氯代烃污染场地生物自然衰减修复研究进展

随着监测自然衰减技术的不断发展和日趋成熟,其在氯代烃污染场地修复领域中的应用越来越广泛和深入。本文在简要回顾监测自然衰减技术来源和发展的基础上,围绕主导氯代烃去除的生物自然衰减过程,综合探究了影响监测自然衰减效率的污染物、生物和环境因素,概述了评估氯代烃污染场地自然衰减能力的实地监测和数值模拟手段,并基于室内模拟实验和场地实际应用现状,分析了其与强化衰减技术联合应用的发展趋势。今后需要在复合污染体系的自然衰减特征、生物降解调控机理研究、数值模拟及同位素分析等手段的应用等方面进一步深入研究,以期为氯代烃污染场地的绿色修复提供参考。     

垃圾填埋场周边桉树光合生理特性研究

为了解垃圾填埋场环境下植物的光合适应性,利用LI-6400便携式光合测定仪,以呼马山森林公园为对照,对位于昆明市东郊垃圾填埋场和对照区的直杆桉Eucalyptus maideni进行了光响应与光合日进程的测定。结果表明:填埋场直杆桉的净光合速率随光强的增加先增加后稍有下降并趋于稳定,光抑制不明显;对照的净光合速率随光强的增加先增加后缓慢下降;在相同光照强度下,填埋场直杆桉的净光合速率、蒸腾速率始终高于呼马山对照的,说明直杆桉可通过提高自身的光合能力和蒸腾速率来适应填埋场的特定环境。胞间CO2浓度随光强的增加先下降后上升,与净光合速率大体呈相反变化;蒸腾速率随光强变化的趋势与气孔导度变化相一致。另外,填埋场直杆桉净光合速率日变化呈单峰曲线,无明显"午休"现象,其变化趋势与蒸腾速率、气孔导度的大体相同。对照的净光合速率、气孔导度、蒸腾速率与填埋场的变化趋势相似,但变化幅度较少。在自然条件下,填埋场直杆桉的净光合速率和蒸腾速率仍明显高于呼马山对照的。     

Site-selection bias and apparent population declines in long-term studies

Detecting population declines is a critical task for conservation biology. Logistical difficulties and the spatiotemporal variability of populations make estimation of population declines difficult. For statistical reasons, estimates of population decline may be biased when study sites are chosen based on abundance of the focal species. In this situation, apparent population declines are likely to be detected even if there is no decline. This site-selection bias is mentioned in the literature but is not well known. We used simulations and real population data to examine the effects of site-selection biases on inferences about population trends. We used a left-censoring method to detect population-size patterns consistent with site-selection bias. The site-selection bias is an important consideration for conservation biologists, and we offer suggestions for minimizing or mitigating it in study design and analysis. Article impact statement: Estimates of population declines are biased if studies begin in large populations, and time-series data show a signature of such an effect.     

大中型卫生填埋场臭气治理探索与实践

填埋场臭气的治理一直是阻碍大中型卫生填埋场发展的难题,以北京市朝阳区高安屯卫生填埋场为例,分析了填埋场臭气产生的原因,介绍了其在渗沥液臭气治理、填埋气臭气治理以及空间除臭三方面的实践经验以及结果,这些对其他卫生填埋场的臭气治理有很好的借鉴作用。     

Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests

Forestry science has a long tradition of studying the relationship between stand productivity and abiotic and biotic site characteristics, such as climate, topography, soil and vegetation. Many of the early site quality modelling studies related site index to environmental variables using basic statistical methods such as linear regression. Because most ecological variables show a typical non-linear course and a non-constant variance distribution, a large fraction of the variation remained unexplained by these linear models. More recently, the development of more advanced non-parametric and machine learning methods provided opportunities to overcome these limitations. Nevertheless, these methods also have drawbacks. Due to their increasing complexity they are not only more difficult to implement and interpret, but also more vulnerable to overfitting. Especially in a context of regionalisation, this may prove to be problematic. Although many non-parametric and machine learning methods are increasingly used in applications related to forest site quality assessment, their predictive performance has only been assessed for a limited number of methods and ecosystems.In this study, five different modelling techniques are compared and evaluated, i.e. multiple linear regression (MLR), classification and regression trees (CART), boosted regression trees (BRT), generalized additive models (GAM), and artificial neural networks (ANN). Each method is used to model site index of homogeneous stands of three important tree species of the Taurus Mountains (Turkey): Pinus brutia, Pinus nigra and Cedrus libani. Site index is related to soil, vegetation and topographical variables, which are available for 167 sample plots covering all important environmental gradients in the research area. The five techniques are compared in a multi-criteria decision analysis in which different model performance measures, ecological interpretability and user-friendliness are considered as criteria.When combining these criteria, in most cases GAM is found to outperform all other techniques for modelling site index for the three species. BRT is a good alternative in case the ecological interpretability of the technique is of higher importance. When user-friendliness is more important MLR and CART are the preferred alternatives. Despite its good predictive performance, ANN is penalized for its complex, non-transparent models and big training effort.     

