scholarly journals A Study of Carbon Dioxide Emission in Different Types of Peatland Use in Kalimantan

2015 ◽  
Vol 18 (1) ◽  
pp. 9
Author(s):  
Nyahu Rumbang
Keyword(s):  
Carbon Dioxide ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Sweet Corn ◽  
Aloe Vera ◽  
Groundwater Table ◽  
West Kalimantan ◽  
Central Kalimantan ◽  
Different Types ◽  
Corn Plants

Study of carbon dioxide emissions in different types of peatlands use in Central and West Kalimantan has been conducted in January-June 2006 and January-April 2007. The study represents 4 types of land use in Central Kalimantan as treatment: 5 years for chinesse cabbage, 10 years for chinesse cabbage, 5 years for sweet corns, and 10 years for sweet corns. As for the treatments in West Kalimantan, they include corn field, Aloe vera field, oil palm plantation, and rubber plantation. Carbon dioxide was measured using infrared gas analysis (model EGM-4, PP systems, Hitchin, UK). In Central Kalimantan, the highest CO2 is emitted from sweet corn plants (arable land for 10 years) by 0.79 g CO2/m2/hour, chinesse cabbage plants (for 5 years) by 0.73 g CO2/m2/hour, chinesse cabbage plants (for 10 years) by 0.67 g CO2/m2/hour and, the least, sweet corn plants (for 5 years) by 0.41 g CO2/m2/hour. The highest CO2 emission from West Kalimantan is released from rubber plants at 1.22 g CO2/m2/hour, followed by palm oil plants by 0.96 g CO2/m2/hour, Aloe vera plants by 0.68 g CO2/m2/hour and corn plants by 0.35 g CO2/m2/hour. Groundwater table depth are the most important factors among other factors that influence CO2 emissions. Groundwater table depth indicated a positive correlation with CO2 emissions in all types of peatlands use. C-organic production of sweet corn plants at 11.66 t C/ha/year is higher than that of chinesse cabbage plants at 1.64 t C/ha /year. Corn plants produce organic-C was 11.66 t C/ha/year, equivalent to the amount of loss of C through CO2 emissions by 11.29 t C/ha/year.Keywords: peat, types of land use, carbon, CO2 emission

scholarly journals The Effect of Paraquat, Difenoconazole, and Butylphenyl Methylcarbamate (BPMC) on CO2 Emissions and Phenolic Acids in Peat Soil

2017 ◽  
Vol 22 (2) ◽  
pp. 77-85
Author(s):  
Indri Hapsari Fitriyani ◽  
Syaiful Anwar ◽  
Arief Hartono ◽  
Diah Tjahyandari
Keyword(s):  
Soil Sample ◽  
Co2 Emissions ◽  
Phenolic Acids ◽  
Soil Ph ◽  
Phenolic Acid ◽  
Co2 Emission ◽  
Oxidation Reaction ◽  
Peat Soil ◽  
Ch4 Emission ◽  
Central Kalimantan

Pesticides are widely used in agriculture, including on peat soil. The objective of this study was to analyze the effect of the application of paraquat, difenoconazole, and butylphenyl methylcarbamate (BPMC) on CO2 emissions and concentrations of phenolic acids in a peat soil. Peat soil sample was taken in District of Pulang Pisau, Central Kalimantan. The peat soil was applied with 1.89 mg kg-1 paraquat, 1.72 mg kg-1 difenoconazole and 1.65 mg kg-1 butylphenyl methylcarbamate (BPMC), then the soil was incubated for 1, 2, 4 , 5, 7, 10, 14, 21, 26 and 30 days. The results showed that the application of pesticides on peat soil increased CO2emission, and decreased CH4 emission and phenolic acid concentrations up to 30 days of incubation. The CO2 emmisions were derived from C of degraded pesticides and from C of phenolic acids, although the oxidation reaction was not accompanied by the change of soil pH. Keyword: CO2 emission, phenolic acids, butylphenyl methylcarbamate (BPMC), difenoconazole, paraquat, peat soil

scholarly journals Soil characteristics and CO2 emissions of ex-burnt peatland in Kubu Raya District, West Kalimantan, Indonesia

