Abstract In this research, an interval-fuzzy possibilistic programming (IFPP) method was developed by integrating interval parameter programming (IPP), fuzzy possibilistic programming (FPP), and a fuzzy expected value equation within a general optimization framework. The developed IFPP method can not only effectively address uncertainties presented in terms of crisp intervals and fuzzy-boundary intervals in both the objective function and constraints, but it can also improve the traditional fuzzy mathematical programming by choosing the credibility degree of constraints based on the decision maker’s preference and avoiding complicated intermediate models with high computational efficiency. The developed method was applied to identify optimal placements for best management practices (BMPs) to control nutrient pollution in the Baoxianghe River watershed in China, in which a GIS-aided export coefficient model (ECM) was employed to estimate the phosphorus loads from a nonpoint source (NPS). The optimization results showed that the hybrid approach could be used to generate a series of implementation levels for BMPs under multiple credibility levels, ensuring that the NPS phosphorus loads discharged into rivers reduce to an allowable level and considering a proper balance between expected system costs and risks of violating the constraints. Relaxing the sub-basin discharge permits suggests a global discharge permit for the entire watershed, which may allow managers to shift BMP implementation among sub-basins to meet the overall discharge permit at a lower cost.
Abstract This research developed an integrated simulation-optimization method (ISOM). This model incorporated eutrophication modeling, water resource allocation and trophic status assessment within a general modeling framework. In ISOM, the simulation effort [i.e. environmental fluid dynamics code (EFDC)] was used to forecast the concentration of water quality variables to evaluate the lake trophic status under various conditions, while the optimization studies were used to identify the optimal water transfer strategies from a number of alternatives. To solve the model, a surrogate-based genetic algorithm (GA) was proposed in which the support vector regression (SVR) was used to create a set of easy-to-use and rapid-response surrogates for identifying the functional relationships between water transfer and lake trophic status. By replacing the EFDC and the corresponding trophic state index (TSI) equations with the surrogates, the computation efficiency could be improved. The developed ISOM was applied to the inter-basin water transfer management of the Niulanjiang-Dianchi Water Transfer Project (NDWTP) to support the eutrophication restoration of Lake Dianchi. Optimal water transfer schemes for three different remediation durations were generated from the model. The results demonstrated that NDWTP could exert a positive influence on the ecology and environment of Lake Dianchi, and that the trophic level for the Lake Dianchi could be effectively mitigated through the adoption of optimal water transfer schemes.
Coastal areas are land–sea transitional zones with complex natural and anthropogenic disturbances. Microorganisms in coastal sediments adapt to such disturbances both individually and as a community. The microbial community structure changes spatially and temporally under environmental stress. In this study, we investigated the microbial community structure in the sediments of Hangzhou Bay, a seriously polluted bay in China. In order to identify the roles and contribution of all microbial taxa, we set thresholds as 0.1% for rare taxa and 1% for abundant taxa, and classified all operational taxonomic units into six exclusive categories based on their abundance. The results showed that the key taxa in differentiating the communities are abundant taxa (AT), conditionally abundant taxa (CAT), and conditionally rare or abundant taxa (CRAT). A large population in conditionally rare taxa (CRT) made this category collectively significant in differentiating the communities. Both bacteria and archaea demonstrated a distance decay pattern of community similarity in the bay, and this pattern was strengthened by rare taxa, CRT and CRAT, but weakened by AT and CAT. This implied that the low abundance taxa were more deterministically distributed, while the high abundance taxa were more ubiquitously distributed.
