Repeatability,Sensitivity, and Uncertainty Analyses of the BANCS Model Developed to Predict Annual Streambank Erosion Rates

Accelerated streambank erosion caused by channel instability can be the leading cause of sediment impairment of streams. Obtaining accurate streambank erosion rates for sediment budgeting and prioritizing mitigation efforts can be difficult and costly. One approach to quantifying streambank erosion rates is through the development and implementation of an empirically derived “Bank Assessment for Non‐point Source Consequences of Sediment” (BANCS) model. This study aims to improve the BANCS model application by evaluating repeatability between users and identifying sensitive and/or uncertain model inputs. Statistical analysis of streambank evaluations conducted by 10 different individuals suggests the implementation of the BANCS model may not be repeatable. This finding may be due to sensitive model inputs, such as streambank height and near‐bank stress level prediction method selection, and/or uncertain model inputs, such as bank material identification and the associated adjustment of erosion potential. Furthermore, it was found assessing streambanks as a group by obtaining a measure of central tendency from individual evaluations, as well as obtaining a higher level of training, may improve model implementation precision. Application of these suggestions may result in improved prediction of streambank erosion rates utilizing the BANCS model methodology.     

Valuing third sector sustainability organisations – qualitative contributions to systemic social transformation

The number and diversity of civil society or third sector sustainability organisations (TSSOs) have increased in recent decades. TSSOs play a prominent role in local approaches to sustainability. However, the contributions made by TSSOs are not fully understood, beyond a limited suite of quantifiable outputs and impacts. In this qualitative study, we examine how four TSSOs from two Australian regions, Tasmania and Queensland's Sunshine Coast, contribute to social transformation beyond discrete outputs. We examine the operation, ethos, scope and influence of these organisations over time. In so doing, we identify three common ways in which these organisations facilitate social change: by (i) enhancing social connectivity through boundary work; (ii) mobilising participatory citizenship and (iii) contributing to social learning. We conclude that TSSOs contribute significantly to the systemic social conditions that enable change for sustainability and the development of community resilience and well-being, but do so in ways undervalued by existing metrics, formal evaluation processes and funding models. Clearer recognition of, and strategic emphasis on, these qualitative contributions to social transformation is vital in ensuring that TSSOs remain viable and effective over the long term.     

Characterization, reactivity, source apportionment, and potential source areas of ambient volatile organic compounds in a typical tropical city

Based on one-year observation, the concentration, sources, and potential source areas of volatile organic compounds (VOCs) were comprehensively analyzed to investigate the pollution characteristics of ambient VOCs in Haikou, China. The results showed that the annual average concentration of total VOCs (TVOCs) was 11.4 ppbV, and the composition was dominated by alkanes (8.2 ppbV, 71.4%) and alkenes (1.3 ppbV, 20.5%). The diurnal variation in the concentration of dominant VOC species showed a distinct bimodal distribution with peaks in the morning and evening. The greatest contribution to ozone formation potential (OFP) was made by alkenes (51.6%), followed by alkanes (27.2%). The concentrations of VOCs and nitrogen dioxide (NO₂) in spring and summer were low, and it was difficult to generate high ozone (O₃) concentrations through photochemical reactions. The significant increase in O₃ concentrations in autumn and winter was mainly related to the transmission of pollutants from the northeast. Traffic sources (40.1%), industrial sources (19.4%), combustion sources (18.6%), solvent usage sources (15.5%) and plant sources (6.4%) were identified as major sources of VOCs through the positive matrix factorization (PMF) model. The southeastern coastal areas of China were identified as major potential source areas of VOCs through the potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models. Overall, the concentration of ambient VOCs in Haikou was strongly influenced by traffic sources and long-distance transport, and the control of VOCs emitted from vehicles should be strengthened to reduce the active species of ambient VOCs in Haikou, thereby reducing the generation of O₃.     

The bean method as a tool to measure sensitive behavior

Conservationists need to measure human behavior to guide decisions and evaluate their impact. However, activities can be misreported and reporting accuracy may change following conservation interventions, making it hard to verify any apparent changes. Techniques for asking sensitive questions are increasingly integrated into survey designs to improve data quality, but some can be costly or hard for nonexperts to implement. We demonstrate a straightforward, low-cost approach, the bean method in which respondents give anonymous answers by adding a colored bean to a jar to denote a yes or no response. We applied the bean method to measure wild-meat hunting and trading over 2 years at a conservation-project (hunting reduction) site in Gola Forest, Liberia. We extended the technique to accommodate questions about hunting and meat-selling frequency. We compared responses given using the bean method and direct questioning for groups that did and did not participate in conservation interventions. Results from the bean method corresponded to those from direct questioning, and there was no indication of change in question sensitivity following conservation interventions. Estimates from both methods indicated that wild-meat trading decreased in project and nonproject households (from 36% to 20%) and that hunting decreased in 1 project group (38–28%). Where inconsistent answers were given (2–6% of respondents), differences were in both directions and were most likely attributable to measurement error. The bean method was quick and straightforward to administer in a low-literacy setting. We showed how it can be modified for answers of more than 2 categories and consider it a valuable tool that could be adapted for a wide range of conservation settings.     

