A modelling system with adjustable emission inventories for cross-boundary air quality management in Hong Kong and the Pearl River Delta, China
Journal:《Computers Environment & Urban Systems》 , 2017 , 62 :222-232
Cite as:Zhang C, Lin H, Chen M, et al. A modelling system with adjustable emission inventories for cross-boundary air quality management in Hong Kong and the Pearl River Delta, China. Computers, Environment and Urban Systems, 2017, 62:222-232.
Abstract:Air quality problems are attracting much attention in Hong Kong (HK) and the Pearl River Delta (PRD) in China. The complex and regional characteristics of air quality problems call for a comprehensive modelling system with a highly reliable simulation and effective communication tools for decision-makers and participants from multiple disciplines. In this paper, we used a modelling management method to develop a Cyberinfrastructure system that couples meteorological and air quality models with a visual analysis to improve the cognition and management of air quality problems. The database management of both the data and the modelling parameters is an innovative advantage of this system; this will be helpful not only for sharing modelling knowledge but also for improving the acknowledgement of modelling scenarios, which are usually conducted by various stakeholders. On the basis of 19 categories of emission inventories that provide detailed information about multiple pollutants in the 11 cities in the study area, this system provides an authoritative and adjustable emission inventory to draw an accurate scientific picture for decision-makers. We applied this system to a case study to investigate the effects of emission control of nitrogen dioxide from vehicles in HK and the PRD on air quality. The simulation showed that the air quality improvement from emission control was very limited and suggested that regional and super-regional co-operation involving the comprehensive emission control of multiple pollutants may be more effective in creating a better future.