2020 ◽  
Vol 21 (8) ◽  
Author(s):  
Dwi Astiani ◽  
TRI WIDIASTUTI ◽  
SITI LATIFAH ◽  
DARBIN SIMATUPANG
Keyword(s):  
Carbon Dioxide ◽  
Co2 Emissions ◽  
Carbon Dioxide Emissions ◽  
Peat Soil ◽  
Carbon Sources ◽  
Chemical Properties ◽  
Soil Characteristics ◽  
Available Phosphorus ◽  
West Kalimantan ◽  
Burnt Site

Abstract. Astiani D, Widiastuti T, Latifah S, Simatupang D. 2020. Soil characteristics and CO2 emissions of ex-burnt peatland in Kubu Raya District, West Kalimantan, Indonesia. Biodiversitas 21: 3691-3698. West Kalimantan, Indonesia has a large extent of tropical peatland with total ​​1.74 million ha with only 44.5% of such areas remaining as peat forest, while the rests have been converted into plantations, agricultural lands, and shrubs. The conversion of peat forest often uses fires to clear the vegetation and is followed by building canal to drain the water. The lack of vegetation combined with drought soil trigger uncontrolled escaped fire, especially in the dry season or El-Nino events, which is likely to affect soil characteristics and emit carbon dioxide. The purpose of this study is to examine the changes in soil characteristics both physical and chemical properties and to investigate CO2 emissions from peat soil post-fire. As a comparison, similar parameters were also assessed in non-burnt sites. The results showed significant differences in some peat soil characters both physically and chemically between ex-burnt and non-burnt peatland. The ex-burnt site had higher pH, available phosphorus and C/N ratio than those in the non-burnt site. Conversely, the total nitrogen and carbon contents, and cation exchange capacity were lower which is likely due to leaching. Peat fires also impacted physical characteristics of the soil such as increasing soil bulk density, reducing soil water content, soil temperature, especially in wet conditions. Carbon dioxide emissions in the ex-burnt site were considered higher than non-burnt site. These results could be brought out as a part of baseline data in managing ex-burnt peatlands to maintain a balance between carbon output and input and efforts on preventing peatland fires from becoming continuous carbon sources.

scholarly journals Distribution of Cadmium in Sweet Corn Grown on a Peat Soil and Its Implication on Food Safety

2018 ◽  
Vol 23 (1) ◽  
pp. 27-33
Author(s):  
Rini Susana ◽  
Denah Suswati
Keyword(s):  
Zea Mays ◽  
Sweet Corn ◽  
Agricultural Soils ◽  
Peat Soil ◽  
Grain Filling ◽  
West Kalimantan ◽  
Dry Ashing ◽  
Safe Limit ◽  
Corn Plants ◽  
The Village

Cadmium (Cd) is a heavy metal that can contaminate agricultural soils, in which one of the sources of Cd in agricultural soils is the use of phosphate fertilizers. Some plant species are known to have the ability to accumulate large amounts of Cd in their organs despite the Cd content in soil is relatively small. Cadmium distribution in various organs of plants also shows a diverse variation. Maize is able to accumulate Cd in its organs, either in roots, leaves or grains. This study aims to determine the distribution of Cd in sweet corn plants grown on a peat soil. Samples of maize plants were taken from nine maize fields in the village of Rasau Jaya 1, Rasau Jaya subdistrict, Kubu Raya district, West Kalimantan. The cultivars of sweet corn planted were Zea mays saccharata cultivar Bonanza and Zea mays saccharata cultivar Secada. Samples for roots, leaves, stems and panicles were taken at the stage of early grain filling. Grain samples were taken at the phase of fresh pod consumption. The Cd contents in the plant organ tissues were determined using dry ashing method. The  results showed that the distribution of Cd in plant organs of sweet corn cultivars Secada and Bonanza follows the pattern of Cd in leaves > roots > grains > panicles > stems. The leaves contain the highest concentration of Cd, while the stems contain the lowest amount of Cd. The Cd concentration in leaves is about 3.5 times higher than that in grains, and 1.5 times higher than that in roots. The average Cd content in grains of sweet corn  is 0.037 mg kg-1, which is still below the safe limit of Cd content in grains allowed by the Standar Nasional Indonesia, i.e. 0.2 mg kg-1.   

