On Trend Association Analysis of Time Series of Atmospheric Pollutants and Meteorological Variables in Mexico City Metropolitan Area

Abstract

The paper studies trend associations between atmospheric pollutants and meteorological variables time series of Mexico City Metropolitan Area (MCMA) by applying the Moving Approximation Transform (MAP). This recently introduced technique measures and visualizes associations of the dynamics between different time series in the form of an association network. The paper studies associations between 5 atmospheric pollutants (SO 2 , O 3, NO 2 , NOx and PM 2.5) and 7 meteorological variables (mean wind velocity, minimum, average and maximum values of both temperature and relative humidity) measured daily during one year in three meteorological stations located in different zones of MCMA. These associations were studied for 4 seasons characterized by different meteorological conditions. For considered stations atmospheric pollutants and meteorological variables for different seasons positive and negative associations have been found and explained.

Constructing Time Series Shape Association Measures: Minkowski Distance and Data Standardization

“…An influence of standardization methods on results of cluster analysis has been studied in several works [18,19,[25][26][27] but sometimes the conclusions of such analysis are contradictory. Description and applications of local trend association measures based on moving approximation transform can be found in [6,3,5]. In comparison with similarity measures the association measures give more powerful instrument for analysis of possible relationships between time series.…”

“…is usually based on simulation and modeling of system dynamics but often such modeling is cost prohibitive or cannot give adequate results due to systems complexity or absence of information necessary for models. In such cases a data driven approach to analysis of complex systems including analysis of relationships between dynamics of system elements can be helpful and complementary to conventional modeling [3,5,6,8,17,21,22].…”

“…Such relationships can exist between dynamics of prices and sell volumes, between growth patterns of competitive companies, between well production data in reservoirs, between wind velocity and air pollution concentration etc. [3,5,6,8,17]. An analysis of direct and inverse relationships between variables mainly based on Pearson's correlation coefficient is widely used in almost all applications of statistics: in medicine, biology, economics, physics, social sciences etc.…”

“…Recently time series shape association measure based on moving approximation transform (MAT) has been introduced and studied in [6]. This measure and its modifications have been used for analysis of possible communications between wells in reservoirs [5] and for analysis associations between atmospheric pollutants and meteorological variables [3]. In [9] a system of axioms defining time series shape association measures has been proposed.…”

Trends and Extremes in Time Series Based on Fuzzy Logic

“…It should be noted that regression derivatives were used earlier, in a simpler form than in this work, for the classification of time series, which made it possible to determine groups of series similar in morphology using various similarity measures [20][21][22][23][24]. In such problems, the choice of similarity measure affects the classification accuracy to a greater extent than the choice of classification method.…”