辽宁某冶炼厂重金属污染对土壤中微生物的有效性影响

对某铜锌冶炼厂周边土壤微生物区系和土壤抗性细菌数进行了实验分析。结果表明,在冶炼厂周边土壤几种重金属含量与对照区土壤相比明显的增加。冶炼厂周边土壤中,土壤微生物的总数下降,土壤微生物各主要生理类群数量明显减少。抗性实验结果表明:由于土壤长期受重金属污染影响,土壤中细菌抗重金属水平提高,耐性菌种多。     

Markov reliability model research of monitoring process in digital main control room of nuclear power plant

Monitoring process is an important part in a high safety digital main control room of nuclear power plant (NPP), it is the source extracted information and found abnormal information in time. As the human factors events arisen from monitoring process recently take place more and more frequent, the authors propose a reliability Markov model to effectively decrease these abnormal events. The model mainly analyzes next monitoring object probability in terms of current information and plant state. The authors divide digital human–machine interface into two parts that are referred as logical homogeneous Markov and logical heterogeneous Markov. For the former, a series of methods of probability evaluation are proposed, such as, Markov transition probability with condition, probability distributed function with human factors, system state and alarm; for the latter, the authors propose the calculation of probability of correlation degree between last time and next time and probability calculation methods with multi-father nodes. The methods can effectively estimate the transition probability from a monitoring component to next monitoring component at time t, can effectively analyze which information is more important in next monitoring process and effectively find more useful information in time t + 1, so that the human factors events in monitoring process can greatly be decreased.     

二氯荧光黄为指示剂的硝酸银滴定法测定废水中氯化物

采用以二氯荧光黄为指示剂的硝酸银滴定法测定废水中氯化物。优化实验条件后,以该法测定质控样,相对误差-1.30%～2.70%,相对标准偏差0.10%～0.14%,加标回收率约为98%。用该法测定废水中氯化物是合理可行的。     

乌鲁木齐市硫酸盐化速率关键影响因子分析

对硫酸盐化速率与大气中污染物质浓度和气象因素的分析结果表明,硫酸盐化速率不仅取决于SO2的浓度,还与PM10显著相关,是因为PM10表面为SO2的催化氧化提供了载体。气压和空气相对湿度对硫酸盐化速率有积极的促进作用,空气中的气态H2O具有凝结污染物质的能力,而降水对污染物质的冲刷效应降低了硫酸盐化速率。影响硫酸盐化速率的是空气中气态H2O而非降水。气温通过影响逆温层和风速共同影响着污染物浓度的扩散和稀释,从而决定着硫酸盐化速率的增减。     

Measurement of the proximity effect for indoor air pollutant sources in two homes

Personal exposure to air pollutants can be substantially higher in close proximity to an active source due to non-instantaneous mixing of emissions. The research presented in this paper quantifies this proximity effect for a non-buoyant source in 2 naturally ventilated homes in Northern California (CA), assessing its spatial and temporal variation and the influence of factors such as ventilation rate on its magnitude. To quantify how proximity to residential sources of indoor air pollutants affects human exposure, we performed 16 separate monitoring experiments in the living rooms of two detached single-family homes. CO (as a tracer gas) was released from a point source in the center of the room at a controlled emission rate for 5-12 h per experiment, while an array of 30-37 real-time monitors simultaneously measured CO concentrations with 15 s time resolution at radial distances ranging from 0.25-5 m under a range of ventilation conditions. Concentrations measured in close proximity (within 1 m) to the source were highly variable, with 5 min averages that typically varied by >100-fold. This variability was due to short-duration (<1 min) pollutant concentration peaks ("microplumes") that were frequently recorded in close proximity to the source. We decomposed the random microplume component from the total concentrations by subtracting predicted concentrations that assumed uniform, instantaneous mixing within the room and found that these microplumes can be modeled using a 3-parameter lognormal distribution. Average concentrations measured within 0.25 m of the source were 6-20 times as high as the predicted well-mixed concentrations.     

Risk assessment of heavy metals in road and soil dusts within PM2.5, PM10 and PM100 fractions in Dongying city, Shandong Province, China

15 road and 14 soil dust samples were collected from an oilfield city, Dongying, from 11/2009-4/2010 and analyzed by inductively coupled plasma-mass spectroscopy (ICP-MS) for V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd and Pb within PM(2.5), PM(10) and PM(100) fractions synchronously. Metal concentrations, sources and human health risk were studied. Results showed that both soil and road dust exhibited higher values for Mn and Zn and lower values for Co and Cd for the three fractions. Mass concentration ratios of PM(2.5)/PM(10) and PM(10)/PM(100) for metals in road and soil dust indicate that most of the heavy metals tend to concentrate in fine particles. Geoaccumulation index and enrichment factors analysis showed that Cu, Zn and Cd exhibited moderate or heavy contamination and significant enrichment, indicating the influence of anthropogenic sources. Vanadium, Cr, Mn and Co were mostly not enriched and were mainly influenced by crustal sources. For Ni, As and Pb, they ranged from not enriched to moderately enriched and were influenced by both crustal materials and anthropogenic sources. The conclusions were confirmed by multivariate analysis methods. Principle component analysis revealed that the major sources were vehicle emission, industrial activities, coal combustion, agricultural activities and crustal materials. The risk assessment results indicated that metal ingestion appeared to be the main exposure route followed by dermal contact. The most likely cause for cancer and other health risks are both the fine particles of soil and road dusts.     

