突发事件区域应急联动影响因素的实证研究

在界定突发事件区域应急联动内涵的基础上,采用Delphi法,识别出突发事件区域应急联动的9个主要影响因素,即应急联动组织机构、应急联动法律法规、应急物资协同调配、应急队伍协同调配、应急预案动态协同、应急信息实时沟通、区域地理位置、区域灾害特征和区域合作基础。同时,运用ISM技术,确定区域应急联动9个影响因素的关联性,计算和分解可达性矩阵,绘制4级递阶有向图,得出区域应急联动影响因素的内在层次性,即划分出"基础层"、"过渡层"和"直接层",为有效构建突发事件区域应急联动机制提供了理论支持与科学依据。     

A provider-based water planning and management model--WaterSim 4.0--for the Phoenix Metropolitan Area

Uncertainty in future water supplies for the Phoenix Metropolitan Area (Phoenix) are exacerbated by the near certainty of increased, future water demands; water demand may increase eightfold or more by 2030 for some communities. We developed a provider-based water management and planning model for Phoenix termed WaterSim 4.0. The model combines a FORTRAN library with Microsoft C# to simulate the spatial and temporal dynamics of current and projected future water supply and demand as influenced by population demographics, climatic uncertainty, and groundwater availability. This paper describes model development and rationale. Water providers receive surface water, groundwater, or both depending on their portfolio. Runoff from two riverine systems supplies surface water to Phoenix while three alluvial layers that underlie the area provide groundwater. Water demand was estimated using two approaches. One approach used residential density, population projections, water duties, and acreage. A second approach used per capita water consumption and separate population growth estimates. Simulated estimates of initial groundwater for each provider were obtained as outputs from the Arizona Department of Water Resources (ADWR) Salt River Valley groundwater flow model (GFM). We compared simulated estimates of water storage with empirical estimates for modeled reservoirs as a test of model performance. In simulations we modified runoff by 80%-110% of the historical estimates, in 5% intervals, to examine provider-specific responses to altered surface water availability for 33 large water providers over a 25-year period (2010-2035). Two metrics were used to differentiate their response: (1) we examined groundwater reliance (GWR; that proportion of a providers' portfolio dependent upon groundwater) from the runoff sensitivity analysis, and (2) we used 100% of the historical runoff simulations to examine the cumulative groundwater withdrawals for each provider. Four groups of water providers were identified, and discussed. Water portfolios most reliant on Colorado River water may be most sensitive to potential reductions in surface water supplies. Groundwater depletions were greatest for communities who were either 100% dependent upon groundwater (urban periphery), or nearly so, coupled with high water demand projections. On-going model development includes linking WaterSim 4.0 to the GFM in order to more precisely model provider-specific estimates of groundwater, and provider-based policy options that will enable "what-if" scenarios to examine policy trade-offs and long-term sustainability of water portfolios.     

Modeling the carbon cycle of urban systems

Although more than 80% of carbon dioxide emissions originate in urban areas, the role of human settlements in the biosphere evolution and in global carbon cycling remains largely neglected. Understanding the relationships between the form and pattern of urban development and the carbon cycle is however crucial for estimating future trajectories of greenhouse gas concentrations in the atmosphere and can facilitate mitigation of climate change. In this paper I review state-of-the-art in modeling of urban carbon cycle. I start with the properties of urban ecosystems from the ecosystem theory point of view. Then I discuss key elements of an urban system and to which degree they are represented in the existing models. In conclusions I highlight necessity of including biophysical as well as human related carbon fluxes in an urban carbon cycle model and necessity of collecting relevant data.     

Monitoring a changing Arctic: Recent advancements in the study of sea ice microbial communities

Sea ice continues to decline across many regions of the Arctic, with remaining ice becoming increasingly younger and more dynamic. These changes alter the habitats of microbial life that live within the sea ice, which support healthy functioning of the marine ecosystem and provision of resources for human-consumption, in addition to influencing biogeochemical cycles (e.g. air–sea CO₂ exchange). With the susceptibility of sea ice ecosystems to climate change, there is a pressing need to fill knowledge gaps surrounding sea ice habitats and their microbial communities. Of fundamental importance to this goal is the development of new methodologies that permit effective study of them. Based on outcomes from the DiatomARCTIC project, this paper integrates existing knowledge with case studies to provide insight on how to best document sea ice microbial communities, which contributes to the sustainable use and protection of Arctic marine and coastal ecosystems in a time of environmental change.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-021-01658-z.     

