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1.
J Hazard Mater ; 476: 135122, 2024 Sep 05.
Artículo en Inglés | MEDLINE | ID: mdl-38986411

RESUMEN

The extensive utilization of rubber-related products can lead to a substantial release of p-phenylenediamine (PPD) antioxidants into the environment. In recent years, studies mainly focus on the pollution characteristics and health risks of PM2.5-bound PPDs. This study presents long-time scale data of PPDs and N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine quinone (6PPD-Q) in PM2.5 and proposes the innovative use of PPDs as new markers for vehicular emissions in the Positive Matrix Factorization (PMF) source apportionment. The results indicate that PPDs and 6PPD-Q were detectable in 100 % of the winter PM2.5 samples, and the concentration ranges of PPDs and 6PPD-Q are 15.6-2.92 × 103 pg·m-3 and 3.90-27.4 pg·m-3, respectively, in which 6PPD and DNPD are the main compounds. Moreover, a competitive formation mechanism between sulfate, nitrate, ammonium (SNA) and 6PPD-Q was observed. The source apportionment results show that the incorporation of PPDs in PMF reduced the contribution of traffic source to PM2.5 from 13.5 % to 9.5 %. In the traffic source factor profiles, the load of IPPD, CPPD, DPPD, DNPD and 6PPD reaches 91.8 %, 91.6 %, 92.9 %, 80.6 % and 87.2 %, respectively. It`s amazing that traditional markers of traffic source, which often overlap with coal burning and industrial sources, over-estimated the contribution of vehicles by one third or more. The discovery of PPDs as specific markers for vehicular emissions holds significant utility, particularly considering the growing proportion of new energy vehicles in the future. The results may prove more accurate policy implications for pollution control. SYNOPSIS: PPDs are excellent indicators of vehicle emissions, and PMF without PPDs over-estimated the contribution of traffic source to PM2.5.

2.
Huan Jing Ke Xue ; 44(5): 2430-2440, 2023 May 08.
Artículo en Chino | MEDLINE | ID: mdl-37177918

RESUMEN

To investigate the change characteristics of secondary inorganic ions in PM2.5 at different pollution stages before and after COVID-19, the online monitoring of winter meteorological and atmospheric pollutant concentrations in Zhengzhou from December 15, 2019 to February 15, 2020 was conducted using a high-resolution (1 h) online instrument. This study analyzed the causes of the haze process of COVID-19, the diurnal variation characteristics of air pollutants, and the distribution characteristics of air pollutants at different stages of haze.The results showed that Zhengzhou was mainly controlled by the high-pressure ridge during the haze process, and the weather situation was stable, which was conducive to the accumulation of air pollutants. SNA was the main component of water-soluble ions, accounting for more than 90%. Home isolation measures during COVID-19 had different impacts on the distribution characteristics of air pollutants in different haze stages. After COVID-19, the concentration of PM2.5 in the clean, occurrence, and dissipation stages increased compared with that before COVID-19 but significantly decreased in the development stage. The home isolation policy significantly reduced the high value of PM2.5. The concentrations of NO2, SO2, NH3, and CO were the highest in the haze development stage, showing a trend of first increasing and then decreasing. The concentration of O3 was lowest in the pre-COVID-19 development stage but highest in the post-COVID-19 development stage. The linear correlation between[NH4+]/[SO42-] and[NO3-]/[SO42-] at different time periods before and after COVID-19 was strong, indicating that the home isolation policy of COVID-19 did not change the generation mode of NO3-, and the corresponding reaction was always the main generation mode of NO3-. The correlation between[excess-NH4+] and[NO3-] was high in different periods before COVID-19, and NO3- generation was related to the increase in NH3 or NH4+ in the process of PM2.5 pollution in Zhengzhou.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , COVID-19 , Humanos , Material Particulado/análisis , Monitoreo del Ambiente/métodos , COVID-19/epidemiología , Aerosoles y Gotitas Respiratorias , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Iones/análisis , Estaciones del Año , China/epidemiología
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