Structure and Content of the Discourse on Climate Change in the Blogosphere: The Big Picture

Based on the texts of 1.3 million blog posts and the structure of the links between the blogs in which these posts appeared, this study presents an analysis of the discourse on climate change in the English-language blogosphere. Our approach combines community detection with probabilistic topic modeling to show how topics related to climate change are discussed across various parts of the blogosphere. We find that there is one community of predominantly climate skeptical blogs but several accepter communities. The topic analysis reveals a series of issues that are characteristic of the climate change discourse in the blogosphere. Two topics, one related to climate change science and one related to climate change politics, are particularly important for characterizing the discourse. We also find that the distribution of topics over the communities cuts across the divide between skeptics and non-skeptics (accepters) and that there are differences in the patterns of interactions between the skeptics and different groups of accepters.     

Geographic range size and extinction risk assessment in nomadic species

Geographic range size is often conceptualized as a fixed attribute of a species and treated as such for the purposes of quantification of extinction risk; species occupying smaller geographic ranges are assumed to have a higher risk of extinction, all else being equal. However many species are mobile, and their movements range from relatively predictable to‐and‐fro migrations to complex irregular movements shown by nomadic species. These movements can lead to substantial temporary expansion and contraction of geographic ranges, potentially to levels which may pose an extinction risk. By linking occurrence data with environmental conditions at the time of observations of nomadic species, we modeled the dynamic distributions of 43 arid‐zone nomadic bird species across the Australian continent for each month over 11 years and calculated minimum range size and extent of fluctuation in geographic range size from these models. There was enormous variability in predicted spatial distribution over time; 10 species varied in estimated geographic range size by more than an order of magnitude, and 2 species varied by >2 orders of magnitude. During times of poor environmental conditions, several species not currently classified as globally threatened contracted their ranges to very small areas, despite their normally large geographic range size. This finding raises questions about the adequacy of conventional assessments of extinction risk based on static geographic range size (e.g., IUCN Red Listing). Climate change is predicted to affect the pattern of resource fluctuations across much of the southern hemisphere, where nomadism is the dominant form of animal movement, so it is critical we begin to understand the consequences of this for accurate threat assessment of nomadic species. Our approach provides a tool for discovering spatial dynamics in highly mobile species and can be used to unlock valuable information for improved extinction risk assessment and conservation planning.     

Physiologically based pharmacokinetic modeling of perfluoroalkyl substances in the human body

Currently, there are limited data on the levels of perfluoroalkyl substances other than perfluorooctane sulfonic acid and perfluorooctanoic acid in the human body. Most of this information has been extracted from biological monitoring of plasma while the occurrence of perfluoroalkyl substances in other human tissues is rarely studied. The objective of the present study was to develop a physiologically based pharmacokinetic model to assess the concentration of perfluoroalkyl substances in human tissues, based on an existing model previously validated for perfluorooctane sulfonic acid and perfluorooctanoic acid. Experimental data on concentrations of perfluoroalkyl substances in human tissues from individuals in Tarragona County (Catalonia, Spain) were used to estimate the values of some distribution and elimination parameters needed for the simulation. No significant correlations were found between these parameters and the chain lengths. The model was finally validated for five perfluoroalkyl substances.     

Machine learning based quantitative consequence prediction models for toxic dispersion casualty

Incidental release of toxic chemicals can pose extreme danger to life in the vicinity. Therefore, it is crucial for emergency responders, plant operators, and safety professionals to have a fast and accurate prediction to evaluate possible toxic dispersion life-threatening consequences. In this work, a toxic chemical dispersion casualty database that contains 450 leak scenarios of 18 toxic chemicals is constructed to develop a machine learning based quantitative property-consequence relationship (QPCR) model to estimate the affected area caused by toxic chemical release within a certain death rate. The results show that the developed QPCR model can predict the toxic dispersion casualty range with root mean square error of maximum distance, minimum distance, and maximum width less than 0.2, 0.4, and 0.3, which indicates that the constructed model has satisfying accuracy in predicting toxic dispersion ranges under different lethal consequences. The model can be further expanded to accommodate more toxic chemicals and leaking scenarios.     

