Assessing carbon dynamics in natural and perturbed boreal aquatic systems

Increases in soil sequestered carbon under conservation agriculture cropping decrease the estimated greenhouse gas emissions of wetland rice using life cycle assessment

How do sand addition, soil moisture and nutrient status influence greenhouse gas fluxes from drained organic soils?

Rivers play an important role in greenhouse gas emissions. Over the past decade, because of global urbanization trends, rapid land use changes have led to changes in river ecosystems that have had a stimulating effect on the greenhouse gas production and emissions. Presently, there is an urgent need for assessments of the greenhouse gas concentrations and emissions in watersheds. Therefore, this study was designed to evaluate river-based greenhouse gas emissions and their spatial-temporal features as well as possible impact factors in a rapidly urbanizing area. The specific objectives were to investigate how river greenhouse gas concentrations and emission fluxes are responding to urbanization in the Liangtan River, which is not only the largest sub-basin but also the most polluted one in Chongqing City. The thin layer diffusion model method was used to monitor year-round concentrations of pCO2, CH4, and N2O in September and December 2014, and March and June 2015. The pCO2 range was (23.38±34.89)-(1395.33±55.45) Pa, and the concentration ranges of CH4 and N2O were (65.09±28.09)-(6021.36±94.36) nmol·L-1 and (29.47±5.16)-(510.28±18.34) nmol·L-1, respectively. The emission fluxes of CO2, CH4, and N2O, which were calculated based on the method of wind speed model estimations, were -6.1-786.9, 0.31-27.62, and 0.06-1.08 mmol·(m2·d)-1, respectively. Moreover, the CO2 and CH4 emissions displayed significant spatial differences, and these were roughly consistent with the pollution load gradient. The greenhouse gas concentrations and fluxes of trunk streams increased and then decreased from upstream to downstream, and the highest value was detected at the middle reaches where the urbanization rate is higher than in other areas and the river is seriously polluted. As for branches, the greenhouse gas concentrations and fluxes increased significantly from the upstream agricultural areas to the downstream urban areas. The CO2 fluxes followed a seasonal pattern, with the highest CO2 emission values observed in autumn, then successively winter, summer, and spring. The CH4 fluxes were the highest in spring and the lowest in summer, while N2O flux seasonal patterns were not significant. Because of the high carbon and nitrogen loads in the basin, the CO2 products and emissions were not restricted by biogenic elements, but levels were found to be related to important biological metabolic factors such as the water temperature, pH, DO, and chlorophyll a. The carbon, nitrogen, and phosphorus content of the water combined with sewage input influenced the CH4 products and emissions. Meanwhile, N2O production and emissions were mainly found to be driven by urban sewage discharge with high N2O concentrations. Rapid urbanization accelerated greenhouse gas emissions from the urban rivers, so that in the urban reaches, CO2/CH4 fluxes were twice those of the non-urban reaches, and all over the basin N2O fluxes were at a high level. These findings illustrate how river basin urbanization can change aquatic environments and aggravate allochthonous pollution inputs such as carbon, nitrogen, and phosphorus, which in turn can dramatically stimulate river-based greenhouse gas production and emissions; meanwhile, spatial and temporal differences in greenhouse gas emissions in rivers can lead to the formation of emission hotspots.

