Statistical and diagnostic evaluation of a new-generation urban dispersion modelling system against an extensive dataset in the Helsinki area

We have developed a modelling system for predicting the traffic volumes, emissions from stationary and vehicular sources, and atmospheric dispersion of pollution in an urban area. This paper describes a comparison of the NO_x and NO₂ concentrations predicted using this modelling system with the results of an urban air quality monitoring network. We performed a statistical analysis to determine the agreement between predicted and measured hourly time series of concentrations at four permanently located and three mobile monitoring stations in the Helsinki Metropolitan Area in 1996–1997 (at a total of ten urban and suburban measurement locations). At the stations considered, the so-called index of agreement values of the predicted and measured time series of the NO₂ concentrations vary between 0.65 and 0.82, while the fractional bias values range from −0.29 to +0.26. In comparison with corresponding results presented in the literature, the agreement between the measured and predicted datasets is good, as indicated by these statistical parameters. The seasonal variations of the NO₂ concentrations were analysed in terms of the relevant meteorological parameters. We also analysed the difference between model predictions and measured data diagnostically, in terms of meteorological parameters, including wind speed and direction (the latter separately for two wind speed classes), atmospheric stability and ambient temperature, at two monitoring stations in central Helsinki. The modelling system tends to overpredict the measured NO₂ concentrations both at the highest (u⩾6 m s⁻¹) and at the lowest wind speeds (u<2 m s⁻¹). For higher wind speeds, the modelling system overpredicts the measured NO₂ concentrations in certain wind direction intervals; specific ranges were found for both monitoring stations considered. The modelling system tends to underpredict the measured concentrations in convective atmospheric conditions, and overpredict in stable conditions. The possible physico-chemical reasons for these differences are discussed.     

Spatial variation of airborne pollutant concentrations in Brisbane,Australia and its potential impact on population exposure assessment

Spread of air pollution sources and non-uniform mixing conditions in urban or regional air sheds often result in spatial variation of pollutant concentrations over different parts of the air sheds. A comprehensive understanding of this variation of concentrations is imperative for informed planning, monitoring and assessment in a range of critical areas including assessment of monitoring network efficiency or assessment of population exposure variation as a function of the location in the city. The aims of this work were to study the citywide variability of pollutants as measured by “urban background” type monitoring stations and to interpret the results in relation to the applicability of the data to population exposure assessments and the network efficiency. A comparison between ambient concentrations of NO_x, ozone and PM₁₀ was made for three stations in the Brisbane air shed network. The best correlated between the three stations were ozone concentrations followed by NO_x concentration, with the worst correlations observed for PM₁₀. With a few exceptions correlations of all pollutants between the stations were statistically significant. Marginally better were the correlations for the lower concentrations of pollutants that represent urban background, over the correlations for higher concentrations, representing peak values. Implications of these findings on application of the monitoring data to air-quality management, as well as the need for further investigations has been discussed.     

A measurement campaign in a street canyon in Helsinki and comparison of results with predictions of the OSPM model

In 1997, a measuring campaign was conducted in a street canyon (Runeberg St.) in Helsinki. Hourly mean concentrations of CO, NO_x, NO₂ and O₃ were measured at street and roof levels, the latter in order to determine the urban background concentrations. The relevant hourly meteorological parameters were measured at roof level; these included wind speed and direction, temperature and solar radiation. Hourly street level measurements and on-site electronic traffic counts were conducted throughout the whole of 1997; roof level measurements were conducted for approximately two months, from 3 March to 30 April in 1997. CO and NO_x emissions from traffic were computed using measured hourly traffic volumes and evaluated emission factors. The Operational Street Pollution Model (OSPM) was used to calculate the street concentrations and the results were compared with the measurements. The overall agreement between measured and predicted concentrations was good for CO and NO_x (fractional bias were −4.2 and +4.5%, respectively), but the model overpredicted the measured NO₂ concentrations (fractional bias was +22%). The agreement between the measured and predicted values was also analysed in terms of its dependence on wind speed and direction; the latter analysis was performed separately for two categories of wind velocity. The model qualitatively reproduces the observed behaviour very well. The database, which contains all measured and predicted data, is available for further testing of other street canyon dispersion models. The dataset contains a larger proportion of low wind speed cases, compared with other available street canyon measurement datasets.     

