北京与成都大气污染特征及空气质量改善效果评估

近年来我国空气质量持续改善,大气颗粒物浓度明显降低.为探究气象条件和减排措施对细颗粒物（PM_2.5）浓度的相对贡献,选取两个典型代表城市——北京和成都,对比分析两城市所处的地理环境条件、污染排放以及气象扩散条件.结果表明,北京与成都2013~2018年重污染天数及污染过程显著减少,SO₂和PM_2.5浓度降幅明显,与2013年相比,两城市2018年SO₂浓度的降幅分别为77.8%和70.9%,PM_2.5浓度分别降低了42.7%和48.5%.冬季PM_2.5浓度下降速率最大,每年分别以13.5μg·m^-3和14.1μg·m^-3的速率降低.2013~2018年成都较北京风速偏小,温度偏高约3℃,静小风日数偏多,冬季静小风频率高,混合层高度、大气容量指数以及通风系数明显偏小,大气扩散条件较差.综合静稳天气指数（SWI）和环境气象指数（EMI）结果表明北京大气扩散条件优于成都,但近几年的变化程度有所不同.2014~2018年两城市的EMI呈减小趋势,2018年成都地区EMI降幅最显著,气象条件明显好转.与2014年相比,2018年北京与成都全年大气污染减排对PM_2.5浓度的贡献分别为33.5%和24.0%,气象条件的贡献分别为7.2%和11.1%;冬季减排贡献分别为31.7%和32.5%,气象条件的贡献比全年的大.     

基于RF-ELM模型的边坡稳定性预测研究

为实现对边坡稳定性的有效预测,将极限学习机算法与旋转森林算法相结合,并依据影响边坡稳定性的六项重要因素,建立了边坡稳定性预测的RF-ELM预测模型。该模型是以极限学习机算法为基分类器,以旋转森林算法为框架的集成学习模型,利用UCI数据库中三组数据集验证了该集成模型确实提高了ELM的预测性能。将RF-ELM模型应用于边坡稳定性的预测问题中,结合39组工程实例数据进行预测实验,结果表明该模型具有较高的预测精度,可有效的对边坡稳定性进行预测。     

Ranked set sample design for environmental investigations

Ranked set sampling can provide an efficient basis for estimating parameters of environmental variables, particularly when sampling costs are intrinsically high. Various ranked set estimators are considered for the population mean and contrasted in terms of their efficiencies and useful- ness, with special concern for sample design considerations. Specifically, we consider the effects of the form of the underlying random variable, optimisation of efficiency and how to allocate sampling effort for best effect (e.g. one large sample or several smaller ones of the same total size). The various prospects are explored for two important positively skew random variables (lognormal and extreme value) and explicit results are given for these cases. Whilst it turns out that the best approach is to use the largest possible single sample and the optimal ranked set best linear estimator (ranked set BLUE), we find some interesting qualitatively different conclusions for the two skew distributions     

CHEMICAL CONSTITUENTS IN STORM FLOW VS. DRY WEATHER DISCHARGES IN CALIFORNIA STORM WATER CONVEYANCES1

ABSTRACT: This research evaluated concentration data for selected water quality parameters in selected California urban separate storm sewer systems during storm event discharges and during dry weather conditions. We used existing monitoring data from multiple regulatory agencies and municipalities originally collected for compliance or local characterization, which allowed systematic assessment of seasonal patterns over a wide region. Long term mean concentration for most parameters in most streams was higher during storm discharges than during dry weather flows to at least 95 percent confidence in 20 of 45 comparative evaluations, and lower statistical confidence in 22 other comparisons. Some regional differences emerged: in four evaluated streams in the San Francisco Bay Area, total concentration of lead, copper and zinc were lower during dry weather than during storm flows to at least 99.9 percent confidence, with only one exception; while the other four evaluated California streams showed the same tendency, but to much lower statistical confidence.     

中国部分地区2021年几次典型沙尘天气遥感监测分析

2021年,中国北方地区经历了多轮大范围沙尘天气,波及西北、华北、东北甚至黄淮、长三角等地区。其中,3月份出现自2010年以来最强沙尘天气过程。该研究基于Himawari-8静止卫星数据和地面同步空气站点监测数据,分析了2021年3月14—17、27—30日和4月14—15日3次典型沙尘天气过程。分析结果显示：2021年3月14—17日沙尘天气影响范围最广,沙尘分别在不同时间段起源于蒙古国西北部、中国甘肃和青海交界处、新疆和甘肃交界处,大范围沙尘天气是多处尘源综合作用的结果。3月27—30日和4月14—15日沙尘主要起源于蒙古国,沙尘源较单一,影响范围相对集中,但某些时段受影响区域的沙尘强度很高。地面同步空气站点PM₁₀监测数据与卫星数据有很好的一致性。     

