A climate-change vulnerability and adaptation assessment for Brazil's protected areas

Brazil hosts the largest expanse of tropical ecosystems within protected areas (PAs), which shelter biodiversity and support traditional human populations. We assessed the vulnerability to climate change of 993 terrestrial and coastal-marine Brazilian PAs by combining indicators of climatic-change hazard with indicators of PA resilience (size, native vegetation cover, and probability of climate-driven vegetation transition). This combination of indicators allows the identification of broad climate-change adaptation pathways. Seventeen PAs (20,611 km²) were highly vulnerable and located mainly in the Atlantic Forest (7 PAs), Cerrado (6), and the Amazon (4). Two hundred fifty-eight PAs (756,569 km²), located primarily in Amazonia, had a medium vulnerability. In the Amazon and western Cerrado, the projected severe climatic change and probability of climate-driven vegetation transition drove vulnerability up, despite the generally good conservation status of PAs. Over 80% of PAs of high or moderate vulnerability are managed by indigenous populations. Hence, besides the potential risks to biodiversity, the traditional knowledge and livelihoods of the people inhabiting these PAs may be threatened. In at least 870 PAs, primarily in the Atlantic Forest and Amazon, adaptation could happen with little or no intervention due to low climate-change hazard, high resilience status, or both. At least 20 PAs in the Atlantic Forest, Cerrado, and Amazonia should be targeted for stronger interventions (e.g., improvement of ecological connectivity), given their low resilience status. Despite being a first attempt to link vulnerability and adaptation in Brazilian PAs, we suggest that some of the PAs identified as highly or moderately vulnerable should be prioritized for testing potential adaptation strategies in the near future.     

Risk assessment and risk reduction of an acrylonitrile production plant

Reducing accident occurrence in petrochemical plants is crucial, thus appropriately allocating management resources to safety investment is a vital issue for corporate management as international competition intensifies. Understanding the priority of safety investment in a rational way helps achieve this objective.In this study, we targeted an acrylonitrile plant. First, Dow Chemical's Fire and Explosion Index (F&EI) identified the reaction process as having the greatest physical risk. We evaluated the severity of accidents in the reaction process using the Process Safety Metrics advocated by the Center for Chemical Process Safety (CCPS); however, this index does not express damages a company actually experience. To solve this problem, we proposed a new metric that adds indirect cost to CCPS metrics. We adopted fault tree analysis (FTA) as a risk assessment method. In identifying top events and basic events, we attempted to improve the completeness of risk identification by considering accidents from the past, actual plant operation and equipment characteristics, natural disasters, and cyber-attacks and terrorist attacks. Consequently, we identified the top events with high priority in handling because of serious accidents as fire/explosion outside the reactor, fire/explosion inside the reactor, and reactor destruction. The new CCPS evaluation index proposed in this study found that fire and explosion outside the reactor has the highest severity. We considered the creation of the fault tree (FT) diagram of the top event, estimating the occurrence probability, and identifying the risk reduction part and capital investment aimed at risk reduction. As an economically feasible selection method for risk reduction investment, using the difference in loss amounts before and after safety investments indicated investment priority.     

太原汾河景区跨桥断面水体污染的时空变化模式研究

选取太原汾河景区跨桥断面8个监测点,在2012年3月—2013年10月期间对河流8项水质参数进行监测,并结合派生的水体综合污染指数及主成分分析方法分析和评价景区水污染时空变化特征。结果表明,景区水质污染变化时空差异明显,上游污染相对较小,下游污染较重;春季溶解氧和p H值变化幅度最大,夏季除总氮和氨氮外,其他各污染物均有显著变化特征,秋季则以氨氮、总氮和总磷变化最为显著。主成分分析结果显示,虽然各监测点水体污染的关键影响因子不同,但总磷是太原市河流水体污染的共同解释因子。     

Using culturomics and social media data to characterize wildlife consumption

Wildlife provides food, medicine, clothing, and other necessities for humans, but overexploitation can disrupt the sustainability of wildlife resources and severely threaten global biodiversity. Understanding the characteristics of consumer behavior is helpful for wildlife managers and policy makers, but the traditional survey methods are laborious and time-consuming. In contrast, culturomics may more efficiently identify the features of wildlife consumption. As a case study of the culturomics approach, we examined tiger bone wine consumption in China based on social media and Baidu search engine data. Tiger bone wine is one of the most purchased tiger products; its consumption is closely related to tiger poaching, which greatly threatens wild tiger survival. We searched a popular social media website for the term “tiger bone wine” and focused on posts that were originally created from 1 January 2012 to 31 December 2018. We filtered and classified posts related to the purchase, sale, or consumption of tiger bone wine and extracted information on providers, consumption motivations, year of production, and place of origin of the tiger bone wines based on the texts and photos of these posts. We found 756 posts related to tiger bone wine consumption, 113 of which mentioned providers of tiger bone wine, including friends (53%), elder relatives (37%), peer relatives (7%), and others (3%). Out of the 756 posts, 266 indicated the motivations of tiger bone wine consumption. Tiger bone wines were consumed as a tonic (34%), medicine (23%), game product (30%), and a symbol of wealth (28%). Some posts indicated ≥2 consumption motivations. These findings were consistent with the search queries from Baidu index. Such information could help develop targeted strategies for tiger conservation. The culturomics approach illustrated by our study is a rapid and cost-efficient way to characterize wildlife consumption.     