Temporal variations of atmospheric aerosol in four European urban areas

Purpose

The concentrations of PM₁₀ mass, PM_2.5 mass and particle number were continuously measured for 18 months in urban background locations across Europe to determine the spatial and temporal variability of particulate matter.

Methods

Daily PM₁₀ and PM_2.5 samples were continuously collected from October 2002 to April 2004 in background areas in Helsinki, Athens, Amsterdam and Birmingham. Particle mass was determined using analytical microbalances with precision of 1 ??g. Pre- and post-reflectance measurements were taken using smoke-stain reflectometers. One-minute measurements of particle number were obtained using condensation particle counters.

Results

The 18-month mean PM₁₀ and PM_2.5 mass concentrations ranged from 15.4 ??g/m³ in Helsinki to 56.7 ??g/m³ in Athens and from 9.0 ??g/m³ in Helsinki to 25.0 ??g/m³ in Athens, respectively. Particle number concentrations ranged from 10,091 part/cm³ in Helsinki to 24,180 part/cm³ in Athens with highest levels being measured in winter. Fine particles accounted for more than 60% of PM₁₀ with the exception of Athens where PM_2.5 comprised 43% of PM₁₀. Higher PM mass and number concentrations were measured in winter as compared to summer in all urban areas at a significance level p?Conclusions Significant quantitative and qualitative differences for particle mass across the four urban areas in Europe were observed. These were due to strong local and regional characteristics of particulate pollution sources which contribute to the heterogeneity of health responses. In addition, these findings also bear on the ability of different countries to comply with existing directives and the effectiveness of mitigation policies.     

Controls on hourly variations in urban background air pollutant concentrations

Average 21st century concentrations of urban air pollutants linked to cardiorespiratory disease are not declining, and commonly exceed legal limits. Even below such limits, health effects are being observed and may be related to transient daytime peaks in pollutant concentrations. With this in mind, we analyse >52,000 hourly urban background readings of PM₁₀ and pollutant gases throughout 2007 at a European town with legal annual average concentrations of common pollutants, but with a documented air pollution-related cardiorespiratory health problem, and demonstrate the hourly variations in PM₁₀, SO₂, NO_x, CO and O₃. Back-trajectory analysis was applied to track the arrival of exotic PM₁₀ intrusions, the main controls on air pollutants were identified, and the typical hourly pattern on ambient concentrations during 2007 was profiled. Emphasis was placed on “worst case” data (>90th percentile), when health effects are likely to be greatest. The data show marked daytime variations in pollutants result from rush-hour traffic-related pollution spikes, midday industrial SO₂ maxima, and afternoon O₃ peaks. African dust intrusions enhance PM₁₀ levels at whatever hour, whereas European PM incursions produce pronounced evening peaks due to their transport direction (across an industrial traffic corridor). Transient peak profiling moves us closer to the reality of personal outdoor exposure to inhalable pollutants in a given urban area. We argue that such an approach to monitoring data potentially offers more to air pollution health effect studies than using only 24 h or annual averages.     

