Mitigation of heat island effect by green stormwater infrastructure: a comparative study between two diverse green spaces in Nanjing

IntroductionStudies have shown that green spaces and water bodies can alleviate heat island effects. However, uncertainty remains regarding the characteristics and influence of Green Stormwater Infrastructures (GSIs) on the cooling effects under different weather conditions. To address this issue, a comparative study was conducted between the green spaces in a wetland park with GSIs and a general green space without GSIs. MethodsIn this study, atmospheric temperatures were collected from both green spaces using mobile measurements to compare the cold island effect. In addition, the precise characteristics of the surface temperatures of the underlying surfaces in the wetland park were explored using an Unmanned Aerial Vehicle (UAV). ResultsThe results revealed that green spaces with GSIs had a stronger cooling effect on the surrounding thermal environment than green spaces without GSIs, in most cases. The heat fluxes of different types of underlying surfaces in green spaces with different GSIs varied at different time periods. During the daytime, permeable pavement and some grasslands had a warming effect. The cooling effect of the other underlying surfaces was in the order of water bodies>arbors>shrubs>grasslands. At night, the changes in heat flux were lower, and only the arbors showed cooling due to evapotranspiration.DiscussionThese findings may provide innovative ideas and methods for planning GSIs to mitigate the urban heat island effects

Deciphering the spatiotemporal trade-offs and synergies between ecosystem services and their socio-ecological drivers in the plain river network area

Understanding changes in ecosystem services (ESs) and quantitatively identifying the drivers that influence these changes are essential for achieving sustainable ecosystem development. In this study, multiple data sources and techniques, including meteorological data, land use/cover data, soil data, the InVEST model, and ArcGIS, were used to analyze the spatiotemporal variation characteristics of carbon storage, habitat quality, soil retention, water yield, and crop product supply in Xinghua City from 2000 to 2015. Additionally, we explored the causes of these changes and the interrelationships among these ESs. The results showed that: (1) During the study period, carbon storage and habitat quality declined, water yield fluctuated and increased, and soil retention had small interannual variations. The supply capacity of crop products first increased rapidly and then stabilized. (2) ESs were influenced by multiple drivers, with altitude having the strongest explanatory power for habitat quality and soil retention, and food production having the strongest explanatory power for crop product supply. (3) Relationships between different ESs were variable and changed over time. This study could enrich the understanding of spatial and temporal changes and drivers of ESs in the plain river network area, which has important implications for future land use planning and sustainable development of ESs

LUCIDENIC ACID A INHIBITS THE BINDING OF HACE2 RECEPTOR WITH SPIKE PROTEIN TO PREVENT SARS-COV-2 INVASION

High infection caused by mutations of SARS-CoV-2 calls for new prevention strategy. Ganoderma lucidum known as a superior immunoenhancer exhibits various antiviral effects, whether it can resist SARS-CoV-2 remains unclear. Herein, virtual screening combined with in vitro hACE2 inhibition assays were used to investigate its anti SARS-CoV-2 effect. Potential 54 active components, 80 core targets and 20 crucial pathways were identified by the component-target-pathway network. The binding characters of these components to hACE2 and its complexes with spike protein including omicron variant was analyzed by molecular docking. Lucidenic acid A was selected as the top molecule with high affinity to all receptors by forming hydrogen bonds. Molecular dynamics simulation showed it had good binding stability with the receptor proteins. Finally, in vitro FRET test demonstrated it inhibited the hACE2 activity with IC50 2 μmol/mL. Therefore, lucidenic acid A can prevent the virus invasion by blocking hACE2 binding with SARS-CoV-2

The Effect of Green Stormwater Infrastructures on Urban-Tier Human Thermal Comfort—A Case Study in High-Density Urban Blocks

