Kocaeli’de evlerde, ofislerde ve okullarda iç ortam hava kalitesinin belirlenmesi

TÜBİTAK ÇAYDAG01.01.2008Bu çalışmada, Kocaeli’de farklı bölgelerde ve farklı mikroçevrelerde (ev, okul, ofis), iç ve dış ortamda yapılan örneklemeler ile aktif ve pasif örnekleme ve ölçüm teknikleri kullanılarak 2 farklı partikül fraksiyonunda (PM2.5 ve PM10) 16 ağır metal (Al, As, Ca, Cr, Cu, Fe, K, Mg, Mn, Ni, Pb, S, Si, Ti, V ve Zn), uçucu organik bileşikler (UOB’ler), SO2, NO2 ve O3 konsantrasyonları belirlenmiştir. Ayrıca, iç ortamda ölçülen konsantrasyonlarla maruziyet arasındaki ilişkiyi kurabilmek için, kişisel örnekleyiciler kullanılarak kişisel maruziyet düzeyleri de belirlenmiştir. NO2 için İç Ortam/Dış Ortam konsantrasyon oranlarının evlerde her 2 mevsimde de okullar ve ofislere nazaran yüksek bulunması evlerin iç ortamlarında NO2 kirletici kaynaklarının ofis ve okullara oranla daha baskın olduğu göstermektedir. İç Ortam/Dış Ortam oranlarının 1’in çok altında bulunması O3 ve SO2’in dış ortam kaynaklı bir kirletici olduğunu ve iç ortamlarda önemli bir kaynağının bulunmadığını göstermektedir. PM2.5 fraksiyonundaki toprak kaynaklı elementlerin iç ve dış ortam konsantrasyonlarının yüksek düzeylerde bulunması bu elementlerin iç ortamlara taşınımının yüksek olduğunu göstermektedir. PM2.5 kişisel maruziyet düzeylerinin As, S, V, Cu ve Cr gibi yanma kaynaklı elementler için iç ortam maruziyet düzeylerinden 2–6 kat daha yüksek olması ve bazı mevsimsel farklılıklar bulunmasına rağmen İç Ortam/Dış Ortam oranlarının genellikle 0.3–0.7 aralığında bulunması gözlenen yüksek kişisel maruziyet düzeylerinde dış ortamların etkisini göstermektedir. PM10 partikül fraksiyonunda belirlenen ağır metallerin büyük bir bölümü için İç Ortam/Dış Ortam oranlarının 1’den küçük bulunması dış ortam kirletici kaynaklarının iç ortam kirletici kaynaklarına daha baskın olduğunu göstermektedir. En yüksek UOB kirlilik düzeylerine örneklenen kişilerde rastlanırken bunu iç ortam ve dış ortam UOB kirlilik düzeyleri takip etmiştir. Her 2 mevsimde de toluen ev, ofis ve okullardaki UOB kirlilik düzeylerine en çok katkıda bulunan bileşik olurken onu etilbenzen, m,p-ksilen, stiren, nonan, hegzan, benzen, o-ksilen ve heptan bileşikleri takip etmektedir. Kentsel alanlarda elde edilen toplam UOB konsantrasyonlarının endüstriyel alanlarda elde edilen değerlerle uyum içinde bulunmuştur. Trafiğin belirteci olan bileşikler (BTEX, 1,2,4-trimetilbenzen) kentsel alanlarda yüksek bulunurken petrokimyanın belirteci olan hexane ve heptane bileşikleri endüstrinin yoğun olduğu alanlarda yüksek bulunmuştur. Ayrıca kentsel ve endüstriyel alanlarda elde edilen UOB konsantrasyonlarının sanayii ve trafikten uzak alanlarda elde edilen konsantrasyonlardan yüksek olması trafik ve sanayiinin tesbit edilen UOBlere olan katkısının ne kadar yüksek olduğunu göstermektedir. İç ortam, dış ortam ve kişisel maruziyet kirlilik düzeylerine etki ederek hava kalitesine olumsuz yönde katkıda bulunan kirletici kaynakların belirlenmesi amacıyla Pozitif Matris Faktörizasyonu (PMF) reseptör modelleme tekniği kullanılmıştır. PMF modellemesi, korelasyon analizi, iç ortam/dış ortam oranları, mikroçevre karakteristikleri, anketler ve zaman aktivite çizelgeleri incelenen kirleticilerin en önemli emisyon kaynaklarının endüstri, trafik ve sigara kullanımı olduğunu göstermektedir. İç ortam, dış ortam ve kişisel maruziyet düzeylerinin dünyanın diğer bölgelerinde yapılan çalışmalarda raporlanan düzeyler ile kıyaslanabilir olduğu bulunmuştur. Kişisel maruziyet konsantrasyonları kullanılarak çalışmada incelenen inorganik ve organik kirleticilerden kaynaklanan sağlık riski değerlendirmesi yapılmıştır. Ev, ofis ve okullarda örneklenen kişiler için hesaplanan “Toplam Kanser Riski” ve “Toplam Tehlike İndeksi” değerleri hem ortalama konsantrasyonlar hem de en kötü senaryo göz önüne alınarak incelendiğinde en yüksek risk altında bulunan kişilerin ev hanımları olduğu bunları öğretmenler ve ofis çalışanlarının takip ettiği söylenebilir. Değerlendirme kentsel, endüstriyel, endüstri ve trafikten uzak alanlar için yapıldığında her 3 alanda da yaşayan kişilerin birbirine yakın ve yüksek kanser riski taşıdıkları söylenebilir. Aynı değerlendirme sigara kullanan ve kullanmayan kişiler için yapıldığında sigara kullanan kişilerin kullanmayanlara nazaran yaklaşık %50 daha fazla kanser riski taşıdıkları gözlenmiştir.In this study, indoor and outdoor