Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.     

A multidecadal oscillation in precipitation and temperature series is pronounced in low flow series from Puget Sound streams

In Pacific Northwest streams, summer low flows limit water available to competing instream (salmon) and out-of-stream (human) uses, creating broad interest in how and why low flows are trending. Analyses that assumed linear (monotonic) change over the last ~60 years revealed declining low flow trends in minimally disturbed streams. Here, polynomials were used to model flow trends between 1929 and 2015. A multidecadal oscillation was observed in flows, which increased initially from the 1930s until the 1950s, declined until the 1990s, and then increased again. A similar oscillation was detected in precipitation series, and opposing oscillations in surface temperature, Pacific Decadal Oscillation, and Interdecadal Pacific Oscillation series. Multidecadal oscillations with similar periods to those described here are well known in climate indices. Fitted model terms were consistent with flow trends being influenced by at least two drivers, one oscillating and the other monotonic. Anthropogenic warming is a candidate driver for the monotonic decline, and variation in (internal) climatic circulation for the oscillating trend, but others were not ruled out. The recent upturn in streamflows suggests that anthropogenic warming has not been the dominant factor driving streamflow trends, at least until 2015. Climate projections based on simulations that omit drivers of multidecadal variation are likely to underestimate the range, and rate of change, of future climatic variation.     

财政分权对环境污染的空间效应

利用2006—2017年我国30个省级行政单位的面板数据,采用空间计量模型对财政分权与环境污染之间的关系进行实证分析,并通过效应分解分别计算出财政收入分权和财政支出分权对环境污染的直接效应、空间溢出效应和总效应。模型估计的结果表明:①财政收入分权与财政支出分权通过直接效应和空间溢出效应两种途径对环境污染产生显著影响,但收入分权与支出分权对环境污染的空间效应具有异质性。②财政收入分权对环境污染具有显著的负向直接效应和负向空间溢出效应,影响系数分别为-5.429和-17.572。提高财政收入分权度不仅有利于减轻本省份环境污染,也对邻近省份的环境污染起到抑制作用。而财政支出分权对环境污染具有显著的负向直接效应和正向的空间溢出效应,影响程度分别为-3.345和1.173。提高财政支出分权虽然有利于减少本省份污染的排放,但在一定程度上引起省际的污染外溢效应,提高邻近省份的污染程度。③从总效应来看,财政收入分权和财政支出分权对环境污染均呈现出显著的负向相关性,影响程度分别为-23.001和-2.172。提高财政分权可降低环境污染水平,有利于环境质量提升。④通过构建不同空间权重矩阵,检验模型的稳健性,结果表明模型估计是稳健可靠的。根据分析结论,可能的启示与建议有:①合理划分中央政府和地方政府之间的财政事权和支出责任,在提高财政支出分权度的同时提高地方政府财政收入分权度,充分发挥地方政府环境治理的积极性和主动性。②继续加大生态环境保护力度,完善绿色经济考核机制,引导地方政府加大对污染治理和环境改善的支出水平及效率。     

Understanding and addressing the environmental risk of microplastics

Over the past decades, the plastic production has been dramatically increased. Indeed, a category of small plastic particles mainly with the shapes of fragments, fibers, or spheres, called microplastics (particles smaller than 5 mm) and nanoplastics (particles smaller than 1 μm) have attracted particular attention. Because of its wide distribution in the environment and potential adverse effects to animal and human, microplastic pollution has been reported as a serious environment problem receiving increased attention in recent years. As one of the commonly detected emerging contaminants in the environment, recent evidence indicates that the concentration of microplastics show an increasing trend, for the reason that up to 12.7 million metric tons of plastic litter is released into aquatic environment from land-based sources each year. Furthermore, microplastic exposure levels of model organisms in laboratory studies are usually several orders of magnitude higher than those found in environment, and the microplastics exposure conditions are also different with those observed in the environment. Additionally, the detection of microplastics in feces indicates that they can be excreted out of the bodies of animal and human. Hence, great uncertainties might exist in microplastics exposure and health risk assessment based on current studies, which might be exaggerated. Policies reduce microplastic emission sources and hence minimize their environmental risks are determined. To promote the above policies, we must first overcome the technical obstacles of detecting microplastics in various samples.     

呼吸效应对矿井封闭火区氧浓度的影响分析

为避免因火区封闭导致重大安全事故发生，通过采集某矿井1 d内3个不同监测点的大气压力变化情况，建立大气压力波动模型并分析计算，同时建立火区内外压差100，750 Pa情形下的氧浓度模型进而获得火区内侧氧气浓度因呼吸效应，在不同压差、体积大小火区、风阻、瓦斯涌出量、封闭时刻等多因素耦合影响下随时间的变化规律，以评估火区危险性。研究结果表明:井下大气随地面大气周期波动，封闭火区内、外侧之间的气压差因外界大气波动呈现16 h的余弦波动和8 h的线性波动周期变化；密闭质量好的火区具有更好地抗干扰性，内侧氧浓度的降低主要依靠瓦斯稀释；密闭质量差的火区，内侧氧浓度易受到火区涌出瓦斯、外界涌入大气双重影响；火区氧浓度在2%~12%之间波动，以至火区存在发生瓦斯爆炸的可能性；火区内外压差较大时，氧浓度波动变化幅度更大，危险作用持续时间更长。结合火区氧浓度波动模型，可有效地对矿井火区采取安全的防范措施，避免瓦斯爆炸事故发生。     

