Challenges for China to achieve carbon neutrality and carbon peak goals: Beijing case study

Enhanced Whale optimization algorithms for parameter identification of solar photovoltaic cell models: a comparative study

Parameter identification of solar photovoltaic (PV) cells is crucial for the PV system modeling. However, finding optimal parameters of PV models is an intractable problem due to the highly nonlinear characteristics between currents and voltages in different environments. To address this problem, whale optimization algorithm (WOA)-based meta-heuristic algorithm has turned out to be a feasible and effective approach. As a highly promising optimization algorithm, different enhanced WOA variants have been proposed. Nevertheless, there has been no comparative study of WOA and its variants for parameter identification of PV models so far. To further investigate and analyze the performance of WOA in the studied problem, this work applied and compared WOA and ten enhanced WOA variants for identifying five PV model parameters. Different evaluation indices including solution accuracy, search robustness, and convergence curve were employed to reveal their performance variation. Based on the simulation results, a multi-model statistical analysis with the Friedman test at a confidence level 0.05 was conducted to rank all algorithms. EWOA that hybridizes the sorting-based differential mutation operator and the Lévy flight strategy ranked first and its performance was further verified. Besides, according to the simulation results, possible effective improvement directions for WOA in tackling this intractable problem are concluded to guide future work.

Estimating Biomass and Carbon Sequestration Capacity of Phragmites australis Using Remote Sensing and Growth Dynamics Modeling: A Case Study in Beijing Hanshiqiao Wetland Nature Reserve, China

Estimating the biomass of Phragmites australis (Cav.) Trin. ex Steud., i.e., a common wetland macrophyte, and the associated carbon sequestration capacity has attracted increasing attention. Hanshiqiao Wetland Nature Reserve (HWNR) is a large P. australis wetland in Beijing, China, and provides an ideal case study site for such purpose in an urban setting. In this study, an existing P. australis growth dynamics model was adapted to estimate the plant biomass, which was in turn converted to the associated carbon sequestration capacity in the HWNR throughout a typical year. To account for local differences, the modeling parameters were calibrated against the above-ground biomass (AGB) of P. australis retrieved from hyperspectral images of the study site. We also analyzed the sensitivity of the modeling parameters and the influence of environmental factors, particularly the nutrient availability, on the growth dynamics and carbon sequestration capacity of P. australis. Our results show that the maximum AGB and below-ground biomass (BGB) of P. australis in the HWNR are 2.93 × 10³ and 2.49 × 10³ g m⁻², respectively, which are higher than the reported level from nearby sites with similar latitudes, presumably due to the relatively high nutrient availability and more suitable inundation conditions in the HWNR. The annual carbon sequestration capacity of P. australis in the HWNR was estimated to be 2040.73 gC m⁻² yr⁻¹, which was also found to be highly dependent on nutrient availability, with a 50% increase (decrease) in the constant of the nutrient availability K_NP, resulting in a 12% increase (23% decrease) in the annual carbon sequestration capacity. This implies that a comprehensive management of urban wetlands that often encounter eutrophication problems to synergize the effects of nutrient control and carbon sequestration is worth considering in future practices.