北京秋冬季一次重污染过程PM2.5来源数值模拟研究

利用WRF模式(The Weather Research and Forecasting Model)和嵌套网格空气质量模式(NAQPMS)对2016年11月发生在京津冀地区一次PM_(2.5)污染事件进行模拟研究并分析污染过程中的天气形势变化.结果表明,均压场、低空逆温层和偏南暖湿气流输送的存在为北京地区PM_(2.5)形成提供了有利条件,NAQPMS模式能够合理的再现北京大气污染物时空变化,细颗粒物PM_(2.5)和可吸入颗粒物PM_(10)模拟与观测数据相关系数达0.71,模拟数据在观测数据两倍范围内占比(FAC2)达65%.源解析结果表明,在不考虑临时实施减控措施下,11月18日区域外输送对北京PM_(2.5)浓度贡献为55.25%,区域内输送贡献为44.75%,北京东北区域PM_(2.5)外地源主要为河北中部、河北南部、天津和山东,所占贡献为9.67%、9.01%、7.90%和7.99%.污染物主要来源为生活源、交通源和工业源,分别占比39.6%、34.6%和20.0%.而实际上北京在唐山、保定采取一系列控制措施后仍在研究时段内出现高PM_(2.5)浓度,意味着在同样天气形势下需要对河北中部、河北南部、天津和山东等浓度贡献占比大的城市加强减排管控才能有效减缓高PM_(2.5)浓度的出现.     

2017年兰州市大气污染物输送来源及传输特征模拟分析

利用HYSPLIT后向轨迹模式,结合兰州市AQI（空气质量指数）及常规大气污染物质量浓度数据,模拟研究了2017年1月1日-12月31日以兰州市为受点的大气污染物输送特征.通过聚类分析确定了抵达兰州市气团的主要输送途径和每类路径所对应的污染物质量浓度特征,并利用受体模型PSCF（潜在源贡献因子分析法）和CWT（权重浓度轨迹分析法）,分析了大气污染区域传输对兰州市空气质量的影响,探讨了影响兰州市空气质量的污染物输送来源和可能的潜在源区.结果表明,在影响兰州市的气流轨迹中,污染轨迹多来自兰州市以西和以北方向,污染轨迹约占总轨迹的39.52%,说明外部污染物的输入对兰州市空气质量具有重要影响.其中,第3类轨迹（对应来向为西）的气团对兰州市的空气质量有较大的影响,该类轨迹虽仅占总轨迹的15.21%,但其中污染轨迹数占56.76%,是影响兰州市空气质量的主要传输路径;第4类轨迹（对应来向为东南）的气团最为清洁.研究显示,对兰州市空气质量影响最大的强潜在源区主要分布在青海共和盆地、兰州市本地及周边区域,中等强度潜在源区为内蒙古自治区南部、宁夏回族自治区及甘肃省河西走廊等地区.      

基于可解释性机器学习的城市O3驱动因素挖掘

受前体物排放和气象条件等因素共同驱动,大气臭氧(O₃)已成为影响城市夏季环境空气质量的主要污染物.目前物理化学机制驱动的演绎模型在进行O₃污染解析时需要的模型参数众多,运算时效性较差;数据驱动的归纳模型运算效率高,但存在可解释性差等问题.通过建立可解释性数据驱动的Correlation-ML-SHAP模型,Correlation模块挖掘O₃浓度关联影响因素,机器学习ML模块耦合可解释性SHAP模块计算各驱动因素对O₃浓度的影响贡献,实现对驱动因素的定量解析,并以晋城市2021年夏季O₃污染过程为例开展应用研究.结果表明,Correlation-ML-SHAP模型能够挖掘并利用强驱动因素模拟O₃浓度和量化影响贡献,其中ML模块采用XGBoost模型模拟准确度最佳. 2021年夏季晋城市O₃污染强驱动因素为：气温、日照强度、湿度和前体物排放水平,贡献权重为：32.1%、 21.3%、 16.5%和15.6%,其中气温、日照强度和前体物排放...     

