“怎样对待垃圾”：亚洲的固体垃圾管理

亚洲正在快速进行城市化,并日益走向“消费型社会”,从全球来看,亚洲的固体垃圾管理面临着更为严峻的挑战 .根据已有数据及发展趋势可以预测 2025年的垃圾数量及成分 .基于低收入国家垃圾数量的超高速增长,在今后的 25年中,垃圾总量将至少会翻一倍 .出于对更广泛商业行为的重视,特提出了区域控制建议 .     

The relative influence of nutrients and habitat on stream metabolism in agricultural streams

Stream metabolism was measured in 33 streams across a gradient of nutrient concentrations in four agricultural areas of the USA to determine the relative influence of nutrient concentrations and habitat on primary production (GPP) and respiration (CR-24). In conjunction with the stream metabolism estimates, water quality and algal biomass samples were collected, as was an assessment of habitat in the sampling reach. When data for all study areas were combined, there were no statistically significant relations between gross primary production or community respiration and any of the independent variables. However, significant regression models were developed for three study areas for GPP (r ² = 0.79–0.91) and CR-24 (r ² = 0.76–0.77). Various forms of nutrients (total phosphorus and area-weighted total nitrogen loading) were significant for predicting GPP in two study areas, with habitat variables important in seven significant models. Important physical variables included light availability, precipitation, basin area, and in-stream habitat cover. Both benthic and seston chlorophyll were not found to be important explanatory variables in any of the models; however, benthic ash-free dry weight was important in two models for GPP.     

The BIOTA Biodiversity Observatories in Africa—a standardized framework for large-scale environmental monitoring

The international, interdisciplinary biodiversity research project BIOTA AFRICA initiated a standardized biodiversity monitoring network along climatic gradients across the African continent. Due to an identified lack of adequate monitoring designs, BIOTA AFRICA developed and implemented the standardized BIOTA Biodiversity Observatories, that meet the following criteria (a) enable long-term monitoring of biodiversity, potential driving factors, and relevant indicators with adequate spatial and temporal resolution, (b) facilitate comparability of data generated within different ecosystems, (c) allow integration of many disciplines, (d) allow spatial up-scaling, and (e) be applicable within a network approach. A BIOTA Observatory encompasses an area of 1?km² and is subdivided into 100 1-ha plots. For meeting the needs of sampling of different organism groups, the hectare plot is again subdivided into standardized subplots, whose sizes follow a geometric series. To allow for different sampling intensities but at the same time to characterize the whole square kilometer, the number of hectare plots to be sampled depends on the requirements of the respective discipline. A hierarchical ranking of the hectare plots ensures that all disciplines monitor as many hectare plots jointly as possible. The BIOTA Observatory design assures repeated, multidisciplinary standardized inventories of biodiversity and its environmental drivers, including options for spatial up- and downscaling and different sampling intensities. BIOTA Observatories have been installed along climatic and landscape gradients in Morocco, West Africa, and southern Africa. In regions with varying land use, several BIOTA Observatories are situated close to each other to analyze management effects.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Anticipating Climate Threshold Damages

Several integrated assessment studies have concluded that future learning about the uncertainties involved in climate change has a considerable effect on welfare but only a small effect on optimal short-term emissions. In other words, learning is important but anticipation of learning is not. We confirm this result in the integrated assessment model “model of investment and technological development” for learning about climate sensitivity and climate damages. If learning about an irreversible threshold is included, though, we show that anticipation can become crucial both in terms of necessary adjustments of pre-learning emissions and resulting welfare gains. We specify conditions on the time of learning and the threshold characteristic, for which this is the case. They can be summarized as a narrow “anticipation window.”     

Simulation of soil loss processes based on rainfall runoff and the time factor of governance in the Jialing River Watershed,China

