Effects of Chemical Composition of PM2.5 on Visibility in a Semi-Rural City of Sichuan Basin

Li, Yun‐Chun; Shu, Man; Ho, Steven Sai Hang; Yu, Jianzhen; Yuan, Zibing; Liu, Zi-Fang; Wang, Xianxiang; Zhao, Xueyan

doi:10.4209/aaqr.2017.08.0264

Cited by 22 publications

(7 citation statements)

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“…Urban greening can mitigate the declining trends, but the effects are not significant. Our findings were similar to those of previous studies [53][54][55], but different conclusions have been drawn.…”

Section: Factors Affecting Atmospheric Visibilitysupporting

confidence: 84%

Long-Term Atmospheric Visibility Trends and Characteristics of 31 Provincial Capital Cities in China during 1957–2016

Chen

Zhu

et al. 2018

Atmosphere

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Millions of pulmonary diseases, respiratory diseases, and premature deaths are caused by poor ambient air quality in developing countries, especially in China. A proven indicator of ambient air quality, atmospheric visibility (AV), has displayed continuous decline in China’s urban areas. A better understanding of the characteristics and the factors affecting AV can help the public and policy makers manage their life and work. In this study, long-term AV trends (from 1957–2016, excluding 1965–1972) and spatial characteristics of 31 provincial capital cities (PCCs) of China (excluding Taipei, Hong Kong, and Macau) were investigated. Seasonal and annual mean values of AV, percentage of ‘good’ (≥20 km) and ‘bad’ AV (<10 km), cumulative percentiles and the correlation between AV, socioeconomic factors, air pollutants and meteorological factors were analyzed in this study. Results showed that annual mean AV of the 31 PCCs in China were 14.30 km, with a declining rate of −1.07 km/decade. The AV of the 31 PCCs declined dramatically between 1973–1986, then plateaued between 1987–2006, and rebounded slightly after 2007. Correlation analysis showed that impact factors (e.g., urban size, industrial activities, residents’ activities, urban greening, air quality, and meteorological factors) contributed to the variation of AV. We also reveal that residents’ activities are the primary direct socioeconomic factors on AV. This study hopes to help the public fully understand the characteristics of AV and make recommendations about improving the air environment in China’s urban areas.

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Section: Factors Affecting Atmospheric Visibilitysupporting

confidence: 84%

Long-Term Atmospheric Visibility Trends and Characteristics of 31 Provincial Capital Cities in China during 1957–2016

Chen

Zhu

et al. 2018

Atmosphere

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“…In the frame of the present study, the carbonaceous matter (organic carbon (OC) and elementary carbon (EC)) was analyzed using a thermo-optical method on a Sunset Lab analyzer (Birch and Cary, 1996) as described by Aymoz et al (2007), using the EUSAAR2 temperature program (Cavalli et al, 2010), except for the five sites of Northern France where the NIOSH870 protocol was employed (Birch and Cary, 1996). Particulate organic matter (OM) contents were then estimated by multiplying the organic carbon mass concentrations by a fixed factor, with = 1.8 × (Li et al, 2018;Ruthenburg et al, 2014;Vlachou et al, 2018a).…”

Section: Chemical Analysesmentioning

confidence: 99%

Polyols and glucose particulate species as tracers of primary biogenic organic aerosols at 28 french sites

Samaké¹,

Jaffrezo²,

Favez³

et al. 2018

Preprint

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Abstract. A growing number of studies are using specific primary sugar species, such as sugar alcohols or primary saccharides, as marker compounds to characterize and apportion primary biogenic organic aerosols (PBOA) in the atmosphere. To better understand their annual cycles, as well as their spatio-temporal abundance in terms of concentrations and sources, we conducted a large study focusing on three major atmospheric primary sugar compounds (i.e. arabitol, mannitol and glucose) measured in various environmental conditions on about 5,300 filter samples collected at 28 sites in France. Our results show significant atmospheric concentrations of polyols (defined here as the sum of arabitol and mannitol) and glucose at each sampling location, highlighting their ubiquity. Results also confirm that polyols and glucose are mainly associated with the coarse rather than the fine aerosol mode. At nearly all sites, atmospheric concentrations of polyols and glucose display a well-marked seasonal pattern, with maximum concentrations from late spring to early autumn, followed by an abrupt decrease in late autumn, and a minimum concentration during wintertime. Such seasonal patterns support biogenic emissions associated with higher biological metabolic activities (e.g. sporulation, growth, etc.) during warmer periods. Results from a previous comprehensive study using Positive Matrix Factorization (PMF) based on an extended aerosol chemical composition dataset of up to 130 species for 16 of the same sample series has also been used in the present work. Results show that PBOA are significant sources of total OM in PM10 (13&#8201;&#177;&#8201;4&#8201;% on a yearly average, and up to 40&#8201;% in some environments in summer) at most of the investigated sites. The mean PBOA chemical profile is clearly dominated by OM (78&#8201;&#177;&#8201;9&#8201;% of the mass of the PBOA PMF factor on average), suggesting that ambient polyols are most likely associated with biological particle emissions (e.g. active spore discharge) rather than soil dust resuspension.

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“…Epidemiological studies have revealed a robust correlation between PM 2.5 levels and the morbidity of cardiovascular and respiratory diseases [1,2]. In addition, PM 2.5 has strong extinction abilities, and therefore, reduces atmospheric visibility and affects traffic safety [3,4]. Tropospheric ozone (O 3 ), as another air pollutant, has adverse effects on human health, ecosystems, and crop growth [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Correlations between PM2.5 and Ozone over China and Associated Underlying Reasons

et al. 2019

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We investigated the spatial-temporal characteristics of the correlations between observed PM2.5 and O3 over China at a national-scale level, and examined the underlying reasons for the varying PM2.5–O3 correlations by using a chemical transport model. The PM2.5 concentrations were positively correlated with O3 concentrations for most regions and seasons over China, while negative correlations were mainly observed in northern China during winter. The strongest positive PM2.5–O3 correlations with correlation coefficients (r) larger than +0.7 existed in southern China during July, and the strongest negative correlations (r < −0.5) were observed in northern China during January. It was a very interesting phenomenon that the positive PM2.5–O3 correlations prevailed for high air temperature samples, while the negative correlations were generally found in cold environments. Together, the effective inhibitory effect of PM2.5 on O3 generation by reducing photolysis rates and the strong titration effect of freshly emitted NO with O3 contributed to the strongest negative PM2.5–O3 correlations in northern China during January (i.e., in cold environments). The strongest positive correlations in southern China during July (i.e., at high temperature), however, were mainly attributed to the promoting effect of high O3 concentration and active photochemical activity on secondary particle formation.

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Effects of Chemical Composition of PM2.5 on Visibility in a Semi-Rural City of Sichuan Basin

Cited by 22 publications

References 0 publications

Long-Term Atmospheric Visibility Trends and Characteristics of 31 Provincial Capital Cities in China during 1957–2016

Long-Term Atmospheric Visibility Trends and Characteristics of 31 Provincial Capital Cities in China during 1957–2016

Polyols and glucose particulate species as tracers of primary biogenic organic aerosols at 28 french sites

Correlations between PM2.5 and Ozone over China and Associated Underlying Reasons

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