The initial aggregation kinetics of hematite nanoparticles (NPs) that were conjugated with two model globular proteins—cytochrome c from bovine heart (Cyt) and bovine serum albumin (BSA)—were investigated over a range of monovalent (NaCl) and divalent (CaCl2) electrolyte concentrations at pH 5.7 and 9. The aggregation behavior of Cyt-NP conjugates was similar to that of bare hematite NPs, but the additional electrosteric repulsion increased the critical coagulation concentration (CCC) values from 69 mM to 113 mM in NaCl at pH 5.7. An unsaturated layer of BSA, a protein larger than Cyt, on hematite NPs resulted in fast aggregation at low salt concentrations and pH 5.7, due to the strong attractive patch-charge interaction. However, the BSA-NP conjugates could be stabilized simply by elevating salt concentrations, owing to the screening of the attractive patch-charge force and the increasing contribution from steric force. This study showed that the aggregation state of protein-conjugated NPs is proved to be completely switchable via ionic strength, pH, protein size, and protein coverage. Macroscopic Cu(II) sorption experiments further established that reducing aggregation of hematite NPs via tailoring ionic strength and protein conjugation could promote the metal uptake by hematite NPs under harsh conditions.
Identifying the sanitation efficacy of reducing fecal contaminations in the environment is important for evaluating health risks of the public and developing future management strategies to improve sanitation conditions. In this study, we estimated the fecal coliforms (FC) entering into the environment in 31 provinces in China under three sanitation scenarios. Our calculation results indicated that, the current FC release is disparate among regions, and the human releases in the rural regions were dominant, accounting for over 90% of the total human releases. Compared with the human release, the FC release from the livestock was of similar magnitude, but has a quite different spatial distribution. In China Women's Development Program, the Chinese government set the target to make over 85% of the population in the rural access to the toilets in 2020. If the target set by the Chinese government is achieved, a decrease of 34% (12-54%) in the FC releases would be anticipated. In the future, the improvement in sanitation and accesses to the safe drinking water in the less developed regions, such as Tibet, Qinghai, and Ningxia, should be considered as a priority. (c) 2016 Elsevier Inc. All rights reserved.
In the last four decades, various techniques including spectroscopic, wet chemical and mass spectrometric methods, have been developed and applied for the detection of ambient nitrous acid (HONO). We developed a HONO detection system based on long path photometry which consists of three independent modules i.e., sampling module, fluid propulsion module and detection module. In the propulsion module, solenoid pumps are applied. With solenoid pumps the pulsed flow can be computer controlled both in terms of pump stroke volume and pulse frequency, which enables the attainment of a very stable flow rate. In the detection module, a customized Liquid Waveguide Capillary Cell (LWCC) is used. The customized LWCC pre-sets the optical fiber in-coupling with the liquid wave guide, providing the option of fast startup and easy maintenance of the absorption photometry. In summer 2014, our system was deployed in a comprehensive campaign at a rural site in the North China Plain. More than one month of high quality HONO data spanning from the limit of detection to 5 ppb were collected. Intercomparison of our system with another established system from Forschungszentrum Juelich is presented and discussed. In conclusion, our instrument achieved a detection limit of 10 pptV within 2 min and a measurement uncertainty of 7%, which is well suited for investigation of the HONO budget from urban to rural conditions in China. (C) 2016 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.
In the last four decades, various techniques including spectroscopic, wet chemical and mass spectrometric methods, have been developed and applied for the detection of ambient nitrous acid (HONO). We developed a HONO detection system based on long path photometry which consists of three independent modules i.e., sampling module, fluid propulsion module and detection module. In the propulsion module, solenoid pumps are applied. With solenoid pumps the pulsed flow can be computer controlled both in terms of pump stroke volume and pulse frequency, which enables the attainment of a very stable flow rate. In the detection module, a customized Liquid Waveguide Capillary Cell (LWCC) is used. The customized LWCC pre-sets the optical fiber in-coupling with the liquid wave guide, providing the option of fast startup and easy maintenance of the absorption photometry. In summer 2014, our system was deployed in a comprehensive campaign at a rural site in the North China Plain. More than one month of high quality HONO data spanning from the limit of detection to 5 ppb were collected. Intercomparison of our system with another established system from Forschungszentrum Juelich is presented and discussed. In conclusion, our instrument achieved a detection limit of 10 pptV within 2 min and a measurement uncertainty of 7%, which is well suited for investigation of the HONO budget from urban to rural conditions in China. (C) 2016 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences.