Peatlands represent 2.5% of all agricultural land in the EU, yet they account for ~ 25% of agricultural greenhouse gas (GHG) emissions, and ~ 5% of total EU-wide GHG emissions. Several studies have shown that peatland rewetting can reduce, or even reverse, the net GHG emissions from previously drained peatlands. We investigated GHG emissions from 14 different European peatland sites (Germany [6], Poland [4] and Netherlands [4]) across a landuse (3 levels) and water table (2 levels) gradient during a 2 year period (July 2021 – June 2023). GHG flux measurements utilizing closed, non-flow-through, dark, non-steady-state chambers were implemented to estimate ecosystem respiration from the study sites. Ecosystem respiration represents the largest share of carbon export to the atmosphere from terrestrial ecosystems. Within the study, landuse gradient was represented by the level of paludiculture (harvest frequency/ soil nitrogen levels), and water table level indicated by Typha- and Carex- dominated vegetation. Initial study results indicate that overall, CO2 fluxes varied across seasons (ANOVA, p<0.001, n = 1738, F = 14.08), with the highest fluxes occurring in summer (0.402 ± 0.342 g CO2 m-2h-1), and lowest in winter (0.233 ± 0.368 g CO2 m-2h-1). Similarly, CH4 fluxes varied seasonally, with the highest CH4 fluxes in summer (6.95 ± 8.07 mg CH4 m-2h-1) and lowest in winter (1.98 ± 4.07 mg CH4 m-2h-1). Average CO2 fluxes decreased with the increasing level of paludiculture intensity for both Typha and Carex dominated sites, while CH4 fluxes typically increased with increasing harvest frequency/ soil nitrogen levels. While CO2 and CH4 fluxes were generally higher in the early morning (as compared to afternoons), particularly during summer and autumn, we could not show an overall significant diurnal difference in GHG fluxes. Seasonal variability in CO2 and CH4 was likely an indicator of the effect of temperature and water table level on GHG fluxes. GHG fluxes at the Typha dominated sites were consistently higher than those of complimentary Carex dominated sites for each landuse class, highlighting the importance of water table and vegetation species on GHG emissions. This research was conducted as part of the Peatland Rewetting In Nitrogen-Contaminated Environments: Synergies and trade-offs between biodiversity, climate, water quality & Society (PRINCESS) project, investigating rewetting of drained, nitrogen contaminated peatlands and their potential role in reducing EU-wide greenhouse gas emissions and improving wetland biodiversity.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Despite the importance of agriculture in California's Central Valley, the potential of alternative management practices to reduce soil greenhouse gas (GHG) emissions has been poorly studied in California. This study aims at (1) calibrating and validating DAYCENT, an ecosystem model, for conventional and alternative cropping systems in California's Central Valley, (2) estimating CO2, N2O, and CH4 soil fluxes from these systems, and (3) quantifying the uncertainty around model predictions induced by variability in the input data. The alternative practices considered were cover cropping, organic practices, and conservation tillage. These practices were compared with conventional agricultural management. The crops considered were beans, corn, cotton, safflower, sunflower, tomato, and wheat. Four field sites, for which at least five years of measured data were available, were used to calibrate and validate the DAYCENT model. The model was able to predict 86-94% of the measured variation in crop yields and 69-87% of the measured variation in soil organic carbon (SOC) contents. A Monte Carlo analysis showed that the predicted variability of SOC contents, crop yields, and N2O fluxes was generally smaller than the measured variability of these parameters, in particular for N2O fluxes. Conservation tillage had the smallest potential to reduce GHG emissions among the alternative practices evaluated, with a significant reduction of the net soil GHG fluxes in two of the three sites of 336 +/- 47 and 550 +/- 123 kg CO2-eq x ha(-1) x yr(-1) (mean +/- SE). Cover cropping had a larger potential, with net soil GHG flux reductions of 752 +/- 10, 1072 +/- 272, and 2201 +/- 82 kg CO2-eq x ha(-1) x yr(-1). Organic practices had the greatest potential for soil GHG flux reduction, with 4577 +/- 272 kg CO2-eq x ha(-1) x yr(-1). Annual differences in weather or management conditions contributed more to the variance in annual GHG emissions than soil variability did. We concluded that the DAYCENT model was successful at predicting GHG emissions of different alternative management systems in California, but that a sound error analysis must accompany the predictions to understand the risks and potentials of GHG mitigation through adoption of alternative practices.

As cities work to reduce their total greenhouse gas (GHG) emissions, the transportation sector is lagging, accounting for a growing percentage of total emissions in many cities. The provision of public transit, and specifically urban rail transit, is widely seen as a useful tool for reducing urban transportation GHG emissions. More research, however, is needed to understand the net impact of new metro rail infrastructure on urban emissions and guide efforts to maximise the GHG savings through rail investments. This paper examines the net GHG emissions of the Jubilee line extension (JLE) in London, UK. The GHG emissions associated with construction, operation, ridership and changes in urban density associated with the provision of the new metro rail infrastructure are assessed. These components are then combined and compared to calculate the net GHG impact across the study period, which extends from opening in 1999 through 2011. The capital GHG emissions from construction of the JLE are calculated as 530 kilotonnes carbon dioxide equivalent (CO2e). The initial mode shift from other rail lines and long-term mode change from automobiles result in yearly GHG savings from riders on the JLE. A quasi-experimental analysis of land-use change near the JLE finds no calculable GHG saving from increased residential density. The GHG payback period is calculated between 13 and 19 years.

