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.     

Modelling and assessing trends in traffic-related emissions using a generalised additive modelling approach

A generalised additive modelling (GAM) approach is used to model daily concentrations of nitrogen oxides (NO_X), nitrogen dioxide (NO₂), carbon monoxide (CO), benzene and 1,3-butadiene at a busy street canyon location in central London. The models were developed for the period July 1998–June 2005 using appropriate meteorological and road traffic covariates. For all models, the complex and localised wind-flow patterns resulting from the street canyon location of the monitoring site, which can be difficult to model deterministically, have a large influence on the model predictions. It is shown that GAMs built using simple covariates explain a large amount of the daily variation for these pollutants (mean r²=0.86). It is found that concentrations of benzene and 1,3-butadiene have declined in line with detailed calculations of emissions trends, with some evidence to suggest that reductions in benzene have been greater than estimated reductions in emissions. Although measured concentrations of NO_X have declined from 1998 to 2005, much of the decline appears to be associated with reductions in overall traffic and meteorological factors rather than reduced emissions of NO_X. Unadjusted NO_X trends show a 28.6% reduction (95% confidence interval from 21.2% to 35.8%) from 1998 to 2005, whereas meteorologically adjusted trends show a 19.3% decline (95% confidence interval from 14.8% to 23.5%) over this period. Analysis shows that there were a higher number of occasions in the early part of the time series that led to strong recirculation of exhaust emissions and higher NO_X concentrations at this location, thus affecting observed trends in concentration.     

Air pollution at a hotspot location in Delhi: Detecting trends,seasonal cycles and oscillations

This paper uses spectral methods to analyze changes in air quality at a single monitoring site in Delhi since 2000. Power spectral density calculations of daily concentration data for particulate matter (PM10), carbon monoxide (CO), oxides of nitrogen (NO_x) and oxides of sulfur (SO_x) reveal the presence of trends and periodic oscillations for all the pollutants. Singular Spectrum Analysis (SSA) is used to decompose daily data into statistically significant non-linear trends, seasonal cycles and other oscillations. Periods of sharp reductions were observed for both SO_x and CO concentrations in 2001 and 2002, respectively. NO_x concentration trends show a sustained rise from 2000 to 2004, followed by small decline thereafter. PM10 concentration trends remain essentially unchanged over the time period. All pollutants also show strong annual and biannual cycles. The observed trends in CO and NO_x likely relate changes in Delhi's vehicular traffic emissions. The sharp drop in both the trend and amplitude of the seasonal cycle of CO coincides with the switch to Compressed Natural Gas (CNG) as a fuel for Delhi's public transport fleet. Observed changes in SO_x and PM10 concentrations were most likely caused by sources unrelated to vehicular traffic.     

A gas/aerosol air pollutants study over the urban area of Rome using a comprehensive chemical transport model

The aim of this study was to identify areas of potential relevant exposure to pollutants within Rome's urban core. To meet this goal, intensive field campaigns were conducted and simulations were performed, using the flexible air quality regional model (FARM), to study winter and summer pollution episodes. The simulations were performed using a complete emission inventory that included traffic flow model results of the Roman street network to better describe, with respect to the available diffuse national emission inventory, the hourly variation of traffic emissions in the city. The meteorological reconstruction was performed by means of both prognostic and diagnostic models by using experimental data collected during the field campaigns. To evaluate the capability of the FARM model to capture the main features of the selected episodes, a comparison of modelled results against observed air quality data for different pollutants was performed at urban and rural sites. FARM performed well in predicting ozone (O₃) and nitrogen dioxide (NO₂) concentrations, showing a good reproduction of both daily peaks and their diurnal variations. The model also showed a good capability to reproduce the magnitude of volatile alkane, aromatic and carbonyl compound concentrations. PM₁₀ model results revealed the tendency to under-predict the observed values. PM composition model results were compared with observed data, evidencing good results for elemental carbon (EC), nitrate (NO₃⁻) and ammonium (NH₄⁺), underestimation for sulphate (SO₄²⁻) and poor performance for organic matter (OM). The soil components of PM were found to be significantly under-predicted by the model, especially during Saharan dust episodes. Overall, the study results show large areas of high O₃ and PM₁₀ concentrations where levels of pollutants should be carefully monitored and population exposure evaluated.     