scholarly journals Enhancing water levels of degraded, bare, tropical peatland in West Kalimantan, Indonesia: Impacts on CO2 emission from soil respiration

2018 ◽  
Vol 19 (2) ◽  
pp. 472-477
Author(s):  
DWI ASTIANI ◽  
BURHANUDDIN BURHANUDDIN ◽  
EVI GUSMAYANTI ◽  
TRI WIDIASTUTI ◽  
MUHAMMAD J. TAHERZADEH
Keyword(s):  
Soil Respiration ◽  
Co2 Emissions ◽  
Water Table ◽  
Carbon Emissions ◽  
Co2 Emission ◽  
Water Levels ◽  
Small Scale ◽  
West Kalimantan ◽  
Tropical Peatland ◽  
Water Tables

Astiani D, Burhanuddin, Gusmayanti E, Widiastuti T, Taherzadeh MJ. 2018. Enhancing water levels of degraded, bare, tropical peatland in West Kalimantan, Indonesia: Impacts on CO2 emission from soil respiration. Biodiversitas 19: 472-477. The major drivers of deforestation in West Kalimantan have been the development for large or small-scale expansion of agricultural activities; the establishment of oil palm and other plantations; fire; and degradation of forests particularly from industrial logging. Our previous research findings have shown that such activities in affected peatland areas have lowered the water table levels (down to 0.5-1.0 m depths), and have significantly increased CO2 emissions from the peat soils. It has been demonstrated that unmanaged, lowered water tables in peatlands act as one of the main factors inflating soil carbon emissions - an issue that has assumed global significance in recent decades. Regulating peatland water tables has the potential to mitigate degraded peatland carbon emissions as well as improve the hydrological functions for communities who farm the peatlands. However, we are still uncertain exactly how much impact controlled raising of the peatlands water tables will have on reducing soil CO2 emissions. The research described here aimed to mitigate CO2 emissions by raising and regulating water levels on drained peatland to restore and enhance its hydrological functions. The results confirmed that raising the water table significantly decreases CO2 emissions and improves water availability and management for crop production in the coastal peatland of Kubu Raya district, West Kalimantan. Water levels previously at 60cm below the soil surface were regulated to raise the watertable up to just 30 cm below the surface and this reduced peatland carbon emissions by about 49%. However, longer-term monitoring is required to ensure that the hydrological benefits and CO2 mitigation can be sustained.

scholarly journals Neural-network-based estimation of regional-scale anthropogenic CO<sub>2</sub> emissions using an Orbiting Carbon Observatory-2 (OCO-2) dataset over East and West Asia

2021 ◽  
Vol 14 (11) ◽  
pp. 7277-7290
Author(s):  
Farhan Mustafa ◽  
Lingbing Bu ◽  
Qin Wang ◽  
Na Yao ◽  
Muhammad Shahzaman ◽  
...  
Keyword(s):  
Neural Network ◽  
Carbon Dioxide ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Net Primary Productivity ◽  
Regional Scale ◽  
Mitigation Strategies ◽  
Generalized Regression Neural Network ◽  
Anthropogenic Co2 ◽  
East And West