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

Summary1. Climate change may significantly influence lake carbon dynamics and consequently the exchange of CO2 with the atmosphere. Warming will accelerate multiple processes that either absorb or release CO2, making predicting the net effect of warming on CO2 exchange with the atmosphere difficult. Here we experimentally test how the CO2 flux of deep and shallow systems responds to warming. To do this, we conducted a greenhouse experiment using mesocosms of two depths, experiencing either ambient or warmed temperatures.2. Deeper mesocosms were found to have a lower average CO2 concentration than shallower mesocosms under ambient temperature conditions. In addition, warming interacts with mesocosm depth to affect the average CO2 concentration; there was no effect of warming on the average CO2 concentration of deep mesocosms, but shallow mesocosms had significantly lower average CO2 concentrations when warmed.3. The difference in CO2 concentration resulting from the depth manipulation was due to varying loss rates of particulate carbon to the sediments. There was a strong negative correlation between CO2 and sedimentation rates in the deep mesocosms suggesting that high particulate carbon loss to the sediments lowered the CO2 concentration in the water column. There was no correlation between CO2 and sedimentation rates observed for shallow mesocosms suggesting enhanced carbon regeneration from the sediments was maintaining higher CO2 concentrations in the water column.4. Relationships between CO2 and algal concentrations indicate that the reduction in CO2 concentrations resulting from warming is due to increased per capita algal turnover rates depleting CO2 in the water column. Our results suggest that the carbon dynamics and CO2 flux of shallow systems will be affected more by climate warming than deep systems and the net effect of warming is to increase CO2 uptake.

Plug-in hybrid electric vehicles (PHEVs) have potential to reduce greenhouse gas (GHG) emissions in the U.S. light-duty vehicle fleet. GHG emissions from PHEVs and other vehicles depend on both vehicle design and driver behavior. We pose a twice-differentiable, factorable mixed-integer nonlinear programming model utilizing vehicle physics simulation, battery degradation data, and U.S. driving data to determine optimal vehicle design and allocation for minimizing lifecycle greenhouse gas (GHG) emissions. The resulting nonconvex optimization problem is solved using a convexification-based branch-and-reduce algorithm, which achieves global solutions. In contrast, a randomized multistart approach with local search algorithms finds global solutions in 59% of trials for the two-vehicle case and 18% of trials for the three-vehicle case. Results indicate that minimum GHG emissions is achieved with a mix of PHEVs sized for around 35 miles of electric travel. Larger battery packs allow longer travel on electric power, but additional battery production and weight result in higher GHG emissions, unless significant grid decarbonization is achieved. PHEVs offer a nearly 50% reduction in life cycle GHG emissions relative to equivalent conventional vehicles and about 5% improvement over ordinary hybrid electric vehicles. Optimal allocation of different vehicles to different drivers turns out to be of second order importance for minimizing net life cycle GHGs.

Farm dams are integral part of Australian agriculture and they contain a substantial fraction of inland fresh water on the Australian continent. Storage of water can alter the physical, chemical and biological processes occurring within the dam and subsequently, any downstream receiving water body. However, limited research has been directed into understanding the factors controlling biogeochemical processes in the dam and the effect of the dam on downstream water quality. In this thesis, a dam (11.8 ML) with a catchment area of 1.3 km2 on a dairy farm at Poowong East (ca. 130 km south-east of Melbourne, VIC) was studied to investigate: (1) the seasonal variations in nutrient concentrations and greenhouse gas (N2O and CH4) emissions, (2) the role of aquatic sediments in the emission of the greenhouse gases, and (3) the biogeochemical cycling of nitrogen and phosphorus in the dam. Fluxes of N2O, CH4 and bioavailable inorganic nutrients (NH4+, NOx and FRP) between the sediment and the water column at 3 different sites within the dam were determined over a period of 18 months (from July 2010 to December 2011). Factors controlling the gas and nutrient fluxes (i.e. temperature, dissolved oxygen, nutrient availability and faunal abundance) were analysed. The physicochemical characteristics of the creek upstream and downstream of the dam were also measured throughout the sampling period. This study also involved sediment core incubations, deployment of equilibrium dialysis samplers (pore water peepers) and planar optode experiments. The dam was found to be a major source of N2O during periods when both NOx and O2 concentrations were high in the water column. Sedimentary CH4 flux increased gradually during summer when the overlying water was very close to, or completely, anoxic. The production rate of CH4 was almost 3 times greater in the deeper site (3.5 metres) than in the shallow site (1 metre) and the highest fluxes were associated with the bottom water temperature maxima. The dam was a net source of NH4+ but a net sink for NOx and FRP. The internal load of NH4+ was almost 3 times higher than the external load on an annual basis. Conversely, the dam removed about 14% and 5% of the annual external NOx and FRP loads, respectively. There was a significant seasonal variation in inorganic nutrient fluxes in the dam. The diffusive flux of nutrients across the sediment-water interface, particularly during summer months, emphasized the role of the bottom sediment as an alternative source of bioavailable nutrients into the water column. This study found that benthic macrofauna (here both Chironomidae and Oligochaeta) did not impose any significant effect on in situ N2O production but the results suggested a perhaps important involvement in the cycling of biogenic CH4. Chironomidae larvae significantly increased sediment oxygen consumption rates and decreased the NH4+ efflux. Chironomidae larvae also appreciably increased the water column NOx-derived denitrification (Dw) as well as the coupled nitrification-denitrification (Dn) rates in the sediment. Overall, this study produced three key findings: (1) Farm dams can be a major source of N2O and CH4 depending on the season and nutrient availability. (2) Seasonal variation of nutrient processing within the dam resulted in significant effects on the downstream water quality. In most sampling months, the outflowing water failed to meet the state and regional water quality standards particularly in terms of turbidity, dissolved oxygen and different forms of nutrients. (3) Long term monitoring of the seasonal variation of the nutrient processing in farm dams is essential to predict the influence of such dams on the downstream water bodies and to assess the effectiveness of any management actions.