北京市非正规垃圾填埋场垃圾成分特性

通过北京市3处典型非正规垃圾填埋场与1处正规垃圾卫生填埋场对比研究,结果表明,非正规垃圾填埋场与正规垃圾填埋场陈腐垃圾物理组成相近,但非正规垃圾填埋场有机物含量更低,同时垃圾分布不均匀;以建筑渣土为主的区域有机质含量一般低于5%;以生活垃圾为主的区域有机质含量与正规垃圾场相近,一般高于10%,内部最高温度可达42℃左右。     

上海某地铁站黑碳浓度水平及个体暴露特征

基于对职业环境空气污染物的个体暴露风险关注,在上海某地铁站进行了ρ(黑碳)的连续定点(新风井和车辆控制室)监测;同时对地铁工作人员进行个体黑碳暴露采样,并与定点监测的ρ(黑碳)比较,探讨个体采样在黑碳暴露研究中的作用. 结果表明:某地铁站新风井处ρ(黑碳)与ρ(NO₂)呈显著相关(R=0.75,P<0.05),而与ρ(PM₁₀)无显著相关性(R=0.43,P>0.1);由ρ(黑碳)日变化及其在工作日和休息日的差异可知,地铁站内ρ(黑碳)可能与室外机动车尾气排放相关;与定点监测结果不同,个体黑碳暴露浓度波动范围大,出现了未在定点监测中观测到的极高值,并且个体黑碳暴露浓度的四分位差值(IQR)是定点监测结果的2倍;尽管车控室内平均个体黑碳暴露浓度较低,但由于个体72%的工作时间是在车控室内度过的,因此车控室的个体黑碳暴露剂量比非车控室环境高.      

污染场地河道底泥浸出液对斑马鱼胚胎的毒性效应

为了评价某污染场地河道底泥对水生生物的毒性效应及其潜在生态风险,以斑马鱼(Brachydanio rerio)为受试生物,进行了河道底泥浸出液对斑马鱼胚胎的发育毒性实验。结果表明,5种底泥浸出液(A1、A2、A3、A4、A5)对斑马鱼胚胎的发育均有毒性效应,浸出液对斑马鱼胚胎的死亡率存在一定的剂量-效应关系,随着浸出液体积分数的增加,死亡率显著上升。浸出液对胚胎孵化抑制作用明显,随着浸出液体积分数的增加,孵化率显著下降。且能引起斑马鱼胚胎多种中毒症状,如水肿,鱼体弯曲,发育不全等异常现象,表明该段河道底泥存在潜在的生态风险。因此,在后期的污染场地河道整治中,需对河道底泥进行挖掘清理和无害化处理。     

土壤环境标准值及制订研究:服务于管理需求的土壤环境标准值框架体系

环境标准是实施环境管理的重要依据。我国现行土壤环境质量标准(GB 15618—1995)已不能满足土壤环境管理的实际需求,研究提出我国适宜的土壤环境标准值体系显得十分迫切和必要。结合国家关于"严格控制新增土壤污染"、"确定土壤环境保护优先区域"、"强化被污染土壤的环境风险控制"和"开展土壤污染治理与修复"的土壤环境政策,分析了我国土壤环境保护和综合治理重点任务及对土壤环境标准值的迫切需求,调研综述了发达国家和地区土壤环境法规及标准值体系现状和经验,初步提出了包括土壤环境质量标准、土壤环境风险管控标准和针对特定污染土壤的治理修复标准的标准值体系,提出了针对"老污染"和"新污染"土壤分别建立不同的土壤环境监管制度,该研究可望为完善和建立我国土壤环境标准值框架体系提供参考。     

层次分析法在垃圾填埋场选址中的应用--以哈尔滨市为例

运用层次分析法对哈尔滨市市区5个简易卫生填埋场进行综合适宜性评价,确定这5处卫生填埋场是否适宜继续堆放垃圾,为下一步选择适宜的垃圾堆放场的新址提供科学依据.研究结果表明,5处垃圾填埋场的适宜性评价的得分值为Z王岗=75.72,Z和平=83.00,Z程家岗=65.57,Z哈东=62.33,Z柳树林=83.22.最后确定柳树林垃圾堆放场是最适宜的垃圾堆放场地.