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  • Title: Isotopic imprints of aerosol ammonium over the north China plain.
    Author: Mgelwa AS, Song L, Fan M, Li Z, Zhang Y, Chang Y, Pan Y, Gurmesa GA, Liu D, Huang S, Qiu Q, Fang Y.
    Journal: Environ Pollut; 2022 Dec 15; 315():120376. PubMed ID: 36228846.
    Abstract:
    Atmospheric PM2.5 poses a variety of health and environmental risks to urban environments. Ammonium is one of the main components of PM2.5, and its role in PM2.5 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 PM2.5 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 PM2.5. 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.
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