高烈度地震区隧道软硬围岩交接段刚柔并济抗减震技术研究*

为提高高烈度地震区隧道抗震性能，以某铁路隧道为研究背景，分析3种抗减震措施下隧道不同监测点隧道拱顶沉降、边墙收敛、衬砌结构PGA及最小安全系数，通过对比分析得到最优抗减震措施。结果表明:相比于工况1，工况2隧道拱顶沉降减小10.54%~81.10%，边墙收敛减小13.92%~78.77%，衬砌结构PGA减小31.42%~72.02%，最小安全系数增加18.04%~66.13%；相比于工况1，工况3结构拱顶沉降减小3.04%~18.02%，边墙收敛减小4.70%~32.00%，PGA增加13.95%~27.48%，最小安全系数增加7.49%~30.99%；工况4即“减震层+SFRC衬砌”刚柔并济法，相比于工况1，隧道拱顶沉降减小18.46%~83.98%，结构边墙收敛减小17.54%~85.47%，PGA减小30.00%~69.98%，最小安全系数增加47.95%~83.56%；4种工况抗减震性能由高到低依次为:工况4＞工况2＞工况3＞工况1。研究结果可为隧道软硬围岩交接段抗震设防提供理论参考。     

梵净山不同森林植被生物量、净生产量、碳储量及空间分布特征

为做好梵净山国家级自然保护区森林植被保护,摸清自然保护区森林植被资源家底,采用2016年第四次森林资源规划设计调查数据及变更至2019年的森林资源数据,计算和分析保护区内森林植被生物量、净生产量、碳储量。梵净山8种森林类型的总生物量为443.72×10⁴t,总碳储量为219.80×10⁴t,总生长量为29.75×10⁴t·a^?1,总凋落量为18.65×10⁴t·a^?1,总净生产量为48.40×10⁴t·a^?1,总生物量、总碳储量较大的是栎林,较小的是铁杉林,桦木林、阔叶混交林、马尾松林、软阔林、杉木林和硬阔林居中;平均碳密度为48.86 t·hm^?2,依次为:桦木林>阔叶混交林>栎林>硬阔林>软阔林>马尾松林>杉木林>铁杉林;总生长量、年凋落量、净生产量较高的是栎林、硬阔林,较低的是马尾松林、阔叶混交林和铁杉林,3种森林类型合计比例不到10%;在龄组中的分配依次为:中龄林>近熟林>成熟林>幼龄林>过熟林。在不同海拔中,梵净山森林植被生物量、碳储量、生长量、凋落量和净生产量主要分布在海拔1201—1800 m,其分布比例分别为50.39%、50.38%、49.21%、50.08%和49.54%;在不同坡向中,梵净山森林植被生物量、碳储量、生长量、凋落量和净生产量主要分布在南坡和北坡,二者合计比例大于60%。     

基于地理探测器的土壤重金属影响因子分析及其污染风险评价

地理探测器能快速定量化揭示驱动重金属含量影响因素的强度,这对于重金属空间预测模型构建变量的确定和土壤污染修复措施的精准实施具有重要意义。利用地理探测器模型,对5种土壤重金属元素Cu、Zn、Pb、Cr、Ni的空间分布和11种环境因子的交互作用进行定量评估,通过单因子指数法进行重庆市土壤重金属污染风险评价。结果表明:研究区内土壤Cu、Zn、Cr和Pb的平均含量是重庆市土壤背景值的1.3—1.4倍,Ni含量低于背景值;其中Cu、Pb达到重度污染水平,其余3种重金属为中度或轻度污染水平。5种重金属元素中Cu和Pb为高度变异(变异系数为0.57、0.4),Zn、Cr和Ni为中等变异(变异系数为0.22—0.29),且各重金属元素之间呈显著正相关性,表明研究区重金属富集受人为干扰影响较大,且污染具有复合性或同源性。地理探测器的因子探测发现高程、坡度和土壤类型对5种土壤重金属含量的解释力最显著,说明地势和土壤类型是土壤重金属含量分布差异的最主要影响因素。交互作用探测发现,高程与其他因子交互作用是重金属空间分异的主导因素,气候条件和土壤类型也是重要影响因子。土壤重金属空间分布是多种因素共同作用的结果,而高程、坡度和土壤类型具有较强的解释力,这些因子可作为土壤重金属含量空间预测模型的辅助变量,也可促进重金属污染治理措施的靶向实施。     

地表水环境遥感监测关键技术与系统

介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取；提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列；发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性；构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测；在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。     

