Article: Investigating PM responses to other air pollutants and meteorological factors across multiple temporal scales

It remains unclear on how PM interacts with other air pollutants and meteorological factors at different temporal scales, while such knowledge is crucial to address the air pollution issue more effectively. In this study, we explored such interaction at various temporal scales, taking the city of Nanjing, China as a case study. The ensemble empirical mode decomposition (EEMD) method was applied to decompose time series data of PM, five other air pollutants, and six meteorological factors, as well as their correlations were examined at the daily and monthly scales. The study results show that the original PM concentration significantly exhibited non-linear downward trend, while the decomposed time series of PM concentration by EEMD followed daily and monthly cycles. The temporal pattern of PM, SO and NO is synchronous with that of PM. At both daily and monthly scales, PM was positively correlated with CO and negatively correlated with 24-h cumulative precipitation. At the daily scale, PM was positively correlated with O, daily maximum and minimum temperature, and negatively correlated with atmospheric pressure, while the correlation pattern was opposite at the monthly scale.

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References

1.

Bandowe B, Meusel H, Huang R, Ho K, Cao J, Hoffmann T . PM₂.₅-bound oxygenated PAHs, nitro-PAHs and parent-PAHs from the atmosphere of a Chinese megacity: seasonal variation, sources and cancer risk assessment. Sci Total Environ. 2013; 473-474:77-87. DOI: 10.1016/j.scitotenv.2013.11.108. View

2.

Wu S, Deng F, Hao Y, Wang X, Zheng C, Lv H . Fine particulate matter, temperature, and lung function in healthy adults: findings from the HVNR study. Chemosphere. 2014; 108:168-74. DOI: 10.1016/j.chemosphere.2014.01.032. View

3.

Lelieveld J, Evans J, Fnais M, Giannadaki D, Pozzer A . The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature. 2015; 525(7569):367-71. DOI: 10.1038/nature15371. View

4.

Huang R, Zhang Y, Bozzetti C, Ho K, Cao J, Han Y . High secondary aerosol contribution to particulate pollution during haze events in China. Nature. 2014; 514(7521):218-22. DOI: 10.1038/nature13774. View

5.

Zhang H, Wang Y, Hu J, Ying Q, Hu X . Relationships between meteorological parameters and criteria air pollutants in three megacities in China. Environ Res. 2015; 140:242-54. DOI: 10.1016/j.envres.2015.04.004. View

6.

Tang C, Coull B, Schwartz J, Di Q, Koutrakis P . Trends and spatial patterns of fine-resolution aerosol optical depth-derived PM emissions in the Northeast United States from 2002 to 2013. J Air Waste Manag Assoc. 2016; 67(1):64-74. DOI: 10.1080/10962247.2016.1218393. View

7.

Zhou Q, Jiang H, Wang J, Zhou J . A hybrid model for PM₂.₅ forecasting based on ensemble empirical mode decomposition and a general regression neural network. Sci Total Environ. 2014; 496:264-274. DOI: 10.1016/j.scitotenv.2014.07.051. View

8.

Chuai X, Feng J . High resolution carbon emissions simulation and spatial heterogeneity analysis based on big data in Nanjing City, China. Sci Total Environ. 2019; 686:828-837. DOI: 10.1016/j.scitotenv.2019.05.138. View

9.

Ren R, Hu W, Dong J, Sun B, Chen Y, Chen Z . A Systematic Literature Review of Green and Sustainable Logistics: Bibliometric Analysis, Research Trend and Knowledge Taxonomy. Int J Environ Res Public Health. 2020; 17(1). PMC: 6982341. DOI: 10.3390/ijerph17010261. View

10.

Wang D, Xu H, Yang S, Wang W, Wang Y . Adsorption Property and Mechanism of Oxytetracycline onto Willow Residues. Int J Environ Res Public Health. 2017; 15(1). PMC: 5800108. DOI: 10.3390/ijerph15010008. View

Investigating PM Responses to Other Air Pollutants and Meteorological Factors Across Multiple Temporal Scales