Aggregation of nanoparticles impacts their reactivity, stability, transport, and fate in aqueous environments, but limited methods are available to characterize structural features and movement of aggregates in liquid. Here, liquid cell transmission electron microscopy (LCTEM) was utilized to directly observe the size, morphology, and motion of aggregates that were composed of 9 and 36 nm hematite nanoparticles, respectively, in water or NaCl solution. When mass concentrations were same, the aggregates of 9 nm nanoparticles were statistically more compact and slightly larger than those of 36 nm nanoparticles. Aggregates in both samples were typically nonspherical. Increasing ionic strength resulted in larger aggregates, and also enhanced the stability of aggregates under electron-beam irradiation. In water, small aggregates moved randomly and approached repeatedly to large aggregates before final attachment. In NaCl solution, small aggregates moved directly toward large aggregates and attached to the latter quickly. This observation provided a direct confirmation of the DLVO theory that the energy barrier to aggregation is higher in water than in salt solutions. This study not only presented the influences of particle size and ionic strength on aggregation state, but also demonstrated that LCTEM is a promising method to link aggregation state to dynamic processes of nanoparticles.
In this master thesis, we explore the probability theory, statistical inference and numerical computation of discrete compound Poisson (DCP) distribution. In particular, we do a very comprehensive literature review of DCP distributions and its applications in related statistical models of count data fields, and especially, we discuss penalized generalized linear model of count data regression.The discrete compound Poisson distributions have the probability generating function in the form of the following: The famous Feller’s characterization of the compound Poisson states that a discrete distribution is compound Poisson if and only if its distribution is discrete infinitely divisible. This is a special case of Levy-Khinchine formula. When the{ai}i=1∞, may take negative values and the sum is absolutely convergent, it is called pseudo discrete compound Poisson distribution.In the first chapter, we introduce an important tool (probability generating function and Fourier transform) as preliminaries and improve the flawed proof of Feller’s characterization, and then we give a short introduction of variable selection method about Lasso and generalization. We close this chapter with the infinitely divisibile prior distribution in Bayesian Lasso and we envisages appropriate zero-inflated distribution as prior distribution which obtains the nonzero sparse estimation of coefficients. The chapter Ⅱ discusses characterizations of DCP distribution(process) with ten methods to prove the probability mass function are given in Appendix, and we give over a hundred kinds of special cases or sub-families of DCP distribution which are listed in a table with references. We use Stein-Chen method and operator semigroup method to obtain the upper bound of the total variation between a sum of independent discrete r.v. and a related discrete compound Poisson r.v., and use row sum in random triangular array to approximate discrete compound Poisson distribution. Chapter Ⅳ studys statistics, parameters estimation, FFT of DCP probability mass. Chapter Ⅴ firstly uses cumulants estimation and Fourier transform estimation to actuarial claim data with zero-inflated and overdispersion properties, then compares its Kolmogorov-Smimov test and Chi-squared test. We give a theorem that a set of count data obeys discrete pseudo compound Poisson distribution if its. probability of zero is larger than the probability of nonzero. Further more, we use this zero-inflated property of pseudo discrete compound Poisson with adding virtual frequency techniques; we get an algorithm to fit any discrete distributions. Chapter V also discusses count GLM related to the DCP distribution and use penalized estimation to select important regression variables. In particular, we consider the Elastic net estimates of negative binomial regression, and we give a necessary and sufficient condition(like Karush-Kuhn-Tucker conditions) for non-zero(zero) coefficient estimates. Using a spider count data, we analysis this real example by negative binomial regression with MLE, Lasso, Elastic net penalties. Next, we set forth the survival functions in discrete frailty model and cured rate models (or long term survivor models with competing causes) which are derived from some DCP distributions. In the last section, we look forword to the future study that mixed Poisson distribution to approximate any discrete distribution, and states the problem of variable selection in mixture components. Due to the complexity of the mixture, it results the high-dimentional problem.
