应用底栖动物为指示生物的松花江干流水生态预警研究

指示生物监测及水生态预警是利用水环境中指示物种的数量、群落结构指标和个体生理指标等描述水生态系统的健康状态,其相比于常规理化监测和预警更直接地反映水体的生态质量。本研究在松花江干流2012—2015年大型底栖无脊椎动物监测结果的基础上,结合各监测点生态质量管理目标,通过分析物种的种类、出现的频次、物种污染敏感性(耐污值),尝试提出了松花江干流监控断面以底栖动物为指示生物的水生态预警模式,研究思路和结果对流域水环境风险管理指标的拓展有积极作用。     

State of research on the automation of HAZOP studies

For more than 30 years, multiple research groups have worked on the automation of hazard and operability (HAZOP) studies, or more specifically on the hazard identification process. So far, very few of these approaches have been used in the chemical process industry. Automatic hazard identification is a knowledge-intensive process that demands high standards with regard to the way in which knowledge is stored and made available. There are various suitable approaches to the qualitative modeling of processes and plants, which are the foundation for reasoning systems that are used for the identification of hazards. Additionally, there are quantitative methods that are based on process simulations and can be used to identify potential hazards. The investigation of the state of research demonstrates that there are sophisticated technologies for automated systems that include powerful reasoning techniques. The benefits and shortcomings of existing technologies are discussed with regard to their industrial applicability. Often, the quality of the necessary specific and generic knowledge is not sufficient to detect potential hazardous events and operational malfunctions. Computer-aided HAZOP systems should be integrated with computer-aided design- or process simulation software using common data models based on the digital representation of the process plant. In order to be used by HAZOP practitioners automated systems need to be comprehensive, serve as specialized decision support systems, and be tested and evaluated using round robin tests.     

Population viability and harvest sustainability for Madagascar lemurs

Subsistence hunting presents a conservation challenge by which biodiversity preservation must be balanced with safeguarding of human livelihoods. Globally, subsistence hunting threatens primate populations, including Madagascar's endemic lemurs. We used population viability analysis to assess the sustainability of lemur hunting in Makira Natural Park, Madagascar. We identified trends in seasonal hunting of 11 Makira lemur species from household interview data, estimated local lemur densities in populations adjacent to focal villages via transect surveys, and quantified extinction vulnerability for these populations based on species-specific demographic parameters and empirically derived hunting rates. We compared stage-based Lefkovitch with periodic Leslie matrices to evaluate the impact of regional dispersal on persistence trajectories and explored the consequences of perturbations to the timing of peak hunting relative to the lemur birth pulse, under assumptions of density-dependent reproductive compensation. Lemur hunting peaked during the fruit-abundant wet season (March–June). Estimated local lemur densities were roughly inverse to body size across our study area. Life-history modeling indicated that hunting most severely threatened the species with the largest bodies (i.e., Hapalemur occidentalis, Avahi laniger, Daubentonia madagascariensis, and Indri indi), characterized by late-age reproductive onsets and long interbirth intervals. In model simulations, lemur dispersal within a regional metapopulation buffered extinction threats when a majority of local sites supported growth rates above the replacement level but drove regional extirpations when most local sites were overharvested. Hunt simulations were most detrimental when timed to overlap lemur births (a reality for D. madagascariensis and I. indri). In sum, Makira lemurs were overharvested. Regional extirpations, which may contribute to broad-scale extinctions, will be likely if current hunting rates persist. Cessation of anthropogenic lemur harvest is a conservation priority, and development programs are needed to help communities switch from wildlife consumption to domestic protein alternatives.     

Cost‐effectiveness of conservation payment schemes for species with different range sizes

Payments to compensate landowners for carrying out costly land‐use measures that benefit endangered biodiversity have become an important policy instrument. When designing such payments, it is important to take into account that spatially connected habitats are more valuable for many species than isolated ones. One way to incentivize provision of connected habitats is to offer landowners an agglomeration bonus, that is, a bonus on top of payments they are receiving to conserve land if the land is spatially connected. Researchers have compared the cost‐effectiveness of the agglomeration bonus with 2 alternatives: an all‐or‐nothing, agglomeration payment, where landowners receive a payment only if the conserved land parcels have a certain level of spatial connectivity, and a spatially homogeneous payment, where landowners receive a payment for conserved land parcels irrespective of their location. Their results show the agglomeration bonus is rarely the most cost‐effective option, and when it is, it is only slightly better than one of the alternatives. This suggests that the agglomeration bonus should not be given priority as a policy design option. However, this finding is based on consideration of only 1 species. We examined whether the same applied to 2 species, one for which the homogeneous payment is best and the other for which the agglomeration payment is most cost‐effective. We modified a published conceptual model so that we were able to assess the cost‐effectiveness of payment schemes for 2 species and applied it to a grassland bird and a grassland butterfly in Germany that require the same habitat but have different spatial‐connectivity needs. When conserving both species, the agglomeration bonus was more cost‐effective than the agglomeration and the homogeneous payment; thus, we showed that as a policy the agglomeration bonus is a useful conservation‐payment option.     

