基于小波分解和SVM的大气污染物浓度预测模型研究

针对大气污染物浓度的精准预测问题,运用小波分解将污染物浓度一维序列分解为高维信息,结合气象及污染物浓度数据,构建了基于小波分解的支持向量机预测模型.最后将模型应用于长沙市2018年PM_2.5和O_{3-8 h}的浓度预测.结果表明：①在其他参数不变的条件下,该模型在平均绝对误差（MAE）、平均绝对百分比误差（MAPE）、均方根误差（RMSE）、一致性水平（IA）和相关系数（R）指标上均优于未经小波分解的预测模型;②在考虑其他污染物对PM_2.5浓度的影响后,预测模型评价指标MAE、MAPE和RMSE分别减少了5.57%、9.91%和3.44%,有着更小的误差;③在考虑气象因素对O_{3-8 h}浓度的影响后,预测模型评价指标MAE、MAPE和RMSE分别减少了1.59%、3.54%和0.82%,同样也有更小的误差.由此可以看出,本文所提模型能够有效预测大气污染物浓度,为相关研究提供了方法参考.     

土地利用结构与空间格局对袁河水质的影响

于2018年7月和2019年1月在袁河干流及支流38个采样点采集水样,测定营养盐离子及重金属等14项水质指标.同时,采用Bioenv分析、Mantle检验与方差分解等方法,揭示土地利用结构与空间格局在子流域和缓冲区对水质变化的影响机制,并基于层次分割理论探讨不同土地利用类型的空间格局特征对水质的影响.结果表明：①袁河流域重金属污染不显著,氮、磷营养盐是水体主要污染物,水质变化具有河段差异,上游污染物浓度低于中、下游.②空间格局在在近距离缓冲区（100 m、300 m）对水质变化的解释率最高（63%）,土地利用结构在远距离缓冲区（3000 m）和子流域尺度对水质变化的解释率最高（33%）,二者交互作用在过渡带（500 m、1000 m）对水质变化的解释率最高（56%）.③在近距离缓冲区和过渡带,单一土地利用类型的空间格局对水质变化的解释能力依次为：林地 > 农田 > 建设用地;在远距离缓冲区为：农田≈林地>建设用地;在子流域依次为：农田 > 林地 > 建设用地.其中,林地的连通性特征（ENN_MN指数）、农田的边缘密度特征（ED指数）和建设用地的形状特征（LPI、LSI指数）是影响水质变化的关键特征,占各自空间格局解释率的37.8%、31.2%、53.8%.以上结果表明,土地利用结构与空间格局是驱动袁河水质变化的重要因素,加强1000 m缓冲区尺度土地利用的管理对保护流域水质具有重要意义.     

Pt-Cu/TiO2{001}纳米片用于CO2加氢制甲醇反应的研究

以高暴露{001}晶面的TiO₂纳米片为载体,利用共还原法负载0.5%的Pt和一定量的Cu得到Pt-Cu/TiO₂{001}催化剂,并在P=3.0 MPa,T=200~300℃,V（N₂）：V（H₂）：V（CO₂）=8：69：23,空速（WHSV）=3600 mL·g^-1·h^-1反应条件下评价了催化剂催化CO₂加氢制甲醇的反应性能.XRD、XPS、EPR和CO₂-TPD等的表征表明,与催化剂Cu/TiO₂相比,引入Pt后,催化剂由于金属Pt的电子促进作用使负载的金属与载体之间的相互作用更强,进而有利于稳定Cu颗粒尺寸且载体形成了更多缺陷（如氧空位、Ti³⁺）.因此,Pt-Cu/TiO₂{001}催化剂的金属与载体界面上的活性位点更多,从而表现出更好的CO₂活化能力和甲醇生成性能.     

