Air pollution at the Bily Kriz mountains in the Czech Republic

An evaluation of air pollution at the Bily Kriz mountains in the Czech Republic is given. Annual daily concentrations of sulphur dioxide (SO₂), nitrogen oxides (NO_x), particulate matter of size 10 mm (PM₁₀) and ozone (O₃) measured in the years 1994–2000 are presented. Air pollution at Bily Kriz is assessed with the reference to the European Union Directives and the standards adopted by the Czech Republic. In general, the concentrations of air pollutants were lower in 1996 for ozone and decreased for SO₂, NO_x and PM₁₀ from 1994. The daily values of SO₂ and PM₁₀ exceeded the European Union limits in approximately 0.0% and 5.5% of cases, respectively. The values of ozone exceeded the limits for the considered period.     

Air pollution and the influence of sources on Paulinia (Brazil) and surroundings

The air quality in the industrial area and surroundings of the city of Paulinia (state of Sao Paulo, Brazil) has been investigated by analysing the concentration of air pollutants (SO₂, PM₁₀, NO, NO₂, CO and ozone) and identifying the main sources of air pollution. A mobile pollutant monitoring unit was used to collect the data at five different sites from November 2000 to July 2002. Critical pollutants were determined based on air quality standards, and sources were identified by principal component analysis. Photochemical reactions play an important role in Paulinia's air pollution: three out of five monitored sites showed levels exceeding the standard air quality of ozone. SO₂ and PM₁₀ appeared as pollutants deserving special attention. All the monitored sites showed vehicles and industrial plants (which release SO₂) to be significant sources of pollution. Depending on the location, ozone was related mainly with vehicular or industrial sources.     

Influence of meteorological factors on air pollution concentration for a coastal region in India

A long-term study of measurement of concentration of NO_x, SO₂ and TSP pollutants have been done in a port and harbour region in India. Monthly measurements of gaseous and particulate pollutants were made at six monitoring stations from January 1997 to December 2000. Meteorological data was also simultaneously collected. In this study, the relationship between monitored ambient air quality data and meteorological factors, such as wind speed, temperature, is statistically analysed, using the SPSS package. The monthly mean concentrations of NO_x, SO₂ and TSP were in the range of 19.5–59.0 μg/m3, 8.6–51.3 μg/m3 and 88.2–199.3 μg/m3, respectively. The results show that TSP is strongly correlated with NO_x and SO₂ with a correlation coefficient of 0.83 and 0.82, respectively. The correlation coefficients for TSP, NO_x, and SO₂ with wind are –0.78, –0.78, and –0.88, respectively.     

Sustainable urban transportation: impact of CO2 mitigation strategies on local pollutants

This paper assesses CO₂ mitigation strategies in Delhi and Mumbai against the dynamics of local pollutants. After testing against techno-economic feasibility, compressed natural gas (CNG) technology, four-stroke two-wheelers and battery-operated vehicles (BOV) were selected as candidate options for Mumbai and Delhi. Multiple constrained optimisation for finding out the optimal mix of vehicles to meet the travel demand under the business-as-usual scenario for the period of CO₂ mitigation targets of 5, 10, 15, 20, 25% resulted in reduced stock of diesel and petrol vehicles, with the reduction spanning over different points of the above time period. In the case of Mumbai, battery-operated three-wheelers dominated the vehicular mix, with the share of CNG vehicles remaining at a standard level. CO₂ reduction targets did not influence the CNG option significantly. CO₂ mitigation influenced the dynamics of local pollutants considerably in both Delhi and Mumbai. In Delhi, TSP and SOx reduction levels against the CO₂ mitigation target were found to be significant. In Mumbai, the percentage reduction in local pollution (TSP in particular) was higher than the target CO₂ reduction. Local pollutants other than TSP and SO_x showed an increasing trend against the CO₂ mitigation strategies in Delhi. In the case of Mumbai, all non-target pollutants showed a falling trend against the CO₂ mitigation strategies, though insignificantly for pollutants other than TSP and SO_x.     

Short-term prediction of means of artificial neural urban NO2 pollution by networks

A neural network model for the short-term prediction of concentrations of urban pollutants was developed and applied to the Turin (Northern Italy) air quality network. In particular, the study was focused on NO₂ concentrations measured at five stations; t + 3 and t + 24 hour NO₂ concentration forecasting based on hourly meteorological and concentration data gave good agreement with observed concentrations. This is particularly true for the mean concentration values and concentration distribution. The time of occurrence of peak values was correctly forecast but the amounts were generally underestimated. To reduce this underestimation, an empirical step function was applied in the t + 24 case. This allowed an accurate estimate to be obtained of the few cases in which 50% of the air quality monitoring stations exceeded the attention level (200 μg m^-3) during the following day for at least one hour.     

