Determination of air quality zones in Turkey

In this study, the particulate matter (with an aerodynamic diameter <10 μm; PM₁₀) profile of Turkey with data from the air quality monitoring stations located throughout the country was used. The number of stations (119) was reduced to 55 after a missing data treatment for statistical analyses. First, a classification method was developed based on ongoing national and international (European Commission directives) legislations to categorize air zones into six groups, from a “Very Clear Air Zone” to a “Polluted Air Zone.” Then, a Geographic Information System (GIS)-based interpolation technique and statistical analyses (correlation analysis and factor analysis) were used to generate PM₁₀ pollution profiles of the annual heating time and nonheating time periods. Finally, the coherent air pollution management zones of Turkey, based on air quality criteria and measured data using a GIS-based model supported by statistical analyses, were suggested. Based on the analysis, four hot spots were identified: (i) the eastern part of the Black Sea region; (ii) the northeastern part of inland Anatolia; (iii) the western part of Northeastern Anatolia; and (vi) the eastern part of Turkey. The possible reasons for the elevated PM₁₀ levels are discussed using topographic, climatologic, land use, and energy utilization parameters. Finally, the suggested air zones were compared with the administrative air zones, which were newly developed by the Turkish Ministry of Environment and Forestry, to evaluate the level of agreement between the two.

Implications: The evaluation of air quality profiles of specific regions is important in the development and/or application of an effective air quality management strategy. Factor analysis (FA), together with correlation analysis (CA), provides useful information to classify air pollution management areas over regional networks that have historical time-series air quality data. In this study, which relied on a FA- and CA-based methodology, the coherent air pollution management zones of Turkey after using a GIS-based model were suggested. Policy makers and scientist can use these suggested zones to construct better air quality management strategies.     

Mapping air quality zones for coastal urban centers

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land–sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year’s worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates.

Implications: A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land–sea breeze effects that can be used to manage local air quality in areas of similar microclimates.     

Determination of organic compounds in indoor air with potential reference to air quality

Concentrations of 15 volatile organic compounds have been investigated in the air of two schoolrooms. The chemical analysis included enrichment on porous polymer beads, heat desorption and gas Chromatographic separation on a capillary column connected to either a flame ionization detector or a mass spectrometer. Samples were collected from the indoor air both in the presence and in the absence of the pupils (boys and girls, age 16–19) as well as from the ambient outdoor air. The qualitative composition of indoor and outdoor air was found to be about the same : aliphatic and aromatic hydrocarbons predominate, though indoors the number of compounds detected is larger and the concentrations are higher. Both the number and the concentration increase in the presence of humans. The mean concentrations of acetone and the sum of the concentrations of C₂-alkylbenzenes were 7.7 and 8.2 μg m⁻³ respectively in an unoccupied room and increased to 19.8 and 12.1 μg m⁻³ respectively in an occupied room.     

Evaluation of air quality by passive and active sampling in an urban city in Turkey: current status and spatial analysis of air pollution exposure

Concentrations of air pollutants, nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), ozone (O(3)), particulate matter (PM(2.5) and PM(10)), trace metals, and polycyclic aromatic hydrocarbons (PAHs) were measured in 2008 and 2009 in the city of Eski?ehir, central Turkey. Spatial distributions of NO(2), SO(2), and ozone were determined by passive sampling campaigns carried out during two different seasons with fairly large spatial coverage. A basic population exposure assessment was carried out employing Geographical Information System techniques by combining population density maps with pollutant distribution maps of NO(2) and SO(2). It was found that 95 % of the population is exposed to NO(2) levels close to the World Health Organization guideline value. Regarding SO(2), a large proportion of the population (83 %) is exposed to levels above the WHO second interim target value. Concentrations of all the pollutants showed a seasonal pattern increasing in winter period, except for ozone having higher concentrations in summer season. Daily PM(10) and PM(2.5) concentrations exceeded European Union limit values almost every sampling day. Toxic fractions of the measured PAHs were calculated and approximately fourfold increase was observed in winter period. Copper, Pb, Sn, As, Cd, Zn, Sb, and Se were found to be moderately to highly enriched in PM(10) fraction, indicating anthropogenic input to those elements measured. Exposure assessment results indicate the need for action to reduce pollutant emissions especially in the city center. Passive sampling turns out to be a practical and economical tool for air quality assessment with large spatial coverage.     

