ABSTRACT It is important to improve ambient air quality by reducing the emission from mobile sources. In order to investigate the characteristics of mobile sources, the statistic of traffic flow and the measurement of suspended particles were conducted in the Gonguan air quality monitoring station of Miaoli County in this investigation. Through chemical mass balance (CMB) receptor model and backward trajectory model, the location and contribution of emission sources were further identified. Accordingly, the improvement strategies for mobile sources were further proposed to improve local ambient air quality. In order to know the traffic flow variability of motor vehicles, passenger cars, motorcycle, heavy-duty diesel trucks, and buses were recorded every 15 minutes by a video camera for both weekend and weekdays. In the meantime, TSP and PM10 were simultaneously collected with high-volume samplers. The metallic content and water-soluble ionic species of particulate matter were analyzed with an inductively coupled plasma-atomic emission spectrophotometer (ICP- AES) and an ionic chromatography (IC). Chemical composition of suspended particles was then be used for source apportionment with the CMB model. Finally, the improvement strategies for mobile source management were further proposed through the correlation of traffic flow and vehicle emission rate. The results showed that the PM10/TSP ratios of suspended particles collected at the rooftop of a four-floor building was higher than those sampled at the air quality monitoring station for all quarters except the third quarter. PM>10 is the main factor for the concentration difference of suspended particles sampled on the rooftop of the building as well as at the monitoring station. Results from traffic flow records showed that passenger cars were the major source contributing greatly to the traffic flow, while no significant variation of buses was observed in the traffic flow. The linear regression of PM>10 concentration and vehicles for different wind directions (i.e. northwest, southwest and northeast) was undertaken. The results showed that, when the winds were blown from the northwest and southwest, the determination coefficients (R2) of the regression were 0.1226 (passenger cars), 0.4821 (motorcycles), 0.1014 (heavy-duty trucks), 0.3113 (buses), and 0.1919 (total traffic flow) respectively. It was 0.6140 (passenger cars), 0.6227 (motorcycles), 0.7761 (heavy-duty trucks), 0.2111 (buses), and 0.6309 (total traffic flow), respectively, for the northeast winds. It concluded that the traffic flow has significant influence on the concentration of suspended particle at the downwind sites. Among the vehicles, heavy-duty trucks played a key role. Consequently, reducing truck flow has to be paid more attention for the improvement of ambient air quality. During the sampling period, Ca, Fe, and Al were the most abundant metals of suspended particles, while Mg, K, Zn, and Cu ranked the second. Besides, the metallic contents of suspended particles sampled at the rooftop were generally lower than those collected at the monitoring station. It suggested that street dusts had major contribution to Gonguan air quality monitoring station. Among the water-soluble ionic species, sulfate (SO42-), nitrate (NO3-), and ammonium (NH4+) were major anions, converting mainly from SO2, NOx, and NH3. The results showed that the metallic contents in the second quarter were higher than that in the fourth quarter. However, an opposite trend was observed for anions. The Back Trajectory Model and CMB were applied to analyze the suspended particle. The results showed that the seasonal variation of air pollutants was also affected by the monsoon. Though air pollutants emitted from the nearby waste incinerators and industrial districts could be transported to the sampling site, resulting in unavoidable influence on suspended particles, tail gas and fugitive dusts emitted from vehicles were the most important sources contributed to the ambient air quality. The results indicated that motor vehicles were the major source of ambient suspended particles on the road sites. Therefore, the reduction of traffic emission should be the first step of the improvement strategies for ambient air quality. Especially, the emission of road dusts resulting from the drive-through of heavy-duty trucks should be paid more attention. This study proposed two strategies for improving ambient air quality: one for raising the road serving level and the other for reducing vehicles on road at the traffic crowd section. After the road serving level was improved, the TSP, NOx, CO and THC were respectively decreased about 41, 5,765, 316, and 62 g/day. The concentration of TSP, NOx, CO, and THC was respectively decreased about 95.66 £gg/m3, 38.59 ppb, 1.93 ppm, and 1.90 ppm. After carrying out special vehicle on the road control strategy, TSP, NOx, CO, and THC could be respectively decreased about 2,136, 19,291, 169,843, and 3181g/day. The concentrations of TSP, NOx, CO, and THC were respectively decreased about 96.03 £gg/m3, 52.25 ppb, 2.05ppm and 1.69ppm.. Thus, ambient air quality can be effectively improved if the heavy-duty trucks can be controlled during the rush hour. Furthermore, a substitute road for heavy-duty trucks is another option for the improvement of ambient air quality.

