The Conservation Status and Conservation Strategy of Picea neoveitchii

Picea neoveitchii is an endemic species in China. It had been listed as an endangered species in red data books. It scatters in several locations of south slope of the Qinling Mountain of China. Upon reviewing the related literature, discussing with leading scholars on gymnosperm, ecology and plant conservation, the field survey was carried out in four locations. There are eleven mature individuals and two seedlings surviving in its natural habitats. With the survey of quadrat method in four locations, related community index were calculated such as relative important value （RIV）, species richness, similarity index, diversity index and evenness index etc. The community could be sorted and characterized as three groups based on the community parameters. The analysis of vegetation table elucidates that Picea neoveitchii is a dominant species with low grouping rate in most surveyed sites. The RAPD analysis shows target species has intraspecific genetic variability. The estimation of Shannon＇s phenotypic diversity index （Ho） also explains the difference of genetic variations of different locations. Due to the lack of enough knowledge and professional guide of conservation biological perspective, Picea neoveitchii had been clear-cut for timber production. The extent of occurrence and area of occupancy declined rapidly from 1950s to 1990s. According to the Conservation Category guideline proposed by the World Conservation Union, the conservation status of Picea neoveitchii was reevaluated as Critically Endangered （CR） B2b C2a D. Upon research in areas of ecology, molecular biology, cluster analysis of environmental parameters, a practical conservation strategy is recommended in this research.     

Thermal treatment and decontamination of mercury-contaminated waste: Recent developments and comparative evaluation

The land disposal restriction regulations have necessitated development of technologies for the treatment of wastes and soils containing mercury. Of all the treatment methods, thermal technologies are the most advanced and proven for a variety of mercury-contaminated waste materials. During the past few years, a number of thermal treatment processes have been developed both for listed and characteristic waste. A review of the technologies identified six that are in either commercial or pilot plant stages. The biggest volumes of waste currently occur in the gas processing and caustic-chlorine industries, so most of the technologies being used appear to have been developed around the characteristics of these two wastes. This article discusses the characteristics of each of the six available thermal treatment processes, and describes the types of mercury-contaminated wastes these technologies have been designed to handle.     

The rising tide: combating coastal pollution

Coastal zones are major hubs for economic and social activity and are in the front line of climate change. To safeguard these fragile ecosystems for our own and future generations we have to move towards more integrated approaches to the assessment and management of coastal and marine environments. Environmental monitoring-broadly defined-has a huge role to play.     

Organizational and behavioural consequences of uncertainty: A case study

This paper examines some of the organizational and behavioural consequences of uncertainty through consideration of a case study. An industrial firm and its problems are described and an attempt is made to understand the origins of the situation using a systems analysis which draws on constructs from the structural, the behavioural and the ‘bureaucratic’ traditions within organization theory. The analysis demonstrates: that the problems are interrelated and stem from the structural arrangements in the firm which are unable to cope with the prevailing uncertainties; that the behavioural difficulties may be seen as manifestations of the underlying structural/environmental mismatch; and, that the problems are exacerbated by apparently logical but paradoxically inappropriate managerial choices and responses. The implications of this study for theory, practice and method are discussed.     

The effect of sulfide on alpha-glucosidases: implications for starch degradation in anaerobic bioreactors

Membrane associated alpha-glucosidase activity was investigated in a methanogenic bioreactor (MR) and a biosulfidogenic bioreactor (SR). Temperature and pH optima studies showed temperature optima of 50 degrees C and pH optima of 8.0 for the alpha-glucosidases from both the MR and SR. Sulfide (at a concentration of 150 mg l(-1)) resulted in the complete loss of all alpha-glucosidase activity in both the MR and SR. beta-Glucosidase activities in our bioreactors were previously shown to be stimulated in the presence of sulfide. alpha-Glucosidases, in contrast, are inhibited by sulfide. This differential effect of sulfide on alpha-glucosidase and beta-glucosidase activities is highlighted and is of crucial consequence to the respective degradation and utilization of starch and cellulose substrates in natural anaerobic environments and anaerobic bioreactors specifically designed for the accelerated digestion of wastewater sludge under biosulfidogenic conditions.     

Comparison of particle light scattering and fine particulate matter mass in central California

Particle light scattering (Bsp) from nephelometers and fine particulate matter (PM2.5) mass determined by filter samplers are compared for summer and winter at 35 locations in and around California's San Joaquin Valley from December 2, 1999 to February 3, 2001. The relationship is described using particle mass scattering efficiency (sigmasp) derived from linear regression of Bsp on PM2.5 that can be applied to estimated PM2.5 from nephelometer data within the 24-hr filter sampling periods and between the every-6th-day sampling frequency. An average of sigmaSp = 4.9 m2/g was found for all of the sites and seasons; however, sigmasp averaged by site type and season provided better PM2.5 estimates. On average, the sigmasp was lower in summer than winter, consistent with lower relative humidities, lower fractions of hygroscopic ammonium nitrate, and higher contributions from fugitive dust. Winter average sigmasp were similar at non-source-dominated sites, ranging from 4.8 m2/g to 5.9 m2/g. The sigmasp was 2.3 m2/g at the roadside, 3.7 m2/g at a dairy farm, and 4.1 m2/g in the Kern County oilfields. Comparison of Bsp from nephelometers with and without a PM2.5 inlet at the Fresno Supersite showed that coarse particles contributed minor amounts to light scattering. This was confirmed by poorer correlations between Bsp and coarse particulate matter measured during a fall sampling period.     

Feasibility of soil dust source apportionment by the pyrolysis-gas chromatography/mass spectrometry method

This study tested the feasibility of using pyrolysis (Py)-gas chromatography (GC)/mass spectrometry (MS) to obtain organic chemical species data suitable for source apportionment modeling of soil-derived coarse particulate matter (PM10) dust on ambient filters. A laboratory resuspension apparatus was used with known soils to generate simulated receptor filter samples loaded with approximately 0.4 mg of PM10 dust, which is within the range of mass loading on ambient filters. Py-GC/MS at 740 degrees C generated five times more resolvable compounds than were obtained with thermal desorption GC/MS at 315 degrees C. The identified compounds were consistent with literature from Py experiments using larger samples of bulk soils. A subset of 91 organic species out of the 178 identified Py products was used as input to CMB8 software in a demonstration of source apportionment using laboratory-generated mixtures simulating ambient filter samples. The 178 quantified organic species obtained by Py of soil samples is an improvement compared with the 38 organic species obtained by thermal desorption of soils and the four functionally defined organic fractions reported by thermal/ optical reflectance. Significant differences in the concentration of specific species were seen between samples from different sites, both geographically distant and close, using analysis of variance and cluster analysis. This feasibility study showed that Py-GC/MS can generate useful source profile data for receptor modeling and justifies continued method development.