屏蔽服冷却系统对人体表面温度影响的研究*

为科学有效地论证多种方式组合的冷却屏蔽服在不同环境条件下对人体表面温度控制的效果，需要对冷却系统及人体敏感部位发热量进行客观评估。通过对5名健康男性的高温测试，探究人体在不同环境温度下体表温度的变化，得出胸部、背部及额头为热量最高部位，并构建以“人体-降温屏蔽服-外界环境”为主体的冷却系统数值模型，对不同环境中的屏蔽服冷却效果展开研究，分析穿戴冷却屏蔽服时人体躯干部分的温度分布及影响。结果表明:在屏蔽服中靠近胸部、背部部位引入相变材料和风扇，均可帮助人体降低体温，提高舒适度。     

Development of machine learning based prediction models for hazardous properties of chemical mixtures

Lower flammability limit (LFL), upper flammability limit (UFL), auto-ignition temperature (AIT) and flash point (FP) are crucial hazardous properties for fire and explosion hazards assessment and consequence analysis. In this study, a comprehensive prediction model set was constructed by using expanded chemical mixture databases of chemical mixture hazardous properties. Machine learning based gradient boosting quantitative structure-property relationship (GB-QSPR) method is implemented for the first time to improve the model performance and prediction accuracy. The result shows that all developed models have significantly higher accuracy than other regular QSPR models, with the 5-fold cross-validation RMSE of LFL, UFL, AIT, and FP models being 1.06, 1.14, 1.08, and 1.17, respectively. All developed QSPR models can be used to estimate reliable chemical mixture hazardous properties and provide useful guidance in chemical mixture hazard assessment and consequence analysis.     

肥煤自燃全过程热动力学特征参数研究

实验测定了林西矿肥煤样品30~900℃煤自燃全过程热动力学特征参数,得出:TG/DTG曲线显示煤样DTG初始临界温度45℃,干裂温度122℃,活性温度195℃,增速温度265℃,质量极大值温度342℃,着火温度465℃,最大热失重速率温度515℃和燃尽温度690℃;DSC曲线显示,煤样初始放热温度60℃、最大热释放速率温度511℃。结合TG-DTG-DSC曲线综合分析可知,煤温达到510℃左右时煤样反应最剧烈。由煤自燃标志气体测定实验系统得出:煤温130℃后CO,CO 2释放量迅速增加,210℃增加速度下降;CH 4,C 2 H 6含量变化具有规律性且两者变化相近;C 2 H 4出现温度为130℃;C 2 H 4/C 2 H 6比值在190~350℃有较强的规律性,呈上升趋势且上升速度较快;350℃之后,CH 4,C 2 H 6,C 2 H 4体积分数均开始急剧增大;C 2 H 4/CO与C 2 H 4/CO 2变化趋势大致相同,在130~350℃时缓慢增长,达到350℃后比值呈指数形式上升。经拟合曲线,得到活化能的3个突变点温度:70,180,220℃,其中180℃与交叉点温度相吻合。通过以上研究,得到了肥煤自燃全过程的热力学特征参数,为实际生产中防治煤自燃提供了理论依据。     

基于Landsat 8遥感数据的天津市地表温度反演

以Landsat 8遥感数据为数据源,进行天津市地表温度反演研究。首先采用单通道算法反演地表温度,并利用均值标准差法进行温度分级。然后建立不同温度等级面积比例的估算模型。再通过随机样点,从不同温度等级和土地覆盖类型2个角度,分别建立并比较不同类样点的地表温度与各指数的拟合模型。结果表明:次高温区域面积比例与人口密度、人均GDP都具有较高的决定系数;地表温度与NDVI、BAEM的二元线性回归决定系数高于地表温度与单一指数的决定系数;将样点分类后,低温点与MNDBI的决定系数高于其他温度等级样点,水域和植被样点与各种指数的决定系数高于其他地物类型样点。     

初始温度和压力对排污空间甲烷-空气混合物爆燃特性影响的模拟研究

市政排污空间作为城市公共基础设施的重要组成部分，易积聚可燃气体形成爆炸性环境。结合排污空间的特殊环境条件，采用Fluidyn-MP多物理场数值模拟软件，建立了20 L球形爆炸罐分析模型，通过改变初始温度和初始压力，对排污空间甲烷-空气混合物爆燃特性及其变化规律进行模拟研究。结果表明:初始温度升高导致甲烷-空气混合物最大爆炸压力降低，缩短了到达最大爆炸压力的时间；初始压力增加导致最大爆炸压力急剧升高，并延长了到达最大爆炸压力的时间；最大爆炸压力对初始压力的敏感程度远大于初始温度的影响。此外，随着初始温度和初始压力的升高，爆炸火焰平均传播速度增加，而火焰传播速度对初始温度较敏感。