Abstract

Abstract. In this paper, we present ship-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of tropospheric trace gases' distribution along the Yangtze River during winter 2015. The measurements were performed along the Yangtze River between Shanghai and Wuhan, covering major industrial areas in eastern China. Tropospheric vertical column densities (VCDs) of nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) were retrieved using the air mass factor calculated by the radiative transfer model. Enhanced tropospheric NO2 and SO2 VCDs were detected over downwind areas of industrial zones over the Yangtze River. In addition, spatial distributions of atmospheric pollutants are strongly affected by meteorological conditions; i.e., positive correlations were found between concentration of pollutants and wind speed over these areas, indicating strong influence of transportation of pollutants from high-emission upwind areas along the Yangtze River. Comparison of tropospheric NO2 VCDs between ship-based MAX-DOAS and Ozone Monitoring Instrument (OMI) satellite observations shows good agreement with each other, with a Pearson correlation coefficient (R) of 0.82. In this study, the NO2 ∕ SO2 ratio was used to estimate the relative contributions of industrial sources and vehicle emissions to ambient NO2 levels. Analysis results of the NO2 ∕ SO2 ratio show a higher contribution of industrial NO2 emissions in Jiangsu Province, while NO2 levels in Jiangxi and Hubei provinces are mainly related to vehicle emissions. These results indicate that different pollution control strategies should be applied in different provinces. In addition, multiple linear regression analysis of ambient carbon monoxide (CO) and odd oxygen (Ox) indicated that the primary emission and secondary formation of HCHO contribute 54.4 ± 3.7 % and 39.3 ± 4.3 % to the ambient HCHO, respectively. The largest contribution from primary emissions in winter suggested that photochemically induced secondary formation of HCHO is reduced due to lower solar irradiance in winter. Our findings provide an improved understanding of major pollution sources along the eastern part of the Yangtze River which are useful for designing specific air pollution control policies.

Highlights

  • Nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) are important atmospheric constituents playing important roles in tropospheric chemistry

  • The higher the wind speed, the higher the NO2 and SO2 vertical column densities (VCDs) under northwesterly wind conditions (Fig. 6b and c), which means that the transport from distant sources is more significant than the contribution from local emission sources. These results suggested that the spatial distributions of pollutants along the Yangtze River are strongly influenced by the meteorological conditions

  • We present the ship-based MAX-differential optical absorption spectroscopy (DOAS) measurements along the Yangtze River from Shanghai to Wuhan (22 November to 4 December 2015)

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Summary

Introduction

Nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) are important atmospheric constituents playing important roles in tropospheric chemistry. Nitrogen oxides (NOx), defined as the sum of nitric oxide (NO) and NO2, are one of the major pollutants in the troposphere, playing a key role in both tropospheric and stratospheric. Q. Hong et al.: Ship-based MAX-DOAS measurements chemistry. Hong et al.: Ship-based MAX-DOAS measurements chemistry It takes part in the catalytic formation of tropospheric ozone (O3), while being a catalyst for the destruction of stratospheric O3 (Crutzen, 1970). Major sources of NOx are high-temperature combustions (e.g., fossil fuel burning and biomass burning) and natural processes (e.g., soil microbial activity and lightning events; Lee et al, 1997). Atmospheric SO2 causes similar environmental problems to NO2, such as acidification of the natural aqua system and formation of secondary aerosols, and causes negative impacts on human health (Chiang et al, 2016).

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