Spectral analysis of vehicle pollutants at traffic intersection in Hong Kong

He, Hong-di; Lu, Wen-Hsiang

doi:10.1007/s00477-012-0560-6

Cited by 9 publications

(2 citation statements)

References 20 publications

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“…The records over time of particulate matter (PM), sulfur dioxide (SO 2 ) and CO, among other atmospheric pollutants, present some interesting features to investigate by time series tools, such as stationarity and nonstationarity (local trend, unit root), periodicity, asymmetry, weak and strong (long-memory) dependence. For example, He and Lu (2012) have studied the periodic variation of the concentrations of CO, carbon dioxide (CO 2 ) and PM at a typical traffic intersection in Hong Kong. In addition, the pollution series may present observations with high levels of concentrations producing sample densities with heavy tails.…”

Section: Introductionmentioning

confidence: 99%

M-regression spectral estimator for periodic ARMA models. An empirical investigation

Sarnaglia

Reisen

Bondon

et al. 2021

Stoch Environ Res Risk Assess

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The M -regression estimator has recently been widely used to build spectral estimators in time series models. In this paper, we extend this approach when the data follow a periodic autoregressive moving average (PARMA) process. We introduce an estimator of the parameters based on the classical Whittle estimator. The finite sample size performances of the proposed estimator are analyzed under the scenarios of PARMA processes with and without additive outliers (AO). Under the non-contaminated scenario, our estimator and the maximum Gaussian and Whittle likelihood estimators have similar behaviors. However, in the contaminated case, the two last estimators are severely biased, while the proposed estimator is robust. As a real data application, carbon monoxide (CO) concentrations are analyzed. A PARMA model is fitted and the data are forecasted with the model.

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Section: Introductionmentioning

confidence: 99%

M-regression spectral estimator for periodic ARMA models. An empirical investigation

Sarnaglia

Reisen

Bondon

et al. 2021

Stoch Environ Res Risk Assess

View full text Add to dashboard Cite

show abstract

“…Petroleum-fueled motor vehicles release regulated air pollutants such as black carbon (BC), carbon monoxide (CO), nitric oxides (NO x ), and particulate matter (PM) [1, 2, 3, 4, 5]. The health impact of these mobile source air pollutants on human populations has been reflected with increasing observations on elevated adverse health effects among near-road residents [6, 7, 8, 9, 10, 11, 12].…”

Section: Introductionmentioning

confidence: 99%

A meta-analysis of selected near-road air pollutants based on concentration decay rates

Liu

Chen

Xue

2019

Heliyon

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Traffic-related air pollution has been associated with various health risks for human populations living near roadways. Understanding the relationship between traffic density and dispersion of vehicle-released air pollutants is important for assessing human exposure to near-road air pollutants. We performed a literature survey targeting publications containing measurement data of traffic-related air pollutants near roads with distance information on their concentration distribution. Concentration decay rates over down-wind distance away from major roads were calculated for black carbon (BC), carbon monoxide (CO) and nitrogen oxides (NO 2 or NO x ) and meta-data analysis on these rates was performed. These analyses showed metadata-based exponential decay rates of 0.0026, 0.0019, 0.0004, and 0.0027 m −1 for BC, CO, NO 2 and NOx, respectively. Using these measurement data-based decay rates, concentrations for BC, CO, NO 2 and NO x over various near-road distances were predicted. These results are useful for enhancing exposure modeling and thus more reliably assessing the health risk of exposure to near road air pollution.

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Statistical analysis of a combination of objective and subjective environmental noise data using factor analysis and multinomial logistic regression

Engel

Segundo

Zannin

2013

Stoch Environ Res Risk Assess

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Spectral analysis of vehicle pollutants at traffic intersection in Hong Kong

Cited by 9 publications

References 20 publications

M-regression spectral estimator for periodic ARMA models. An empirical investigation

M-regression spectral estimator for periodic ARMA models. An empirical investigation

A meta-analysis of selected near-road air pollutants based on concentration decay rates

Statistical analysis of a combination of objective and subjective environmental noise data using factor analysis and multinomial logistic regression

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