Measurement of atmospheric particles and anionic species across central Taiwan

The ambient air concentrations and fluxes of various anionic species were sampled by MOUDI, TSP and dry deposition plates at a traffic sampling site in Taichung, central Taiwan. In the sampling period, from September to December 2000, the ambient air particle concentrations (PM₁, PM_2.5, PM₁₀ and TSP) were lower in the September than in the other three months (October to December). The reason is that the northwest wind brought more particles (diameter less than 10 μm) and the higher wind speed caused higher dry deposition fluxes and TSP concentrations in the last three months. The anion species percentages of TSP were 0.24%, 13.7%, 0.52%, 12.0%, 18.9'% and 54.6% for F^-, Cl^-, Br^-, NO₂^-, NO₃^- and SO₄^2-, respectively. The results revealed that SO₄^2-, NO₃^-, Cl^- and NO₂^- were the dominant species at the traffic sampling site. The ion-size distributions of Cl^-, NO₂^- and NO₃^- were unimodal, the main peak being between 3.2 and 5.6 μm. In contrast, the size distribution of SO₄^2- was bimodal, with the main peaks in the particle size ranges 0.32.0.56 μm and 3.2.5.6 μm. The ambient average particle dry deposition flux was 6.28 μg/m2/s, and the dry deposition fluxes were 0.01, 94.6, 0.05, 34.7, 72.2 and 376.4 ng/m2/s for F^-, Cl^-, Br^-, NO₂^-, NO₃^- and SO₄^2-, respectively. The dry deposition velocities were 3.10, 0.03, 3.67, 0.05, 1.54, 2.03 and 3.67 cm/s for F^-, Cl^-, Br^-, NO₂^-, NO₃^- and SO₄^2-, respectively.     

Study of the weekday-weekend variation of air pollutants in a typical Mediterranean coastal town

A study of the air pollution in the Greek coastal town Volos was performed using the available data of the last ten years. Quantile analysis showed that ozone concentrations during weekends were higher by 5–10% in comparison to those on weekdays, while the inverse was observed for the other pollutants, indicating the occurrence of the so called 'weekend effect'. Analysis of the maximum values of the high ozone period showed even higher differences. The pollutants NO, NO₂, CO, and SO₂ were lower during weekends compared to weekdays, by about 30%, 20%, 25% and 10% respectively.     

Trends in air quality and population exposure in Santiago, Chile, 1989–2001

This study focused on establishing trends in the period 1988–2001 in PM_2.5, PM₁₀ and ozone concentrations in Santiago, Chile, and linking those to population exposure. There is strong seasonality in the concentration levels, driven by prevailing meteorological conditions, with the concentration of particulates peaking at the beginning of winter, whereas the ozone concentration is highest during the summer. The levels of PM_2.5 and PM₁₀ have substantially decreased since the late 1980s and so has the population exposure. Nevertheless, the majority of the population is still exposed to annual average levels that are above standard values. The situation with ozone exposure is different; no substantial decrease can be observed in the data. If anything, certain parts of Santiago, notably the south-east, have shown increased levels of ozone. Overall population exposure indicates that the average person was more at risk of ozone in the year 2000 than they were in 1993.     

Separate determination of PM10 emission factors of road traffic for tailpipe emissions and emissions from abrasion and resuspension processes

Little is known about the relevance of mechanically produced particles of road traffic from abrasion and resuspension processes in relation to the exhaust pipe particles. In this paper, emission factors of PM₁₀ and PM₁ for light and heavy-duty vehicles were derived for different representative traffic regimes from concentration differences of particles and nitrogen oxides (NO_x) in ambient air upwind and downwind of busy roads, or alternatively of kerbsides and nearby background sites. Hereby, PM₁ was interpreted as direct exhaust emissions and PM₁₀-PM₁ as mechanically produced emissions from abrasion and resuspension processes. The results show that abrasion and resuspension processes represent a significant part of the total primary PM₁₀ emissions of road traffic. At sites with relatively undisturbed traffic flow they are in the same range as the exhaust pipe emissions. At sites with disturbed traffic flow due to traffic lights, emissions from abrasion/resuspension are even higher than those from the exhaust pipes.     

