Air quality modelling at street level in the urban areas of Hong Kong

2014 ◽  
Author(s):  
Xiaolin Xie
Keyword(s):  
Hong Kong ◽  
Air Quality ◽  
Urban Areas ◽  
Air Quality Modelling ◽  
Street Level

Building spatial-temporal NO2 land use regression models in complex urban environment

2020 ◽  
Author(s):  
Peng Wei ◽  
Yang Xing ◽  
Li Sun ◽  
Zhi Ning
Keyword(s):  
Land Use ◽  
Hong Kong ◽  
Air Quality ◽  
Urban Environment ◽  
Real Time ◽  
Urban Areas ◽  
Personal Exposure ◽  
Pollutant Emission ◽  
Land Use Regression ◽  
Pollutant Distribution

<p>Air quality and traffic-related pollutants in urban areas are major concerns especially in meg-cities. Current Air Quality Monitoring Station (AQMS) cannot sufficiently reveal these pollution conditions with limited point measurements and limited information cannot supply adequate insight on personal exposure in a complex urban environment. Land Use Regression (LUR) model provided a feasible solution for estimating outdoor personal exposure by adding multiple data sources. However, fixed-site passive monitoring still lacks enough spatial coverage or spatial flexibility to estimate pollutant distribution at the fine-scale level.</p><p>A Mobile Air Sensor Network (MASEN) project was deployed in the Hong Kong area, with electrochemical gas sensors installed on the routine buses to capture on-road NO<sub>x</sub> pollutant measurement, the data was collected by the integrated sensor system and transfer to the database for real-time visualization. Compared with previous mobile measurements used for LUR model building which limited to 1-2 routes, this measurement covered major roads in the Hong Kong area and get an overview of pollutant distribution at various ambient. Two main variables were introduced to improve the model performance: 1) Sky View Factor (SVF) which represented pollutant dispersion status were obtained from Google street view image, a deep learning model was used for scene parsing to recognized targets in this procedure, 2) a Real-time Traffic Congestion Index (RTCI) which represented traffic pollutants emission was obtained from Google map and merged with road network. A common LUR model will be built based on a distance-decay regression selection strategy for variables selection. Meanwhile, a spatial-temporal LUR model will be built which contained both diurnal variability and day-to-day variability. Finally, a high-resolution pollution map of the urban areas will illustrate NO<sub>2</sub> pollutant distribution.</p><p>In this work, we aimed at estimating traffic-related pollutants in a complex city environment and identifying hotspots at both spatial and temporal aspects. Meanwhile, the novel data source which closely associated with traffic-related pollutant emission also gives a better understanding of guidance on urban planning.</p>

Reducing NO2 Pollution over Urban Areas: Air Quality Modelling as a Fundamental Management Tool

2012 ◽  
Vol 223 (8) ◽  
pp. 5307-5320 ◽  
Author(s):  
C. Borrego ◽  
A. Monteiro ◽  
E. Sá ◽  
A. Carvalho ◽  
D. Coelho ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Management Tool ◽  
Air Quality Modelling ◽  
No2 Pollution

Air Quality Modelling for the Hong Kong Path Project

2006 ◽  
pp. 125-133
Author(s):  
Julie Noonan ◽  
William Physick ◽  
Martin Cope ◽  
Manuela Burgers ◽  
Marilyn Olliff
Keyword(s):  
Hong Kong ◽  
Air Quality ◽  
Air Quality Modelling

Improving the Protection of Children Against Air Pollution Threats in Romania � The RokidAIR Project Approach and Future Perspectives

2017 ◽  
Vol 68 (4) ◽  
pp. 841-846
Author(s):  
Hai-Ying Liu ◽  
Daniel Dunea ◽  
Mihaela Oprea ◽  
Tom Savu ◽  
Stefania Iordache
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Health Effects ◽  
Urban Areas ◽  
Behavioural Change ◽  
Health Assessment ◽  
Warning System ◽  
Personal Exposure ◽  
Mobile Technologies ◽  
Quality Maps

This paper presents the approach used to develop the information chain required to reach the objectives of the EEA Grants� RokidAIR project in two Romanian cities i.e., Targoviste and Ploiesti. It describes the PM2.5 monitoring infrastructure and architecture to the web-based GIS platform, the early warning system and the decision support system, and finally, the linking of air pollution to health effects in children. In addition, it shows the analysis performance of the designed system to process the collected time series from various data sources using the benzene concentrations monitored in Ploiesti. Moreover, this paper suggests that biomarkers, mobile technologies, and Citizens� Observatories are potential perspectives to improve data coverage by the provision of near-real-time air quality maps, and provide personal exposure and health assessment results, enabling the citizens� engagement and behavioural change. This paper also addresses new fields in nature-based solutions to improve air quality, and studies on air pollution and its mental health effects in the urban areas of Romania.

Flood alleviation in a heavily urbanized area – Kai Tak Nullah, Hong Kong

2012 ◽  
Vol 7 (4) ◽  
Author(s):  
Alan K. L. Chan ◽  
Colin K. C. Wong ◽  
Robin H. N. Lee ◽  
Mike W. H. Cho
Keyword(s):  
Hong Kong ◽  
Public Engagement ◽  
Urban Areas ◽  
Hydraulic Modelling ◽  
The Public ◽  
Design Considerations ◽  
Urbanized Area ◽  
Development Area ◽  
The Government ◽  
Exercise Design

The existing Kai Tak Nullah flows from Po Kong Village Road along Choi Hung Road and Tung Tau Estate into Kai Tak Development Area before discharging into the Victoria Harbour. Historically its upstream has been subject to flooding under storm conditions and this has had serious repercussions for the adjacent urban areas. A study has been commissioned by the Drainage Services Department of the Government of the Hong Kong Special Administrative Region (HKSAR), China to investigate the flood mechanisms and to provide flood alleviation measures by improving the capacity of the Kai Tak Nullah. In addition to flood alleviation, there is a strong public aspiration to rehabilitate the Kai Tak Nullah by a comparatively natural river design. Since the Kai Tak Nullah is located within a heavily urbanized area, traffic and environmental impacts are also highly concerned. The final flood alleviation scheme has thus had to strike a balance among the aforesaid factors with assistance from the hydraulic modelling utilizing InfoWorks Collection Systems (CS) software. This paper presents the public engagement exercise, design considerations, methodologies, and recommendations regarding the reconstruction and rehabilitation of the Kai Tak Nullah.

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