On the nature of air pollution dynamics in Mexico City—I. Nonlinear analysis

Raga, G. B.; Moyne, Luis Le

doi:10.1016/1352-2310(96)00122-7

Cited by 58 publications

(23 citation statements)

References 7 publications

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“…Lanfredi and Macchiato (1997) have found that random behavior dominates over the chaotic behavior in time series of pollutants like NO x , O 3 and CO. Raga and Le Moyne (1996) have applied nonlinear analysis to O 3 , NO 2 , SO 2 and CO time series obtained from 13 monitoring stations in Mexico City, finding low-dimensional chaotic behavior in those time. Related to total ozone concentration, Chattopadhyay and Chattopadhyay (2008) have found the existence of chaotic behavior in Arosa, using the correlation dimension method.…”

Section: Chaotic Behavior In Air Pollution Time Seriesmentioning

confidence: 99%

A Study of the Dynamic Behaviour of Fine Particulate Matter in Santiago, Chile

Calderón

Pérez

2015

Aerosol Air Qual. Res.

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We present here a study about the limitations found when trying to develop an accurate atmospheric particulate matter forecasting model based on real data, and evidence that the time series of fine particulate matter concentration exhibit deterministic chaotic behavior. We have calculated the Lyapunov exponents of PM 2.5 time series obtained from measurements from four monitoring stations located in the city of Santiago, Chile, in recent years. Values obtained for the largest Lyapunov exponents turned out to be positive and ranging between 0.3 and 0.5 which, according to the theory of chaos, is a condition for the presence of deterministic chaos and random behavior in time series. Given the shape of decay of autocorrelation functions and values of correlation dimension and Hurst exponents, random behavior can be discarded: we therefore conclude that the series are chaotic and very sensitive to initial conditions. The study presented here can be replicated in other mid-sized cities that present similar situations to the city of Santiago, where complexity of topography, meteorology and seasonal trends favor the generation of high concentration episodes of atmospheric particulate matter and where a reliable air quality forecasting model may be important for environmental management.

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Section: Chaotic Behavior In Air Pollution Time Seriesmentioning

confidence: 99%

A Study of the Dynamic Behaviour of Fine Particulate Matter in Santiago, Chile

Calderón

Pérez

2015

Aerosol Air Qual. Res.

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“…Raga and Le Moyne (1996) analyzed basin-wide monitoring data and identified a pattern of transport from the north-west to the south-east using nonlinear analysis. Raga et al (1999) identified evidence of the upslope flow on the southern edge of the basin by looking at measurements of primary and secondary pollutants.…”

Section: Introductionmentioning

confidence: 99%

Mexico City basin wind circulation during the MCMA-2003 field campaign

et al. 2005

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Abstract. MCMA-2003 was a major field campaign investigating the atmospheric chemistry of the Mexico City Metropolitan Area (MCMA) in April of 2003. This paper describes the wind circulation patterns during the campaign both within the Mexico City basin and on the regional scale. ''Time roses'' are introduced to concisely analyze the diurnal wind patterns. Three episode types were identified that explain the conditions encountered: ''O3-South'', ''Cold Surge'' and ''O3-North''. These can be diagnosed from a combination of synoptic and basin observations based on whether the day was predominantly cloudy, or whether the O3 peak was in the north or south of the basin. O3-South days have weak synoptic forcing due to an anti-cyclone over the eastern Pacific. Strong solar heating leads to northerly flows in the basin and an evening shift due to a gap flow from the south-east. Peak ozone concentrations are in the convergence zone in the south of the city. Cold Surge days are associated with ''El Norte'' events, with strong surface northerlies bringing cold moist air and rain. Stable conditions lead to high concentrations of primary pollutants and peak ozone in the city center. O3-North days occur when the sub-tropical jet is closer to Mexico City. With strong westerlies aloft, the circulation pattern is the same as O3-South days except for a wind shift in the mid-afternoon leading to ozone peaks in the north of the city. This classification is proposed as a means of understanding pollutant transport in the Mexico City basin and as a basis for future meteorological and chemical analysis. Furthermore, model evaluation and design of policy recommendations will need to take into account the three episode types.

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“…It relates to many a factor, such as the movement and transformation of air pollutants, pollutants emission and climate condition (Li and Tang 1998). Previous studies indicate that some air pollutants exhibit nonlinearities, such as surface ozone (Li et al 1994;Raga and Le Moyne 1996), carbon dioxide (CO 2 ) emissions (Tao et al 2010;Tunç et al 2009;Liu et al 2007), TSP and PM 10 concentration (Saarikoski et al 2007;Slini et al 2006), just to name a few examples. Some studies focus on the methods and models for air quality assessment and the prediction of daily API time series.…”

Section: Introductionmentioning

confidence: 99%

A chaotic analysis on air pollution index change over past 10 years in Lanzhou, northwest China

Huang

Liu

et al. 2011

Stoch Environ Res Risk Assess

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In terms of the chaos theory, the phase-spacereconstruction method has been employed to describe the multi-dimensional phase space for the time series of air pollution index (API) during the past 10 years in Lanzhou, northwest China. The mutual information and Cao method were used to determine the reconstruction parameters, and the characteristic quantities including the Lyapunov exponent and the correlation dimension were calculated respectively. As a result, the correlation dimensions were fractioned, and the maximum Lyapunov exponent (k 1 ) [ 0. It shows that these presented the obvious chaotic characteristics that resulted from the evolution of non-linear chaotic dynamic system in the time series of air pollution index over the past 10 years. In the meanwhile, three or even four main dynamic variables were discussed here that could effectively interpret the changes of air pollution index time series and their causes. Some reasonable preventive countermeasures were thus put forward. These findings might provide a scientific basis for probing further into the regional complexity and evolution of the time series of air pollution index.

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On the nature of air pollution dynamics in Mexico City—I. Nonlinear analysis

Cited by 58 publications

References 7 publications

A Study of the Dynamic Behaviour of Fine Particulate Matter in Santiago, Chile

A Study of the Dynamic Behaviour of Fine Particulate Matter in Santiago, Chile

Mexico City basin wind circulation during the MCMA-2003 field campaign

A chaotic analysis on air pollution index change over past 10 years in Lanzhou, northwest China

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