Large increases in emissions of methane and nitrous oxide from eutrophication in Lake Erie

AbstractEutrophication is linked to greenhouse gas emissions from inland waters. Phytoplankton blooms in Lake Erie, one of Earth’s largest lakes, have increased with nutrient runoff linked to climate warming, although greenhouse gas emissions from this or other large eutrophic lakes are not well characterized. We measured greenhouse gases around Lake Erie in all four seasons and found that CH4 and N2O emissions have increased 10 times or more with re-eutrophication, especially during and after phytoplankton blooms. Lake Erie is a positive source of CH4 throughout the entire year and around the entire lake, with the highest emissions in spring and summer near the mouth of the Maumee River. While Lake Erie is an overall N2O source, it is an N2O sink in winter throughout the lake and in some locations during large phytoplankton blooms. We estimate that Lake Erie emits ~6300 metric tons of CH4-C yr−1 (± 19%) and ~600 metric tons N2O-N yr−1 (± 37%): almost 500,000 metric tons CO2-eq yr−1 total. These results highlight the gravity of eutrophication-related increases in large lake GHG emissions: an overlooked, but potentially major feedback to global climate change.

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Climate Change-Greenhouse Gas Emissions Analysis and Forecast in Romania

Sustainability ◽

10.3390/su132112186 ◽

2021 ◽

Vol 13 (21) ◽

pp. 12186

Author(s):

Georgiana Moiceanu ◽

Mirela Nicoleta Dinca

Keyword(s):

Climate Change ◽

Carbon Dioxide ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Exponential Function ◽

Global Climate Change ◽

Function Analysis ◽

Global Climate ◽

Ghg Emissions ◽

Gas Emissions

Greenhouse gases (GHG), such as carbon dioxide, methane, nitrous oxide, and other gases, are considered to be the main cause of global climate change, and this problem has received significant global attention. Carbon dioxide has been considered the most significant gas contributing to global climate change. Our paper presents an analysis of the greenhouse gas emissions in Romania along with a forecast for the years to come. For the study, data from the National Institute of Statistics and Eurostat were gathered and used for the analysis in order to present the results. To obtain the results, the data gathered were analyzed using forecasting methods that can be of help in solving some uncertainties that surround the future. The greenhouse gas (GHG) emissions trends in Romania were analyzed both for linear and exponential function methods. The obtained results showed that the linear function analysis of total GHG emissions in Romania had a forecast accuracy higher than the exponential function method. From the analytical methods used we can draw the conclusion that the emissions are on a descending scale and choosing a proper method is important in analyzing data.

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Greenhouse gas emissions from the water–air interface of a grassland river: a case study of the Xilin River

Scientific Reports ◽

10.1038/s41598-021-81658-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Xue Hao ◽

Yu Ruihong ◽

Zhang Zhuangzhuang ◽

Qi Zhen ◽

Lu Xixi ◽

...

Keyword(s):

Carbon Dioxide ◽

Land Use ◽

Nitrous Oxide ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Ghg Emissions ◽

Nitrous Oxide Emissions ◽

Gas Emissions ◽

Sand Land ◽

Very High

AbstractGreenhouse gas (GHG) emissions from rivers and lakes have been shown to significantly contribute to global carbon and nitrogen cycling. In spatiotemporal-variable and human-impacted rivers in the grassland region, simultaneous carbon dioxide, methane and nitrous oxide emissions and their relationships under the different land use types are poorly documented. This research estimated greenhouse gas (CO2, CH4, N2O) emissions in the Xilin River of Inner Mongolia of China using direct measurements from 18 field campaigns under seven land use type (such as swamp, sand land, grassland, pond, reservoir, lake, waste water) conducted in 2018. The results showed that CO2 emissions were higher in June and August, mainly affected by pH and DO. Emissions of CH4 and N2O were higher in October, which were influenced by TN and TP. According to global warming potential, CO2 emissions accounted for 63.35% of the three GHG emissions, and CH4 and N2O emissions accounted for 35.98% and 0.66% in the Xilin river, respectively. Under the influence of different degrees of human-impact, the amount of CO2 emissions in the sand land type was very high, however, CH4 emissions and N2O emissions were very high in the artificial pond and the wastewater, respectively. For natural river, the greenhouse gas emissions from the reservoir and sand land were both low. The Xilin river was observed to be a source of carbon dioxide and methane, and the lake was a sink for nitrous oxide.

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

10.5194/egusphere-egu21-4474 ◽

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

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 (CO2) and methane (CH4) data from seven peatlands in Estonia collected during vegetation season in 2017&#8211;2020. Additionally, we used temperature and water table depth data measured in situ. We studied relationships between CO2, CH4, 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 (Reco) over drained and extracted sites than over intact ones. Over the extracted cites the correlation between Reco CO2 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 CO2 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.