Assessment of Uncertainty in Long-Term Mass Balances for Acidification Assessments: A MAGIC Model Exercise

Long-term (1860–2010) catchment mass balance calculations rely on models and assumptions which are sources of uncertainty in acidification assessments. In this article, we report on an application of MAGIC to model acidification at the four Swedish IM forested catchments that have been subject to differing degrees of acidification stress. Uncertainties in the modeled mass balances were mainly associated with the deposition scenario and assumptions about sulfate adsorption and soil mass. Estimated base cation (BC) release rates (weathering) varied in a relatively narrow range of 47–62 or 42–47 meq m⁻² year⁻¹, depending on assumptions made about soil cation exchange capacity and base saturation. By varying aluminum solubility or introducing a dynamic weathering feedback that allowed BC release to increase at more acidic pHs, a systematic effect on predicted changes in acid neutralizing capacity (ΔANC ca. 10–41 μeq l⁻¹) and pH (ca. ΔpH = 0.1–0.6) at all sites was observed. More robust projections of future changes in pH and ANC are dependent on reducing uncertainties in BC release rates, the timing, and extent of natural acidification through BC uptake by plants, temporal changes in soil element pools, and fluxes of Al between compartments.     

Use of fugacity model to analyze temperature-dependent removal of micro-contaminants in sewage treatment plants

Effluents from sewage treatment plants (STPs) are known to contain residual micro-contaminants including endocrine disrupting chemicals (EDCs) despite the utilization of various removal processes. Temperature alters the efficacy of removal processes; however, experimental measurements of EDC removal at various temperatures are limited. Extrapolation of EDC behavior over a wide temperature range is possible using available physicochemical property data followed by the correction of temperature dependency. A level II fugacity-based STP model was employed by inputting parameters obtained from the literature and estimated by the US EPA’s Estimations Programs Interface (EPI) including EPI’s BIOWIN for temperature-dependent biodegradation half-lives. EDC removals in a three-stage activated sludge system were modeled under various temperatures and hydraulic retention times (HRTs) for representative compounds of various properties. Sensitivity analysis indicates that temperature plays a significant role in the model outcomes. Increasing temperature considerably enhances the removal of β-estradiol, ethinyestradiol, bisphenol, phenol, and tetrachloroethylene, but not testosterone with the highest biodegradation rate. The shortcomings of BIOWIN were mitigated by the correction of highly temperature-dependent biodegradation rates using the Arrhenius equation. The model predicts well the effects of operating temperature and HRTs on the removal via volatilization, adsorption, and biodegradation. The model also reveals that an impractically long HRT is needed to achieve a high EDC removal. The STP model along with temperature corrections is able to provide some useful insight into the different patterns of STP performance, and useful operational considerations relevant to EDC removal at winter low temperatures.     

From land cover change to land function dynamics: a major challenge to improve land characterization

Land cover change has always had a central role in land change science. This central role is largely the result of the possibilities to map and characterize land cover based on observations and remote sensing. This paper argues that more attention should be given to land use and land functions and linkages between these. Consideration of land functions that provide a wide range of goods and services makes more integrated assessments of land change possible. The increasing attention to multifunctional land use is another incentive to develop methods to assess changes in land functions. A number of methods to quantify and map the spatial extent of land use and land functions are discussed and the implications for modeling are identified based on recent model approaches in land change science. The mixed use of land cover, land use and land function in maps and models leads to inconsistencies in land change assessments. Explicit attention to the non-linear relations between land cover, land use and land function is essential to consistently address land change. New methods to map and quantify land function dynamics will enhance our ability to understand and model land system change and adequately inform policies and planning.     

