我国高速公路周边土壤重金属污染现状及研究进展

以我国高速公路周边土壤重金属为研究对象，综述了我国高速公路周边土壤重金属污染特征、影响因素、来源、环境风险及其研究进展。高速公路周边土壤主要受Pb、Cd、Cr、Cu、Zn等重金属污染，主要呈现指数分布、偏态分布和两者混合分布等特点，并且受到土地利用、风向、地形、车流量等多种因素的综合影响。土壤重金属的来源除了受成土母质等自然因素影响以外，公路交通和周边工农业活动也会对其来源产生较大影响。传统的土壤重金属评价方法主要采用单因子指数法、地累积指数法、生态风险评价法等对重金属的污染等级和环境风险进行评价。未来的研究应将重金属形态分析、空间和地统计分析、重金属稳定同位素示踪和源解析模型以及预测模型等多种手段相结合，开展高速公路周边土壤重金属的污染特征、时空分布、来源及预测预警研究等，为我国高速公路沿线工农业生产布局及其土壤重金属污染防控提供科学依据和决策支撑。     

大型碳化硅生产园区面源源强及减排指标核算

以某年产25万吨大型碳化硅园区无组织排放面源为例,提出基于多个地面站气象数据的CALPUFF模型地面浓度反推方法,优化流场模拟,使得无组织面源源强核算结果更加准确,并以环境保护目标空气质量达标为原则,核算其大气污染物减排指标,得出具体结论:园区大气污染物SO2、NOX、CO、PM10年排放量分别为449.06t、86.98t、5158.58t、115.06t;无组织排放SO2、CO及PM10的减排比例分别为63.5%、19.2%、42.44%,对应减排量分别为285.16 t/a、990.45 t/a、48.83 t/a。     

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。     

基于加速度限控制策略的振动试验过载停机实验研究

西门子Simcenter Testlab振动控制采集分析系统在航天振动试验领域应用十分广泛,但是在实际工程应用中常常由于对软件工作机制理解不到位,参数设置不合理造成试验异常中断,这不仅给产品带来了巨大的安全隐患,而且也增加了试验时间和成本,严重影响研制进度。因此,本文针对某航天产品正弦振动试验的过载停机故障,从软件加速度限控制功能的角度分析了潜在原因,并且开展了实验验证。首先描述了振动试验过程和过载停机现象,排除了硬件原因,然后对可能的加速度限控制功能设置和通道量程过小等原因设计了三组实验进行分析验证,得出了此次试验过载停机①与加速度限控制(频域)设置无关,②而与通道量程(时域)设置有关,③通过忽略限幅通道过载设置可使试验正常进行的分析结论,最后针对Simcenter Testlab加速度限控制功能和通道量程设置提出了使用建议,为后续航天产品振动试验提供参考。     

3种喹诺酮类抗生素在骆马湖饮用水源地沉积物上的吸附特征

为探究喹诺酮类抗生素(QNs)在饮用水源地的吸附特征,2019年6月于江苏骆马湖饮用水源地采集沉积物样品,用5种动力学方程拟合沉积物对诺氟沙星(NOR)、环丙沙星(CIP)和氧氟沙星(OFL)的吸附动力学过程,并用Langmuir和Freundlich模型拟合以上3种QNs的吸附热力学过程,分析了pH、水土比和不同Na~+、Ca~(2+)、Mg~(2+)、Al~(3+)浓度对吸附过程的影响。结果表明:骆马湖沉积物对3种QNs的吸附在8h达到平衡,准二级动力学方程和Langmuir模型能更好地描述3种QNs的吸附动力学和热力学过程。酸性条件下,3种QNs的吸附效果更好,且在pH=5时平衡吸附量最大。平衡吸附量随着水土比的上升而下降。Na~+对吸附的抑制作用不明显,Ca~(2+)和Mg~(2+)的抑制作用较强,而Al~(3+)对吸附表现为促进作用。应在枯水期和南水北调时期加强对骆马湖饮用水源地(尤其是东北部)QNs污染的关注。     

Effects of rainfall on surface environment and morphological characteristics in the Loess Plateau

Environmental Science and Pollution Research - Slope failure is a one of major process that causes severe landform variation and environment variation, and slope failure has become a major hidden...     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Atmospheric depositional fluxes and sources apportionment of organochlorine pesticides in the Pearl River Delta region, South China

Organochlorine pesticides (OCPs) have variously been phased out in agricultural activities, but they are still widely detected in air, water, and soil systems due to their recalcitrant nature in the environment. The purposes of this study were to assess potential OCP pollution via dry and wet deposition over the fast developing Pearl River Delta area with 41,700 km², where the main effort has been focused on emerging pollutants such as petroleum hydrocarbons and PM2.5. We quantified both the dry and wet deposition fluxes of 19 OCPs including dichlorodiphenyltrichloroethanes (DDTs), endosulfans (Endos), and hexachlorocyclohexanes (HCHs). The results showed that each year about 67.4, 42.0, 15.0, and 8.07 kg of total OCPs, DDTs, Endos, and HCHs were returned to the ground, among which 11.7, 10.4, 0.84, and 0.16 kg were in the dry deposition forms. The large spatial variations in OCP deposition fluxes indicated that OCP pollution in the air is mainly influenced on local scales because evaporation from local soil is likely the major source of the phased out OCPs. Source analysis indicated that DDTs may be still in use as antifouling agent and/or dicofol, but Endos and HCHs were mainly derived from the residual of historical usage. The study suggests that the historical OCP pollutants are persistent at high levels in this area and should not be overlooked, while we tackle emerging pollutants.     

Improving artificial forest biomass estimates using afforestation age information from time series Landsat stacks

China maintains the largest artificial forest area in the world. Studying the dynamic variation of forest biomass and carbon stock is important to the sustainable use of forest resources and understanding of the artificial forest carbon budget in China. In this study, we investigated the potential of Landsat time series stacks for aboveground biomass (AGB) estimation in Yulin District, a key region of the Three-North Shelter region of China. Firstly, the afforestation age was successfully retrieved from the Landsat time series stacks in the last 40 years (from 1974 to 2013) and shown to be consistent with the surveyed tree ages, with a root-mean-square error (RMSE) value of 4.32 years and a determination coefficient (R ²) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R ² values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in seven counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360 %. For the persistent forest area since 1974, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 0.98 t/ha. For the artificial forest planted after 1974, the AGB density increased about 1.03 t/ha a year from 1974 to 2013. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.     

改性壳聚糖复合凹凸棒土絮凝油漆废水

将壳聚糖、阳离子淀粉和二甲基二烯丙基氯化铵(DMDAAC)进行三元接枝共聚,制备了三元接枝改性壳聚糖(CTS-DMDAAC-CS),通过红外光谱和扫描电镜对其结构进行了表征。并且将三元接枝改性壳聚糖与凹凸棒土进行优化复配,对油漆废水进行了絮凝实验,得出了当pH=12,沉降时间为20 min,复合絮凝剂投加量为0.2 g,三元接枝共聚物∶凹凸棒土=1∶10时,该复合絮凝剂对油漆去除率最佳能够达到89.3%,并且絮凝效果好,是一种新型绿色环保的有机-无机复合絮凝剂。