How do greenhouse gas emissions vary with biofertilizer type and soil temperature and moisture in a tropical grassland?

Pedosphere ◽  
2020 ◽  
Vol 30 (5) ◽  
pp. 607-617
Author(s):  
Abmael da Silva CARDOSO ◽  
Juliana Bega JUNQUEIRA ◽  
Ricardo Andrade REIS ◽  
Ana Claudia RUGGIERI
Keyword(s):  
Soil Temperature ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Gas Emissions ◽  
Tropical Grassland ◽  
Soil Temperature And Moisture

Remotely sensed temperature is a proxy of greenhouse gas emissions in intact and managed peatlands

2021 ◽  
Author(s):  
Ain Kull ◽  
Iuliia Burdun ◽  
Gert Veber ◽  
Oleksandr Karasov ◽  
Martin Maddison ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Water Table ◽  
Ecosystem Respiration ◽  
Ghg Emissions ◽  
Remotely Sensed ◽  
Water Table Depth ◽  
Gas Emissions

<p>Besides water table depth, soil temperature is one of the main drivers of greenhouse gas (GHG) emissions in intact and managed peatlands. In this work, we evaluate the performance of remotely sensed land surface temperature (LST) as a proxy of greenhouse gas emissions in intact, drained and extracted peatlands. For this, we used chamber-measured carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>) data from seven peatlands in Estonia collected during vegetation season in 2017–2020. Additionally, we used temperature and water table depth data measured in situ. We studied relationships between CO<sub>2</sub>, CH<sub>4</sub>, in-situ parameters and remotely sensed LST from Landsat 7 and 8, and MODIS Terra. Results of our study suggest that LST has stronger relationships with surface and soil temperature as well as with ecosystem respiration (R<sub>eco</sub>) over drained and extracted sites than over intact ones. Over the extracted cites the correlation between R<sub>eco</sub> CO<sub>2</sub> and LST is 0.7, and over the drained sites correlation is 0.5. In natural sites, we revealed a moderate positive relationship between LST and CO<sub>2</sub> emitted in hollows (correlation is 0.6) while it is weak in hummocks (correlation is 0.3). Our study contributes to the better understanding of relationships between greenhouse gas emissions and their remotely sensed proxies over peatlands with different management status and enables better spatial assessment of GHG emissions in drainage affected northern temperate peatlands.</p>

Comparison of RZWQM2 and DNDC Models to Simulate Greenhouse Gas Emissions under Combined Inorganic/Organic Fertilization in a Subsurface-Drained Field

2020 ◽  
Vol 63 (4) ◽  
pp. 771-787
Author(s):  
Qianjing Jiang ◽  
Zhiming Qi ◽  
Chandra A. Madramootoo ◽  
Ward Smith ◽  
Naeem A. Abbasi ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Water Content ◽  
Soil Water Content ◽  
Ghg Emissions ◽  
Measured Data ◽  
Gas Emissions ◽  
N Management ◽  
Better Than

HighlightsRZWQM2 was compared with DNDC to predict greenhouse gas emissions.RZWQM2 was applied to simulate the greenhouse gas emissions under manure application.RZWQM2 performed better than DNDC in simulating soil water content and CO2 emissions.Abstract. N management has the potential to mitigate greenhouse gas (GHG) emissions. Process-based models are promising tools for evaluating and developing management practices that may optimize sustainability goals as well as promote crop productivity. In this study, the GHG emission component of the Root Zone Water Quality Model (RZWQM2) was tested under two different types of N management and subsequently compared with the Denitrification-Decomposition (DNDC) model using measured data from a subsurface-drained field with a corn-soybean rotation in southern Ontario, Canada. Field-measured data included N2O and CO2 fluxes, soil temperature, and soil moisture content from a four-year field experiment (2012 to 2015). The experiment was composed of two N treatments: inorganic fertilizer (IF), and inorganic fertilizer combined with solid cattle manure (SCM). Both models were calibrated using the data from IF and validated with SCM. Statistical results indicated that both models predicted well the soil temperature, but RZWQM2 performed better than DNDC in simulating soil water content (SWC) because DNDC lacked a heterogeneous soil profile, had shallow simulation depth, and lacked crop root density functions. Both RZWQM2 and DNDC predicted the cumulative N2O and CO2 emissions within 15% error under all treatments, while the timing of daily CO2 emissions was more accurately predicted by RZWQM2 (RMSE = 0.43 to 0.54) than by DNDC (RMSE = 0.60 to 0.67). Modeling results for N management effects on GHG emissions showed consistency with the field measurements, indicating higher CO2 emissions under SCM than IF, higher N2O emissions under IF in corn years, but lower N2O emissions in soybean years. Overall, RZWQM2 required more experienced and intensive calibration and validation, but it provided more accurate predictions of soil hydrology and better timing of CO2 emissions than DNDC. Keywords: CO2 emission, Corn-soybean rotation, Inorganic fertilization, Manure application, N2O emission, Process-based modeling.