Development of an individual exposure model for application to the Southern California children's health study

The Southern California Children's Health Study (CHS) investigated the relationship between air pollution and children's chronic respiratory health outcomes. Ambient air pollutant measurements from a single CHS monitoring station in each community were used as surrogates for personal exposures of all children in that community. To improve exposure estimates for the CHS children, we developed an Individual Exposure Model (IEM) to retrospectively estimate the long-term average exposure of the individual CHS children to CO, NO₂, PM₁₀, PM_2.5, and elemental carbon (EC) of ambient origin. In the IEM, pollutant concentrations due to both local mobile source emissions (LMSE) and meteorologically transported pollutants were taken into account by combining a line source model (CALINE4) with a regional air quality model (SMOG). To avoid double counting, local mobile sources were removed from SMOG and added back by CALINE4. Limited information from the CHS survey was used to group each child into a specific time-activity category, for which corresponding Consolidated Human Activity Database (CHAD) time-activity profiles were sampled. We found local traffic significantly increased within-community variability of exposure to vehicle-related pollutants. PM-associated exposures were influenced more by meteorologically transported pollutants and local non-mobile source emissions than by LMSE. The overall within-community variability of personal exposures was highest for NO₂ (±20–40%), followed by EC (±17–27%), PM₁₀ (±15–25%), PM_2.5 (±15–20%), and CO (±9–14%). Between-community exposure differences were affected by community location, traffic density, and locations of residences and schools in each community. Proper siting of air monitoring stations relative to emission sources is important to capture community mean exposures.     

Estimation of road vehicle exhaust emissions from 1992 to 2010 and comparison with air quality measurements in Genoa,Italy

An investigation into road transport exhaust emissions in the Genoa urban area was performed by comparing the quantities of carbon monoxide (CO), nitrogen oxides (NO_x), nitrogen dioxide (NO₂) and particulate matter (PM) emitted by different vehicle categories with air quality measurements referred to the same pollutants. Exhaust emissions were evaluated by applying the PROGRESS (computer PROGramme for Road vehicle EmiSSions evaluation) code, developed by the Internal Combustion Engines Group of the University of Genoa, to eight different years (from 1992 to 2010), considering spark ignition and Diesel passenger cars and light duty vehicles, heavy duty vehicles and buses, motorcycles and mopeds. Changes in terms of vehicles number, mileage and total emissions are presented together with relative distributions among the various vehicle categories. By comparing 1992 and 2010 data, calculated trends show a 7% increase in the number of vehicles, with total mileage growing at a faster rate (approx. 22%); total emissions decrease considerably, by approximately 50% for NO_x and PM, 70% for HC and 80% for CO, due to improvements in engines and fuels forced by the stricter European legislation and the fleet renewal, while primary NO₂ emission will be very close to 1992 level, after a decrease of about 18% in 2000.Air quality was analysed by selecting traffic and background measuring stations from the monitoring network managed by the Environmental Department of the Province of Genoa: average annual concentrations of considered pollutants from 1994 to 2007 were calculated in order to obtain the relative historical trends and compare them with European public health limits and with road vehicle emissions. Though an important reduction in pollutant concentrations has been achieved as a consequence of cleaner vehicles, some difficulties in complying with present and/or future NO₂ and PM₁₀ limits are also apparent, thus requiring suitable measures to be taken by the local authorities.     

