Research on PM2.5 Concentration Based on Dissipative Structure Theory

Research on PM2.5 Concentration Based on Dissipative Structure Theory

www.nature.com/scientificreports OPEN Research on ­PM2.5 concentration based on dissipative structure theory: a case study of Xi’an, China Xiaoke Sun, Hong Chen*, Zhizhen Liu & Hengrui Chen PM2.5 pollution has become a serious urban environmental problem, especially in developing countries with increasing urbanization. Understanding the proportion of PM2.5 generation sources has laid a foundation for better ­PM2.5 concentration reduction This paper used Point of Interesting (POI)data, building profle data of Xi’an, PM2.5 concentration and wind monitoring data of fve provinces near Xi’an as the basic data. And this paper studied the spatial distribution of various buildings in Xi’an, the temporal and spatial distribution of ­PM2.5 in Xi’an and the fve provinces, and found that the spatial distribution of ­PM2.5 concentration in Xi’an and the building distribution in Xi’an does not match. Based on this, a quantitative model of ­PM2.5 concentration in Xi’an, energy consumption, wind, and other factors is established through the qualitative and quantitative analysis of ­PM2.5 concentration in Xi’an. Entropy theory and dissipative structure theory are applied to analyze this phenomenon. The results show ­PM2.5 in Xi’an mainly comes from the spread of ­PM2.5 in the fve provinces. The PM2.5 generated by energy consumption in Xi’an is not enough to cause serious ­PM2.5 pollution. And further suggestions on how to reduce ­PM2.5 concentration in Xi’an are put forward. With the rapid economic growth and development of infrastructure in developing countries, urbanization and motorization are accelerating. So are the demands in industry, living, and transportation based on fossil fuel, 1 leading to serious urban air pollution . PM2.5 refers to particles within an aerodynamic equivalent diameter of 2.5 microns in ambient air, which can levitate in the air for a long time. Although PM 2.5 is only a fraction of the Earth’s atmosphere, it has a great efect on air quality and visibility. Its main chemical composition includes organic carbon, elemental carbon, nitrate, sulfate, ammonium salt, sodium salt2. With small particle size, it has strong activity, easily attached with toxic and harmful substances (such as heavy metal, microorganisms). Meanwhile, it has a long residence time and transportation distance in the atmosphere. It has great infuence on health of human and air quality, reducing the overall comfort of the city3. In developing countries like China, with a rapid development in economy and infrastructure, there are many sources of PM 2.5, causing large-scale envi- ronmental pollution. Terefore, it is very serious to fnd the primary factors of PM2.5 concentration to reduce it. Under such circumstance, Chinese government spared no efort to improve urban transport system, the governance of industrial enterprises, and the transformation of domestic energy system (boiler transformation, 4,5 bulk coal transformation), which greatly reduced PM2.5 emissions . It can tell through the air pollution in lots of cities in China, especially in Beijing. In Beijing, one of the important measures to control urban air pollu- tion is optimizing its energy structure. It has adopted stricter emission standards for coal-fred boiler pollut- ants. Financial subsidies are provided for replacement and reconstruction on coal-fred facilities. Meanwhile, it accelerates the development of clean energy such as natural gas and electricity. Comprehensive control of motor vehicle pollution is also carried out, including new and in-use vehicle control, promotion of new energy vehicles, improvement on quality of oil products, trafc control measures, economic incentives. An efective air quality management system has been established afer such laws and regulations, efective law enforcement, systematic planning, strict local standards, sound monitoring systems, and rising public environmental awareness. Tese measures produced a very signifcant efect. During 2013 to 2017, the annual average concentration of PM 2.5 dropped from 89.5 to 58 μg/m3. With development of emerging geographic information systems (GIS), GPS technology, environmental detection technology, and big data mining methods, there are efective research methods for in-depth study 6–8 of the sources of PM2.5 and analysis of the relationship between them . With the big data mining method, we 9 can analyze the real-time monitoring data of both PM 2.5 and wind to fnd the correlation between them . With College of Transportation Engineering, Chang’an University, Xi’an 710064, China. *email: [email protected] SCIENTIFIC REPORTS | (2020) 10:16435 | https://doi.org/10.1038/s41598-020-73598-9 1 Vol.:(0123456789) www.nature.com/scientificreports/ GIS, the real-time monitoring data of PM 2.5 and wind, and other interfering factors in each area can be visually displayed. It is useful to help researchers analyze their connection and identify related models with the