Suitable temperature indicator for adverse health impacts in sub-tropical cities: a case study in Hong Kong from 2010-2019.

Heat-health warning systems and services are important preventive actions for extreme heat, however, global evidence differs on which temperature indicator is more informative for heat-health outcomes. We comprehensively assessed temperature predictors on their summer associations with adverse health impacts in a high-density subtropical city. Maximum, mean, and minimum temperatures were examined on their associations with non-cancer mortality and hospital admissions in Hong Kong during summer seasons 2010-2019 using Generalized Additive Models and Distributed Lag Non-linear Models.

Interpretable semi-supervised clustering enables universal detection and intensity assessment of diverse aviation hazardous winds.

The identification of aviation hazardous winds is crucial and challenging in air traffic management for assuring flight safety, particularly during the take-off and landing phases. Existing criteria are typically tailored for special wind types, and whether there exists a universal feature that can effectively detect diverse types of hazardous winds from radar/lidar observations remains as an open question. Here we propose an interpretable semi-supervised clustering paradigm to solve this problem, where the prior knowledge and probabilistic models of winds are integrated to overcome the bottleneck of scarce labels (pilot reports).

AI-supported estimation of safety critical wind shear-induced aircraft go-around events utilizing pilot reports.

The occurrence of wind shear and severe thunderstorms during the final approach phase contributes to nearly half of all aviation accidents. Pilots usually employ the go-around procedure in order to lower the likelihood of an unsafe landing. However, multiple factors influence the go-arounds induced by wind shear.

Interpretable ensemble imbalance learning strategies for the risk assessment of severe-low-level wind shear based on LiDAR and PIREPs.

The occurrence of severe low-level wind shear (S-LLWS) events in the vicinity of airport runways poses a significant threat to flight safety and exacerbates a burgeoning problem in civil aviation. Identifying the risk factors that contribute to occurrences of S-LLWS can facilitate the improvement of aviation safety. Despite the significant influence of S-LLWS on aviation safety, its occurrence is relatively infrequent in comparison to non-SLLWS incidents.

Numerical simulation research on the overturning of gantry crane by downbursts.

Based on the simulation of the fluid-structure interaction response, the cause of an overturning of a gantry crane induced by a downburst in Shenzhen is studied in this paper. According to the results, (1) Vicroy's downburst model could establish the steady-state wind field of the downburst more reasonably when there was only low-level wind speed observation data, and its simulation results were close to the two-dimensional downburst numerical simulation results; (2) Compared with the normal exponential vertical profile of wind speed, the disturbance caused by the front girder of the double-girder gantry crane structure under the downburst wind field was more severe, which increases the probability of the gantry crane overturning. (3) The downwind displacement of the main girder of the gantry crane under the condition of downburst is far greater than that under the normal condition.

Assessing wind field characteristics along the airport runway glide slope: an explainable boosting machine-assisted wind tunnel study.

Aircraft landings are especially perilous when the wind is gusty near airport runways. For this reason, an aircraft may deviate from its glide slope, miss its approach, or even crash in the worst cases. In the study, we used the state-of-the-art glass-box model, the Explainable Boosting Machine (EBM), to estimate the variation in headwind speed and turbulence intensity along the airport runway glide slope and to interpret the various contributing factors.

Short-Term Nationwide Airport Throughput Prediction With Graph Attention Recurrent Neural Network.

With the dynamic air traffic demand and the constrained capacity resources, accurately predicting airport throughput is essential to ensure the efficiency and resilience of air traffic operations. Many research efforts have been made to predict traffic throughputs or flight delays at an airport or over a network. However, it is still a challenging problem due to the complex spatiotemporal dynamics of the highly interacted air transportation systems.

Intercomparison of Local Warming Trends of Shanghai and Hong Kong Based on 120-Year Temperature Observational Data.

Using surface air temperature observations from 1901 to 2020, this study compared the warming trends of Shanghai and Hong Kong over a period of 120 years. The statistical results reveal the following: (1) The average temperatures of the two cities underwent fluctuating increases during the past 120 years, with linear warming rates of 0.23 °C/decade in Shanghai and 0.

Probable cross-corridor transmission of SARS-CoV-2 due to cross airflows and its control.

A COVID-19 outbreak occurred in May 2020 in a public housing building in Hong Kong - Luk Chuen House, located in Lek Yuen Estate. The horizontal cluster linked to the index case' flat (flat 812) remains to be explained. Computational fluid dynamics simulations were conducted to obtain the wind-pressure coefficients of each external opening on the eighth floor of the building.

Impact of the COVID-19 on the vertical distributions of major pollutants from a tower in the Pearl River Delta.

The outbreak of the 2019 novel coronavirus (COVID-19) had a large impact on human health and socio-economics worldwide. The lockdown implemented in China beginning from January 23, 2020 led to sharp reductions in human activities and associated emissions. The declines in primary pollution provided a unique opportunity to examine the relationship between anthropogenic emissions and air quality.

On the Use of Dynamic Calibration to Correct Drop Counter Rain Gauge Measurements.

Dynamic calibration was performed in the laboratory on two catching-type drop counter rain gauges manufactured as high-sensitivity and fast response instruments by Ogawa Seiki Co. Ltd. (Japan) and the Chilbolton Rutherford Appleton Laboratory (UK).

Dual challenges of heat wave and protective facemask-induced thermal stress in Hong Kong.

During the COVID-19 pandemic, wearing protective facemasks (PFMs) can effectively reduce infection risk, but the use of PFMs can amplify heat-related health risks. We studied the amplified PFM-induced human thermal stress via both field measurements and model simulations over a typical subtropical mountainous city, Hong Kong. First, a hot and humid PFM microenvironment has been observed with high temperature (34-35 °C) and high humidity (80-95%), resulting in an aggravated facial thermal stress with a maximal PFM-covered facial heat flux of 500 W/m under high-intensity activities.

Understanding heat patterns produced by vehicular flows in urban areas.

Vehicular traffic has strong implication in the severity and degree of Urban Heat Island (UHI) effect in a city. It is crucial to map and monitor the spatio-temporal heat patterns from vehicular traffic in a city. Data observed from traffic counting stations are readily available for mapping the traffic-related heat across the stations.

Process analysis of a regional air pollution episode over Pearl River Delta region, China, using the MM5-CMAQ model.

Unlabelled: This study focuses on the influences of a warm high-pressure meteorological system on aerosol pollutants, employing the simulations by the Models-3/CMAQ system and the observations collected during October 10-12, 2004, over the Pearl River Delta (PRD) region. The results show that the spatial distributions of air pollutants are generally circular near Guangzhou and Foshan, which are cities with high emissions rates. The primary pollutant is particulate matter (PM) over the PRD.

Accurate extraction of Lagrangian coherent structures over finite domains with application to flight data analysis over Hong Kong International Airport.

Locating Lagrangian coherent structures (LCS) for dynamical systems defined on a spatially limited domain present a challenge because trajectory integration must be stopped at the boundary for lack of further velocity data. This effectively turns the domain boundary into an attractor, introduces edge effects resulting in spurious ridges in the associated finite-time Lyapunov exponent (FTLE) field, and causes some of the real ridges of the FTLE field to be suppressed by strong spurious ridges. To address these issues, we develop a finite-domain FTLE method that renders LCS with an accuracy and fidelity that is suitable for automated feature detection.