Seasonality of Soil Erosion Under Mediterranean Conditions at the Alqueva Dam Watershed

The Alqueva reservoir created the largest artificial lake of Western Europe in 2010. Since then, the region has faced challenges due to land-use changes that may increase the risk of erosion and shorten the lifetime of the reservoir, increasing the need to promote land management sustainability. This paper investigates the aspect of seasonality of soil erosion using a comprehensive methodology that integrates the Revised Universal Soil Loss Equation (RUSLE) approach, geographic information systems, geostatistics, and remote-sensing. An experimental agro-silvo pastoral area (typical land-use) was used for the RUSLE factors update. The study confirmed the effect of seasonality on soil erosion rates under Mediterranean conditions. The highest rainfall erosivity values occurred during the autumn season (433.6 MJ mm ha^?1 h^?1), when vegetation cover is reduced after the long dry season. As a result, the autumn season showed the highest predicted erosion (9.9 t ha^?1), contributing 65 % of the total annual erosion. The predicted soil erosion for winter was low (1.1 t ha^?1) despite the high rainfall erosivity during that season (196.6 MJ mm ha^?1 h^?1). The predicted annual soil loss was 15.1 t ha^?1, and the sediment amount delivery was 4,314 × 10³ kg. Knowledge of seasonal variation would be essential to outline sustainable land management practices. This model will be integrated with World Overview of Conservation Approaches and Technologies methods to support decision-making in that watershed, and it will involve collaboration with both local people and governmental institutions.     

Errors and uncertainties in a gridded carbon dioxide emissions inventory

Emission inventories (EIs) are the fundamental tool to monitor compliance with greenhouse gas (GHG) emissions and emission reduction commitments. Inventory accounting guidelines provide the best practices to help EI compilers across different countries and regions make comparable, national emission estimates regardless of differences in data availability. However, there are a variety of sources of error and uncertainty that originate beyond what the inventory guidelines can define. Spatially explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes and there are no specific guidelines to achieve spatial emission estimates. The errors and uncertainties associated with the spatial estimates are unique to the approaches employed and are often difficult to assess. This study compares the global, high-resolution (1 km), fossil fuel, carbon dioxide (CO₂), gridded EI Open-source Data Inventory for Anthropogenic CO₂ (ODIAC) with the multi-resolution, spatially explicit bottom-up EI geoinformation technologies, spatio-temporal approaches, and full carbon account for improving the accuracy of GHG inventories (GESAPU) over the domain of Poland. By taking full advantage of the data granularity that bottom-up EI offers, this study characterized the potential biases in spatial disaggregation by emission sector (point and non-point emissions) across different scales (national, subnational/regional, and urban policy-relevant scales) and identified the root causes. While two EIs are in agreement in total and sectoral emissions (2.2% for the total emissions), the emission spatial patterns showed large differences (10~100% relative differences at 1 km) especially at the urban-rural transitioning areas (90–100%). We however found that the agreement of emissions over urban areas is surprisingly good compared with the estimates previously reported for US cities. This paper also discusses the use of spatially explicit EIs for climate mitigation applications beyond the common use in atmospheric modeling. We conclude with a discussion of current and future challenges of EIs in support of successful implementation of GHG emission monitoring and mitigation activity under the Paris Climate Agreement from the United Nations Framework Convention on Climate Change (UNFCCC) 21st Conference of the Parties (COP21). We highlight the importance of capacity building for EI development and coordinated research efforts of EI, atmospheric observations, and modeling to overcome the challenges.

