The Study of Emission Inventory on Anthropogenic Air Pollutants and Source Apportionment of PM2.5 in the Changzhutan Urban Agglomeration, China

Air pollutant dispersion around high-rise building cluster forms: the case of Port City, Colombo, Sri Lanka

Air quality in dense urban environments is a growing concern, especially in rapidly developing cities. In the face of growing traffic associated with urbanisation, there is evidence for high levels of pollutant concentration at street level which is influenced by building forms. In this paper, we examine the potential effects of high-rise, cluster developments permitted by the local planning authorities in the newly established Port City development in Colombo, Sri Lanka. We designed possible building forms based on specific guidelines for the development in terms of plot coverage, floor area ratio, and maximum height. The three-dimensional building clusters were simulated using the RANS RNG k-epsilon turbulence model, to determine pollutant dispersion of a complex street formation in a high-dense high-rise building cluster, within the development and the surrounding context (existing Colombo). Results show that while increased porosity within the built fabric facilitates better pollution dispersion, a low correlation was seen between wind velocity and pollution concentration, especially in deep narrow high-rise canyons. Dispersion patterns at street level and at the urban canopy differed with each built form and are dependent on each canyon geometry. Thus, the study highlights the need for building regulations to take a holistic approach to capture the various elements of a complex urban cluster rather than the current two-dimensional parameters proposed for Port City, Colombo.

Causality and dynamic spillover effects of megacities on regional industrial pollution reduction

Regional economic power and local environmental policies have a substantial impact on pollution reduction in urban agglomerations (UAs); however, whether megacities in UAs exert spillover effects of pollution reduction on surrounding cities remains unknown. This study presents a causal analytic framework to evaluate the spillover effects of megacities on regional industrial pollution reduction in three major UAs in China between 2005 and 2016. The interaction between industrial pollution reduction and infrastructure investment indicators was also examined. Results indicated a good fit for spatial spillover of sulfur dioxide reduction (SR) in the Pearl River Delta (PRD) and Yangtze River Delta (YRD) but not in the Beijing-Hebei-Tianjin cluster (JJJ). Spatial spillover of dust reduction (DR) was evident in the PRD and JJJ but not the YRD. Spatial analysis showed that infrastructure investment indicators, at megacity and UA levels, had short-term spillover effects on surrounding cities for DR but not SR. However, spatial spillover effects, at both the city and UA levels, were substantial over the long term. In addition, the results of the spatial-time lag analysis suggest a linear relationship between pollution control-related infrastructure investment indicators and long-term pollution reduction. This study provides new information regarding the spatial spillover effects of megacities on regional industrial pollution reduction in UAs.

Isotopic imprints of aerosol ammonium over the north China plain

Atmospheric PM_2.5 poses a variety of health and environmental risks to urban environments. Ammonium is one of the main components of PM_2.5, and its role in PM_2.5 pollution will likely increase in the coming years as NH₃ emissions are still unregulated and rising in many cities worldwide. However, partitioning urban NH₄⁺ sources remains challenging. Although the ¹⁵N natural abundance (δ¹⁵N) analysis is a promising approach for this purpose, it has seldom been applied across multiple cities within a given region. This limits our understanding of the regional patterns and controls of NH₄⁺ sources in urban environments. Here, we collected PM_2.5 samples using an active sampling technique during winter at six cities in the North China Plain to characterize the concentrations, δ¹⁵N and sources of NH₄⁺ in PM_2.5. We found substantial variations in both the concentrations and δ¹⁵N of NH₄⁺ among the sites. The mean NH₄⁺ concentrations across the six cities ranged from 3.6 to 12.1 μg m^-3 on polluted days and from 0.9 to 10.6 μg m^-3 on non-polluted days. The δ¹⁵N ranged from 6.5‰ to 13.9‰ on polluted days and from 8.7‰ to 13.5‰ on non-polluted days. The δ¹⁵N decreased with increasing NH₄⁺ concentrations at all six sites. We found that non-agricultural sources (vehicle exhaust, ammonia slip and urban wastes) contributed 72%-94% and 56%-86% of the NH₄⁺ on polluted and non-polluted days, respectively, and that during polluted days, combustion-related emissions (vehicle exhaust and ammonia slip) were positively associated with the proportion of urban area, population density and number of vehicles, highlighting the importance of local sources of particulate pollution. This study suggests that the analysis of ¹⁵N in aerosol NH₄⁺ is a promising approach for apportioning atmospheric NH₃ sources over a large region, and this approach has potential for mapping rapidly and precisely the sources of NH₃ emissions.

Spatial and Socio-Classification of Traffic Pollutant Emissions and Associated Mortality Rates in High-Density Hong Kong via Improved Data Analytic Approaches

Excessive traffic pollutant emissions in high-density cities result in thermal discomfort and are associated with devastating health impacts. In this study, an improved data analytic framework that combines geo-processing techniques, social habits of local citizens like traffic patterns and working schedule and district-wise building morphologies was established to retrieve street-level traffic NOx and PM2.5 emissions in all 18 districts of Hong Kong. The identification of possible human activity regions further visualizes the intersection between emission sources and human mobility. The updated spatial distribution of traffic emission could serve as good indicators for better air quality management, as well as the planning of social infrastructures in the neighborhood environment. Further, geo-processed traffic emission figures can systematically be distributed to respective districts via mathematical means, while the correlations of NOx and mortality within different case studies range from 0.371 to 0.783, while varying from 0.509 to 0.754 for PM2.5, with some assumptions imposed in our study. Outlying districts and good practices of maintaining an environmentally friendly transportation network were also identified and analyzed via statistical means. This newly developed data-driven framework of allocating and quantifying traffic emission could possibly be extended to other dense and heavily polluted cities, with the aim of enhancing health monitoring campaigns and relevant policy implementations.