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Amid China's rapid economic expansion, the country's industrial solid waste (ISW) problem is escalating. As each sector generates distinct types of ISW, a multi-indicator assessment of each sector is essential to address China's New Solid Waste Policy. To investigate the ISW situation of each sector and perform a comprehensive assessment, we formulate an industrial solid waste ecological analysis framework based on ISW generation and ISW flow in the sector. Various indicators (i.e., solid waste utilization coefficient, solid waste threat coefficient, and solid waste threat intensity) are employed to assess the utilization of solid waste generated for each sector, as well as the threat of solid waste originating in each sector to society. Ecological network analysis probes the interrelationships between diverse sectors. Taking Shanghai in 2017 as an example, the study indicates that some sectors (e.g., production and supply of electric power and heat power (EH) and metal smelting and rolling processing sector (MS)) exhibit higher direct ISW generation and the direct industrial solid waste value-added coefficient (SVAC) for common industrial solid waste (CISW). Specifically, the direct CISW generation of EH and MS is 539.21Mt and 277.00Mt respectively. The direct SVAC of EH and MS is 157.06kg/103RMB and 126.27kg/103RMB respectively. These sectors should prioritize reducing emissions at the source. Additionally, the threats to society from various sectors are relatively insignificant for the CISW, while for the hazardous waste (HW), all sectors pose a considerable threat to Shanghai's society. Moreover, some sectors (e.g., mining industry) exhibit the highest mutualism relationships in the CISW and the HW. Enhancing mining sector technologies is a vital strategy for mitigating ISW sources. Specifically, MI has 9 pairs of mutualism relationships in the CISW and 8 pairs in the HW. These insights will provide empirical evidence for tackling the ISW problem in Shanghai. [ABSTRACT FROM AUTHOR]

In recent years, the number of countries concerned about environmental protection continues to increase. With a continuous expansion of economic scale, many emerging markets are also sustainably enhancing their management for industrial carbon emissions in foreign direct investment (FDI). Therefore, the impact of FDI on the host country's industrial carbon emissions has been a hot topic of researches. This study selects panel data of 30 medium and large cities in China from 2006 to 2019. Combined with dynamic panel GMM estimation and panel threshold model, this study empirically analyzes the impact factors of FDI on the host country's industrial carbon emissions. This study is based on the perspective of dual environmental management systems. This study draws the following conclusions: When taking the dual environmental management system factors as threshold variables into the empirical research process, only the FDI in Beijing, Tianjin, and Shanghai shows a certain inhibitory effect on Chinese industrial carbon emissions. The FDI in other cities increases the scale of industrial carbon emissions. At the same time, in the formal environmental management system, FDI has no significant impact on China's industrial carbon emissions. It indicates that the formal environmental management system of each city is not effective in policy formulation or implementation. In addition, the corresponding role of environmental management systems, such as innovation compensation and mandatory emission reduction, is not played. With the exception of Beijing and Shanghai, informal environmental management systems in other cities help curb the scale of industrial carbon emissions brought by FDI. [ABSTRACT FROM AUTHOR]

Background: Staphylococcus aureus is one predominant cause of skin and soft-tissue infections (SSTIs), but little information exists regarding the characterization of S. aureus from non-native patients with SSTIs in China. Methods: In this study, we enrolled 52 non-native patients with S. aureus SSTIs, and 65 native control patients with S. aureus SSTIs in Shanghai. 52 and 65 S. aureus isolates were collected from both groups, respectively. S. aureus isolates were characterized by antimicrobial susceptibility testing, toxin gene detection, and molecular typing with sequence type, spa type, agr group and SCCmec type. Results: Methicillin-resistant S. aureus (MRSA) was detected in 8 non-native patients and 14 native patients with SSTIs. Overall, antimicrobial susceptibilities of S. aureus isolated from non-native patients were found higher than those from native patients. CC59 (ST338 and ST59) was found in a total of 14 isolates (4 from non-native patients; 10 from native patients), 9 of which were carrying lukS/F-PV (3 from non-native patients; 6 from native patients). ST7 was found in 12 isolates and all 12 isolates were found in native patients. The livestock-associated clone ST398 was found in 11 isolates (6 from non-native patients; 5 from native patients), and 5 ST398 lukS/F-PV-positive methicillin-susceptible S. aureus (MSSA) were all discovered among non-native patients. The molecular epidemiology of S. aureus isolated from non-native patients was quite different from those from native patients. lukS/F-PV was more frequent in isolates originating from non-native patients with SSTIs compared to native patients (31 vs. 7, P <0.0001). Conclusions: CC59 was the most common clonal complex among patients with SSTIs in Shanghai. The other most common sequence types were ST7 and Livestock ST398. The molecular epidemiology of S. aureus isolated from non-native patients was quite different from those from native patients. S. aureus isolated from non-native patients was more likely to carry lukS/F-PV. [ABSTRACT FROM AUTHOR]

