Statistical models for the prediction of respirable suspended particulate matter in urban cities

Goyal, P.; Chan, Andy; Jaiswal, Neeru

doi:10.1016/j.atmosenv.2005.11.041

Cited by 134 publications

(64 citation statements)

References 14 publications

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“…Numerous reports describe model results on different air quality variables and different locations from multiple linear regression (MLR) analysis (Hubbard and Cobourn, 1998;Barrero et al, 2006;Stadlober et al, 2008), nonlinear multiple regressions (Cobourn, 2007), artificial neural networks (ANN) (Gardner and Dorling, 1998;Nunnari et al, 1998;Reich et al, 1999;Benvenuto and Marani, 2000;Perez et al, 2000;Perez, 2001;Kukkonen et al, 2003;Hooyberghs et al, 2005;Papanastasiou et al, 2007), generalized additive models and fuzzy-logic-based models (Cobourn et al, 2000). Other authors compared several methods on a single dataset (from the same measurement site) or combined various approaches in order to improve the specific air pollutant forecast (Agirre-Basurko et al, 2006;Goyal et al, 2006;AlAlawi et al, 2008). Comrie (1997) compared the potential of traditional regression and neural networks to forecast ozone pollution under different climate and ozone regimes.…”

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confidence: 99%

The impact of weather and atmospheric circulation on O3 and PM10 levels at a rural mid-latitude site

et al. 2009

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Abstract. In spite of the strict EU regulations, concentrations of surface ozone and PM 10 often exceed the pollution standards for the Netherlands and Europe. Their concentrations are controlled by (precursor) emissions, social and economic developments and a complex combination of meteorological actors. This study tackles the latter, and provides insight in the meteorological processes that play a role in O 3 and PM 10 levels in rural mid-latitudes sites in the Netherlands. The relations between meteorological actors and air quality are studied on a local scale based on observations from four rural sites and are determined by a comprehensive correlation analysis and a multiple regression (MLR) analysis in 2 modes, with and without air quality variables as predictors. Furthermore, the objective Lamb Weather Type approach is used to assess the influence of the large-scale circulation on air quality. Keeping in mind its future use in downscaling future climate scenarios for air quality purposes, special emphasis is given to an appropriate selection of the regressor variables readily available from operational meteorological forecasts or AOGCMs (Atmosphere-Ocean coupled General Circulation Models). The regression models perform satisfactory, especially for O 3 , with an R 2 of 57.0% and 25.0% for PM 10 . Including previous day air quality information increases significantly the models performance by 15% (O 3 ) and 18% (PM 10 ). The Lamb weather types show a seasonal distinct pattern for high (low) episodes of average O 3 and PM 10 concentrations, and these are clear related with the meteorology-air quality correlation analysis. Although using Correspondence to: M. Demuzere (matthias.demuzere@ees.kuleuven.be) a circulation type approach can provide important additional physical relations forward, our analysis reveals the circulation method is limited in terms of short-term air quality forecast for both O 3 and PM 10 (R 2 between 0.12 and 23%). In summary, it is concluded that the use of a regression model is more promising for short-term downscaling from climate scenarios than the use of a weather type classification approach.

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confidence: 99%

The impact of weather and atmospheric circulation on O3 and PM10 levels at a rural mid-latitude site

et al. 2009

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“…Nevertheless, there are also cases in which the ARIMA models worked better [35], and the importance of selecting an appropriate ANNs architecture to solve the corresponding problem is shown [36]. As an alternative, it has been proposed to combine models deploying different methods in order to improve the time series forecasting, commonly obtaining better results than in isolated models [37]; [38]; [39]; [40]; [41]; [42]. Some of these hybrid models have been directly applied to the problem of forecasting spare-parts demand in hybrid industries, combining linear regression and ANNs and working with small sample sizes [43].…”

Section: Forecasting With the Arima And Anns Modelsmentioning

confidence: 99%

Automobile spare-parts forecasting: A comparative study of time series methods

Vargas¹,

Cortés²

2017

Int. J. Automot. Mech. Eng.

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In Mexico, the automotive industry is considered to be strategic in the industrial and economic development of the country because it generates production, employment and foreign exchange. Good demand forecasts are needed for better manufacturing management. The time series modelling tools applied to the monthly demand forecasting of automobile spare parts in Mexico are assessed, for the case of a transnational enterprise, considering affordability. The classic methods of moving averages, final value and exponential smoothing, the prestigious autoregressive integrated models of moving averages (ARIMA), the rarely implemented artificial neural networks (ANNs) and the very little explored ARIMA-ANNs hybrid models are compared. A good performance of the models involving ANNs is observed, but they were not as steady as the ARIMA models in the post-sample periods. The mean absolute percentage error (MAPE) was reduced from an original 57% to 32.65%. The obtained results could help demonstrate the importance of improving industrial forecasting methodologies for better planning.

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“…For the best performance of the model, residuals should be random i.e. they should follo w the normal d istribution with zero mean and constant variance [35]. Figure 15 indicates histograms of the residuals of mixing height model.…”

Section: Rainfallmentioning

confidence: 99%

Studies on Meteorological Parameters and Mixing Height in Gold Mining Area

Roy¹,

Gupta²,

Singh³

2012

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Gold mining at Ko lar Go ld Fields is closed but some industries in this area are in operation and some may like to be established. Data on at mospheric and meteorological parameters were generated using SODA R (Sound Detection and Ranging) and auto matic weather station in different seasons. Over 2000 sodar echograms were recorded and classified into six categories like rising layer, thermal plu me (free), ground based layer (spiky top), ground based layer (flat top), ground based mu ltiple layers and dot echo structures. Using echograms, unstable period was determined to know the d iluting capability of at mosphere for pollutants in the seasons. The highest duration of mixing heights revealed the period of h ighest dispersion. Based on the sodar echograms and mixing height, stability classes for the d ifferent times of the day were evaluated, which can be used for the estimation of dispersion coefficients. Influence of wind speed, wind direction, temperature, hu midity, solar rad iation and rainfall on mixing heights was studied. Statistical model was developed for the prediction of mixing height. Model adequacy was checked using F-statistics, normal d istribution curve and correlation between predicted and measured values of mixing heights.

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Statistical models for the prediction of respirable suspended particulate matter in urban cities

Cited by 134 publications

References 14 publications

The impact of weather and atmospheric circulation on O<sub>3</sub> and PM<sub>10</sub> levels at a rural mid-latitude site

The impact of weather and atmospheric circulation on O<sub>3</sub> and PM<sub>10</sub> levels at a rural mid-latitude site

Automobile spare-parts forecasting: A comparative study of time series methods

Studies on Meteorological Parameters and Mixing Height in Gold Mining Area

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Statistical models for the prediction of respirable suspended particulate matter in urban cities

Cited by 134 publications

References 14 publications

The impact of weather and atmospheric circulation on O&lt;sub&gt;3&lt;/sub&gt; and PM&lt;sub&gt;10&lt;/sub&gt; levels at a rural mid-latitude site

The impact of weather and atmospheric circulation on O&lt;sub&gt;3&lt;/sub&gt; and PM&lt;sub&gt;10&lt;/sub&gt; levels at a rural mid-latitude site

Automobile spare-parts forecasting: A comparative study of time series methods

Studies on Meteorological Parameters and Mixing Height in Gold Mining Area

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Product

Resources

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The impact of weather and atmospheric circulation on O<sub>3</sub> and PM<sub>10</sub> levels at a rural mid-latitude site

The impact of weather and atmospheric circulation on O<sub>3</sub> and PM<sub>10</sub> levels at a rural mid-latitude site