某炼油厂焦化制氢车间职业病危害识别及控制措施

针对某炼厂实际工艺流程,分析了炼化企业焦化、制氢工段生产过程中可能存在的职业病危害因素.根据对现场检测结果的分析,提出了炼化企业职业病危害因素控制技术措施.     

Who avoids being involved in personal carbon trading? An investigation based on the urban residents in eastern China

Environmental Science and Pollution Research - Personal carbon trading scheme has been pulled into the public eye with the increasing urgency of downstream carbon emission reduction, and its...     

Development of global soil erosion research at the watershed scale: a bibliometric analysis of the past decade

Environmental Science and Pollution Research - At the watershed scale, soil erosion is a cascading system that includes detachment–transport–deposition processes while sediment yield is...     

Remediation of heavy metal–polluted alkaline vegetable soil using mercapto-grafted palygorskite: effects of field-scale application and soil environmental quality

Environmental Science and Pollution Research - Remediation materials are the most critical factors for in situ immobilization of soil contaminated by heavy metals. In this study, in order to...     

基于广州塔多层观测的城市臭氧污染垂直分布特征及成因分析

利用2019年11月1日—2020年4月30日广州主城区和广州塔121 m、454 m O₃浓度同步监测数据,分析了广州市O₃垂直污染分布特征及成因.结果表明：①近地面O₃浓度变化主要取决于人类活动如工业排放和机动车尾气排放等,而高空O₃浓度主要取决于天气过程,如辐射造成光学反应加剧和区域传输.②地面的O₃浓度高于垂直观测站点,其日变化均呈单峰型分布,表现为日出后太阳辐射增强O₃浓度升高,在午后14：00—15：00达到一日中的最高值.③广州塔454 m的O₃浓度日变化呈明显的双峰型特征,第1个峰值出现早上7：00后,O₃浓度随着日出后边界层混合抬升而升高,第2个峰值持续出现在午后,因高温、辐射导致的光化学反应剧烈生成.相对广州其他站点的第2峰值滞后的现象,可能是由于近地面臭氧生成后垂直传输到塔顶出现的垂直混合的时间差,受到边界层抬升强度不同的影响.④广州塔121 m站点,O₃浓度与风速的关系非常明显,广州南部地区臭氧贡献度达到了45%.在广州的冬季和春季,其中尤以冬季12—1月,广州臭氧污染贡献源广州塔中可能 来自于南部,广州塔顶454 m来自于东南部.     

Effects of vermiculite on the growth process of submerged macrophyte Vallisneria spiralis and sediment microecological environment

Ecological restoration is one of the hot technologies for the reconstruction of eutrophic lake ecosystems in which the restoration and propagation of submerged plants is the key and difficult step. In this paper, the effect of vermiculite on the growth process of Vallisneria spiralis and sediment microenvironment were investigated, aiming to provide a theoretical basis for the application of vermiculite in aquatic ecological restoration. Results of growth indexes demonstrated that 5% and 10% vermiculite treatment groups statistically promote the growth of Vallisneria spiralis compared to the control. Meanwhile, the results of ecophysiological indexes showed that photosynthetic pigment, soluble sugar content, superoxide dismutase (SOD), and catalase (CAT) activity of 5% and 10% group were increased compared with the control while the malondialdehyde (MDA) content exhibited the opposite result (p < 0.05), which illustrated that vermiculite can improve the resistance of plants and delay the aging process of Vallisneria spiralis. In addition, result of PCA (Principal Component Analysis) demonstrated 5% and 10% group has improved the sediment physical conditions and create more ecological niche for microorganisms directly, and then promoted the growth of plants. The dissolution results showed that vermiculite can dissolve the constant and trace elements needed for plant growth. Furthermore, the addition of vermiculite increased the diversity of microorganisms in the sediments, and promoted the increase of plant growth-promoting bacteria and phosphorus-degrading bacteria. This study could provide a technique reference for the further application of vermiculite in the field of ecological restoration.     

