scholarly journals Geographic Setting and Groundwater Table Control Carbon Emission from Indonesian Peatland: A Meta-Analysis

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 832
Author(s):  
Nisa Novita ◽  
Nurul Silva Lestari ◽  
Mega Lugina ◽  
Tatang Tiryana ◽  
Imam Basuki ◽  
...  
Keyword(s):  
Land Cover ◽  
Co2 Emissions ◽  
Water Table ◽  
Emission Reduction ◽  
Meta Analysis ◽  
Water Table Depth ◽  
Climate Mitigation ◽  
Soil Emissions ◽  
Emission Reduction Target ◽  
The Impact

Peat restoration is a key climate mitigation action for achieving Indonesia’s Nationally Determined Contribution (NDC) emission reduction target. The level of carbon reduction resulting from peat restoration is uncertain, owing in part to diverse methodologies and land covers. In this study, a meta-analysis was conducted to assess the impact of rewetting on reduction of total CO2 in soil and heterotrophic emissions at the country level. The tier 2 emission factor associated with the land cover category in Indonesia was also calculated. The analysis included a total of 32 studies with 112 observations (data points) for total CO2 emissions and 31 observations for heterotrophic emissions in Indonesia. The results show that the land cover category is not a significant predictor of heterotrophic and total soil emissions, but the highest observed soil emissions were found in the plantation forest. Using the random-effects model, our results suggest that an increase in the water table depth of 10 cm would result in an increase in total CO2 emissions of 2.7 Mg CO2 ha−1 year−1 and an increase in heterotrophic emissions of 2.3 Mg CO2 ha−1 year−1. Our findings show that managing water table depth in degraded peatlands in various land cover types is important to achieve Indonesia’s emission reduction target by 2030.

scholarly journals High soil solution carbon und nitrogen concentrations in a drained Atlantic bog are reduced to natural levels by 10 yr of rewetting

2013 ◽  
Vol 10 (10) ◽  
pp. 15809-15849 ◽  
Author(s):  
S. Frank ◽  
B. Tiemeyer ◽  
J. Gelbrecht ◽  
A. Freibauer
Keyword(s):  
Soil Solution ◽  
Water Table ◽  
Water Table Depth ◽  
Peat Layer ◽  
Deep Drainage ◽  
Dissolved Carbon ◽  
Total Dissolved Nitrogen ◽  
Natural Site ◽  
Nitrogen Concentrations ◽  
The Impact

Abstract. Artificial drainage of peatlands causes dramatic changes in the release of greenhouse gases and in the export of dissolved carbon (C) and nutrients to downstream ecosystems. Rewetting anthropogenically altered peatlands offers a possibility to reduce nitrogen (N) and C losses. In this study, we investigate the impact of drainage and rewetting on the cycling of dissolved C and N as well as on dissolved gases over a period of 1 yr and 4 month, respectively. The peeper technique was used to receive a high vertical sampling resolution. Within one Atlantic bog complex a near natural site, two drained grasslands sites with different mean water table positions, and a former peat cutting area rewetted 10 yr ago were chosen. Our results clearly indicate that drainage increased the concentration of dissolved organic carbon (DOC), ammonia, nitrate and dissolved organic nitrogen (DON) compared to the near natural site. Drainage depth further determined the release and therefore the concentration level of DOC and N species, but the biochemical cycling and therefore dissolved organic matter (DOM) quality and N species composition were unaffected. Thus, especially deep drainage can cause high DOC losses. In general, DOM at drained sites was enriched in aromatic moieties as indicated by SUVA280 and showed a higher degradation status (lower DOC to DON ratio) compared to the near natural site. At the drained sites, equal C to N ratios of uppermost peat layer and DOC to DON ratio of DOM in soil solution suggest that the uppermost degraded peat layer is the main source of DOM. Nearly constant DOC to DON ratios and SUVA280 values with depth furthermore indicated that DOM moving downwards through the drained sites remained largely unchanged. DON and ammonia contributed most to the total dissolved nitrogen (TN). The subsoil concentrations of nitrate were negligible due to strong decline in nitrate around mean water table depth. Methane production during the winter months at the drained sites moved downwards to areas which were mostly water saturated over the whole year (>40 cm). Above these depths, the recovery of the water table in winter months led to the production of nitrous oxide around mean water table depth at drained sites. 10 yr after rewetting, the DOM quality (DOC to DON ratio and SUVA280) and quantity were comparable to the near natural site, indicating the re-establishment of mostly pristine biochemical processes under continuously water logged conditions. The only differences occur in elevated dissolved methane and ammonia concentrations reflecting the former disturbance by drainage and peat extraction. Rewetting via polder technique seems to be an appropriate way to revitalize peatlands on longer timescales and to improve the water quality of downstream water bodies.

