粉煤灰的有效利用

介绍了我国粉煤灰利用状况及政策，结合实例分析了粉煤灰的有效利用和清洁生产对促进粉煤灰有效利用的作用。     

炼油厂废裂化催化剂的综合利用

炼油厂的催化裂化催化剂用过一段时间后就失去活性 ,卸出系统后成了废物 ,污染环境。该研究在实验的基础上介绍了综合利用方案 ,可达到变废为宝、增加效益、净化环境的目的     

天祝地震危险区划研究

研究天祝地震危险区划是一个综合性的课题。通过研究基本查清了自治县的地震危险家底,并进行了分析研究,得出了今后预防地震和主要防震减灾以及地震监测预报等方面的实施意见。揭示了本县的地域异常规律,划分了重点地震危险区。可见研究天祝地震危险区划分和强震预测、预报是很有意义的。     

废电池的环境污染及资源化价值分析

分析了各类废电池的资源化,安再生利用价值由高到低顺序依次为铅酸蓄电池、镍镉、镍氢电池、普通干电池。电池中含有的主要污染物质包括重金属以及酸、碱等电解质溶液。对环境和人体健康危害较大的废电池类别主要为：（1）含汞电池，指氧化汞电池，部分汞含量较高的锌锰和碱锰干电池；（2）铅酸蓄电池；（3）含镉电池，主要是Ni-Cd电池。废电池中化学物质释放进入环境过程是在电池包壳破损后发生的，或者是电池包壳本身发生浸蚀作用。普通家用干电池中的污染物质大多呈固态，由电池内部迁移到环境中是一种缓慢的过程。文中还分析了废电池污染环境的主要途径、采用各种不同处理、处置方式管理废电池可能引起的环境污染。     

Spatial Pattern Analysis of Regional Water Use Profile Based on the Gini Coefficient and Location Quotient

Water resources have become a barrier hampering socioeconomic development. Changes in the spatial distribution of water use profile have direct impacts to regional water use efficiency. However, the related research is inadequate, and a more suitable way to analyze regional water use profile is necessary. The Gini coefficient and location quotient, two reliable methods commonly used in discussing the spatial distribution of elements, were introduced and calculated. Taking Gansu Province as the study area, the concentration effect of industrial water use was the strongest, followed by domestic, environmental, and agricultural water use. However, a balanced distribution of agricultural water use failed to be coordinated with the production conditions, the center of Gansu’s grain production should be established to enhance the scale effect of agricultural production. The industrial agglomeration effect remained weak, and each region’s dominant industries need to be developed vigorously. Gansu’s domestic water use was consistent with its population distribution, but it is necessary to reduce the water use gap between urban and rural areas. With a growing awareness of environmental protection, environmental water use exhibited a more balanced distribution. Overall, the methods are simple and have good applicability, and the results can provide a reference in water use optimization.     

Fe-絮凝降阻法处理后的印染污泥燃烧特性

为明确印染污泥焚烧特性,提高其处理效率.以Fe-絮凝降阻法深度处理的印染污泥为研究对象,通过TG-DTG热重曲线法研究不同干燥时间（1.5、2.0、2.5、3.0、3.5和4.0 h）对深度处理的印染污泥燃烧特性的影响,并对深度处理的印染污泥燃烧过程的动力学和失重速率进行拟合.结果表明:不同干燥时间下,深度处理的印染污泥的焚烧过程均可分为4个阶段,阶段1为水蒸发阶段（15.9~106.9℃）,阶段2为低沸点有机物析出阶段（106.9~235.5℃）,阶段3为挥发分的析出和燃烧阶段（235.5~479.0℃）,阶段4为难挥发物质和碳酸盐分解阶段（479.0~852.2℃）,污泥最大失重率均在410.0℃左右,最大失重均出现在阶段3.最佳干燥时间为2.0 h（含水率为3.60%）,该条件下深度处理的印染污泥在阶段3失重峰值前、后分别为0.5级和2级反应,活化能分别为7.227和87.040 kJ/mol.失重峰值前、后的失重速率方程分别为y=9.003 18-0.099 68x（R2=0.998 1）和y=5.576+2.105/{1+exp[（x-18.076）/1.349]}（R2=0.997 8）.研究显示,深度处理的印染污泥主要在第3阶段燃烧,所得失重速率方程与其第3阶段燃烧的失重速率数据较好吻合.      

