测定降尘中的多种重金属的方法研究

降尘采用全自动石墨消解仪消解,用电感等离子体发射光谱仪(ICP-OES)测定降尘中的Cu、Ni、Zn、Pb、Ba、As、Mn、AL、Fe、Cr、Sr、Cd、Ti等13种重金属元素含量.选择合适的波长,标准曲线的相关系数均大于0.999,各元素的分析信号值与浓度呈良好的线性关系,分析标准土壤样品都在不确定度范围内.并计算其空白加标和样品加标回收率,建立了测定降尘中重金属的最优消解方法.结果表明,空白加标和样品加标回收率均处于合理范围,分别为90.1%~104%和85.9%~96.7%.     

城市污水处理厂污水及污泥中典型药物及其代谢产物的定量检测

基于超声溶剂萃取、固相萃取和超高效液相色谱-质谱联用技术（UPLC-MS/MS）,建立了一种适用于城市污水处理厂污水和污泥中2种典型药物（磺胺甲恶唑和卡马西平）及其5种代谢产物的同步分析方法.污水样品添加硫酸酸化、Na₂EDTA络合金属离子后经固相萃取富集净化;污泥样品通过甲醇/0.2 mol·L^-1柠檬酸溶液（1：1,体积比）超声萃取后经固相萃取富集净化.采用UPLC-MS/MS电喷雾电离源在多反应监测模式下进行目标物的定量分析.结果表明,在优化条件下,7种目标物标准曲线的线性可决系数（R²）均大于0.99,方法回收率为74%~217%,日内与日间相对标准偏差稳定（RSD<20%）,污水定量限为0.17~2.42 ng·L^-1,污泥定量限为0.20~2.85 μg·kg^-1.将该方法成功应用于两家城市污水处理厂样品中,除N-AcSMX外其余6种目标物被检出,其在污水和污泥中的浓度分别为3.92（SMX-DG）~667（LCBZ）ng·L^-1和0.41（2OH-CBZ）~2.74（CBZ）μg·kg^-1.     

Evaluating the short-term effect of ambient temperature on non-fatal outdoor falls and road traffic injuries among children and adolescents in China: a time-stratified case-crossover study

● A study assessing the temperature-injury relationship was conducted among students. ● The maximum risks of injury appeared at moderate temperatures. ● The temperature effect on outdoor falls was greater in older students. Although studies have suggested that non-optimal temperatures may increase the risk of injury, epidemiological studies focusing on the association between temperature and non-fatal injury among children and adolescents are limited. Therefore, we investigated the short-term effect of ambient temperature on non-fatal falls and road traffic injuries (RTIs) among students across Jiangsu Province, China. Meteorological data and records of non-fatal outdoor injuries due to falls and RTIs among students aged 6–17 were collected during 2018–2020. We performed a time-stratified case-crossover analysis with a distributed lag nonlinear model to examine the effect of ambient temperature on the risk of injury. Individual meteorological exposure was estimated based on the address of the selected school. We also performed stratified analyses by sex, age, and area. A total of 57322 and 5455 cases of falls and RTIs were collected, respectively. We observed inverted U-shaped curves for temperature-injury associations, with maximum risk temperatures at 18 °C (48th of daily mean temperature distribution) for falls and 22 °C (67th of daily mean temperature distribution) for RTIs. The corresponding odds ratios (95% confidence intervals) were 2.193 (2.011, 2.391) and 3.038 (1.988, 4.644) for falls and RTIs, respectively. Notably, there was a significant age-dependent trend in which the temperature effect on falls was greater in older students (P-trend < 0.05). This study suggests a significant association between ambient temperature and students’ outdoor falls and RTIs. Our findings may help advance tailored strategies to reduce the incidence of outdoor falls and RTIs in children and adolescents.     

Factors affecting the distribution of microplastics in soils of China

● Microplastic (MP) abundance in soil of China was highly heterogeneous. ● MP abundance was higher near large rivers and central land affected by monsoons. ● MP abundance was correlated with longitude, mulching film, and average temperature. ● Factors suitable for predicting MP pollution using models were discussed. Microplastics (MPs) are found worldwide in high abundance, posing a potential threat to ecosystems. Despite the ubiquity of MPs in the environment, very little is known about the regional distribution of MPs and underlying factors affecting this distribution in the field, which likely include human activity, but also features of the environment itself. Here, out of a total of 1157 datapoints investigated in 53 Chinese studies, 9.68% datapoints were removed as outliers in the heterogeneity analysis. This review revealed that the abundance of MPs was highly heterogeneous. In addition, microplastic (MP) distribution maps based on China demonstrated that the highest abundance of MPs tended to occur near large rivers and central land affected by the intersection of two monsoons. The model-fitting and previous studies showed that MP abundance in China was correlated with longitude, agricultural mulching film usage per capita, temperature, and precipitation. However, due to the heterogeneity of MPs and the low matching degree between the current environmental data and the sampling points, this pattern was not as evident as reported in any single study. Factors affecting the distribution of MPs can not be captured by linear relationships alone, and systematic selection of suitable environmental factors and further model optimization are needed to explore the cause of MP pollution in soil. Overall, this review revealed an uneven distribution of MPs and serves as a reference for model prediction to assess and control plastic pollution in natural soil environments.     