spati- otemporal characteristics obtained from GIS8,10. Te famous physicist Prigogine introduced the concept of open systems to the second law of thermodynamics in 1969 and developed it to establish the dissipative structure theory. Dissipative structure theory explains how an open system changes from disorder to order, which is an extension of entropy theory. At present, dissipative structure theory has made a huge impact in many felds of natural sciences and social sciences, such as physics, astronomy, biology, economics, and philosophy 11. However, research of dissipative structure theory on the dif- fusion of pollutants is rarely studied. Some scholars have done some studies about Beijing. By omitting Trafc-related information like vehicle types, numbers and density of vehicles, they combined atmospheric chemical difusion models with statistical GAMM models and simplifed the mathematical algorithm. Tey found 17.2–37.3% of PM2.5 may be related to trafc emissions12. Some studies have proposed a comprehensive framework for estimating trafc-related air pollution concentrations in real-time trafc and basic meteorological information. Te impact was further evaluated13. Adopting provincial panel data and panel data models from 2001 to 2012, some scholars analyzed the main driving forces afecting regional emissions at the regional level in China. It turns out the decisive factor of carbon emissions is economic growth. Carbon emissions vary from region to region, decreasing from central 14 to western and eastern regions . Tere are also studies analyzing the composition of collected PM 2.5 by analyz- ing the chemical composition. But through this method, it is hard to distinguish whether the source of PM 2.5 is in this region or not3,15,16. Tese studies considered factors such as energy consumption, vehicle emissions, economic growth and population growth without fully taking the impact of difusion of pollutants from other surrounding cities17–19. Based on these studies, this paper adds the impact of peripheral urban pollutants on the research of urban pollutants. It has been confrmed that the PM2.5 concentration is comprehensively afected by the factors such as energy consumption, economic growth, population growth, and vehicle emissions20–23. Nowadays, most researches on urban pollution focus on the analysis of pollution sources in a certain city, or large-region macro analysis of multiple cities. Tere are few studies that integrate these factors and the pollution of peripheral cities in the study area into a system for analysis. Terefore, these previous studies may be inaccurate. Tis study bases on the data of PM2.5 concentration and wind in fve provinces (explained the province selection in “Regional elevation and terrain analysis of the fve provinces” section) and data of infuencing factors (such as energy consumption) in Xi’an to analyze the PM 2.5 concentration in Xi’an. Taking advantage of a combination of qualitative and quanti- tative analysis methods, entropy theory, dissipative structure theory, this paper has studied the primary factors of PM2.5 concentration in Xi’an and analyzed how to reduce the PM 2.5 concentration efectively. And this study will propose a more comprehensive PM2.5 reduction method than the previous one-sided and a more efective plan for improving the urban environment research on basis of a clear analysis of the source of PM 2.5 in Xi’an and sources outside Xi’an. Te rest of this article is organized as followed: afer this introduction, second section introduces materials and methods, including data and the theory; third section presents the case description; fourth section presents the results, discussions, and related implications; ffh section presents the conclusion. Materials and methods Data. Tis study aims to fnd the main source of PM 2.5 pollutants in Xi’an. PM 2.5 is mainly produced from industrial, living, economic, transportation and other aspects. As a class of tiny particulates, PM2.5 has a long res- idence time in the atmosphere and can spread a long distance with the wind. Terefore, whether PM 2.5 in Xi’an has been increased by the difusion of other areas should be considered. To analyze the relationship between PM2.5 concentration and wind, this study collected the PM2.5 concentration and wind speed of Xi’an (11 PM2.5 monitoring points) and fve provinces (261 PM2.5 monitoring points and 45 wind monitoring points) from Octo- ber 15, 2018 to April 15, 2019, according to the heating time in Northern China: November 15 to March 15, for a total of 183 days from China National Environmental Monitoring Station, China Meteorological Data Network, and National Centers for Environmental Information (https ://www.ncdc.noaa.gov/). And the locations of PM2.5 monitoring points are divided into three categories: (1) Automatic monitoring points, located 3–15 m away from the ground; (2) Monitoring points located near buildings above 20 m, located 15–25 m away from the ground; (3) Roadside monitoring point is located 2–5 m away from the ground.

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