Gongchen Li

Effect of short-chain organic acids and pH on the behaviors of pyrene in soil-water system.

The effects of five short-chain organic acids (SCOAs) on the behaviors of pyrene in soil-water system were investigated. The influences of the quantity and species of organic acids, pH, and soil dissolved organic matter were considered. The results showed the presence of SCOAs inhibited the adsorption and promoted the desorption of pyrene in the following order: citric acid>oxalic acid>tartaric acid>lactic acid>acetic acid. The decreased extents of pyrene adsorption performance enhanced with increasing SCOA concentrations, while the decreasing rate became less pronounced at high SCOA concentrations. In the presence of organic acids, the adsorption ability of pyrene decreased with increasing pH. However, there was a slight increase of pyrene adsorption with the addition of oxalic acid, tartaric acid and citric acid above pH 8. The capacity for pyrene retention differentiated significantly between the soils with and without dissolved organic matter. The presence of SCOAs was also favorable for the decrease of pyrene adsorption on soil without dissolved organic matter. The results of this study have important implications for the remediation of persistent organic pollutants in soil and groundwater.

Effects of fulvic acid concentration and origin on photodegradation of polycyclic aromatic hydrocarbons in aqueous solution: importance of active oxygen.

With an Xe arc lamp house as simulated sunlight, the influences of fulvic acid (FA) concentration and origins on photodegradation of acenaphthene, fluorine, phenanthrene, fluoranthene and pyrene in aqueous solution have been studied. Similar effects of FAs, collected from five places around China, on polycyclic aromatic hydrocarbon (PAH) photodegradation have been observed. Active oxygen was of significance in PAH photodegradation with the presence of FAs. For systems with 1.25 mg L(-1) FAs, the contributions of 8*OH to PAH photodegradation rates were from 33% to 69%. FAs had two opposite effects, i.e., stimulating the generation of active oxygen and advancing PAH photodegradation; competing with PAHs for energy and photons and restraining PAH photodegradation. Generally, photodegradation rates of the 5 PAHs decreased with the increase of FAs concentration; except fluoranthene and pyrene were advanced in solutions with low FA concentration. The influences of FA concentration on PAH photodegradation were more significant than FA origin.

An integrated multi-level watershed-reservoir modeling system for examining hydrological and biogeochemical processes in small prairie watersheds

Eutrophication of small prairie reservoirs presents a major challenge in water quality management and has led to a need for predictive water quality modeling. Studies are lacking in effectively integrating watershed models and reservoir models to explore nutrient dynamics and eutrophication pattern. A water quality model specific to small prairie water bodies is also desired in order to highlight key biogeochemical processes with an acceptable degree of parameterization. This study presents a Multi-level Watershed-Reservoir Modeling System (MWRMS) to simulate hydrological and biogeochemical processes in small prairie watersheds. It integrated a watershed model, a hydrodynamic model and an eutrophication model into a flexible modeling framework. It can comprehensively describe hydrological and biogeochemical processes across different spatial scales and effectively deal with the special drainage structure of small prairie watersheds. As a key component of MWRMS, a three-dimensional Willows Reservoir Eutrophication Model (WREM) is developed to addresses essential biogeochemical processes in prairie reservoirs and to generate 3D distributions of various water quality constituents; with a modest degree of parameterization, WREM is able to meet the limit of data availability that often confronts the modeling practices in small watersheds. MWRMS was applied to the Assiniboia Watershed in southern Saskatchewan, Canada. Extensive efforts of field work and lab analysis were undertaken to support model calibration and validation. MWRMS demonstrated its ability to reproduce the observed watershed water yield, reservoir water levels and temperatures, and concentrations of several water constituents. Results showed that the aquatic systems in the Assiniboia Watershed were nitrogen-limited and sediment flux played a crucial role in reservoir nutrient budget and dynamics. MWRMS can provide a broad context of decision support for water resources management and water quality protection in the prairie region.

Applications of inexact programming methods to waste management under uncertainty: current status and future directions

Waste management problems are subject to uncertainties presented as intervals, random variables and/or fuzzy sets. During the past 20 years, inexact programming methods have been developed and applied increasingly to waste management problems under uncertainty. To obtain a snapshot of these studies, this paper gives a review on recent developments, applications, challenges, and barriers associated with inexact programming techniques in supporting waste management. The results indicate that the majority of inexact programming methods can be categorized as two-stage stochastic programming, chance-constrained programming, fuzzy flexible programming, fuzzy robust programming, interval-parameter programming, mixed-integer programming, multiple-objective programming, and nonlinear programming. The demanding areas for future research efforts would include: expansion of conventional concepts to quantify uncertainties, integration of single inexact programming method with other programming methods to deal with multiple uncertainties and even complexities (e.g. nonlinearities and interactions), integration of inexact programming with other modeling techniques (e.g. life cycle assessment, multiple-criteria decision analyses, and waste flow simulation) to support sustainable waste management, development of more efficient algorithms to solve the proposed methods, linkage of waste management with its environmental impacts (e.g. air pollutants and GHG emissions as well as leachate pollution) within an inexact optimization framework, and applications of the developed methods to novel (e.g. specific types of wastes) or real-world waste management cases in different countries.

DMSP-IEES: A Stochastic Programming Model Based on Dual-Interval and Multi-Stage Scenarios Modeling Approaches for Energy Systems Management and GHG Emissions Control

Energy-related activities contribute a major portion of anthropogenic greenhouse gas (GHG) emissions into the atmosphere. In this study, a dual-interval multi-stage stochastic programming model for the planning of integrated energy-environment systems (DMSP-IEES) model is developed for integrated energy-environment systems management, in which issues of GHG-emission mitigation can be reflected throughout the process of energy systems planning. By integrating methodologies of interval linear programming (when numbers are described as interval values without distribution information), dual-interval programming (when lower and upper bounds of interval values are not available as deterministic values but as discrete intervals), and multi-stage stochastic programming, the DMSP-IEES model is capable of dealing with uncertainties expressed as discrete intervals, dual intervals, and probability distributions within a multi-stage context. Decision alternatives can also be generated through analysis of the single- and dual-interval solutions according to projected applicable conditions. A case study is provided for demonstrating the applicability of the developed methodology. The results indicate that the developed model can tackle the dual uncertainties and the dynamic complexities in the energy-environment management systems through a multi-layer scenario tree. In addition, it can reflect the interactions among multiple system components and the associated trade-offs.