Continuous measurement of gaseous pollutants in Buenos Aires city

Data on CO, NO, NO₂ and O₃ concentrations measured in Buenos Aires city using a continuous monitoring station are reported. This is the first systematic study of this kind carried out in the city, which is, together with its surroundings, the third more populated in Latin America. Measurements were performed during 12 months in one of the principal avenues near downtown. Results indicate that vehicular traffic is the principal source of CO and NO_x. The concentration of O₃ is generally quite low and results from the mixing of clean air masses with exhaust gases containing high amounts of NO. The monthly averages of CO and NO decrease from Winter to Summer in correlation with the increase of the mean wind speed and average temperature. These results are compared with previous measurements on the spatial distribution of NO₂ in the whole city using passive diffusion tubes and with the concentration of CO, which is being continuously registered since several years in the downtown area. Measurements performed at a green, windy, low traffic area beneath the La Plata river are also shown.     

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.     

Assessment of traffic-related air pollution in the urban streets before and during the 2008 Beijing Olympic Games traffic control period

In order to investigate the air quality and the abatement of traffic-related pollution during the 2008 Olympic Games, we select 12 avenues in the urban area of Beijing to calculate the concentrations of PM₁₀, CO, NO₂ and O₃ before and during the Olympic traffic controlling days, with the OSPM model.Through comparing the modeled results with the measurement results on a representative street, the OSPM model is validated as sufficient to predict the average concentrations of these pollutants at street level, and also reflects their daily variations well, i.e. CO presents the similar double peaks as the traffic flow, PM₁₀ concentration is influenced by other sources. Meanwhile, the model predicts O₃ to stay less during the daytime and ascend in the night, just opposite to NO₂, which reveals the impact of photochemical reactions. In addition, the predicted concentrations on the windward side often exceed the leeward side, indicating the impact of the special street shape, as well as the wind.The comparison between the predicted street concentrations before and during the Olympic traffic control period shows that the overall on-road air quality was improved effectively, due to the 32.3% traffic flow reduction. The concentrations of PM₁₀, CO and NO₂ have reduced from 142.6 μg m⁻³, 3.02 mg m⁻³ and 118.7 μg m⁻³ to 102.0 μg m⁻³, 2.43 mg m⁻³ and 104.1 μg m⁻³. However, the different pollutants show diverse changes after the traffic control. PM₁₀ decreases most, and the reduction effect focusing on the first half-day even clears the morning peak, whereas CO and NO₂ have even reductions to minify the daily fluctuations on the whole. Opposite to the other pollutants, ozone shows an increase of concentration. The average reduction rate of PM₁₀, CO, NO₂ and O₃ are respectively 28%, 19.3%, 12.3% and −25.2%. Furthermore, the streets in east, west, south and north areas present different air quality improvements, probably induced by the varied background pollution in different regions around Beijing, along with the impact of wind force. This finding suggests the pollution control in the surrounding regions, not only in the urban area.     

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.     

Variability of Nox and No2 concentrations observed at pedestrian level in the city centre of a medium sized urban area

NO_x and NO₂ concentrations were measured at different locations in a city centre of an urban zone (Population 450 000) in order to study the variation of the outdoor exposure at pedestrian level. These measurements were carried out to understand the influence of traffic emissions at each measured site. The observations were done during four weeks in winter, including several days with high pollution levels. The results at different locations have been used to analyse criteria recommended for locating observation sites in a monitoring network. No large differences in background pollution averaged over several weeks have been found throughout the city centre, even during pollution peaks. Measurements were also carried out inside one street canyon. The contribution of the street traffic to the NO=NO_x−NO₂ concentrations observed at side-walk has been found important, i.e., several times the background level. On the other hand, the majority of observed NO₂ pollution is due to the contribution of background pollution within the street. The pollutant excess at pedestrian level is strongly correlated to the street traffic emission and to the atmospheric turbulence observed at roof level. Application of a box model to the street data demonstrates that such models can be useful to estimate the pollutant accumulation within the street.     