scholarly journals Carbon dioxide emissions from an <i>Acacia</i> plantation on peatland in Sumatra, Indonesia

2011 ◽  
Vol 8 (4) ◽  
pp. 8269-8302 ◽  
Author(s):  
J. Jauhiainen ◽  
A. Hooijer ◽  
S. E. Page
Keyword(s):  
Co2 Emissions ◽  
Water Table ◽  
Carbon Dioxide Emissions ◽  
Co2 Emission ◽  
Root Respiration ◽  
Water Table Depth ◽  
Rooting Zone ◽  
Before And After ◽  
Plantation Development ◽  
Peat Surface

Abstract. Peat surface CO2 emission, groundwater table depth and peat temperature were monitored for two years along transects in an Acacia plantation on thick tropical peat (>4 m) in Sumatra, Indonesia. A total of 2300 emission measurements were taken at 144 locations. The autotrophic root respiration component of the CO2 emission was separated from heterotrophic emissions caused by peat oxidation in three ways: (i) by comparing CO2 emissions within and beyond the tree rooting zone, (ii) by comparing CO2 emissions with and without peat trenching (i.e. cutting any roots remaining in the peat beyond the tree rooting zone), and (iii) by comparing CO2 emissions before and after Acacia tree harvesting. On average, the contribution of root respiration to daytime CO2 emission is 21 % along transects in mature tree stands. At locations 0.5 m from trees this is up to 80 % of the total emissions, but it is negligible at locations more than 1.3 m away. This means that CO2 emission measurements well away from trees are free of any root respiration contribution and thus represent only peat oxidation emission. We find daytime mean annual CO2 emission from peat oxidation alone of 94 t ha−1 yr−1 at a mean water table depth of 0.8 m, and a minimum emission value of 80 t ha−1 yr−1 after correction for the effect of diurnal temperature fluctuations, which resulted in a 14.5 % reduction of the daytime emission. There is a positive correlation between mean long-term water table depths and peat oxidation CO2 emission. However, no such relation is found for instantaneous emission/water table depth within transects and it is clear that factors other than water table depth also affect peat oxidation and total CO2 emissions. The increase in the temperature of the surface peat due to plantation development may explain over 50 % of peat oxidation emissions.

scholarly journals Can a regional-scale reduction of atmospheric CO<sub>2</sub> during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO<sub>2</sub> retrievals

2021 ◽  
Vol 14 (3) ◽  
pp. 2141-2166
Author(s):  
Michael Buchwitz ◽  
Maximilian Reuter ◽  
Stefan Noël ◽  
Klaus Bramstedt ◽  
Oliver Schneising ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Satellite Data ◽  
Emission Reduction ◽  
Regional Scale ◽  
Surface Fluxes ◽  
East China ◽  
Analysis Method ◽  
Transport Modelling ◽  
Scale Reduction ◽  
The Impact

Abstract. The COVID-19 pandemic resulted in reduced anthropogenic carbon dioxide (CO2) emissions during 2020 in large parts of the world. To investigate whether a regional-scale reduction of anthropogenic CO2 emissions during the COVID-19 pandemic can be detected using space-based observations of atmospheric CO2, we have analysed a small ensemble of OCO-2 and GOSAT satellite retrievals of column-averaged dry-air mole fractions of CO2, i.e. XCO2. We focus on East China and use a simple data-driven analysis method. We present estimates of the relative change of East China monthly emissions in 2020 relative to previous periods, limiting the analysis to October-to-May periods to minimize the impact of biogenic CO2 fluxes. The ensemble mean indicates an emission reduction by approximately 10 % ± 10 % in March and April 2020. However, our results show considerable month-to-month variability and significant differences across the ensemble of satellite data products analysed. For example, OCO-2 suggests a much smaller reduction (∼ 1 %–2 % ± 2 %). This indicates that it is challenging to reliably detect and to accurately quantify the emission reduction with current satellite data sets. There are several reasons for this, including the sparseness of the satellite data but also the weak signal; the expected regional XCO2 reduction is only on the order of 0.1–0.2 ppm. Inferring COVID-19-related information on regional-scale CO2 emissions using current satellite XCO2 retrievals likely requires, if at all possible, a more sophisticated analysis method including detailed transport modelling and considering a priori information on anthropogenic and natural CO2 surface fluxes.