Land-use forecasting and hydrologic model integration for improved land-use decision support

This paper develops a methodology for integrating a land-use forecasting model with an event scale, rainfall-runoff model in support of improving land-use policy formulation at the watershed scale. The models selected for integration are loosely coupled, structured upon a common GIS platform that facilitates data exchange. The hydrologic model HEC-HMS is calibrated for a specific storm event that occurred within central Washington State. The land-use forecasting model, What If? is implemented to forecast future spatial distributions of low-density residential land-uses under low and high population growth estimates. Forecasted land-use distribution patterns for the years 2015, 2025, and 2050 are then used as land-use data input for the calibrated hydrologic model, keeping all other parameters constant. Impacts to the stream discharge hydrograph are predicted as the study area becomes increasingly developed as forecasted by What If?. The initial results of this integration process demonstrate the synergy that can be generated through the linkage of the selected models. The ability to quantifiably forecast the potential hydrologic implications of proposed land-use policies before their implementation offers land-use decision-makers a valuable tool for discerning which proposed land-use alternatives will be effective at minimizing storm water runoff.     

The integrated project AquaTerra of the EU sixth framework lays foundations for better understanding of river-sediment-soil-groundwater systems

The integrated project "AquaTerra" with the full title "integrated modeling of the river-sediment-soil-groundwater system; advanced tools for the management of catchment areas and river basins in the context of global change" is among the first environmental projects within the sixth Framework Program of the European Union. Commencing in June 2004, it brought together a multidisciplinary team of 45 partner organizations from 12 EU countries, Romania, Switzerland, Serbia and Montenegro. AquaTerra is an ambitious project with the primary objective of laying the foundations for a better understanding of the behavior of environmental pollutants and their fluxes in the soil-sediment-water system with respect to climate and land use changes. The project performs research as well as modeling on river-sediment-soil-groundwater systems through quantification of deposition, sorption and turnover rates and the development of numerical models to reveal fluxes and trends in soil and sediment functioning. Scales ranging from the laboratory to river basins are addressed with the potential to provide improved river basin management, enhanced soil and groundwater monitoring as well as the early identification and forecasting of impacts on water quantity and quality. Study areas are the catchments of the Ebro, Meuse, Elbe and Danube Rivers and the Brévilles Spring. Here we outline the general structure of the project and the activities conducted within eleven existing sub-projects of AquaTerra.     

Assessing the impact of leather industries on the quality of water discharged into the East China Sea from Wenzhou Watersheds

Ammonium nitrogen and total germanium are among the main pollutants in the wastewater discharged from the leather industry. The intake of high concentrations of ammonium nitrogen and/or total germanium harms human health and biological species, as is well documented in literature. This paper focuses on assessing the trends of ammonium nitrogen and total germanium concentrations through time in two watersheds (Aojiang and Oujiang) in the Wenzhou metropolitan area of Zhejiang Province and their relationships with the released wastewater using regression and correlation statistics. The paper also utilizes the integrated pollution index to evaluate water quality in the two watersheds. Preliminary results show that, from 1992 to 1998 in the Aojing watershed, the concentrations of ammonium nitrogen and total germanium increased 13 and 14 times, respectively, decreasing somewhat after 1998, while between 1992 and 1997 in the Oujiang watershed, the concentrations increased, then decreased after 1997. The concentrations of ammonium nitrogen and total germanium are positively related to the amount of released wastewater. The concentrations of ammonium nitrogen and total germanium exceeded water standards 12 and 3 times, respectively, in Pingyang county of the Aojiang watershed, 14 and 3.3 times in Lucheng District of the Oujiang watershed, and 14 and 3.8 times in the Ouhai Oujiang watershed, respectively. In Pingyang county of the Aojiang watershed, the water quality degraded from Type III in 1992 to over Type V in 2003, and in the Oujiang watershed, the water quality degraded from Type II to over Type IV in 1999, when they were compared with the water quality standards. The water quality slightly improved in 2003 for the Oujiang watershed. It appears that pollution did have a direct positive correlation with leather industry production in the Pingyang Aojing watershed, while there was a negative correlation between the two in the Oujiang watershed. In these two watersheds, the integrated pollution index did not appear to relate to population dynamics and agricultural production. This paper also discusses the current new methodologies and approaches adopted nationally and internationally to reduce the contaminants and purify the environment for maintaining a sustainable and healthier environment in Wenzhou.     

