Spatial variations in the N2O emissions and denitrification potential of riparian buffer strips in a contaminated urban river

Spatial variations in the N₂O emissions and denitrification potential of riparian buffer strips (RBS) in a polluted river were examined. The river received large pollutant inputs from urban runoff and wastewater discharge, resulting in impaired water quality in the river and downstream reservoir. The potential for nitrogen removal by RBS was evaluated by measuring in situ N₂O emission fluxes in static closed chambers and sediment denitrification potentials with acetylene inhibition techniques. The results showed that N₂O emission fluxes decreased from the upstream (16.39 μg/(m²·h)) to downstream (0.30 μg/(m²·h)) sites and from the water body to upland sites. The trend in decreasing N₂O emission fluxes in the downstream direction was mainly associated with sediment/soil textures (clay loam→sandy soil) and sediment/soil water contents and was also related to the vegetation along the RBS and nutrients in the sediments/soils. The correlation coefficient was highest (r=0.769) between the N₂O emission flux and sediment/soil water content. Sediment/soil denitrification potentials under N-amended and ambient conditions were higher (highest 32.86 mg/(kg·h)) for the upstream sites, which were consistent with in situ N₂O flux rates.     

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.     

Application of a three-dimensional model for assessing effects of small clear-cuttings on radiation and soil temperature

A three-dimensional model Mixfor-3D of soil–vegetation–atmosphere transfer (SVAT) was developed and applied to estimate possible effects of tree clear-cutting on radiation and soil temperature regimes of a forest ecosystem. The Mixfor-3D model consists of several closely coupled 3D sub-models describing: forest stand structure; radiative transfer in a forest canopy; turbulent transfer of sensible heat, H₂O and CO₂ between ground surface and the atmospheric surface layer; evapotranspiration of ground surface vegetation and soil; heat and moisture transfer in soil. The model operates with the horizontal grid resolution, 2 m × 2 m; vertical resolution, 1 m and primary time step, 1 h.     

Uncertainty analysis of climate change mitigation options in the forestry sector using a generic carbon budget model

Industrialized countries agreed on a reduction of greenhouse gas emissions under the Kyoto Protocol. Many countries elected forest management activities and the resulting net balance of carbon emissions and removals of non-CO₂ greenhouse gases by forest management in their climate change mitigation measures. In this paper a generic dynamic forestry model (FORMICA) is presented. It has an empirical basis. Several modules trace C pools relevant for the Kyoto Protocol and beyond: biomass, litter, deadwood and soil, and harvested wood products. The model also accounts for the substitution of fossil fuels by wood products and bioenergy.     

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.     

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.     

Two-way coupling versus one-way forcing of plankton and fish models to predict ecosystem changes in the Benguela

‘End-to-end’ models have been adopted in an attempt to capture more of the processes that influence the ecology of marine ecosystems and to make system wide predictions of the effects of fishing and climate change. Here, we develop an end-to-end model by coupling existing models that describe the dynamics of low (ROMS–N₂P₂Z₂D₂) and high trophic levels (OSMOSE). ROMS–N₂P₂Z₂D₂ is a biogeochemical model representing phytoplankton and zooplankton seasonal dynamics forced by hydrodynamics in the Benguela upwelling ecosystem. OSMOSE is an individual-based model representing the dynamics of several species of fish, linked through opportunistic and size-based trophic interactions. The models are coupled through a two-way size-based predation process. Plankton provides prey for fish, and the effects of predation by fish on the plankton are described by a plankton mortality term that is variable in space and time. Using the end-to-end model, we compare the effects of two-way coupling versus one-way forcing of the fish model with the plankton biomass field. The fish-induced mortality on plankton is temporally variable, in part explained by seasonal changes in fish biomass. Inclusion of two-way feedback affects the seasonal dynamics of plankton groups and usually reduces the amplitude of variation in abundance (top-down effect). Forcing and coupling lead to different predicted food web structures owing to changes in the dominant food chain which is supported by plankton (bottom-up effect). Our comparisons of one-way forcing and two-way coupling show how feedbacks may affect abundance, food web structure and food web function and emphasise the need to critically examine the consequences of different model architectures when seeking to predict the effects of fishing and climate change.     

