贡嘎山本底站大气中VOCs的研究

为研究中国西南地区大气中挥发性有机物（VOCs）区域性本底浓度和变化特征,利用不锈钢钢瓶采样、三步冷冻浓缩进样-气相色谱/质谱联用技术（GC/MS）,测定了贡嘎山大气本底站大气中的VOCs组成、浓度及季节变化,并利用PCA（principal component analysis）受体模型对大气中VOCs来源进行了初步分析.结果表明,贡嘎山地区TVOCs和NMHCs的年平均浓度（体积分数）分别为9.40×10-9±4.55×10-9和7.73×10-9±4.43×10-9,且两者的最高和最低浓度都出现在同一次采样.在TVOCs中,芳香烃所占比例最大,为37.3%,烷烃（30.0%）和卤代烃（19.8%）次之,烯烃的比例最低,为12.9%.通过PCA受体模型分析发现,贡嘎山地区大气中VOCs的主要来源可以归结为交通源、生物源和燃烧源.贡嘎山地区大气中TVOCs呈现明显的季节变化,变化特征为秋季〉冬季〉春季〉夏季,秋季和冬季大气中的TVOCs浓度分别极显著（P〈0.01）和显著地高于夏季（P〈0.05）,由于光化学性质的差异,4种类型的VOCs季节变化也呈现出不同的特征.异戊二烯是生物源的重要排放物,其排放速率与大气温度呈指数相关,在20℃以上随着温度的升高排放速率明显增强,其最高和最低值分别出现在夏季的下午和冬季的上午.与其他地区的研究结果相比,贡嘎山地区TVOCs的排放处于中等水平,有着明显的本底站排放特征.     

Characteristics of indoor/outdoor PM2.5 and elemental components in generic urban, roadside and industrial plant areas of Guangzhou City, China

Quantitative information on mass concentrations and other characteristics, such as spatial distribution, seasonal variation, indoor/outdoor （I/O） ratio, correlations and sources, of indoor and outdoor PM2.5 and elemental components in Guangzhou City were provided. Mass concentration of PM2.5 and elemental components were determined by standard weight method and proton-induced X-ray emission （PIXE） method. 18 elements were detected, the results showed positive results. Average indoor and outdoor PM2.5 concentrations in nine sites were in the range of 67.7-74.5μg/m^3 for summer period, and 109.9-123.7 μg/m^3 for winter period, respectively. The sum of 18 elements average concentrations were 5362.6-5533.4 ng/m^3 for summer period, and 8416.8-8900.6 ng/m^3 for winter period, respectively. Average concentrations of PM2.5 and element components showed obvious spatial characteristic, that the concentrations in roadside area and in industrial plant area were higher than those in generic urban area. An obvious seasonal variation characteristic was found for PM2.5 and elemental components, that the concentrations in winter were higher than that in summer. The I/O ratio of PM2.5 and some elemental components presented larger than 1 sometimes. According to indoor/outdoor correlation of PM2.5 and element concentrations, it was found that there were often good relationships between indoor and outdoor concentrations. Enrichment factors were calculated to evaluate anthropogenic versus natural elements sources.     

BDE-28对斑马鱼核受体介导的内分泌干扰效应研究

2,4,4’-三溴联苯醚(BDE-28)在环境中普遍存在,且在长江流域多种水生生物中检出。目前,国内外对高溴代PBDEs(如BDE-47、BDE-99等)的水生脊椎动物内分泌干扰效应报道较多,而BDE-28的有关研究则相对较少。将斑马鱼胚胎暴露于2、20和200μg·L~(-1)的BDE-28后,借助q-RT-PCR方法对幼鱼8个重要受体包括雄激素受体(AR)、甲状腺激素受体(TR)、芳香烃受体(AhR)、雌激素受体(ER)、糖皮质激素受体(GR)、孕烷X受体(PXR)、盐皮质激素受体(MR)和过氧化物酶体增殖物激活受体(PPAR)相关基因的转录水平进行了研究。结果表明,BDE-28暴露可导致AR、TR和Ah R的基因下调,其中核心受体AR和TR在低中高3种浓度下的下调倍数分别为3.03、2.64、10.10和2.21、2.18、2.31,芳香烃受体基因2(ahr2)在暴露于2和20μg·L~(-1)的BDE-28后,下调倍数分别为12.65和9.23,而雌激素受体(er1)基因在低中高浓度显著上调,上调倍数分别为12.29、12.67和15.87,雌激素受体(er2a)基因在2和20μg·L~(-1)BDE-28下的上调倍数分别为10.83和17.19。进一步采用分子对接和分子动力学模拟的方法研究BDE-28与AR、TR、Ah R和ER之间的相互作用。结果显示,BDE-28与这些受体通过疏水和氢键等相互作用稳定结合,动力学模拟后骨架原子的均方根偏差(RMSD)在5 ns后较稳定。由此可知,BDE-28通过AR、TR、Ah R和ER受体介导产生内分泌干扰效应。     