Effect on fatality risk of changing from secondary to primary seat belt enforcement

BACKGROUND: Most seat belt use laws originally passed in the United States contained language restricting enforcement to drivers already stopped for some other reason. States that have since removed this secondary enforcement restriction have reported increased seat belt use. The purpose of the present study was to estimate the effect of these law changes on driver fatality rates. METHOD: Trends in passenger vehicle driver death rates per billion miles traveled were compared for 10 states that changed from secondary to primary seat belt enforcement and 14 states that remained with secondary enforcement. RESULTS: After accounting for possible economic effects and other general time trends, the change from secondary to primary enforcement was found to reduce annual passenger vehicle driver death rates by an estimated 7% (95% confidence limits 3.0-10.9). CONCLUSION: The majority of U.S. states still have secondary enforcement laws. If these remaining secondary laws were amended, an estimated 696 deaths per year could be prevented.     

木材在不同放置角度下火蔓延特性的实验研究

选用厚度为2 mm与3 mm的木材,研究了可碳化固体可燃物在静止氛围中不同角度下的火蔓延特性.研究表明,在不同角度范围内火蔓延经历着熄灭、稳定燃烧、加速燃烧以及快速燃烧等变化过程.对两种厚度的木材火蔓延行为对比分析发现,在自然对流条件下,两种厚度木材的火蔓延极限角度分别为-5°,5°.另外,研究了试样上下表面火焰参数与火蔓延速度之间的关系.在10°＜α＜60°范围内,火蔓延速度计算值与实验值能较好拟合.     

Modelling outflow from a ruptured pipeline transporting compressed volatile liquids

The paper presents a mathematical model for predicting outflow rates from a ruptured pipeline transporting compressed volatile liquids. The main focus of the paper is the methodology used to predict thermodynamic properties of interest. The model is validated using experimental data in the open literature. As the field scale outflow data does not include typical operating conditions the model is further validated at higher pressures and longer pipelines by comparing outflow rates calculated using a commercial pipeline simulation package, PROFES. The mathematical model predictions of mass flow rate and pipeline inventory agree well with the measured data and the more sophisticated pipeline model.

The simple pipeline rupture model is a useful tool for consequence analysis as it has a fast runtime on a standard PC. A further advantage is it is more easily, without having to address all of the numerical issues that arise when using a more sophisticated pipeline model. This allows a safety engineer to focus on the potential hazard rather than driving the model.     

From conference abstract to publication in the conservation science literature

Every 2 years, the conservation community comes together at The Society for Conservation Biology's International Congress for Conservation Biology (ICCB) to share new developments in conservation science and practice. Publication of findings presented at conferences in scientific journals adds to the permanent record and helps increase the potential impact of the work presented. However, quantitative research on publication rates for meetings relevant to conservation is lacking. For the 25th ICCB, (Auckland, New Zealand in 2011), we examined study publication rates and presenter demographics, recorded titles, number of authors, presenter affiliations, gender, country of the study region, publication status, and elapsed time between presentation and publication. Of the 980 contributions (782 talks and 198 posters), 587 (60%) were published as peer-reviewed journal articles or book chapters. Mean time to publication was 13.7 months for all presentation abstracts and 21.3 months excluding abstracts with corresponding articles that were published before the meeting. The gender breakdown of presenters was almost even (53% male, 47% female), but representation of the countries where the presenting authors were based was skewed. The political units with the most contributions were by far the United States, Australia, New Zealand, and the United Kingdom. Presenters based in 16 different English-speaking countries made up 74% of the total sample, but this did not influence the likelihood of their abstract leading to a publication. Examination of conference presenters and publication of their presentations is useful to identify biases and potential challenges that need to be addressed to make conference communications permanent and increase their reach beyond conference attendees.     