Modeling Large Fire Frequency and Burned Area in Canadian Terrestrial Ecosystems with Poisson Models

Large wildland fires are major disturbances that strongly influence the carbon cycling and vegetation dynamics of Canadian boreal ecosystems. Although large wildland fires have recently received much scrutiny in scientific study, it is still a challenge for researchers to predict large fire frequency and burned area. Here, we use monthly climate and elevation data to quantify the frequency of large fires using a Poisson model, and we calculate the probability of burned area exceeding a certain size using a compound Poisson process. We find that the Poisson model simulates large fire occurrence well during the fire season (May through August) using monthly climate, and the threshold probability calculated by the compound Poisson model agrees well with historical records. Threshold probabilities are significantly different among different Canadian ecozones, with the Boreal Shield ecozone always showing the highest probability. The fire prediction model described in this study and the derived information will facilitate future quantification of fire risks and help improve fire management in the region.     

Occurrence,distribution, and multi-phase partitioning of triclocarban and triclosan in an urban river receiving wastewater treatment plants effluent in China

Occurrence, distribution, spatial and seasonal variations, and partitioning between aqueous phase and suspended particulate matters (SPM) of triclocarban (TCC) and triclosan (TCS) in Xiaoqing River, which receives wastewater treatment plant (WWTP) effluents, were studied. The distribution of the total TCC and TCS levels in surface water and sediments along the river were discussed. The highest TCC and TCS concentrations were both found near the discharge port of WWTPs, and the TCC and TCS levels decreased downstream of the WWTPs as a result of their distances from the source of WWTP discharges. The mean values of TCC and TCS in low-flow season were 1.62 and 1.80 times, respectively, as much as in high-flow season in surface water. The study on partitioning of TCC and TCS between aqueous phase and SPM shown the mean level of dissolved TCC accounted for about 10 % of the total level in surface water, whereas the TCS level was about 30 %. The TCC concentrations detected in the surface sediment samples (0 to 5 cm) ranged from 226 to 1,956 ng/g, with a mean value of 733 ng/g. The TCS levels were between 85 and 705 ng/g, with a mean value of 255 ng/g. The distribution and variations of TCC and TCS in sediments along the river were highly consistent with those in the water phase. The TCC and TCS levels in deep sediments (5 to 10 cm) were significantly lower than those in surface sediments. The mean TCC level in surface sediments was about 2.4 times as much as in deep sediments, and the TCS level in surface sediments was 3.1 times as much as in deep sediments.     

酸性矿井水中和沉淀法除铁优化

针对山西某煤矿高矿化度、高铁酸性矿井水除铁效果差、出水容易返色等问题,采用NaOH中和调pH、曝气及化学氧化等处理工艺进行酸性矿井水中和沉淀法除铁优化实验研究。结果表明,采用NaOH中和沉淀法除铁时,投加中和剂使出水pH达6.7以上时,出水中铁含量低于10 mg/L,满足排放要求。对于本实验废水NaOH所需投加量为2.8 g/L,铁的去除率可达到99.75%;以H2O2对原水进行氧化处理,可迅速将Fe(Ⅱ)氧化成Fe(Ⅲ),其用量与原水中Fe(Ⅱ)的含量成正比。当其用量为1.6 mL/L时,可将原水中的Fe(Ⅱ)完全转化为Fe(Ⅲ),投加中和剂使出水pH达到4.5以上时,能使出水中铁含量满足排放要求。对于实验废水所需的NaOH投加量为2.0 g/L,比直接中和沉淀所需的NaOH用量要节省28.6%。曝气处理对原水中Fe(Ⅱ)的氧化效果不明显。     

Role of cosubstrate and bioaccessibility played in the enhanced anaerobic biodegradation of organochlorine pesticides (OCPs) in a paddy soil by nitrate and methyl-β-cyclodextrin amendments

The present study was conducted to investigate the anaerobic biodegradation potential of biostimulation by nitrate (KNO₃) and methyl-β-cyclodextrin (MCD) addition on an aged organochlorine pesticide (OCP)-contaminated paddy soil. After 180 days of incubation, total OCP biodegradation was highest in soil receiving the addition of nitrate and MCD simultaneously and then followed by nitrate addition, MCD addition, and control. The highest biodegradation of chlordanes, hexachlorocyclohexanes, endosulfans, and total OCPs was 74.3, 63.5, 51.2, and 65.1 %, respectively. Meanwhile, MCD addition significantly increased OCP bioaccessibility (p?<?0.05) evaluated by Tenax TA extraction and a three-compartment model method. Moreover, the addition of nitrate and MCD also obtained the highest values of soil microbial activities, including soil microbial biomass carbon and nitrogen, ATP production, denitrifying bacteria count, and nitrate reductase activity. Such similar trend between OCP biodegradation and soil-denitrifying activities suggests a close relationship between OCP biodegradation and N cycling and the indirect/direct involvement of soil microorganisms, especially denitrifying microorganisms in the anaerobic biodegradation of OCPs.