Determining Decision Thresholds and Evaluating Indicators when Conservation Status is Measured as a Continuum

Categorization of the status of populations, species, and ecosystems underpins most conservation activities. Status is often based on how a system's current indicator value (e.g., change in abundance) relates to some threshold of conservation concern. Receiver operating characteristic (ROC) curves can be used to quantify the statistical reliability of indicators of conservation status and evaluate trade‐offs between correct (true positive) and incorrect (false positive) classifications across a range of decision thresholds. However, ROC curves assume a discrete, binary relationship between an indicator and the conservation status it is meant to track, which is a simplification of the more realistic continuum of conservation status, and may limit the applicability of ROC curves in conservation science. We describe a modified ROC curve that treats conservation status as a continuum rather than a discrete state. We explored the influence of this continuum and typical sources of variation in abundance that can lead to classification errors (i.e., random variation and measurement error) on the true and false positive rates corresponding to varying decision thresholds and the reliability of change in abundance as an indicator of conservation status, respectively. We applied our modified ROC approach to an indicator of endangerment in Pacific salmon (Oncorhynchus nerka) (i.e., percent decline in geometric mean abundance) and an indicator of marine ecosystem structure and function (i.e., detritivore biomass). Failure to treat conservation status as a continuum when choosing thresholds for indicators resulted in the misidentification of trade‐offs between true and false positive rates and the overestimation of an indicator's reliability. We argue for treating conservation status as a continuum when ROC curves are used to evaluate decision thresholds in indicators for the assessment of conservation status. Determinación de Umbrales de Decisiones y Evaluación delos Indicadores cuando se Mide el Estado de de Conservación como un Continuo     

Adaptive capacity and climate change: the role of community opinion leaders

The contribution of the informal community sector to the development of collective response strategies to socioecological change is not well researched. In this article, we examine the role of community opinion leaders in developing and mobilising stocks of adaptive capacity. In so doing, we reveal a largely unexplored mechanism for building on latent social capital and associated networks that have the potential to transcend local-scale efforts – an enduring question in climate change adaptation and other cross-scalar sustainability issues. Participants drawn from diverse spheres of community activity in the Sunshine Coast, Australia, were interviewed about their strategies for influencing their community objectives and the degree to which they have engaged with responding to climate change. The results show community opinion leaders to be politically engaged through rich bridging connections with other community organisations, and vertically with policy-makers at local, state, national and international levels. Despite this latent potential, the majority of community opinion leaders interviewed were not strategically engaged with responding to climate change. This finding suggests that more work is needed to connect networks knowledgeable about projected climate change impacts with local networks of community opinion leaders. Attention to the type of community-based strategies considered effective and appropriate by community opinion leaders and their organisations also suggests avenues for policy-makers to facilitate community engagement in responding to climate change across sectors likely to be affected by its impacts. Opportunities to extend understanding of adaptive capacity within the community sector through further research are also suggested.     

基于APCS-MLR和PMF模型的煤矸山周边耕地土壤重金属污染特征及源解析

以重庆市南川区某煤矸山周边耕地土壤为研究对象,运用内梅罗指数法和地累积指数法分析土壤重金属污染水平和分布特征,并采用绝对因子得分-多元线性回归(APCS-MLR)和正定矩阵因子分解(PMF)模型,探析研究区土壤重金属来源及其贡献率.结果表明,下游区土壤中8项重金属均值含量均高于上游区,其中Cu、 Ni和Zn含量显著高于上游区(P<0.05).内梅罗综合污染指数表现为：下游区(1.22)>上游区(0.95),重金属污染程度由大到小表现为：Cd>Cu>Hg、 As、 Pb、 Cr、 Ni和Zn.地累积指数由大到小表现为：Cd>As>Cu=Hg>Ni>Zn=Cr>Pb.源解析表明,研究区土壤中Cu、 Ni和Zn主要受煤矸山堆存影响,APCS-MLR模型的贡献率分别为49.8%、 94.5%和73.2%,PMF模型的贡献率分别为62.8%、 62.2%和63.1%; Cd、 Hg和As主要受农业和交通混合源影响,APCS-MLR模型的贡献率分别为49.8%、 94.5%和73.2%,PMF模型的贡献率分别为62.8%、 62.2%和63.1...     

