基于遥感热红外图像研究哈尔滨市污水处理厂热岛效应

热岛效应正成为城市气候变化的主要因素之一。作为城市必要的设施,污水处理厂因其产生的温室气体排放和处理运行过程中消耗大量的能源和资源对全球性气候变化产生影响,而其对区域性气候变化的影响却鲜有研究。利用热红外遥感图像反演地表温度是研究和监测热岛效应常用的手段之一。通过利用LandsatTM/ETM+图像对哈尔滨市九座污水处理厂2000-2013年的地表温度进行反演,并利用热岛强度来评价污水处理厂的热岛效应。研究发现,十三年间污水处理厂热岛强度增加了53%。通过主成分分析和多元线性回归分析发现,污水处理厂热岛强度与处理水量、城市表面温度等呈正相关性,而与排放标准、污水处理厂距离松花江中心的距离、建设施工状态和主体处理工艺呈负相关性。

An AI-empowered indoor digital contact tracing system for COVID-19 outbreaks in residential care homes

An AI-empowered indoor digital contact-tracing system was developed using a centralized architecture and advanced low-energy Bluetooth technologies for indoor positioning,with careful preservation of privacy and data security.We analyzed the contact pattern data from two RCHs and investigated a COVID-19 outbreak in one study site.To evaluate the effectiveness of the system in containing outbreaks with minimal contacts under quarantine,a simulation study was conducted to compare the impact of different quarantine strategies on outbreak containment within RCHs.The significant difference in contact hours between weekdays and weekends was observed for some pairs of RCH residents and staff during the two-week data collection period.No significant difference between secondary cases and uninfected contacts was observed in a COVID-19 outbreak in terms of their demographics and contact patterns.Simulation results based on the collected contact data indicated that a threshold of accumulative contact hours one or two days prior to diagnosis of the index case could dramatically increase the efficiency of outbreak containment within RCHs by targeted isolation of the close contacts.This study demonstrated the feasibility and efficiency of employing an AI-empowered system in indoor digital contact tracing of outbreaks in RCHs in the post-pandemic era.

Unraveling adaptive changes in electric vehicle charging behavior toward the postpandemic era by federated meta-learning

Dear Editor,Electric vehicle(EV)sales have significantly grown over the years to fulfill growing demands for economic travel and greenhouse gas mitigation.1 However,the surge in the number of EVs has led to charging anxiety as users struggle to find an available charging station before running out of electricity,resulting in longer reserve and waiting times.2 Moreover,severe mobility restrictions caused by infectious diseases,such as coronavirus disease 2019(COVID-19),have greatly affected people’s travel behavior3,4 and hindered their willingness to use EVs,given that charging in public spaces consumes time and increases the risk of contracting the virus.5 This implies that in the postpandemic era,in which individuals coexist with the virus,the interplay between the two important trends,namely vehicle electrification and mobility restrictions,can extensively affect people’s daily commuting by using EVs.

The effects of different travel modes and travel destinations on COVID-19 transmission in global cities

The international community has made significant efforts to flatten the COVID-19 curve,including predicting transmission[1,2],executing unprecedented global lockdowns and social distancing[3,4],promoting the wearing of facemasks and social distancing measures[5],and isolating confirmed cases and contacts[6].Because of the adverse consequences of these lockdown measures[7],many cities have reopened so they can rebuild their economies.However,as mobility has gradually returned towards normal,imported cases from unknown sources have disrupted the recovery situation,and cities are continually at high risk of new waves of infection[8,9]since airborne transmission is the dominant transmission route[10].

Synergetic analysis of springtime air pollution episodes over Gwangju,Korea

The characteristics of springtime aerosols,including their optical and microphysical properties,were analyzed for the months of March to May of 2009 in Gwangju（35.23°N,126.84°E）,Korea.A high Light Detection and Ranging（LIDAR）-derived aerosol depolarization ratio（δ） of 0.25 ± 0.04 was determined on dust particles during the observation period.The？ngstr？m exponent values of the 440–870 nm wavelength pair（？_（440–870）） and single-scattering albedo at 675 nm（Ω_（675）） measured by a CIMEL sun/sky radiometer were 0.77 ± 0.19 and 0.95 ±0.01,respectively.The elevated dust layers reached a maximum elevation of 4 km above sea level.Anthropogenic/smoke particles that originated from highly populated/industrialized regions could be distinguished by their relatively smaller particle size（？_（440–870） ranged between1.33 and 1.36） and higher light-absorbing（Ω_（675） of 0.92 ± 0.01） characteristics.These aerosols are mostly distributed at altitudes 〈 1.2 km.The root-mean-square deviation（RMSD） between the aerosol optical depth（AOD,τ） derived from LIDAR_（（τ_（LIDAR））） and from the CIMEL sun/sky radiometer_（（τ_（CIMEL））） varied with respect to the surface PM10 concentration.The RMSD between τ_（LIDAR） and τ_（CIMEL） was as low as 13% under lower PM_（10） concentration levels（〈 100 μg/m^3）.In contrast,the RMSD between τ_（LIDAR） and τ_（CIMEL） increased three times（~31%） under high surface PM_（10） concentration levels（〉100 μg/m^3）.These results suggest that the accuracy of τ_（LIDAR） is influenced by specific atmospheric conditions,regardless of its uncertainty.