Green stormwater infrastructure (GSI) is a key approach to greening and cooling high-density blocks. Previous studies have focused on the impact of a single GSI on thermal comfort on sunny days, ignoring rainwater’s role and GSI combinations. Therefore, based on measured data of a real urban area in Nanjing, China, this study utilized 45 single-GSI and combination simulation scenarios, as well as three local climate zone (LCZ) baseline scenarios to compare and analyze three high-density blocks within the city. Among the 32 simulations specifically conducted in LCZ1 and LCZ2, 2 of them were dedicated to baseline scenario simulations, whereas the remaining 30 simulations were evenly distributed across LCZ1 and LCZ2, with 15 simulations allocated to each zone. The physiological equivalent temperature (PET) was calculated using the ENVI-met specification to evaluate outdoor thermal comfort. The objective of this research was to determine the optimal GSI combinations for different LCZs, their impact on pedestrian thermal comfort, GSI response to rainwater, and the effect of GSI on pedestrian recreation areas. Results showed that GSI combinations are crucial for improving thermal comfort in compact high-rise and mid-rise areas, while a single GSI suffices in low-rise areas. In extreme heat, rainfall is vital for GSI’s effectiveness, and complex GSI can extend the thermal comfort improvement time following rainfall by more than 1 h. Adding shading and trees to GSI combinations maximizes thermal comfort in potential crowd activity areas, achieving up to 54.23% improvement. Future GSI construction in high-density blocks should focus on different combinations of GSI based on different LCZs, offering insights for GSI planning in Southeast Asia

Data Efficient and Stability Indicated Sampling for Developing Reactive Machine Learning Potential to Achieve Ultra-long Simulation in Lithium Metal Batteries

Modelling the formation of solid-liquid interphase (SEI) is challenging as its strict requirement with both simulation accuracy and length. Machine learning potential (MLP) based molecular dynamics (MD) simulation is expected to play a role in this field while currently its use is hindered by sampling efficiency and simulation stability. In this work, we tackle the two challenges together. We propose the stability-indicated sampling (SIS) algorithm for efficiently sampling training data using physical infor mation (temperature). Unlike previous strategies, our method does not need prior knowledge of reaction networks or training multiple MLPs for uncertainty estimation. Compared with the recent proposed methods HAIR and DP-GEN, our approach gives significant improvement of sampling efficiency with less requirements with the initial training data, to realize > 10 ns MLPMD simulation using ab initio MD (AIMD) trajectory of just a few ps. We introduce the concept underlying instability consis tency by showing the accuracy of reaction mechanisms and radial distribution function (RDF) can be improved by SIS-MLPMD, although their information is not explicitly used in our sampling decision. Furthermore, we show that long-time MLPMD simu lation of Lithium metal battery (LMB) can not only reproduce some well-known SEI components including LiF, Li2O, LiOH, LiS and the incomplete N-S breaking in high concentration systems, but also ionic aggregation structures of LiF, which is not shown in our AIMD training data but matches previous results of electrochemical impedance spectroscopy. Our work is expected to help accelerate future investigations, especially for studying long-time (≥ ns scale) reaction dynamics in interfacial problems

Distributed optimization for EVs integrated power system considering flexible ramping requirement

More flexible ramping service is required due to the increase of renewable power generation in power systems. Electric vehicles (EVs) could provide such flexible ramping products (FRPs) at low cost while participating in the electricity market through aggregation. However, EVs’ dispatching capability cannot be fully utilized without the right incentives. This paper addresses a distributed optimal model developed between EV aggregators (EVAs) and the independent system operator (ISO). To make such concept, a cloud-edge collaborated market structure is adopted. At the edge level, EVAs assess the dispatching capability and solve the market bidding subproblem. At the cloud level, ISO solves the market clearing subproblem considering system economy and security. The overall problem is solved by the analytical target cascading (ATC) method. Heuristic constraints are also introduced into the model to improve convergence performance. The model is tested on a modified IEEE 30-bus system. Results demonstrate that the proposed method can incentivize EVAs with different owners to shift load and provide FRPs accurately, meanwhile reducing the cost and increasing the consumption of renewable energy effectively

A multiple-fidelity Method for Accurate Simulation of MoS 2 Properties Using JAX-ReaxFF and Neural Network Potentials