environment samples were taken from different regions and microenvironments (home, school, office) in Kocaeli. Through active and passive sampling and measurement techniques, 16 heavy metals (Al, As, Ca, Cr, Cu, Fe, K, Mg, Mn, Ni, Pb, S, Si, Ti, V and Zn) at 2 different particle fractions (PM2.5 and PM10), volatile organic compounds (VOCs), and SO2, NO2 and O3 concentrations were determined. Moreover, in an effort to establish the relationship between exposure and the indoor concentrations measured, personal samplers were used to determine personal exposure levels. Indoor/outdoor concentration ratios for NO2 were higher in homes than in schools or offices in both summer and winter, which shows that sources of NO2 pollutants in indoor environments of homes are more dominant than those found in offices or schools. The indoor/outdoor ratios were far below 1, indicating that O3 and SO2 are pollutants originating from outdoor environments and that they do not have significant sources in indoor environments. The presence of high levels of indoor and outdoor concentrations of crustal elements at PM2.5 fractions indicates that these elements are transported into indoor environments at high levels. PM2.5 personal exposure levels were 2–6 times higher than indoor levels for combustion-related elements such as As, S, V, Cu and Cr, and although there were some seasonal differences, the indoor/outdoor environment ratios generally ranged between 0.3–0.7 and indicated the effect of outdoor environments on the observed high personal exposure levels. The indoor/outdoor ratios for a major portion of the determined heavy metals at PM10 particle fractions were smaller than 1, showing that outdoor pollutants are more dominant than indoor pollutants. The highest VOC pollution levels were encountered in individuals in the sample, and this was followed by VOC pollution levels in indoor and outdoor environments. In both seasons, toluene levels were the highest pollutants for homes, offices and schools, followed by ethylbenzene, m/p-xylene, styrene, nonane, hexane, benzene, o-xylene and heptane. Total VOC concentrations obtained from urban areas were consistent with values obtained from industrial areas. Components that are indicators of traffic (BTEX, 1,2,4-trimethylbenzene) were measured at high levels in urban areas, while hexane and heptane components, which are indicators of petrochemistry, were recorded at high levels in high- industry areas. Moreover, VOC concentrations obtained from urban and industrial areas were higher than concentrations found in areas far from industry and traffic, which demonstrates the high contribution of traffic and industry to measured VOCs. This study investigated the summer and winter concentrations of selected pollutants and the relationship between indoor and outdoor environments. In order to determine pollutant sources that negatively contribute to air quality by affecting the degree of indoor, outdoor and personal exposures, the Positive Matrix Factorization (PMF) receptor modeling technique was used, which is a multivariate statistical analysis method. PMF, correlation analyses, indoor/outdoor ratios, microenvironment characteristics, responses to questionnaires, and time activity information suggested that industry, traffic and smoking represent the main emission sources of pollutants investigated. Indoor, outdoor and personal exposure concentration values were compared to values measured in different parts of the world, thereby evaluating consistency with the observed pollution level. Based on personal exposure concentrations, an assessment was conducted concerning the health risks associated with the inorganic and organic pollutants investigated in this study. When the calculated values for “Total Health Risk” and “Total Hazard Index” for people sampled in homes, offices and schools were examined by considering both the average concentrations and the worst scenarios, it was revealed that housewives are at the highest risk, followed by teachers and office workers. An examination of urban, industrial and far from urban, industrial and traffic areas revealed that people living in all of these three areas are subjected to high cancer risks, which are at similar levels. When the same evaluation was carried out for smokers and non-smokers, it was observed that smokers have a 50% higher risk of cancer compared to non-smokers