污染天气条件下人工降雨对成渝西南区域环境空气质量的影响评估

基于成渝地区大气污染防控形势的严峻性,选取该区域西南部的乐山市作为研究对象,对2016—2020年人工降雨对该城市环境空气质量的影响进行研究。评估发现:冬季改善效果最好,平均每毫米降雨量可降低环境空气质量指数(AQI)约10,对应的SO₂、NO₂、CO、O₃、PM₁₀、PM_2.5浓度分别降低1.8 μg/m³、3.8 μg/m³、0.1 mg/m³、8.1 μg/m³、6.9 μg/m³、8.9 μg/m³;其次是春季,每毫米降雨量可降低AQI约8,对应的6项污染物浓度分别降低1.0 μg/m³、3.3 μg/m³、0.1 mg/m³、8.1 μg/m³、6.1 μg/m³、8.4 μg/m³;再次是夏季,每毫米降雨量可降低AQI约3,对应的6项污染物浓度分别降低0.6 μg/m³、1.6 μg/m³、0.03 mg/m³、6.9 μg/m³、1.2 μg/m³、2.0 μg/m³;秋季每毫米降雨量可降低AQI约1,对应的6项污染物浓度分别降低0.4 μg/m³、0.6 μg/m³、0.01 mg/m³、3.5 μg/m³、0.1 μg/m³、0.1 μg/m³。计算不同季节降雨总量与污染物削减量之间的Pearson相关系数,结果表明,春季人工降雨总量与O₃浓度削减总量呈显著正相关,夏、秋两季人工降雨总量与PM_2.5浓度削减总量呈显著正相关。     

2019年秋季三亚市一次典型臭氧污染个例气象成因解析

三亚市位于海南岛最南端,旅游资源丰富,生态环境良好,是海南建设国际旅游岛和国家生态文明试验区的重要城市之一。2019年秋季三亚市出现的一次臭氧(Ozone,O₃)污染过程,为科学认识三亚市此次O₃污染特征及气象学成因,也为进一步开展O₃污染预警预报和科学治理提供技术支撑,利用2019年11月1—6日三亚市生态环境局对外发布的大气污染物数据,以及地面常规观测数据,结合ECMWF发布的第5代资料(the fifth generation ECMWF reanalysis data,ERA5),采用相关分析和后向轨迹模型对其进行分析。结果表明,11月4日和5日O₃-8 h(臭氧最大8 h滑动平均)分别为162μg·m^-3和180μg·m^-3,超标百分比为101.25%和112.50%。5日O₃-1 h(臭氧最大1 h平均)达到了203μg·m^-3,超标百分比为101.50%。14:00—19:00是O₃     

SVD在串联故障电弧检测及选相中的应用*

煤矿井下发生串联故障电弧易引发火灾等安全事故,为了预防电气火灾、指导线路维修,利用三相电动机及变频器负载开展不同线路、不同电流条件下的串联故障电弧实验,研究三相串联故障电弧的检测及选相方法。首先,对单相电流进行一阶差分处理后,建立改进的吸引子轨迹矩阵作为故障特征矩阵;其次,对故障特征矩阵进行奇异值分解,采用特征矩阵的奇异值构建串联故障电弧检测及选相的特征向量;最后,利用极限学习机建立故障电弧检测及选相模型,并测试检测及选相准确率。研究结果表明:提出的SVD方法可以利用单相电流实现三相电动机及变频器负载回路中的串联故障电弧检测及选相。     

Trends in Raindrop Kinetic Energy with Modeled Climate Warming in the Lake Tahoe Basin

Two means by which climate change may increase surface soil erosion in mountainous terrain are: (1) increasing the frequency of extreme rainfall events and (2) decreasing the duration of snow cover on bare soil. We used output from four general circulation models (GCMs) and two greenhouse gas trajectories to produce a suite of hydrologic variables at a daily time‐step for historic and projected 21st Century conditions. We statistically disaggregated the daily rainfall to hourly, using hourly rainfall from a network of nine weather stations in the Tahoe Basin, and filtered out rain falling on a snowpack. We applied published equations to convert hourly intensity to raindrop kinetic energy (KE) for each day and grid cell in the Basin, averaged across grid cells, and created time series of total annual and maximum annual hourly kinetic energy (TKE and MKE) on snow‐free ground. Using the Generalized Extreme Value distribution, we calculated the significance of long‐term trends in KE on snow‐free ground, and estimated energy levels for return periods of 2, 20, and 100 years. We then detrended the snowpack data and compared the resulting trends in KE with the trends resulting from changes in both rainfall energy and snowpack under two GCMs. Principal findings include (1) upward trends in MKE, (2) stronger upward trends in TKE; and (3) an effect of increasing rainfall intensities on KE in some cases, and a strong effect of reduced snowpack in all cases examined.     

The effect of summer drought on the predictability of local extinctions in a butterfly metapopulation

The ecological impacts of extreme climatic events on population dynamics and community composition are profound and predominantly negative. Using extensive data of an ecological model system, we tested whether predictions from ecological models remain robust when environmental conditions are outside the bounds of observation. We observed a 10-fold demographic decline of the Glanville fritillary butterfly (Melitaea cinxia) metapopulation on the Åland islands, Finland in the summer of 2018 and used climatic and satellite data to demonstrate that this year was an anomaly with low climatic water balance values and low vegetation productivity indices across Åland. Population growth rates were strongly associated with spatiotemporal variation in climatic water balance. Covariates shown previously to affect the extinction probability of local populations in this metapopulation were less informative when populations were exposed to severe drought during the summer months. Our results highlight the unpredictable responses of natural populations to extreme climatic events.