N2O emission from a sequencing batch reactor for biological N and P removal from wastewater

Nitrous oxide （N2O） is a greenhouse gas that can be released during biological nitrogen removal from wastewater. N2O emission from a sequencing batch reactor （SBR） for biological nitrogen and phosphorus removal from wastewater was investigated, and the aims were to examine which process, nitrification or denitrification, would contribute more to N2Oemission and to study the effects of heterotrophic activities on N2O emission during nitrification. The results showed that N2O emission was mainly attributed to nitrification rather than to denitrification. N2O emission during denitrification mainly occurred with stored organic carbon as the electron donor. During nitrification, NaO emission was increased with increasing initial ammonium or nitrite concentrations. The ratio of N2O emission to the removed ammonium nitrogen （N2O- N/NH4-N） was 2.5% in the SBR system with high heterotrophic activities, while this ratio was in the range from 0.14% to 1.06% in batch nitrification experiments with limited heterotrophic activities.     

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.     

Soil enzyme activities and their indication for fertility of urban forest soil

To reveal the biological characteristics of urban forest soil and the effects of soil enzyme on soil fertility as well as the correlation between physicochemical properties and enzyme activities, 44 urban forest soil profiles in Nanjing were investigated. Basic soil physicochemical properties and enzyme activities were analyzed in the laboratory. Hydrogen peroxidase, dehydrogenase, alkaline phosphatase, and cellulase were determined by potassium permanganate titration, TTC (C₁₉H₁₅N₄·Cl) colorimetry, phenyl phosphate dinatrium colorimetry, and anthrone colorimetry, respectively. The result showed that soil pH, organic carbon (C), and total nitrogen (N) had great effects on hydrogen peroxidase, dehydrogenase, and alkaline phosphatase activities in 0–20 cm thick soil. However, pH only had great effect on hydrogen peroxidase, dehydrogenase, and alkaline phosphatase activities in 20–40 cm thick soil. Hydrogen peroxidase, dehydrogenase, and alkaline phosphatase were important biological indicators for the fertility of urban forest soil. Both in 0–20 cmand 20–40 cmsoil, soil enzyme system (hydrogen peroxidase, dehydrogenase, alkaline phosphatase, and cellulase) had a close relationship with a combination of physicochemical indicators (pH, organic C, total N, available K, available P, cation exchange capacity (CEC), and microbial biomass carbon (C_mic)). The more soil enzyme activities there were, the higher the fertility of urban forest soil.     

Response of tree growth to a changing climate in boreal central Canada: A comparison of empirical,process-based,and hybrid modelling approaches

The impact of 2 × CO₂ driven climate change on radial growth of boreal tree species Pinus banksiana Lamb., Populus tremuloides Michx. and Picea mariana (Mill.) BSP growing in the Duck Mountain Provincial Forest of Manitoba (DMPF), Canada, is simulated using empirical and process-based model approaches. First, empirical relationships between growth and climate are developed. Stepwise multiple-regression models are conducted between tree-ring growth increments (TRGI) and monthly drought, precipitation and temperature series. Predictive skills are tested using a calibration–verification scheme. The established relationships are then transferred to climates driven by 1× and 2 × CO₂ scenarios using outputs from the Canadian second-generation coupled global climate model. Second, empirical results are contrasted with process-based projections of net primary productivity allocated to stem development (NPP_s). At the finest scale, a leaf-level model of photosynthesis is used to simulate canopy properties per species and their interaction with the variability in radiation, temperature and vapour pressure deficit. Then, a top-down plot-level model of forest productivity is used to simulate landscape-level productivity by capturing the between-stand variability in forest cover. Results show that the predicted TRGI from the empirical models account for up to 56.3% of the variance in the observed TRGI over the period 1912–1999. Under a 2 × CO₂ scenario, the predicted impact of climate change is a radial growth decline for all three species under study. However, projections obtained from the process-based model suggest that an increasing growing season length in a changing climate could counteract and potentially overwhelm the negative influence of increased drought stress. The divergence between TRGI and NPP_s simulations likely resulted, among others, from assumptions about soil water holding capacity and from calibration of variables affecting gross primary productivity. An attempt was therefore made to bridge the gap between the two modelling approaches by using physiological variables as TRGI predictors. Results obtained in this manner are similar to those obtained using climate variables, and suggest that the positive effect of increasing growing season length would be counteracted by increasing summer temperatures. Notwithstanding uncertainties in these simulations (CO₂ fertilization effect, feedback from disturbance regimes, phenology of species, and uncertainties in future CO₂ emissions), a decrease in forest productivity with climate change should be considered as a plausible scenario in sustainable forest management planning of the DMPF.     