Levels and constituents of ambient air pollution have substantially changed in China over the last decade. Such changes may lead to the variations in health effects of air pollution. Very limited studies, however, have investigated the temporal variations in health effects of air pollution on a long-term scale, especially in China. We evaluated the temporal variations in short-term associations between PM 10 and NO 2 concentrations and emergency department (ED) visits during a 12-year period from 2008 to 2019 in Shanghai, China. A quasi-Poisson generalized linear regression was performed to assess the associations between PM 10 and NO 2 concentrations and ED visits during entire study period and three specific periods. We evaluated the temporal variations of period-specific associations with an interaction variable between pollutant concentrations and period indicators. We further investigated the concentration-response relationships for specific periods. The effects on specific subpopulations (males and females; 18–65 years old and >65 years old) were also examined. A 10 μg/m3 increase of PM 10 and NO 2 corresponded to 0.48% (95% CI: 0.36%, 0.59%) and 1.51% (95% CI: 1.25%, 1.78%) increase in ED visits at lag0–7 day for entire study period, respectively. The short-term associations between ED visits and NO 2 remained unchanged over time (P -value > 0.05), while the effects from PM 10 were significantly inconsistent (P -value < 0.05), with the highest effect observed during the intermediate period of 2012–2015 and the lowest effect observed during the initial period of 2008–2011. Similar temporal trends were found in subgroups, except for elderly group. Despite substantial reduction in ambient PM 10 and NO 2 concentrations, the short-term effects on ED visits for NO 2 remained stable and even increased for PM 10. More efforts were needed to reduce harmful components in air pollution mixture to reduce the health hazards of air pollution. [Display omitted] • PM 10 and NO 2 were associated with increased emergency department visits. • Effects remained stable for NO 2 and increased for PM 10 over study period. • Temporal trends of effects were similar in subgroups, except for elderly group. [ABSTRACT FROM AUTHOR]

Population growth, economic development, and industrialization have resulted in a notable surge in the hazardous waste (HW) generation, consequently leading to adverse effects on human health and environmental safety. In this work, a Waste Extended Input-Output-based Transformer-Long Short-Term Memory (WEIO-TL) method was developed to simulate the HW generation patterns of various economic industries in the supply chain and generate the desired strategies for reducing HW generation. The WEIO-TL method was applied to Shanghai to identify its HW reduction path and potential by 2035. Multiple scenarios were designed to investigate the impacts of different degrees of economic and technological development on HW generation. The primary results indicated that the economic proportion of each key industry and the technological innovation capability were the main factors influencing the HW generation in Shanghai. The six key industries identified by the WEIO were the chemical industry (CI), other services (OS), transportation equipment (MTE), computers, communication, and other electronic equipment (MCCOEE), wholesale and retail trades (WRT), and construction (C). HW generation would peak at 1570.9 kt in 2025 and subsequently decrease to 949.0 kt by 2035 under the optimal scenario based on the optimal TL model (R2 and RMSE values of 0.976 and 5.968), associated with industry structure optimization (i.e., part of high-polluting industries would be shifted to service) and technological innovation capability improvement. The results of the study will serve as a theoretical foundation to guide other cities toward achieving "zero waste." [Display omitted] • The embodied HW generated along the supply chain was uncovered. • The economic proportion of each key industry and technological innovation were key factors for HW generation. • A Waste Extended Input-Output-based Transformer-Long Short-Term Memory method was developed. • HW generation intensity would decrease from 0.32 to 0.05 t per million RMB in 2035 under the ZW scenario. [ABSTRACT FROM AUTHOR]

[Display omitted] • The abnormal change in weather elements under climate change were identified. • The extreme value of user demand under extreme weather was estimated. • The damage to operation efficiency of gas turbine under climate change was examined. • The operation optimization strategies adapted to climate change were proposed. • It is expected to be a demonstration for rational operation of other CCHP systems. The operation optimization of a CCHP system of a hospital in Shanghai, China, was used as a study case for demonstrating the feasibility and applicability of the dynamic interactive model (as introduced in Part I of this article). This model comprehensively considered the impact of climate change on users' demand and power generation of equipment, coupling these aspects to the operational optimization of CCHP system. The obtained results demonstrated that the increase of temperature would pose a large influence on user demand and impair the operation efficiency of gas turbine. Moreover, the implementation of energy cascade utilization mechanism and tiered electricity price would also affect operation schedule of a CCHP system. Compared with traditional optimization model, the developed dynamic interactive model could effectively overcome the problem of insufficient cooling and excessive heating in both summer and winter seasons under climate change, and achieve stable energy supply. Overall, the proposed model could help improve system economy, realize efficient utilization of energy and enhance energy-supply stability, which is of high value for supporting long-term sustainable management of energy supply systems under climate change. [ABSTRACT FROM AUTHOR]