喀斯特流域水化学特征及水-岩作用分析——以后寨河流域为例

本文选取后寨流域作为研究对象,基于对水体中主要离子的主成分分析和离子比值分析,研究丰枯期水化学特征及水-岩作用程度。研究表明,水体中各离子的主成分荷载值和站点得分能够辨识流域内主要水化学成分及水-岩(T_2g~2、T_2g~3)作用特征,丰水期主成分反映碳酸盐岩可溶性和水动力条件组合的影响,枯水期主成分反映蒸发岩和水动力条件组合的影响。水流作用强的石灰岩地区,管道发育,水流变化迅速,水体中离子浓度低。随着白云岩含量增加或水流作用减弱,水体中离子含量增大。枯水期从上游至中下游水流作用减弱,蒸发作用增强。     

石墨烯修饰碳毡电极与微生物相互作用过程中的电化学特征

在希瓦氏菌(Shewanella putrefaciens)呼吸驱动下,成功制备了生源性还原态的氧化石墨烯(r-GO)修饰的碳毡电极,进一步研究了r-GO修饰碳毡电极与微生物相互作用的电化学特征.结果表明:经r-GO修饰的碳毡电极与微生物的相互作用程度得到显著提升,这主要是由于修饰后电极的扩散内阻(R_(dif))得到快速降低的结果.将r-GO修饰后的碳毡电极作为阳极应用于微生物燃料电池(MFC)中,经微生物呼吸驱动下的石墨烯修饰电极,由于R_(dif)降低导致电极的电化学活性增强,使得电极和微生物相互作用程度得到提升,从而缩短了MFC启动时间,提高了MFC的产电能力.研究进一步表明,r-GO对电极的修饰,调控了对电极电化学活性及生源性电子向电极表面的传递过程.     

三峡工程运行对洞庭湖水环境及富营养化风险影响评述

洞庭湖的江湖关系受自然因素及人为因素影响,其江湖关系的变化影响洞庭湖水文、水质、水环境容量和营养状态.近年来洞庭湖的富营养化指数不断升高,但水环境变化及富营养化风险变化的原因错综复杂,如何区分三峡工程运行等人类活动和气候变化等自然因素对洞庭湖水环境、富营养化风险的影响是洞庭湖江湖关系研究的难点.根据近年来洞庭湖江湖关系、水环境或富营养化水平的相关研究,对洞庭湖由于三峡工程运行导致的江湖关系变化,以及该变化对洞庭湖水环境、富营养化风险的影响的研究进展进行系统梳理、分析、总结和评述.现阶段研究得出,三峡工程运行导致的江湖关系变化影响洞庭湖不同时段的水环境容量,在一定程度上改善了枯水期和泄水期洞庭湖水质;三峡工程运行后洞庭湖水体中的ρ（TP）有所降低,但洞庭湖湖体ρ（TN）、ρ（TP）仍相对较高,已能够满足藻类生长的需求,水华发生的制约条件是水体透明度和水流流速;江湖关系变化后洞庭湖富营养化风险增大的时段是蓄水期,其他时段富营养化风险减小;流速较低的东洞庭湖湖滩区、蓄水期流速降低明显的南洞庭湖滩区水华发生的风险增大,为水华发生的敏感区域.大型枢纽工程对通江湖泊污染物迁移转化影响的机理分析、对通江湖泊水环境影响的模拟及相关参数研究、对湖泊水环境及富营养化风险的长期影响等方面的研究还有待进一步完善.      

行为科学关于安全控制的研究述评与未来研究展望

从行为科学的视角,探讨人的因素在事故发生过程中的作用,取得了许多重要的进展。笔者从个体因素、群体因素、组织因素以及跨水平的多因素交互作用等4个方面总结了行为科学关于安全控制的相关研究,分析了各种因素对安全绩效的影响。在此基础上,提出一个包含个体、群体和组织因素在内的整合性事故发生路径模型,指出行为科学关于安全控制的未来研究方向,尤其是需要深入揭示一些高阶变量,如领导、组织学习等对安全生产的影响机制,以及采用跨层次的方法来探讨组织因素、群体因素和个体因素在安全生产过程中的交互作用。     

Effects of Human Population Density and Proximity to Markets on Coral Reef Fishes Vulnerable to Extinction by Fishing