Litter decomposition and nitrogen mineralization from an annual to a monthly model

The forest litter decomposition model (FLDM) described in this paper provides an important basis for assessing the impacts of forest management on seasonal stream water quality and export of dissolved organic carbon (DOC). By definition, models with annual time steps are unable to capture seasonal, within-year variation. In order to simulate seasonal variation in litter decomposition and DOC production and export, we have modified an existing annual FLDM to account for monthly dynamics of decomposition and residual mass in experimental litterbags placed in 21 different forests across Canada.The original annual FLDM was formulated with three main litter pools (fast, slow, and very slow decomposing litter) to address the fact that forest litter is naturally composed of a mixture of organic compounds that decompose at different rates. The annual FLDM was shown to provide better simulations than more complex models like CENTURY and SOMM.The revised monthly model retains the original structure of the annual FLDM, but separates litter decomposition from nitrogen (N) mineralization. In the model, monthly soil temperature, soil moisture, and mean January soil temperature are shown to be the most important controlling variables of within-year variation in decomposition. Use of the three variables in a process-based definition of litter decomposition is a significant departure from the empirical definition in the annual model. The revised model is shown to give similar calculations of residual mass and N concentration as the annual model (r² = 0.91, 0.78), despite producing very different timeseries of decomposition over six years. It is shown from a modelling perspective that (i) forest litter decomposition is independent of N mineralization, whereas N mineralization is dependent on litter decomposition, and (ii) mean January soil temperature defines litter decomposition in the summer because of winter-temperatures’ role in modifying forest-floor microorganism community composition and functioning in the following summer.     

An optimized policy for the reduction of CO2 emission in the Brazilian Legal Amazon

The Brazilian government has already acknowledged the importance of investing in the development and application of technologies to reduce or prevent CO₂ emissions resulting from human activities in the Legal Brazilian Amazon (BA). The BA corresponds to a total area of 5 × 10⁶ km² from which 4 × 10⁶ km² was originally covered by the rain forest. One way to interfere with the net balance of greenhouse gases (GHG) emissions is to increase the forest area to sequester CO₂ from the atmosphere. The single most important cause of depletion of the rain forest is cattle ranching. In this work, we present an effective policy to reduce the net balance of CO₂ emissions using optimal control theory to obtain a compromising partition of investments in reforestation and promotion of clear technology to achieve a CO₂ emission target for 2020. The simulation indicates that a CO₂ emission target for 2020 of 376 million tonnes requires an estimated forest area by 2020 of 3,708,000 km², demanding a reforestation of 454,037 km². Even though the regional economic growth can foster the necessary political environment for the commitment with optimal emission targets, the reduction of 38.9% of carbon emissions until 2020 proposed by Brazilian government seems too ambitious.     

Relationships of nitrous oxide fluxes with water quality parameters in free water surface constructed wetlands

The effects of chemical oxygen demand (COD) concentration in the influent on nitrous oxide (N₂O) emissions, together with the relationships between N₂O and water quality parameters in free water surface constructed wetlands, were investigated with laboratoryscale systems. N₂O emission and purification performance of wastewater were very strongly dependent on COD concentration in the influent, and the total N₂O emission in the system with middle COD influent concentration was the least. The relationships between N₂O and the chemical and physical water quality variables were studied by using principal component scores in multiple linear regression analysis to predict N₂O flux. The multiple linear regression model against principal components indicated that different water parameters affected N₂O flux with different COD concentrations in the influent, but nitrate nitrogen affected N₂O flux in all systems.     