Source identification and prediction of nitrogen and phosphorus pollution of Lake Taihu by an ensemble machine learning technique

● A machine learning model was used to identify lake nutrient pollution sources. ● XGBoost model showed the best performance for lake water quality prediction. ● Model feature size was reduced by screening the key features with the MIC method. ● TN and TP concentrations of Lake Taihu are mainly affected by endogenous sources. ● Next-month lake TN and TP concentrations were predicted accurately. Effective control of lake eutrophication necessitates a full understanding of the complicated nitrogen and phosphorus pollution sources, for which mathematical modeling is commonly adopted. In contrast to the conventional knowledge-based models that usually perform poorly due to insufficient knowledge of pollutant geochemical cycling, we employed an ensemble machine learning (ML) model to identify the key nitrogen and phosphorus sources of lakes. Six ML models were developed based on 13 years of historical data of Lake Taihu’s water quality, environmental input, and meteorological conditions, among which the XGBoost model stood out as the best model for total nitrogen (TN) and total phosphorus (TP) prediction. The results suggest that the lake TN is mainly affected by the endogenous load and inflow river water quality, while the lake TP is predominantly from endogenous sources. The prediction of the lake TN and TP concentration changes in response to these key feature variations suggests that endogenous source control is a highly desirable option for lake eutrophication control. Finally, one-month-ahead prediction of lake TN and TP concentrations (R² of 0.85 and 0.95, respectively) was achieved based on this model with sliding time window lengths of 9 and 6 months, respectively. Our work demonstrates the great potential of using ensemble ML models for lake pollution source tracking and prediction, which may provide valuable references for early warning and rational control of lake eutrophication.     

重金属铜和铅的生态毒性归一化及土壤环境基准研究

鉴于土壤性质对重金属生态毒性的潜在影响,开展了铜和铅的土壤生态毒性的归一化分析,一方面通过土壤性质(pH、OC(有机碳含量)、CEC(阳离子交换量)和Clay(黏土含量))和土壤生物毒性数据建立多元回归归一化模型(铜(铅)分别含10(5)种土壤生物),此外,在毒性数据和土壤性质数据不足以建立多元回归模型时,构建种间外推...     

人体动力特性振动台试验研究

随着社会发展和经济水平的提高,人们对于生产、生活的环境质量要求也不断提升,因而环境振动已越来越多的引起了社会的关注,为了研究环境振动对人体的影响,需要了解人体动力特性和在振动环境下的响应。对20名受试者以站、坐、躺姿进行了水平两向输入白噪声的振动台试验,测得人体头、肩、腹、上肢、下肢五个部位的振动响应,通过对人体各部分振动频率与身高、体重、年龄的关系分析,给出了人体频率分布规律。     

拟动力试验方法的发展与展望

结构抗震试验是模拟地震作用、分析掌握地震机制及结构抗震性能的有效方法。对拟动力试验技术的研究现状和进展进行了概括总结,分析探讨了拟动力试验特别是基于子结构技术试验的逐步积分方法、加载控制方式、误差分析、拟动力子结构试验、实时子结构试验、远程协同拟动力试验、混合子结构拟动力试验等关键技术,对比分析了拟动力试验技术与其他试验方法的差异,以及拟动力试验技术中基于子结构技术各试验方法间的区别和特点,并进一步阐述了各种拟动力试验的现存问题、应用前景,指出了需要进一步研究的方向。     

施用硼钼对花生硼钼吸收积累与分配的影响

取广东省几个花生主产区土壤作盆栽试验,探讨硼、钼施用对花生朋、钼的吸收、运转和积累分配的影响。结果表明,花生施用B、Mo后,各生育期和各部作的B、Mo含量和吸收量均极显著地增加：B、Mo配合施用抑制植株对B的吸收而促进其对Mo的吸收;在高P下配合施用B、Mo对植株B、Mo吸收均有一定的促进作用：植林吸收B、Mo后．B主要向叶转移．Mo主要积累花籽粒中。     

基于多重退化路径模型的FLNG液化系统寿命预测

为提高FLNG液化系统使用寿命的预测准确性,本文针对FLNG液化系统建立考虑多组分相关性的多重退化路径模型(MDDPM),计算出液化系统的Phase-Type寿命分布密度函数和预测寿命;以丙烷预冷混合制冷剂液化系统为例,应用MDDPM计算得到液化系统的预测寿命,并与仅考虑固有依赖条件下的液化系统预测寿命进行对比.结果表明:基于MDDPM的液化系统预测寿命比仅考虑固有依赖条件下的液化系统预测寿命短258天.系统各组分间相关性考虑不充分而导致液化系统预测寿命估计过高不容忽视,使用MDDPM进行寿命预测更准确、更安全.