Quantifying the Air Pollutants Emission Reduction during the 2008 Olympic Games in Beijing

Wang, Yafei; Zhao, Meng; Xing, Jia; Wu, Ye; Zhou, Yu; Lei, Yu; He, Kebin; Fu, Lixin; Hao, Jiming

doi:10.1021/es9028167

Cited by 343 publications

(178 citation statements)

References 32 publications

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“…It was noteworthy that, during the month of August in 2008, R value suddenly drops to much lower than what is expected during this time of year. This was likely due to the 2008 Beijing Olympics Games, during which several traffic and emission restrictions were strictly enforced from the period of April 2007 to January 2009, as has also been confirmed by Wang et al [49].…”

Section: Airrgb Trend Of Citiessupporting

confidence: 57%

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

2017

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Urban air pollution is one of the most widespread global sustainability problems. Previous research has studied growth or fall of particulate matter (PM) levels using on-ground monitoring stations in urban regions. However, studying this worldwide is difficult because most cities do not have sufficient infrastructure to monitor air quality. Thus, satellite data is increasingly being employed to solve this limitation. In this paper, we use 16 years (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) of aerosol optical depth (AOD) and Angstrom exponent (α) datasets, retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) sensors on the National Aeronautics and Space Administration's (NASA) Terra satellite to study air quality over 60 locations globally. We propose a novel technique, called AirRGB decomposition, to characterize urban air quality by decomposing AOD and α retrievals into 'components' of three distinct scenarios. In the AirRGB decomposition method, using AOD and α dataset three scenarios were investigated: 'R'-high α and high AOD, 'G'-high α and low AOD, and 'B'-low α and low AOD values. These scenarios were mapped and quantified over a triangular red, green and blue color scale. This visualization easily segregates regions having a high concentration of industrial aerosol from only natural aerosols. Our analysis indicates that a sharp divide exists between North American and European cities and Asian cities in terms of baseline pollution and slopes of R and G trends. We found that while pollution in cities in China has started to decrease (e.g., since 2011 for Beijing), it continues to increase in South Asia and Southeast Asia. e.g., R offset of Beijing and New Delhi was 54.98 and 50.43 respectively but R slope was −0.04 and 0.08 respectively. High offset (≥45) and slope (≥0.025) of B for New York, Tokyo, Sydney and Sao Paolo shows that they have clean air, which is still getting better.

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Section: Airrgb Trend Of Citiessupporting

confidence: 57%

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

2017

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“…As a result, the traffic volume and vehicular exhaust decreased significantly (Wang et al, 2010a;Zhou et al, 2010). For example, during the Olympic Games the traffic volume and average PM 2.5 concentration near a major road -about 1.2 km away from the TH site -reduced by 21 % and 46.3 % compared to those in June, respectively (Kong et al, 2010).…”

Section: Seasonal Patterns Of Carbonaceous Speciesmentioning

confidence: 99%

“…This led to additional measures to reduce emissions in targeted sectors in neighboring provinces of Tianjin, Hebei, Shanxi, Shandong, and Inner Mongolia, in order to assure good air quality for the Beijing Olympic Games. Consequently, surface and satellite measurements showed that the measures taken in Beijing and surrounding regions during the Olympic Summer Games likely had a noticeable effect on emission reduction and air quality improvement (Cermak and Knutti 2009;UNEP, 2009;Wang et al, 2010a, b). The emission control and large reduction in Beijing represents a human-perturbation experiment of unprecedented scale, and provides a rare opportunity to study the impact of pollution emissions on the air quality and atmospheric chemistry (Wang et al, 2010b).…”