Application of a Lagrangian particle model to assess the impact of harbour,industrial and urban activities on air quality in the Taranto area,Italy

This paper evaluates the relative impact on air quality of harbour emissions, with respect to other emission sources located in the same area. The impact assessment study was conducted in the city of Taranto, Italy. This area was considered as representative of a typical Mediterranean harbour region, where shipping, industries and urban activities co-exist at a short distance, producing an ideal case to study the interaction among these different sources. Chemical and meteorological field campaigns were carried out to provide data to this study. An emission inventory has been developed taking into account industrial sources, traffic, domestic heating, fugitive and harbour emissions. A 3D Lagrangian particle dispersion model (SPRAY) has then been applied to the study area using reconstructed meteorological fields calculated by the diagnostic meteorological model MINERVE. 3D short term hourly concentrations have been computed for both all and specific sources. Industrial activities are found to be the main contributor to SO₂. Industry and traffic emissions are mainly responsible for NO_x simulated concentrations. CO concentrations are found to be mainly related to traffic emissions, while primary PM₁₀ simulated concentrations tend to be linked to industrial and fugitive emissions. Contributions of harbour activities to the seasonal average concentrations of SO₂ and NO_x are predicted to be up to 5 and 30 μg m⁻³, respectively to be compared to a overall peak values of 60 μg m⁻³ for SO₂ and 70 μg m⁻³ for NO_x. At selected urban monitoring stations, SO₂ and NO_x average source contributions are predicted to be both of about 9% from harbour activities, while 87% and 41% respectively of total concentrations are predicted to be of industrial origin.     

Assessment of ambient air quality in the port of Naples

Two experimental monitoring campaigns were carried out in 2012 to investigate the air quality in the port of Naples, the most important in southern Italy for traffic of passengers and one of the most important for goods. Therefore, it represents an important air pollution source located close to the city of Naples. The concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and BTEX (benzene, toluene, ethylbenzene, and xylenes) in the air were measured at 15 points inside the Naples port area through the use of passive samplers. In addition, a mobile laboratory was positioned in a fixed point inside the port area to measure continuous concentration of pollutants together with particulate matter, ambient parameters, and wind direction and intensity. The pollution levels monitored were compared with those observed in the urban area of Naples and in other Mediterranean ports. Even though the observation time was limited, measured concentrations were also compared with limit values established by European legislation. All the measured pollutants were below the limits with the exception of nitrogen dioxide: its average concentration during the exposition time exceeded the yearly limit value. A spatial analysis of data, according to the measured wind direction and intensity, provided information about the effects that ship emissions have on ambient air quality in the port area. The main evidence indicates that ship emissions influence sulfur dioxide concentration more than any other pollutants analyzed.

Implications: Two monitoring campaigns were carried out to measure BTEX, SO₂, NO₂, and PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) air concentrations in the port of Naples. NO₂ hourly average and PM₁₀ daily average comply with European legislative standards. Spatial variation of pollutants long the axis corresponding to the prevailing wind direction seems to indicate a certain influence of ship emissions for SO₂. For NO₂ and PM₁₀, a correlation between concentrations in the harbor and those measured by the air quality monitoring stations sited in the urban area of Naples was observed, indicating a possible contribution of the near road traffic to the air pollution in the port of Naples.     

Analysis of air quality within a street canyon using statistical and dispersion modelling techniques

The dispersion model, ADMS-Urban, alongside the statistical modelling technique, generalized additive modelling, have been used to predict hourly NO_x and nitrogen dioxide (NO₂) concentrations at a busy street canyon location and the results compared with measurements. Generalized additive models (GAMs) were constructed for NO₂ and NO_x concentrations using input data required to run ADMS-Urban. Bivariate polar plots have been produced from the wind flow (speed and direction) and pollution data (measured and predicted concentrations) to provide further information regarding the complex wind-pollutant interactions in an urban street canyon. The predictions made with the GAMs show excellent agreement with measured concentrations at this location, reproducing both the magnitude of NO_x and NO₂ concentrations and also the wind speed-wind direction dependence of pollutant sources within the canyon. However, the predictions made with ADMS-Urban under-estimated the measured NO_x by 11% and NO₂ by 21% and there are clear differences in the bivariate polar plots. Several sensitivity tests were carried out with ADMS-Urban in an attempt to produce predictions in closer agreement to those measured at Gillygate. Increasing the primary NO₂ fraction in ADMS-Urban (from 10% to 20%) had a considerable effect on the predictions made with this model, increasing NO₂ predictions by ∼20%. However, the bivariate plots still showed major differences to those of the measurements. This work illustrates that generalized additive modelling is a useful tool for investigating complex wind-pollutant interactions within a street canyon.     

