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Zheng Y.,Peking University | Zheng Y.,Beijing Key Laboratory for Solid Waste Utilization and Management | Han F.,Peking University
Stochastic Environmental Research and Risk Assessment | Year: 2016

Watershed-scale water quality (WWQ) models are now widely used to support management decision-making. However, significant uncertainty in the model outputs remains a largely unaddressed issue. In recent years, Markov Chain Monte Carlo (MCMC), a category of formal Bayesian approaches for uncertainty analysis (UA), has become popular in the field of hydrological modeling, but its applications to WWQ modeling have been rare. This study systematically evaluated the applicability of MCMC in assessing the uncertainty of WWQ modeling, using Differential Evolution Adaptive Metropolis (DREAM(ZS)) and SWAT as the representative MCMC algorithm and WWQ model, respectively. The nitrate pollution in Newport Bay watershed was the case study for numerical experiments. It has been concluded that the efficiency and effectiveness of a MCMC algorithm would depend on some critical designs of the UA, including: (i) how many and which model parameters to be considered as random in the MCMC analysis; (ii) where to fix the non-random model parameters; and (iii) which criteria to stop the Markov Chain. The study results also indicate that the MCMC UA has to be management-oriented, that is, management objectives should be factored into the designs of the UA, rather than be considered after the UA. © 2015, Springer-Verlag Berlin Heidelberg.

Zheng Y.,Peking University | Zheng Y.,Beijing Key Laboratory for Solid Waste Utilization and Management | Lin Z.,Peking University | Li H.,Peking University | And 4 more authors.
Science of the Total Environment | Year: 2014

Urban stormwater runoff delivers a significant amount of polycyclic aromatic hydrocarbons (PAHs), mostly of atmospheric origin, to receiving water bodies. The PAH pollution of urban stormwater runoff poses serious risk to aquatic life and human health, but has been overlooked by environmental modeling and management. This study proposed a dynamic modeling approach for assessing the PAH pollution and its associated environmental risk. A variable time-step model was developed to simulate the continuous cycles of pollutant buildup and washoff. To reflect the complex interaction among different environmental media (i.e. atmosphere, dust and stormwater), the dependence of the pollution level on antecedent weather conditions was investigated and embodied in the model. Long-term simulations of the model can be efficiently performed, and probabilistic features of the pollution level and its risk can be easily determined. The applicability of this approach and its value to environmental management was demonstrated by a case study in Beijing, China. The results showed that Beijing's PAH pollution of road runoff is relatively severe, and its associated risk exhibits notable seasonal variation. The current sweeping practice is effective in mitigating the pollution, but the effectiveness is both weather-dependent and compound-dependent. The proposed modeling approach can help identify critical timing and major pollutants for monitoring, assessing and controlling efforts to be focused on. The approach is extendable to other urban areas, as well as to other contaminants with similar fate and transport as PAHs. © 2014 Elsevier B.V.

Guo Y.-Y.,Peking University | Wang J.-J.,Peking University | Wang J.-J.,Clemson University | Kong D.-L.,Peking University | And 7 more authors.
Environmental Science and Technology | Year: 2013

Growing evidence has revealed high heterogeneity of fine root networks in both structure and function, with different root orders corporately maintaining trees' physiological activities. However, little information is available on how fine root heterogeneity of trees responds to environmental stresses. We examined concentrations of seven potentially toxic metals (Cr, Ni, Cu, Zn, As, Cd, and Pb) within fine root networks and their correlations with root morphological and macro-elemental traits in six Chinese subtropical trees. The contributions of different orders of roots to fine-root metal storage and return were also estimated. Results showed no consistent pattern for the correlation among different metal concentration against root traits. Unlike root metal concentration that generally decreased with root order, root metal storage was commonly lowest in middle root orders. Root senescence was at least comparable to leaf senescence contributing to metal removal. Although the first-order roots constituted 7.2-22.3% of total fine root biomass, they disproportionately contributed to most of metal return fluxes via root senescence. The two distinct root functional modules contributed differentially to metal uptake, allocation, and return, with defensive (lower-order) roots effectively stabilizing and removing toxic metals and bulk buffering (higher-order) roots possessing a persistent but diluted metal pool. Our results suggest a strong association of physiological functions of metal detoxification and metal homeostasis with the structural heterogeneity in fine root architecture. © 2013 American Chemical Society.

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