     

基质比对ABR厌氧氨氧化工艺脱氮性能的影响

为解决厌氧氨氧化底物去除不彻底导致总氮去除偏低的问题,通过控制不同的进水基质比,对厌氧折流板反应器(ABR)的厌氧氨氧化脱氮性能进行了研究.结果表明,ABR厌氧氨氧化系统最佳进水N_2~O--N/NH+4-N为1.34,此时NH+4-N和N_2~O--N的去除率同时达到99.99%左右,总氮去除率达到峰值为87%,当进水N_2~O--N/NH+4-N从1逐渐降低至0.49和从1.34逐渐提高至1.62时,反应器对NH+4-N和N_2~O--N的绝对去除量较为稳定,NH+4-N或N_2~O--N过量对ABR厌氧氨氧化系统没有产生明显抑制;此外,不同基质比条件下,NH+4-N和N_2~O--N的去除基本在第1隔室完成,基质比变化对ABR各隔室的脱氮效果没有产生显著影响,ABR厌氧氨氧化系统对基质浓度的变化具有较好的稳定性.     

Analysis of PFAAs in American alligators part 1: Concentrations in alligators harvested for consumption during South Carolina public hunts

Environmental contamination resulting from the production or release of harmful chemicals can lead to negative consequences for wildlife and human health. Perfluorinated alkyl acids (PFAAs) were historically produced as protective coatings for many household items and currently persist in the environment, wildlife, and humans. PFAAs have been linked to immune suppression, endocrine disruption, and developmental toxicity in wildlife and laboratory studies. This study examines the American alligator, Alligator mississippiensis, as an important indicator of ecosystem contamination and a potential pathway for PFAA exposure in humans. Alligator meat harvested in the 2015 South Carolina (SC) public hunt season and prepared for human consumption was collected and analyzed for PFAAs to determine meat concentrations and relationships with animal body size (total length), sex, and location of harvest. Of the 15 PFAAs analyzed, perfluorooctane sulfonate (PFOS) was found in all alligator meat samples and at the highest concentrations (median 6.73 ng/g). No relationship was found between PFAA concentrations and total length or sex. Concentrations of one or all compounds varied significantly across sampling locations, with alligators harvested in the Middle Coastal hunt unit having the highest PFOS concentrations (median 16.0 ng/g; p = 0.0001). Alligators harvested specifically from Berkley County, SC (located in the Middle Coastal hunt unit) had the highest PFOS concentrations and the greatest number of PFAAs detected (p < 0.0001). The site-specific nature of PFAA concentrations in alligator meat observed in this study suggests a source of PFAA contamination in Berkley County, SC.     

Economic analysis of adaptive strategies for flood risk management under climate change

Climate change requires reconsideration of flood risk management strategies. Cost-benefit analysis (CBA), an economic decision-support tool, has been widely applied to assess these strategies. This paper aims to describe and discuss probabilistic extensions of CBA to identify welfare-maximising flood risk management strategies under climate change. First, uncertainty about the changes in return periods of hydro-meteorological extremes is introduced by probability-weighted climate scenarios. Second, the analysis is extended by learning about climate change impacts. Learning occurs upon the probabilistic arrival of information. We distinguish between learning from scientific progress, from statistical evidence and from flood disasters. These probabilistic extensions can be used to analyse and compare the economic efficiency and flexibility of flood risk management strategies under climate change. We offer a critical discussion of the scope of such extensions and options for increasing flexibility. We find that uncertainty reduction from scientific progress may reduce initial investments, while other types of learning may increase initial investments. This requires analysing effects of different types of learning. We also find that probabilistic information about climate change impacts and learning is imprecise. We conclude that risk-based CBA with learning improves the flexibility of flood risk management strategies under climate change. However, CBA provides subjective estimates of expected outcomes and reflects different decision-maker preferences than those captured in robustness analyses. We therefore advocate robustness analysis in addition to, or combined with, cost-benefit analysis to support local investment decisions on flood risk reduction and global strategies on allocation of adaptation funds for flood risk management.     

