Analysis Of Greenhouse Gas Emissions Research Articles

Characterisation analysis of national greenhouse gas emissions in DPR of Korea: emission trends for a 12-year period

Characterisation analysis of national greenhouse gas emissions in DPR of Korea: emission trends for a 12-year period

Energy demand and greenhouse gas emissions analysis in Colombia: A LEAP model application

Colombia represents that group of developing countries that is facing new challenges in energy demand due to climatic phenomena, technological changes and the growing use of renewable energy. This article presents a joint research work between the Unidad de Planeación Minero Energética - UPME (In Spanish) and the University of Bogotá Jorge Tadeo Lozano to analyze the energy demand and greenhouse gas emissions produced in Colombia. The study was conducted using the Long-Range Energy Alternatives Planning System (LEAP) software, through the construction of a model based on the year 2015 and with two future scenarios (positive and negative). The LEAP model is extrapolated until the years 2030 and 2050 to obtain the future predictions of the country's economic sectors: tertiary sector, industrial sector, housing sector and transport sector. The negative scenario is characterized by low economic growth and few incentives for technological change, which translates into low growth in energy efficiency, as well as a low substitution of petroleum-based energy. In contrast, in the positive scenario the economic growth of the sectors is greater and the technological substitution is accelerated which allows higher efficiency levels in the final use of energy and a greater migration towards cleaner technologies.

Embodied energy and greenhouse gas emissions analysis of a prefabricated modular house: The “Moby” case study

Buildings are big consumers of energy and materials, and important producers of waste and emissions. Prefabrication presents an opportunity to reduce impacts in the building sector; however, few studies have focused on prefabricated houses and with contradictory findings. The main goal of this article is to assess the embodied energy (EE) and greenhouse gas emissions (GHG) of a prefabricated modular house, based on a modular system to enable different layouts. A “cradle-to-site” analysis was performed, including materials production, transport to plant, modules’ production, transport to site and final assemblage on site. Several house final locations were addressed to assess transport related impacts. Scenarios for alternative building structural materials (steel; concrete; timber and light steel framing (LSF)) and house size (bedroom number) were also analyzed, aiming at understanding the influence of these aspects in the results, and representing other prefabricated modular houses currently produced in Europe. The calculated embodied impacts show that materials production is the most important phase (64–90% of EE and 59–87% of GHG) and that the structures with LSF framing or timber have the lowest impacts, while steel and concrete the highest. Embodied impacts increase with the house size; however, a larger house leads to lower impacts per inhabitant, but similar impacts per m2 (similar conclusion could be drawn for non-prefab buildings). The impacts of transportation (of modules, workers and finishing materials) vary significantly for the various house final locations and can be significant for overseas locations, which can jeopardize the potential benefits of modular prefabrication.

Comparative life-cycle cost and GHG emission analysis of five different water heating systems for residential buildings in Australia

In this paper, five different types of water heating systems namely electric instantaneous, electric storage, natural gas instantaneous, natural gas storage, and heat pump are studied for Australian conditions. The study is carried out for understanding the life cycle cost of each system under similar water demand conditions. The focus is made on life-cycle cost (LCC) that include the running costs on an annual basis, and total running cost for the system life, maintenance cost; and greenhouse gas (GHG) emissions. The observations reveal that five systems had major differences in the upfront cost, running cost, and life-cycle cost, and GHG emissions. The observed LCC and GHG emissions for electric instantaneous, electric storage, natural gas instantaneous, natural gas storage, and heat pump are 9005 AU$, 12,724 AU$, 6955 AU$, 7479 AU$, and 8098 AU$, and 1862 tons of CO2, 2306 tons of CO2, 851 tons of CO2, 917 tons of CO2, and 842 tons of CO2 respectively.