Volatile organic compounds in the air of Izmir,Turkey

A sampling program was conducted to determine the ambient VOC levels in the city of Izmir, Turkey during daytime and overnight periods between mid-August and mid-September 1998. Sampling sites were selected at high-density traffic roads and junctions far from stationary VOC sources. Samples were analyzed for benzene, toluene, m, p-xylene and o-xylene (BTX), alkylbenzenes (ethylbenzene, 1,3,5-trimethylbenzene, 1,2,4-trimethylbenzene), n-hexane and, n-heptane. Results were compared with similar data from other cities around the world and for probable health dangers and sources of the compounds. Results of this study indicated that Izmir has rather high ambient BTX concentrations compared to many polluted cities in the world. Toluene was the most abundant VOC in Izmir air and was followed by xylenes, benzene and alkylbenzenes, respectively. All were strongly dependent on the expected daily variations of traffic flow in the city. The concentrations of other VOCs correlated well with benzene concentration at most sampling sites, excluding Gumuldur station indicating that ambient VOC levels were mainly affected by motor vehicle emissions. The toluene-to-benzene ratios for urban and non-urban sites were in good agreement with previously reported values, indicating a good relationship between the motor vehicle emissions and ambient VOC levels.     

Urban air quality

Since 1950 the world population has more than doubled, and the global number of cars has increased by a factor of 10. In the same period the fraction of people living in urban areas has increased by a factor of 4. In year 2000 this will amount to nearly half of the world population. About 20 urban regions will each have populations above 10 million people.Seen over longer periods, pollution in major cities tends to increase during the built up phase, they pass through a maximum and are then again reduced, as abatement strategies are developed. In the industrialised western world urban air pollution is in some respects in the last stage with effectively reduced levels of sulphur dioxide and soot. In recent decades however, the increasing traffic has switched the attention to nitrogen oxides, organic compounds and small particles. In some cities photochemical air pollution is an important urban problem, but in the northern part of Europe it is a large-scale phenomenon, with ozone levels in urban streets being normally lower than in rural areas. Cities in Eastern Europe have been (and in many cases still are) heavily polluted. After the recent political upheaval, followed by a temporary recession and a subsequent introduction of new technologies, the situation appears to improve. However, the rising number of private cars is an emerging problem. In most developing countries the rapid urbanisation has so far resulted in uncontrolled growth and deteriorating environment. Air pollution levels are here still rising on many fronts.Apart from being sources of local air pollution, urban activities are significant contributors to transboundary pollution and to the rising global concentrations of greenhouse gasses. Attempts to solve urban problems by introducing cleaner, more energy-efficient technologies will generally have a beneficial impact on these large-scale problems. Attempts based on city planning with a spreading of the activities, on the other hand, may generate more traffic and may thus have the opposite effect.     

Assessment of air quality benefits from national air pollution control policies in China. Part II: Evaluation of air quality predictions and air quality benefits assessment