Interpretation of air quality in relation to monitoring station's surroundings

This study explores the appropriateness of the locality of air monitoring stations which are meant to indicate air quality in the area. Daily variations in NO₂ and PM₁₀ concentrations at 14 monitoring stations in Hong Kong are examined. The daily variations in NO₂ at a number of background monitoring stations exhibit patterns similar to variations in traffic volume while variations in PM₁₀ concentration exhibit less discernible pattern. Principal component analysis (PCA) and cluster analysis (CA) are applied to analyse NO₂ and PM₁₀ measurements between January 2001 and December 2005. The results show that NO₂ concentrations at background stations within the urban area are highly influenced by vehicle emissions. The effect vehicle emission has on NO₂ at stations within new towns is smaller. CA results also show that variations in PM₁₀ concentrations are distinguished by the area the station is located in. PCA results show that there are two principal components (PC's) associated with variations in roadside concentration of PM₁₀. The strong influence of roadside emissions towards concentrations of NO₂ and PM₁₀ at a number of urban background stations may be due to their close proximity to busy roadways and the high density of surrounding tall buildings, which creates an enclosure that hinders dispersion of roadside emissions and results in air pollution behaviour that reflects variation in traffic.     

Multi-year hourly PM2.5 carbon measurements in New York: Diurnal,day of week and seasonal patterns

Multi-year hourly measurements of PM_2.5 elemental carbon (EC) and organic carbon (OC) from a site in the South Bronx, New York were used to examine diurnal, day of week and seasonal patterns. The hourly carbon measurements also provided temporally resolved information on sporadic EC spikes observed predominantly in winter. Furthermore, hourly EC and OC data were used to provide information on secondary organic aerosol formation. Average monthly EC concentrations ranged from 0.5 to 1.4 μg m^?3 with peak hourly values of several μg m^?3 typically observed from November to March. Mean EC concentrations were lower on weekends (approximately 27% lower on Saturday and 38% lower on Sunday) than on weekdays (Monday to Friday). The weekday/weekend difference was more pronounced during summer months and less noticeable during winter. Throughout the year EC exhibited a similar diurnal pattern to NO_x showing a pronounced peak during the morning commute period (7–10 AM EST). These patterns suggest that EC was impacted by local mobile emissions and in addition by emissions from space heating sources during winter months. Although EC was highly correlated with black carbon (BC) there was a pronounced seasonal BC/EC gradient with summer BC concentrations approximately a factor of 2 higher than EC. Average monthly OC concentrations ranged from 1.0 to 4.1 μg m^?3 with maximum hourly concentrations of 7–11 μg m^?3 predominantly in summer or winter months. OC concentrations generally correlated with PM_2.5 total mass and aerosol sulfate and with NO_x during winter months. OC showed no particular day of week pattern. The OC diurnal pattern was typically different than EC except in winter when OC tracked EC and NO_x indicating local primary emissions contributed significantly to OC during winter at the urban location. On average secondary organic aerosol was estimated to account for 40–50% of OC during winter and up to 63–73% during summer months.     

