Kinetic parameter estimation for decomposition of organic peroxides by means of DSC measurements

The thermal stability of organic peroxides (cumene hydroperoxide 80 wt% and dicumyl peroxide) was studied by means of calorimetric measurement (DSC, TA Q1000) in an isotherm mode and a dynamic mode. Analysis of power profiles released in the isothermal mode was combined with the analysis of the decomposed compounds by a gas chromatograph/mass spectrometer (GC/MS) to determine the reaction mechanisms corresponding to each of the two reactions. In this work, a methodology for estimating kinetic parameters was based on the comparison of the power profile (dynamic mode) given by the model to that obtained experimentally by changing the parameters values. Parameter estimation is achieved using the mixed estimation method where a genetic algorithm is combined with a locally convergent method.     

中国北方某市城市绿地土壤重金属空间分布特征、污染评价及来源解析

为掌握北方某市城市中心区绿地土壤环境状况,对其中心区城市绿地土壤重金属（Cd、Hg、As、Pb、Cu、Cr、Zn和Ni）的空间分布、来源及污染现状进行分析和评价.结果表明,该市中心区的城市绿地土壤环境质量整体良好.土壤重金属Cd、Hg、As、Pb、Cr、Cu、Zn和Ni的含量均值分别为：0.172、0.202、9.02、34.7、57.0、31.2、85.7以及26.3mg·kg^-1.Cd、Hg、Pb和Zn平均含量均超过同为北方地区的京津唐土壤背景值.所有点位各项重金属含量均不超过国家建设用地土壤污染风险管控标准的污染风险筛选值.空间上,As、Cr和Ni含量高值出现于西北部;Cd和Zn含量高值出现于东北部;Hg、Pb和Cu的高值区集中在城市核心区.对于不同土地利用类型土壤,Cd、Zn和Ni在企业绿地土壤中含量显著高于其他元素,Hg、Pb和Cu等在公园绿地和居民绿地土壤中含量较高.土壤污染评价结果表明,97.2%的样点内梅罗综合污染指数小于1,为清洁土壤;所有样点潜在生态风险指数均小于80,属轻微生态风险水平.多元统计分析表明,Cu、Pb和Hg为人为源,与古建筑保护的彩绘以及对古树保护采用杀虫剂有关;Cr为自然源,可能来源于土壤母质和地球化学过程;Cd、Zn、Ni和As为混合来源,部分可能来源于人类活动和工业生产,另一部分来源于岩石的风化和土壤母质等.利用受体模型对超标元素进行来源定量解析,Cd按来源贡献率高低依次为源2（占46.1%）、源3（占33.1%）、源1（17.7%）和其他源（占3.1%）;Cu源贡献率主要为源1（占93.0%）;Zn源贡献率依次为源1（占52.4%）、源3（占24.2%）、源2（占20.0%）以及其他源（占3.4%）;Ni源贡献率依次为源1（占56.3%）、源2（占37.8%）以及源3（占5.8%）.推测源1和源3为人为源,源2为自然来源.     

气相色谱／质谱（GC／MS）联用在我国大气有机污染监测中的应用

概述ＧＣ／ＭＳ联用在我国大气有机污染监测中的应用，介绍大气中有机污染物，如多环芳烃、硝基多环芳烃、多氯二苯并二恶英、多氯二苯并呋喃、碳氢化合物、苯系物、恶臭、有机硫化合物、多组分有机污染物的测定。     

Long-term variation of PM2.5 levels and composition at rural, urban, and roadside sites in Hong Kong: Increasing impact of regional air pollution

Long-term study of air pollution plays a decisive role in formulating and refining pollution control strategies. In this study, two 12-month measurements of PM_2.5 mass and speciation were conducted in 00/01 and 04/05 to determine long-term trend and spatial variations of PM_2.5 mass and chemical composition in Hong Kong. This study covered three sites with different land-use characteristics, namely roadside, urban, and rural environments. The highest annual average PM_2.5 concentration was observed at the roadside site (58.0±2.0 μg m⁻³ (average±2σ) in 00/01 and 53.0±2.7 μg m⁻³ in 04/05), followed by the urban site (33.9±2.5 μg m⁻³ in 00/01 and 39.0±2.0 μg m⁻³ in 04/05), and the rural site (23.7±1.9 μg m⁻³ in 00/01 and 28.4±2.4 μg m⁻³ in 04/05). The lowest PM_2.5 level measured at the rural site was still higher than the United States’ annual average National Ambient Air Quality Standard of 15 μg m⁻³. As expected, seasonal variations of PM_2.5 mass concentration at the three sites were similar: higher in autumn/winter and lower in summer. Comparing PM_2.5 data in 04/05 with those collected in 00/01, a reduction in PM_2.5 mass concentration at the roadside (8.7%) but an increase at the urban (15%) and rural (20%) sites were observed. The reduction of PM_2.5 at the roadside was attributed to the decrease of carbonaceous aerosols (organic carbon and elemental carbon) (>30%), indicating the effective control of motor vehicle emissions over the period. On the other hand, the sulfate concentration at the three sites was consistent regardless of different land-use characteristics in both studies. The lack of spatial variation of sulfate concentrations in PM_2.5 implied its origin of regional contribution. Moreover, over 36% growth in sulfate concentration was found from 00/01 to 04/05, suggesting a significant increase in regional sulfate pollution over the years. More quantitative techniques such as receptor models and chemical transport models are required to assess the temporal variations of source contributions to ambient PM_2.5 mass and chemical speciation in Hong Kong.     