Reactive force field (ReaxFF) is one of the most commonly used force field to model the chemical reactions on atomic level. Recently, JAX-ReaxFF, combined with auto- matic differentiation, has been used to efficiently parameterize ReaxFF. However, pre- dicted properties using parameterized ReaxFF may be inaccurate due to the inductive bias of its analytical formula. While neural network-based potentials (NNPs) trained on density functional theory (DFT)-labeled data offer a more accurate method, it re- quires a large amount of training data to be trained from scratch. To overcome these issues, we present a multiple-fidelity method that combines JAX-ReaxFF and NNP, and apply the method on MoS 2 , a promising two-dimensional (2D) semiconductor for flexible electronics due to its excellent mechanical, optical, and electronic properties. By optimizing ReaxFF for MoS 2 and incorporating implicit prior physical information in the functional forms, we show that ReaxFF can serve as a cost-effective way to generate pretraining data, facilitating more accurate simulations of MoS 2 properties, such as the convex hull diagram, sulfur vacancy formation, and interaction with S 8 using SchNet. Moreover, in the Mo-S-H multi-element system, the pretraining strat- egy can reduce root-mean-square errors(RMSE) of energy by 20%. This approach can be extended to a wide variety of material systems, accelerating their computational research

Advanced Nanocellulose‐Based Composites for Flexible Functional Energy Storage Devices

Abstract With the increasing demand for wearable electronics (such as smartwatch equipment, wearable health monitoring systems, and human–robot interface units), flexible energy storage systems with eco‐friendly, low‐cost, multifunctional characteristics, and high electrochemical performances are imperative to be constructed. Nanocellulose with sustainable natural abundance, superb properties, and unique structures has emerged as a promising nanomaterial, which shows significant potential for fabricating functional energy storage systems. This review is intended to provide novel perspectives on the combination of nanocellulose with other electrochemical materials to design and fabricate nanocellulose‐based flexible composites for advanced energy storage devices. First, the unique structural characteristics and properties of nanocellulose are briefly introduced. Second, the structure–property–application relationships of these composites are addressed to optimize their performances from the perspective of processing technologies and micro/nano‐interface structure. Next, the recent specific applications of nanocellulose‐based composites, ranging from flexible lithium‐ion batteries and electrochemical supercapacitors to emerging electrochemical energy storage devices, such as lithium‐sulfur batteries, sodium‐ion batteries, and zinc‐ion batteries, are comprehensively discussed. Finally, the current challenges and future developments in nanocellulose‐based composites for the next generation of flexible energy storage systems are proposed.Recent advances on nanocellulose‐based composites consisting of nanocellulose and other electrochemical materials for emerging flexible energy‐storage devices are comprehensively discussed, with a focus on structure–property–application relationships to optimize their performance. The current challenges and future developments regarding design and fabrication of nanocellulose‐based composites for the next generation of energy‐storage systems are discussed and proposed. imageNational Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809Key Technology Research and Development Program of TianjinFederal Ministry for Economic Affairs and Energy http://dx.doi.org/10.13039/501100006360Ministry for Science and Culture of Lower Saxony http://dx.doi.org/10.13039/501100010570WIPANOChina Scholarship Council http://dx.doi.org/10.13039/501100004543Niedersächsisches Ministerium für Wissenschaft und Kultur http://dx.doi.org/10.13039/501100010570Bundesministerium für Wirtschaft und Energie http://dx.doi.org/10.13039/501100006360Innovation Project of Excellent Doctoral Dissertation of Tianjin University of Science and TechnologyTianjin Research Innovation Project for Postgraduate Students http://dx.doi.org/10.13039/50110001906

Cooperated control strategy of generator re-dispatching and multi-HVDC modulation after ultra HVDC block

With the increase of DC project voltage level and transmission capacity, the security and stability risk caused by DC blocking is gradually increasing. Aiming at reserve dispatch after ultra-high voltage direct current (UHVDC) block, scenarios of DC power modulation participating in dispatching are presented. Mathematical models of generator re-dispatching incorporated control of DC in AC/DC hybrid grid in three situations in terms of enough reserve capacity in the disturbed province, regional reserve capacity sufficient and insufficient to make up for the power deficiency are presented. Then, a decision-aid system for optimal reserve dispatch after UHVDC block is proposed. Simulation results of Central China power grid indicate that the proposed scheduling scheme can reduce the operation risks of security and load loss if necessary