The high-volume air sampling (PS-1) and micro-orifice uniform deposit impactor (MOUDI) were used to measure the concentrations of polycyclic aromatic hydrocarbons (PAHs) in the atmosphere for four seasons at Zuoying and Siaogang in Kaohsiung city, together with the size distributions. Also, the CMB (Chemical Mass Balance) receptor model was employed to determine the potential sources of PAHs. The results show that the highest concentrations of PAHs occurred in winter, being 143.9 ng/m3 and 182.9 ng/m3 at Zuoying and Siaogang, respectively; while the lowest concentrations of PAHs occurred in summer, being 81.4 ng/m3 and 95.2 ng/m3. The low-weight PAHs in the two sites were abundant in gaseous phase, being 55.89 - 95.89 % and 67.07 - 96.61 % at Zuoying and Siaogang, respectively. Meanwhile, the high-weight PAHs were almost present in particulate phase, being 55.24 - 83.50 % and 46.87 - 77.26 % at Zuoying and Siaogang, respectively. The sizes of 50th percentile of cumulative size distribution, d50 of Zuoying and Siaogang were 0.89 £gm and 0.35 £gm, respectively. Hence, most atmospheric PAHs existed in fine-particle ranges (¡Õ1.0£gm). The results of by CMB receptor modeling indicated that the major sources of pollution was exhaust emission (49 - 62 %) in Zuoying, and was burning source (49 - 64 %) in Siaogang.

The concentrations of seventy-one hydrocarbons (HC) from C2 to C15 were measured simultaneously at two sites in Kaohsiung city in the morning (07-10), the afternoon (13-16), and the evening (18-21) on 14 days in spring 2003. Results show that the most abundant species of Kaohsiung¡¦s air is toluene (43.36-54.49 £gg m-3), followed by i-pentane, 1,2,4-trimethylbenzene, benzene, n-butane, propane and acetylene, in the range 10.36¡V17.11 £gg m-3. The concentrations of 14 halocarbons are in the range 0.25¡V4.57 £gg m-3. Alkanes (around 44.8%) represent the largest proportion of the total HC, followed by aromatics (35.1%), alkenes (15.5%) and halocarbons (5.4%). The afternoon HC concentrations are much lower than those in the morning and at night, due to relatively intense photochemical reaction and favorable dispersion conditions from noon to afternoon. Notable increases in daily HC concentrations are consistent with high temperature, and low HC concentrations on Sunday coincide with low traffic volume. Photochemical activity is investigated, and HC concentrations are found to decline as the NO2/NOx ratio increases. Correlation analyses imply that vehicle exhaust is the dominant source of atmospheric hydrocarbons in Kaohsiung. The profiles of traffic exhausts were also measured for 25 HC species during the morning and afternoon rush hours on four different days in all three traffic tunnels in Kaohsiung City. Results show that VOC concentrations increase with traffic flow rate, and emission profiles in the three tunnels are mostly in the range C2 ¡V C6. Besides the traffic conditions and vehicle type, the pattern of emissions in each tunnel was also influenced by other factors, such as vehicle age, nearby pollution sources, and the spatial or temporal variation of HC in the urban atmosphere. The ozone formation potential (OFP) in each tunnel was assessed based on the maximum incremental reactivities of the organic species, demonstrating that OFP increases with traffic flow rate. Vehicle distribution influences the contributions of organic group to OFP in a tunnel. Meanwhile, when ranked in descending order of contribution to OFP in all tunnels, the organic groups followed the sequence alkenes, aromatics, and alkanes. The possible source categories affecting the atmospheric HC species were further analyzed using factor analysis. Results showed that the major sources of ambient HC at the Nan-Chie and Hsiung-Kong sites are: vehicle exhaust, petrol/diesel exhaust, industrial processes (for example, plastic/rubber process), combustion exhaust, solvent fugitive or business/consume exhaust. Based on the results of factor analysis, source profiles (or fingerprints) were selected and receptor modeling was conducted based on chemical mass balance (CMB). Results of receptor modeling indicated that, at Nan-Chie site, vehicle exhaust (46.33% and 56.36%) represent the largest proportion of total HC, followed by industrial processes (29.63% and 22.37%) in the morning (07-10) and the evening (18-21), respectively; but were industrial process (40.39%) and solvent fugitive exhaust (30.61%) in the afternoon (13-16). Similarly at Hsiung-Kong site, vehicle exhaust (around 46.19% and 49.29%) represent the largest proportion of total HC, followed by industrial processes (23.19% and 26.11%) in the morning and evening, respectively; but were solvent fugitive exhaust (38.85%), vehicle exhaust (28.95%) and industrial process (25.19%) in the afternoon. It is evident that relatively low traffic volumes in the afternoon at both sites reduce the contribution of traffic exhaust to ambient HC.