Air Quality Modeling of Interpollutant Trading for Ozone Precursors in an Urban Area

Abstract

Emission trading is a market‐based approach designed to improve the efficiency and economic viability of emission control programs; emission trading has typically been confined to trades among single pollutants. Interpollutant trading (IPT), as described in this work, allows for trades among emissions of different compounds that affect the same air quality end point, in this work, ambient ozone (O₃) concentrations. Because emissions of different compounds impact air quality end points differently, weighting factors or trading ratios (tons of emissions of nitrogen oxides (NO_x) equivalent to a ton of emissions of volatile organic compounds [VOCs]) must be developed to allow for IPT. In this work, IPT indices based on reductions in O₃ concentrations and based on reductions in population exposures to O₃ were developed and evaluated using a three‐dimensional gridded photochemical model for Austin, TX, a city currently on the cusp of nonattainment with the National Ambient Air Quality Standards for O₃ concentrations averaged over 8 hr. Emissions of VOC and NO_x from area and mobile sources in Austin are larger than emissions from point sources. The analysis indicated that mobile and area sources exhibited similar impacts. Trading ratios based on maximum O₃ concentration or population exposure were similar. In contrast, the trading ratios did exhibit significant (more than a factor of two) day‐to‐day variability. Analysis of the air quality modeling indicated that the daily variability in trading ratios could be attributed to daily variations in both emissions and meteorology.     

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.     

Estimating Future NO2 Levels in the Greater Los Angeles Area by Source–Type Contribution

Two indicator pollutants, carbon monoxide (CO) for mobile source influence and sulfur dioxide (SO₂) for stationary source influence, were used to estimate source-type contributions to ambient NO₂ levels in a base year and to predict NO₂ concentrations in a future year. For a specific source-receptor pair, the so-called influence coefficient of each of three source categories (mobile sources, power plants, and other stationary sources) was determined empirically from concurrent measurements of CO and SO₂ concentrations at the receptor site and CO and SO₂ emissions from each source category in the source area. Those coefficients, which are considered time invariant, were used in conjunction with the base year and future year NO _x emission values to estimate source-type contribution to ambient NO₂ levels at seven study sites selected from the Greater Los Angeles area for both the base year period, 1974 through 1976, and the future goal year of 1987 in which the air quality standards for NO₂ are to be attained. The estimated NO₂ air quality at the seven sites is found to meet the national annual standard of 5 pphm and over 99.9% of total hours, the California 1-hr NO₂ standard of 25 pphm in 1987. The estimated power plant contributions to ambient NO₂ levels are found to be considerably smaller than those to total NO _x emissions in the area. Providing that reasonably complete air quality and emissions data are available, the present analysis method may prove to be a useful tool in evaluating source contributions to both short-term peak and long-term average NO₂ concentrations for use in control strategy development.     

Measurement and Three-Dimensional Modeling of Airflow and Pollutant Dispersion in an Undersea Traffic Tunnel

Abstract

Airflow and pollutant dispersion in a cross-harbor traffic tunnel were experimentally and numerically studied. Concentrations of the gaseous pollutants CO, NO_x, and total hydrocarbons (THC) at three axial locations in the tunnel, together with traffic flow rate, traffic speed, and types of vehicle were measured. Three-dimensional (3D) turbulent flow and dispersion of air pollutants in the tunnel were modeled and solved numerically using the finite volume method. Traffic emissions were modeled accordingly as banded line sources along the tunnel floor. The results reveal that cross-sectional concentrations are nonuniformly distributed and that concentrations rise with downstream distance. The piston effect of vehicles alone can provide 9–23% dilution of air pollutants in the tunnel, compounded to a 23–74% dilution effect according to the ventilation condition.     