混合酸消解变化对土壤和沉积物中痕量硒分析影响

基于各3种采集环境样本、国家标准物质的土壤和沉积物,以当前环境监测行业常用的3种消解方法,探讨20种混合酸系统条件在消解条件变化中对复杂样本硒元素测定的影响。确定了最佳土壤和沉积物消解的组合为王水系统(盐酸∶硝酸∶氢氟酸∶过氧化氢∶高氯酸=3∶1∶1∶1∶1),各消解法的处理结果部分(n=5)∶水浴法消解时间仅需0.5h,总处理时间2h,准确度回收率达101%~104%,精密度RSD为1.95%~2.20%;电热板法总处理时间较长(7.5h),回收率106%,RSD偏高为8.46%,不推荐使用;微波法处理的总时间亦长达7.0h,回收率93.8%,但精密度亦偏高为8.24%,因此采用水浴法应用于环境样本的测定。该优化消解方法已直接应用于环境中农业、建筑用土和管道淤泥沉积物的3种样品类型前处理,利用同一优化条件即可快速对应土壤和沉积物性质样品,单次可批量处理72~84个样本,解决高通量样品痕量硒测定需求,提供环境污染监测和检测行业一参考依据。     

Critical review for the quantification of leachate production: Evaluation example for the “Oum Azza” public landfill in Rabat city,Morocco

The estimation of leachate quantities produced in landfills is necessary to dimension the treatment plants allowing to reduce the polluting load of these effluents and consequently avoid their negative impacts on the environment. Different leachate quantification methods were used in this study to assess the leachate volume produced at the Oum Azza landfill. The water balance method give comparable estimations of leachate production to the Ouled Berjal landfill ratio. The first method showed average values between 487 and 495 m³/day for 2015, 2018, and 2019, and at the same time, the second method gave values between 470 and 477 m³/day for the same years. In contrast, the World Bank ratio showed high values that vary between 2260 and 2295 m³/day for 2015, 2018, and 2019. The on-site data and the statistical analysis showed us that the World Bank ratio is not adapted for the estimation of the leachates produced in Oum Azza landfill, while the water balance and the ratio of Ouled Berjal landfill allowed to give comparable results to reality.     

A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.     

乙酰丙酮荧光法在线监测环境空气中的甲醛

我国现行环境空气中甲醛的标准测定方法普遍难以满足当前大气监测中对痕量浓度水平甲醛的监测需要。在乙酰丙酮分光光度法的基础上改进得到的乙酰丙酮荧光法具有更低的检出限和更高的灵敏度，适用于大气中痕量浓度水平甲醛的监测。基于乙酰丙酮荧光法设计了甲醛在线监测系统，并对其主要性能指标进行了评估测试。测试结果显示，该系统的吸收效率为98.9%~100.1%，检出限为0.045 4×10^-9，精密度为0.44%，线性误差为-0.55%，线性范围为0.0~80.0×10^-9，响应时间为282 s，单日零点漂移为-0.04×10^-9~1.33×10^-9，单日跨度漂移为-0.90×10^-9~3.45×10^-9。测试结果表明，其各项性能指标均能满足当前对大气环境中痕量浓度水平甲醛的监测需求。     

A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification

● Established a quantification method of pollutant emission standard. ● Predicted the SO₂ emission intensity of single coking enterprises in China. ● Evaluated the influence of pollutant discharge standard on prediction accuracy. ● Analyzed the SO₂ emissions of Chinese provincial and municipal coking enterprises. Industrial emissions are the main source of atmospheric pollutants in China. Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely. Based on China’s coking enterprises in 2020, we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards (QRPES) into the construction of support vector regression (SVR) and random forest regression (RFR) prediction methods for SO₂ emission of coking enterprises in China. The results show that, affected by the types of coke ovens and regions, China’s current coking enterprises have implemented a total of 21 emission standards, with marked differences. After adding QRPES, it was found that the root mean squared error (RMSE) of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a, and theR² increased from 0.890 and 0.881 to 0.926 and 0.945, respectively. This shows that the QRPES can greatly improve the prediction accuracy, and the SO₂ emissions of each enterprise are highly correlated with the strictness of standards. The predicted result shows that 45% of SO₂ emissions from Chinese coking enterprises are concentrated in Shanxi, Shaanxi and Hebei provinces in central China. The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.     

我国居住建筑室内PM_(2.5)研究现状及进展

分析了我国居住建筑室内PM_(2.5)污染水平,总结了现阶段PM_(2.5)的研究方法,主要包括理论分析法、数值模拟法和实验测试法。指出室外源是室内PM_(2.5)的主要污染来源,而室内烟草烟雾、烹饪及人员活动也会严重影响室内PM_(2.5)浓度。针对目前研究中存在的问题,提出了标定典型建筑在不同影响因素下的I/O比范围、研究家具和家电的颗粒物释放状况、加强农村室内外空气颗粒物污染调查等建议。