Multifractal property and long-range cross-correlation behavior of particulate matters at urban traffic intersection in Shanghai

Abstract. This study reports results of PM1 chemical composition determined using a Time-of-Flight Aerosol Chemical Speciation Monitor (ToF-ACSM) over a 14-month period (1 February 2017–13 April 2018) at the Marseille–Longchamp supersite (MRS-LCP) in France. Parallel measurements were performed with an aethalometer, an ultrafine particle monitor and a suite of instruments to monitor regulated pollutants (PM2.5, PM10, NOx, O3 and SO2). The average PM1 chemical composition over the period was dominated by organic aerosol (OA; 49.7 %) and black carbon (BC; 17.1 %), while sulfate accounted for 14.6 %, nitrate for 10.2 %, ammonium for 7.9 % and chloride for 0.5 % only. Wintertime was found to be the season contributing the most to the annual PM1 mass concentration (30 %), followed by autumn (26 %), summer (24 %) and spring (20 %). During this season, OA and BC concentrations were found to contribute 32 % and 31 % of their annual concentrations, respectively, as a combined result of heavy urban traffic, high emissions from residential heating and low planetary boundary layer (PBL) height. Most (75 %) of the 15 days exceeding the target daily PM2.5 concentration value recommended by the World Health Organization (WHO) occurred during this season. Local and long-range pollution episodes with contrasting chemical composition could be distinguished, accounting for 40 % and 60 % of the exceedance days, respectively. Enhanced OA and BC concentrations, mostly originating from domestic wood burning under nocturnal land breeze conditions, were observed during local pollution episodes, while high levels of oxygenated OA and inorganic nitrate were associated with medium-/long-range transported particles. In summertime, substantially higher concentrations of sulfate were found, with an average and a maximum contribution to the PM1 mass of 24 % and 66 %, respectively. Results from k-means clustering analysis of daily profiles of sulfate concentrations clearly reveal the significant influence of local harbour/industrial activities on air quality in addition to the more regional contribution of shipping traffic that originates from the Mediterranean basin.

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Exploring Urban Road System Structure and Operation Mechanism about the Traffic Intersection Congestion

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.209-211.945 ◽

2012 ◽

Vol 209-211 ◽

pp. 945-951

Author(s):

Xue Zhong Zhang ◽

Wei Shui Fei ◽

Xiao Jun Ning

Keyword(s):

Traffic Congestion ◽

City Planning ◽

Hot Spot ◽

Urban Traffic ◽

System Structure ◽

Traffic Demand ◽

Urban Road ◽

Operational Mechanism ◽

Traffic Intersection ◽

Road System

In the face of increasingly congested urban traffic caused by all sorts of harm, how to solve the traffic congestion problem in the urban is becoming the major hot spot which domestic and foreign experts and scholars pay close attention to and study. This paper in a microscopic angle to analyze the problem -- urban traffic intersection congestion，not in macroscopical city planning, transportation planning, urban traffic demand to discuss. Through exploring the urban road system structure and operational mechanism, development of the automobile overpass is to solve the intersection congestion.

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Long-Range Dependence of Traffic Flow and Speed of a Motorway: Dynamics and Correlation with Historical Incidents

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2616-06 ◽

2017 ◽

Vol 2616 (1) ◽

pp. 49-57 ◽

Cited By ~ 4

Author(s):

Sai Chand ◽

Gregory Aouad ◽

Vinayak V. Dixit

Keyword(s):

Time Series ◽

Long Range ◽

Traffic Congestion ◽

Hurst Exponent ◽

Fractal Theory ◽

Urban Traffic ◽

Spatial And Temporal Variation ◽

Long Range Dependence ◽

Incident Rates ◽

Sydney Australia

Speed and flow of vehicles tend to have several effects on the dynamics of a transport system. Fluctuations of these variables can implicate congestion, can lower predictability, and may even catalyze crashes. A concept of fractal theory called the Hurst exponent—a measure of the long-range dependence (LRD) of a time series—was used to understand the fluctuations in flow and speed of a motorway in Sydney, Australia. The spatial and temporal variation of the LRD for flow ( Hflow) and speed ( Hspeed) at several monitor sites is discussed. Furthermore, the effects of number of lanes on flow and speed predictability are explored. It was observed that the flow predictability of two-lane sections was significantly lower when compared with three-lane and four-lane sections. Conversely, the speed predictability of four-lane sections was considerably higher than that of two-lane and three-lane sections. Finally, traffic congestion was defined with regard to the LRD of speed, and its correlation with historical incident rates was measured. It was ascertained that monitor sites with a historically high proportion of large Hspeed were correlated with unsafe locations. This study could lead to many applications of fractal analysis on highways and urban traffic.