Ankara ve Ottawa atmosferlerindeki organik kirleticilerin mevsimsel değişiklikleri ve kaynaklarının belirlenmesi

This study aimed at providing a thorough understanding of temporal and spatial variations of VOCs and underlying factors in different microenvironments in two different urban atmospheres, with different degrees of regulatory enforcement. The VOC data were collected in field campaigns conducted in Ankara, Turkey, and Ottawa, Canada over the years 2000-2004. Insight into the sources of VOCs in different urban atmospheres was sought by using three commonly used receptor models namely; Positive Matrix Factorization (PMF), Chemical Mass Balance (CMB) Model and Conventional Factor Analysis (CFA). Motor vehicle related source profiles were developed to use in receptor modeling. Motor vehicles are the most abundant VOC sources with about 60% and 95% contributions to ambient levels in Ankara and Ottawa, respectively. Residential heating (31%) during winter season, biogenic (9%) and architectural coating (12%) emissions during summer season and solvent use (about 12%) emissions are the next abundant VOC sources in Ankara. In addition, a new method to estimate the contribution of sources from wind sectors in urban atmosphere was developed and implemented in this study. The comparison of the results of these two cities demonstrated the influence of control measures on ambient levels and sources of VOCs observed in different urban atmospheres. VOC levels in Ankara exceed EU levels and they are about factor of two higher than that are measured in Ottawa owing to lack of implementation of emission control regulations for VOCs in Ankara compared to well adopted regulations in Ottawa.Ph.D. - Doctoral Progra

Spatial and temporal variations in atmospheric VOCs, NO2, SO2, and O3 concentrations at a heavily industrialized region in Western Turkey, and assessment of the carcinogenic risk levels of benzene

Ambient concentrations of volatile organic compounds (VOCs), nitrogen dioxide (NO2), sulphur dioxide (SO2) and ground-level ozone (O3) were measured at 55 locations around a densely populated industrial zone, hosting a petrochemical complex (Petkim), a petroleum refinery (Tupras), ship-dismantling facilities, several iron and steel plants, and a gas-fired power plant. Five passive sampling campaigns were performed covering summer and winter seasons of 2005 and 2007. Elevated concentrations of VOCs, NO2 and SO2 around the refinery, petrochemical complex and roads indicated that industrial activities and vehicular emissions are the main sources of these pollutants in the region. Ozone concentrations were low at the industrial zone and settlement areas, but high in rural stations downwind from these sources due to NO distillation. The United States Environmental Protection Agency's positive matrix factorization receptor model (EPA PMF) was employed to apportion ambient concentrations of VOCs into six factors, which were associated with emissions sources. Traffic was found to be highest contributor to measured ∑VOCs concentrations, followed by the Petkim and Tupras.Median cancer risk due to benzene inhalation calculated using a Monte Carlo simulation was approximately 4 per-one-million population, which exceeded the U.S. EPA benchmark of 1 per one million. Petkim, Tupras and traffic emissions were the major sources of cancer risk due to benzene inhalation in the Aliaga airshed. Relative contributions of these two source groups changes significantly from one location to another, demonstrating the limitation of determining source contributions and calculating health risk using data from one or two permanent stations in an industrial area.TUBITAK (104Y276