Major chemical compositions, possible sources, and mass closure analysis of PM2.5 in Jinan, China

Gu, Jie; Shu-shan, DU; Dao-wen, Han; Hou, Lijun; Yi, Jing; Xu, Ja; Liu, Guanghui; Han, Bin; Yang, Guangwu; Zhang, Bai

doi:10.1007/s11869-013-0232-9

Cited by 72 publications

(37 citation statements)

References 54 publications

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“…However, compared with other sources, the relative contribution of crop residue burning to the variation of local and regional PM 2.5 concentrations remained unclear. Previous studies [1][2][3][4] have quantified the contribution of different sources to PM 2.5 concentrations in different cities and some major sources (e.g., traffic and coal burning) have been widely acknowledged. For this study, we found that although the PM 2.5 concentrations measured at stations close to crop residue burning spots were notably higher than those stations not close to crop residue burning spots, the correlations between the existence of crop residue burning spots and local PM 2.5 concentrations were not significant.…”

Section: Source Apportionment Methods Should Be Employed To Quantifymentioning

confidence: 99%

“…2017, 9, 971 2 of 14 sources to local PM 2.5 concentrations. Hence, many studies [1][2][3][4] have been conducted to analyze sources of PM 2.5 concentrations in different cities and have shown that emission sources such as traffic, coal burning, biomass burning, cooking, dust related emissions, industrial pollution, and secondary inorganic aerosol all contributed significantly to variations of PM 2.5 concentrations. In addition to these sources, the contribution of crop residue-materials left over from the production of crops-burning to local and regional haze episodes has been widely discussed recently.…”

Section: Introductionmentioning

confidence: 99%

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Examining the Influence of Crop Residue Burning on Local PM2.5 Concentrations in Heilongjiang Province Using Ground Observation and Remote Sensing Data

Chen

Zhuang

et al. 2017

Remote Sensing

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Abstract:Although a many studies concerning crop residue burning have been conducted, the influence of crop residue burning on local PM 2.5 concentrations remains unclear. The number of crop residue burning spots was the highest in Heilongjiang province and we extracted crop residue burning spots for this region using MOD14A1 (Thermal Anomalies & Fire Daily L3 Global 1 km) data and national land cover data. By analyzing the temporal variation of crop residue burning and PM 2.5 concentrations in Heilongjiang province, we found that the total number of crop residue burning spots was not correlated with the variations of PM 2.5 concentrations at a provincial (regional) scale. However, crop residue burning exerted notable influence on the variations of PM 2.5 concentrations at a local scale. We experimented with a set of buffer zone radiuses to examine the influencing area of crop residue burning. The results suggest that the valid influencing area of crop residue burning was between 50 and 80 km. The mean PM 2.5 concentration measured at stations close to crop residue burning spots was more than 60 µg/m 3 higher than that measured at stations not close to crop residue burning spots. However, no consistent, significant correlation existed between the existence of crop residue burning spots and local PM 2.5 concentrations, indicating that local PM 2.5 concentrations were influenced by a diversity of factors and not solely controlled by crop residue burning. This research also provides suggestions for better understanding the role of crop residue burning in local and regional air pollution.

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Section: Source Apportionment Methods Should Be Employed To Quantifymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Examining the Influence of Crop Residue Burning on Local PM2.5 Concentrations in Heilongjiang Province Using Ground Observation and Remote Sensing Data

Chen

Zhuang

et al. 2017

Remote Sensing

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“…Thus, the air masses backward trajectories were short, indicating air masses move slowly and pollutants were able to accumulate. Many studies indicated that the Beijing -Tianjin region and Shandong Province are a severely polluted region (Yang et al, 2011;Gu et al, 2014;Wang et al, 2015b;Zikova et al, 2016). Both cluster 2 and cluster 3 showed air masses moving from the northern Russia.…”

Section: Influence Of Air Masses Transport and Potential Source Contrmentioning

confidence: 99%

Chemical Characteristics of PM2.5 during a 2016 Winter Haze Episode in Shijiazhuang, China

Chen

Zhang

Zhu

et al. 2017

Aerosol Air Qual. Res.