Spatial analysis of agricultural greenhouse gas emission at the municipality (LAU-2) level across Poland

Polska jest zobowiązana do corocznego raportowania krajowej emisji gazów cieplarnianych (GHG) w formie Krajowych Raportów Inwentaryzacyjnych (NIR) do Sekretariatu Konwencji Klimatycznej (UNFCCC). Całkowita emisja GHG w kraju pochodzi z wielu sektorów gospodarki. Jednym z nich jest rolnictwo. W prezentowanej pracy metodologia opracowana przez Międzyrządowy Zespół ds. Zmian Klimatu (IPCC) została użyta do oszacowania przestrzennego zróżnicowania emisji gazów cieplarnianych pochodzących z rolnictwa w całej Polsce na poziomie gmin. Obliczono wielkości emisji metanu, podtlenku azotu oraz dwutlenku węgla pochodzących z rolnictwa w każdej z 2173 polskich gmin. Następnie wielkości te zostały przeliczone na ekwiwalenty dwutlenku węgla, zsumowane i dzięki temu otrzymano całkowitą emisję z rolnictwa w każdej gminie. Autorzy pracy użyli danych na temat zasobów gospodarstw i charakterystyki systemów rolniczych w gminach ze Spisu Rolnego z 2010 roku (NAC2010), które zostały zebrane przez Główny Urząd Statystyczny w Polsce (GUS). Wyniki obliczeń naniesiono na mapę i po raz pierwszy dla Polski otrzymano rozkład przestrzenny emisji rolniczych gazów cieplarnianych na poziomie gmin. Największą emisję GHG z rolnictwa zaobserwowano w rejonach Podlasia i Wielkopolski. Jest ona związana z dużą intensywnością rolniczej produkcji zwierzęcej i roślinnej w tych rejonach.

Milk technology assessment based on greenhouse gas emissions

The resulted of determination greenhouse gas emissions under the tied maintenance of cattle and mechanized removal of manure when preparing byproducts for using with industrial production of cattle. The determination was made on the basis of the obtained data on the consumed gross energy of different sex and age groups of cattle, which was determined taking into account raw protein, raw fat, crude fiber and nitrogen-free extractives in the feed and biogenic elements of by-products. The determination was made taking into account the amount of food consumed and the yield of by-products. On the basis of the gross energy consumed by the animals and these byproducts, the values of methane emissions, direct and incidental nitrogen emissions were determined, both in absolute values and in the units per one conventional head and CO2 equivalent per year. With a herd of 703 heads, the consumption of gross energy per day was 1170435.38 mJ. The output of by-products per day is 12.300 kg. The output of by-products per day is 12.300 kg. The distribution of feeds with the tied content of cows is carried out by the mobile feed distributor KTU-10, directly into the feeding troughs. Manure from the stalls is raked manually into the manure channels, where the TSN-3B transporter is mounted, which removes it from the barn. It was determined that when the animals were tied in the Kharkiv region of Ukraine in the State Enterprise «Gontarovka», the emissions of greenhouse gases during the preparation of organic wastes of industrial milk production amounted to 16640.90 kg in CO2 equivalent per 1 head, while the annual emissions for the flock were as follows: methane — 8701156.055 СО2, and direct and indirect nitrogen emissions — 382.325 СО2. The results of the research will form the basis for the analysis of greenhouse gas emissions with various cattle technologies in order to identify technologies that can provide minimum greenhouse gas emissions.

Spatial analysis of energy use and GHG emissions from cereal production in India

Agriculture contributes 18% of India's greenhouse gas (GHG) emissions. Yet, little is known about the energy requirements of individual crops, making it difficult to link nutrition-enhancing dietary changes to energy consumption and climate change. We estimate the energy and CO2 intensity of food grains (rice, wheat, sorghum, maize, pearl millet and finger millet) taking into account their irrigation requirements, water source, dependence on groundwater, yields, fertilizer and machinery inputs.Rice is the most energy-intensive cereal, while millets are the least. Total energy use contributes 16% of GHG emissions for rice, due to its high methane emissions, and 56% for wheat. Fertilizer production and use dominates GHG emissions from all crops, contributing 52% of GHGs from cereals. Energy intensities vary by up to a factor of four across the country, due to varying water requirements, irrigation sources and groundwater table depths. The results suggest that replacing rice with other cereals has the potential to reduce energy consumption and GHGs, though the spatial variation of production shifts would influence the extent of this reduction and the possible trade-offs with total production.