Applying Statistical Causal Analyses to Agricultural Conservation: A Case Study Examining P Loss Impacts

Estimating the effect of agricultural conservation practices on reducing nutrient loss using observational data can be confounded by factors such as differing crop types and management practices. As we may not have the full knowledge of these confounding factors, conventional statistical meta‐analysis methods can be misleading. We discuss the use of two statistical causal analysis methods for quantifying the effects of water and soil conservation practices in reducing P loss from agricultural fields. With the propensity score method, a subset of data was used to form a treatment group and a control group with similar distributions of confounding factors. With the multilevel modeling method, data were stratified based on important confounding factors, and the conservation practice effect was evaluated for each stratum. Both methods resulted in similar estimates of the conservation practice effect (total P load reduction avg. ~70%). In addition, both methods show evidence of conservation practices reducing the incremental increase in total P export per unit increase in fertilizer application. These results are presented as examples of the types of outcomes provided by statistical causal analyses, not to provide definitive estimates of P loss reduction. The enhanced meta‐analysis methods presented within are applicable for improved assessment of agricultural practices and their effects and can be used for providing realistic parameter values for watershed‐scale modeling.     

Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.     

An Analysis of Patterns and Trends in United States Stormwater Utility Systems

Several factors, such as municipality location and population, are thought to influence trends among stormwater utilities (SWUs); however, no analysis of the relationship between these factors and SWU characteristics has been performed. This article corroborates hypothesized relationships and identifies trends and patterns in the establishment, funding mechanism, and magnitude of SWUs by analyzing location, population density, home value, and year of establishment for a comprehensive national SWU database with data for 1,490 SWUs. The equivalent residential unit (ERU), a SWU that charges based on impervious area, was the most prevalent funding mechanism in all National Oceanic and Atmospheric Administration Climate Regions of the United States except the West and West‐North‐Central. The ERU was also found in larger cities with high population densities, whereas the Flat Fee, a SWU that charges a single rate for all properties, was found in smaller towns. Higher home values were correlated with higher monthly fees for 28% of the municipalities analyzed. The residential equivalence factor, a SWU that charges based on runoff produced, was popular in municipalities with higher home values, whereas the Flat Fee was popular in municipalities with lower home values. The number of SWUs established increased with Phase I municipal separate stormwater and sewer system (MS4) permit and Phase II small MS4 permit deadlines. Summary tables provide guidance to aid municipalities considering a SWU.     

Modeling urban solar energy with high spatiotemporal resolution: A case study in Toronto,Canada

This research presents a method to determine the maximum potential for the capturing of solar radiation on the rooftop of buildings in an urban environment. This involves the modeling of solar energy potential and comparison to historical building energy demand profiles through the use of 3-D solar simulation software tools and geographic information systems (GIS). The objective is to accurately identify the amount of surface area that is suitable for solar photovoltaic (PV) installations and to estimate the hourly PV electricity generation potential of existing building rooftops in an urban environment. This study demonstrates a viable approach for modeling urban solar energy and offers valuable information for electricity distributors, policy makers, and urban energy planners to facilitate the substantial design of a green built environment. The developed methodology is comprised of three main sections: (1) determination of suitable rooftop area, (2) determination of the amount of incident solar radiation available per rooftop, and (3) estimation of hourly solar PV electricity generation potential. A case study was performed using this method for Ryerson University, located in Toronto, Canada. It was found that solar PV could supply up to 19% of the study area’s electricity demands during peak consumption hours. The potential benefits of solar PV was also estimated based upon hourly greenhouse gas emission intensity factors as well as Time-of-Use (TOU) savings through the Ontario Feed-in-Tariff (FIT) program, which allows for better representation of the positive impacts of solar technologies.     

CFD simulation of MSW combustion and SNCR in a commercial incinerator

A CFD scheme was presented for modeling municipal solid waste (MSW) combustion in a moving-grate incinerator, including the in-bed burning of solid wastes, the out-of-bed burnout of gaseous volatiles, and the selective non-catalytic reduction (SNCR) process between urea (CO(NH₂)₂) and NO_x. The in-bed calculations provided 2-D profiles of the gas–solid temperatures and the gas species concentrations along the bed length, which were then used as inlet conditions for the out-of-bed computations. The over-bed simulations provided the profiles of incident radiation heat flux on the top of bed. A 3-dimensional benchmark simulation was conducted with a 750 t/day commercial incinerator using the present coupling scheme incorporating with a reduced SNCR reduction mechanism. Numerical tests were performed to investigate the effects of operating parameters such as injection position, injection speed and the normalized stoichiometric ratio (NSR) on the SNCR performance. The simulation results showed that the distributions of gas velocity, temperature and NO_x concentration were highly non-uniform, which made the injection position one of the most sensitive operating parameters influencing the SNCR performance of moving grate incinerators. The simulation results also showed that multi-layer injections were needed to meet the EU2000 standard, and a NSR 1.5 was suggested as a compromise of a satisfactory NO_x reduction and reasonable NH₃ slip rates. This work provided useful guides to the design and operation of SNCR process in moving-grate incinerators.     

Variability and Trends in Runoff Efficiency in the Conterminous United States

Variability and trends in water‐year runoff efficiency (RE) — computed as the ratio of water‐year runoff (streamflow per unit area) to water‐year precipitation — in the conterminous United States (CONUS) are examined for the 1951 through 2012 period. Changes in RE are analyzed using runoff and precipitation data aggregated to United States Geological Survey 8‐digit hydrologic cataloging units (HUs). Results indicate increases in RE for some regions in the north‐central CONUS and large decreases in RE for the south‐central CONUS. The increases in RE in the north‐central CONUS are explained by trends in climate, whereas the large decreases in RE in the south‐central CONUS likely are related to groundwater withdrawals from the Ogallala aquifer to support irrigated agriculture.