平原河网地区非点源污染风险差异化分区防控研究

土地利用优化和空间防控策略对非点源污染风险控制及水环境质量的改善具有重要意义。本文以太湖流域典型平原河网地区-上海市青浦区为研究对象,将灰色线性规划模型与最小累积阻力模型相结合,以控制非点源污染风险和增加经济效益、生态效益为目标,进行土地利用结构优化与空间分区防控研究,在空间上划设了水资源保育区、水资源重点防护区、非点源污染一般阻控区、非点源污染中等阻控区及非点源污染重点阻控区,并针对不同分区提出具有针对性的防控措施。与2012年相比,预测2020年优化防控方案下,可减少总氮、总磷的输出10.96%和41.33%。由此表明,优化土地利用结构和构建空间差异化防控机制是有效调控非点源污染风险,实现区域可持续土地利用,促进经济发展和保证生态环境安全的有效途径。     

城市电力供应系统公共安全风险评估体系及应用

城市电力供应系统与城市公共安全关系紧密，文章分析了导致城市电力供应系统故障或事故的主要风险因素、事故类型及其风险程度，建立了城市电力供应系统公共安全风险评估体系。利用建立的风险评估体系，对某市电力供应系统的安全性进行了风险评估，同时验证了该体系在城市电力供应系统风险评估中的良好适用性。     

Mowers versus growers: Riparian buffer management in the Southern Blue Ridge Mountains,USA

Despite long-standing knowledge of the benefits of riparian buffers for mitigating nonpoint source pollution, many streams are unprotected by buffers. Even landowners who understand ecological values of buffers mow riparian vegetation to the streambank. Do trends in rural riparian conditions reflect the development of riparian forest science? What motivates residential riparian management actions? Using high-resolution orthoimagery, we quantified riparian conditions and trends between 1998 and 2015 in the rural upper Little Tennessee River basin in Macon County, North Carolina and explored how landowners view riparian zone management and riparian restoration programs. Buffer composition in 2015 was as follows: no buffer (32.5%), narrow (19.3%), forested (26.7%), shrub (7.2%), and intermediate (7.0%). Relative to 1998, the greatest decrease occurred in the no buffer class (−17.7%, 46 km) and the largest increases occurred in the shrub (+72.5%, 20 km) and narrow (12.6%, 14 km) classes. Forested buffer marginally increased. Semi-structured interview data suggest that landowners prioritize recreational and scenic aspects of riparian buffers over ecological functions such as filtration and bank stabilization. Riparian restoration programs might be made more enticing to non-adopters if outreach language appealed to landowner priorities, design elements demonstrated intentional management, and program managers highlighted areas where ecological goals and landowner values align.     

Fuzzy experts on recreational vessels, a risk modelling approach for marine invasions

Understanding risks from the human-mediated spread of non-indigenous species (NIS) is a critical component of marine biosecurity management programmes. Recreational boating is well-recognised as a NIS pathway, especially at a regional scale. Assessment of risks from this pathway is therefore desirable for coastal environments where recreational boating occurs. However, formal or quantitative risk assessment for the recreational vessel pathway is often hampered by lack of data, hence often relies on expert opinion. The use of expert opinion itself is sometimes limited by its inherent vagueness, which can be an important source of uncertainty that reduces the validity and applicability of the assessment. Fuzzy logic, specifically interval type-2 fuzzy logic, is able to model and propagate this type of uncertainty, and is a useful technique in risk assessment where expert opinion is relied upon. The present paper describes the implementation of a NIS fuzzy expert system (FES) for assessing the risk of invasion in marine environments via recreational vessels. The FES was based on expert opinion gathered through systematic elicitation exercises, designed to acknowledge important uncertainty sources (e.g., underspecificity and ambiguity). The FES, using interval type-2 fuzzy logic, calculated an invasion risk value (integrating NIS infection and detection probabilities) for a range of invasion scenarios. These scenarios were defined by all possible combinations of two vessel types (moored and trailered), five vessel components (hull, deck, internal spaces, anchor, fishing gear), two infection modes (fouling, water/sediment retention) and six frequently visited marine habitats (marina, mooring, farm, ramp, wharf, anchorage). Although invasion risk values determined using the FES approach was scenario-specific, general patterns were identified. Moored vessels consistently showed higher invasion risk values than trailered vessels. Invasion risk values were higher for anchorages, moorings and wharves. Similarly, hull-fouling was revealed as the highest infection risk mode after pooling results across all habitats. The NIS fuzzy expert system presented here appears as a valuable prioritising and decision-making tool for NIS research, prevention and control activities. Its easy implementation and wide applicability should encourage the development and application of this type of system as an integral part of biosecurity, and other environmental management plans.     

