Research on Carbon Reduction of Residential Buildings in Severe Cold Regions Based on Renovation of Envelopes

Abstract

The demand for heating in cold regions drives up carbon emissions every year. In order to achieve China’s carbon neutrality target by 2060, CO2 emissions in the cold regions must be reduced. In this paper, using Design Builder software, a simulation model of residential buildings in severe cold regions was created, and the most appropriate parameter design scheme for carbon emission reduction of residential buildings in severe cold regions was derived by simulating the experimental data of the original parameter design scheme and the changed parameter design scheme, as well as the calculation of carbon dioxide emission reduction rate. In order to make the comparison of the results easier, no change was made in the selection of the changed scheme for the external insulation material, foamed polystyrene panels. The results show that the most suitable parameter scheme for houses in severe cold regions is 85 mm thick foamed polystyrene panels for exterior walls, 200 mm thick foamed polystyrene panels for roofs, and exterior windows should use semi-tempered plastic steel frame and triple glass 6 mm glass + vacuum + 6 mm low-e glass + 12 mm air + 6 mm glass composed of windows. This technique saves 30.32% of energy as compared to the original parameter design approach. The efficiency of energy conservation is 33.03%. The emission reduction effect is significant. The best parametric design plan has a static payback period of 5 years. The best parametric design plan has a discounted payback period of 7 and a net present value of USD 65,413.39. This scheme can provide a great economic return while also increasing the performance of the building.

Horizontal Shower Heat Exchanger as an Effective Domestic Hot Water Heating Alternative

“…The discounted payback period (DPP) and the internal rate of return (IRR) were also determined. These indices are often used to evaluate projects in the broadly defined energy sector [49,50].…”

“…As part of the analysis, the impact of modifying the independent variables, i.e., the amount of investment outlays and energy prices, on the calculation results was assessed. For this purpose, a two-factor sensitivity analysis was used [49]. In addition, the risk of lowering projected savings in case of a change in the value of the discount rate (r) was also examined.…”