Abstract. Atmospheric carbon dioxide (CO2) is the most significant greenhouse gas, and its concentration is continuously increasing, mainly as a consequence of anthropogenic activities. Accurate quantification of CO2 is critical for addressing the global challenge of climate change and for designing mitigation strategies aimed at stabilizing CO2 emissions. Satellites provide the most effective way to monitor the concentration of CO2 in the atmosphere. In this study, we utilized the concentration of the column-averaged dry-air mole fraction of CO2, i.e., XCO2 retrieved from a CO2 monitoring satellite, the Orbiting Carbon Observatory-2 (OCO-2), and the net primary productivity (NPP) provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the anthropogenic CO2 emissions using the Generalized Regression Neural Network (GRNN) over East and West Asia. OCO-2 XCO2, MODIS NPP, and the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) CO2 emission datasets for a period of 5 years (2015–2019) were used in this study. The annual XCO2 anomalies were calculated from the OCO-2 retrievals for each year to remove the larger background CO2 concentrations and seasonal variability. The XCO2 anomaly, NPP, and ODIAC emission datasets from 2015 to 2018 were then used to train the GRNN model, and, finally, the anthropogenic CO2 emissions were estimated for 2019 based on the NPP and XCO2 anomalies derived for the same year. The estimated and the ODIAC CO2 emissions were compared, and the results showed good agreement in terms of spatial distribution. The CO2 emissions were estimated separately over East and West Asia. In addition, correlations between the ODIAC emissions and XCO2 anomalies were also determined separately for East and West Asia, and East Asia exhibited relatively better results. The results showed that satellite-based XCO2 retrievals can be used to estimate the regional-scale anthropogenic CO2 emissions, and the accuracy of the results can be enhanced by further improvement of the GRNN model with the addition of more CO2 emission and concentration datasets.

scholarly journals Social and Economic Factors of Industrial Carbon Dioxide in China: From the Perspective of Spatiotemporal Transition

2021 ◽  
Vol 13 (8) ◽  
pp. 4268
Author(s):  
Jingyuan Li ◽  
Jinhua Cheng ◽  
Beidi Diao ◽  
Yaqi Wu ◽  
Peiqi Hu ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Co2 Emissions ◽  
Spatial Data ◽  
Emission Reduction ◽  
Co2 Emission ◽  
Carbon Dioxide Emission ◽  
Spatial Data Analysis ◽  
Co2 Emission Reduction ◽  
Intensity Effect ◽  
Industrial Carbon

The reduction of CO2 emission has become one of the significant tasks to control climate change in China. This study employs Exploratory Spatial Data Analysis (ESDA) to identify the provinces in China with different types of spatiotemporal transition, and applies the Logarithmic Mean Divisia Index (LMDI) to analyze the influencing factors of industrial CO2 emissions. Spatial autocorrelation of provincial industrial CO2 emissions from 2003 to 2017 has been demonstrated. The results are as follows: (1) 30 provinces in China are categorized into 8 types of spatiotemporal transition, among which 24 provinces are characterized by stable spatial structure and 6 provinces show significant spatiotemporal transition; (2) For all types of spatiotemporal transition, economic scale effect is mostly contributed to industrial CO2 emission, while energy intensity effect is the most crucial driving force to reduce industrial carbon dioxide emission; (3) provinces of type HH-HH, HL-HL and HL-HH are most vital for CO2 emission reduction, while the potential CO2 emission increase of developing provinces in LL-LL, LH-LH and LL-LH should also be taken into account. Specific measures for CO2 emission reduction are suggested accordingly.

scholarly journals Management of Environmental Performance and Impact of the Carbon Dioxide Emissions (CO2) on the Economic Growth in the GCC Countries

2019 ◽  
pp. 252-268 ◽  
Author(s):  
H. Dkhili ◽  
L. B. Dhiab
Keyword(s):  
Economic Growth ◽  
Carbon Dioxide ◽  
Co2 Emissions ◽  
Environmental Performance ◽  
Carbon Dioxide Emissions ◽  
Environmental Kuznets Curve ◽  
Co2 Emission ◽  
Kuznets Curve ◽  
Gcc Countries ◽  
Integration Test