Assessing the sustainability of biofuel production from camelina in Spain, results of the ITAKA project – analysis of GHG emissions

PurposeWith the rapid growth and increased consumption of biofuels worldwide, and the multitude of policy decisions supporting this expansion, growing concerns about the biofuels sustainability have arisen. Therefore, the European project “ITAKA”, aiming at supporting the development of aviation biofuels in an economically, socially and environmentally sustainable manner, has devoted considerable effort to take sustainability into account, in a quantitative and qualitative manner. This paper aims to calculate a robust assessment of a life-cycle greenhouse gas (GHG) for the entire ITAKA value chain.Design/methodology/approachThe calculation for the produced bio jet fuel has been set up using the roundtable on sustainable biomaterials (RSB) European Union (EU) renewable energy directive (RED) methodology, through the online RSB tool. This pathway includes feedstock production, feedstock processing, biofuel production, biofuel distillation and all transport steps involved.FindingsA significant reduction in GHG emissions has been demonstrated, up to 66 per cent emission reduction if one considers a mature pathway for the entire ITAKA biofuel chain.Practical implicationsThe camelina oil produced can be sustainable according to RSB and RSB EU RED schemes if the practices defined in the project are applied.Originality/valueApplication of different frameworks (actual vs theoretical) to the ITAKA value chain has aimed at testing and demonstrating the commercial application of the sustainability standards in Europe and the readiness of biofuels in Europe as a major means to decrease GHG emissions in aviation.

A GHG emissions analysis method for product remanufacturing: A case study on a diesel engine

Environmental change has become the most serious global problem in recent years. The increased greenhouse gas (GHG) emission is one of the consequences of environmental change. Remanufacturing of waste products constitutes a good production practice destined for environment protection. Nevertheless, GHG emissions are inevitably generated in the remanufacturing process. This study provides an insight into the characteristics of GHG emissions associated with product remanufacturing and presents a new analysis method for GHG emissions based on the Petri net, thus introducing a new theoretical concept for cleaner production of used products. In this method, the boundary of the GHG emission for product remanufacturing is defined, the dynamic characteristics of GHG emissions are analyzed, and the GHG emission analysis model is set up based on the Petri net. Based on this method, the GHG emissions in each remanufacturing process can be quantitatively analyzed. Accordingly, suggestions for energy conservation and GHG emission reduction are proposed. A WD615.87 diesel engine remanufacturing paradigm is presented as a case study throughout the text, whereby elicited results showed that the proposed method is effective in the analysis of GHG emissions for product remanufacturing.

Cradle-to-cooked-edible-meat analysis of greenhouse gas emissions

This study aimed to synthesize mean cradle-to-cooked-edible-meat greenhouse gas emission factors for bovine, ovine, pig, and poultry meat through a systematic review process. 64 studies involving 42 countries/regions, published between 1997 and 2015 were identified meeting selection criteria using Cochrane search strategies. Major emission activities were identified and synthesised into a cradle-to-cooked-edible-meat lifecycle system. 270 emission factors were identified from publications and taken as baselines. 67% baseline evaluation boundaries stopped at farm-gate, only 3% at home/restaurants. Baseline emission gaps were identified by comparing baseline evaluation systems against the synthesised system. Emission factors for major activities were identified from publications and mean values were used to fill emission gaps in order to obtain the cradle-to-cooked-edible-meat emission factors, which were then grouped to obtain a mean cradle-to-cooked-edible-meat emission factor for each meat type. Mean emission factors (kg CO2-eq/kg) for adjusted cradle-to-cooked-edible-meats were: Bovine 61.3 (n = 124), Ovine 61.2 (n = 38), Pig 15.8 (n = 56) and Poultry 9.4 (n = 52), which are significantly higher than the adjusted means for carcass at regional-distribution-centre: Bovine 23.9 (n = 118), Ovine 23.3 (n = 9), Pig 5.0 (n = 51) and Poultry 3.6 (n = 45); or the adjusted means for saleable meat at retail: Bovine 32.3 (n = 122), Ovine 31.2 (n = 36), Pig 7.9 (54), and Poultry 4.2 (n = 50). This study confirmed current meat emission evaluations reflect only a fraction of dietary impacts. Emission factors for cooked-edible-meat could be three times the amount of meat commodities at farm-gate. Emission factors vary significantly within and between meat types.

