Spatio-temporal variations of PM2.5 emission in China from 2005 to 2014

Jin, Qiang; Fang, Xing; Wen, Bo; Shan, Aidang

doi:10.1016/j.chemosphere.2017.05.133

Cited by 103 publications

(51 citation statements)

References 13 publications

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“…The present study revealed that mean PM concentrations in spring were higher than those in summer, consistent with other studies [13,18,19,22]. In East Asia, PM 10 levels peak in March through April [23].…”

Section: Discussionsupporting

confidence: 92%

“…As daily PM concentration varies, it is di cult to determine high and low PM on a daily basis. Previous studies have indicated that the average concentration of PM in Seoul is higher in spring than in other seasons due to transport of aerosols from the Asian continent [18,19]. In contrast, in summer, frequent precipitation and low transport from the Asian continent will lead to a lower concentration of PM than in other seasons [19].…”

Section: Determination Of High-pm and Low-pm Periodsmentioning

confidence: 95%

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Effects of Particulate Matter on Healthy Skin: A Comparative Study Between High and Low-particulate Matter Periods

Yoon

Park

et al. 2020

Preprint

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Background The influence of airborne particulate matter (PM) on skin has primarily been studied in patients with skin diseases such as atopic dermatitis. Recently, the effect of PM on healthy human skin has gained attention. This study aimed to evaluate the relationship between PM concentration and objective skin changes in healthy subjects. Methods This prospective study enrolled 25 healthy volunteers without any skin disease. Data regarding daily meteorological parameters and air pollution were collected during a high-PM period and a low-PM period for 14 days. Environmental and lifestyle factors that might influence skin conditions of subjects were also collected during the study period. Biophysical parameters of the skin such as transepidermal water loss (TEWL), hydration, erythema index, and melanin index were measured. Pores, wrinkles, sebum, and skin tone were evaluated using a facial analysis system. Results Mean TEWL value during the high-PM period was significantly higher than that during the low-PM period (10.16 g/m2/h vs. 5.99 g/m2/h, p = 0.0005). Mean erythema index was significantly higher in the high-PM period than that in the low-PM period (4.3 vs. 3.42, p = 0.038). For facial analysis system indices, uniformity of skin tone was higher in the low-PM period than that in the high-PM period (p < 0.0001). In addition, with increasing PM10 and PM2.5, TEWL also showed increase when other environmental components were constant [regression coefficient (RC) = 0.1529, p < 0.0001 for PM10; RC = 0.2055, p = 0.0153 for PM2.5]. Conclusions Increased PM concentrations may contribute to disturbed barrier function, increased facial erythema, and uneven skin tone even in healthy human skin.

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Section: Discussionsupporting

confidence: 92%

Section: Determination Of High-pm and Low-pm Periodsmentioning

confidence: 95%

Effects of Particulate Matter on Healthy Skin: A Comparative Study Between High and Low-particulate Matter Periods

Yoon

Park

et al. 2020

Preprint

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“…With an increase in regional differentiation [17], analysis on small district cities can be more valuable. Secondly, the existing studies used mostly rough and historical data [24], causing the research results to lack accuracy and practicality.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Spatial-Temporal Characteristics of the PM2.5 Concentrations in Weifang City, China

Dai

Liu

2018

Sustainability

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Air pollution, which accompanies industrial progression and urbanization, has become an urgent issue to address in contemporary society. As a result, our understanding and continued study of the spatial-temporal characteristics of a major pollutant, defined as 2.5-micron or less particulate matter (PM2.5), as well as the development of related approaches to improve the environment, has become vital. This paper studies the characteristics of yearly, quarterly, monthly, daily, and hourly PM2.5 concentrations, and discusses the influencing factors based on the hourly data of nationally controlled and provincially controlled monitoring stations, from 2012 to 2016, in Weifang City. The main conclusion of this study is that the annual PM2.5 concentrations reached a peak in 2013. With efficient aid from the government, this value has decreased annually and has high spatial characteristics in the northwest and low spatial characteristics in the southeast. Second, the seasonal and monthly PM2.5 concentrations form a U-shaped trend, meaning that the concentration is high in the summer and low in the winter. These trends are highly relevant to the factors of plantation, humidity, temperature, and precipitation. Third, within a week, higher PM2.5 concentrations appear on Mondays and Saturdays, whereas the lowest concentration occurs on Wednesdays. It can be inferred that PM2.5 concentrations tend to be highly dependent on human activities and living habits. Lastly, there are hourly discrepancies within the peaks and troughs depending on the month, and the overall daytime PM2.5 concentrations and reductive rates are higher in the daytime than in the nighttime.

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“…As for studies on PM 2.5 pollution, previous scholars have generally used descriptive statistical analyses and combined spatial autocorrelation analyses to study a spatial cluster of annual PM 2.5 concentrations [7][8][9]. However, concentrations change in space, which tends to change the means of local areas.…”

Section: Introductionmentioning

confidence: 99%

“…As for studies of polluted periods, previous researchers have mainly analyzed changes in PM 2.5 concentrations using statistical methods that include the year, quarter, or day to analyze variations in the concentration of PM 2.5 [7,9,15,21]. These researchers have used overall temporal information to analyze the evolutionary features of PM 2.5 based on a simple method, where temporal characteristics of PM 2.5 are evaluated with the assumption that the statistical properties of the time series do not vary over time.…”

Section: Introductionmentioning

confidence: 99%

Joint Governance Regions and Major Prevention Periods of PM2.5 Pollution in China Based on Wavelet Analysis and Concentration-Weighted Trajectory

Zhao

et al. 2020

Sustainability

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China has made some progress in controlling PM2.5 (particulate matter with an aerodynamic diameter of ≤2.5 μm) pollution, but there are still some key areas that need further strengthening. Considering that excessive prevention and control efforts affect economic development, this paper combined an empirical orthogonal function, a continuous wavelet transform, and a concentration-weighted trajectory method to study joint regional governance during key pollution periods to provide suggestions for the efficient control of PM2.5. The results from our panel of data of PM2.5 in China from 2016 to 2018 could be decomposed into two modes. In the first mode, the pollution center was in central Shaanxi Province, and the main eruption period was from November to January of the following year. As the center of this region, Xi’an should cooperate with the four cities in eastern Sichuan (Nanchong, Guangan, Bazhong, and Dazhou) to control PM2.5, since the eruption occurred in this area. Moreover, governance should last for at least two cycles, where one cycle is at least 23 days. The pollution center of the second mode was in the western part of Xinjiang. Therefore, after the prevention and control efforts during the first mode are completed, the regional city of Kashgar should continue to build a joint governance zone for PM2.5 along the Tianshan mountains in the east, focusing on prevention and control over two cycles (where one cycle is 28 days).

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Spatio-temporal variations of PM2.5 emission in China from 2005 to 2014

Cited by 103 publications

References 13 publications

Effects of Particulate Matter on Healthy Skin: A Comparative Study Between High and Low-particulate Matter Periods

Effects of Particulate Matter on Healthy Skin: A Comparative Study Between High and Low-particulate Matter Periods

Analysis of Spatial-Temporal Characteristics of the PM2.5 Concentrations in Weifang City, China

Joint Governance Regions and Major Prevention Periods of PM2.5 Pollution in China Based on Wavelet Analysis and Concentration-Weighted Trajectory

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