Diurnal, seasonal, and spatial variation of PM 2.5 in Beijing

Li, Runkui; Li, Zhipeng; Gao, Wenju; Ding, Wenjun; Xu, Qun; Song, Xianfeng

doi:10.1007/s11434-014-0607-9

Cited by 83 publications

(33 citation statements)

References 34 publications

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“…PM 2.5/10 concentrations were significantly different among the four seasons in this study, and this finding was consistent with that in published papers on PM pollution in northern China [51,52]. Annual and seasonal average concentrations of PM had been used to investigate the effects of landscape pattern in another study [40], but the differences among seasons were quite significant.…”

Section: Scale-dependent Effects Of Greenspace Pattern On Pm Pollutionsupporting

confidence: 91%

Effects of Urban Greenspace Patterns on Particulate Matter Pollution in Metropolitan Zhengzhou in Henan, China

Lei

Duan

et al. 2018

Atmosphere

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This case study was conducted to quantify the effects of urban greenspace patterns on particle matter (PM) concentration in Zhengzhou, China by using redundancy and variation partitioning analysis. Nine air-quality monitoring stations (AQMS) were selected as the central points. Six distances of 1 km, 2 km, 3 km, 4 km, 5 km, and 6 km were selected as the side lengths of the squares with each AQMS serving as the central point, respectively. We found:(1) the fine size of PM (PM 2.5 ) and coarse size of PM (PM 10 ) among four seasons showed significant differences; during winter, the concentration of PM 2.5 and PM 10 were both highest, and PM 2.5 and PM 10 concentration in summer were lowest. (2) To effectively reduce the PM 2.5 pollution, the percentage of greenspace, the differences in areas among greenspace patches, and the edge complexity of greenspace patches should be increased at distances of 2 km and 3 km. To effectively reduce PM 10 , the percentage of greenspace at a distance of 4 km, the edge density at distances of 2 km and 4 km, and the average area of greenspace patches at a distance of 1 km should be increased. (3) Greenspace pattern significantly affected PM 2.5 at a distance of 3 km, and PM 10 at a distance of 4 km. From shorter distance to longer distance, the proportion of variance explained by greenspace showed a decline-increase-decline-increase trend for PM 2.5 , and a decline-increase-decline trend for PM 10 . At shorter distances, the composition of greenspace was more effective in reducing the PM pollution, and the configuration of greenspace played a more important role at longer distances. The results should lead to specific guidelines for more cost-effective and environmentally sound greenspace planning.

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Section: Scale-dependent Effects Of Greenspace Pattern On Pm Pollutionsupporting

confidence: 91%

Effects of Urban Greenspace Patterns on Particulate Matter Pollution in Metropolitan Zhengzhou in Henan, China

Lei

Duan

et al. 2018

Atmosphere

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“…PM 2.5 concentrations monitored by air quality stations were used to distinguish between unpolluted days, moderately polluted days, and heavily polluted days. As reported in previous studies, the 35 stations in Beijing are unevenly distributed across the city, and record different pollution patterns [14]; therefore, it is inadvisable to simply average the pollutants' concentrations recorded by all 35 stations, as distinct differences occur between northern and southern stations (the latter commonly have much higher pollutant concentrations than the former) [32]. Consequently, the air quality station closest to each AERONET station was selected as a reference with which to determine the air quality situation of data recorded by the AERONET stations.…”

Section: Data Selection and Analytical Methodsmentioning

confidence: 92%

“…According to China's national ambient air quality standard release in 2012 (NAAQS-2012) [42,43], daily mean PM2.5 concentrations less than 75 µg/m 3 are classed as qualified (unpolluted); concentrations between 75 µg/m 3 and 150 µg/m 3 are classed as moderatedly polluted, while concentrations greater than 150 µg/m 3 are classed as heavily polluted [13,32]. In order to guarantee that real-time monitoring data are representative, at least 20 h of observation data are required for calculation of the daily average, considering that some data may be missing on any given day.…”