驾驶员风险认知能力对交通安全的影响

为辨别不同驾驶员风险认知能力对驾驶安全的影响。通过设置13种存在潜在风险的交通情景,引入惩罚用时机制,利用驾驶模拟器,对熟练驾驶员和非熟练驾驶员在风险认知培训前后的风险认知能力进行比较,找出不同驾驶员对风险认知的差异。试验结果显示,熟练驾驶员的风险认知能力比非熟练驾驶员要高,两者在引起交通风险的因素上是不同的,培训后的风险认知能力较之前有很大提高。培训能够拓宽驾驶员对潜在风险的认知程度,更好地将驾驶员的操作技能、知识体系和外在行为衔接在一起,从而减少交通事故的发生。     

Targeted Application of Seasonal Load Duration Curves Using Multivariate Analysis in Two Watersheds Flowing Into Lake Houston1

Teague, Aarin, Philip B. Bedient, and Birnur Guven, 2011. Targeted Application of Seasonal Load Duration Curves Using Multivariate Analysis in Two Watersheds Flowing Into Lake Houston. Journal of the American Water Resources Association (JAWRA) 47(3):620‐634. DOI: 10.1111/j.1752‐1688.2011.00529.x Abstract: Water quality is a problem in Lake Houston, the primary source of drinking water for the City of Houston, Texas, due to pollutant loads coming from the influent watersheds, including Spring Creek and Cypress Creek. Statistical analysis of the historic water quality data was developed to understand the source characterization and seasonality of the watershed. Multivariate analysis including principal component, cluster, and discriminant analysis provided a custom seasonal assessment of the watersheds so that loading curves may be targeted for season specific pollutant source characterization. The load duration curves have been analyzed using data collected by the U.S. Geologic Survey with corresponding City of Houston water quality data at the sites to characterize the behavior of the pollutant sources and watersheds. Custom seasons were determined for Spring Creek and Cypress Creek watersheds and pollutant source characterization compared between the seasons and watersheds.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

A review of public acceptance of nature-based solutions: The ‘why’, ‘when’, and ‘how’ of success for disaster risk reduction measures

Nature-based solutions (NbS) are increasingly recognized as sustainable approaches to address societal challenges. Disaster risk reduction (DRR) has benefited by moving away from purely ‘grey’ infrastructure measures towards NbS. However, this shift also furthers an increasing trend of reliance on public acceptance to plan, implement and manage DRR measures. In this review, we examine how unique NbS characteristics relate to public acceptance through a comparison with grey measures, and we identify influential acceptance factors related to individuals, society, and DRR measures. Based on the review, we introduce the PA-NbS model that highlights the role of risk perception, trust, competing societal interests, and ecosystem services. Efforts to increase acceptance should focus on providing and promoting awareness of benefits combined with effective communication and collaboration. Further research is required to understand interconnections among identified factors and how they can be leveraged for the success and further uptake of NbS.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-021-01502-4.     

北京市地下水中典型抗生素分布特征与潜在风险

应用气相色谱与质谱联用仪分析了北京市地下水内磺胺类(SAs)、氟喹诺酮类(FQs)、四环素类(TCs)、β-内酰胺类和大环内酯类等5大类抗生素.结果表明,北京地下水抗生素以SAs、FQs和TCs等3类为主,检出率分别为78.9%、100%和47.3%,其中甲氧苄氨嘧啶(TMP)、环丙沙星(CIP)和诺氟沙星(NOR)检出率均在70%以上.污灌区地下水样点抗生素浓度显著高于水源地和南水回灌区样点,磺胺二甲嘧啶(SDD)和磺胺嘧啶(SDZ)在污灌区检出峰值达到236 ng·L-1和96.8ng·L-1.生态风险评价结果表明,研究区地下水抗生素污染风险较小,但在污灌区显示中等或高等风险等级.CIP应作为研究区地下水抗生素监测中的重点监测对象.     

南京北郊黑碳气溶胶的来源解析

利用七波段黑碳仪对2015年1~12月南京北郊地区黑碳(black carbon,BC)气溶胶实时监测,并结合黑碳仪模型对该期间内BC进行来源解析,探讨化石燃料排放产生BC(BCff)与生物质燃烧产生BC(BCbb)各自的贡献大小.结果表明,观测期间BC的吸收波长指数(α)和生物质燃烧对BC的贡献百分比(BB)的变化范围都较大但趋势较为一致;冬季α值偏高而夏季α值较低,表明不同季节时间BC来源和强度的差异性.BCff在各季节BC总浓度中占比略有不同但均高于75%;BC、BCff和BCbb的日变化趋势均呈双峰特征,在07:00~09:00和18:00~21:00左右浓度有最大值;全天中,BCff对BC贡献最大,浓度值约为BCbb的3~5倍;夜晚BC浓度普遍高于白天,其平均浓度值是白天的1.2倍.由浓度权重轨迹分析的结果可知,影响南京北郊地区高浓度BC的源区主要集中在浙江、安徽以及江西和福建等地区.