scholarly journals Impact of Grazing Intensity and Seasons on Greenhouse Gas Emissions in Tropical Grassland

Ecosystems ◽  
2016 ◽  
Vol 20 (4) ◽  
pp. 845-859 ◽  
Author(s):  
Abmael da Silva Cardoso ◽  
Liziane de Figueiredo Brito ◽  
Estella Rosseto Janusckiewicz ◽  
Eliane da Silva Morgado ◽  
Rondineli Pavezzi Barbero ◽  
...  
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Grazing Intensity ◽  
Gas Emissions ◽  
Tropical Grassland

Low-Carbon Russia: Prospects after the Crisis

2009 ◽  
pp. 107-120 ◽  
Author(s):  
I. Bashmakov
Keyword(s):  
Economic Growth ◽  
Potential Energy ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Low Carbon ◽  
Modeling Tools ◽  
Gas Emissions ◽  
Scenario Approach

On the eve of the worldwide negotiations of a new climate agreement in December 2009 in Copenhagen it is important to clearly understand what Russia can do to mitigate energy-related greenhouse gas emissions in the medium (until 2020) and in the long term (until 2050). The paper investigates this issue using modeling tools and scenario approach. It concludes that transition to the "Low-Carbon Russia" scenarios must be accomplished in 2020—2030 or sooner, not only to mitigate emissions, but to block potential energy shortages and its costliness which can hinder economic growth.

Ecological specificities of the interaction between animal breeding and climate changes, caused by greenhouse gas emissions

2017 ◽  
Vol 4 (3) ◽  
pp. 62-72
Author(s):  
O. Zhukorsky ◽  
O. Nykyforuk ◽  
N. Boltyk
Keyword(s):  
Greenhouse Gases ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Climatic Conditions ◽  
Animal Breeding ◽  
Gas Emissions ◽  
Climate Conditions ◽  
Emissions Inventory ◽  
Theoretical Substantiation ◽  
Global Problems

Aim. Proper development of animal breeding in the conditions of current global problems and the decrease of anthropogenic burden on environment due to greenhouse gas emissions, caused by animal breeding activity, require the study of interaction processes between animal breeding and external climatic conditions. Methods. The theoretical substantiation of the problem was performed based on scientifi c literature, statistical informa- tion of the UN Food and Agriculture Organization and the data of the National greenhouse gas emissions inventory in Ukraine. Theoretically possible emissions of greenhouse gases into atmosphere due to animal breeding in Ukraine and specifi c farms are calculated by the international methods using the statistical infor- mation about animal breeding in Ukraine and the economic-technological information of the activity of the investigated farms. Results. The interaction between the animal breeding production and weather-and-climate conditions of environment was analyzed. Possible vectors of activity for the industry, which promote global warming and negative processes, related to it, were determined. The main factors, affecting the formation of greenhouse gases from the activity of enterprises, aimed at animal breeding production, were characterized. Literature data, statistical data and calculations were used to analyze the role of animal breeding in the green- house gas emissions in global and national framework as well as at the level of specifi c farms with the consid- eration of individual specifi cities of these farms. Conclusions. Current global problems require clear balance between constant development of sustainable animal breeding and the decrease of the carbon footprint due to the activity of animal breeding.

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