Jialing River is the largest tributary in the catchment area of Three Gorges Reservoir, and it is also one of the important areas of sediment yield in the upper reaches of the Yangtze River. In recent years, significant changes of water and sediment characteristics have taken place. The "Long Control" Project implemented since 1989 had greatly changed the surface appearance of the Jialing River Watershed (JRW), and it had made the environments of the watershed sediment yield and sediment transport change significantly. In this research, the Revised Universal Soil Loss Equation was selected and used to predict the annual average amount of soil erosion for the special water and sediment environments in the JRW after the implementation of the "Long Control" Project, and then the rainfall–runoff modulus and the time factor of governance were both considered as dynamic factors, the dynamic sediment transport model was built for soil erosion monitoring and forecasting based on the average sediment yield model. According to the dynamic model, the spatial and temporal distribution of soil erosion amount and sediment transport amount of the JRW from 1990 to 2007 was simulated using geographic information system (GIS) technology and space-grid algorithm. Simulation results showed that the average relative error of sediment transport was less than 10% except for the extreme hydrological year. The relationship between water and sediment from 1990 to 2007 showed that sediment interception effects of the soil and water conservation projects were obvious: the annual average sediment discharge reduced from 145.3 to 35 million tons, the decrement of sediment amount was about 111 million tons, and decreasing amplitude was 76%; the sediment concentration was also decreased from 2.01 to 0.578 kg/m³. These data are of great significance for the prediction and estimation of the future changing trends of sediment storage in the Three Gorges Reservoir and the particulate non-point source pollution load carried by sediment transport from watershed surface.     

Evaluation of concentration efficiency of the Pseudomonas aeruginosa phage PP7 in various water matrixes by different methods

Enteric viruses monitoring in surface waters requires the concentration of viruses before detection assays. The aim of this study was to evaluate different methods in terms of recovery efficiencies of bacteriophage PP7 of Pseudomonas aeruginosa, measured by real-time PCR, using it as a viral control process in water analysis. Different nucleic acid extraction methods (silica–guanidinium thiocyanate, a commercial kit (Qiagen Viral RNA Kit) and phenol–chloroform with alcohol precipitation) exhibited very low recovery efficiencies (0.08–4.18 %), being the most efficient the commercial kit used for subsequent experiments. To evaluate the efficiency of three concentration methods, PBS (as model for clean water) and water samples from rivers were seeded to reach high (HC, 10⁶ pfu ml^?1) and low concentrations (LC, 10⁴ pfu ml^?1) of PP7. Tangential ultrafiltration proved to be more efficient (50.36?±?12.91, 17.21?±?9.22 and 12.58?±?2.35 % for HC in PBS and two river samples, respectively) than adsorption–elution with negatively charged membranes (1.00?±?1.34, 2.79?±?2.62 and 0.05?±?0.08 % for HC in PBS and two river samples, respectively) and polyethylene glycol precipitation (15.95?±?7.43, 4.01?±?1.12 and 3.91?±?0.54 %, for HC in PBS and two river samples, respectively), being 3.2–50.4 times more efficient than the others for PBS and 2.7–252 times for river samples. Efficiencies also depended on the initial virus concentration and aqueous matrixes composition. In consequence, the incorporation of an internal standard like PP7 along the process is useful as a control of the water concentration procedure, the nucleic acid extraction, the presence of inhibitors and the variability of the recovery among replicas, and for the calculation of the sample limit of detection. Thus, the use of a process control, as presented here, is crucial for the accurate quantification of viral contamination.     

Effect of power plant emission reductions on a nearby wilderness area: a case study in northwestern Colorado

This study evaluates the effect of emission reductions at two coal-fired power plants in northwestern Colorado on a nearby wilderness area. Control equipment was installed at both plants during 1999–2004 to reduce SO₂ and NOx emissions. One challenge was separating the effects of local from regional emissions, which also declined during the study period. The long-term datasets examined confirm that emission reductions had a beneficial effect on air and water quality in the wilderness. Despite a 75 % reduction in SO₂ emissions, sulfate aerosols measured in the wilderness decreased by only 20 %. Because the site is relatively close to the power plants (<75 km), the slow rate of conversion of SO₂ to sulfate, particularly under conditions of low relative humidity, might account for this less than one-to-one response. On the clearest days, emissions controls appeared to improve visibility by about 1 deciview, which is a small but perceptible improvement. On the haziest days, however, there was little improvement perhaps reflecting the dominance of regional haze and other components of visibility degradation particularly organic carbon and dust. Sulfate and acidity in atmospheric deposition decreased by 50 % near the southern end of the wilderness of which 60 % was attributed to power plant controls and the remainder to reductions in regional sources. Lake water sulfate responded rapidly to trends in deposition declining at 28 lakes monitored in and near the wilderness. Although no change in the acid–base status was observed, few of the lakes appear to be at risk from chronic or episodic acidification.