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Spatial and Temporal Variations of PM 2.5 and Its Relation to Meteorological Factors in the Urban Area of Nanjing, China

View Article: PubMed Central - PubMed

ABSTRACT

The serious air pollution problem has aroused widespread public concerns in China. Nanjing city, as one of the famous cities of China, is faced with the same situation. This research aims to investigate spatial and temporal distribution characteristics of fine particulate matter (PM2.5) and the influence of weather factors on PM2.5 in Nanjing using Spearman-Rank analysis and the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) method. Hourly PM2.5 observation data and daily meteorological data were collected from 1 April 2013 to 31 December 2015. The spatial distribution result shows that the Maigaoqiao site suffered the most serious pollution. Daily PM2.5 concentrations in Nanjing varied from 7.3 μg/m3 to 336.4 μg/m3. The highest concentration was found in winter and the lowest in summer. The diurnal variation of PM2.5 increased greatly from 6 to 10 a.m. and after 6 p.m., while the concentration exhibited few variations in summer. In addition, the concentration was slightly higher on weekends compared to weekdays. PM2.5 was found to exhibit a reversed relation with wind speed, relative humidity, and precipitation. Although temperature had a positive association with PM2.5 in most months, a negative correlation was observed during the whole period. Additionally, a high concentration was mainly brought with the wind with a southwest direction and several relevant factors are discussed to explain the difference of the impacts of diverse wind directions.

No MeSH data available.


Related in: MedlinePlus

Box-Whiskers plot of PM2.5 mass concentration related with wind direction. Bottom and top of the blue box represent 25th and 75th percentile, whereas bottom and top of the vertical dotted line mean minimum and maximum value. The red solid lines represent median value and the firebrick square represent mean value. Outliers are depicted by the “+”.
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ijerph-13-00921-f010: Box-Whiskers plot of PM2.5 mass concentration related with wind direction. Bottom and top of the blue box represent 25th and 75th percentile, whereas bottom and top of the vertical dotted line mean minimum and maximum value. The red solid lines represent median value and the firebrick square represent mean value. Outliers are depicted by the “+”.

Mentions: As an important meteorological factor, the role of wind direction cannot be ignored [49]. PM2.5 concentration related with specific wind direction is presented in Figure 10. The figure shows that southwest wind led to the highest PM concentration, followed by north wind and northwest wind. Remarkably, such a result is not consistent with what people had expected, that is, owing to the industry pollution in the north region [20], the winds from north were expected to lead to high PM2.5 concentration, meanwhile southwest wind should not. However, the results were not as expected and there is a slight difference among north winds. There are several possible aspects to be discussed about this contrast. First, there is a big iron and steel industry zone close to the urban area in the southwest of Nanjing and the base of Ma’anshan iron and steel industry is also located in the direction adjacent to Nanjing city. Therefore, large amount of particles generated from the industry can spread to urban areas by a southwest wind, which directly aggravates the PM2.5 pollution. Second, particles can be transported into Nanjing from the north region, which could be confirmed by the trajectories of air flows using the HYSPLIT model in Figure 11. Nonetheless, with the transportation of pollutants, cold air is usually brought by air flows directly from the north and then it encounters the warm flows from south in the Nanjing area. In the process, favorable weather conditions can be formed and directly lead to the attenuation of PM2.5, which cause unremarkable PM2.5 pollution by winds with north directions. Meanwhile, due to the mountain terrain in the northwest, it is not beneficial to the horizontal diffusion of air pollutants and leads to higher PM2.5 concentration related with northwest wind. Additionally, the result might partly verify the preliminary analysis of the pollution source that PM2.5 pollution is mainly derived from local pollution while regional transportation was responsible for about 28.5% [43]. Certainly, the analysis of wind direction involves many factors, such as pollution sources, terrain, mixing layer, etc., and due to the limited data, basic analysis is only given for the statistic result in this section.