CSTR和MBR反应器的短程硝化快速启动

为实现短程硝化的快速启动,采用完全混合反应器(CSTR)和膜生物反应器(MBR)进行短程硝化启动性能对比研究,考察两个反应器在启动时间、氮素转化和污泥性能3个方面的差异.结果表明在进水C/N=1,温度为30℃±1℃,pH为7.5~8.0,DO为0.6~1.0 mg·L~(-1),结合缺氧/好氧比为1∶3(15 min∶45 min)和缩短HRT,CSTR和MBR分别运行56 d和44 d成功启动短程硝化,MBR启动周期较短.运行至第14 d、第28 d和第56 d时,CSTR和MBR亚硝累积率平均为51%、66%、89%和50%、71%、93%,硝酸盐氮生成速率(以NO_3~--N/MLVSS计)依次为7.4、4.0、1.7和7.6、3.5、1.0 mg·(g·h)~(-1),MBR在第28 d和第56 d表现出较高的亚硝累积率和较低的NO_3~--N产率,有利于短程硝化的快速启动.整个运行过程中,两个反应器内的亚硝化污泥均呈黄色,SVI在55~110 mL·g~(-1),MLVSS/MLSS稳定在0.6~0.8左右,良好的污泥性能为CSTR和MBR短程硝化的快速启动创造了有利条件.MBR在短程硝化快速启动中展现出更明显的优势.     

Ancient pests: the season of the Santorini Minoan volcanic eruption and a date from insect chitin

Attributing a season and a date to the volcanic eruption of Santorini in the Aegean has become possible by using preserved remains of the bean weevil, Bruchus rufipes, pests of pulses, from the storage jars of the West House, in the Bronze Age settlement at Akrotiri. We have applied an improved pre-treatment methodology for dating the charred insects, and this provides a date of 1744–1538 BC. This date is within the range of others obtained from pulses from the same context and confirms the utility of chitin as a dating material. Based on the nature of the insect material and the life cycle of the species involved, we argue for a summer eruption, which took place after harvest, shortly after this material was transported into the West House storeroom.     

Predicting ectotherm disease vector spread—benefits from multidisciplinary approaches and directions forward

The occurrence of ectotherm disease vectors outside of their previous distribution area and the emergence of vector-borne diseases can be increasingly observed at a global scale and are accompanied by a growing number of studies which investigate the vast range of determining factors and their causal links. Consequently, a broad span of scientific disciplines is involved in tackling these complex phenomena. First, we evaluate the citation behaviour of relevant scientific literature in order to clarify the question “do scientists consider results of other disciplines to extend their expertise?” We then highlight emerging tools and concepts useful for risk assessment. Correlative models (regression-based, machine-learning and profile techniques), mechanistic models (basic reproduction number R ₀) and methods of spatial regression, interaction and interpolation are described. We discuss further steps towards multidisciplinary approaches regarding new tools and emerging concepts to combine existing approaches such as Bayesian geostatistical modelling, mechanistic models which avoid the need for parameter fitting, joined correlative and mechanistic models, multi-criteria decision analysis and geographic profiling. We take the quality of both occurrence data for vector, host and disease cases, and data of the predictor variables into consideration as both determine the accuracy of risk area identification. Finally, we underline the importance of multidisciplinary research approaches. Even if the establishment of communication networks between scientific disciplines and the share of specific methods is time consuming, it promises new insights for the surveillance and control of vector-borne diseases worldwide.     

Best‐practice recommendations for estimating interaction effects using meta‐analysis

One of the key advantages of meta‐analysis (i.e., a quantitative literature review) over a narrative literature review is that it allows for formal tests of interaction effects—namely, whether the relationship between two variables is contingent upon the value of another (moderator) variable. Interaction effects play a central role in organizational science research because they highlight boundary conditions of a theory: Conditions under which relationships change in strength and/or direction. This article describes procedures for estimating interaction effects using meta‐analysis, distills the technical literature for a general readership of organizational science researchers, and includes specific best‐practice recommendations regarding actions researchers can take before and after data collection to improve the accuracy of substantive conclusions regarding interaction effects investigated meta‐analytically. Copyright © 2010 John Wiley & Sons, Ltd.