Impact of nitrogen fertilizer source on nitrous oxide (N2O) emissions from three different agricultural soils during freezing conditions

ABSTRACT

Nitrogen (N) application is the main agricultural management that increases nitrous oxide (N₂O) concentration in the atmosphere. Freezing conditions are common phenomenon in the northern China that significantly affect soil N₂O emissions through alterations in nutrients availability and microbial population. To develop a comprehensive understanding of how N fertilizer managements affect soil N₂O emissions during the freezing process, a lab incubation was conducted in three typical cultivated soils (black soil, fluvo-aquic soil, or loess soil) by adding different N fertilizer sources, including ammonium chloride, sodium nitrate, or urea at different N levels (0, 80, 200, or 500 mg N/kg) at the start of freezing. The N₂O emissions in the fluvo-aquic soil were significantly higher than in other soils. The application of nitrate in the fluvo-aquic soil promoted N₂O emissions by five- and seven-fold higher compared to ammonium chloride and urea, whereas N₂O emissions in black soil were enhanced by application of ammonium chloride. Data indicate that denitrification is the major pathway for N₂O production in the fluvo-aquic soil during the freezing process, while ammonia oxidation responses accounts for elevated N₂O production in black soil. No significant influence of N fertilizer levels on N₂O emissions were found during soil freezing. These results suggest that agricultural practices that focus on mitigation of N₂O emissions need to avoid selection of nitrate as N fertilizer source in fluvo-aquic soil prior to the freezing season. Future studies need to focus on how the expression of enzymes and/or shifts in microbial communities respond to different N fertilizers during freezing conditions.     

A comprehensive model to estimate the simultaneous release of acidic and basic gaseous pollutants from swine slurry under different scenarios

Swine slurry is a source of atmospheric pollutants. Emissions of basic and acidic compounds from slurry are largely dependent on the surface pH. In a storage system, the pH at the surface layers changes over time due to the volatilisation of ammonia (NH₃), carbon dioxide (CO₂) and acetic acid (HAc). In this article, a comprehensive gas emission–pH (GE–pH) coupled model is proposed to describe the simultaneous release of acidic and basic gaseous pollutants from swine slurry. The model was applied to describe the release of NH₃, CO₂, HAc and hydrogen sulphide (H₂S) from standard slurries stored in animal houses, outside storage tanks and lagoons. The modelled results agreed well with values reported in the literature and could be reasonably interpreted. The key parameters affecting the release of gases were: initial pH, initial concentration of total ammonium nitrogen and inorganic carbon, slurry temperature and air velocity. This study suggests that future modelling studies on gas emissions from animal slurry should consider the concentration of inorganic carbon and the frequency in which the slurry surface is mixed or altered, because they affect the surface pH and the release of gaseous pollutants from slurry.     

Evaluation of greenhouse gas emissions from wetland and agriculture ecosystems in Sanjiang Plain

Carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄) are important greenhouse gases (GHGs). The objective of this study is to quantify the aggregate GHG (CH₄, N₂O and CO₂) emissions and estimate economic losses of three ecosystems (marsh, paddy field and upland) in the Sanjiang Plain, excluding the Muling-Xiangkai Plain, south of Wanda Mountain. The results indicate the economic losses from GHG emissions of marshes were from 6.40 to 7.75?×?10⁹ CNY (Chinese Yuan), those of paddy fields were from 1.41 to 3.20?×?10⁹ CNY; and from uplands were from 0.26 to 0.49?×?10⁹ CNY. Using linear trend analysis, the economic losses through GHG emissions of marshes fell between 1982 and 2005, but those from paddy fields and uplands increased. In our study, the sequence in magnitude of the economic losses from GHG emissions was: marshes > paddy fields > uplands. In fact, the economic value of GHG emissions was negative because of these adverse impacts on the environment. This article could provide a reference for calculation of GHG exchange. The results suggest that improvement of fertiliser use efficiency for more precise agricultural management and returning straw to cropland could mitigate GHG emissions and would help to achieve sustainable development.