U.S. rice paddies, critical for food security, are increasingly contributing to non‐CO2 greenhouse gas (GHG) emissions like methane (CH4) and nitrous oxide (N2O). Yet, the full assessment of GHG balance, considering trade‐offs between soil organic carbon (SOC) change and non‐CO2 GHG emissions, is lacking. Integrating an improved agroecosystem model with a meta‐analysis of multiple field studies, we found that U.S. rice paddies were the rapidly growing net GHG emission sources, increased 138% from 3.7 ± 1.2 Tg CO2eq yr−1 in the 1960s to 8.9 ± 2.7 Tg CO2eq yr−1 in the 2010s. CH4, as the primary contributor, accounted for 10.1 ± 2.3 Tg CO2eq yr−1 in the 2010s, alongside a notable rise in N2O emissions by 0.21 ± 0.03 Tg CO2eq yr−1. SOC change could offset 14.0% (1.45 ± 0.46 Tg CO2eq yr−1) of the climate‐warming effects of soil non‐CO2 GHG emissions in the 2010s. This escalation in net GHG emissions is linked to intensified land use, increased atmospheric CO2, higher synthetic nitrogen fertilizer and manure application, and climate change. However, no/reduced tillage and non‐continuous irrigation could reduce net soil GHG emissions by approximately 10% and non‐CO2 GHG emissions by about 39%, respectively. Despite the rise in net GHG emissions, the cost of achieving higher rice yields has decreased over time, with an average of 0.84 ± 0.18 kg CO2eq ha−1 emitted per kilogram of rice produced in the 2010s. The study suggests the potential for significant GHG emission reductions to achieve climate‐friendly rice production in the U.S. through optimizing the ratio of synthetic N to manure fertilizer, reducing tillage, and implementing intermittent irrigation.

Taking Stock of Strategies on Climate Change and the Way Forward: A Strategic Climate Change Framework for Australia

Relationships between greenhouse gas emissions and cultivable bacterial populations in conventional, organic and long-term grass plots as affected by environmental variables and disturbances

The carbon dioxide (CO2) emissions at the water–air interface in the urban river–lake continuum remain unknown, posing challenges for assessing carbon sinks in aquatic ecosystems draining this unique urban characteristic. This study investigates the driving factors of diurnal variations of CO2 emission fluxes at the water–air interface in an urban river (Qingshangang, QSG) and a connected landscape lake (Lihu, LH). Continuous monitoring was conducted from 8:00 a.m. to 7:00 p.m. in July 2024 at both QSG and LH sites. The results reveal significant temporal and spatial differences in CO2 concentration and flux. The CO2 concentration in QSG (120.91 ± 93.99 μmol L−1) clearly exceeds that of LH (69.14 ± 51.09 μmol L−1), with an overall mean of 95.02 ± 69.69 μmol L−1 for the river–lake system as a whole. The CO2 flux at QSG (77.53 ± 64.59 mmol m−2 d−1) is significantly higher than that of LH (53.50 ± 37.32 mmol m −2 d −1), with a total average of 65.51 ± 54.10 mmol m −2 d −1. The concentrations and fluxes were significantly negatively correlated with environmental factors such as pH, dissolved oxygen (DO), percent dissolved oxygen (DO%), water temperature (Twater), chlorophyll (Chl-a), and chemical oxygen demand of manganese (CODMn), and significantly positively correlated with electrical conductivity (EC). DO%, EC, and Chl-a are the main environmental factors affecting CO2 flux by stepwise regression analysis. The considerably higher CO2 concentration and flux observed in the QSG can be attributed to carbon and nutrient inputs from its surrounding environment. Conversely, the lower CO2 flux in the connected lake is due to the effective restoration by aquatic plants. Our study underscores the importance of recognizing urban rivers as potential hotspots for CO2 emissions, thereby emphasizing the imperative for high-time-resolution monitoring efforts on these rivers in future research endeavors.