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.     

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.     

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.     

Annual simulation of secondary pollution over northern Italy

A secondary pollution modelling system for simulating airborne dispersion and chemical reactions is applied over a regional scale domain located in the North-West of Italy, where urban and industrial areas are present. It was found an overestimation of NO₂ in the urban areas, probably due to an underestimation of the vertical diffusivity; the analysis of O_X confirms that the discrepancies in O₃ and NO₂ are mainly due to local scale effects; the model shows a general underestimation of the observed PM10 concentrations due to the uncertainties in the emission inventories, spatial resolution, and the adopted aerosol modelling approach.     

Sampling errors in the study of acid gases and anion species in atmospheric aerosols

Atmospheric acid aerosols were sampled by two annular denuder systems (ADS) and a micro-orifice uniform deposit impactor (MOUDI) at a traffic site in central Taiwan. Theoretical analysis showed that the relative artifact for HNO₃ gas sampling was about 0.53 when the initial HNO₃ concentration was under 0.2 µg/m³ and should be considered carefully. The concentrations of gaseous acid at the traffic sampling site were higher than those in the other study. The size distributions of acid aerosols were unimodal for Cl^-, NO₂^-, and NO₃^-, and bimodal for SO₄^2-. The dominant acid ions in particles less than 18 µm were SO₄^2-, NO₃^-, NO₂^- and Cl^-.     

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.     

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.     

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.     

Characteristic study of particulates and metallic elements at an urban sampling site in Taichung, central Taiwan

Atmospheric total suspended particulate concentrations and metallic element concentrations were measured at three locations, characteristic of urban, suburban and rural sites. The sampling period was from July 2000 to August 2000. The results indicated that the urban sampling site had the highest total suspended particulate concentrations (average 108.61μ1m3), followed by the suburban site (average 60.11μ1m3) and the rural site (average 53.31μ1m3). The average PM_2.5 concentrations (24.11μ1m3) were higher than the PM_2.5-10 concentrations (12.81μ1m3) at the urban site. The average distributed ratios for PM_2.5/PM_2.5-10 were about 1.29, 1.53, 0.12, 1.12 and 2.31 for Pb, Zn, Fe, Ni and Cr, respectively. The average total suspended particulate mass ratios for daytime and nighttime were about 1.72. As for the elements Cu, Pb, Zn, Fe, Ni and Cr, these ratios were about 0.63, 0.97, 0.54, 1.66, 0.53 and 1.12, respectively. The total suspended particulate daytime concentrations of Pb and Zn were positively correlated (R = 0.925) at the urban sampling site. The elements Ni and Cr were positively correlated both during the daytime (R = 0.648) and the nighttime (R = 0.511), revealing that they came from the same emission source during daytime and nighttime, at the urban sampling site.     

Monitoring of phytoplankton biomass and nutrients in a polluted stream

The spatial and temporal variations in the concentrations of nutrients (NH₄⁺, NO₂⁻, PO₄³⁻, SiO₄⁻) and chlorophyll a were monitored simultaneously in a slow-flowing watercourse (Saricay Stream, Turkey), which runs in a rural–urban gradient. Chlorophyll a concentrations ranged between 0.044 μg l^-1 and 206.15 μg l^-1 and, in general, the higher concentrations of chlorophyll a and ammonium were measured downstream of the raw sewage outfalls. Nitrate was by far the most abundant form of inorganic nitrogen, and its concentration ranged between 411.71 μM and 87.25 μM. Silicates and phosphates were always potentially limiting to biomass relative to nitrogen. Agricultural run-off and point discharges from urban sources greatly affected the chemical composition of the water in the Saricay Stream and drove the system towards eutrophication.     

Diurnal and seasonal variations of carbon monoxide and nitrogen dioxide in Delhi city

Motor vehicle exhaust emissions are one of the major causes of air quality deterioration in most of the cities of the developing world. Carbon monoxide (CO) and nitrogen dioxide (NO₂) are significant contributors to this adverse effect on the environment. This study analyses air quality data for three years from 1997 to 1999, at two air quality control regions in Delhi city. The regions are a major traffic intersection and the moderately busy straight Khelgaon Marg road. The data were obtained from the Central Pollution Control Board (CPCB), Delhi. The results show that the highest ground-level concentrations of CO and NO₂ occurred during winter (November to March) and the lowest during the tropical monsoon period (July to September) at both regions. Typical average monthly, weekly and diurnal cycles of CO at both regions have also been analysed, and show that CO concentrations are higher at the intersection than along the road. Further, the monthly average NO₂ concentrations were also found to be higher at the intersection.     

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.     

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.     

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.     

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.     

Trends of exhaust emissions from gasoline motor vehicles in the metropolitan area of Mexico city

Light duty gasoline vehicles account for most of CO, hydrocarbons and NO_x emissions to the urban environment in the metropolitan area of Mexico City. In order to ameliorate air pollution, several control measures have been imposed in the last decade, such as: up-grade of gasoline's quality, stringent environmental standards, and catalytic converters. On the other hand and from the beginning of 2001, Tier I emission standards became mandatory for all new model year sold in the country. Car manufacturers in Mexico do not guarantee the performance of their exhaust emissions systems for a given mileage. In this work, we present results on brand new vehicles that indicate that NO_x emission factors, though they are within the Tier I standard, deteriorate rapidly with the travelled distance (mileage).     

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.     

Limited provision of roads as a bottleneck on vehicle CO2 emissions in Asia: an international comparison of national trends

This paper explores the relationship between road infrastructure, economic growth and road CO₂ emissions. The basic premise is that many developing nations have achieved sufficient wealth to generate substantial demand for road vehicles, but that actual use is constrained by limited provision of surfaced roads. Our main result is that for comparable levels of income (GDP/capita), CO₂ emissions per length of paved road are far higher in rapidly developing Asia as compared to the USA. These findings suggest existence of an 'infrastructure bottleneck', that when relieved, may influence the future trajectory of road transport CO₂ emissions in developing Asia.     

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.