Altitude dependence of polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) in surface soil from Tibetan Plateau, China

Remote mountain areas besides high latitude regions are beginning to receive increased attention in studying the transport and behavior of persistent organic pollutants (POPs). In the present work, surface soil samples were collected from the Tibetan Plateau, the highest plateau in the world which includes the northern slope of Mt. Qomolangma, to investigate the levels and trends of polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) along the altitudinal gradient. The average PCB and PBDE concentrations were 185.6 ng kg⁻¹ dry weight (dw) (range 47.1–422.6 ng kg⁻¹ dw) and 11.1 ng kg⁻¹ dw (range 4.3–34.9 ng kg⁻¹ dw), respectively. Regression analysis between the log-transformed TOC-normalized concentrations and the altitudes of the sampling sites showed two opposite trends with regard to altitude dependence: negative relationship with altitude below about 4500 m followed by a positive altitude dependence above this point. Considering minimum anthropogenic activities and very sparse precipitation in the north of Himalayas, the trends above 4500 m imply that the significant altitude dependence of these two groups of POPs were irrespective of pollution sources, but could be predicted by the global distillation effect involving cold condensation in high altitude mountain areas. Increasing levels of heavier congeners were found in higher altitude sites, although the lighter congeners were the main contributors to the total amount, suggesting that less volatile congeners seem to become enriched easier than those more volatile at higher altitudes in this region.     

白洋淀两种生境中芦苇地上生物量及其影响因子分析

文章在野外调查的基础上,在白洋淀台田和沼泽中各选择6个样区,统计分析了2种生境芦苇地上生物量;运用冗余分析方法(RDA),分析了芦苇生长季(4～9月)平均水深、土壤/底泥有机质、全氮和全磷等对两类生境中芦苇地上生物量的影响.结果表明,台田、沼泽中芦苇地上生物量分别为1 408.2±527.5 gDW/m2、723.2±...     

Analysis of the severity of vehicle-bicycle crashes with data mining techniques

Introduction: Although cycling is increasingly being promoted for transportation, the safety concern of bicyclists is one of the major impediments to their adoption. A thorough investigation on the contributing factors to fatalities and injuries involving bicyclist. Method: This paper designs an integrated data mining framework to determine the significant factors that contribute to the severity of vehicle-bicycle crashes based on the crash dataset of Victorian, Australia (2013–2018). The framework integrates imbalanced data resampling, learning-based feature extraction with gradient boosting algorithm and marginal effect analysis. The top 10 significant predictors of the severity of vehicle-bicycle crashes are extracted, which gives an area under ROC curve (AUC) value of 0.8236 and computing time as 37.8 s. Results: The findings provide insights for understanding and developing countermeasures or policy initiatives to reduce severe vehicle-bicycle crashes.     

PCR-DGGE研究Carrousel 2000氧化沟工艺调试过程中的微生物多样性

收集Carrousel 2000型氧化沟工艺启动过程中活性污泥样品,直接提取微生物的基因组DNA并纯化,然后对细菌16S rDNA的V3高变区进行PCR扩增和DGGE分离,通过比较DGGE图谱的相似性来研究工艺调试过程中微生物种群的变化情况.研究表明,活性污泥中具有非常丰富的微生物种群.调试初期水质波动对氧化沟中微生物种群的影响非常明显,但接种的成熟活性污泥中微生物种群能够很快适应新型氧化沟工艺的结构及水力特性.调试从4月开始,4月氧化沟中微生物种群相似性Cs最大值为68.9%,5~6月Cs最大值为70.8%,8月Cs最大值为73.0%,可见氧化沟中微生物种群相似性逐渐增加,直至稳定.在此过程中,系统对COD、氨氮的处理效果同步提高并趋于稳定.综合分析好氧活性污泥在氧化沟中驯化期为2个月.图4表4参12     

减压法在新型双程序柱上的应用——废水中苯系物的测定

本文采用减压法解决了新型双程序柱载气流速过低问题,使测定结果灵敏度提高,保留时间缩短。用于粗苯车间废水中苯系物的测定,回收率为９０３～１０１６,最低检出浓度为００００７～０００１４ｇ／Ｌ。     

老港填埋场新鲜渗滤液性质研究

用系列滤膜对老港填埋场2003年3月份新鲜渗滤液进行了梯度分离．并研究了其CODcr、氨氮、TOC、IC、TC、TS、FS、电导率、pH、色度,浊度的变化趋势与不同孔径膜之间的关系。结果表明,随着膜孔径的减小,CODcr、氨氮、TOC、IC、TC、TS、FS、色度、浊度等都有不同程度的降低,但降低不大,说明可溶性部分物质对新鲜渗滤液的污染性贡献最大;电导率、pH则先增大后减小。     

毒性废水稀释中强度改变与浓度改变的跟随性研究

适用于已知毒物和毒性应用剂量测定的经典技术方法,以样品稀释过程中毒性强度改变与浓度改变的等比率跟随性为基础。废水中的毒性物质常以未知和混合为特征,高毒性的样品现状浓度距离方法预试验中最小全致死浓度较远,以已知毒物重铬酸钾毒性为对照,形成5种毒物高层级等强度毒性,通过这些高毒性废水同步等比率稀释后毒性改变的同步性测定试验,证明毒性废水稀释中强度改变与浓度改变的跟随状态具有不确定性。     

Development of machine learning multi-city model for municipal solid waste generation prediction

● A database of municipal solid waste (MSW) generation in China was established. ● An accurate MSW generation prediction model (WGMod) was constructed. ● Key factors affecting MSW generation were identified. ● MSW trends generation in Beijing and Shenzhen in the near future are projected. Integrated management of municipal solid waste (MSW) is a major environmental challenge encountered by many countries. To support waste treatment/management and national macroeconomic policy development, it is essential to develop a prediction model. With this motivation, a database of MSW generation and feature variables covering 130 cities across China is constructed. Based on the database, advanced machine learning (gradient boost regression tree) algorithm is adopted to build the waste generation prediction model, i.e., WGMod. In the model development process, the main influencing factors on MSW generation are identified by weight analysis. The selected key influencing factors are annual precipitation, population density and annual mean temperature with the weights of 13%, 11% and 10%, respectively. The WGMod shows good performance with R² = 0.939. Model prediction on MSW generation in Beijing and Shenzhen indicates that waste generation in Beijing would increase gradually in the next 3–5 years, while that in Shenzhen would grow rapidly in the next 3 years. The difference between the two is predominately driven by the different trends of population growth.     

Phytosociological inference and resource management

The application of vegetation information to resource management problems is reviewed in four areas: (1) the stratification of vegetation data by classification and gradient analysis, (2) the storage and retrieval of these data, (3) the sources of vegetation information, and (4) the accuracy and resolution requirements posed by different management applications. Conclusions indicate that the successful application of inference methods to resource management problems requires an appropriate integration of these four components.