The illicit connections between sewage and stormwater pipes result in the discharge of untreated sewage into receiving rivers, posing significant odor and health hazards. While thioethers are recognized as key odorants in sewage systems, their distribution in stormwater systems remain poorly characterized. This study analyzed 12 types of thioethers in stormwater pipes sampled at 21 sites in China. Advanced analytical techniques, including Mantel analysis and Structural Equation Modeling, were employed to examine the relationships between overlying water properties, sediment microbial characteristics, and thioether concentrations. Results showed that sediment thioether loads (36.77 ± 50.14 μg S/m; range: 7.24–99.96 μg S/m) were substantially higher than those in the overlying water (12.02 ± 42.52 μg S/m; range: 0.03–92.76 μg S/m), highlighting sediment as a critical pollution reservoir. Dissolved oxygen, NH₃-N, and terrestrial-derived dissolved organic nitrogen were identified as key factors shaping sediment microbiome composition, particularly fermentative, sulfate-reducing, and denitrifying bacteria, which in turn drives thioether formation. Specifically, dominant compounds like dimethyl disulfide and dimethyl trisulfide were found to be produced through the anaerobic fermentation of methionine and redox conversion of methanethiol, as well as the anaerobic fermentation of cysteine and methylation of polysulfides. Humic substances could facilitate methanethiol redox conversion and polysulfide methylation by serving as methyl donors and enhancing electron transfer efficiency. Additionally, NH₃-N may promote microbial metabolism by providing amino groups essential for the synthesis of metabolic precursors. Therefore, effective mitigation of odorous thioethers in stormwater systems necessitates integrated strategies targeting both sulfur-containing organic precursors and nitrogen-rich pollutants.

The odor nuisance of urban surface water after rainfall events has aroused public concerns and threaten the aquatic organisms. Herein, the first study to investigate 150 odorants in storm sewer discharge was performed in humid regions of China. During rainfall events, the total concentrations of odorants at storm sewer outlet increased by 1.3–2.1 fold from 1.7–9.4 μg/L to 2.1–20.0 μg/L with 37 odorants having detection frequencies above 50 % on rainy days, and the concentrations of total odorants in air also significantly increased resulting in worse odor nuisance. The accumulation of odorants in sewer sediment and the remobilization of sewer sediment were factors resulting in more intensified emission of odorants from storm sewer on rainy days. More than half of odorants discharged during rainfall were contributed by sewer sediment. Thioethers, indoles, 2-isopropyl-3‑methoxy pyrazine, acetophenone and coumarin exhibited high sediment-accumulation. Quantitative structure-property relationship models revealed that enhanced sediment-accumulation of chained aliphatic and aromatic odorants can be explained by the electrostatic attraction and topological characteristic, respectively. The multicriteria analysis was further introduced for relative odorants ranking by considering the variations in hazard criteria of environmental occurrence, ecotoxicity, persistence, odor nuisance and sediment accumulation. Among priority odorants, thioethers and indoles were attributed by their distinct sediment-accumulation and odor nuisance potential, while chlorinated anisole and pinenes prioritized due to their higher ecotoxicity. These findings provide novel insights into the odorants from storm sewer discharges and explore the environmental behaviors of odorants in sewer sediment.

In 2017 about 37% of the world's wind turbines and 50% of the world's photovoltaic (PV) panels are installed in China. But at the same time a huge amount of wind power and PV power is wasted mainly because of insufficient flexibility of thermal power which is the dominant source in China's electricity system. This paper aims to assess the flexibility requirements for thermal power plants to accommodate large-scale variable renewable energies (VREs). This paper constructs three scenarios for the reference year of 2030, where VREs account for 16%, 19% and 22% in the electricity system respectively, and simulates corresponding residual load time series (residual load = load − hydropower − nuclear power − wind power − PV power). We find that the current average 1%/min ramp rate of thermal power plants is basically sufficient to deal with ramps in residual load in the future. But the current average 60% minimum load level of thermal power plants has to be improved to 40% or even 30%, otherwise the economic losses of VREs curtailment will be as high as 947.2×10⁸ – 1632.0×10⁸ CNY per year in the future. It is necessary and beneficial for the central authority to invest in retrofitting the existing huge thermal power plants to improve their minimum load level.

In 2011 China initiated policies to promote the adoption of solar photovoltaic (PV) using feed-in tariff (FIT) policies. Since then the PV domestic market expanded substantially. In the past six years, the FIT policies were updated (adjustment of tariff levels, division of three FIT regions, setting of installation quotas) to address emerging problems such as PV waste, explosive installation, unbalanced spatial distribution. This paper aims to investigate the historical development and implementation of FIT policies in China from 2011 to 2016. The tools of net present value (NPV)/internal rate of return (IRR), learning curve and the system dynamics are employed to show the degree of economic incentives of FIT policies, to understand the learning rate of centralized PV systems, and to study the dynamic mechanism of the FIT system. We conclude that in the near term the tariff levels should be adjusted more frequently to keep IRR values in the range of 8–12%, and a tight quota combined with the deployment of ultra-high voltage (UHV) lines should be continued for the provinces with severe PV waste.

Diagnosis by comparison is a realistic approach to detect faults of multiprocessor systems. This paper considers a pessimistic diagnostic strategy for hypercube-like multiprocessor systems under the comparison model. The pessimistic strategy is a diagnostic process whereby all faulty nodes can be correctly identified and at most one fault-free node may be misjudged as a faulty node. We propose a pessimistic diagnosis algorithm based on the largest component in the faulty system. For a system with N=2n nodes and n≥5 , when the number of faulty nodes is bounded by 2n−2 , the algorithm can correctly identify all nodes except at most one node left undiagnosed. The time complexity of the algorithm is O(Nlog2N) .