Spatial and Temporal Variations of PM 2.5 and Its Relation to Meteorological Factors in the Urban Area of Nanjing, China
Box-Whiskers plot of PM2.5 mass concentration related with wind direction. Bottom and top of the blue box represent 25th and 75th percentile, whereas bottom and top of the vertical dotted line mean minimum and maximum value. The red solid lines represent median value and the firebrick square represent mean value. Outliers are depicted by the “+”.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036754&req=5

ijerph-13-00921-f010: Box-Whiskers plot of PM2.5 mass concentration related with wind direction. Bottom and top of the blue box represent 25th and 75th percentile, whereas bottom and top of the vertical dotted line mean minimum and maximum value. The red solid lines represent median value and the firebrick square represent mean value. Outliers are depicted by the “+”.
Mentions: As an important meteorological factor, the role of wind direction cannot be ignored [49]. PM2.5 concentration related with specific wind direction is presented in Figure 10. The figure shows that southwest wind led to the highest PM concentration, followed by north wind and northwest wind. Remarkably, such a result is not consistent with what people had expected, that is, owing to the industry pollution in the north region [20], the winds from north were expected to lead to high PM2.5 concentration, meanwhile southwest wind should not. However, the results were not as expected and there is a slight difference among north winds. There are several possible aspects to be discussed about this contrast. First, there is a big iron and steel industry zone close to the urban area in the southwest of Nanjing and the base of Ma’anshan iron and steel industry is also located in the direction adjacent to Nanjing city. Therefore, large amount of particles generated from the industry can spread to urban areas by a southwest wind, which directly aggravates the PM2.5 pollution. Second, particles can be transported into Nanjing from the north region, which could be confirmed by the trajectories of air flows using the HYSPLIT model in Figure 11. Nonetheless, with the transportation of pollutants, cold air is usually brought by air flows directly from the north and then it encounters the warm flows from south in the Nanjing area. In the process, favorable weather conditions can be formed and directly lead to the attenuation of PM2.5, which cause unremarkable PM2.5 pollution by winds with north directions. Meanwhile, due to the mountain terrain in the northwest, it is not beneficial to the horizontal diffusion of air pollutants and leads to higher PM2.5 concentration related with northwest wind. Additionally, the result might partly verify the preliminary analysis of the pollution source that PM2.5 pollution is mainly derived from local pollution while regional transportation was responsible for about 28.5% [43]. Certainly, the analysis of wind direction involves many factors, such as pollution sources, terrain, mixing layer, etc., and due to the limited data, basic analysis is only given for the statistic result in this section.

View Article: PubMed Central - PubMed

ABSTRACT

The serious air pollution problem has aroused widespread public concerns in China. Nanjing city, as one of the famous cities of China, is faced with the same situation. This research aims to investigate spatial and temporal distribution characteristics of fine particulate matter (PM2.5) and the influence of weather factors on PM2.5 in Nanjing using Spearman-Rank analysis and the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) method. Hourly PM2.5 observation data and daily meteorological data were collected from 1 April 2013 to 31 December 2015. The spatial distribution result shows that the Maigaoqiao site suffered the most serious pollution. Daily PM2.5 concentrations in Nanjing varied from 7.3 μg/m3 to 336.4 μg/m3. The highest concentration was found in winter and the lowest in summer. The diurnal variation of PM2.5 increased greatly from 6 to 10 a.m. and after 6 p.m., while the concentration exhibited few variations in summer. In addition, the concentration was slightly higher on weekends compared to weekdays. PM2.5 was found to exhibit a reversed relation with wind speed, relative humidity, and precipitation. Although temperature had a positive association with PM2.5 in most months, a negative correlation was observed during the whole period. Additionally, a high concentration was mainly brought with the wind with a southwest direction and several relevant factors are discussed to explain the difference of the impacts of diverse wind directions.

No MeSH data available.


Related in: MedlinePlus