PIXGRO: A model for simulating the ecosystem CO2 exchange and growth of spring barley

A model, PIXGRO, developed by coupling a canopy flux sub-model (PROXEL_NEE; PROcess-based piXEL Net Ecosystem CO₂ Exchange) to a vegetation structure submodel (CGRO), for simulating both net ecosystem CO₂ exchange (NEE) and growth of spring barley is described. PIXGRO is an extension of the stand-level CO₂ and H₂O-flux model PROXEL_NEE, that simulates the NEE on a process basis, but goes further to include the dry matter production, partitioning, and crop development for spring barley. Dry matter partitioned to the leaf was converted to leaf area index (LAI) using relationships for the specific leaf area (SLA). The canopy flux component, PROXEL_NEE was calibrated using information from the literature on C3 plants and was tested using CO₂ flux data from an eddy-covariance (EC) method in Finland with long-term observations. The growth component (CGRO) was calibrated using data from the literature on spring barley as well as data from the Finland site. It was then validated against field data from two sites in Germany and partly via the use of MODIS remotely sensed LAI from the Finland site.Both the diurnal and the seasonal patterns of gross CO₂ uptake were very well simulated (R² = 0.92). A slight seasonal bias may be attributed to leaf ageing. Crop growth was also well simulated; simulated dry matter agreed with field observed data from Germany (R² = 0.90). For LAI, the agreement between the simulated and observed was good (R² = 0.80), giving an indication that functions describing the conversion of fixed CO₂ to dry matter and the subsequent partitioning leaf dry matter and LAI simulation were robust and provided reliable estimates.The MODIS LAI at a resolution of 1000 m agreed poorly (R² = 0.45) with the PIXGRO simulated LAI and the observed LAI at the Finland site in 2001. We attributed this to the coarse resolution of the image and/or the small size of the barley field (about 17 ha or 0.25 km²) at the Finland site. By deriving a regression relation between the observed LAI and NDVI from a higher resolution MODIS (500 m resolution), the MODIS-recalculated LAI agreed better with the PIXGRO-simulated LAI (R² = 0.86).PIXGRO provides a prototype model bridging the disciplines of plant physiology, crop modeling and remote sensing, for use in a spatial context in evaluating carbon balances and plant growth at stand level, landscape, regional, and with some care, continental scales. Since almost 50% of the European land surface is covered by crops, such a model is needed for the dynamic estimation of LAI and NEE of croplands.     

Modification of an ecosystem model for filling medium-sized gaps in tower-based estimates of net ecosystem productivity

Gap filling of flux data is necessary to assist with periodic interruptions in the measurement data stream. The gap-filling model (GFM), first described in Xing et al. [Xing, Z., Bourque, C.P.-A., Meng, F.-R., Zha, T.-S., Cox, R.M., Swift, E., 2007. A simple net ecosystem productivity model for gap filling of tower-based fluxes: an extension of Landsberg's equation with modifications to the light interception term. Ecol. Model. 206, 250–262], was modified to account for the day-to-day control of net ecosystem productivity (NEP) by incorporating air and soil temperature as new controlling variables in the calculation of NEP. To account for the multiple-phase influences of air and soil temperature on plant growth we model ecosystem respiration as a function of soil and canopy respiration. The paper presents model development in an incremental fashion in order to quantify the contribution of individual model enhancements to the prediction of NEP during periods when air and soil temperature variations are important.     

Inter-annual variability of ecosystem production in boreal jack pine forests (1975-2004) estimated from tree-ring data using CBM-CFS3

We describe and apply a method of using tree-ring data and an ecosystem model to reconstruct past annual rates of ecosystem production. Annual data on merchantable wood volume increment and mortality obtained by dendrochronological stand reconstruction were used as input to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate net ecosystem production (NEP), net primary production (NPP), and heterotrophic respiration (Rh) annually from 1975 to 2004 at 10 boreal jack pine (Pinus banksiana Lamb.) stands in Saskatchewan and Manitoba, Canada. From 1975 (when sites aged 41-60 years) to 2004 (when they aged 70-89 years), all sites were moderate C sinks except during some warmer than average years where estimated Rh increased. Across all sites and years, estimated annual NEP averaged 57 g Cm⁻² yr⁻¹ (range −31 to 176 g Cm⁻² yr⁻¹), NPP 244 g Cm⁻² yr⁻¹ (147-376 g Cm⁻² yr⁻¹), and Rh 187 g Cm⁻² yr⁻¹ (124-270 g Cm⁻² yr⁻¹). Across all sites, NPP was related to stand age and density, which are proxies for successional changes in leaf area. Regionally, warm spring temperature increased NPP and defoliation by jack pine budworm 1 year previously reduced NPP. Our estimates of NPP, Rh, and NEP were plausible when compared to regional eddy covariance and carbon stock measurements. Inter-annual variability in ecosystem productivity contributes uncertainty to inventory-based assessments of regional forest C budgets that use yield curves predicting averaged growth over time. Our method could expand the spatial and temporal coverage of annual forest productivity estimates, providing additional data for the development of empirical models accounting for factors not presently considered by these models.     