洪泽湖水体富营养化时空分布特征与影响因素分析

通过2014年—2017年对洪泽湖12个水质断面定期调查,采用营养状态指数(TLI)综合评价其水体富营养状态,同时应用主成分分析方法(PCA)分析其富营养化状态的时空变化特征。结果表明,洪泽湖70%以上的调查断面水质全年处于轻度富营养化状态,夏季是其富营养化最严重的季节;洪泽湖年内水体水质差异较大,而其水华特征并未呈现明显差异;洪泽湖富营养化很大程度上受制于营养盐的积累程度,并与湖泊透明度呈现极显著的负相关关系(p0.001),与湖水pH值呈现极显著的正相关关系。     

加速溶剂同时萃取和净化-气相色谱-三重四极杆串联质谱测定土壤和沉积物中8种多溴联苯醚

建立了土壤和沉积物中8种多溴联苯醚(PBDEs,BDE-28、BDE-47、BDE-99、BDE-100、BDE-153、BDE-154、BDE-183和BDE-209)加速溶剂同时萃取和净化-气相色谱-三重四极杆串联质谱(ASE-GC-MS-MS)的分析方法。通过优化加速溶剂萃取与弗罗里硅土在线净化和串联质谱多反应监测模式的条件,较好地去除基质干扰,并提高了三重四极杆串联质谱定性的准确性及定量的灵敏性。该方法采用改进的色谱柱能同时分析包括高溴代联苯醚BDE-209在内的8种PBDEs,其浓度范围为1～100 ng/mL(BDE-209为10～1 000 ng/mL),线性良好,线性回归系数均大于0.997。方法检出限为0.004～0.1 ng/g,方法回收率为75%～110%,方法精密度为2.4%～15.6%。适于批量处理土壤和沉积物中含有多组分痕量PBDEs的样品。     

土壤污染风险规制中的行政裁量研究

我国土壤污染风险规制在专家遴选标准、建设用地和农用地污染风险管控要求，以及风险管控措施等方面存在不同程度的行政裁量。社会理性和科学理性的缺失形成了土壤污染风险行政裁量困局。土壤污染信息制度中“适时公开”的规定使得公众缺乏必要污染信息，弱化其参与程度，导致对行政决定合法性的质疑。此外，土壤污染风险管控标准中专家遴选标准和论证规则的欠缺导致土壤污染风险规制科学理性的缺失。为此，需要建构关照事实和规范的协商式行政裁量模式，强调公众的实质性参与以弥合技术理性和公众理性的鸿沟。同时，在程序上确定专家遴选标准和风险管控标准的论证规则以保证土壤污染风险管控的科学性和客观性。在不妨碍行政裁量权灵活性和能动性的前提下，规范行政裁量权的行使，控制行政裁量权的滥用。     

我国安全生产行政执法统计指标体系研究与应用

我国安全生产行政执法统计指标体系自施行以来，一直存在统计指标体系过于繁杂、部分统计指标较笼统，未充分体现安全生产重点工作及其成效等问题，创新改革安全生产行政执法统计制度具有重要的理论意义和实用价值。通过梳理安全生产行政执法统计指标体系演变脉络，在实地调研和现场访谈的基础上，基于PDCA理论提出以执法人员-执法对象-执法行为“三位一体”的安全生产行政执法统计指标体系，明确包含执法力量、执法对象、执法检查和事故查处等方面的综合评价指标，并在实践中得以应用和检验，为全面分析安全生产执法效能拓展空间，统计制度的后续修订和安全生产综合分析工作奠定基础。     

时间因素对钻屑瓦斯解吸指标K1值测定的影响分析

针对时间因素对钻屑瓦斯解吸指标K1测定结果的影响，采用恒温瓦斯放散试验深入分析钻屑瓦斯解吸指标K1测定理论的准确性，总结因时间因素导致K1值测定误差所带来的现场问题。研究结果表明:K1值的测定误差与时间关系密切，测定启动时间越晚，误差越大；测定启动时间由第1 min延后至第2 min，绝对误差和相对误差最大值分别增加0.081 cm3/(g·min1/2)和2.20%；高瓦斯压力条件矿井或煤层的局部高瓦斯压力区域、构造煤发育区的钻屑瓦斯解吸指标K1值测定结果偏低，测定误差偏大。研究结果可为煤与瓦斯突出预测水平的提升提供技术支撑。     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.