Analysis of the air pollution climate at a central urban background site

Measurements of air pollutants from a background site in central London are analysed. These comprise hourly data for CO, NO, NO₂, O₃, SO₂ and PM₁₀ from 1996 to 2008 and particle number count from 2001 to 2008. The data are analysed in terms of long-term trends, annual, weekly and diurnal cycles, and autocorrelation and cross-correlation functions. CO, NO and NO₂ show a typical traffic-associated pattern with two daily peaks and lesser concentrations at the weekend. Particle number count and PM₁₀ show a similar cycle, but with smaller amplitude. Ozone has an annual cycle with a maximum in May, influenced by the spring maximum in background ozone, but the diurnal and weekly cycles are dominated by losses through reaction with nitric oxide. Particle number count shows a minimum corresponding with maximum air temperatures in August, whereas the CO, NO NO₂ and SO₂ show a minimum in June/July. There is a lower particle count to NO_x ratio at the background site compared to a central London kerbside site (Marylebone Road) and a seasonal pattern in particle count to NO_x and PM₁₀ ratios consistent with loss of nanoparticles by evaporation during atmospheric transport. Sulphur dioxide peaks in the morning in summer, but at midday in winter consistent with emissions from elevated sources mixing down from aloft as the diurnal mixed layer deepens. Implications for epidemiological studies of air quality and health are discussed. Sulphur dioxide, carbon monoxide, nitric oxide and nitrogen dioxide show clear downward trends over the measurement period, PM₁₀ declines initially before levels stabilised, and ozone concentrations increased.     

An assessment of the impact of climate change on air quality at two UK sites

Possible effects of climate change on air quality are studied for two urban sites in the UK, London and Glasgow. Hourly meteorological data were obtained from climate simulations for two periods representing the current climate and a plausible late 21st century climate. Of the meteorological quantities relevant to air quality, significant changes were found in temperature, specific humidity, wind speed, wind direction, cloud cover, solar radiation, surface sensible heat flux and precipitation. Using these data, dispersion estimates were made for a variety of single sources and some significant changes in environmental impact were found in the future climate. In addition, estimates for future background concentrations of NO_x, NO₂, ozone and PM₁₀ upwind of London and Glasgow were made using the meteorological data in a statistical model. These showed falls in NO_x and increases in ozone for London, while a fall in NO₂ was the largest percentage change for Glasgow. Other changes were small. With these background estimates, annual-average concentrations of NO_x, NO₂, ozone and PM₁₀ were estimated within the two urban areas. For London, results averaged over a number of sites showed a fall in NO_x and a rise in ozone, but only small changes in NO₂ and PM₁₀. For Glasgow, the changes in all four chemical species were small. Large-scale background ozone values from a global chemical transport model are also presented. These show a decrease in background ozone due to climate change. To assess the net impact of both large scale and local processes will require models which treat all relevant scales.     

Size-selected particles in an urban atmosphere of Brisbane,Australia

Interpretations of source contributions and the behaviour of particles in the urban atmosphere of Brisbane were made by comparing the results of elemental analyses with the measured meteorological conditions, PM₁₀, light scattering, gaseous pollutant concentrations and particle size distributions.Carbon was determined to be the most abundant element in the fine particles (FP). Although many of the other elements in the greater relative abundances are usually associated with natural origins, the major influence resulting in changes to FP mass was concluded to be by elements from anthropogenic sources. This conclusion was based on the significant positive relationships between the anthropogenic elements (e.g., Pb, Br, C, Ti, V, Mn, etc.) with the FP mass. The major influence on the PM₁₀ mass concentrations was determined to be the elements usually associated with natural origins such as Na and Cl. In addition, the positive relationship of submicrometre particle number concentrations with FP carbon and with vehicular-emitted gaseous species including NO_x and CO implied a significant contribution of vehicle exhausts to aerosols in this size range.     

Neural network modelling and prediction of hourly NOx and NO2 concentrations in urban air in London

Multilayer perceptron (MLP) neural networks were trained to model hourly NO_x and NO₂ pollutant concentrations in Central London from basic hourly meteorological data. Results have shown that the models perform well when compared to previous attempts to model the same pollutants using regression based models. This work also illustrates that MLP neural networks are capable of resolving complex patterns of source emissions without any explicit external guidance.     

Sources and processes affecting concentrations of PM10 and PM2.5 particulate matter in Birmingham (U.K.)