Following the meteorological evaluation in Part I, this Part II paper presents the statistical evaluation of air quality predictions by the U.S. Environmental Protection Agency (U.S. EPA)’s Community Multi-Scale Air Quality (Models-3/CMAQ) model for the four simulated months in the base year 2005. The surface predictions were evaluated using the Air Pollution Index (API) data published by the China Ministry of Environmental Protection (MEP) for 31 capital cities and daily fine particulate matter (PM_2.5, particles with aerodiameter less than or equal to 2.5 μm) observations of an individual site in Tsinghua University (THU). To overcome the shortage in surface observations, satellite data are used to assess the column predictions including tropospheric nitrogen dioxide (NO₂) column abundance and aerosol optical depth (AOD). The result shows that CMAQ gives reasonably good predictions for the air quality.The air quality improvement that would result from the targeted sulfur dioxide (SO₂) and nitrogen oxides (NO_x) emission controls in China were assessed for the objective year 2010. The results show that the emission controls can lead to significant air quality benefits. SO₂ concentrations in highly polluted areas of East China in 2010 are estimated to be decreased by 30–60% compared to the levels in the 2010 Business-As-Usual (BAU) case. The annual PM_2.5 can also decline by 3–15 μg m^?3 (4–25%) due to the lower SO₂ and sulfate concentrations. If similar controls are implemented for NO_x emissions, NO_x concentrations are estimated to decrease by 30–60% as compared with the 2010 BAU scenario. The annual mean PM_2.5 concentrations will also decline by 2–14 μg m^?3 (3–12%). In addition, the number of ozone (O₃) non-attainment areas in the northern China is projected to be much lower, with the maximum 1-h average O₃ concentrations in the summer reduced by 8–30 ppb.     

Interaction between air pollution and meteorologicalparameters 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.     

Inherent uncertainty in air quality modeling

This paper summarizes the discussions of a working group that was charged with the task of examining inherent uncertainty in air quality modeling. The major topics of the paper are:

• 1.1. Definition of inherent uncertainty in air quality models;
• 2.2. Determination of inherent uncertainty;
• 3.3. Role of inherent uncertainty in model evaluation.

The concepts introduced here are illustrated through a numerical simulation with Gifford's fluctuating plume model.     

Association between air quality and quality of life

Air quality—or its converse, air pollution—is a significant risk factor for human health. Recent studies have reported association between air pollution and human health. There are numerous diseases that may be caused by air pollution such as respiratory infection, lung cancer, cardiovascular disease, chronic obstructive pulmonary disease, and asthma. In this study, the relationship between air quality and quality of life was examined by using canonical correlation analysis. Data of this study was collected from 27 countries. WHO statistics were used as the main source of quality of life data set (Y variables set). European Environment Agency statistics and (for outdoor air-PM10) WHO statistics were used as the main source of air quality data set (X variables set). It is found that there are significant positive correlation between air quality and quality of life.     

interpretation of air quality data with respect to the national ambient air quality standards

San Diego Gas &; Electric has developed a quality assurance program for continuous emission monitors (CEM). Extractive, rather than in situ, monitors were selected as a result of an in-house evaluation program. Two extractive systems have been certified and a good operating and maintenance record has been established on these systems. A successful program requires the involvement and support of all affected personnel. It is desirable to have one or two key personnel coordinate the development of the program. It is also highly desirable to have good in-house source testing capabilities.     

Analysis of atmospheric conditions during air pollution episodes in Ankara, Turkey

This paper presents a detailed analysis of the meteorological conditions that are associated with strong air pollution episodes in Ankara, Turkey. Based on climatological and air quality data [SO2 and TSP (total suspended particulates)] obtained for the winter months during 1989-1994, the analysis showed that the presence of weak atmospheric pressure gradients and warm air advection were the most important factors leading to high SO2 and TSP concentrations. In addition, the onset of the high air pollution episodes was generally associated with a trend toward negative vorticity at the 850-hPa level.     

Sequential box models for indoor air quality: Application to airliner cabin air quality

In this paper we present the development and application of a model for indoor air quality. The model represents a departure from the standard box models typically used for indoor environments which has applicability in residences and office buildings. The model has been developed for a physical system consisting of sequential compartments which communicate only with adjacent compartments. Each compartment may contain various source and sink terms for a pollutant as well as leakage, and air transfer from adjacent compartments. The mathematical derivation affords rapid calculation of equilibrium concentrations in an essentially unlimited number of compartments. The model has been applied to air quality in the passenger cabin of three commercial aircraft. Simulations have been performed for environmental tobacco smoke (ETS) under two scenarios, CO₂ and water vapor. Additionally, concentrations in one aircraft have been simulated under conditions different from the standard configuration. Results of the simulations suggest the potential for elevated concentrations of ETS in smoking sections of non-air-recirculating aircraft and throughout the aircraft when air is recirculated. Concentrations of CO₂ and water vapor are consistent with expected results. We conclude that this model may be a useful tool in understanding indoor air quality in general and on aircraft in particular.     