In this study, the occurrence and distribution of polychlorinated biphenyls (PCBs) were investigated via sampling studies conducted around a thermal power plant (Seyit&ouml / mer, K&uuml / tahya), a scrap metal yard (Kizilirmak, Kirikkale), transformer repair and maintenance facility (Lake Eymir, Ankara), and two organized industrial districts (izmit and Mersin), and 120 samples composed mainly of sediments were collected from those sites. Total PCBs ranged from not detected to 385 ng/g for all samples. Analysis of samples indicates enrichment of PCBs with special emphasis to sediments collected around the Seyit&ouml / mer thermal power plant. Congener specific results indicate domination of profiles by penta- and hexa-chlorobiphenyls. Overall, the PCB concentrations observed in sampling sites are comparable to the background levels of soil/sediments around the world. To identify relevant pollution sources, congener specific data were further evaluated in the subsequent process of source apportionment using Chemical Mass Balance (CMB) receptor model. A general overview of the source apportionment results indicate that equipments (transformers and capacitors) mainly used in the energy generation/transmission and high energy consuming industries as the major PCB sources. PCBs used in open applications were also predicted as sources depending on site characteristics. Overall, indications of contaminated sites are evident in a number of locations / yet, no major contamination is evident in any media according to the current relevant national regulatory actions. However, findings of this study suggest that, over expanded time exposure, threat to the environment and human health may be of concern.

This study examines the application of two receptor models, namely Positive Matrix Factorization (PMF) and Chemical Mass Balance (CMB), on the investigation of sites contaminated with PCBs. Both models are typically used for apportionment of pollution sources in atmospheric pollution studies, however have gained popularity in the last decade on the investigation of PCBs in soil/sediments. The aim of the study is four-fold / (i) to identify the status of PCB pollution in Lake Eymir area via sampling and analysis of PCBs in collected soil/sediment samples, (ii) to modify the CMB model software in terms of efficiency and user-friendliness (iii) to apply the CMB model to Lake Eymir area PCB data for apportionment of the sources as well as to gather preliminary information regarding degradation of PCBs by considering the history of pollution in the area (iv) to explore the use of PMF for both source apportionment and investigation of fate of PCBs in the environment via use of Monte-Carlo simulated artificial data sets. Total PCB concentrations (Aroclor based) were found to be in the range of below detection limit to 76.3 ng/g dw with a median of. 1.7 ng/g dw for samples collected from the channel between Lake Mogan and Lake Eymir. Application of the CMB model yield contribution of highly chlorinated PCB mixtures (Aroclor 1254 and Aroclor 1260 / typically used in transformers) as sources. The modified CMB model software provided user more efficient and user friendly working environment. Two uncertainty equations, developed and existing in literature, were found to be effective for better resolution of sources by the PMF model.