Channel Evolution Models as Predictors of Sediment Yield

This paper recounts our predictions of channel evolution of the Black Vermillion River (BVR) and sediment yields associated with the evolutionary sequence. Channel design parameters allowed for the prediction of stable channel form and coincident sediment yields. Measured erosion rates and basin‐specific bank erosion curves aided in prediction of the stream channel succession time frame. This understanding is critical in determining how and when to mitigate a myriad of instability consequences. The BVR drains approximately 1,062 km² in the glaciated region of Northeast Kansas. Once tallgrass prairie, the basin has been modified extensively for agricultural production. As such, channelization has shortened the river by nearly 26 km from pre‐European dimensions; shortening combined with the construction of numerous flow‐through structures have produced dramatic impacts on discharge and sediment dynamics. Nine stream reaches were established within three main tributaries of the BVR in 2007. Reaches averaged 490 m in length, were surveyed, and assessed for channel stability, while resurveys were conducted annually through 2010 to monitor change. This work illustrates the association of current stream state, in‐channel sediment contributions, and prediction of future erosion rates based on stream evolution informed by multiple models. Our findings suggest greater and more rapid sedimentation of a federal reservoir than has been predicted using standard sediment prediction methods.     

三亚城区PM2.5中水溶性离子特征与来源分析

基于2019年三亚城区站点PM_2.5中水溶性离子在线观测数据,分析了水溶性离子的质量浓度水平、不同时间尺度和不同PM_2.5浓度下的特征,探讨了气象因子对离子组分的影响,通过主成分分析（PCA）解析来源.结果表明：2019年三亚城区总水溶性离子（TWSI）质量浓度为8.173 μg·m^-3,占ρ（PM_2.5）的58.4%,各离子质量浓度大小依次为：ρ（SO₄^2-） > ρ（NO₃^-） > ρ（K⁺） > ρ（NH₄⁺） > ρ（Na⁺） > ρ（Cl^-） > ρ（Ca²⁺） > ρ（F^-） > ρ（Mg²⁺） > ρ（NO₂^-）,其中二次离子SO₄^2-、NO₃^-、NH₄⁺（SNA）和K⁺为主要离子组分,占总水溶性离子的80.0%,海盐粒子Na⁺及Cl^-之和占比为14.7%,且与风速呈显著正相关;TWSI季节浓度变化特征明显,秋季最高,春冬季次之,夏季最低,主要与秋冬季风速较大、主导风向转为东北风,易受外来传输有关;SO₄^2-在各个季节均是浓度及占比最高的离子,硫氧化率（SOR）的日均值均大于0.1,存在显著的SO₂向SO₄^2-转化的过程;PCA分析结果表明三亚城区水溶性离子主要受海洋源、二次源及生物质燃烧源的影响.     

三亚市臭氧污染特征、输送路径及潜在源区分析

基于2015-2019年三亚市空气质量自动监测数据和气象观测资料,结合后向轨迹聚类与潜在源区分析等方法,分析了三亚市O₃污染特征。结果表明:2015-2019年三亚市O₃浓度总体优良,优良天数比例为97.9%(标准状态),超标天均为轻度污染,多发生在秋冬季。O₃浓度与平均相对湿度、气温和降水量呈负相关关系,与平均风速呈正相关关系,同时与风向密切相关。6-8月气温较高,主导风向为偏南风,O₃及其前体物以本地排放为主,O₃浓度较低;秋冬季盛行东北风,易受到来自内陆的污染传输影响,O₃浓度相对较高。当日最高气温为20~30℃、日均相对湿度为65%~85%、日均风速为3~8 m/s、主导风向为东北风时,三亚市发生O₃超标的概率较高。台风外围和冷高压南下是导致三亚市O₃超标的2种典型天气形势。经聚类分析得到,2019年2个污染过程气团输送路径均来自东北方向,潜在源区分析WPSCF与WCWT的高值区一致性较好,均表明珠三角地区是三亚市重要的O₃污染潜在源区,需要加强与珠三角地区O₃污染的联防联控。     

Effects of social networks on interventions to change conservation behavior

Social networks are critical to the success of behavioral interventions in conservation because network processes such as information flows and social influence can enable behavior change to spread beyond a targeted group. We investigated these mechanisms in the context of a social marketing campaign to promote a wildlife poisoning hotline in Cambodia. With questionnaire surveys we measured a social network and knowledge and constructs from the theory of planned behavior at 3 points over 6 months. The intervention initially targeted ∼11% (of 365) of the village, but after 6 months ∼40% of the population was knowledgeable about the campaign. The likelihood of being knowledgeable nearly doubled with each additional knowledgeable household member. In the short term, there was also a modest, but widespread improvement in proconservation behavioral intentions, but this did not persist after 6 months. Estimates from stochastic actor-oriented models suggested that the influences of social peers, rather than knowledge, were driving changes in intention and contributed to the failure to change behavioral intention in the long term, despite lasting changes in attitudes and perceived norms. Our results point to the importance of accounting for the interaction between networks and behavior when designing conservation interventions.