An exploration of meteorological effects on PM2.5 air quality in several provinces and cities in Vietnam

• Published in: Journal of environmental sciences (China) Vol. 145; pp. 139 - 151
• Main Authors: Nguyen, Giang Tran Huong, La, Luan Thien, Hoang-Cong, Huy, Le, Anh Hoang
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2024
• Subjects: Air pollution; Causality analysis; Convergent cross mapping; Fine particulate matter; Meteorological effect; Vietnam; Air pollution; Convergent cross mapping; Vietnam; Fine particulate matter; Meteorological effect; Causality analysis
• ISSN: 1001-0742; 1878-7320
• DOI: 10.1016/j.jes.2023.07.020

Linking meteorology and air pollutants is a key challenge. The study investigated meteorological effects on PM2.5 concentration using the advanced convergent cross mapping method, utilizing hourly PM2.5 concentration and six meteorological factors across eight provinces and cities in Vietnam. Results demonstrated that temperature (ρ = 0.30) and radiation (ρ = 0.30) produced the highest effects, followed by humidity (ρ = 0.28) and wind speed (ρ = 0.24), while pressure (ρ = 0.22) and wind direction (ρ = 0.17) produced the weakest effects on PM2.5 concentration. Comparing the ρ values showed that temperature, wind speed, and wind direction had greater impacts on PM2.5 concentration during the dry season whereas radiation had a more influence during the wet season; Southern stations experienced larger meteorological effects. Temperature, humidity, pressure, and wind direction had both positive and negative influences on PM2.5 concentration, while radiation and wind speed mostly had negative influences. During PM2.5 pollution episodes, there was more contribution of meteorological effects on PM2.5 concentration indicated by ρ values. At contaminated levels, humidity (ρ = 0.45) was the most dominant factor affecting PM2.5 concentration, followed by temperature (ρ = 0.41) and radiation (ρ = 0.40). Pollution episodes were pointed out to be more prevalent under higher humidity, higher pressure, lower temperature, lower radiation, and lower wind speed. The ρ calculation also revealed that lower temperature, lower radiation, and higher humidity greatly accelerated each other under pollution episodes, further enhancing PM2.5 concentration. The findings contributed to the literature on meteorology and air pollution interaction.