Decomposition analysis of corporate carbon dioxide and greenhouse gas emissions in Japan: Integrating corporate environmental and financial performances

AbstractRecent empirical studies often support the positive relationship between corporate environmental performance (CEP) in terms of carbon dioxide (CO2) and greenhouse gas (GHG) emissions and corporate financial performance (CFP). However, this depends on the measurements of CEP (the absolute and relative CEP) and CFP (accounting‐based and market‐based CFP). To understand the relationship structurally, based on the literature, this study proposes identity models that integrate CO2 and GHG emissions and financial factors. The models decompose CO2 (GHG) emissions into carbon intensity (GHG intensity), energy intensity, the cost‐to‐sales ratio, the total‐assets‐turnover ratio (TATR), leverage, and equity. The model of supply‐chain GHG emissions additionally adopts supply‐chain GHG intensity. As a decomposition method, this study uses the log‐mean Divisia index. As an application example of the CO2 model, this study targets Japanese manufacturing firms in 16 sectors from fiscal years (FY) 2011 to 2015. Results show that the change in CO2 emissions as of 2015 (−802.1 kilotonnes [kt]) is decomposed into 2922.5 kt for carbon intensity, −26036.3 kt for energy intensity, −6350.5 kt for the cost‐to‐sales ratio, −8495.6 kt for the TATR, −7912.3 kt for leverage, and 45070.1 kt for equity. Average values of relative contribution ratios are 20.6% for carbon intensity, 19.1% for energy intensity, and the remaining approximately 60% for financial factors. Among the 16 sectors, as of 2015, the change in total CO2 emission is statistically significantly positive for equity and significantly negative for the TATR and leverage.

On the Uncertainty Control in the Complex Multiphysics Systems in the Task of Multi-Scale Stochastic GHG and Carbon Balance Modeling

The problem of uncertainty analysis in complex multi-component systems is considered. The problem of decision making with uncertainty in tasks modeling carbon balance and the analysis of greenhouse gas (GHG) emissions using satellite tools was considered. Approaches to decision making under uncertainty are described in terms of interval, fuzzy, and stochastic assessments. Different approaches and algorithms to calculate carbon and GHG emissions are described. For every algorithm, errors and uncertainties are analyzed and estimated. Algorithms for uncertainty analysis based on integrated interlinked models of the system are presented. Algorithms for the analysis of components of vegetation productivity assessment using satellite data are proposed. Uncertainty component analysis allows the understanding of important properties of the system studied, and its feedback as to its anthropogenic load and impact on the climate. It was demonstrated that the comprehensive analysis of uncertainties allows not only the reduction of errors, but new knowledge about the studied systems.

Greenhouse gas emission monitoring system for manufacturing prefabricated components

Abstract Excessive greenhouse gas (GHG) emissions from construction stage pose an obvious and emerging challenge. Most previous studies on emissions from the construction phase only focused on emission prediction in advance of the actual construction activities or on quantitative analysis after building construction. A system that enables builders to monitor emissions from construction activities in real time is still lacked, although GHG emission monitoring (GEM) and analysis are considered as the top activities that must be performed to minimize excessive environmental impacts. As an initial exploration, this paper proposes a GEM system based on Internet of things (IoT) technology to real-time monitor emissions when manufacturing prefabricated components. In this system, Radio Frequency Identification (RFID) sensors are adopted to identify the component ID, and the corresponding material usage data are extracted from a database that is preset in the GEM system. Laser sensors are installed in the components production line to measure the running time of equipment so that energy usage can be calculated in real time. In addition, a data service platform was developed to implement wireless data transmission from production line to computing platform, where the monitoring results are visually presented. A production line of real-life prefabricated components in China is adopted to demonstrate that the IoT-based monitoring system can acquire and analyze real-time carbon emission data from the manufacturing process. The results indicate that GEM system can facilitate project teams to timely control irregular emissions, identify potential emission risks and explore possible strategies for minimizing carbon emissions in the construction sector.