The application of the RAINS model for Greece

In order to comply in 2010 with the emission ceilings proposed by European commission under the convention on transboundary air pollution, Greece has to develop and implement a cohesive strategy affecting all the sectors of the economy. The RAINS model was used for the evaluation of the environmental and economic impacts arising from the use of a number of control technologies under alternative energy scenarios. To this purpose a number of modifications regarding the input databases of RAINS were made. The analysis clearly reveals that the reduction of SO₂ emissions can be achieved in a lower cost compared to the reduction of NO_x emissions. Moreover, the complementarity of CO₂ abatement policies and the SO₂/NO_x abatement policies is also accented.     

Spatial and diurnal variations in concentration of atmospheric NOx along urban-rural roadways in Nanjing, Southeastern China

Atmospheric NO_x concentrations (including NO₂ and NO) on the roadside environments of urban trunk, belt highway and suburban road as well as a reference in a forest area were measured. NO_x concentrations on roadside environments tended to be higher than that on the reference. With the exception of suburban road, NO_x concentrations over both of the urban trunk and belt highway exceeded the limited value of National Air Environmental Quality Standards. Gradient measurement of NO_x on the downwind side of the belt highway shows that it declined to background level over 100 m from the road edge.     

Interaction between air pollution and meteorological parameters in Erzurum, Turkey

In recent years, the rapid increase in population density has caused increases in the consumption of fuel, and the outdoor air quality has deteriorated in the crowded urban areas of Turkey. Erzurum, a city in the eastern part of Turkey, is influenced by air pollutants such as SO₂ and suspended particles. It is known that, in general, the air pollution concentrations have a close relationship with meteorological factors. In this study, the relationship between outdoor air quality data and meteorological factors, such as wind speed, rainfall, temperature, sunshine hours and relative humidity, is statistically analysed, using the code SPSS. According to the results obtained through multiple linear regression analysis, there are moderate levels of correlation between SO₂ and particle concentrations and meteorological factors in Erzurum.     

A statistical model for predicting carbon monoxide levels

This paper presents a statistical model that is able to predict carbon monoxide (CO) concentrations as a function of meteorological conditions and various air quality parameters. The experimental work was conducted in an urban atmosphere, where the emissions from cars are prevalent. A mobile air pollution monitoring laboratory was used to collect data, which were divided into two groups: a development group and a testing group. Only the development dataset was used for developing the model. The model was determined by using a stepwise multiple regression modelling procedure. Thirteen independent variables were selected as inputs: non-methane hydrocarbon (NMHC), methane (CH₄), suspended dust, carbon dioxide (CO₂), nitrogen oxide (NO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), wind speed, wind direction, temperature, relative humidity and solar energy. It was found that NO has the most effect on the predicted CO concentration. The contribution of NO to the CO concentration variations was 91.3%. Adding in the terms for NO₂), NMHC and CH₄ improved the model by only a further 2.3%. The derived model was shown to be statistically significant, and model predictions and experimental observations were shown to be consistent.     

Roadside particulate levels at 30 locations in the Kathmandu Valley, Nepal

Roadside particulate levels (PM₁₀) at 30 locations throughout the Kathmandu Valley, Nepal are reported. There were seven sampling cycles from January to December 1999. PM₁₀ levels ranged between 1000 and 6000 μ/m3 for 1-h sampling. There was no consistent trend in PM10 levels with respect to monitoring cycle, average precipitation or wind speed. There is no WHO guideline for PM₁₀ (no safe exposure threshold), but the EPA 24-h standard is 150 μ/m3. The major sources of roadside PM₁₀ include dust re-suspension from vehicular movement and human activity, and particulate emissions from old vehicles. Other sources of PM₁₀ in the valley include cement and brick factories. Studies are currently being conducted to determine the lead content of PM₁₀ from roadside samples. Additional studies are warranted to assess the potential adverse human health effects of acute or chronic exposure to high particulate levels reported in this study.     

Studies of air quality predictors based on neural networks

In recent years, urban air pollution has emerged as an acute problem because of its negative effect on health and living conditions. Regional air quality problems, in general, are linked to violations of specified air quality standards. The current study aims to find neural network based air quality predictors, which can work with a limited number of datasets and are robust enough to handle data with noise and errors. A number of available variations of neural network models, such as the Recurrent Network Model (RNM), the Change Point Detection Model with RNM (CPDM), the Sequential Network Construction Model (SNCM), the Self Organising Feature Model (SOFM), and the Moving Window Model (MWM), were implemented using MATLAB software for predicting air quality. Developed models were run to simulate and forecast based on the annual average data for 15 years from 1985 to 1999 for seven parameters, viz. VOC, NO_x, CO, SO₂, PM₁₀, PM_2.5 and NH₃ for one county of California, USA. The models were fitted with first nine years of data to predict data for remaining six years. The models, in general, could predict air quality patterns with modest accuracy. However, the SOFM model performed extremely well in comparison with the other models for predicting long-term (annual) data.     