A Bayesian hierarchical approach to quantifying stakeholder attitudes toward conservation in the presence of reporting error

Stakeholder support is vital for achieving conservation success, yet there are few reliable mechanisms to monitor stakeholder attitudes toward conservation. Approaches used to assess attitudes rarely account for bias arising from reporting error, which can lead to falsely reporting a positive attitude toward conservation (false-positive error) or not reporting a positive attitude when the respondent has a positive attitude toward conservation (false-negative error). Borrowing from developments in applied conservation science, we used a Bayesian hierarchical model to quantify stakeholder attitudes as the probability of having a positive attitude toward wildlife notionally (or in abstract terms) and at localized scales while accounting for reporting error. We compared estimates from our model, Likert scores, and naïve estimates (i.e., proportion of respondents reporting a positive attitude in at least 1 question that was only susceptible to false-negative error) with true stakeholder attitudes through simulations. We then applied the model in a survey of tea estate staff on their attitudes toward Asian elephants (Elephas maximus) in the Kaziranga–Karbi Anglong landscape of northeast India. In simulations, Bayesian model estimates of stakeholder attitudes toward wildlife were less biased than naïve estimates or Likert scores. After accounting for reporting errors, we estimated the probability of having a positive attitude toward elephants notionally as 0.85 in the Kaziranga landscape, whereas the proportion of respondents who had positive attitudes toward elephants at a localized scale was 0.50. In comparison, without accounting for reporting errors, naïve estimates of proportions of respondents with positive attitudes toward elephants were 0.69 and 0.23 notionally and at local scales, respectively. False (positive and negative) reporting probabilities were consistently not 0 (0.22–0.68). Regular and reliable assessment of stakeholder attitudes–combined with inference on drivers of positive attitudes–can help assess the success of initiatives aimed at facilitating human behavioral change and inform conservation decision making.     

Estimating the normal background rate of species extinction

A key measure of humanity's global impact is by how much it has increased species extinction rates. Familiar statements are that these are 100–1000 times pre‐human or background extinction levels. Estimating recent rates is straightforward, but establishing a background rate for comparison is not. Previous researchers chose an approximate benchmark of 1 extinction per million species per year (E/MSY). We explored disparate lines of evidence that suggest a substantially lower estimate. Fossil data yield direct estimates of extinction rates, but they are temporally coarse, mostly limited to marine hard‐bodied taxa, and generally involve genera not species. Based on these data, typical background loss is 0.01 genera per million genera per year. Molecular phylogenies are available for more taxa and ecosystems, but it is debated whether they can be used to estimate separately speciation and extinction rates. We selected data to address known concerns and used them to determine median extinction estimates from statistical distributions of probable values for terrestrial plants and animals. We then created simulations to explore effects of violating model assumptions. Finally, we compiled estimates of diversification—the difference between speciation and extinction rates for different taxa. Median estimates of extinction rates ranged from 0.023 to 0.135 E/MSY. Simulation results suggested over‐ and under‐estimation of extinction from individual phylogenies partially canceled each other out when large sets of phylogenies were analyzed. There was no evidence for recent and widespread pre‐human overall declines in diversity. This implies that average extinction rates are less than average diversification rates. Median diversification rates were 0.05–0.2 new species per million species per year. On the basis of these results, we concluded that typical rates of background extinction may be closer to 0.1 E/MSY. Thus, current extinction rates are 1,000 times higher than natural background rates of extinction and future rates are likely to be 10,000 times higher. Estimación de la Tasa Normal de Extinción de Especies     

Impact of human development on safety consciousness in construction

The International Labour Organization (ILO) reports that the risk of fatal occupational injuries in developing countries is almost twice as high as in developed countries, indicating a potential relationship between the fatality rates and the development level. The human development index (HDI), based on life expectancy, knowledge level and purchasing power parity, endorsed by the United Nations Development Programme, is a widely accepted measure of the development level. This study investigates the relationship between the HDI and the fatality rates reported by the ILO. A 23-country data set is used to demonstrate the general trend of the relationship followed by country-specific analyses for Australia, Spain, Hungary and Turkey. The study conducted is limited to fatal occupational injuries in construction, where the accidents are notoriously high. The results demonstrate a statistically significant inverse relationship between the fatality rates and the HDI.