With the carbon reduction targets being set in the Paris Agreement on Climate Change, China is facing great pressure to meet its emission reduction commitment. The electric power industry as the major source of carbon emissions needs to be a focus. However, the uncertainty of power systems, the risk of reducing emissions and the fuzziness of carbon capture technology popularization rate and carbon reduction targets makes previous planning methods unsatisfactory for current planning. This paper establishes an interval fuzzy programming with a risk measure model which takes carbon capture technology and carbon reduction targets into account, to ensure that the complex electric management system achieves the best developmental state. It was concluded that in order to reduce carbon emissions, wind power and hydropower would be the best choices, and coal-fired power would be the suboptimal choice, and solar power would play a complementary role. Besides, decision makers should put much more effort into promoting and improving carbon capture technology instead of simply setting emission reduction targets. The non-synchronism of the downward trend in carbon emissions per unit of electricity generation and electric power industry total carbon emissions need to be taken seriously.

The waste landfill disposes of a large amount of urban garbage, and the harmful substances in the waste have serious impacts on the ecological environment of the landfill and its surroundings. To systematically investigate the pollution mechanisms and associated health risks posed by landfills, we conducted a comprehensive study in Guangxi Province, China by collecting water, soil, and leachate samples from 12 operational landfill sites. These samples were analyzed using inductively coupled plasma mass spectrometry and ultraviolet-visible spectroscopy to quantify concentrations of 18 priority pollutants, including heavy metals and nutrients. Geostatistical analysis revealed moderate spatial clustering of pollutants in soils and groundwater, with significant positive correlations observed between Mn, Cd, and Pb concentrations across leachate-soil-groundwater systems. Notably, as exhibited 2.3-fold higher carcinogenic risk values compared to Cd, while Zn demonstrated the highest non-carcinogenic hazard quotient among all studied pollutants. Contaminant transport pathways were evaluated through correlation models, revealing that Cu and Hg in leachate significantly influenced groundwater quality around landfills. These findings provide critical insights for implementing site-specific pollution control strategies and optimizing health risk management protocols in landfill-impacted regions.