PCA-APCS-MLR和地统计学的典型农田土壤重金属来源解析

人类活动往往会增加表层土壤重金属含量,进而影响了区域土壤重金属的精确定量与评估.为系统研究浙江省西部石煤矿山周边典型农田土壤重金属污染源的空间分布特征及其贡献率,采集并分析了耕地表层土壤样品和农产品中Cd、 Hg、 As、 Cu、 Zn和Ni等重金属,重点探讨各元素地球化学特征并对农产品进行生态风险评价.采用相关性分析、主成分分析(PCA)和绝对主成分得分-多元线性回归受体模型(APCS-MLR),解析了该地区土壤中重金属污染的来源和源贡献率,并采用地统计学分析法对土壤中Cd、 As的空间分布特点进行了分析.结果表明,研究区内6种土壤重金属(Cd、 Hg、 As、 Cu、 Zn和Ni)含量都超过风险筛选值,其中Cd和As含量超过风险管制值,其超标率分别为36.11%和0.69%,而农产品中Cd也存在严重超标.通过分析认为研究区土壤重金属污染源主要有2个：源1(Cd、 Cu、 Zn和Ni)为矿业活动源和自然源,对Cd、 Cu、 Zn和Ni的贡献率分别为78.53%、 84.41%、 87%和89.13%;源2(Hg和As)以工业源为主,对Hg和As的贡献率分别为83.22%和82.41%...     

肇庆市一次典型污染天气的污染物来源解析

利用污染物及气象观测数据对肇庆市2018年12月17～23日大气污染过程进行了分析,采用了CMAQ-ISAM模型以及混合受体模型对本次大气污染来源进行了解析研究.结果表明,12月19～21日肇庆地区受近地面弱气压影响而形成的较为不利的污染物扩散条件,是肇庆大气污染过程的诱导因素;在本次污染发生前的清洁时段,肇庆污染主要来自于本地及清远,其贡献率分别为19. 2%和10. 7%,而受江西、湖南、湖北以及陕西等地的远距离污染物传输作用影响约为64. 5%;在污染时段,随着地面高气压场南移,肇庆地区受珠三角主要城市和粤东城市的区域传输贡献明显,肇庆、佛山、东莞、广州和惠州贡献率依次为25. 5%、14. 8%、9. 8%、9. 5%和5. 3%,河源、梅州、汕尾、揭阳、汕头和潮州这6个广东省东部城市贡献率共计13. 7%,而受福建、江西以及长江三角洲等地的远距离污染物传输作用影响约为32. 9%,且经过海上通道传输的污染物贡献更为显著.因此,输送到海面上的气溶胶颗粒经吸湿增长后回到陆地,是本次肇庆污染天气的主要成因之一.     

基于多种新型受体模型的PM2.5来源解析对比

为了解多种新型受体模型的适用性,利用正定矩阵分解/多元线性引擎2-物种比值（PMF/ME2-SR）、偏目标转换-正定矩阵分解（PTT-PMF）、正定矩阵分解（PMF）和化学质量平衡（CMB）这4种受体模型对我国北方典型城市细颗粒物(PM_2.5)数据进行同步解析并互相验证.结果发现,燃煤源（25%～26%）、扬尘源（19%～21%）、二次硝酸盐（17%～19%）、二次硫酸盐（16%）、机动车源（13%～15%）、生物质燃烧源（4%～7%）和钢铁源（1%～2%）这7种主要污染源对研究地区PM_2.5有贡献.通过比较不同模型获得的源成分谱和源贡献以及计算各源的差异系数（CD）和平均绝对误差（AAE）,发现4种模型的解析结果具有较高的一致性（平均CD值在0.6～0.7之间）,但不同模型对各污染源中组分的识别存在差异.相比于传统PMF模型,PMF/ME2-SR模型由于纳入一次源类的特征比值,能够更好地区分源谱特征较为相似的源类,如扬尘源的CD和AAE分别比PMF模型低15%和54%; PTT-PMF模型以实测一次源谱和虚拟二次源谱为约束目标,计算的二次硫...