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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.


Monthly variation of PM2.5 concentrations in Nanjing. The bar represents PM2.5 concentrations and the line means standard deviation.
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ijerph-13-00921-f004: Monthly variation of PM2.5 concentrations in Nanjing. The bar represents PM2.5 concentrations and the line means standard deviation.

Mentions: Figure 4 shows monthly variation of PM2.5 concentrations in Nanjing. For 2014, the highest PM2.5 concentration appeared in January. In addition, the concentration in February, March, and April continually decreased. There was a sharp rise of PM2.5 concentration in May, and the value in June was a little higher than in May. Subsequently, the concentration value reduced in the next two months. The lowest concentration of the whole year was observed in August, and the average value was 42.4 μg/m3, which is very close to the grade-1 value (32 μg/m3) national standard [41]. The concentration continued to increase in September, October and November. However, a rare decline occurred in December. Monthly variation in 2013 and 2015 was basically analogous to that in 2014, but several differences were observed: the lowest average value was found in July of 2013 and September of 2015; the concentration continually increased from October to December in both 2013 and 2015, different from the decrease in December of 2014; PM2.5 pollution was the highest for the studied period in the winter of 2013, followed by January in 2014, indicating that pollution was on going.


Spatial and Temporal Variations of PM 2.5 and Its Relation to Meteorological Factors in the Urban Area of Nanjing, China
Monthly variation of PM2.5 concentrations in Nanjing. The bar represents PM2.5 concentrations and the line means standard deviation.
© Copyright Policy
Related In: Results  -  Collection

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

ijerph-13-00921-f004: Monthly variation of PM2.5 concentrations in Nanjing. The bar represents PM2.5 concentrations and the line means standard deviation.
Mentions: Figure 4 shows monthly variation of PM2.5 concentrations in Nanjing. For 2014, the highest PM2.5 concentration appeared in January. In addition, the concentration in February, March, and April continually decreased. There was a sharp rise of PM2.5 concentration in May, and the value in June was a little higher than in May. Subsequently, the concentration value reduced in the next two months. The lowest concentration of the whole year was observed in August, and the average value was 42.4 μg/m3, which is very close to the grade-1 value (32 μg/m3) national standard [41]. The concentration continued to increase in September, October and November. However, a rare decline occurred in December. Monthly variation in 2013 and 2015 was basically analogous to that in 2014, but several differences were observed: the lowest average value was found in July of 2013 and September of 2015; the concentration continually increased from October to December in both 2013 and 2015, different from the decrease in December of 2014; PM2.5 pollution was the highest for the studied period in the winter of 2013, followed by January in 2014, indicating that pollution was on going.

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.