Effect of nitrification inhibitor on plant biomass and N2O emission rates in alpine meadows on the Tibetan Plateau

ABSTRACT

Treatment with nitrification inhibitors, such as dicyandiamide (DCD) and 3,4-dimethylpyrazole phosphate (DMPP) have been strongly indicated to increase grassland biomass and mitigate soil N₂O emission rates. However, the responses of both alpine meadow aboveground biomass and N₂O emission rates to nitrification inhibitors remains unclear. We separately applied three doses of DCD and DMPP to alpine grassland soils with three duplicates. The biomass and N₂O emission rates were subsequently measured by a clear-cut method and in-situ static chamber gas chromatography during the growing season. Our findings indicated that aboveground biomass increased significantly, and N₂O emission rate decreased significantly at 6.8?kg?ha^?1 DCD and DMPP. Furthermore, the biomass increase effect was more significant than the N₂O emission rate mitigation effect (p?<?0.05). The highest ratios of DCD treatments on meadow production increase and N₂O emission rate decrease were 27.2% and 36.3%, respectively. Our findings provide insight into the enhanced grassland primary production and decreased N₂O flux by nitrification inhibitor treatment in alpine meadows, which may be beneficial to help mitigate global warming.     

Simulation of NO and N2O emissions from a spruce forest during a freeze/thaw event using an N-flux submodel from the PnET-N-DNDC model integrated to CoupModel

The amount of nitrogen gases (N₂O, NO and N₂) emitted from forest soils depends on interactions between soil properties, climatic factors and soil management. To increase the understanding of nitrogen processes in soil ecosystems, two dynamic models, CoupModel (coupled heat and mass transfer model for soil–plant–atmosphere systems) and the denitrification–decomposition (DNDC) model were selected. Both are dynamic models with different submodels for soil, vegetation, hydrology and climate system. CoupModel has a higher degree of detail on soil physical and abiotic components, whereas the DNDC model contains details of microbiological processes involved in production of nitrogen gases. To improve the previous simple submodel of nitrogen emission in CoupModel, we included a submodel corresponding to the forest version of DNDC containing photosynthesis/evapotranspiration-nitrogen (PnET-N-DNDC model).     

Hydrogen peroxide (H2O2) requirement for the oxidation of crude oil in contaminated soils by a modified Fenton's reagent

The oxidation of soil organic matter (SOM) and total petroleum hydrocarbon were investigated in two soils at eight different hydrogen peroxide (H₂O₂) concentrations to determine the optimal H₂O₂ dosage for the efficient remediation of soils contaminated by crude oil with minimal SOM removal. In our study, H₂O₂ concentrations up to 1100 mM increased the SOM destruction up to 10%–15% in the two soils while no improvement of the crude oil removal efficiencies was observed. The results indicate that the destruction of SOM significantly limits the oxidation of crude oil because SOM might consume H₂O₂ more effectively than crude oil at H₂O₂ concentrations above 1100 mM. In addition, H₂O₂ concentrations higher than 1100 mM were not expected for both soils because of the extremely rapid H₂O₂ decomposition, and low H₂O₂ utilization, of both soils.     

生物黑炭还田对晚稻CH4和N2O综合减排影响研究

利用静态箱法测定了稻草直接还田和生物黑炭还田对湖南晚稻CH4和N2O排放的影响。结果表明,与单施化肥处理相比,添加稻草和生物黑炭处理的CH4排放量分别增加了24.70%（P〈0.05）和6.32%,而N2O的排放量分别降低了37.08%（P〈0.05）和37.61%（P〈0.05）;生物黑炭CH4排放量较稻草还田减少了14.74%（P〈0.05）。按100年统计稻田CH4和N2O的综合增温潜势（GWP）表明,单位产量的GWP由大到小顺序为稻草（RS）,不施肥（CK）,黑炭（BC）,化肥（CF）。综上说明,生物黑炭还田能保持晚稻产量稳定,减少了当季晚稻CH4和N2O的排放,具有一定的生态环境效益。     

Production of N2O in two biologic nitrogen removal processes: a comparison between conventional and short-cut nitrogen removal processes