This paper summarizes the arguments and counterarguments within the scientific discussion on the issue the Management of Environmental Performance and the Carbon Dioxide Emissions (CO2) on the Economic Growth, with an innovative study in the context of the GCC countries. The main goal of the paper is to examine empirically the environmental Kuznets curve hypothesis for the GCC countries. The methodological tool of this contribution tries to measure the effect of the emission of the CO2 on the Growth Economic and environmental performance. The main purpose of the research is focused on the empirical approach justified by the use of a dynamic panel modeling on a sample of the GCC countries during the period of 2002-2018. Systematization literary sources and approaches for solving the problem of the reaction of the development of the Environmental Performance with the level of the the Carbon Dioxide Emissions (CO2) and the economic growth. The study employed a GMM model system. Subsequently, the authors displayed a Panel Co-integration test of Pedroni (2004), the Kao Residual Co-integration test (1999), and the Granger causality tests. The results found unidirectional causal relationships between economic growth and the entire variable of the sample, except the variable CO2 emission. These relationships are statistically significant at the level of 5%. For the relation between Economic Growth and CO2 emission, one the hypothesis of the paper was checking a non-significant and unidirectional relationship. The results showed a long-run unidirectional causality between the variables and implied that Economic Growth in the GCC countries has a positive and significant unidirectional relation with Environment Performance, trade openness, foreign direct investment, and investment. The results confirm the existence of a negative relationship as insignificant, and unidirectional, between economic growth and CO2 emissions in the GCC countries. Finally, this finding doesn’t support the validity of the EKC hypothesis and provide information's to take the necessary policy suggestions to maintain the environmental performance and limit the average of the CO2 emissions. The results of the research can be useful for the GCC countries to avoid the higher level of Carbon Dioxide Emissions (CO2) and maintain a good Environmental Performance. Keywords: environmental performance, Environmental Kuznets Curve, CO2 emissions.

scholarly journals Neural Network Based Estimation of Regional Scale Anthropogenic CO<sub>2</sub> Emissions Using OCO-2 Dataset Over East and West Asia

2021 ◽  
Author(s):  
Farhan Mustafa ◽  
Lingbing Bu ◽  
Qin Wang ◽  
Na Yao ◽  
Muhammad Shahzaman ◽  
...  
Keyword(s):  
Neural Network ◽  
Carbon Dioxide ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Anthropogenic Activities ◽  
Regional Scale ◽  
Mitigation Strategies ◽  
Generalized Regression Neural Network ◽  
Anthropogenic Co2 ◽  
East And West

Abstract. Atmospheric carbon dioxide (CO2) is the most significant greenhouse gas and its concentration is continuously increasing mainly as a consequence of anthropogenic activities. Accurate quantification of CO2 is critical for addressing the global challenge of climate change and designing mitigation strategies aimed at stabilizing the CO2 emissions. Satellites provide the most effective way to monitor the concentration of CO2 in the atmosphere. In this study, we utilized the concentration of column-averaged dry-air mole fraction of CO2 i.e., XCO2 retrieved from a CO2 monitoring satellite, the Orbiting Carbon Observatory 2 (OCO-2) to estimate the anthropogenic CO2 emissions using Generalized Regression Neural Network over East and West Asia. OCO-2 XCO2 and the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) CO2 emission datasets for a period of 5 years (2015–2019) were used in this study. The annual XCO2 anomalies were calculated from the OCO-2 retrievals for each year to remove the larger background CO2 concentrations and seasonal variabilities. Then the XCO2 anomaly and ODIAC emission datasets from 2015 to 2018 were used to train the GRNN model, and finally, the anthropogenic CO2 emissions were estimated for 2019 based on the XCO2 anomalies derived for the same year. The XCO2-based estimated and the ODIAC actual CO2 emissions were compared and the results showed a good agreement in terms of spatial distribution. The CO2 emissions were estimated separately over East and West Asia. In addition, correlations between the ODIAC emissions and XCO2 anomalies were also determined separately for East and West Asia, and East Asia exhibited relatively better results. The results showed that satellite-based XCO2 retrievals can be used to estimate the regional scale anthropogenic CO2 emissions and the accuracy of the results can be enhanced by further improvement of the GRNN model with the addition of more CO2 emission and concentration datasets.

scholarly journals Revealing Urban Carbon Dioxide (CO2) Emission Characteristics and Influencing Mechanisms from the Perspective of Commuting