Evaluating CO2 reduction strategies in the US

We constructed a model to simulate emissions of CO₂ from electricity generation in the US and, using the model, we developed 20-year projections of emissions under various regulatory scenarios.     

Modeling the vegetation-atmosphere carbon dioxide and water vapor interactions along a controlled CO2 gradient

Ecosystem functioning is intimately linked to its physical environment by complex two-way interactions. These two-way interactions arise because vegetation both responds to the external environment and actively regulates its micro-environment. By altering stomatal aperture, and therefore the transpiration rate, plants modify soil moisture and atmospheric humidity and these same physical variables, in return, modify stomatal conductance. Relationships between biotic and abiotic components are particularly strong in closed, managed environments such as greenhouses and growth chambers, which are used extensively to investigate ecosystem responses to climatic drivers. Model-assisted designs that account for the physiological dynamics governing two-way interactions between biotic and abiotic components are absent from many ecological studies. Here, a general model of the vegetation-atmosphere system in closed environments is proposed. The model accounts for the linked carbon-water physiology, the turbulent transport processes, and the energy and radiative transfer within the vegetation. Leaf gas exchange is modeled using a carbon gain optimization approach that is coupled to leaf energy balance. The turbulent transport within the canopy is modeled in two-dimensions using first-order closure principles. The model is applied to the Lysimeter CO₂ Gradient (LYCOG) facility, wherein a continuous gradient of atmospheric CO₂ is maintained on grassland assemblages using an elongated chamber where the micro-climate is regulated by variation in air flow rates. The model is employed to investigate how species composition, climatic conditions, and the imposed air flow rate affect the CO₂ concentration gradient within the LYCOG and the canopy micro-climate. The sensitivity of the model to key physiological and climatic parameters allows it to be used not only to manage current experiments, but also to formulate novel ecological hypotheses (e.g., by modeling climatic regimes not currently employed in LYCOG) and suggest alternative experimental designs and operational strategies for such facilities.     

Identification of important factors for water vapor flux and CO2 exchange in a cropland

Water vapor flux and carbon dioxide (CO₂) exchange in croplands are crucial to water and carbon cycle research as well as to global warming evaluation. In this study, a standard three-layer feed-forward back propagation neural network technique associated with the Bayesian technique of automatic relevance determination (ARD) was employed to investigate water vapor and CO₂ exchange between the canopy of summer maize and atmosphere in responses to variations of environmental and physiological factors. These factors, namely the photosynthetically active radiation (PAR), air temperature (T), vapor pressure deficient (VPD), leaf-area index (LAI), soil water content in root zone (W), and friction velocity (U*), were used as inputs in neural network analysis. Results showed that PAR, VPD, T and LAI were the primary factors regulating both water vapor and CO₂ fluxes with VPD and W more critical to water vapor flux and PAR and T more crucial to CO₂ exchange. Furthermore, two time variables “day of the year (DOY)” and “time of the day (TOD)” could also improve the simulation results of neural network analysis. The important factors identified by the neural network technique used in this study were in the order of PAR > T > VPD > LAI > U* > TOD for water vapor flux and in the order of VPD > W > LAI > T > PAR > DOY for CO₂ exchange. This study suggests that neural network technique associated with ARD could be a useful tool for identifying important factors regulating water vapor and CO₂ fluxes in terrestrial ecosystem.     

