Satellite remote sensing of changes in NO x emissions over China during 1996–2010

Qiang, Zhang; Geng, Guannan; Wang, Siwen; Richter, Andreas; He, Kebin

doi:10.1007/s11434-012-5015-4

Cited by 130 publications

(101 citation statements)

References 22 publications

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“…In JJA, the gas-phase formation of sulfate increased to 0.039 Tg S season −1 with a relative contribution of 57 %, making it the only process that determined the IAV of sulfate concentration over NC in this season. Since gas-phase oxidation of SO 2 is sensitive to temperature and humidity (Yao et al, 2002;Zhang et al, 2012), we conclude that the variations in temperature and specific humidity were the key factors that drove the IAV of sulfate over NC. The relatively high MAD values of temperature in NC in both DJF and JJA (Fig.…”

Section: Sulfatementioning

confidence: 85%

Simulation of the interannual variations of aerosols in China: role of variations in meteorological parameters

Liao

2014

Atmos. Chem. Phys.

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Abstract. We used the nested grid version of the global three-dimensional Goddard Earth Observing System chemical transport model (GEOS-Chem) to examine the interannual variations (IAVs) of aerosols over heavily polluted regions in China for years [2004][2005][2006][2007][2008][2009][2010][2011][2012]. The role of variations in meteorological parameters was quantified by a simulation with fixed anthropogenic emissions at year 2006 levels and changes in meteorological parameters over (particles with a diameter of 2.5 µm or less) aerosol concentrations exhibited large IAVs in North China (NC; 32-42 • N, 110-120 • E), with regionally averaged absolute percent departure from the mean (APDM) values of 17, 14, 14, and 11 % in December-JanuaryFebruary (DJF), March-April-May (MAM), June-JulyAugust (JJA), and September-October-November (SON), respectively. Over South China (SC; 22-32 • N, 110-120 • E), the IAVs in PM 2.5 were found to be the largest in JJA, with the regional mean APDM values of 14 % in JJA and of about 9 % in other seasons. The concentrations of PM 2.5 over the Sichuan Basin (SCB; 27-33 • N, 102-110 • E) were simulated to have the smallest IAVs among the polluted regions examined in this work, with APDM values of 8-9 % in all seasons. All aerosol species (sulfate, nitrate, ammonium, black carbon, and organic carbon) were simulated to have the largest IAVs over NC in DJF, corresponding to the large variations in meteorological parameters over NC in this season. Process analyses were performed to identify the key meteorological parameters that determined the IAVs of different aerosol species in different regions. While the variations in temperature and specific humidity, which influenced the gasphase formation of sulfate, jointly determined the IAVs of sulfate over NC in both DJF and JJA, wind (or convergence of wind) in DJF and precipitation in JJA were the dominant meteorological factors to influence IAVs of sulfate over SC and the SCB. The IAVs in temperature and specific humidity influenced gas-to-aerosol partitioning, which were the major factors that led to the IAVs of nitrate aerosol in China. The IAVs in wind and precipitation were found to drive the IAVs of organic carbon aerosol. We also compared the IAVs of aerosols simulated with variations in meteorological parameters alone with those simulated with variations in anthropogenic emissions alone; the variations in meteorological fields were found to dominate the IAVs of aerosols in northern and southern China over 2004-2012. Considering that the IAVs in meteorological fields are mainly associated with natural variability in the climate system, the IAVs in aerosol concentrations driven by meteorological parameters have important implications for the effectiveness of shortterm air quality control strategies in China.

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Section: Sulfatementioning

confidence: 85%

Simulation of the interannual variations of aerosols in China: role of variations in meteorological parameters

Liao

2014

Atmos. Chem. Phys.

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“…Pollutants emitted from vehicles -such as NO x , volatile organic compounds (VOCs), black carbon (BC) and other traffic-related particulate matter (PM) -have increased over the last decades Zhang et al, 2012). Apart from the primary PM, the oxidation of traffic-related gaseous pollutants such as NO x , VOCs, semi-volatile VOCs (SVOCs) and lowvolatility VOCs (LVOCs) leads to the formation of particu-late nitrate and secondary organic aerosols (SOA), exacerbating PM pollution.…”

Section: Introductionmentioning

confidence: 99%

Impacts of traffic emissions on atmospheric particulate nitrate and organics at a downwind site on the periphery of Guangzhou, China

Qin

Tan

et al. 2017

Atmos. Chem. Phys.

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Abstract. Particulate matter (PM) pollution on the peripheries of Chinese megacities can be as serious as in cities themselves. Given the substantial vehicular emissions in inner-city areas, the direct transport of primary PM (e.g., black carbon and primary organics) and effective formation of secondary PM from precursors (e.g., NO x and volatile organic compounds) can contribute to PM pollution in "buffer" zones between cities. To investigate how traffic emissions in inner-city areas impact these adjacent buffer zones, a suite of real-time instruments were deployed in Panyu, downwind from central Guangzhou, from November to December 2014. Nitrate mass fraction was higher on high-PM days, with the average nitrate-to-sulfate ratio increasing from around 0.35 to 1.5 as the PM mass concentration increased from 10 to 160 µg m −3 . Particulate nitrate was strongly correlated with excess ammonium (([NHwith higher concentrations in December than in November due to lower temperatures. The organic mass fraction was the highest across all PM 1 levels throughout the campaign. While organic aerosols (OA) were dominated by secondary organic aerosols (SOA = semi-volatile oxygenated organic aerosols + low-volatility oxygenated organic aerosols) as a campaign average, freshly emitted hydrocarbon-like organic aerosols (HOA) contributed up to 40 % of OA during high-OA periods, which typically occurred at nighttime and contributed 23.8 to 28.4 % on average. This was due to daytime traffic restrictions on heavy-duty vehicles in Guangzhou, and HOA almost increased linearly with total OA concentration. SOA increased as odd oxygen (O x = O 3 + NO 2 ) increased during the day due to photochemistry. A combination of nighttime traffic emissions and daytime photochemistry contributed to the buildup of PM in Panyu. The mitigation of PM pollution in inner-city areas by reducing vehicular traffic can potentially improve air quality in peripheral areas.

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“…China has witnessed worsening air quality during the past two decades, due to the rapid urbanization, economic growth, industrial development, and increasing amount of vehicles [20]. Although municipal government adopted a series of measures including reduction and control of factory pollution, the air quality is still serious in some cities [21].…”

mentioning

confidence: 99%

Effects of ambient air pollution on allergic rhinitis among preschool children in Changsha, China

Deng

et al. 2013

Chin. Sci. Bull.

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Satellite remote sensing of changes in NO x emissions over China during 1996–2010

Cited by 130 publications

References 22 publications

Simulation of the interannual variations of aerosols in China: role of variations in meteorological parameters

Simulation of the interannual variations of aerosols in China: role of variations in meteorological parameters

Impacts of traffic emissions on atmospheric particulate nitrate and organics at a downwind site on the periphery of Guangzhou, China

Effects of ambient air pollution on allergic rhinitis among preschool children in Changsha, China

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