Section: Introductionmentioning

confidence: 99%

Carbonaceous species in PM<sub>2.5</sub> at a pair of rural/urban sites in Beijing, 2005–2008

et al. 2011

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Abstract. One-week integrated PM 2.5 samples were collected over four years (2005)(2006)(2007)(2008) at a pair of sites, one rural and one urban site, in the area of Beijing, China. Weekly organic and elemental carbon (OC and EC) concentrations from these samples were measured to investigate their atmospheric concentrations, temporal variation patterns and the factors influencing these aspects. A slightly systematic decrease in annual mean concentration of OC and an opposite trend for EC at both sites was observed. Since OC accounted for about 70 % of total carbon (TC, i.e. OC + EC) the total carbonaceous mass experienced a slight decline on a yearly basis over the study period. Its fraction of PM 2.5 mass at the urban site in 2008 was significantly lower than observed 10 years earlier (1999), indicating that the relative importance of carbonaceous species in PM 2.5 has decreased. In urban Beijing clear seasonal variations (by factors of 1.35 ∼ 3.0) were shown in both OC and EC with higher weekly concentrations and fluctuations in winter and much lower values in summer and spring. The minimum seasonal urban excesses of OC (3.0 µg m −3 ) and EC (1.3 µg m −3 ) occurred in the summer of 2008, which were only one-ninth and one-seventh of their corresponding maximum values, respectively. This reduction in the urban-difference, coupled with more positive stable carbon isotope values of EC at the urban site in that summer relative to the preceding summers, supports that the special clean air campaign for the 2008 Summer Olympic Games very likely had noticeable impact on the ambient concentrations of carbonaceous aerosols in the Beijing area, particularly on the local urban scale. Less consistent seasonal patterns in OC and EC, their scattered correlation, andCorrespondence to: K. He (hekb@tsinghua.edu.cn) higher mass ratios of OC to EC (OC/EC) at the rural site indicate more complex and variable major sources regarding aerosol formation in the rural area. These emission sources include biomass burning during the harvest seasons, widely used high-polluting family stoves and small boilers for cooking and heating with high OC/EC ratios, and a greater relative quantity of secondary organic aerosols.

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“…Other factors that were not discussed in this paper may also contribute to overall air quality, including meteorological conditions (Barman et al, 2008;Cermak and Knutti, 2009;Wang et al, 2009;Ren et al, 2011), topographical influences, emission sources (Wang et al, 2010), transport from the stratosphere and long-range transport (Zhao et al, 2010a). Further examination of all these variables could improve ability to predict variance in air quality.…”

Section: Tablementioning

confidence: 96%

Quantifying the impacts of socio-economic factors on air quality in Chinese cities from 2000 to 2009

Zhao

Chen

Wang

et al. 2012

Environmental Pollution

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a b s t r a c tSocio-economic factors have significant influences on air quality and are commonly used to guide environmental planning and management. Based on data from 85 long-term daily monitoring cities in China, air quality as evaluated by AOFDAQ-A (Annual Occurrence Frequency of Daily Air Quality above Level III), was correlated to socio-economic variable groups of urbanization, pollution and environmental treatment by variation partitioning and hierarchical partitioning methods. We found: (1) the three groups explained 43.5% of the variance in AOFDAQ-A; (2) the contribution of "environmental investment" to AOFDAQ-A shown a time lag effect; (3) "population in mining sector" and "coverage of green space in built-up area" were respectively the most significant negative and positive explanatory socioeconomic variables; (4) using eight largest contributing individual factors, a linear model to predict variance in AOFDAQ-A was constructed. Results from our study provide a valuable reference for the management and control of air quality in Chinese cities.

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Quantifying the Air Pollutants Emission Reduction during the 2008 Olympic Games in Beijing

Cited by 343 publications

References 32 publications

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

Carbonaceous species in PM<sub>2.5</sub> at a pair of rural/urban sites in Beijing, 2005–2008

Quantifying the impacts of socio-economic factors on air quality in Chinese cities from 2000 to 2009

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Quantifying the Air Pollutants Emission Reduction during the 2008 Olympic Games in Beijing

Cited by 343 publications

References 32 publications

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

Carbonaceous species in PM&lt;sub&gt;2.5&lt;/sub&gt; at a pair of rural/urban sites in Beijing, 2005–2008

Quantifying the impacts of socio-economic factors on air quality in Chinese cities from 2000 to 2009

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Carbonaceous species in PM<sub>2.5</sub> at a pair of rural/urban sites in Beijing, 2005–2008