Vertical distribution and migration of heavy metals in soil of green stormwater infrastructure receiving roof runoff.

In order to achieve effective management of urban stormwater runoff, green stormwater infrastructure (GSI) has been widely used worldwide. However, the problem of heavy metal contamination in GSI soils has gradually become a limiting factor for their development. In this paper, concentrations of 6 heavy metals were detected in soils from 0 to 80 cm depth in the GSI receiving roof runoff.

Contrasting fate and binding behavior of Mn and Cu with dissolved organic matter during in situ remediation using multicomponent capping in malodorous black water.

The common use of peroxides in the remediation of malodorous black water may lead to the activation of heavy metals in sediment when eliminating black and odorous substances. The mechanisms of heavy metal interactions with dissolved organic matter (DOM) in response to in situ capping have not been elucidated, but this information could guide the optimization of capping materials. We developed a capping material consisting of hydrothermally carbonized sediment (HCS), hydrated magnesium carbonate (HMC) and sodium percarbonate (SPC) and used microcosm experiments to investigate the dynamics of Mn and Cu at the sediment-water interface in malodorous black water.

An improved Back Propagation Neural Network framework and its application in the automatic calibration of Storm Water Management Model for an urban river watershed.

The use of the Storm Water Management Model (SWMM) to simulate flows in urban river watersheds necessitates the proper calibration of the various parameters involved in the process. Back Propagation Neural Network (BPNN) is often used to establish relationship between two sets of multivariate variables, such as parameters and simulation results of SWMM. The aim of this study is to establish an improved BPNN to calibrate SWMM.

An in-depth investigation of the influence of sample size on PCA-MLR, PMF, and FA-NNC source apportionment results.

The mechanism by which parameters influence the source apportionment results of receptor models is not well understood. Three mature receptor models, namely, principal component analysis-multiple linear regression (PCA-MLR), positive matrix factorization (PMF) and factor analysis with nonnegative constraints (FA-NNC), were comparatively employed for source apportionment of 16 polycyclic aromatic hydrocarbons in 30 street dust samples. The results indicated that the FA-NNC and PMF models produced results with a higher degree of similarity than the results obtained with the PCA-MLR model.

An improved nonnegative matrix factorization with the imputation method model for pollution source apportionment during rainstorm events.

Data scarcity caused by extreme conditions during storms adds difficulties in performing pollution source apportionment. This study integrated nonnegative matrix factorization with the imputation method (NMF-IM) to fill in missing data (NAs) and conduct source apportionment. A total of 367 river samples and 35 runoff samples were taken from the Banqiao and Nanfei River basins located in Hefei, China, during four rainfall events from June to August 2020.

Watershed health assessment using the coupled integrated multistatistic analyses and PSIR framework.

Quantitatively assessing watershed health under anthropogenic activities and management responses is important for the scientific planning and management of watersheds. The current research on watershed health assessments insufficiently reflects watershed scale information from different dimensions, which leads to the incomplete understanding of watersheds and thus the lack of systematic management. This study investigated the health status in the Chaohu Lake watershed (CLW) based on monthly sampling data at 46 river sites in 2018.

Refining the diagnostics of non-point source metals pollution to urban lakes based on interaction normalized PMF coupled with Bayesian network.

Spatiotemporal variability complicates source apportionment of metals in urban lakes, especially when rainfall drives urban non-point source pollution. As, Cd, Cr, Pb, Hg, Ag, Co, Cu, Fe, Mn, Ni, Sb, Sr and Zn concentrations in 648 water samples collected before and after rain in 6 urban lakes of Beijing, China were determined during 2013-2015. The response of metals concentrations after rain to the interaction between rainfall and antecedent dry days was significant.

The influence of rainfall and catchment characteristics on runoff generation in urban catchments-a case study in Hebi City of China.

An in-depth understanding of the rainfall-runoff process is essential for effective stormwater management. However, the understanding of the hierarchy of rainfall characteristics in terms of their importance in influencing runoff generation is limited. This paper investigates the influence of rainfall characteristics and catchment characteristics on runoff generation in urban catchments.

Systematic evaluation of management measure effects on the water environment based on the DPSIR-Tapio decoupling model: A case study in the Chaohu Lake watershed, China.

Watershed management measures have been widely implemented worldwide to reduce the water quality deterioration in rivers and lakes, which continue to face increasing stresses from human activities. Due to the complexity of influential factors within watersheds, systematic and reliable approaches are urgently needed to evaluate the effects of watershed managerial practices on scientific applications. In this study, the driving force-pressure-state-impact-response (DPSIR) model integrated by Tapio decoupling analysis was established using 30 quantitative indicators to systematically evaluate their effects on overall watershed water environmental health of Chaohu Lake watershed, China, which was under intensive management practices during 2000-2019.

Differential analysis of FA-NNC, PCA-MLR, and PMF methods applied in source apportionment of PAHs in street dust.

Many source apportionment models have been applied to identify pollution sources, and differences often exist in the diagnostic results. The reasons causing these differences have not been fully elucidated. In this study, three receptor models, principal component analysis-multiple linear regression (PCA-MLR), positive matrix factorization (PMF), and factor analysis-nonnegative constraints (FA-NNC), were compared and applied for the analysis of 16 EPA priority polycyclic aromatic hydrocarbons (PAHs) adsorbed in street dust samples from Harbin City (China).

[Comparison of Characteristics and Source Apportionment of Polycyclic Aromatic Hydrocarbons in Different Environmental Media in the Urban Area of Daqing City].

In order to investigate the various pollution characteristics and sources of polycyclic aromatic hydrocarbons (PAHs) in different environmental media, 23 street dust samples and four soil samples were collected in October 2012 in Daqing City. After extraction by Dionex ASE300 and purification, the content of the US EPA priority pollutants[16 individual PAH and total PAHs (ΣPAHs)] was determined by using gas chromatography-mass spectrometry (GC/MS). The results showed that the range of ΣPAHs content in street dust was 579.