Urban construction land demand prediction and spatial pattern simulation under carbon peak and neutrality goals:A case study of Guangzhou,China

Urban construction land has relatively high human activity and high carbon emissions.Research on urban construction land prediction under carbon peak and neutrality goals(hereafter“dual carbon”goals)is important for territorial spatial planning.This study analyzed quantitative relationships between carbon emissions and urban construction land,and then modified the construction land demand prediction model.Thereafter,an integrated model for urban construction land demand prediction and spatial pattern simulation under“dual carbon”goals was developed,where urban construction land suitability was modified based on carbon source and sink capacity of different land-use types.Using Guangzhou as a case study,the integrated model was validated and applied to simulate the spatiotemporal dynamics of its urban construction land during 2030–2060 under baseline development and“dual carbon”goals scenarios.The simulation results showed that Guangzhou’s urban construction land expanded rapidly until 2030,with the spatial pattern not showing an intensive development trend.Guangzhou’s urban construction land expansion slowed during 2030–2060,with an average annual growth rate of 0.2%,and a centralized spatial pattern trend.Under the“dual carbon”goal scenario,Guangzhou’s urban construction land evolved into a polycentric development pattern in 2030.Compared with the baseline development scenario,urban construction land expansion in Guangzhou during 2030–2060 is slower,with an average annual growth rate of only 0.1%,and the polycentric development pattern of urban construction land was more prominent.Furthermore,land maintenance and growth,that is,a carbon sink,is more obvious under the“dual carbon”goals scenario,with the forest land area nearly 10.6%higher than that under the baseline development scenario.The study of urban construction land demand prediction and spatial pattern simulation under“dual carbon”goals provides a scientific decision-making support tool for territorial spatial planning,aiding in quantifying territorial spatial planning.

Building energy efficiency and COVID-19 infection risk:Lessons from office room management

To prevent COVID-19 outbreaks,many indoor environments are increasing the volume of fresh air and running air conditioning systems at maximum power.However,it is essential to consider the comfort of indoor occupants and energy consumption simultaneously when controlling the spread of infection.In this study,we simulated the energy consumption of a three-storey office building for postgraduate students and teachers at a university in Beijing.Based on an improved Wells-Riley model,we established an infection risk-energy consumption model considering non-pharmaceutical interventions and human comfort.The infection risk and building energy efficiency under different room occupancy rates on weekdays and at weekends,during different seasons were then evaluated.Energy consumption,based on the real hourly room occupancy rate during weekdays was 43%–55%lower than energy consumption when dynamic room occupancy rate was not considered.If all people wear masks indoors,the total energy consumption could be reduced by 32%–45%and the proportion of energy used for ventilation for epidemic prevention and control could be reduced by 22%–36%during all seasons.When only graduate students wear masks in rooms with a high occupancy,total energy consumption can be reduced by 15%–25%.After optimization,compared with the strict epidemic prevention and control strategy(the effective reproductive number Rt=1 in all rooms),energy consumption during weekdays(weekends)in winter,summer and transition seasons,can be reduced by 45%(74%),43%(69%),and 55%(78%),respectively.The results of this study provide a scientific basis for policies on epidemic prevention and control,carbon emission peak and neutrality,and Healthy China 2030.