Application of nonparametric regression methods to study the relationship between NO2 concentrations and local wind direction and speed at background sites

Donnelly, Aoife; Misstear, Bruce; Broderick, Brian

doi:10.1016/j.scitotenv.2010.12.001

Cited by 50 publications

(32 citation statements)

References 12 publications

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“…High temperature in the tropical climate usually increases the quantity of biomass burning and the evaporation of materials, for example soil dust, from the surface earth [23], [24]. In contrast to temperature, wind speed showed a negative influence on the concentration of PM 10 , which means that the concentration of PM 10 tends to be higher in low wind speed areas [25]. Reference [26] stated that tall building in effect and hilly regions prevent wind speeds from being sufficiently strong to be able to transport the pollution away and will affect the concentration of the air pollutants.…”

Section: Regression Standardized Predicted Valuementioning

confidence: 99%

Airborne Particulate Matter and Meteorological Interactions during the Haze Period in Malaysia

Payus¹,

Abdullah²,

Sulaiman³

2013

IJESD

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Abstract-Haze has become a major concern as it has highly significant impacts over Malaysia by several occurrences of haze episodes throughout the country. During the haze periods, airborne particulate matter (PM 10 ) was found as the major pollutant while the other air quality parameters remained within the permissible healthy standards. Haze arise by fires from land clearing in Indonesia that builds up during the dry season affecting tourism, transportation, biodiversity, and contributing to health problems across the region. The variations of the PM 10 concentrations are due to various atmospheric processes of emissions, dilutions and accumulations that are affected by meteorological conditions. In this study, an analysis of haze status will be performed using PM 10 values from two commercial urban and industrial areas, which involved Kajang and Shah Alam, and one station that was located outside the city, which is in Kota Bahru, Kelantan, that was selected as a rural station for comparison. The aim of this study is to determine the correlation of PM 10 concentrations with the meteorological factors (namely on temperature, wind speed and ultraviolet intensity) at different monitoring stations (at different type of land use). Twelve (12) multiple regression models with interactions for each station were developed from data sets of 90; the best model was used to forecast the upcoming haze weather.Index Terms-Haze, airborne particulate matter (PM 10 ), multiple regression models with interactions, meteorological factors.

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Section: Regression Standardized Predicted Valuementioning

confidence: 99%

Airborne Particulate Matter and Meteorological Interactions during the Haze Period in Malaysia

Payus¹,

Abdullah²,

Sulaiman³

2013

IJESD

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“…Henry et al (2002) used nonparametric regression with a Gaussian kernel to establish the relationship between the concentration of air pollutants and wind direction. This method is extended to CO 2 daily evolution by the expression provided by Donnelly et al (2011) …”

Section: The Kernel Smoothing Proceduresmentioning

confidence: 99%

Daily patterns of CO2 in the lower atmosphere of a rural site

Pérez

Sánchez

García

et al. 2014

Theor Appl Climatol

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This paper investigates patterns of daily evolutions of CO 2 in the lower atmosphere at a rural site over 2 years. The first part is devoted to observation analysis using a clustering procedure. However, direct application of the average-linkage method yielded undesirable results. In order to improve this procedure, data were previously processed using three smoothing procedures: the kernel smoothing method, the elliptical procedure, and the second-order cylindrical model. These procedures successfully revealed that clusters were based on daily concentration and range. However, the unequal distribution of frequencies in the clusters proved to be a noticeable disadvantage. Four alternative and simpler schemes for grouping observations were proposed in the second part of this paper. The first, comprising groups following fixed values of daily range and mean concentration, provided a sharp contrast between spring, with a marked daily cycle linked to the biological peak, and summer with a smooth daily cycle and low concentration when the biological minimum was reached. The second scheme is based on isopleth analysis and considers observation groups of similar frequencies following an increasing order of mean concentration and daily range. As a result, seasonal evolution was less marked. Straight lines were the borders for groups in the third scheme, which was similar and simpler than the second. The final scheme divided observations by means of equations of daily range as a quadratic function of daily concentration. The groups formed may be linked to seasons, with the group prevailing in summer presenting a noticeable daily range.

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“…NO 2 and other nitrogen oxides are also precursor of ozone and particulate matter, whose effects on human health and the environment are well documented. Concentrations of NO 2 have been analysed extensively in many urban areas (Carslaw, 2005;Grice et al, 2009;Roberts-Semple et al, 2012) as well as in background sites (Donnelly et al, 2011;Menezes et al, 2016). Moreover, these studies acknowledge that meteorological conditions influence NO 2 levels (Shi and Harrison, 1997;Donnelly et al, 2011;Russo and Soares, 2014).…”

Section: Introductionmentioning

confidence: 99%

Modelling spatio-temporal data with multiple seasonalities: TheNO2Portuguese case

2017

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a b s t r a c tThis study aims at characterizing the spatial and temporal dynamics of spatio-temporal data sets, characterized by high resolution in the temporal dimension which are becoming the norm rather than the exception in many application areas, namely environmental modelling. In particular, air pollution data, such as NO 2 concentration levels, often incorporate also multiple recurring patterns in time imposed by social habits, anthropogenic activities and meteorological conditions. A two-stage modelling approach is proposed which combined with a block bootstrap procedure correctly assesses uncertainty in parameters estimates and produces reliable confidence regions for the space-time phenomenon under study. The methodology provides a model that is satisfactory in terms of goodness of fit, interpretability, parsimony, prediction and forecasting capability and computational costs. The proposed framework is potentially useful for scenario drawing in many areas, including assessment of environmental impact and environmental policies, and in a myriad applications to other research fields.

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Application of nonparametric regression methods to study the relationship between NO2 concentrations and local wind direction and speed at background sites

Cited by 50 publications

References 12 publications

Airborne Particulate Matter and Meteorological Interactions during the Haze Period in Malaysia

Airborne Particulate Matter and Meteorological Interactions during the Haze Period in Malaysia

Daily patterns of CO2 in the lower atmosphere of a rural site

Modelling spatio-temporal data with multiple seasonalities: TheNO2Portuguese case

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