Hourly average concentrations of PM₁₀ and PM_2.5 have been measured simultaneously at a site within Birmingham U.K. between October 1994 and October 1995. Comparison of PM₁₀ and NO_x data with two other sites in the same city shows comparable summer and winter mean concentrations and highly significant inter-site correlations for both hourly and daily mean data. Over a four-month period samples were also collected for chemical analysis of sulphate, nitrate, chloride, ammonium and elemental and organic carbon. Analysis of the data indicates a marked difference between summer and winter periods. In the winter months PM_2.5 comprises about 80% of PM₁₀ and is strongly correlated with NO_x indicating the importance of road traffic as a source. In the summer months, coarse particles (PM₁₀−PM_2.5) account for almost 50% of PM₁₀ and the influence of resuspended surface dusts and soils and of secondary particulate matter is evident. The chemical analysis data are also consistent with three sources dominating the PM₁₀ composition: vehicle exhaust emissions, secondary ammonium salts and resuspended surface dusts. Coarse particles from resuspension showed a positive dependence on windspeed, whilst elemental carbon derived from road traffic exhibited a negative dependence.     

Retrospective assessment of air quality management practices in Taiwan

In 1995, Taiwan's Environmental Protection Administration (EPA/TW) instituted a policy of levying emission taxes on polluters in order to combat the rampant national issue of pollution. Since that time, pollution control strategies, tightening exhaust emission standards for industry, improvements in fuel quality, and new stricter vehicle emission standards, etc., have been implemented. This study evaluates the effectiveness of these measures and examines the improvement of Taiwan's air quality. In this paper, we conduct a detailed analysis of change in the concentrations of pollutants (SO₂, NO_x and particulate matter [PM]) between two three-year periods (from 1996 to1998 and from 2000 to 2002). The pollution levels were generally lower in the latter period. Concentrations at 14 EPA/TW stations in central Taiwan were simulated and source apportionment analyses in three of Central Taiwan's largest cities were conducted using a trajectory transfer-coefficient air quality model. Correlation coefficients (r) between simulations and observations for the monthly means of the concentrations of SO₂, NO_x, PM_2.5 and PM₁₀ during the study periods at the 14 stations are 0.56, 0.63, 0.70 and 0.31, respectively. The sulfur control policy greatly reduced SO₂ concentration island-wide, a stringent emission standard put into place for gasoline vehicles reduced NO_x concentration along highways, and an emissions tax placed on construction sites, as well as a regular program for road-dust sweeping, reduced primary particulate matter. Among all of the pollution abatement policies implemented, the most effective method for reducing PM_2.5 concentrations in the three largest cities involved the reduction of fine ammonium sulfate aerosols from point sources (56–63% of net PM_2.5 reduction). The next largest reduction was attributed to a diminishment in primary PM_2.5 emanating from point sources (27–56% of net PM_2.5 reduction). Secondary particulate matter, especially sulfate, was reduced from distances up to 150 km leeward of major pollution point sources such as Taichung Power Plant.     

Air pollution characteristics associated with mesoscale atmospheric patterns in northwest continental Europe

An impact related daily air quality index (DAQx), calculated for 15 air quality monitoring stations (traffic, background, and industry) in Belgium, France, Germany and Luxembourg, was compared to mesoscale atmospheric patterns between 2001 and 2007. Meteorological conditions were described by the Hess and Brezowsky synoptic weather classification system and gridded data of the EU FP6 ENSEMBLES project of total precipitation and mean surface temperature. DAQx values indicate sufficient to poor air quality in the urban area of Brussels and at urban traffic stations, as well as satisfactory air quality at the background stations. The air quality index refers to more than 90% to the presence of high PM₁₀, O₃ and NO₂ concentrations. SO₂ and CO play only a minor role. The investigation of weather regimes indicates that zonal and mixed cyclonic circulation regimes are associated with better air quality than meridional and anticyclonic weather regimes. In general, weather regimes with high daily precipitation lead to better air quality than dryer air masses because of lower contribution of PM₁₀ to the air quality index. A trend analysis of weather regimes from 1978 to 2007 shows significant (α = 0.05) positive trends for weather classes associated with lower PM₁₀ concentrations. The results of a case study at a German station examining the relationship between PM₁₀ concentrations and local meteorological quantities (wind speed and precipitation) confirm the results of the regional analysis.     