2019 ◽  
Vol 11 (2) ◽  
pp. 385 ◽  
Author(s):  
Huihui Wang ◽  
Weihua Zeng
Keyword(s):  
Carbon Dioxide ◽  
Co2 Emissions ◽  
Urban Areas ◽  
Co2 Emission ◽  
Urban Transport ◽  
Emission Characteristics ◽  
Factors Affecting ◽  
Ring Road ◽  
Increasing Trend ◽  
Carbon Dioxide Co2

Commuting to and from work is one of the most important and regular routines using urban transport, being a major source for an increase in transport-related carbon dioxide (CO2) emissions. In this study, we explore the characteristics of CO2 emissions from commuter travel in Beijing from different perspectives. A bottom-up approach from a macro perspective is used to analyze recent changing trends of carbon emissions due to commuter travel modes in Beijing, and to identify the main sources of carbon emission increases that affect transportation. To identify CO2 emission characteristics and influencing mechanisms in Beijing, the proportion of commuting modes, commuting distance, and commuting-related CO2 emissions by Ring Roads was analyzed. The commuting-related CO2 emission model, based on Tobit models from the microscopic perspective, was constructed to explore the main factors affecting CO2 emissions of individuals/households. Results show that CO2 emissions due to commuting in Beijing in recent years has presented an increasing trend. In 2014, the amount of CO2 emissions from commuters had already reached the level of 553.68 × 104 t, with CO2 emissions generated by car trips accounting for 75–80% of emissions. Average individual/household commuting-related CO2 emissions on the Ring Road inside the main urban areas of Beijing shows a gradual increasing trend, with the growth trends between the 3rd–5th Ring Road being the largest. Household locations separated by Ring Roads and the occupation type of residents are important factors affecting CO2 emissions. Commuters with access to a car, those having a higher income, and those located in the outer regions of the main urban areas produce more CO2 emissions. To reduce the increasing trend of CO2 emissions in Beijing, it is important that the government accelerates the development of public transport, industry, and residential facilities along the outskirts of the city, along the Ring Road, and along the radix road.

scholarly journals Current and future CO<sub>2</sub> emissions from drained peatlands in Southeast Asia

2010 ◽  
Vol 7 (5) ◽  
pp. 1505-1514 ◽  
Author(s):  
A. Hooijer ◽  
S. Page ◽  
J. G. Canadell ◽  
M. Silvius ◽  
J. Kwadijk ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Southeast Asia ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Management Practices ◽  
Greenhouse Gas Emission ◽  
Land Development ◽  
Climate Mitigation ◽  
Tropical Peatland ◽  
Carbon Dioxide Co2

Abstract. Forested tropical peatlands in Southeast Asia store at least 42 000 Million metric tonnes (Mt) of soil carbon. Human activity and climate change threatens the stability of this large pool, which has been decreasing rapidly over the last few decades owing to deforestation, drainage and fire. In this paper we estimate the carbon dioxide (CO2) emissions resulting from drainage of lowland tropical peatland for agricultural and forestry development which dominates the perturbation of the carbon balance in the region. Present and future emissions from drained peatlands are quantified using data on peatland extent and peat thickness, present and projected land use, water management practices and decomposition rates. Of the 27.1 Million hectares (Mha) of peatland in Southeast Asia, 12.9 Mha had been deforested and mostly drained by 2006. This latter area is increasing rapidly because of increasing land development pressures. Carbon dioxide (CO2) emission caused by decomposition of drained peatlands was between 355 Mt y−1 and 855 Mt y−1 in 2006 of which 82% came from Indonesia, largely Sumatra and Kalimantan. At a global scale, CO2 emission from peatland drainage in Southeast Asia is contributing the equivalent of 1.3% to 3.1% of current global CO2 emissions from the combustion of fossil fuel. If current peatland development and management practices continue, these emissions are predicted to continue for decades. This warrants inclusion of tropical peatland CO2 emissions in global greenhouse gas emission calculations and climate mitigation policies. Uncertainties in emission calculations are discussed and research needs for improved estimates are identified.

Sign in / Sign up

Export Citation Format

Share Document