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- W2615360907 abstract "To obtain a comprehensive picture of characteristics and sources of haze pollution in Zhengzhou, we analyzed annual air pollutant (fine particulate matter (PM2.5), inhalable particulate matter (PM10), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2) and ozone (O3)) observations at nine monitoring stations from March 1, 2013 to February 28, 2014. A case study on haze pollution was carried out using observations, metrological data, aerosol optical depth (AOD) values and Hybrid receptor models. Results of annual variations of air pollutants indicated that PM2.5 pollution in Zhengzhou was the most severe. Monthly variations revealed that all air pollutants except O3 showed peak values in December because of the increased local emissions during heating, while the lowest value found in August was probably because of the favorable dispersion conditions. The monthly variation patterns of O3 concentrations show the peak values in August due to higher temperature and stronger solar radiation. The diurnal variations showed that PM2.5 concentration variations were consistent with the traffic flow. The high values of PM2.5/PM10 and PM2.5/CO occurred in the afternoon probably due to the strong photochemical reactions. Results of the case study showed that relative humidity and wind speed were the main meteorological factors influencing PM2.5 concentrations. Back trajectories show that regional transport from the northeast and southeast of Zhengzhou (such as Puyang, Kaifeng, Zhoukou, and Xuchang in Henan province) also made a big contribution to the PM2.5 pollution in Zhengzhou. Our results demonstrated that the spatial-temporal distributions of PM2.5 in Zhengzhou were determined by complex factors such as primary emissions, secondary production, meteorological conditions and local/regional-transport." @default.
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- W2615360907 date "2017-01-01" @default.
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- W2615360907 title "A Study of Characteristics and Origins of Haze Pollution in Zhengzhou, China, Based on Observations and Hybrid Receptor Models" @default.
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- W2615360907 doi "https://doi.org/10.4209/aaqr.2016.06.0238" @default.
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