Unveiling land footprint of solar power: A pilot solar tower project in China

Unveiling characteristics and determinants of China's wind power geographies towards low-carbon transition

The temporal and spatial patterns of wind power installation and the evaluation of carbon emission reduction potentials are of great significance to promoting China's wind power development planning and dual carbon targets achievement. This study analyzes the temporal and spatial characteristics, identifies main driving factors, and measures carbon emission reduction potentials of China's wind power installation by province based on spatial autocorrelation analysis and spatial econometric model. Overall, China's wind power installed capacity increased rapidly from 346 MW in 2000 to 279,550 MW in 2020, basically showing a significant positive spatial correlation during 2000 and 2020. Regarding driving factors of wind power installation, the technological factors and environmental factors were the main positive factors for wind power installation, and the economic factors and resource endowments showed positive spatial spillover effects. Regarding carbon emission reduction potentials, the carbon emission reduction potentials of China's wind power installation increased by year, among which Northwest China gradually accelerated Northeast China after 2015. Based on China's wind power evolution characteristics and carbon emission reduction potentials, this study attempts to provide quantitative supports and policy implications to promote sustainable development of wind power industry and the achievement of carbon peak and carbon neutrality within China.

Land use requirements for the power sector considering renewable energy development and water consumption in China

In 2020, China pledged to peak its carbon emission before 2030 and achieve carbon neutrality before 2060. These ambitious carbon targets will inevitably boost the development of renewable energy generation, which has advantages from energy and water perspectives but disadvantages from land use perspective. Therefore, it is necessary to discuss the interaction among renewable energy development, water consumption as well as land use in the power sector, and determine a reasonable power-related land use range for the land administration in China. In this research, a series of multi-period, multi-regional power system optimization models with different objective functions and constraints are established to study the interrelationship among renewable energy development, water consumption, and land use in the coverage area of China Southern Power Grid from 2018 to 2030, and provide a reasonable land use range for the power sector in this region in 2030. Based on the above calculation results, the development of renewable energy promoted by energy and water policies will increase the land use of power sector under a cost objective function, and the minimum land area demand for this power system in 2030 considering energy and water policies is 24785.14 km². What is more, according to the influence of land use constraint on the total cost of power sector from 2018 to 2030, this paper selected the increase ratio from 5 to 16% compared with the minimum land area demand as the reasonable land use range.

Systems Accounting for Carbon Emissions by Hydropower Plant

Hydropower is the largest renewable source of electricity generation, the carbon emissions of which have attracted a lot attention. However, the system boundaries of existing studies are either incomplete or inaccurate. Therefore, this study provides a systems accounting framework for evaluating both the direct and indirect carbon emissions from a hydropower plant. It is based on the hybrid method as a combination of the process analysis and the input-output analysis. To demonstrate the framework, a case study for a typical pumped storage hydropower plant (NPSHP) is carried out. The total carbon emissions are estimated as 5828.39 kt in the life-cycle of the case system. The end-of-use stage causes the largest carbon emissions (38.4%), followed by the construction stage (34.5%), the operation stage (25.6%), and the preparation stage (1.5%). The direct carbon emissions are mainly released from sediments in the end-of-use stage and the surface of reservoirs in the operation stage (94.8%). The indirect carbon emissions are 2.8 times higher than the direct carbon emissions. The material, machinery, energy, and service inputs respectively account for 7.1%, 14.7%, 15.9%, and 62.3% of the total indirect carbon emissions by the case system. The indicator of EGOC (electricity generation on carbon emission) for the NPSHP is calculated as 26.06 g CO2-eq./kWh, which is lower than that of most other power plants.

Biodiversity Loss from Freshwater Use for China's Electricity Generation

Electricity generation has two major, under-investigated impacts on freshwater biodiversity due to its water use: the consumption of freshwater and thermal emissions to freshwater. Here, we analyze the spatiotemporal freshwater biodiversity impacts of China's electric power system and the driving factors for these impacts. We show that between 2008 and 2017, the freshwater consumption of electricity generation peaked in 2013 (13.6 Gm³). Meanwhile, the freshwater consumption factor of China's electricity generation decreased from 3.2 to 2.0 L/kWh. However, due to increasing thermal emissions, the biodiversity loss via freshwater use increased from 1.1 × 10⁸ in 2008 to 1.6 × 10⁸ PDF m³ year. The overall biodiversity loss per unit of electricity generation decreased from 3.2 × 10^-5 to 2.5 × 10^-5 PDF m³ year/kWh. Biodiversity loss from thermal pollution is 60% higher than that driven by water consumption. Electricity transmission results in the shifting of biodiversity impacts across regions. The results show that 15% of total biodiversity loss was embedded in transmission networks. In terms of electrical power system drivers of biodiversity loss, the total generation was the main driving factor of the increase in loss (rather than shifts in generation type, for example). Our results indicate the necessity of assessing the biodiversity impacts of electricity generation and incorporating them into energy system planning.