Search

Atmospheric ambient gaseous ammonia (NH 3 ), the most abundant alkaline gas, affects public health and climate change through its key role in the formation of secondary aerosols via reactions with acidic gases. Estimation of the contributions of ammonia sources is very challenging in the urban atmosphere. Stable nitrogen isotope ratio (δ 15 N) measurements have shown that urban aerosol NH 4 + and gaseous NH 3 are derived from fossil fuel combustion-related (FF) sources, such as coal combustion, NH 3 slip, and vehicle exhaust, and volatilization-related sources, such as agriculture and urban water volatilization. Biomass burning (BB) sources, especially residential biofuel, can produce vast quantities of NH 3 and other pollutants and may greatly influence air quality and contribute to increased urban NH 3 emissions. In the present study, we continually collected PM 2.5 samples at three urban sites in Central China during autumn and analyzed the major water-soluble ions and δ 15 N values of aerosol NH 4 + . The concentrations of NH 4 + from BB increased in all three cities from September to November 2017, which was likely caused by increased heating demands with the decrease in temperature during the season. Furthermore, BB was responsible for a severe haze event (maximum PM 15 N values did not show this pattern. According to the Bayesian model after isotope fractionation correction, FF sources contributed to 56.4 ± 17.1%, 46.4 ± 18.2%, and 51.8 ± 14.9% of aerosol NH 4 + in Nanchang, Wuhan, and Changsha, respectively, throughout autumn. The contributions from BB sources were 34.5 ± 20.4%, 46.4 ± 21.4%, and 40.4 ± 17.4% for Nanchang, Wuhan, and Changsha, respectively. We also found the fraction of aerosol NH 4 + from BB increased in all three cities from September to November 2017, which was likely caused by increased heating demands with the decrease in temperature during the season. Furthermore, BB was responsible for a severe haze event (maximum PM 2.5 of 205.69 μg/m 3 ) in Nanchang. These findings suggest government controls to improve air quality should include BB sources in addition to FF sources., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The determination of the spatiotemporal patterns and driving factors of PM 2.5 is of great interest to the atmospheric and climate science community, who aim to understand and better control the atmospheric linkage indicators. However, most previous studies have been conducted on pollution-sensitive cities, and there is a lack of large-scale and long-term systematic analyses. In this study, we investigated the spatiotemporal evolution of PM 2.5 and its influencing factors by using an exploratory spatiotemporal data analysis (ESTDA) technique and spatial econometric model based on remote sensing imagery inversion data of the Yangtze River Economic Belt (YREB), China, between 2000 and 2016. The results showed that 1) the annual value of PM 2.5 was in the range of 23.49-37.67 μg/m 3 with an inverted U-shaped change trend, and the PM 2.5 distribution presented distinct spatial heterogeneity; 2) there was a strong local spatial dependence and dynamic PM 2.5 growth process, and the spatial agglomeration of PM 2.5 exhibited higher path-dependence and spatial locking characteristics; and 3) the endogenous interaction effect of PM 2.5 was significant, where each 1% increase in the neighbouring PM 2.5 levels caused the local PM 2.5 to increase by at least 0.4%. Natural and anthropogenic factors directly and indirectly influenced the PM 2.5 levels. Our results provide spatial decision references for coordinated trans-regional air pollution governance as well as support for further studies which can inform sustainable development strategies in the YREB., Competing Interests: Declaration of competing interest The authors declare that there is no conflict of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)