The high-volume air sampling (PS-1) and micro-orifice uniformdeposit impactor (MOUDI) were used to measure the concentrations ofpolycyclic aromatic hydrocarbons (PAHs) in the atmosphere for fourseasons at Tuzo-Yin and Hsiung-Kong site in Kaohsiung city, in the airof a agricultural residue open burning area in Jhu-Shan and Sin-Gang siteduring the rice straw non-burning and burning periods, together with thesize distributions. Also, the receptor model was employed to determinethe potential sources of PAHs. The results show that the highest concentrations of PAHs occurred inwinter, being 143.9 ng/m3 and 182.9 ng/m3 at Tzuo-Yin and Hsiung-Kongsite, respectively; while the lowest concentrations of PAHs occurred insummer, being 81.4 ng/m3 and 95.2 ng/m3. The low-weight PAHs in thetwo sites were abundant in gaseous phase, being 43.8−96.7% and65.2−97.5% at Tzuo-Yin and Hsiung-Kong site, respectively. Meanwhile,the high-weight PAHs were almost present in particulate phase, being40.5−95.2% and 24.8−94.1 % at Tzuo-Yin and Hsiung-Kong site,respectively. The average PAHs concentrations were 330.04 and 567.81 ng/m3during the rice straw non-burning and burning period in Jhu-Shan site, theaverage PAHs concentrations were 427.16 and 571.80 ng/m3 during therice straw non-burning and burning period in Sin-Gang site, respectively,in the rice straw burning period, which were higher than those on thenon-burning days. The results of by CMB receptor modeling indicated that the major sources of pollution was exhaust emission (49.5−63.3%) in Tzuo-Yin site,and was burning source (49.1−63.7%) in Hsiung-Kong site in Kaohsiungcity. The results of APCA model analysis indicated that the major sourcesof pollution was mobile source (gasoline and diesel) were 66.5¡Ó8.0%during the rice straw non-burning period, and was mobile (gasoline) andrice straw non-burning source were 57.3¡Ó6.9% during the rice strawburning period in Jhu-Shan site in Central Taiwan. The results of APCAmodel analysis indicated that the major sources of pollution was mobile(gasoline) and plastics incinerator source were 54.3¡Ó6.4% during the ricestraw non-burning period, and was burning incense in temple, rice straw,mobile (gasoline and diesel) source were 50.7¡Ó4.6% during the rice strawburning period in Sin-Gang site in Central Taiwan.

Neighboring northern Kaohsiung with a dense population of petrochemical and petroleum industrial complexes included China Petroleum Company (CPC) refinery plant, Renwu and Dazher petrochemical industrial plants. In recent years, although many scholars have conducted regional studies, but are still limited by the lack of relevant information evidences (such as odorous matters identification and VOCs fingerprint database), while unable to clearly identify the causes of poor ambient air quality. By sampling and analyzing VOCs, we will be able to understand the major sources of VOCs in northern Kaohsiung and their contribution, and to provide the air quality management and control countermeasures for local environmental protection administration. In this study, we sampled and analyzed the speciation of VOCs and sulfur-containing odorous matters (SOMs) in the CPC refinery plants, Renwu and Dazher petrochemical complexes simultaneously with stack sampling. The sampling of VOCs and SOMs were conducted on January 7th, 14th, and 19th, 2011 (dry season) and May 6th, 13rd, and 23rd, 2011 (wet season). We established the emission source database, investigated the characteristics of VOC fingerprints, and estimate the emission factor of each stack. It helps us understand the temporal and spatial distribution of VOCs and ascertain major sources and their contribution of VOCs. Major VOCs emitted from the stacks of the CPC refinery plant were toluene and acetone. It showed that petroleum refinery processes had similar VOCs characteristics and fingerprints. The fingerprints of stack emissions at Renwu and Dashe industrial complexes varied with their processes. Hydrogen sulfide was the major sulfur-containing odorous matter in all petrochemical plants. Compared to other petrochemical complexes, Renwu industrial complex emitted a variety of SOMs species as well as relatively high concentrations of sulfur-containing odorous matters. The petrochemical industrial complexes in the industrial ambient of VOCs analysis results showed that isobutane, butane, isopentane, pentane, propane of alkanes, propene of alkenes, toluene, ethylbenzene, xylene, styrene of aromatics, 2-Butanone (MEK), acetone, of carbonyls are major species of VOCs. In addition, ethene+acetylene+ethane (C2), 1,2-dichloroethane, chloromethane, dichloromethane, MTBE were also occasionally found. Sulfur-containing odorous matter (SOMs) analytical results showed that major odorous matters included hydrogen sulfide, methanethiol, dimethyl sulfide, and carbon disulfide. The highest hydrogen sulfide concentration went up to 5.5 ppbv. In this study, the species of VOCs were divided into alkanes, alkenes, aromatics, carbonyls, and others. The temporal and spatial distribution of various types of VOCs strongly correlated with near-surface wind direction. The most obvious contaminants were alkanes, aromatics, and carbonyls of the dispersion to the downwind. Generally, the ambient air surrounding the petrochemical industrial complexes was influenced by various pollutants in the case of high wind speeds. It showed that stack emission and fugitive sources had an important contribution to ambient air quality. TSOMs and hydrogen sulfide emitting mainly from local sources resulted in high concentration of TSOMs and hydrogen sulfide surrounding the petrochemical industrial complex. Principal component analysis (PCA) results showed that the surrounding areas of petrochemical industrial complexes, regardless of dry or wet seasons, were mainly influenced by the process emissions and solvent evaporation. The impact of traffic emission sources ranked the second. Chemical mass balance receptor modeling showed that stack emissions from the CPC refinery plants contributed about 48 %, while fugitive emission sources and mobile sources contributed about 30 % and 11%, respectively. The stack emissions from Renwu industrial complex contributed about 75 %, while fugitive emission sources and mobile sources contributed about 17 % and 5 %, respectively. The stack emissions from Dazher industrial complex contributed about 68 %, while fugitive emission sources and mobile sources contributed about 21 % and 2 %, respectively.