Real-data-based high-resolution GHG emissions accounting of urban residents private transportation

ABSTRACTWorldwide, cities are monitoring their greenhouse gas emissions as a means to inform future greenhouse gas emissions mitigation policies and advance urban sustainability. Most urban GHG accounting frameworks provide data at the overall city scale. Studies have suggested that internal socioeconomic factors and location-specific spatial circumstances influence and shape urban greenhouse gas emissions emission volumes. This manuscript presents a comprehensive high-resolution spatial analysis of private vehicle travel-related greenhouse gas emissions of Tel Aviv-Jaffa (Israel) residents and explores some initial linkages to various socio-spatial explanatory factors. The studied city was divided into 1,121 small areas (ranging between 0.5 and 0.1 km2). Therefore, it allows exploring the extent to which the unique specific characteristics (social and spatial) of different parts of the city contribute to the private vehicles use levels and their rates of emissions, and identify areas that present different consumption patterns. This type of analysis can be used to advance tailored policies suitable for any socio-spatial circumstances as well as to examine existing and emerging approaches to greenhouse gas emissions mitigation and advancement of urban sustainability.

Simulation of macauba palm cultivation: an energy-balance and greenhouse gas emissions analysis

ABSTRACTThe expansion of the production and use of bioenergy is one of the most efficient mechanisms to reduce greenhouse gas (GHG) emissions. Nevertheless, the environmental impact of the production processes for many raw materials remains unexplored. Several studies have pointed to macauba palm as a promising species for biofuel production in the tropics, but investigations on the environmental benefits of its cultivation have not been reported so far. In this work, an analysis of macauba production system in terms of GHG emissions and CO2 uptake has been conducted for a productive cycle. The energy conversion efficiency per unit area of land has been put in relationship with crop productivity and related to the dilution effect of production inputs. Simulation results estimate GHG emissions of 180 Mg CO2eq·ha-1 and a CO2 fixation ranging from 796 to 1137 Mg CO2eq·ha-1. The net energy balance would reach 512.3 GJ·ha-1 and energy efficiency would be 24.2 GJ·GJ-1. These results suggest that macauba would outperform traditional energy crops such as sugarcane, oil palm, sunflower, corn or jatropha in terms of efficiency. The domestication and exploitation in extensive farming of this species as an agroforestry crop, although still at an early stage, has a bright future.

Role of linkage structures in supply chain for managing greenhouse gas emissions

This study describes a structural decomposition analysis (SDA) of Japanese greenhouse gas (GHG) emissions from 1990 to 2005, focusing on four linkage structures in the Leontief inverse representing supply chains in Japan. The developed RAS-invariant decomposition was applied to Japanese linked input–output tables for the three 5-year periods studied. It examined the effect of the Leontief inverse on emissions changes into the specific effects of forward linkage, backward linkage, the average of forward/backward linkage and kernel structure. Our SDA method solves the problem of parameter independence completely. The accuracy of those effects has been improved mathematically compared with conventional methods. For example, it was detected that backward linkage contributes to an increase in GHG emissions, while conventional methods erroneously determine a decrease. The results of the SDA confirmed that forward linkage and kernel structure contributed to a rise in GHG emissions, and that backward linkage consistently increased emissions in the three periods. Some sectors have robust linkage in the supply chain with consistently increasing emissions, which should be preferentially improved to mitigate their indirect GHG emissions in Japan.

Development and application of a life cycle greenhouse gas emission analysis model for mobile air conditioning systems

Mobile air conditioning (MAC) is potentially a huge source of greenhouse gas (GHG) emissions in China from a life cycle (LC) perspective as the vehicle population increases in the future. The MAC-GHG-LCA model is developed to calculate LC GHG emissions from MAC systems, covering life-span refrigerant leakage (direct emissions) and emissions caused by energy use in MAC system production and operation (indirect emissions). Using R152a and R1234yf as alternative refrigerants instead of R134a in MAC systems can decrease LC GHG emissions by 22–32% and 17–29%, respectively. Their GHG reduction benefits mainly result from their lower global warming potential (GWP) values though the indirect emissions are only slight lower or even higher than R134a. Using R744 can offer reduction in 2050 though it will cause an increase of 20% in 2020. Total LC GHG emissions from MAC systems of the whole light duty vehicle (LDV) fleet in China will be 159 million tonnes of CO2-equivalent in 2050 in the scenario where R134a will be the only refrigerant adopted, about 3 times that in 2015. It is found that alternative low-GWP refrigerants can help reduce LC GHG emissions from MAC systems effectively. The shift from conventional cooling and heating technology to advanced heat pump technology in electric vehicles (EVs) can reduce electricity use in MAC system operation and reduce LC GHG emissions from the MAC systems in EVs.