Preparation,Characterization, and Rapid Adsorption of Hg<Superscript>2+</Superscript> on Nanoscale Aramid-based Adsorbent

A series of nanaoscale aramid-based adsorbents were prepared by the functionalization of poly (p-phenylene terephthalamide) (PPTA) with different content of ethylenediamine (EDA). Their structures were characterized by field emission scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis, and elemental analysis. Metal ions, including Hg²⁺, Pb²⁺, Ag⁺, Cu²⁺, Cd²⁺, and Ni²⁺ were chosen as the models to explore the binding behaviors of PPTA–ECH–EDA in aqueous medium. Results showed that PPTA–ECH–EDA exhibited higher adsorption capacity for Hg²⁺ due to their nanoscale structures. In particular, the adsorption rate was so high that equilibrium was achieved within 15 min for Hg²⁺. The adsorption of Hg²⁺ on PPTA–ECH–EDA followed the pseudo second-order model well. Langmuir and Freundlich models were employed to fit the isothermal adsorption, and the results revealed that Freundlich isotherm was a better model to predict the experimental data. The adsorption mechanism was revealed by X-ray photoelectron spectroscopy. It is preconceived that PPTA–ECH–EDA could be used as an effective adsorbent for fast removal of heavy ions from wastewater.     

Leaching of heavy metals from E-waste in simulated landfill columns

In recent history the volume of electronic products purchased by consumers has dramatically escalated. As a result this has produced an ever-increasing electronic waste (E-waste) stream, which has generated concerns regarding the E-waste’s potential for adversely impacting the environment. The leaching of toxic substances from obsolete personal computers (PCs) and cathode ray tubes (CRTs) of televisions and monitors, which are the most significant components in E-waste stream, was studied using landfill simulation in columns. Five columns were employed. One column served as a control which was filled with municipal solid waste (MSW), two columns were filled with a mixture of MSW and CRTs, and the other two were filled with MSW and computer components including printed wire boards, hard disc drives, floppy disc drives, CD/DVD drives, and power supply units. The leachate generated from the columns was monitored for toxic materials throughout the two-year duration of the study. Results indicate that lead (Pb) and various other heavy metals that were of environmental and health concern were not detected in the leachate from the simulators. When the samples of the solids were collected from underneath the E-waste in the columns and were analyzed, significant amount of Pb was detected. This indicates that Pb could readily leach from the E-waste, but was absorbed by the solids around the E-waste materials. While Pb was not observed in the leachate in this study, it is likely that the Pb would eventually enter the leachate after a long term transport.     

Biodegradation of nicosulfuron by the bacterium Serratia marcescens N80

By enrichment culturing of the sludge collected from the industrial wastewater treatment pond, we isolated a highly efficient nicosulfuron degrading bacterium Serratia marcescens N80. In liquid medium, Serratia marcescens N80 grows using nicosulfuron as the sole nitrogen source, and the optimal temperature, pH values, and inoculation for degradation are 30–35°C, 6.0–7.0, and 3.0% (v/v), respectively. With the initial concentration of 10 mg L^?1, the degradation rate is 93.6% in 96 hours; as the initial concentrations are higher than 10 mg L^?1, the biodegradation rates decrease as the nicosulfuron concentrations increase; when the concentration is 400 mg L^?1, the degradation rate is only 53.1%. Degradation follows the pesticide degradation kinetic equation at concentrations between 5 mg L^?1 and 50 mg L^?1. Identification of the metabolites by the liquid chromatography/mass spectrometry (LC/MS) indicates that the degradation of nicosulfuron is achieved by breaking the sulfonylurea bridge. The strain N80 also degraded some other sulfonylurea herbicides, including ethametsulfuron, tribenuron-methyl, metsulfuron-methyl, chlorimuron-ethyl,and rimsulfuron.     

Applying the GM(1,1) model to simulate and predict the ecological footprint values of Suzhou city,China

The ecological footprint value (abbreviated as EF) is the quantitative indicator on evaluating the sustainable development status of a region. How to simulate the EF’s trend with a long-time data series has been heatedly discussed. The economic development of Suzhou, one of the most developed cities in Yangtze Delta, China, has been accelerated in the past 20 years, and it is necessary to evaluate the influence of the socioeconomic growth on local natural resources. The EF values of Suzhou from 1999 to 2018 were calculated and simulated using both the ARIMA model and the GM(1,1) model. The ARIMA model has been used in the prediction of EF values in several cases. However, the EF data series of the city consisted of white noise and could not be fitted by the ARIMA model. The GM(1,1) model, an approach forecasting nonlinear data series, was not found in the studies of the EF simulation. Through the model precision test, the GM(1,1) model introduced fit the EF data series well and was considered to be appropriate to simulate the EF values for Suzhou. The fitting performance was accurate, and the EF values of the city could be forecasted by the model in short term. With the proposed model, the ecological sustainability status of the city was analyzed.