Modelling concentrations of airborne primary and secondary PM10 and PM2.5 with the BelEUROS-model in Belgium

The Eulerian Chemistry-Transport Model BelEUROS was used to calculate the concentrations of airborne PM₁₀ and PM_2.5 over Europe. Both primary as well as secondary particulate matter in the respirable size-range was taken into account. Especially PM_2.5 aerosols are often formed in the atmosphere from gaseous precursor compounds. Comprehensive computer codes for the calculation of gas phase chemical reactions and thermodynamic equilibria between compounds in the gas-phase and the particulate phase had been implemented into the BelEUROS-model. Calculated concentrations of PM₁₀ and PM_2.5 are compared to observations, including both the spatial and daily, temporal distribution of particulate matter in Belgium for certain monitoring locations and periods. The concentrations of the secondary compounds ammonium, nitrate and sulfate have also been compared to observed values. BelEUROS was found to reproduce the observed concentrations rather well. The model was applied to assess the contribution of emissions derived from the sector agriculture in Flanders, the northern part of Belgium, to PM₁₀- and PM_2.5-concentrations. The results demonstrate the importance of ammonia emissions in the formation of secondary particulate matter. Hence, future European emission abatement policy should consider more the role of ammonia in the formation of secondary particles.     

过氧化氢和一氧化氮在小球藻抗阿特拉津胁迫中的作用

过氧化氢(H_2O_2)和一氧化氮(NO)作为信号分子,可调节植物生长、发育以及应对外源性胁迫。利用过氧化氢酶(CAT)以及NO清除剂(PTIO),研究了除草剂阿特拉津(atrazine,100μg·L~(-1))影响小球藻生长的机理,并分析内源性H_2O_2和NO在小球藻抗除草剂胁迫中的作用。研究结果表明,阿特拉津在诱发小球藻细胞死亡的过程中,不同程度促发了H_2O_2和NO生成;外源CAT可通过清除H_2O_2和诱导NO来缓解阿特拉津对小球藻的生长抑制;PTIO与阿特拉津的联合实验进一步证实,小球藻体内的NO诱导与H_2O_2的爆发无关,它们之间的合成没有相关性。因此,除草剂阿特拉津主要通过诱导小球藻体内的H_2O_2爆发来破坏藻细胞,抑制其生长,与NO的信号传递无关。     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.     

Modeling seasonal course of carbon fluxes and evapotranspiration in response to low temperature and moisture in a boreal Scots pine ecosystem

Environmental conditions act above and below ground, and regulate carbon fluxes and evapotranspiration. The productivity of boreal forest ecosystems is strongly governed by low temperature and moisture conditions, but the understanding of various feedbacks between vegetation and environmental conditions is still unclear. In order to quantify the seasonal responses of vegetation to environmental factors, the seasonality of carbon and heat fluxes and the corresponding responses for temperature and moisture in air and soil were simulated by merging a process-based model (CoupModel) with detailed measurements representing various components of a forest ecosystem in Hyytiälä, southern Finland. The uncertainties in parameters, model assumptions, and measurements were identified by generalized likelihood uncertainty estimation (GLUE). Seasonal and diurnal courses of sensible and latent heat fluxes and net ecosystem exchange (NEE) of CO₂ were successfully simulated for two contrasting years. Moreover, systematic increases in efficiency of photosynthesis, water uptake, and decomposition occurred from spring to summer, demonstrating the strong coupling between processes. Evapotranspiration and NEE flux both showed a strong response to soil temperature conditions via different direct and indirect ecosystem mechanisms. The rate of photosynthesis was strongly correlated with the corresponding water uptake response and the light use efficiency. With the present data and model assumptions, it was not possible to precisely distinguish the various regulating ecosystem mechanisms. Our approach proved robust for modeling the seasonal course of carbon fluxes and evapotranspiration by combining different independent measurements. It will be highly interesting to continue using long-term series data and to make additional tests of optional stomatal conductance models in order to improve our understanding of the boreal forest ecosystem in response to climate variability and environmental conditions.     

地质封存CO_2泄漏对蚯蚓的毒性效应

二氧化碳捕集与封存技术(CO_2 capture and storage, CCS)是当前国际上公认的CO_2减排的有效措施,但封存在地下的CO_2仍然因为各种不稳定因素存在泄漏风险,对土壤环境及土壤生态系统产生威胁。选择赤子爱胜蚓为研究对象,通过模拟高浓度CO_2对蚯蚓形态与生理变化的影响,探究CCS泄漏所产生的土壤高浓度CO_2对蚯蚓的毒性效应。研究表明,土壤高浓度CO_2使蚯蚓出现生殖环带肿大、尾部串珠以及断尾等外部形态变化,皮肤和刚毛受到损伤并且表皮发生褶皱等现象;随着CO_2浓度的增加以及暴露时间的延长,蚯蚓的死亡率不断增加,土壤高浓度CO_2对蚯蚓的7 d和14 d半致死浓度分别为26.39%和17.78%;蚯蚓体腔细胞溶酶体中性红保留时间(NRRT)减少。因此,蚯蚓有望作为监测CO_2泄漏的指示生物,NRRT可作为识别CO_2泄漏的敏感指标。     