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Energy Consumption and Greenhouse Gas Emissions of Nickel Products

Energies ◽

10.3390/en13215664 ◽

2020 ◽

Vol 13 (21) ◽

pp. 5664

Author(s):

Wenjing Wei ◽

Peter B. Samuelsson ◽

Anders Tilliander ◽

Rutger Gyllenram ◽

Pär G. Jönsson

Keyword(s):

Energy Consumption ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Process Model ◽

Ghg Emissions ◽

Primary Energy ◽

Nickel Metal ◽

Gas Emissions ◽

Nickel Smelting ◽

Ore Grade

The primary energy consumption and greenhouse gas emissions from nickel smelting products have been assessed through case studies using a process model based on mass and energy balance. The required primary energy for producing nickel metal, nickel oxide, ferronickel, and nickel pig iron is 174 GJ/t alloy (174 GJ/t contained Ni), 369 GJ/t alloy (485 GJ/t contained Ni), 110 GJ/t alloy (309 GJ/t contained Ni), and 60 GJ/t alloy (598 GJ/t contained Ni), respectively. Furthermore, the associated GHG emissions are 14 tCO2-eq/t alloy (14 tCO2-eq/t contained Ni), 30 t CO2-eq/t alloy (40 t CO2-eq/t contained Ni), 6 t CO2-eq/t alloy (18 t CO2-eq/t contained Ni), and 7 t CO2-eq/t alloy (69 t CO2-eq/t contained Ni). A possible carbon emission reduction can be observed by comparing ore type, ore grade, and electricity source, as well as allocation strategy. The suggested process model overcomes the limitation of a conventional life cycle assessment study which considers the process as a ‘black box’ and allows for an identification of further possibilities to implement sustainable nickel production.

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Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO2 and CH4 in situ observations in summer 2018

10.5194/egusphere-egu2020-3363 ◽

2020 ◽

Author(s):

Theresa Klausner ◽

Mariano Mertens ◽

Heidi Huntrieser ◽

Michal Galkowski ◽

Gerrit Kuhlmann ◽

...

Keyword(s):

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Urban Areas ◽

Ghg Emissions ◽

Capital City ◽

Detailed Knowledge ◽

Emission Flux ◽

Gas Emissions ◽

Mixing Ratios

Urban areas are recognised as a significant source of greenhouse gas emissions (GHG), such as carbon dioxide (CO2) and methane (CH4). The total amount of urban GHG emissions, especially for CH4, however, is not well quantified. Here we report on airborne in situ measurements using a Picarro G1301-m analyser aboard the DLR Cessna Grand Caravan to study GHG emissions downwind of the German capital city Berlin. In total, five aircraft-based mass balance experiments were conducted in July 2018 within the Urban Climate Under Change [UC]2 project. The detection and isolation of the Berlin plume was often challenging because of comparatively small GHG signals above variable atmospheric background concentrations. However, on July 20th enhancements of up to 4 ppm CO2 and 21 ppb CH4 were observed over a horizontal extent of roughly 45 to 65 km downwind of Berlin. These enhanced mixing ratios are clearly distinguishable from the background and can partly be assigned to city emissions. The estimated CO2 emission flux of 1.39 &#177; 0.75 t s-1 is in agreement with current inventories, while the CH4 emission flux of 5.20 &#177; 1.61 kg s-1 is almost two times larger than the highest reported value in the inventories. We localized the source area with HYSPLIT trajectory calculations and the high resolution numerical model MECO(n) (down to ~1 km), and investigated the contribution from sewage-treatment plants and waste deposition to CH4, which are treated differently by the emission inventories. Our work highlights the importance of a) strong CH4 sources in the surroundings of Berlin and b) a detailed knowledge of GHG inflow mixing ratios to suitably estimate emission rates.

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Model for Calculating Regional Energy use, Industrial Production and Greenhouse Gas Emissions for Evaluating Global Climate Scenarios

Image 2.0 ◽

10.1007/978-94-011-1200-0_3 ◽

1994 ◽

pp. 79-131 ◽

Cited By ~ 1

Author(s):

H. J. M. de Vries ◽

J. G. J. Olivier ◽

R. A. van den Wijngaart ◽

G. J. J. Kreileman ◽

A. M. C. Toet

Keyword(s):

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Industrial Production ◽

Energy Use ◽

Global Climate ◽

Climate Scenarios ◽

Gas Emissions ◽

Regional Energy

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

Transactions of the ASABE ◽

10.13031/trans.13668 ◽

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.

