The total amount of greenhouse gas emissions directly or indirectly generated by thermal power enterprises at any given time can be offset through afforestation, energy conservation and emission reduction. The present situation and control methods of CO₂ emission in China's coal-fired thermal power industry are introduced. The complex ecosystem is a unity of ecological functions composed of human society, economic activities and natural conditions. In the context of carbon neutrality and based on the theory of composite ecosystem, this paper divides the coal-fired thermal power plants in China into environmental management zones, calculates the atmospheric environmental capacity, and puts forward the concept of regional atmospheric environmental capacity, classification and zoning control. Finally, the management and control units are classified, and differentiated management and control requirements are put forward to provide a reference for regional air quality standard planning.

In this study, the generality and prediction accuracy of a generalised series model for large eddy simulation of premixed and non-premixed turbulent combustion is explored. The model is based on Taylor series expansion of the chemical source term in scalar space and implemented into OpenFOAM. The mathematical model does not depend on the combustion regimes, and has the correct limiting behaviour. The numerical error sources are outlined and analysed. The model is first applied to a piloted methane/air non-premixed jet flame (Sandia Flame D). The statistical (time-averaged and RMS) results agree well with experimental measurements, particularly with regard to the mixture fraction, velocity, temperature, and concentrations of major species CH4, CO2, H2O, and O2. The concentrations of intermediates CO and H2 are over-predicted, due to the limitations of the reduced reaction mechanism employed. Then, a Bunsen piloted flame is simulated. Most of the statistical properties of both reactive species and progress variable are well reproduced. The only major discrepancy evident is in the temperature, which is attributed to the experimental uncertainties of temperature fields in the pilot stream. These findings have demonstrated the model`s generality for both premixed and non-premixed combustion simulation, as well as the accuracy of prediction of reactive species distribution.

In recent years, there has been a notable rise in the incidence of breast cancer among young patients, who exhibit worse survival outcomes and distinct characteristics compared to the intermediate and elder patients. Therefore, it’s imperative to identify identify the specific features unique to young patients, which could offer insights into potential therapeutic strategies and improving survival outcomes. In our study, we performed an integrative analysis of bulk transcriptional and genomic data from extensive clinical cohorts to identify prognostic factors. Additionally, we analyzed the single-cell transcriptional data and conducted in vitro experiments. Our work confirmed that young patients exhibited higher grading, worse disease-free survival (DFS), a higher frequency of mutations in TP53 and BRCA1, a lower frequency of mutations in PIK3CA, and upregulation of eight metabolic pathways. Notably, galactose metabolism pathway showed upregulation in young patients and was associated with worse DFS. Further analysis and experiments indicated that galactose metabolism pathway may regulate the stemness of cancer cells and ultimately contribute to worse survival outcomes. In summary, our finding identified distinct clinicopathological, transcriptional, and genomics features and revealed a correlation between galactose metabolism pathway, stemness, and poor disease-free survival of breast cancer in young patients.