An inexpensive method to estimate CO and NOx emissions from mobile sources

CO and NO_x measurements from mobile sources at two urban locations in Córdoba City, Argentina, were used to develop a very simple method to estimate emission from these sources. This development was possible because primary urban air pollution in Córdoba comes mostly from mobile sources and because a field measurement campaign was conducted by the city government during 1995–1996 that has allowed us to have a complete and valuable data bank. Air concentrations of CO, NO_x as well as physical, and meteorological variables were measured at two urban sites with two monitoring stations. We compared the measured CO and NO_x air concentration data with the predictions of a method that uses regression analysis to estimate the emission factor from the mobile sources. The agreement is good, considering the simplicity of the approach.     

Harbour of Ravenna: The contribution of harbour traffic to air quality

Ravenna is one of the main Italian ports and has assumed a leadership position in Italy for some products and markets. The commercial harbour and the adjacent industrial area are very important for the economic system of Ravenna but, at the same time, they are highly critical areas.In particular, on average 8000 ships per year pass through the harbour of Ravenna, influencing air quality in harbour environment.The paper originates from a study about the contribution of different sources of air pollution in Ravenna and its aim is to evaluate the maritime traffic contribution to the air quality in the port area and to determine the suitability of an urban air quality model to support the air quality management in Ravenna. NO_x and PM are selected as modelled pollutants.The study is made up of two parts. The first deals with the evaluation of annual emission of PM₁₀ and NO_x coming from ships through a standard European methodology while in the second we simulated the diffusion of these pollutants in the whole area. In order to evaluate the capability of the model to treat maritime traffic emissions, we compared hour-by-hour simulated concentrations with data collected by a fixed monitoring station located near the Candiano Canal.NO_x concentrations obtained by short- and long-term simulations show a good match with the values measured by the fixed monitoring station, located in the centre of harbour area, and these results are also supported by FA2 performance index.Instead the omission of the secondary particulate and the contribution of other sources of particulate matter in the port area are probably the most important causes of the PM₁₀ underestimation.The worse results obtained according to the performance indexes indicate the need to consider the formation and transport of secondary particulate matter in order to obtain more reliable predictions.     

An empirical approach for the prediction of daily mean PM10 concentrations

An empirical model has been devised to predict concentrations of PM₁₀ at background and roadside locations in London. Factors to calculate primary PM₁₀ and PM_2.5 concentrations are derived from annual mean NO_X, PM_2.5 and PM₁₀ measurements across London and south east England. These factors are used to calculate daily means for the primary and non-primary PM₁₀ fractions for the London area. The model accurately predicts daily mean PM₁₀ and EU Directive Limit values across a range of sites from kerbside to rural. Predictions of future PM₁₀ can be made using the expected reductions in secondary PM₁₀ and site specific annual mean NO_X predicted from emission inventories and dispersion modelling. The model suggests that the EU Directive Limit values will be exceeded close to many of London's busiest roads, and perhaps at central background sites should there be a repeat of 1996 meteorological conditions during 2005. A repeat of 1997 meteorology conditions during 2005 would lead to the EU Limit Value being exceeded alongside the busiest central London roads only. The model is applicable for London and south east England but the methodology could be applied elsewhere at a city or regional level. The model relies on the currently observed ratio between NO_X and PM₁₀. This ratio has remained constant over the last 4 years but might change in the future. The NO_X:PM₁₀ ratio derived from measurements and used in this model, implies that emission inventories might over estimate primary PM₁₀ by more than 50%.