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Spatiotemporal Evolution of Global Greenhouse Gas Emissions Transferring via Trade: Influencing Factors and Policy Implications

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17145065 ◽

2020 ◽

Vol 17 (14) ◽

pp. 5065 ◽

Cited By ~ 1

Author(s):

Zhangqi Zhong ◽

Xu Zhang ◽

Weina Gao

Keyword(s):

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Global Climate ◽

Anthropogenic Activities ◽

Spillover Effects ◽

Economic Benefits ◽

Policy Implications ◽

Energy Structure ◽

Gas Emissions ◽

Factors Influencing

Global climate change caused by greenhouse gas emissions (GHGs) from anthropogenic activities have already become the focus of the world. A more systematic and comprehensive analysis on the factors influencing the changes of global GHGs transferring via trade have not been fully discussed. To this end, employing spatial econometric regression models and multi-regional input-output models, this paper reveals factors influencing the GHGs transferring via trade changes in 39 major economies, so as to develop the relevant GHGs reduction policies. The results indicate that regions with the highest net outflow of GHGs transferring via trade are primarily Russia and Canada, and the adverse effects of promoting GHGs reduction on the national economy could be avoided by these regions owing to trade relations. Additionally, factors influencing the changes in GHGs transferring via trade have significant spatial autocorrelation, and population size and energy structure exert significant spatial spillover effects on the changes in the GHGs transferring via trade. On this basis, this paper suggests that one more effective way to prevent trade from the rigorous demands of environmental governance measures while preserving the economic benefits of international trade may be to facilitate cooperation between countries on GHGs mitigation. Further, we articulate more balanced environment governance policies, including conducting the sharing of advanced energy technologies and developing clearer production technologies.

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Carbon Emissions of Hotels: The Case of the Sri Lankan Hotel Industry

Buildings ◽

10.3390/buildings9110227 ◽

2019 ◽

Vol 9 (11) ◽

pp. 227 ◽

Cited By ~ 1

Author(s):

Udara Willhelm Abeydeera ◽

Karunasena

Keyword(s):

Climate Change ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Carbon Emissions ◽

Global Climate ◽

Sri Lankan ◽

Gas Emissions ◽

Study Approach ◽

Mitigate Climate Change

The need to mitigate climate change has become a major global concern, and greenhouse gas emissions are a major cause of global climate change. Therefore, the need to curb greenhouse gas emissions has been well recognized by global researchers, policymakers and academics. Carbon emissions of hotel operations have seized the attention of global researchers. However, carbon emissions of the hotels in developing countries remain to be a less explored domain. Therefore, carbon emissions of Sri Lankan hotels were explored using a case study approach. Five hotels in the Colombo suburb were explored, which revealed that each hotel released more than 7000 tons of carbon annually. Results further indicated the use of purchased electricity as the dominant source of carbon emissions. Emissions caused by transport activities were not included in the calculations due to the unavailability of data. Recommendations were made to overcome the issues identified during data collection as well as to reduce the carbon emissions from hotel operations. Wider adoption of the methodology used in this research will benefit the hotels to keep track of the carbon emissions using a systematic approach.

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Application of Sterilization Process for Inactivation of Bacillus Stearothermophilus in Biomedical Waste and Associated Greenhouse Gas Emissions

Applied Sciences ◽

10.3390/app10155056 ◽

2020 ◽

Vol 10 (15) ◽

pp. 5056

Author(s):

Cevat Yaman

Keyword(s):

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Bacillus Stearothermophilus ◽

Ghg Emissions ◽

Biological Indicator ◽

Steam Treatment ◽

Waste Collection ◽

Gas Emissions ◽

Biomedical Waste ◽

Sterilization Process

This study investigated the biomedical waste collection, transportation, and treatment activities in the city of Kocaeli, Turkey. As an alternative to incineration technology, a steam autoclave was used to sterilize the biomedical waste. Information regarding the collection, transportation, treatment and associated greenhouse gas emissions (GHG) were also investigated. Prior to sterilization, biological indicator vials containing Bacillus stearothermophilus were placed in the center of the load to ensure that the pathogens were destroyed. GHG emissions were calculated based on the fuel consumed by the biomedical waste collection vehicles and the electricity/natural gas used at the sterilization plant. Results of this work revealed that the total biomedical waste generated per year increased from 1362 tons in 2009 to 2375 tons in 2019. The amount of biomedical waste generated per hospital bed was determined as 1.19 kg.bed−1.day−1. Results show that for efficient sterilization of biomedical wastes, the steam treatment system process should be operated at a contact time of 45 min, a temperature of 150 °C, and at a steam pressure of 5 bar. Biological indicator tests showed that the number of living Bacillus stearothermophilus decreased significantly, with removal rates greater than 6log10. Finally, it was determined that the biomedical waste management activities generated a total of GHG emissions of 5573 ton CO2 equivalency (tCO2-e) from 2009 to 2019. Furthermore, the average global warming factor (GWF) was calculated to be 0.269 tCO2-e per ton of biomedical waste generated. This study showed that the sterilization process is very effective in destroying the pathogens and the management of biomedical waste generates considerable amounts of GHG emissions.

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