciences, this could, for example, lead to estimates of the magnitude of a 10-year return period rainstorm that exceed the 20-year storm, or similar nonphysical results. This problem, as well as the potential for overfitting, is exacerbated for small to moderate sample sizes and for nonlinear quantile regression models. As a remedy, this study introduces a novel nonlinear quantile regression model, the monotone composite quantile regression neural network (MCQRNN), that (1) simultaneously estimates multiple non-crossing, nonlinear conditional quantile functions; (2) allows for optional monotonicity, positivity/non-negativity, and generalized additive model constraints; and (3) can be adapted to estimate standard least-squares regression and non-crossing expectile regression functions. First, the MCQRNN model is evaluated on synthetic data from multiple functions and error distributions using Monte Carlo simulations. MCQRNN outperforms the benchmark models, especially for non-normal error distributions. Next, the MCQRNN model is applied to real-world climate data by estimating rainfall Intensity–Duration–Frequency (IDF) curves at locations in Canada. IDF curves summarize the relationship between the intensity and occurrence frequency of extreme rainfall over storm durations ranging from minutes to a day. Because annual maximum rainfall intensity is a non-negative quantity that should increase monotonically as the occurrence frequency and storm duration decrease, monotonicity and non-negativity constraints are key constraints in IDF curve estimation. In comparison to standard QRNN models, the ability of the MCQRNN model to incorporate these constraints, in addition to non-crossing, leads to more robust and realistic estimates of extreme rainfall.     

Additive versus multiplicative models in ecologic regression

Much research in environmental epidemiology relies on aggregate-level information on exposure to potentially toxic substances and on relevant covariates. We compare the use of additive (linear) and multiplicative (log-linear) regression models for the analysis of such data. We illustrate how both additive and multiplicative models can be fit to aggregate-level data sets in which disease incidence is the dependent variable, and contrast these results with similar models fitted to individual-level data. We find (1) that for aggregate-level data, multiplicative models are more likely than additive models to introduce bias into the estimation of rates, an effect not found with individual-level data; and (2) that under many circumstances multiplicative models reduce the precision of the estimates, an effect also not found in individual-level models. For both additive and multiplicative models of aggregate-level data, we find that, in the presence of covariates, narrow confidence interval are obtained only when two or more antecedent factors are strongly related to the measured covariate and/or the exposure of primary substantive interest. We conclude that the equivalency of fitting additive versus multiplicative models in studies with individual-level binary data does not carry over to studies that analyze aggregate-level information. For aggregate data, we strongly recommend use of additive models. Supported by Grant #1 U19 EH000102 from the National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA.     

Novel theoretical insights into geomorphic process–environment relationships using simulated response curves

Robust models of geomorphic process–environment relationships are important to advance theoretical knowledge of geomorphic systems. Here, we examined a generalized additive modeling (GAM) based approach to provide new theoretical insights into process–environment relationships. More precisely, we (i) simulated the shapes of the relationships between geomorphic processes and environmental variables based on GAM and (ii) compared the shapes of the simulated response curves to (a) the hypothetical curves based on theory and (b) the response curves produced by generalized linear modeling (GLM). Hitherto, GLM was the most common technique to study the relationships between environmental gradients and geomorphic processes. The study is based on empirical cryoturbation and solifluction data and environmental variables from subarctic Finland. Our results showed that non‐linear relationships were more common than linear responses and the simulated GAM based response curves coincided more closely with the hypothetical response curves than did the response curves derived from GLM. The simulated response curves showed high potential in geomorphic hypothesis testing. In conclusion, our findings indicate that careful examination of the response curves may provide new insights into theoretical debates in the earth sciences. Copyright © 2010 John Wiley and Sons, Ltd.