Section: Aerosol Radiative Forcing On Heavily Polluted Days Moderatementioning

confidence: 99%

Analysis of Aerosol Radiative Forcing over Beijing under Different Air Quality Conditions Using Ground-Based Sun-Photometers between 2013 and 2015

et al. 2016

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Aerosol particles can strongly affect both air quality and the radiation budget of the atmosphere. Above Beijing, the capital city of China, large amounts of aerosols within the atmospheric column have caused the deterioration of local air quality and have influenced radiative forcings at both the top and the bottom of the atmosphere (BOA and TOA). Observations of aerosol radiative forcing and its efficiency have been made using two sun-photometers in urban Beijing between 2013 and 2015, and have been analyzed alongside two air quality monitoring stations' data by dividing air quality conditions into unpolluted, moderately polluted, and heavily polluted days. Daily average PM 2.5 concentrations varied greatly in urban Beijing (5.5-485.0 µg/m 3 ) and more than one-third of the analyzed period is classified as being polluted according to the national ambient air quality standards of China. The heavily polluted days had the largest bottom of atmosphere (BOA) and top of atmosphere (TOA) radiative forcings, but the smallest radiative forcing efficiencies, while the unpolluted days showed the opposite characteristics. On heavily polluted days, the averaged BOA aerosol radiative forcing occasionally exceeded´150 W/m 2 , which represents a value about three-times greater than that for unpolluted days. BOA aerosol radiative forcing was around two-to-three times as large as TOA aerosol radiative forcing under various air quality conditions, although both were mostly negative, suggesting that aerosols had different magnitudes of cooling effects at both the surface and the top of the atmosphere. Unpolluted days had the largest average values of aerosol radiative forcing efficiencies at BOA (and TOA) levels, which exceeded 190 W/m 2 (´70 W/m 2 ), compared with the lowest average values in heavily polluted days of around´120 W/m 2 (´55 W/m 2 ). These results suggest that the high concentrations of particulate matter pollution in the urban Beijing area had a strong cooling effect at both BOA and TOA levels.

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“…The use of API has stopped and new national ambient air quality standards that take into account PM 2.5 , PM 10 , O 3 , SO 2 and NO 2 have been released to replace API. Aerosol pollution (PM 2.5 and PM 10 ) is the major reason for the deterioration of the air quality in Beijing, especially during winter [36]. With the API publicized by the Ministry of Environmental Protection of People's Republic of China, the annual API declined from around 110 to 80 by the end of 2012 (the lower the API, the better the air quality) as shown in Figure 12.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Aerosol Properties in Beijing Based on Ground-Based Sun Photometer and Air Quality Monitoring Observations from 2005 to 2014

et al. 2016

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Aerosol particles are the major contributor to the deterioration of air quality in China's capital, Beijing. Using ground-based sun photometer observations from 2005 to 2014, the long-term variations in optical properties and microphysical properties of aerosol in and around Beijing were investigated in this study. The results indicated little inter-annual variations in aerosol optic depth (AOD) but an increase in the fine mode AODs both in and outside Beijing. Furthermore, the single scattering albedo in urban Beijing is larger, while observations at the site that is southeast of Beijing suggested that the aerosol there has become more absorbing. The intra-annual aspects were as follow: The largest AOD and high amount of fine mode aerosols are observed in the summer. However, the result of air pollution index (API) that mainly affected by the dry density of near-surface aerosol indicated that the air quality has been improving since 2006. Winter and spring were the most polluted seasons considering only the API values. The inconsistency between AOD and API suggested that fine aerosol particles may have a more important role in the deterioration of air quality and that neglecting particulate matter with aerodynamic diameter less than 2.5 µm (PM 2.5 ) in the calculation of API might not be appropriate in air quality evaluation. Through analysis of the aerosol properties in high API days, the results suggested that the fine mode aerosol, especially PM 2.5 has become a major contributor to the aerosol pollution in Beijing.

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Diurnal, seasonal, and spatial variation of PM 2.5 in Beijing

Cited by 83 publications

References 34 publications

Effects of Urban Greenspace Patterns on Particulate Matter Pollution in Metropolitan Zhengzhou in Henan, China

Effects of Urban Greenspace Patterns on Particulate Matter Pollution in Metropolitan Zhengzhou in Henan, China

Analysis of Aerosol Radiative Forcing over Beijing under Different Air Quality Conditions Using Ground-Based Sun-Photometers between 2013 and 2015

Analysis of Aerosol Properties in Beijing Based on Ground-Based Sun Photometer and Air Quality Monitoring Observations from 2005 to 2014

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