Prediction of the Fate and Transport Processes of Atrazine in a Reservoir

The fate and transport processes of a toxic chemical such as atrazine, an herbicide, in a reservoir are significantly influenced by hydrodynamic regimes of the reservoir. The two-dimensional (2D) laterally-integrated hydrodynamics and mass transport model, CE-QUAL-W2, was enhanced by incorporating a submodel for toxic contaminants and applied to Saylorville Reservoir, Iowa. The submodel describes the physical, chemical, and biological processes and predicts unsteady vertical and longitudinal distributions of a toxic chemical. The simulation results from the enhanced 2D reservoir model were validated by measured temperatures and atrazine concentrations in the reservoir. Although a strong thermal stratification was not identified from both observed and predicted water temperatures, the spatial variation of atrazine concentrations was largely affected by seasonal flow circulation patterns in the reservoir. In particular, the results showed the effect of flow circulation on spatial distribution of atrazine during summer months as the river flow formed an underflow within the reservoir and resulted in greater concentrations near the surface of the reservoir. Atrazine concentrations in the reservoir peaked around the end of May and early June. A good agreement between predicted and observed times and magnitudes of peak concentrations was obtained. The use of time-variable decay rates of atrazine led to more accurate prediction of atrazine concentrations, while the use of a constant half-life (60 days) over the entire period resulted in a 40% overestimation of peak concentrations. The results provide a better understanding of the fate and transport of atrazine in the reservoir and information useful in the development of reservoir operation strategies with respect to timing, amount, and depth of withdrawal.     

Modeling Postfire Response and Recovery using the Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS)1

Abstract: This paper investigates application of the Army Corps of Engineers’ Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS) to a burned watershed in San Bernardino County, California. We evaluate the HEC‐HMS’ ability to simulate discharge in prefire and postfire conditions in a semi arid watershed and the necessary parameterizations for modeling hydrologic response during the immediate, and subsequent recovery, period after a wildfire. The model is applied to City Creek watershed, which was 90% burned during the Old Fire of October 2003. An optimal spatial resolution for the HEC‐HMS model was chosen based on an initial sensitivity analysis of subbasin configurations and related model performance. Five prefire storms were calibrated for the selected model resolution, defining a set of parameters that reasonably simulate prefire conditions. Six postfire storms, two from each of the following rainy (winter) seasons were then selected to simulate postfire response and evaluate relative changes in parameter values and model behavior. There were clear trends in the postfire parameters [initial abstractions (I_a), curve number (CN), and lag time] that reveal significant (and expected) changes in watershed behavior. CN returns to prefire (baseline) values by the end of Year 2, while I_a approaches baseline by the end of the third rainy season. However, lag time remains significantly lower than prefire values throughout the three‐year study period. Our results indicate that recovery of soil conditions and related runoff response is not entirely evidenced by the end of the study period (three rainy seasons postfire). Understanding the evolution of the land surface and related hydrologic properties during the highly dynamic postfire period, and accounting for these changes in model parameterizations, will allow for more accurate and reliable discharge simulations in both the immediate, and subsequent, rainy seasons following fire.     

A statistical analysis of the carbon dioxide capture process

Post combustion carbon dioxide (CO₂) capture is one of the most commonly adopted technologies for reducing industrial CO₂ emissions, which is now an important goal given the widespread concern over global warming. Research on amine-based CO₂ capture has mainly focused on improving effectiveness and efficiency of the CO₂ capture process. Our research work focuses on studying the relationships among the significant parameters influencing CO₂ production because an enhanced understanding of the intricate relationships among the parameters involved in the process is critical for improving efficiency of the CO₂ capture process. This paper presents a statistical study that explores the relationships among parameters involved in the amine-based post combustion CO₂ capture process at the International Centre for CO₂ Capture (ITC) located in Regina, Saskatchewan of Canada. A multiple regression technique has been applied for analysis of data collected at the CO₂ capture pilot plant at ITC. The parameters have been carefully selected to avoid issues of multicollinearity, and four mathematical models among the key parameters identified have been developed. The models have been tested, and accuracy of the models is found to be satisfactory. The models developed in this study describe part of the CO₂ capture process and can help to predict performance of the CO₂ capture process at ITC under different conditions. Some results from a preliminary validation process will also be presented.