Analysis of life-cycle GHG emissions for iron ore mining and processing in China—Uncertainty and trends

Total iron ore demand in China grew to 1.1 billion tonnes in 2013 as a result of ongoing urbanization and massive infrastructure development. Iron ore and steel production are major sources for greenhouse gas (GHG) emissions. Since China has committed to lowering carbon intensity to meet climate change mitigation goals, detailed studies of the energy use and GHG emissions associated with iron ore mining and processing can aid in quantifying the impact and effectiveness of emissions reduction strategies. In this study, a life-cycle model for mining and processing of Chinese iron ores is developed and used to estimate GHG emissions. Results show that the mean life-cycle GHG emissions for Chinese iron ore production are 270 kg CO2e/tonne, with a 90% confidence interval ranging from 210 to 380 kg CO2e/tonne. The two largest contributors to overall GHG emissions are agglomeration (60%) and ore processing (23%). Iron content (ore grade) varies from 15% to 60% and is the largest contributor (40%) to the uncertainty of the results. Iron ore demand growth and the depletion of rich ore deposits will result in increased exploitation of lower grade ores with the concomitant increase in energy consumption and GHG emissions.

Systems-Level Analysis of Energy and Greenhouse Gas Emissions for Coproducing Biobased Fuels and Chemicals: Implications for Sustainability

In light of advances in the simultaneous production of biobased fuels and chemicals, a prospective well-to-wheel lifecycle assessment (LCA) model of a two-step multistage torrefaction biorefinery is constructed to quantify both lifecycle greenhouse gas (GHG) emissions and energy return on primary fossil energy investment (EROIfossil) for a transportation-range biofuel product. Coproducts—including cyclopentanone (CPO), biochar, and a potential net electricity export—are handled via six coproduct scenarios, evaluated across both market-based allocation and displacement methods. Process-scale performance metrics and product distributions are compared across cases to evaluate trade-offs between process and environmental performance; carbon flows are visualized to better explain patterns of carbon yield and waste. LCA results include median GHG values spanning from −30.8 to +36.1 g CO2e/MJ-fuel and median EROIfossil values ranging from 1.6 to 12.8 MJ-fuel/MJ-PEfossil. Sensitivity results for the Market CPO ca...

Development and application of China provincial road transport energy demand and GHG emissions analysis model

Energy consumption and greenhouse gas (GHG) emissions of China’s road transport sector have been increasing rapidly in recent years. Previous studies on the future trends trend to focus on the national picture and cannot offer regional insights. We build a novel bottom-up model to estimate the future energy demand and GHG emissions of China’s road transport at a provincial level, considering local economic development, population and policies. Detailed technical characteristics of the future vehicle fleets are analyzed in several up-to date scenarios. The results indicate that China’s vehicle stock will keep increasing to 543 million by 2050. The total direct petroleum demand and associated GHG emissions will peak at 508 million tonnes of oil equivalent (Mtoe) and 1500 million tonnes CO2 equivalent (Mt CO2,e) around 2030 in the Reference scenario. Natural gas vehicle diffusion has a large impact on petroleum demand reduction in the short term, with decreases of 41–46 Mtoe in 2050. Compared to the Reference case, battery electric and fuel cell vehicles will reduce petroleum demand by 94–157 and 28–54 Mtoe in 2050, respectively. When combined with decarbonization of future power supply, battery electric vehicles can play a significant role in reducing Well-to-Wheels GHG emissions in 2050 with 295–449 Mt CO2,e more reductions. The spatial distributions of future vehicle stock, energy demand and GHG emissions vary among provinces and show a generally downward trend from east to west. Policy recommendations are made in terms of the development of alternative fuels and vehicle technologies considering provincial differences, expansion of natural gas vehicle market and acceleration of electric vehicle market penetration.