纳米二氧化硅对两性生殖和孤雌生殖卤虫无节幼体毒性影响的比较研究

研究了纳米二氧化硅(Nano-SiO_2)悬浮液对美国大盐湖两性生殖型卤虫(Artemia francisana,GSL)和渤海湾孤雌生殖型卤虫(Artemia parthenogenetica,BH)无节幼体的急性毒性和抗氧化酶系统的影响。研究结果表明,Nano-SiO_2对GSL和BH无节幼体24 h-LC50分别为23.02 mg·m L~(-1)和20.96 mg·m L~(-1),属低级毒性。Nano-SiO_2降低了GSL和BH无节幼体还原型谷胱甘肽(GSH)含量,抑制了过氧化氢酶(CAT)和超氧化物歧化酶(SOD)活性,致丙二醛(MDA)含量升高,表明氧化应激反应是导致Nano-SiO_2对卤虫无节幼体致死的作用机制之一。     

A process-based model designed for filling of large data gaps in tower-based measurements of net ecosystem productivity

In this paper we present a simple hybrid gap-filling model (GFM) designed with a minimum number of parameters necessary to capture the ecological processes important for filling medium-to-large gaps in Flux data. As the model is process-based, the model has potential to be used in filling large gaps exhibiting a broad range of micro-meteorological and site conditions. The GFM performance was evaluated using “Punch hole” and extrapolation experiments based on data collected in west-central New Brunswick. These experiments indicated that the GFM is able to provide acceptable results (r² > 0.80) when >500 data points are used in model parameterization. The GFM was shown to address daytime evolution of NEP reasonably well for a wide range of weather and site conditions. An analysis of residuals indicated that for the most part no obvious trends were evident; although a slight bias was detected in NEP with soil temperature. To explore the portability of the GFM across ecosystem types, a transcontinental validation was conducted using NEP and ancillary data from seven ecosystems along a north-south transect (i.e., temperature–moisture gradient) from northern Europe (Finland) to the Middle East (Israel). The GFM was shown to explain over 75% of the variability in NEP measured at most ecosystems, which strongly suggests that the GFM maybe successfully applied to forest ecosystems outside Canada.     

纳米TiO2与重金属Cd对铜绿微囊藻生物效应的影响

为了更全面地评价纳米TiO2的生物效应,尤其是纳米TiO2与其他环境污染物的联合作用,以铜绿微囊藻为受试生物,探讨了不同浓度的纳米TiO2,以及纳米TiO2与Cd联合作用对藻生长的影响。根据叶绿素a及藻胆蛋白的含量变化,低浓度的纳米TiO2溶液(0～50mg.L-1)可以促进藻的生长,当纳米TiO2的浓度大于50mg·L-1时,藻细胞的生长有所抑制,生长减慢,并呈剂量-效应关系;当纳米TiO2与Cd离子同时存在时,由于纳米TiO2对Cd离子的吸附作用,水中游离态Cd离子浓度降低,Cd离子对藻的毒性明显降低。因此,纳米TiO2的生态毒性和环境效应不容忽视,同时,应重视纳米材料及与其他环境污染物质共同作用后的生物效应。     

