Three-dimensional fluorescence excitation–emission matrix(EEM) coupled with parallel factor analysis(PARAFAC) was performed for a total of 18 water samples taken from three water sources(two lakes and one wastewater treatment plant(WWTP) secondary effluent),with the purpose of identifying the major ultrafiltration(UF) membrane foulants in different water sources. Three fluorescent components(C1, C2 and C3) were identified,which represented terrestrially derived humic-like substances(C1), microbially derived humic-like substances(C2), and protein-like substances(C3). The correlations between the different fluorescent components and UF membrane fouling were analyzed. It was shown that for the WWTP secondary effluent, all three components(C1, C2 and C3) made a considerable contribution to the irreversible and total fouling of the UF membrane.However, for the two lakes, only the C3 exhibited a strong correlation with membrane fouling, indicating that the protein-like substances were the major membrane foulants in the lake waters. Significant attachment of C1, C2 and C3 to the UF membrane was also confirmed by mass balance analyses for the WWTP secondary effluent; while the attachment of C1 and C2 was shown to be negligible for the two lakes. The results may provide basic formation for developing suitable fouling control strategies for sustainable UF processes. 相似文献
Objective: The objective of this research was to study risk factors that significantly influence the severity of crashes for drivers both under and not under the influence of alcohol.
Methods: Ordinal logistic regression was applied to analyze a crash data set involving drivers under and not under the influence of alcohol in China from January 2011 to December 2014.
Results: Four risk factors were found to be significantly associated with the severity of driver injury, including crash partner and intersection type. Age group was found to be significantly associated with the severity of crashes involving drivers under the influence of alcohol. Crash partner, intersection type, lighting conditions, gender, and time of day were found to be significantly associated with severe driver injuries, the last of which was also significantly associated with severe crashes involving drivers not under the influence of alcohol.
Conclusions: This study found that pedestrian involvement decreases the odds of severe driver injury when a driver is under the influence of alcohol, with a relative risk of 0.05 compared to the vehicle-to-vehicle group. The odds of severe driver injury at T-intersections were higher than those for traveling along straight roads. Age was shown to be an important factor, with drivers 50–60 years of age having higher odds of being involved in severe crashes compared to 20- to 30-year-olds when the driver was under the influence of alcohol.
When the driver was not under the influence of alcohol, drivers suffered more severe injuries between midnight and early morning compared to early nighttime. The vehicle-to-motorcycle and vehicle-to-pedestrian groups experienced less severe driver injuries, and vehicle collisions with fixed objects exhibited higher odds of severe driver injury than did vehicle-to-vehicle impacts. The odds of severe driver injury at cross intersections were 0.29 compared to travel along straight roads. The odds of severe driver injury when street lighting was not available at night were 3.20 compared to daylight. The study indicated that female drivers are more likely to experience severe injury than male drivers when not under the influence of alcohol. Crashes between midnight and early morning exhibited higher odds of severe injury compared to those occurring at other times of day.
The identification of risk factors and a discussion on the odds ratio between levels of the impact of the driver injury and crash severity may benefit road safety stakeholders when developing initiatives to reduce the severity of crashes. 相似文献
Saproxylic (dead-wood-associated) and old-growth species are among the most threatened species in European forest ecosystems,
as they are susceptible to intensive forest management. Identifying areas with particular relevant features of biodiversity
is of prime concern when developing species conservation and habitat restoration strategies and in optimizing resource investments.
We present an approach to identify regional conservation and restoration priorities even if knowledge on species distribution
is weak, such as for saproxylic and old-growth species in Switzerland. Habitat suitability maps were modeled for an expert-based
selection of 55 focal species, using an ecological niche factor analyses (ENFA). All the maps were then overlaid, in order
to identify potential species’ hotspots for different species groups of the 55 focal species (e.g., birds, fungi, red-listed
species). We found that hotspots for various species groups did not correspond. Our results indicate that an approach based
on “richness hotspots” may fail to conserve specific species groups. We hence recommend defining a biodiversity conservation
strategy prior to implementing conservation/restoration efforts in specific regions. The conservation priority setting of
the five biogeographical regions in Switzerland, however, did not differ when different hotspot definitions were applied.
This observation emphasizes that the chosen method is robust. Since the ENFA needs only presence data, this species prediction
method seems to be useful for any situation where the species distribution is poorly known and/or absence data are lacking.
In order to identify priorities for either conservation or restoration efforts, we recommend a method based on presence data
only, because absence data may reflect factors unrelated to species presence. 相似文献
