Limits...
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.


Seasonal distribution of PM2.5 concentrations for three years based on the CEEMDAN decomposition results.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC5036754&req=5

ijerph-13-00921-f008: Seasonal distribution of PM2.5 concentrations for three years based on the CEEMDAN decomposition results.

Mentions: In general, low-frequency signals contain yearly variations while high frequency signals include sudden changes. IMFs from IMF1 to IMF6 mean the period less than a year while IMF8 represents inter-annual changes. In addition, the IMF7 represents the cycle of about a year. Therefore, the original signal was reconstructed by getting together the IMFs without IMF8 and the residue to obtain seasonal changes of PM2.5 mass concentration in Nanjing. The mean concentration in each season was computed by averaging the reconstructed data series in the four seasons. Figure 8 shows the mean concentration in the different seasons of three years, where the data are not complete in the spring and winter of 2013. Several details can be seen: (1) the seasonal PM2.5 concentration varied greatly; (2) the highest concentration was always found in winter while the lowest was in summer; and (3) the concentration in winter of 2015 was a little higher than in 2014.


Spatial and Temporal Variations of PM 2.5 and Its Relation to Meteorological Factors in the Urban Area of Nanjing, China
Seasonal distribution of PM2.5 concentrations for three years based on the CEEMDAN decomposition results.
© Copyright Policy
Related In: Results  -  Collection

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

ijerph-13-00921-f008: Seasonal distribution of PM2.5 concentrations for three years based on the CEEMDAN decomposition results.
Mentions: In general, low-frequency signals contain yearly variations while high frequency signals include sudden changes. IMFs from IMF1 to IMF6 mean the period less than a year while IMF8 represents inter-annual changes. In addition, the IMF7 represents the cycle of about a year. Therefore, the original signal was reconstructed by getting together the IMFs without IMF8 and the residue to obtain seasonal changes of PM2.5 mass concentration in Nanjing. The mean concentration in each season was computed by averaging the reconstructed data series in the four seasons. Figure 8 shows the mean concentration in the different seasons of three years, where the data are not complete in the spring and winter of 2013. Several details can be seen: (1) the seasonal PM2.5 concentration varied greatly; (2) the highest concentration was always found in winter while the lowest was in summer; and (3) the concentration in winter of 2015 was a little higher than in 2014.

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.