SO_2与CeO_2超细颗粒非均相反应产物的细胞毒性效应

大气二次细颗粒物(secondary fine particulate matters,SFPMs)是我国城市大气PM_(2.5)的主要组成部分。然而由于PM_(2.5)组成成份复杂,其毒性产生的来源并不明确。在本研究中,我们以二氧化铈(CeO_2)超细颗粒物(UFPs)为大气细矿物质颗粒模型,研究了SO_2气体在模拟大气环境中,如湿度(RH)、紫外光照(UV)和NO_2存在条件下,在CeO_2UFPs界面经多相反应生成的二次无机细颗粒物的性质及与细胞毒性的构效关系。实验通过实时高通量细胞分析系统,实时观察了CeO_2-SFPMs暴露对小鼠单核巨噬细胞(RAW264.7)增殖的影响;并进一步检测了CeO_2-SFPMs对细胞膜通透性和细胞凋亡的影响。结果表明,SO_2与CeO_2UFPs作用后可转化为硫酸盐,在有NO_2存在下转化更为明显。CeO_2-SFPMs对细胞毒性效应与其生成的环境条件相关,并具有时间效应性。RAW264.7细胞暴露于CeO_2-SFPMs 8 h,细胞增殖无明显变化;暴露8~25 h后,CeO_2-SFPMs对细胞增殖的抑制率随CeO_2@CeO_2+SO_2@CeO_2+SO_2+RH≈@CeO_2+SO_2+RH+UV@CeO_2+SO_2+RH+NO_2的顺序显著升高。CeO_2-SFPMs对Raw264.7细胞膜通透性和细胞凋亡的影响研究也证明CeO_2-SFPMs@CeO_2+SO_2+RH+NO_2产生的细胞毒性最明显。     

铬渣污染土壤PM10和PM2.5组分中六价铬的生物可给性及健康风险评估

为获取土壤细颗粒组分中污染物的浓度及其生物可给性,分析了某铬渣污染场地土壤PM_(10)和PM_(2.5)组分中六价铬的浓度分布特征,并采用统一生物可给性测试方法(Unified Bioaccessibility Method,UBM)和呼吸吸入生物可给性测试方法(Inhalation Bioaccessibility Method,IBM) 2种体外模拟法测试了六价铬在胃、肠及肺中的生物可给性。结果显示:(1)六价铬和总铬在PM_(10)和PM_(2.5)组分中的含量大多明显低于PM_(250)组分,PM_(10)组分中六价铬和总铬的累积因子(accumulation factors,AF)分别为0.080#12.297和0.008#0.261,PM_(2.5)组分中六价铬和总铬的AF分别为0.019#5.721和0.005#0.342,相比于总铬而言,六价铬在细颗粒中的累积程度更高。较低的有机质(organic matter,OM)含量可能导致了六价铬AF的明显增加。不同组分中六价铬占总铬的比例分别为2%#17%(<250μm)、21%#98%(<10μm)和22%#82%(<2.5μm),表明在土壤细颗粒中,铬更多地以六价铬的形式存在;(2)通过UBM获取的PM_(250)组分中六价铬在胃提取阶段的生物可给性因子为0.0301%#0.9483%,平均值为0.4821%;肠阶段可给性因子为0.0018%#0.3934%,平均值为0.1578%,约为胃提取阶段的0.33倍;(3)通过IBM获取的PM_(10)组分中六价铬在肺阶段的生物可给性因子为2.52%#41.50%,平均值14.47%; PM_(2.5)组分中六价铬的生物可给性因子为2.40%#88.12%,平均值为48.86%,约为PM_(10)组分的3.38倍;(4)在考虑生物可给性条件下,六价铬产生的人体总致癌风险水平从2 430.04×10~(-6)下降至125.83×10~(-6),而且,六价铬呼吸途径产生的致癌风险水平极高,是经口摄入的5.04#176.38倍(胃)、10.92#10 198.00倍(肠),表明呼吸吸入是六价铬致癌风险最为关键的暴露途径。因此,通过测定土壤细颗粒组分中六价铬的生物可给性,能够显著提高铬渣污染土壤健康风险评估的可靠性。     

Effects of boreal forest management practices on the climate impact of CO2 emissions from bioenergy

In Life Cycle Assessment (LCA), carbon dioxide (CO₂) emissions from biomass combustion are traditionally assumed climate neutral if the bioenergy system is CO₂ flux neutral, i.e. the quantity of CO₂ released approximately equals the amount of CO₂ sequestered in biomass. This convention is a plausible assumption for fast growing biomass species, but is inappropriate for slower growing biomass, like forests. In this case, the climate impact from biomass combustion can be potentially underestimated if CO₂ emissions are ignored, or overestimated, if biogenic CO₂ is considered equal to anthropogenic CO₂. The estimation of the effective climate impact should take into account how the CO₂ fluxes are distributed over time: the emission of CO₂ from bioenergy approximately occurs at a single point in time, while the absorption by the new trees is spread over several decades. Our research target is to include this dynamic time dimension in unit-based impact analysis, using a boreal forest stand as case study. The boreal forest growth is modelled with an appropriate function, and is investigated under different forestry regimes (affecting the growth rate and the year of harvest). Specific atmospheric decay functions for biomass-derived CO₂ are then elaborated for selected combinations of forest management options. The contribution to global warming is finally quantified using the GWP_bio index as climate metric. Results estimates the effects of these practices on the characterization factor used for the global warming potential of CO₂ from bioenergy, and point out the key role played by the selected time horizon.     