Made available in DSpace on 2016-12-23T14:04:31Z (GMT). No. of bitstreams: 1 dissertacao Trindade.pdf: 2131237 bytes, checksum: 514907f9bd367cc5bd486dcd27fa2d9d (MD5) Previous issue date: 2009-03-13 / A identificação de fontes para material particulado tem sido um tema de crescente interesse em todo o mundo para auxiliar a gestão da qualidade do ar. Esta classe de estudos é convencionalmente baseada no uso de modelos receptores, que identificam e quantificam as fontes responsáveis a partir da concentração do contaminante no receptor. Existe uma variedade de modelos receptores disponíveis na literatura, este trabalho compara os resultados dos modelos receptores balanço químico de massa (BQM) e fatoração de matriz positiva (FMP) para o banco de dados de PM2,5, da região de Brighton, Colorado, com o intuito de investigar as dificuldades na utilização de cada modelo, bem como suas vantagens e desvantagens. Inicialmente, já é conhecido que o modelo BQM tem a desvantagem de necessitar dos perfis das fontes, determinados experimentalmente, para ser aplicado e também tem limitações quando as fontes envolvidas são similares. Já o modelo FMP não requer os perfis de fontes, mas tem a desvantagem de precisar de elevada quantidade amostral da concentração do contaminante no receptor. Os resultados mostraram, baseados nas medidas de performance que os dois modelos foram aptos para reproduzir os dados do receptor com ajustes aceitáveis. Todavia, resultados diferentes se ajustaram a medidas de performance. O modelo BQM, utilizou 9 tipos de fontes e o modelo FMP encontrou apenas 6 tipos de fontes. Constatou-se com isso que o modelo FMP tem dificuldades em modelar fontes que aparecem ocasionalmente. As fontes sulfato de amônio, solos, veículos a diesel e nitrato de amônio tiverem boas correlações nos resultados dos dois modelos de contribuições de fontes. Os perfis de fontes utilizados no modelo BQM e resultados do modelo FMP que mais se assimilaram foram das fontes nitrato de amônio, solos, sulfato de amônio e combustão de madeira e ou/ veículos desregulados. Verificou-se no modelo FMP que as espécies não características de determinadas fontes aparecem nos resultados dos perfis das fontes, o que torna-se ainda mais complexo a identificação das fontes, requerendo elevado conhecimento sobre a composição de inúmeras fontes. / The identification of sources of particulate matter has been a topic of growing interest throughout the world to assist the air quality management. This class of studies is conventionally based on the use of receptor models, which identify and quantify the sources responsible from the concentration of the contaminant in the receptor. There are a variety of receptor models, this study compares the results of chemical mass balance (CMB) and positive matrix factorization (PMF) models for a database of PM2.5, for the region of Brighton, Colorado, with a view to investigate the difficulties in the use of each model, as well as its advantages and disadvantages. It is known that the CMB model has the disadvantage of requiring source profiles, determined experimentally, to be applied and also has limitations when the sources involved are similar. On the other hand, the PMF model does not require source profiles, it has the disadvantage to require a large amount sample, in receptor. The results showed, based on performance measures that both models were able to reproduce the data of the receptor with reasonable fit. However, different results were adjusted for performance measurements. The CMB model, used 9 types of sources and PMF model found only 6 types of sources, it was noted by that what the PMF model has difficulty in modeling sources that appear occasionally. The sources ammonium sulfate, soil, diesel vehicles and ammonium nitrate have good correlation in the results of the two model of sources apportionment. The source profiles used in the CMB model and results of the PMF model that present more similarities were of the sources ammonium nitrate, soil, ammonium sulfate and combustion of wood and/or smoker vehicles. It was verified what the PMF model does not separate well species in the source profiles, therefore becomes even more complex to identify the sources in the FMP model, requiring considerable knowledge about the composition of many sources. For the database used with similar sources, the lack of confidence in the results based only on receptors models for a final decision on the source apportionment.