Digital economy and carbon emission: The coupling effects of the economy in Qinghai region of China.

This study provides an in-depth analysis of the complex relationship between the digital economy and carbon emissions, fully drawing on essential principles of environmental economics, coupled economics, and sustainable development theory. Focusing on the Qinghai region in the western province of China, the study employs highly sophisticated methods such as multiple regression analysis and system dynamics modeling to reveal the multidimensional coupling effects between digital economy development and carbon emission dynamics. The study's results clearly show that in the Qinghai region of China, the booming growth of the digital economy is related to carbon emissions. Of particular interest, the study finds that this relationship exhibits a high degree of complexity and non-linearity and evolves gradually over time. Initially, the rapid expansion of the digital economy, accompanied by high energy consumption and increased carbon emissions, posed a significant challenge to environmental protection. However, a clear inverted "U"-shaped relationship has emerged as the digital economy evolves. This key inflection point signals a shift in the landscape as the digital economy begins to deliver some ecological benefits, potentially reducing the trend of carbon emissions in the future. The findings of this study go beyond simple causality and reveal a complex and evolving dynamic relationship between the digital economy and carbon emissions. Through such insights, this study provides a solid academic foundation and carefully constructs actionable policy recommendations to drive sustainable development. These insights apply to the Qinghai region of China and provide valuable references and lessons for other areas facing similar challenges.

Flexibility during the COVID-19 Pandemic Response: Healthcare Facility Assessment Tools for Resilient Evaluation.

Healthcare facilities are facing huge challenges due to the outbreak of COVID-19. Around the world, national healthcare contingency plans have struggled to cope with the population health impact of COVID-19, with healthcare facilities and critical care systems buckling under the extraordinary pressures. COVID-19 has starkly highlighted the lack of reliable operational tools for assessing the level sof flexibility of a hospital building to support strategic and agile decision making. The aim of this study was to modify, improve and test an existing assessment tool for evaluating hospital facilities flexibility and resilience. We followed a five-step process for collecting data by (i) doing a literature review about flexibility principles and strategies, (ii) reviewing healthcare design guidelines, (iii) examining international healthcare facilities case studies, (iv) conducting a critical review and optimization of the existing tool, and (v) assessing the usability of the evaluation tool. The new version of the OFAT framework (Optimized Flexibility Assessment Tool) is composed of nine evaluation parameters and subdivided into measurable variables with scores ranging from 0 to 10. The pilot testing of case studies enabled the assessment and verification the OFAT validity and reliability in support of decision makers in addressing flexibility of hospital design and/or operations. Healthcare buildings need to be designed and built based on principles of flexibility to accommodate current healthcare operations, adapting to time-sensitive physical transformations and responding to contemporary and future public health emergencies.

[Spatiotemporal Change and Source Apportionment of Non-point Source Nitrogen and Phosphorus Pollution Loads in the Three Gorges Reservoir Area].

The Three Gorges Reservoir area (TGRA) is a critical water source protection area in China and one of the regions with rapid economic development in the Yangtze River basin. Non-point source pollution is the leading cause of the deterioration of the water environment in the TGRA; therefore, studying the non-point source pollution status in the TGRA is of great significance to the regional ecological security and sustainable development. The improved export coefficient model was used to estimate the total non-point source nitrogen and phosphorus pollution loads in the TGRA from 1990 to 2015, the spatial and temporal characteristics of the non-point source nitrogen and phosphorus pollution were analyzed, and the primary sources of pollution were determined by calculating the contribution rate of each pollution source. The results concluded that the nitrogen and phosphorus pollution loads were highest in the hinterland of the reservoir, followed by the end of the reservoir, with the lowest in the head of the reservoir, showing significant spatial heterogeneity in the TGRA. The total loads of nitrogen and phosphorus pollution increased firstly and then decreased, which reached the highest value in 2000 and the lowest value in 2015. The contribution rate of each pollution source to the nitrogen and phosphorus pollution loads, from highest to lowest, were land use, rural life, livestock, and poultry farming. Among them, the land use type of dry land was the predominant source of non-point source nitrogen and phosphorus pollution.

Probabilistic modelling of prospective environmental concentrations of gold nanoparticles from medical applications as a basis for risk assessment.

BACKGROUND: The use of gold nanoparticles (Au-NP) based medical applications is rising due to their unique physical and chemical properties. Diagnostic devices based on Au-NP are already available in the market or are in clinical trials and Au-NP based therapeutics and theranostics (combined diagnostic and treatment modality) are in the research and development phase. Currently, no information on Au-NP consumption, material flows to and concentrations in the environment are available. Therefore, we estimated prospective maximal consumption of Au-NP from medical applications in the UK and US. We then modelled the Au-NP flows post-use and predicted their environmental concentrations. Furthermore, we assessed the environment risks of Au-NP by comparing the predicted environmental concentrations (PECs) with ecological threshold (PNEC) values. RESULTS: The mean annual estimated consumption of Au-NP from medical applications is 540 kg for the UK and 2700 kg for the US. Among the modelled concentrations of Au-NP in environmental compartments, the mean annual PEC of Au-NP in sludge for both the UK and US was estimated at 124 and 145 µg kg(-1), respectively. The mean PEC in surface water was estimated at 468 and 4.7 pg L(-1), respectively for the UK and US. The NOEC value for the water compartment ranged from 0.12 up to 26,800 µg L(-1), with most values in the range of 1000 µg L(-1). CONCLUSION: The results using the current set of data indicate that the environmental risk from Au-NP used in nanomedicine in surface waters and from agricultural use of biosolids is minimal in the near future, especially because we have used a worst-case use assessment. More Au-NP toxicity studies are needed for the soil compartment.