纳米水稳型C60（nC60）促进Zn2+和Cr6+ 在大型溞体内的吸收、抗氧化性和急性毒性

富勒烯(C60)作为一种被广泛使用的纳米工程材料,其环境行为和所造成的毒效应越来越引起人们的关注,特别是其与重金属的联合毒性.文章选取模式生物大型溞研究纳米水稳型富勒烯(nC60)与Zn+和Cr6+的联合毒性.按EPA 2024急性毒性试验结果,nC60对大型溞48 h-LC50为0.47 mg·L-1,最大无观察效应浓度(NOEC)为0.10 mg·L-1.NOEC浓度选定为nC60亚急性试验浓度,用于联合毒性试验.nC60增强了Zn2+和Cr6+对大型溞的毒性,Zn2和Cr6+对大型溞48 h-LC50分别由2.33mg·L-1和0.40mg·L-1降低为1.52 mg·L-1和033 mg·L-1;nC60增加了大型溞对Zn2+和Cr6+的摄入,暴露1440 min后体内Zn2+和Cr6+累积量分别由6.52 μg·g-1湿重和1.52 μg·g-1湿重增加到9.98 μg ·g-1湿重和3.01 μg·g-1湿重;nC60和Zn2+和Cr6+联合作用于大型潘后,大型溞SOD酶活性均呈现出增强的诱导现象,联合作用时诱导作用强于两种物质单独作用.此研究表明:在亚急性浓度下,nC60增强了Zn2+和Cr6+对大型溞的毒性,提高了大型潘体内Zn2+和Cr6+的积累,并提高大型溞体内自由基活性.     

纳米二氧化铈对蛋白核小球藻的生物学效应研究

纳米二氧化铈(CeO_2)在被广泛使用的同时,其潜在的环境效应也受到人们越来越多的关注。以蛋白核小球藻(Chlorella pyrenoidosa)为实验材料,研究纳米CeO_2的生物学效应,为探索纳米材料对微藻的生物学效应提供理论基础和数据支持。研究结果显示:1)纳米CeO_2在低浓度(≤80 mg·L~(-1))时可促进蛋白核小球藻的生长及色素、可溶性蛋白等的合成,但在高浓度(80 mg·L~(-1))下具有毒性效应;2)低浓度纳米CeO_2可诱导藻细胞合成超氧化物歧化酶(superoxide dismutase,SOD)等可溶性蛋白,以抵御纳米CeO_2的胁迫;但在高浓度时又会降低SOD活力;3)随着纳米CeO_2浓度的升高,藻细胞中丙二醛(malondialdehyde,MDA)含量显著增加,说明藻细胞中活性氧自由基(reactive oxygen species,ROS)过量积累,这将破坏藻细胞的膜结构与功能,使细胞遭受严重损伤。     

纳米二氧化钛(nTiO_2)与双酚A对斜生栅藻(Scenedes-mus obliquus)的联合毒性效应

纳米二氧化钛(n Ti O2)在被人们广泛使用的同时,其潜在的环境影响也受到越来越多的关注。为深入探讨n Ti O2与环境中现有污染物的相互作用及生物效应,以斜生栅藻(Scenedesmus obliquus)为受试生物,按照毒性单位法、相加指数法和混合毒性指数法,研究了n Ti O2与双酚A(BPA,一种常见的环境类雌激素)的联合毒性效应。结果显示,n Ti O2与BPA对S.obliquus生长的72 h半抑制浓度(EC50)分别为28.7 mg·L-1与1.81 mg·L-1。而n Ti O2与BPA共存时,在不同毒性比(4:1,3:1,2:1,1:1,1:2和1:3)下,其联合毒性作用(以BPA计)的72 h EC50值分别为2.198,1.58,1.153,0.428,0.306和0.189 mg·L-1。两者的联合毒性作用不仅仅是简单的相加,而是随着两者毒性比的变化,由拮抗作用转变为相加作用,继而转变为协同作用。这表明,n Ti O2进入环境后与现有污染物的毒性比(浓度比)可能是其联合毒性作用模式的一个重要影响因素。