A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

• A spectral machine learning approach is proposed for predicting mixed antibiotic. • Pretreatment is far simpler than traditional detection methods. • Performance of the model is compared in different influencing factors. • Spectral machine learning is promising in the detection of complex substances. Antibiotics are widely used in medicine and animal husbandry. However, due to the resistance of antibiotics to degradation, large amounts of antibiotics enter the environment, posing a potential risk to the ecosystem and public health. Therefore, the detection of antibiotics in the environment is necessary. Nevertheless, conventional detection methods usually involve complex pretreatment techniques and expensive instrumentation, which impose considerable time and economic costs. In this paper, we proposed a method for the fast detection of mixed antibiotics based on simplified pretreatment using spectral machine learning. With the help of a modified spectrometer, a large number of characteristic images were generated to map antibiotic information. The relationship between characteristic images and antibiotic concentrations was established by machine learning model. The coefficient of determination and root mean squared error were used to evaluate the prediction performance of the machine learning model. The results show that a well-trained machine learning model can accurately predict multiple antibiotic concentrations simultaneously with almost no pretreatment. The results from this study have some referential value for promoting the development of environmental detection technologies and digital environmental management strategies.     

Developing “precise-acting” strategies for improving anaerobic methanogenesis of organic waste: Insights from the electron transfer system of syntrophic partners

Methanogenesis is the last step in anaerobic digestion, which is usually a rate-limiting step in the biological treatment of organic waste. The low methanogenesis efficiency (low methane production rate, low methane yield, low methane content) substantially limits the development of anaerobic digestion technology. Traditional pretreatment methods and bio-stimulation strategies have impacts on the entire anaerobic system and cannot directly enhance methanogenesis in a targeted manner, which was defined as “broad-acting” strategies in this perspective. Further, we discussed our opinion of methanogenesis process with insights from the electron transfer system of syntrophic partners and provided potential targeted enhancing strategy for high-efficiency electron transfer system. These “precise-acting” strategies are expected to achieve an efficient methanogenesis process and enhance the bio-energy recovery of organic waste.     

白银矿区土壤重金属及可培养细菌重金属耐受性研究

对白银矿区土壤重金属进行分析研究,分离、筛选和鉴定了受污染土壤中的可培养细菌,并考察其对土壤中重金属胁迫的耐受性。结果表明：白银矿区王岘镇尾渣堆和东大沟河沟土壤重金属污染Pb＞Zn＞Cu;从污染最严重的土壤中分离、筛选出砖红色微杆菌（Microbacterium testaceum）、特基拉芽孢杆菌（Bacillus tequilensis）和解单端孢菌素微杆菌（Microbacterium trichothecenolyticum）3种细菌,其中菌株M1（Microbacterium testaceum）对Pb、Zn、Cu、Cd的胁迫具有明显的耐受性。     

北京市某废弃焦化厂不同车间土壤中多环芳烃（PAHs）的分布特征及风险评价

以北京市某废弃焦化厂为研究对象,系统采集了6个车间0～4m深的26个土壤样本,利用GC/MS检测了U.S.EPA优控的16种多环芳烃(PAHs)的含量,分析了PAHs在焦化厂不同车间表层土壤的污染状况和深层土壤中的垂直分布特征并对土壤污染风险进行了评估.结果表明,1)该废弃焦化厂不同车间表层土壤(0～20cm)总PAHs(∑PAHs)的残留量介于672.8～144814.3ng·g-1之间;污染程度排序为:回收车间>老粗苯车间>焦油车间>炼焦车间>水处理车间>制气车间.2)该厂未受扰动的土壤样品显示PAHs主要聚集在表层土壤,并随着土壤深度的增加而迅速减少;其他样点由于土壤扰动,∑PAHs含量最大值出现在第三层土壤(80～180cm);该厂4m深底层土壤仍有高浓度PAHs,∑PAHs含量最高值出现在炼焦车间,达12953.1ng·g-1.3)焦化厂土壤PAHs污染主要集中在3环和4环的PAHs单体上,分别占到污染总量的51.3%和31.7%.4)根据Maliszewska-Kordybach的PAHs总量标准及加拿大土壤PAHs单体治理标准,该厂回收、老粗苯、焦油和炼焦车间表层和深层土壤PAHs含量均达到重污染水平,并对其周围土地带来较大风险,需要治理.     

焦化厂A/O出水中的有机污染物分析

采用色谱－质谱（GC／MS）联用仪分析和鉴定了上海宝钢焦化厂A／O生化阶段出水的有机污染物组成,共检出各类有机污染物70多种。结合焦化废水专用混凝剂的混凝处理实验结果,指出了各类有机污染物的去除情况。     

Retrospective Estimation of Radiation Load and Its Effect on Some Biological Parameters of Reindeer (Rangifer tarandus) from Wrangel Island

The results of the electron paramagnetic resonance (EPR) analysis of pure tooth enamel and the data on the radionuclide content in bones were used for estimating the radiation load on reindeer that lived on Wrangel Island in the 1970s and early 1980s. Based on the measurements of the lower jaws, some biological parameters of the Wrangel reindeer population were estimated and compared with those in the Novaya Zemlya and Taimyr populations. Changes in only two of these parameters—the degree of root cementum resorption and animal life span–might be attributed to the effect of the radiation load.