An integrated fuzzy-stochastic modeling approach for risk assessment of groundwater contamination

An integrated fuzzy-stochastic risk assessment (IFSRA) approach was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with site conditions, environmental guidelines, and health impact criteria. The contaminant concentrations in groundwater predicted from a numerical model were associated with probabilistic uncertainties due to the randomness in modeling input parameters, while the consequences of contaminant concentrations violating relevant environmental quality guidelines and health evaluation criteria were linked with fuzzy uncertainties. The contaminant of interest in this study was xylene. The environmental quality guideline was divided into three different strictness categories: "loose", "medium" and "strict". The environmental-guideline-based risk (ER) and health risk (HR) due to xylene ingestion were systematically examined to obtain the general risk levels through a fuzzy rule base. The ER and HR risk levels were divided into five categories of "low", "low-to-medium", "medium", "medium-to-high" and "high", respectively. The general risk levels included six categories ranging from "low" to "very high". The fuzzy membership functions of the related fuzzy events and the fuzzy rule base were established based on a questionnaire survey. Thus the IFSRA integrated fuzzy logic, expert involvement, and stochastic simulation within a general framework. The robustness of the modeling processes was enhanced through the effective reflection of the two types of uncertainties as compared with the conventional risk assessment approaches. The developed IFSRA was applied to a petroleum-contaminated groundwater system in western Canada. Three scenarios with different environmental quality guidelines were analyzed, and reasonable results were obtained. The risk assessment approach developed in this study offers a unique tool for systematically quantifying various uncertainties in contaminated site management, and it also provides more realistic support for remediation-related decisions.     

深圳市工业区VOCs污染特征与臭氧生成敏感性

于2020年9~10月在深圳北部典型工业区开展在线观测以分析该地VOCs污染状况,并使用基于观测的模型(OBM)研究臭氧生成敏感性.观测期间VOCs的总浓度为48.5×10^-9,浓度水平上烷烃>含氧有机物(OVOCs)>卤代烃>芳香烃>烯烃>乙炔>乙腈.臭氧生成潜势(OFP)为320μg/m³,其中芳香烃、OVOCs以及烷烃贡献最大,这3类物种OFP贡献总和超过90%.乙烯与苯呈现“两峰一谷”的日变化特征,主要受到机动车排放的贡献.相对增量反应性(RIR)分析表明,削减人为源VOCs对控制当地臭氧生成最为有效,当中又应优先控制芳香烃;经典动力学曲线(EKMA)分析表明该片区臭氧生成处于过渡区,在开展VOCs区域联防联控的同时,需要在当地进行有力的NOx控制以强化该地区臭氧污染长期管控.     

Uncertainty Models for Estimates of Physical Characteristics of River Segments Over Large Areas

Spatially comprehensive estimates of the physical characteristics of river segments over large areas are required in many large‐scale analyses of river systems and for the management of multiple basins. Remote sensing and modeling are often used to estimate river characteristics over large areas, but the uncertainties associated with these estimates and their dependence on the physical characteristics of the segments and their catchments are seldom quantified. Using test data with varying degrees of independence, we derived analytical models of the uncertainty associated with estimates of upstream catchment area (CA), segment slope, and mean annual discharge for all river segments of a digital representation of the hydrographic network of France. Although there were strong relationships between our test data and estimates at the scale of France, there were also large relative local uncertainties, which varied with the physical characteristics of the segments and their catchments. Discharge and CA were relatively uncertain where discharge was low and catchments were small. Discharge uncertainty also increased in catchments with large rainfall events and low minimum temperature. The uncertainty of segment slope was strongly related to segment length. Our uncertainty models were consistent across large regions of France, suggesting some degree of generality. Their analytical formulation should facilitate their use in large‐scale ecological studies and simulation models.