Predicting hourly air pollutant levels using artificial neural networks coupled with uncertainty analysis by Monte Carlo simulations

Recent progress in developing artificial neural network (ANN) metamodels has paved the way for reliable use of these models in the prediction of air pollutant concentrations in urban atmosphere. However, improvement of prediction performance, proper selection of input parameters and model architecture, and quantification of model uncertainties remain key challenges to their practical use. This study has three main objectives: to select an ensemble of input parameters for ANN metamodels consisting of meteorological variables that are predictable by conventional weather forecast models and variables that properly describe the complex nature of pollutant source conditions in a major city, to optimize the ANN models to achieve the most accurate hourly prediction for a case study (city of Tehran), and to examine a methodology to analyze uncertainties based on ANN and Monte Carlo simulations (MCS). In the current study, the ANNs were constructed to predict criteria pollutants of nitrogen oxides (NO_x), nitrogen dioxide (NO₂), nitrogen monoxide (NO), ozone (O₃), carbon monoxide (CO), and particulate matter with aerodynamic diameter of less than 10 μm (PM₁₀) in Tehran based on the data collected at a monitoring station in the densely populated central area of the city. The best combination of input variables was comprehensively investigated taking into account the predictability of meteorological input variables and the study of model performance, correlation coefficients, and spectral analysis. Among numerous meteorological variables, wind speed, air temperature, relative humidity and wind direction were chosen as input variables for the ANN models. The complex nature of pollutant source conditions was reflected through the use of hour of the day and month of the year as input variables and the development of different models for each day of the week. After that, ANN models were constructed and validated, and a methodology of computing prediction intervals (PI) and probability of exceeding air quality thresholds was developed by combining ANNs and MCSs based on Latin Hypercube Sampling (LHS). The results showed that proper ANN models can be used as reliable metamodels for the prediction of hourly air pollutants in urban environments. High correlations were obtained with R ² of more than 0.82 between modeled and observed hourly pollutant levels for CO, NO_x, NO₂, NO, and PM₁₀. However, predicted O₃ levels were less accurate. The combined use of ANNs and MCSs seems very promising in analyzing air pollution prediction uncertainties. Replacing deterministic predictions with probabilistic PIs can enhance the reliability of ANN models and provide a means of quantifying prediction uncertainties.     

Spatiotemporal analysis of traffic emissions in over 5000 municipal districts in Brazil

Exposure to traffic emission is harmful to human health. Emission inventories are essential to public health policies aiming at protecting human health, especially in areas with incomplete or nonexistent air pollution monitoring networks. In Brazil, for example, only 1.7% of municipal districts have a monitoring network, and only a few studies have reported data on vehicle emission inventories. No studies have presented emission inventories by municipality. In this study, we predicted vehicular emissions for 5570 municipal districts in Brazil during the period 2001–2012. We used a top-down method to estimate emissions. Carbon dioxide (CO₂) is the pollutant with the highest emissions, with approximately 190 million tons per year during the period 2001–2012). For the other traffic-related pollutants, we predicted annual emissions of 1.5 million tons for carbon monoxide (CO), 1.2 million tons of nitrogen oxides (NO_x), 209,000 tons of nonmethane hydrocarbons (NMHC), 58,000 tons of particulate matter (PM), and 42,000 tons for methane (CH₄). From 2001 to 2012, CO, NMHC, and PM emissions decreased by 41, 33, and 47%, respectively, whereas those CH₄, NO_x, and CO₂ increased by 2, 4, and 84%, respectively. We estimated uncertainties in our study and found that NO_x was the pollutant with the lowest percentage difference, 8%, and NMHC with the highest one, 30%. For CO, CH₄, CO₂, and PM, the values were 22, 14, 21, and 20%, respectively. Finally, we found that during 2001 and 2012 emissions increased in the Northwest and Northeast. In contrast, pollutant emissions, except for CO₂, decreased in the Southeast, South, and part of Midwest. Our predictions can be critical to efforts developing cost-effective public policies tailored to individual municipal districts in Brazil.

Implications: Emission inventories may be an alternative approach to provide data for air quality forecasting in areas where air quality data are not available. This approach can be an effective tool in developing spatially resolved emission inventories.     

