ArticlePloS one2015
PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing, China.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Accountability Assessment of Source-Specific Impacts of Regulations on Emissions and Air Quality Using Positive Matrix Factorization.Environmental science & technology · 2025Article
- Sources and Specified Health Risks of 12 PMToxics · 2024Article
- Effect of Evaluation of Various Emission Control Policies on PMACS omega · 2024Article
- Wintertime investigation of PMScientific reports · 2024Article
- Prediction of Pollutant Concentration Based on Spatial-Temporal Attention, ResNet and ConvLSTM.Sensors (Basel, Switzerland) · 2023Article
- Role of air pollutants in dengue fever incidence: evidence from two southern cities in Taiwan.Pathogens and global health · 2023Article
- Identification of differentially expressed genes and pathways in BEAS-2B cells upon long-term exposure to particulate matter (PMEnvironmental health and preventive medicine · 2023Article
- Rigorous quantification of statistical significance of the COVID-19 lockdown effect on air quality: The case from ground-based measurements in Ontario, Canada.Journal of hazardous materials · 2021Article
- Effect of Air Pollution on Obesity in Children: A Systematic Review and Meta-Analysis.Children (Basel, Switzerland) · 2021Review
- Joint association of cigarette smoking and PMBMC pulmonary medicine · 2021Article
- Association of temporary Environmental Protection Agency regulation suspension with industrial economic viability and local air quality in California, United States.Environmental sciences Europe · 2021Article
- Relationship of meteorological factors and air pollutants with medical care utilization for gastroesophageal reflux disease in urban area.World journal of gastroenterology · 2020Article
- PM2.5 induces apoptosis, oxidative stress injury and melanin metabolic disorder in human melanocytes.Experimental and therapeutic medicine · 2020Article
- Does environmental regulation reduce China's haze pollution? An empirical analysis based on panel quantile regression.PloS one · 2020Article
- Understanding PMPeerJ · 2020Article
- Sex-Dependent Effects of PMInternational journal of environmental research and public health · 2019Article
- Robust Analysis of PMSensors (Basel, Switzerland) · 2019Article
- Effects of particulate matter (PM) on childhood asthma exacerbation and control in Xiamen, China.BMC pediatrics · 2019Article
- Source Apportionment and Influencing Factor Analysis of Residential Indoor PMInternational journal of environmental research and public health · 2018Article
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17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveLimited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM2.5 and meteorological factors.
methodsDaily and hourly PM2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM).
resultsAnnual mean and median of PM2.5 concentrations were 88.07 μg/m3 and 71.00 μg/m3, respectively, from August 2013 to July 2014. PM2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM2.5 showed a long-term trend of fluctuations, with 2-6 peaks each month. PM2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM2.5 concentration using the GAMM model (R2 = 0.59, AIC = 7373.84).
conclusionPM2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM2.5.
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