Analysis and interpretation of the monitoring data for C2–C11 hydrocarbons in the atmosphere of a rural Portuguese site

This paper focuses the application of a measurement technique for determining atmospheric C₂–C₆ hydrocarbons after canister sampling and analysis by gas chromatography/flame ionisation detection (GC/FID), as well of an adsorption-sampling technique for C₆–C₁₁ compounds and GC/FID analysis after thermal desorption and cryogenic concentration. Tens of samples collected at Giesta, a rural area located 20 km to the SE of the coastal Portuguese city of Aveiro, were analysed. The characterisation of C₂ C₁₁ hydrocarbons is presented, considering seasonal variations, diurnal cycles, the influence of air masses and different photochemical conditions. Ratios between hydrocarbons and principal components analysis were applied to differentiate between biogenic and anthropogenic sources.     

An ozone climatology: relationship between meteorology and ozone in the Southeast USA

A statistical analysis of ozone (O₃) concentrations and meteorological parameters was performed to determine the relationship between meteorological changes and ambient O₃ concentrations in the Southeast United States. The correlation between average daily maximum O₃ concentration and various meteorological variables was analysed on a monthly basis from April through October during 1980-1994. The correlations were strongest during the summer months, particularly June, July, and August. Analysis of long term O₃ concentration trends indicates increasing trends during the 1980s and decreasing trends during the early 1990s.     

Source contribution of atmospheric aerosols in Bangkok metropolitan area by CMB8 receptor model

The CMB₈ model was applied for source apportionment of particulate matter in Bangkok area. The 24 h of ambient data were collected and analysed for elemental composition during December 1996 to January 1997 by high volume air samplers at a station in Bangkok, Thailand. Seven source profiles and the average mass concentrations of 42 ambient data were used to run the chemical mass balance (CMB₈) model. The source apportionment by CMB₈ gave similar results comparing with factor analysis – multiple regression (FA–MR) model of the same data. The results revealed that major sources of particulate matter in Bangkok were: soil (33%), road dust (33%) and automobile (15%). The minor source contributions were: sea salt (4.34%), refuse incineration and biomass burning (0.84%), steel mill (0.62%) and fuel oil combustion (0.35%). The lack of source profile for biomass or open burning in Bangkok resulted in much lower predicted contribution of this source when compared to that from FA–MR. When apply this CMB₈ model with daily ambient data, the result revealed that one fourth of daily CMB₈ source apportionment had high value of ² (>4). These exceedance values of Chi² also point out that one of the selected sources (biomass burning) may not be the true contributing sources. Presumably, accurate biomass burning source profile is needed to improve the CMB calculation of source contributions for particulate matter in Bangkok metropolitan area.     

Application of an ISCST3 model for predicting urban air pollution in the Izmir metropolitan area

A Gaussian atmospheric dispersion model, Industrial Source Complex Short Term (ISCST3), was used to estimate ground-level concentrations of sulphur dioxide (SO₂) emitted from source categories of industrial and domestic heating in the city of Izmir, Turkey. Predictions were estimated for the year 2000 across a study area of 80 km x 100 km. Statistical analyses were carried out to evaluate the model performance by comparing predicted and observed SO₂ concentrations at four ambient air quality monitoring stations using two main methods root mean square error (RMSE) and an index of agreement (d). The results showed that industry was found as the most air-polluting sector and industries located at outside of the metropolitan area were found to carry important risks for urban air quality. The most polluted area was found at a distance of about 1 km from a major petroleum refinery and a large petrochemical industry.     

A structural decomposition analysis of air pollution from fossil fuel combustion in India

During the last decade, there has been worldwide concern with global climate change, which has been induced by greenhouse gases (GHGs) due to the use of fossil fuels. The CO₂ emissions from fossil fuel combustion have been identified as the single most significant source of GHG emissions into the atmosphere. Realising the need to control and regulate emissions of pollutants, the objective of the present study estimates the trend of CO₂, SO₂ and NO_x between the periods 1991-92 and 1996-97. An input-output structural decomposition analysis approach is used to determine their sources of change. It also provides a set of alternative scenarios for the year 2001-2 and 2006-7. The sources of changes in the amount of CO₂, SO₂ and NO_x emissions are categorised into four factors: the ecoefficiency, the structure of production, the structure of demand, and the volume of demand. Results indicate that the electricity sector contributes more towards direct, as well as indirect, emission coefficients. The petroleum product sector also contributes more in this respect. The dominant role is played by the structure of demand and the volume of demand.