Next Article in Journal
An Analysis of Environment Behavior Relationships towards the Design of a Local Mixed-used Street: Based on Behavior Settings of Belgium Street in Cebu City, Philippines
Previous Article in Journal
Hybrid Input-Output Analysis of Embodied Carbon and Construction Cost Differences between New-Build and Refurbished Projects
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Sustainability 2018, 10(9), 3228; https://doi.org/10.3390/su10093228

Relevance Analysis on the Variety Characteristics of PM2.5 Concentrations in Beijing, China

1
Department of Engineering Physics, Tsinghua University, Beijing 100084, China
2
Beijing Key Laboratory of City Integrated Emergency Response Science, Tsinghua University, Beijing 100084, China
*
Author to whom correspondence should be addressed.
Received: 9 August 2018 / Revised: 7 September 2018 / Accepted: 7 September 2018 / Published: 10 September 2018
Full-Text   |   PDF [3940 KB, uploaded 14 September 2018]   |  

Abstract

Air pollution has become one of the most serious environmental problems in the world. Considering Beijing and six surrounding cities as main research areas, this study takes the daily average pollutant concentrations and meteorological factors from 2 December 2013 to 30 June 2017 into account and studies the spatial and temporal distribution characteristics and the relevant relationship of particulate matter smaller than 2.5 μm (PM2.5) concentrations in Beijing. Based on correlation analysis and geo-statistics techniques, the inter-annual, seasonal, and diurnal variation trends and temporal spatial distribution characteristics of PM2.5 concentration in Beijing are studied. The study results demonstrate that the pollutant concentrations in Beijing exhibit obvious seasonal and cyclical fluctuation patterns. Air pollution is more serious in winter and spring and slightly better in summer and autumn, with the spatial distribution of pollutants fluctuating dramatically in different seasons. The pollution in southern Beijing areas is more serious and the air quality in northern areas is better in general. The diurnal variation of air quality shows a typical seasonal difference and the daily variation of PM2.5 concentrations present a “W” type of mode with twin peaks. Besides emission and accumulation of local pollutants, air quality is easily affected by the transport effect from the southwest. The PM2.5 and PM10 concentrations measured from the city of Langfang are taken as the most important factors of surrounding pollution factors to PM2.5 in Beijing. The concentrations of PM10 and carbon monoxide (CO) concentrations in Beijing are the most significant local influencing factors to PM2.5 in Beijing. Extreme wind speeds and maximal wind speeds are considered to be the most significant meteorological factors affecting the transport of pollutants across the region. When the wind direction is weak southwest wind, the probability of air pollution is greater and when the wind direction is north, the air quality is generally better. View Full-Text
Keywords: relevance analysis; spatial and temporal distribution characteristics; PM2.5; Beijing relevance analysis; spatial and temporal distribution characteristics; PM2.5; Beijing
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Zhai, B.; Chen, J.; Yin, W.; Huang, Z. Relevance Analysis on the Variety Characteristics of PM2.5 Concentrations in Beijing, China. Sustainability 2018, 10, 3228.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top