High-resolution multi-scale air pollution system:Evaluation of modelling performance and emission control strategies

A high percentage of the world's population lives in areas where air pollutant concentrations exceed the World Health Organization guidelines.This work aims to develop and test,a high-resolution multi-scale air pollution modelling system by integrating a set of adequate tools.This system is able to provide detailed air pollutant concentrations in urban areas and support air quality management strategies through a better identification of different atmospheric processes.It also allows furthering the design and assessment of air pollution control measures for a specific area.To evaluate its performance and suitability,the system was applied to the Macao Special Administrative Region(SAR),China,one of the most densely populated areas on earth,during a winter period when this area is affected by high levels of Particulate Matter(PM).Although the developed system tends to underestimate the PM concentrations,it revealed a good performance in reproducing the temporal and spatial air pollution patterns.Several exceedances of the Chinese air quality standards were calculated and high population exposure to PM pollution was estimated.The tested urban atmospheric emission reduction scenarios have shown air quality improvements,indicating that emission reduction measures at urban level should focus on the domestic sector.However,it is crucial to implement joint pollution prevention strategies with neighbouring regions to improve the air quality in Macao SAR.The approach developed in this work can support policymakers in defining new strategies to reduce atmospheric pollution in urban areas.

Application of PCR and real-time PCR for monitoring cyanobacteria, Microcystis spp. and Cylindrospermopsis raciborskii in Macao freshwater reservoir

Freshwater algal blooms have become a growing concern world-wide. They are caused by a high level ofcyanobacteria, predominantly Microcystis spp. and Cylindrospermopsis raciborskii, which can produce microcystin and cylindrospermopsin, respectively. Longtime exposure to these cyanotoxins may affect public health, thus reliable detection, quantification, and enumeration of these harmful algae species has become a priority in water quality management. Traditional manual enumeration of algal bloom cells primarily involves microscopic identification which limited by inaccuracy and time-consumption. With the development of molecular techniques and an increasing number of microbial sequences available in the Genbank database, the use of molecular methods can be used for more rapid, reliable, and accurate detection and quantification. In this study, multiplex polymerase chain reaction （PCR） and real-time quantitative PCR （qPCR） techniques were developed and applied for monitoring cyanobacteria Microcystis spp. and C. raciborskii in the Macao Storage Reservoir （MSR）. The results showed that the techniques were successful for identifying and quantifying the species in pure cultures and mixed cultures, and proved to be a potential application for water sampling in MSR. When the target species were above 1 million cells/L, similar cell numbers estimated by microscopic enumeration and qPCR were obtained. Further quantification in water samples indicated that the ratio of the estimated number of cell by microscopy and qPCR was 0.4-12.9 for cyanobacteria and 0.2-3.9 for C. raciborskii. However, Microcystis spp. was not observed by manual enumeration, while it was detected at low levels by qPCR, suggesting that qPCR is more sensitive and accurate. Thus the molecular approaches provide an additional reliable monitoring option to traditional micro- scopic enumeration for the ecosystems monitoring program.