scholarly journals Profitable Decarbonization through E-Mobility

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4042
Author(s):  
Gürkan Kumbaroğlu ◽  
Cansu Canaz ◽  
Jonathan Deason ◽  
Ekundayo Shittu
Keyword(s):  
Power Generation ◽  
Co2 Emissions ◽  
Emission Reduction ◽  
Large Scale ◽  
Cost Effective ◽  
Electricity Sector ◽  
Complex Relationships ◽  
The Cost ◽  
Relationship Of ◽  
The Impact

This paper focuses on the interdependent relationship of power generation, transportation and CO2 emissions to evaluate the impact of electric vehicle deployment on power generation and CO2 emissions. The value of this evaluation is in the employment of a large-scale, bottom-up, national energy modeling system that encompasses the complex relationships of producing, transforming, transmitting and supplying energy to meet the useful demand characteristics with great technological detail. One of such models employed in this analysis is the BUEMS model. The BUEMS model provides evidence of win-win policy options that lead to profitable decarbonization using Turkey’s data in BUEMS. Specifically, the result shows that a ban on diesel fueled vehicles reduces lifetime emissions as well as lifetime costs. Furthermore, model results highlight the cost-effective emission reduction potential of e-buses in urban transportation. More insights from the results indicate that the marginal cost of emission reduction through e-bus transportation is much lower than that through other policy measures such as carbon taxation in transport. This paper highlights the crucial role the electricity sector plays in the sustainability of e-mobility and the value of related policy prescriptions.

Valutazione economica di una politica di riorientamento dei consumi alimentari finalizzata alla riduzione dell'obesitŕ

2012 ◽  
pp. 75-98
Author(s):  
Rosaria Viscecchia ◽  
Antonio Stasi ◽  
Maurizio Prosperi
Keyword(s):  
Climate Change ◽  
Co2 Emissions ◽  
Meta Analysis ◽  
Economic Effect ◽  
Environmental Benefits ◽  
Food Demand ◽  
Partial Substitution ◽  
The European Union ◽  
Relevant Effect ◽  
The Impact

Modern lifestyle is one among the most relevant causes of alimentary disorder and environmental problems. Preventing both of them implies a win-win strategy for the improvement of social wellness (i.e. health and environmental benefits). A suitable strategy could be addressed to the partial substitution of caloric food (e.g. beef meat), which is also responsible for a large amount of greenhouse gas (ghgs) emissions, with less caloric food (e.g. vegetables), which is proved of exerting a lower impact on climate change. The analysis is referred to the Italian case study, based on data from the Italian Statistical Institute (istat). The relationship between obesity and ghgs emissions is here explained experimentally through a 5-stage methodology. In the first step, a regression model (ols method) is adopted to explain obesity rate in terms of ratio of people consuming meat more than once a week, and the ratio of people consuming vegetables less than once a day. The outcome of this analysis allows simulating a policy target in terms of obesity abatement, provided by a reasonable change in food demand. In the third step, a meta-analysis of Life Cycle Assessment (lca) studies has been performed in order to calculate the CO2 emissions of the food types we considered. In the fourth step, the observed change in food demand from the previous step is combined with lca indicators, in order to evaluate the impact of food industry on climate change. Finally, in the fifth step, the benefits of the obesity reduction are calculated considering the cost saving for health care of the obesity, which amounts to 1.700 Eur per person. In addition, the value of the CO2 emission have been compared with the value of the European Union Allowance (eua) of CO2 emissions, which was evaluated in 2009 in terms of 21.45 eur/t CO2. Consequently, we found that the effect of the policy can be estimated in terms of 1,032 Million eur, of which the impacts on human health is the most important (about 1.020 Million eur). The study shows the evidence that the consumption of food with low content of calories has a most relevant effect in the reduction of obesity, but very limited economic effect in terms of CO2 emissions.

