Nine New Zealand native white-rot fungi were studied for their ability to grow and survive on different substrates formulated from bark, wheat straw, sawdust, apple pomace and maize products in order to identify their pentachlorophenol (PCP) biodegradation potential and to select a fungal carrier for bioaugmentation of polluted soils. Isolates were also evaluated to mineralize (14)C-PCP in liquid culture and in soil. The American fungus Phanerochaete chrysosporium outgrew the native fungi on the substrates tested, but the high colonisation did not result in superior PCP dechlorination as measured by chloride release. Whilst Trametes versicolor inocula produced on wheat straw and SCS (sawdust-corn meal-starch-mix) gave the highest chloride release, colonization of these two substrates as measured by biological potential was lower compared to the pomace and pomace-sawdust-mix. Neither lignin peroxidase nor manganese peroxidase production were measured for New Zealand white-rot fungi during the experiments. Laccase was the only enzyme detected. In liquid culture, the mineralisation rate was higher for T. versicolor isolates compared to P. chyrysoporium. Very little to no pentachloroanisole (PCA) was captured in the volatile fraction of T. versicolor isolates, whereas 75% of the volatile fraction of P. chrysosporium consisted of PCA. The soil microcosms studies, using contaminated soil from a timber treatment site, clearly showed that the New Zealand T. versicolor isolates mineralized PCP. Degradation of PCP in non-sterile soil was higher in the presence of white-rot fungi than in soil without white-rot fungus. This demonstrates that viable white-rot fungus is necessary for significant PCP degradation and that T. versicolor isolates showed PCP remediation potential. Wheat straw and SCS could be suitable carriers for New Zealand native T. versicolor isolates for bioremediation of PCP polluted soil sites. 相似文献
Environmental Science and Pollution Research - The extensive application of chemically synthesized anionic surfactants would cause serious pollution of water and increase health risk to humans.... 相似文献
Local governments are the dominant players in haze pollution control; furthermore, financial power reconstruction affects the effectiveness of haze control. Government innovation preference achieves win-win results for environmental protection and economic development by increasing innovation support. Therefore, a moderating variable for government innovation preference was added to the fiscal decentralization effect on haze pollution, and their interactive effect on haze pollution was studied. This study was conducted in 30 provincial regions. Thus, the severity of regional haze pollution differs because of temporal heterogeneity and asynchronous development. Furthermore, we analyzed the impact on haze pollution from the perspectives of the temporal and spatial differences in different regions of China. The results indicate that (1) fiscal decentralization increases haze pollution, while government innovation preferences control it. (2) In a local evaluation model with a diversified background, fiscal decentralization restrains haze pollution, and pollution source complexity reduces government innovation preference’s control pollution function. The interaction term revealed that government innovation preferences had a significant moderating effect. (3) Fiscal decentralization and government innovation preferences control the heterogeneity of haze pollution in different regions.
Zero-inflated data arise in many contexts. In this paper, we develop a zero-inflated Bayesian hierarchical model which deals with spatial effects, correlation among near-locating measurements as well as excess zeros simultaneously. Inference, including the sampling from the posterior distributions, predictions at new locations, and model selection, is carried out by using computationally efficient Markov chain Monte Carlo techniques. The posterior distributions are simulated using a Gibbs sampler with the embedded ratio-of-uniform method and the slice sampling algorithm. The approach is illustrated via an application to herbaceous data collected in the Missouri Ozark Forest Ecosystem Project. The results from the proposed model are compared with those generated from a non-zero inflated model. The proposed model fully incorporates the information from data collection and provides more reliable inference. A predictive $p$ value is computed for model checking and it indicates that the proposed model fits the data well. 相似文献