Application of back-trajectory techniques to the delimitation of urban clean air zones

Following a request by environmental authorities in New Zealand, atmospheric modelling has been applied to delimitation of clean air zones for urban areas. This approach involved the integration of a kinematic trajectory model with an atmospheric mesoscale model to identify the spatial extent of the catchment of air affecting air pollution concentrations in Christchurch on nights of high air pollution. The Regional Atmospheric Modelling System (RAMS) was configured for the region and idealised simulations performed to obtain predicted wind fields for synoptic situations typical of winter smog events. The predicted surface wind fields on two grids, with horizontal resolutions of 1.5 and 0.5 km, respectively, were then used to derive back-trajectories from the late evening peak of pollution over the central city (around 2200 NZST) to the time at which people tend to first light their domestic fires (around 1800 NZST). The results indicate that although winds are often light, the air tends to travel from a significant distance outside the city boundary over this time period. In particular, cold air typically travels up to 20 km from the Canterbury Plains to the west into the city during these air pollution events, as well as from small valleys in the Port Hills to the south of the city. This research illustrates the significance of upstream sources of air for providing relatively clean air to the city, and acting as buffer zones. It is, therefore, possible to identify the area around the city to which urban air quality is particularly sensitive. This area could either be designated as a buffer zone, or included within the clean air zone of the city. This technique also provides a useful tool for identifying the role of different components of the local wind field responsible for air pollution dispersion and transport in different parts of the area.     

Indoor air quality and health

During the last two decades there has been increasing concern within the scientific community over the effects of indoor air quality on health. Changes in building design devised to improve energy efficiency have meant that modern homes and offices are frequently more airtight than older structures. Furthermore, advances in construction technology have caused a much greater use of synthetic building materials. Whilst these improvements have led to more comfortable buildings with lower running costs, they also provide indoor environments in which contaminants are readily produced and may build up to much higher concentrations than are found outside. This article reviews our current understanding of the relationship between indoor air pollution and health. Indoor pollutants can emanate from a range of sources. The health impacts from indoor exposure to combustion products from heating, cooking, and the smoking of tobacco are examined. Also discussed are the symptoms associated with pollutants emitted from building materials. Of particular importance might be substances known as volatile organic compounds (VOCs), which arise from sources including paints, varnishes, solvents, and preservatives. Furthermore, if the structure of a building begins to deteriorate, exposure to asbestos may be an important risk factor for the chronic respiratory disease mesothelioma. The health effects of inhaled biological particles can be significant, as a large variety of biological materials are present in indoor environments. Their role in inducing illness through immune mechanisms, infectious processes, and direct toxicity is considered. Outdoor sources can be the main contributors to indoor concentrations of some contaminants. Of particular significance is Radon, the radioactive gas that arises from outside, yet only presents a serious health risk when found inside buildings. Radon and its decay products are now recognised as important indoor pollutants, and their effects are explored. This review also considers the phenomenon that has become known as Sick Building Syndrome (SBS), where the occupants of certain affected buildings repeatedly describe a complex range of vague and often subjective health complaints. These are often attributed to poor air quality. However, many cases of SBS provide a valuable insight into the problems faced by investigators attempting to establish causality. We know much less about the health risks from indoor air pollution than we do about those attributable to the contamination of outdoor air. This imbalance must be redressed by the provision of adequate funding, and the development of a strong commitment to action within both the public and private sectors. It is clear that meeting the challenges and resolving the uncertainties associated with air quality problems in the indoor environment will be a considerable undertaking.