scholarly journals RZ-TRADEOFF: A New Model to Estimate Riparian Water and Air Quality Functions

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 769 ◽  
Author(s):  
Hassanzadeh ◽  
Vidon ◽  
Gold ◽  
Pradhanang ◽  
Lowder
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Land Cover ◽  
Water Table ◽  
Best Management Practices ◽  
Management Practices ◽  
Overland Flow ◽  
Subsurface Flow ◽  
Riparian Zones ◽  
The Impact

Riparian zones are often used as best management practices due to their ability to remove nitrate (NO3−) from subsurface flow. Research suggests that beyond local biogeochemical controls, the impact of riparian zones on nitrogen removal and other functions, such as phosphorus dynamics and greenhouse gas emissions, largely depends on land-use/land-cover, hydrogeomorphology, and weather. In this study, we therefore present RZ-TRADEOFF, a novel and easily applicable model that connects multiple riparian functions and characteristics (NO3− and phosphate (PO43−), concentration and removal in subsurface flow, total phosphorus (TP) removal in overland flow, nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2) emissions, water table) to landscape hydrogeomorphic characteristics, weather, and land-cover/land-use. RZ-TRADEOFF was developed with data from past studies and digital databases, and validated with data collected from the literature. Three functions (water table, PO43− and CO2) were observed to be significantly influenced by climate/weather, while the others were primarily influenced by hydrogeomorphology and land use. The percent bias and normalized root mean square error respectively were −3.35% and 0.28 for water table, 16.00% and 0.34 for NO3− concentration, −7.83% and 20.82 for NO3− removal, 6.64% and 0.35 for PO43− concentration, 2.55% and 0.17 for TP removal, 40.33% and 0.23 for N2O, 72.68% and 0.18 for CH4, and −34.98% and 0.91 for CO2. From a management standpoint, RZ-TRADEOFF significantly advances our ability to predict multiple water and air quality riparian functions using easily accessible data over large areas of the landscape due to its scalability.

scholarly journals Examining the Impact and Influencing Channels of Carbon Emission Trading Pilot Markets in China

2021 ◽  
Vol 13 (10) ◽  
pp. 5664
Author(s):  
Qiong Wu ◽  
Kanittha Tambunlertchai ◽  
Pongsa Pornchaiwiseskul
Keyword(s):  
Co2 Emissions ◽  
Emission Intensity ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Emission Trading ◽  
So2 Emission ◽  
Green Development ◽  
Carbon Emission Trading ◽  
The Impact ◽  
Trading Policy

As China has an important role in global climate change, the Chinese government has set goals to improve its environmental efficiency and performance and launched carbon emission trading pilot markets in 2013, aiming to reduce CO2 emissions. Based on panel data of 30 provinces from 2005 to 2017, this paper uses the difference-in-difference method to study the impact of China’s carbon emission trading pilot markets on carbon emissions and regional green development. The paper also explores possible influencing channels. The main conclusions are as follows: (1) China’s carbon emission trading policy has promoted a reduction in CO2 emissions and carbon emission intensity and has increased green development in the pilot areas. (2) The main path for China’s carbon emission trading policy to achieve carbon emission reduction and regional green development is to promote technology adoption. (3) China’s carbon emission trading policy achieves green development through synergistic SO2 emission reduction. The pilot carbon markets have reduced both the amount of SO2 emissions and SO2 emission intensity.

scholarly journals Temporal water table changes in soil toposequence of the Poznań Lakeland (western Poland)

2017 ◽  
Vol 68 (4) ◽  
pp. 167-173
Author(s):  
Michał Kozłowski ◽  
Jolanta Komisarek
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Water Table ◽  
Root Zone ◽  
Linear Regression Analysis ◽  
Temporal Trends ◽  
Water Table Depth ◽  
The Mean ◽  
The Impact

