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This paper describes a study of local biogenic volatile organic compounds (BVOC) emissions from the Hong Kong Special Administrative Region (HKSAR). An improved land cover and emission factor database was developed to estimate Hong Kong emissions using MEGAN, a BVOC emission model developed by Guenther et al. (2006). Field surveys of plant species composition and laboratory measurements of emission factors were combined with other data to improve existing land cover and emission factor data. The BVOC emissions from Hong Kong were calculated for 12 consecutive years from 1995 to 2006. For the year 2006, the total annual BVOC emissions were determined to be 12,400 metric tons or 9.82 × 109 g C (BVOC carbon). Isoprene emission accounts for 72%, monoterpene emissions account for 8%, and other VOCs emissions account for the remaining 20%. As expected, seasonal variation results in a higher emission in the summer and a lower emission in the winter, with emission predominantly in day time. A high emission of isoprene occurs for regions, such as Lowest Forest-NT North, dominated by broadleaf trees. The spatial variation of total BVOC is similar to the isoprene spatial variation due to its high contribution. The year to year variability in emissions due to weather was small over the twelve-year period (?1.4%, 2006 to 1995 trendline), but an increasing trend in the annual variation due to an increase in forest land cover can be observed (+7%, 2006 to 1995 trendline). The results of this study demonstrate the importance of accurate land cover inputs for biogenic emission models and indicate that land cover change should be considered for these models.  相似文献   
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Perfluorinated compounds (PFCs) were measured in zooplankton and five fish species collected from Gaobeidian Lake, which receives discharge from wastewater treatment plant (WWTP) in Beijing, China. The mean total PFCs in five fish were in the order: crucian carp > common carp > leather catfish > white semiknife carp > tilapia. Perfluorooctane sulfonate (PFOS) occurred at the greatest concentrations, with mean concentrations ranging from 5.74 to 64.2 ng/ml serum. Perfluorodecanoic acid (PFDA) was the second dominant PFC in fish samples except for common carp in which perfluorooctane sulfonamide (PFOSA) was dominant. A positive linear relationship (r2 = 0.85, p < 0.05) was observed between ln PFOS concentrations (ln ng/ml) and trophic level (based on δ15N) if tilapia was excluded. The risk assessment showed that PFOS might not pose an immediate risk to fish in Gaobeidian Lake.  相似文献   
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Laboratory partitioning experiments were conducted to elucidate the sorption behaviour and partitioning of perfluoroalkyl compounds (PFCs). Three different sediment types were used and separately spiked with perfluorooctanoate (PFOA), perfluorooctane sulfonate (PFOS) and perfluorooctane sulfonamide (PFOSA) at low environmentally realistic concentrations. PFOA, PFOS and PFOSA were mainly distributed in the dissolved phase at low suspended solid concentrations, indicating their long-range transport potential in the marine environment. In all cases, the equilibrium isotherms were linear and the organic carbon normalised partition coefficients (KOC) decreased in the following order: PFOSA (log KOC = 4.1 ± 0.35 cm3 g−1) > PFOS (3.7 ± 0.56 cm3 g−1) > PFOA (2.4 ± 0.12 cm3 g−1). The level of organic content had a significant influence on the partitioning. For the sediment with negligible organic content the density of the sediment became the most important factor influencing the partitioning. Ultimately, data on the partitioning of PFCs between aqueous media and suspended solids are essential for modelling their transport and environmental fate.  相似文献   
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The effects of removing moisture from gaseous samples on the measurement of pollutant concentration were studied. Simple mathematical analysis was conducted to derive the formula for correcting the measured results. It was found that the error increases with increase in relative humidity or increase in temperature. The error may become significant under extreme conditions.  相似文献   
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Phthalates are a large family of ubiquitous environmental pollutants suspected of being endocrine disruptors. Epidemiological studies have associated phthalate metabolites with decreased reproductive parameters and linked phthalate exposure with the level of urinary 5-methyl-2′-deoxycytidine(5mdC, a product of methylated DNA). In this study, adult male mice were exposed to 450 mg di-isobutyl phthalate(DiBP)/(kg·day) via dietary exposure for 28 days. Mono-isobutyl phthalate(Mi BP, the urinary metabolite) and reproductive function parameters were determined. The levels of 5mdC and 5-hydroxymethyl-2′-deoxycytidine(5hmdC) were measured in urine to evaluate if their contents were also altered by DiBP exposure in this animal model. Results showed that DiBP exposure led to a significant increase in the urinary 5mdC level and significant decreases in sperm concentration and motility in the epididymis, accompanied with reduced testosterone levels and downregulation of the P450 cholesterol side-chain cleavage enzyme(P450scc) gene in the mice testes. Our findings indicated that exposure to DiBP increased the urinary 5mdC levels,which supported our recent epidemiological study about the associations of urinary 5mdC with phthalate exposure in the male human population. In addition, DiBP exposure impaired male reproductive function, possibly by disturbing testosterone levels; P450scc might be a major steroidogenic enzyme targeted by DiBP or other phthalates.  相似文献   
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Tropospheric ozone is a secondary air pollutant produced in the presence of nitrogen oxides (NO_x),volatile organic compounds (VOCs),and solar radiation.In an urban environment,ground-level vehicular exhaust is the major anthropogenic source of ozone precursors.In the cases of street canyons,pollutant dilution is weakened by the surrounding buildings that creates localized high concentration of NO_x and VOCs,and thus leads to high potential of ozone formation.By considering the major physical and chemica...  相似文献   
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Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.  相似文献   
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