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Comparative Multifractal Detrended Fluctuation Analysis of Heavy Ion Interactions at a Few GeV to a Few Hundred GeV

Advances in High Energy Physics ◽

10.1155/2016/7287803 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9 ◽

Cited By ~ 5

Author(s):

Gopa Bhoumik ◽

Argha Deb ◽

Swarnapratim Bhattacharyya ◽

Dipak Ghosh

Keyword(s):

Long Range ◽

Detrended Fluctuation Analysis ◽

Heavy Ion ◽

Projectile Energy ◽

Fluctuation Analysis ◽

Data Set ◽

Multifractal Detrended Fluctuation Analysis ◽

Range Correlation ◽

Multifractal Property ◽

Detrended Fluctuation

We have studied the multifractality of pion emission process in16O-AgBr interactions at 2.1 AGeV and 60 AGeV,12C-AgBr and 24Mg-AgBr interactions at 4.5 AGeV, and32S-AgBr interactions at 200 AGeV using Multifractal Detrended Fluctuation Analysis (MFDFA) method which is capable of extracting the actual multifractal property filtering out the average trend of fluctuation. The analysis reveals that the pseudorapidity distribution of the shower particles is multifractal in nature for all the interactions; that is, pion production mechanism has inbuilt multiscale self-similarity property. We have employed MFDFA method for randomly generated events for32S-AgBr interactions at 200 AGeV. Comparison of expt. results with those obtained from randomly generated data set reveals that the source of multifractality in our data is the presence of long range correlation. Comparing the results obtained from different interactions, it may be concluded that strength of multifractality decreases with projectile mass for the same projectile energy and for a particular projectile it increases with energy. The values of ordinary Hurst exponent suggest that there is long range correlation present in our data for all the interactions.

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Analysis of long-range transport of particulate matters in connection with air circulation over Central and Eastern part of Europe

Physics and Chemistry of the Earth Parts A/B/C ◽

10.1016/j.pce.2009.12.008 ◽

2010 ◽

Vol 35 (9-12) ◽

pp. 523-529 ◽

Cited By ~ 13

Author(s):

Sabina Stefan ◽

Cristian Necula ◽

Florinela Georgescu

Keyword(s):

Long Range ◽

Long Range Transport ◽

Particulate Matters ◽

Range Transport ◽

Air Circulation

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MULTIFRACTAL DETRENDED CROSS-CORRELATION ANALYSIS OF CHINESE STOCK MARKETS BASED ON TIME DELAY

Fractals ◽

10.1142/s0218348x11005415 ◽

2011 ◽

Vol 19 (03) ◽

pp. 329-338 ◽

Cited By ~ 24

Author(s):

XIAOJUN ZHAO ◽

PENGJIAN SHANG ◽

QIUYUE JIN

Keyword(s):

Time Delay ◽

Correlation Analysis ◽

Long Range ◽

Power Law ◽

Spectrum Analysis ◽

Cross Correlation ◽

Analysis Time ◽

Singularity Spectrum ◽

Stock Indices ◽

Cross Correlation Analysis

Multifractal detrended cross-correlation analysis (MF-DXA) has been developed to detect the long-range power-law cross-correlation of two simultaneous series. However, the synchronization of underlying data can not be guaranteed integrated by a variety of factors. We artificially imbed a time delay in considered series and study its influence on the multifractal cross-correlation analysis. Time delay is found to affect the multifractal characterization, where a larger time delay causes a weaker multifractality. We also propose an alternative modification on MF-DXA to make the process more robust. The logarithmic return and volatility of Chinese stock indices show cross-correlation scaling behavior and strong multifractality by MF-DXA as well as singularity spectrum analysis.

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