Abstract The paper presents results of determination of temporal changes in water table depths in the toposequence of Retisols/Luvisols and Phaeozems/Gleysols. Assessment of temporal trends in the water table depth was made with the use of the linear regression analysis. The results obtained indicate that the mean water table depth and mean high and low water table depths were deeper in the soil at the upper part of the slope in comparison with soil located at the footslope. A higher amplitude of water table was observed in Retisols than in Gleysols but the highest variability of water table level was noted in the soils at the footslope compared to those at the slope summit. In Retisols, with each month of observation from 1993 to 2012, the water table showed a tendency to increase. These trends were the highest from January to April, which may be related to the tendency of increasing monthly sums of precipitation in December, January and February. In the Gleysol at the footslope, in the period 1993–2012 and in the vegetation season, the water table depth showed a tendency to decrease. This trend may be due to the impact of water table on the soil water content at the root zone, which is used in the process of evapotranspiration.

scholarly journals Large-scale regionalization of water table depth in peatlands optimized for greenhouse gas emission upscaling

2014 ◽  
Vol 18 (9) ◽  
pp. 3319-3339 ◽  
Author(s):  
M. Bechtold ◽  
B. Tiemeyer ◽  
A. Laggner ◽  
T. Leppelt ◽  
E. Frahm ◽  
...  
Keyword(s):  
Land Cover ◽  
Boundary Conditions ◽  
Water Level ◽  
Water Table ◽  
Ghg Emissions ◽  
Water Table Depth ◽  
Water Levels ◽  
Predictor Variables ◽  
Organic Soils ◽  
Depth Information

Abstract. Fluxes of the three main greenhouse gases (GHG) CO2, CH4 and N2O from peat and other soils with high organic carbon contents are strongly controlled by water table depth. Information about the spatial distribution of water level is thus a crucial input parameter when upscaling GHG emissions to large scales. Here, we investigate the potential of statistical modeling for the regionalization of water levels in organic soils when data covers only a small fraction of the peatlands of the final map. Our study area is Germany. Phreatic water level data from 53 peatlands in Germany were compiled in a new data set comprising 1094 dip wells and 7155 years of data. For each dip well, numerous possible predictor variables were determined using nationally available data sources, which included information about land cover, ditch network, protected areas, topography, peatland characteristics and climatic boundary conditions. We applied boosted regression trees to identify dependencies between predictor variables and dip-well-specific long-term annual mean water level (WL) as well as a transformed form (WLt). The latter was obtained by assuming a hypothetical GHG transfer function and is linearly related to GHG emissions. Our results demonstrate that model calibration on WLt is superior. It increases the explained variance of the water level in the sensitive range for GHG emissions and avoids model bias in subsequent GHG upscaling. The final model explained 45% of WLt variance and was built on nine predictor variables that are based on information about land cover, peatland characteristics, drainage network, topography and climatic boundary conditions. Their individual effects on WLt and the observed parameter interactions provide insight into natural and anthropogenic boundary conditions that control water levels in organic soils. Our study also demonstrates that a large fraction of the observed WLt variance cannot be explained by nationally available predictor variables and that predictors with stronger WLt indication, relying, for example, on detailed water management maps and remote sensing products, are needed to substantially improve model predictive performance.

scholarly journals Trade in the Carbon-Constrained Future: Exploiting the Comparative Carbon Advantage of Swedish Trade

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3613
Author(s):  
Hana Nielsen ◽  
Astrid Kander
Keyword(s):  
Co2 Emissions ◽  
Carbon Intensity ◽  
Climate Mitigation ◽  
Efficient Production ◽  
Annual Data ◽  
Low Carbon ◽  
Welfare Gains ◽  
Electricity System ◽  
Sectoral Differences ◽  
The Impact

This paper introduces a new concept of comparative carbon advantage as a potential climate mitigation tool. According to the concept, welfare gains in terms of reduced global CO2 emissions can be achieved by exploiting cross-country sectoral differences in carbon intensity and decarbonized electricity system. The paper empirically tests the concept by utilizing annual data of Sweden between 1995 and 2008. Overall, the results show that Sweden contributed nearly 590 million tons of potential CO2 emissions savings through its exports by having an efficient and low-carbon production and electricity system. This total amount of 590 million tons of CO2 emissions relates to the total savings made if the same amount and composition of Swedish exports was produced using the world average technology. Furthermore, the contribution of Sweden’s low carbon electricity generation was over 34% of the total savings, of which some 20% were direct exports of electricity and 80% was electricity embodied in exported products. This research provides a critical understanding of the impact of efficient production and low carbon electricity in generating relative comparative carbon advantage—a policy relevant aspect for the increasingly globalized, and carbon-constrained, world.

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