Understanding the risks of mercury sulfide nanoparticles in the environment: Formation, presence, and environmental behaviors

Mercury (Hg) could be microbially methylated to the bioaccumulative neurotoxin methylmercury (MeHg), raising health concerns. Understanding the methylation of various Hg species is thus critical in predicting the MeHg risk. Among the known Hg species, mercury sulfide (HgS) is the largest Hg reservoir in the lithosphere and has long been considered to be highly inert. However, with advances in the analytical methods of nanoparticles, HgS nanoparticles (HgS NPs) have recently been detected in various environmental matrices or organisms. Furthermore, pioneering laboratory studies have reported the high bioavailability of HgS NPs. The formation, presence, and transformation (e.g., methylation) of HgS NPs are intricately related to several environmental factors, especially dissolved organic matter (DOM). The complexity of the behavior of HgS NPs and the heterogeneity of DOM prevent us from comprehensively understanding and predicting the risk of HgS NPs. To reveal the role of HgS NPs in Hg biogeochemical cycling, research needs should focus on the following aspects: the formation pathways, the presence, and the environmental behaviors of HgS NPs impacted by the dominant influential factor of DOM. We thus summarized the latest progress in these aspects and proposed future research priorities, e.g., developing the detection techniques of HgS NPs and probing HgS NPs in various matrices, further exploring the interactions between DOM and HgS NPs. Besides, as most of the previous studies were conducted in laboratories, our current knowledge should be further refreshed through field observations, which would help to gain better insights into predicting the Hg risks in natural environment.     

Denitrification and microbial community in MBBR using A. donax as carbon source and biofilm carriers for reverse osmosis concentrate treatment

In this study,raw Arundo donax(A.donax)pieces were applied as carbon source and biofilm carriers for denitrification in a lab-scale moving bed biofilm reactor(MBBR)for the treatment of reverse osmosis concentrate gathered from local wastewater reuse plant.At stable phase(about 60 days),efficient denitrification performance was obtained with73.2%±19.5%NO_(3-)~-N average removal and 8.10±3.45 g N/(m~3·day)NO_(3-)~-N average volumetric removal rate.Mass balance analysis showed that 4.84 g A.donax was required to remove 1 g TN.Quantitative real-time PCR analysis results showed that the copy numbers of 16S r-RNA,narG,nirS,nosZ and anammox gene of carrier biofilm and suspended activated sludge in the declination phase(BF2 and AS2)were lower than those of samples in the stable phase(BF1 and AS1),and relatively higher copy numbers of nirS and nirK genes with lower abundance of narG and nosZ genes were observed.High-throughput sequencing analysis was conducted for BF2 and AS2,and similar dominant phyla and classes with different abundance were obtained.The class Gammaproteobacteria affiliated with the phylum Proteobacteria was the most dominant microbial community in both BF2(52.6%)and AS2(41.7%).The PICRUSt prediction results indicated that 33 predictive specific genes were related to denitrification process,and the relative abundance of 18 predictive specific genes in BF2 were higher than those in AS2.     

镧掺杂TiO2/g-C3N4复合光催化剂的制备及其可见光催化活性研究

以工业二氧化钛(TiO_2)、硝酸镧(LaN_3O_9·5H_2O)、三聚氰胺(C_3H_6N_6)为原料制备了La掺杂TiO_2/g-C_3N_4复合光催化剂.采用X射线衍射(XRD)、X射线光电子能谱(XPS)、透射电子显微镜(TEM)、傅里叶变换红外(FT-IR)、紫外-可见吸收光谱(UV-Vis)、荧光光谱(PL)等表征方法对光催化剂结构进行分析,表明复合样品中La以La~(3+)形式存在于TiO_2晶体中,并形成TiO_2/g-C_3N_4异质结构,其禁带宽度减小、吸收带边红移,光催化效率有明显提高.以亚甲基蓝为目标污染物评价其光催化活性,镧掺杂量为4%(质量分数)、煅烧温度为520℃、煅烧时间为2 h时,复合样品光催化活性最佳,在12 LED灯下,180 min后对10 mg·L~(-1)亚甲基蓝溶液的去除率达97%.     

Development of a method for comprehensive water quality forecasting and its application in Miyun reservoir of Beijing, China

Water quality forecasting is an essential part of water resource management. Spatiotemporal variations of water quality and their inherent constraints make it very complex. This study explored a data-based method for short-term water quality forecasting. Prediction of water quality indicators including dissolved oxygen, chemical oxygen demand by KMnO₄ and ammonia nitrogen using support vector machine was taken as inputs of the particle swarm algorithm based optimal wavelet neural network to forecast the whole status index of water quality. Gubeikou monitoring section of Miyun reservoir in Beijing, China was taken as the study case to examine effectiveness of this approach. The experiment results also revealed that the proposed model has advantages of stability and time reduction in comparison with other data-driven models including traditional BP neural network model, wavelet neural network model and Gradient Boosting Decision Tree model. It can be used as an effective approach to perform short-term comprehensive water quality prediction.