Coral reef fisheries are crucial to the livelihoods of tens of millions of people; yet, widespread habitat degradation and unsustainable fishing are causing severe depletion of stocks of reef fish. Understanding how social and economic factors, such as human population density, access to external markets, and modernization interact with fishing and habitat degradation to affect fish stocks is vital to sustainable management of coral reef fisheries. We used fish survey data, national social and economic data, and path analyses to assess whether these factors explain variation in biomass of coral reef fishes among 25 sites in Solomon Islands. We categorized fishes into 3 groups on the basis of life‐history characteristics associated with vulnerability to extinction by fishing (high, medium, and low vulnerability). The biomass of fish with low vulnerability was positively related to habitat condition. The biomass of fishes with high vulnerability was negatively related to fishing conducted with efficient gear. Use of efficient gear, in turn, was strongly and positively related to both population density and market proximity. This result suggests local population pressure and external markets have additive negative effects on vulnerable reef fish. Biomass of the fish of medium vulnerability was not explained by fishing intensity or habitat condition, which suggests these species may be relatively resilient to both habitat degradation and fishing. Efectos de la Densidad de Poblaciones Humanas y la Proximidad del Mercado sobre Peces de Arrecifes de Coral Vulnerables a la Extinción     

Assessment of Management to Mitigate Anthropogenic Effects on Large Whales

United States and Canadian governments have responded to legal requirements to reduce human‐induced whale mortality via vessel strikes and entanglement in fishing gear by implementing a suite of regulatory actions. We analyzed the spatial and temporal patterns of mortality of large whales in the Northwest Atlantic (23.5°N to 48.0°N), 1970 through 2009, in the context of management changes. We used a multinomial logistic model fitted by maximum likelihood to detect trends in cause‐specific mortalities with time. We compared the number of human‐caused mortalities with U.S. federally established levels of potential biological removal (i.e., species‐specific sustainable human‐caused mortality). From 1970 through 2009, 1762 mortalities (all known) and serious injuries (likely fatal) involved 8 species of large whales. We determined cause of death for 43% of all mortalities; of those, 67% (502) resulted from human interactions. Entanglement in fishing gear was the primary cause of death across all species (n = 323), followed by natural causes (n = 248) and vessel strikes (n = 171). Established sustainable levels of mortality were consistently exceeded in 2 species by up to 650%. Probabilities of entanglement and vessel‐strike mortality increased significantly from 1990 through 2009. There was no significant change in the local intensity of all or vessel‐strike mortalities before and after 2003, the year after which numerous mitigation efforts were enacted. So far, regulatory efforts have not reduced the lethal effects of human activities to large whales on a population‐range basis, although we do not exclude the possibility of success of targeted measures for specific local habitats that were not within the resolution of our analyses. It is unclear how shortfalls in management design or compliance relate to our findings. Analyses such as the one we conducted are crucial in critically evaluating wildlife‐management decisions. The results of these analyses can provide managers with direction for modifying regulated measures and can be applied globally to mortality‐driven conservation issues. Evaluación del Manejo para Mitigar Efectos Antropogénicos sobre Ballenas Mayores     

Which forcing factors fit? Using ecosystem models to investigate the relative influence of fishing and changes in primary productivity on the dynamics of marine ecosystems

Fishing mortality and primary production (or proxy for) were used to drive the dynamics of fish assemblages in 9 trophodynamic models of contrasting marine ecosystems. Historical trends in abundance were reconstructed by fitting model predictions to observations from stock assessments and fisheries independent survey data. The model fitting exercise derives values for otherwise unknown parameters that specify the relative strength of trophic interactions and, in some instances, a time series anomaly for changes in primary production. We measured how much better or worse were model predictions when bottom-up forcing by primary production were added to top-down forcing by fishing. Searching for cross system patterns, the relative contribution of fishing and changes in primary production, mediated through trophic interactions, are evaluated for the ecosystems as a whole and for selected similar species in different ecosystems. The analysis provides a simple qualitative way to explain which forcing factors have most influence on modeled dynamics. Both fishing and primary production forcing were required to obtain the best model fits to data. Fishing effects more strongly influenced 6 of 9 of the ecosystems, but primary production was more often found to be the main factor influencing the selected pelagic and demersal fish stock trends. Examination of sensitivity to ecological and model parameters suggests that the results are the product of complex food-web interactions rather than simple deterministic responses of the models.