The N2O production in two nitrogen removal processes treating domestic wastewater was investigated in laboratory-scale aerobic-anoxic sequencing batch reactors （SBRs）. Results showed that N2O emission happened in the aerobic phase rather than in the anoxic phase. During the aerobic phase, the nitrogen conversion to N2O gas was 27.7% and 36.8% of NH＋-N loss for conventional biologic N-removal process and short-cut biologic N-removal process. The dissolved N2O was reduced to N2 in the anoxic denitrification phase. The N2O production rate increased with the increasing of nitrite concentration and ceased when NH＋-N oxidation was terminated. Higher nitrite accumulation resulted in higher NEO emission in the short-cut nitrogen removal process. Pulse-wise addition of 20 mg NO2 -N. L- 1 gave rise to 3-fold of N2O emission in the conventional N-removal process, while little change happened with 20 mg NOS-N L-1 was added to SBR1.     

H_2O_2致大鼠RTE细胞系氧化应激作用及GSH保护作用的体外研究

许多具有氧化作用的空气污染物,均能使细胞产生氧化损伤,使胸腺基质淋巴生成素(thymic stromal lymphopoietin,TSLP)含量上升。而TSLP是一种启动过敏性炎症的重要因子,会导致哮喘等疾病发生率的上升。在本研究中用过氧化氢(H_2O_2)模拟具有氧化作用的空气污染物进行染毒,研究细胞氧化应激水平的变化,并讨论还原型谷胱甘肽(GSH)对细胞受氧化损伤的保护作用。将大鼠支气管上皮细胞(RTE)分组培养,每组设置6个平行实验,分别用低、中、高剂量H_2O_2染毒3 h;高剂量设置1个重复,作为保护组,在染毒前用GSH保护2 h。结果显示,高剂量组H_2O_2(3.2 mmol·L~(~(-1)))染毒的细胞,其细胞活力下降(P0.01),丙二醛(MDA)水平上升(P0.01),TSLP水平上升(P0.05),与之相比,用GSH保护后的同剂量染毒组,上述指标得到全面缓解(P0.01)。这表明高浓度的H_2O_2会损伤细胞活力,并使MDA及TSLP水平上升,而GSH对TSLP及MDA的升高有极显著的抑制作用,即对细胞有一定的保护作用。     

山西工矿区土壤二氧化硫与多环芳烃复合污染对小麦种子萌发和幼苗生长的影响

以小麦为供试植物,山西工矿区生黄土为供试土壤,进行了土壤中二氧化硫(SO2)与多环芳烃(PAHs)单一及复合污染对小麦种子萌发率及小麦幼苗株高、根伸长和地下生物量影响的研究,以期考察复合污染的生态毒性效应。结果表明,小麦种子萌发对SO2与PAHs单一及复合污染均不敏感;SO2和PAHs单一污染时,小麦幼苗的株高与根伸长均受到一定程度的影响,低浓度SO2或PAHs处理对小麦生长起促进作用,高浓度则为抑制作用;小麦幼苗株高与SO2浓度呈显著负相关(r=-0.954,P<0.05),但与PAHs浓度的相关性不显著;SO2与PAHs复合污染条件下,对小麦幼苗株高或根伸长的联合作用多体现为协同作用,在低浓度情况下(SO2<500mg·kg-1)表现为协同促进;当SO2达到500～1000mg·kg-1时,对小麦幼苗株高或根伸长的联合作用均体现为协同抑制。SO2和PAHs单一污染时,小麦幼苗地下生物量与SO2、PAHs浓度均为显著负相关(rPAHs=-0.953,rSO2=-0.916,P<0.05);复合污染条件下,在SO2浓度为10mg·kg-1时,对地下生物量的联合作用多体现协同促进作用;而在SO2浓度为1000mg·kg-1,PAHs为50～100mg·kg-1时,对地下生物量的联合作用均体现为协同抑制作用。多元逐步回归分析进一步表明,SO2与PAHs复合污染条件下,小麦幼苗株高、根伸长都受到了SO2及PAHs的共同影响,而SO2是影响小麦幼苗地下生物量的主要因素。     

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.