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To better understand the chemical characteristics and the potential source regions of PM 2.5 measured from 18 January until 22 January 2016 in Shijiazhuang, China, PM 2.5 was measured continuously and integrated daily sampling using midvolume samplers was conducted at the three sites. The mean concentration of PM 2.5 at the three sites reached 113, 131 and 119 µg m -3 during the sampling period, the higher concentrations occurred at early morning and noon, similar variation trends were found in the three sites. The concentrations of OC were higher than EC at three sampling sites and the OC/EC ratios ranged from 9.09 to 12.4 with a daily mean value of 10.8 during a haze pollution episode (HPE), which suggested that carbonaceous compositions might be from same source. The total concentration of water soluble inorganic ions (WSII) at the sites ranged from 72.2 to 100.0 µg m -3 with a mean of 84.3 µg m -3. The dominant species were NO 3 -, SO 4 2-, NH 4 + , Cl -, accounting for 88.4% of the mean PM 2.5 WSII mass. The most abundant measured element was Na with average mass concentrations of 41.5, 37.0, and 38.1 µg m -3 during the HPE. Relative humidity during HPE was higher than during clean days with average values of 70.1% and 60.2%, suggesting that high relative humidity and low wind speed favored formation of secondary inorganic ions and accelerated hygroscopic growth. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) and a potential source contribution function (PSCF) analysis were used to assess the data. Back-trajectories for the three sites identified similar transport pathways. PSCF analysis showed a significant regional impact on PM 2.5 at Shijiazhuang during the polluted period. The potential source areas for PM 2.5 in Shijiazhuang were the Beijing-Tianjin region and Shandong Province. The results of the present study show the need for the development of PM 2.5 control measurements on a regional scale.

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“…Recent studies have suggested that airborne pollutants, PM 2.5 in particular, are closely related to cardiovascular disease-related mortality (Garrett and Casimiro, 2011;Li et al, 2015a;Lanzinger et al, 2015), emergency room visits and all-year non-accidental mortality (Pasca et al, 2014). Due to its strong negative influences on public health, scholars have been working towards a better understanding of sources (Guo et al, 2012;Zhang et al, 2013Zhang et al, , 2016Gu et al, 2014;Cao et al, 2014), characteristics (Wei et al, 2012;Zhang et al, 2013;Hu et al, 2015;F. Zhang et al, 2015;Zhen et al, 2016) and seasonal variations (Cao et al, 2012;Shen et al, 2014;Yang and Christakos, 2015;Chen et al, 2015; of PM 2.5 .…”

Section: Introductionmentioning

confidence: 99%

Understanding meteorological influences on PM<sub>2.5</sub> concentrations across China: a temporal and spatial perspective

et al. 2018

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Abstract. With frequent air pollution episodes in China, growing research emphasis has been put on quantifying meteorological influences on PM 2.5 concentrations. However, these studies mainly focus on isolated cities, whilst meteorological influences on PM 2.5 concentrations at the national scale have not yet been examined comprehensively. This research employs the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM 2.5 concentrations in 188 monitoring cities across China. Results indicate that meteorological influences on PM 2.5 concentrations have notable seasonal and regional variations. For the heavily polluted North China region, when PM 2.5 concentrations are high, meteorological influences on PM 2.5 concentrations are strong. The dominant meteorological influence for PM 2.5 concentrations varies across locations and demonstrates regional similarities. For the most polluted winter, the dominant meteorological driver for local PM 2.5 concentrations is mainly the wind within the North China region, whilst precipitation is the dominant meteorological influence for most coastal regions. At the national scale, the influence of temperature, humidity and wind on PM 2.5 concentrations is much larger than that of other meteorological factors. Amongst eight factors, temperature exerts the strongest and most stable influence on national PM 2.5 concentrations in all seasons. Due to notable temporal and spatial differences in meteorological influences on local PM 2.5 concentrations, this research suggests pertinent environmental projects for air quality improvement should be designed accordingly for specific regions.

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Major chemical compositions, possible sources, and mass closure analysis of PM2.5 in Jinan, China

Cited by 72 publications

References 54 publications

Examining the Influence of Crop Residue Burning on Local PM2.5 Concentrations in Heilongjiang Province Using Ground Observation and Remote Sensing Data

Examining the Influence of Crop Residue Burning on Local PM2.5 Concentrations in Heilongjiang Province Using Ground Observation and Remote Sensing Data

Chemical Characteristics of PM2.5 during a 2016 Winter Haze Episode in Shijiazhuang, China

Understanding meteorological influences on PM<sub>2.5</sub> concentrations across China: a temporal and spatial perspective

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Major chemical compositions, possible sources, and mass closure analysis of PM2.5 in Jinan, China

Cited by 72 publications

References 54 publications

Examining the Influence of Crop Residue Burning on Local PM2.5 Concentrations in Heilongjiang Province Using Ground Observation and Remote Sensing Data

Examining the Influence of Crop Residue Burning on Local PM2.5 Concentrations in Heilongjiang Province Using Ground Observation and Remote Sensing Data

Chemical Characteristics of PM2.5 during a 2016 Winter Haze Episode in Shijiazhuang, China

Understanding meteorological influences on PM&lt;sub&gt;2.5&lt;/sub&gt; concentrations across China: a temporal and spatial perspective

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Understanding meteorological influences on PM<sub>2.5</sub> concentrations across China: a temporal and spatial perspective