The impact of transportation control measures on emission reductions during the 2008 Olympic Games in Beijing,China

Traffic congestion and air pollution were two major challenges for the planners of the 2008 Olympic Games in Beijing. The Beijing municipal government implemented a package of temporary transportation control measures during the event. In this paper, we report the results of a recent research project that investigated the effects of these measures on urban motor vehicle emissions in Beijing. Bottom–up methodology has been used to develop grid-based emission inventories with micro-scale vehicle activities and speed-dependent emission factors. The urban traffic emissions of volatile organic compounds (VOC), carbon monoxide (CO), nitrogen oxides (NO_x) and particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀) during the 2008 Olympics were reduced by 55.5%, 56.8%, 45.7% and 51.6%, respectively, as compared to the grid-based emission inventory before the Olympics. Emission intensity was derived from curbside air quality monitoring at the North 4th Ring Road site, located about 7 km from the National Stadium. Comparison between the emission intensity before and during the 2008 Olympics shows a reduction of 44.5% and 49.0% in daily CO and NO_x emission from motor vehicles. The results suggest that reasonable traffic system improvement strategies along with vehicle technology improvements can contribute to controlling total motor vehicle emissions in Beijing after the Olympic Games.     

Summer air quality over an artificial lake

In the summer of 1998, the air quality (indicators: CO, NO, NO₂, O₃) above the water surface of the Lake Balderey (Essen, Ruhr area, North Rhine-Westphalia, Germany), an artificial lake used for recreation purposes, was measured using the Fourier transform infrared spectroscopy (FTIR) and differential optical absorption spectroscopy (DOAS) remote measurement methods. The lake, with an area of 3 km² was created by damming the Ruhr and is surrounded by higher ground. In calm, bright weather conditions, this location results in a low-exchange situation (formation of temperature inversions, cold air dynamics) with a sustained impact on pollutant concentrations over the lake. The results of trace substance measurements (1/2 h mean values) were compared with values from comparison stations (suburban, high traffic and forest) located outside the area of the lake. In general, it was found that mean CO and NO concentrations over the lake were very low (0.3 ppm and 7.5 ppb, respectively). NO₂ values (15 ppb) were some 3.5 times higher than those recorded at the forest station and O₃ values, at 27 ppb, almost reached the same level as at the forest station (30 ppb). Mass flow densities as a function of wind direction, diurnal courses, differences between weekdays and weekends and comparisons with air quality standards are presented for the lake station.     

Exposure to hazardous air pollutants along Oba Akran road, Lagos-Nigeria

We measured toxic air pollutants along Oba Akran road in Lagos to evaluate pedestrian exposure. PM₁₀, CO, O₃, NO₂, SO₂, CH₄, noise, wind velocity and temperature were measured simultaneously with portable analyzers. Our results showed that pedestrian exposure to PM₁₀ (with an average of 274.6 μg m⁻³ for all samples) and CO (with an average of 19.27 ppm for all samples) was relatively high. CO is a traffic-related pollutant, so the influence of the local traffic emissions on CO levels is strong. The high concentration of the PM₁₀ measured at the three environments also suggests that the traffic is a major source of ultrafine particles. The overall average concentrations for the 72-day experimental period for SO₂, NO₂ and O₃ are 101.2, 62.5 and 0.32 ppb respectively, all of which are below the US national ambient air quality standards. Strong traffic impacts can be observed from the concentrations of some of these pollutants measured in these three environments. Most clear is a reflection of diesel truck traffic activity rich in black carbon concentrations. The diurnal variation of O₃ and NO₂ also showed that NO₂ was depleted by photochemically formed O₃ during the day and replenished at night as O₃ was destroyed. A multivariate statistical analysis (Principal Component Analysis, Factor Analysis) has been applied to a set of data in order to determine the contribution of different sources. It was found that the main principal components, extracted from the air pollution data, were related to gasoline combustion, oil combustion and ozone interactions.