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Since they account for a significant share of industrial sector emissions, the greenhouse gas emissions reduction in the industrial sector is concentrated on energy-intensive industries. U2019 This article discusses the research gap between general, independent, emissions minimization strategies and organisation-specific plans developed using in-house or commercial software and/or energy management consultants. In updated Define-Measure-Process-Output-Customer framework, a Supplier-Input-Process-Output-Customer scheme is used to create a high-level, visual path to carbon freehood, indicating the source, input, processing, output, and customer for each carbon mitigation step. To generate modeling software output, the Analyse step requires an energy audit, as well as heat and renewable energy studies. The Improve step models the potential emissions reduction steps in order of priority order of effectiveness, new technology, heat recovery, and renewables, with the budget or timeline as the primary measure.
Source link: https://doi.org/10.3303/CET2294007
More than 21% of carbon dioxide emissions worldwide come from land-based industries. It is increasingly critical to identify and model the relationship between land-based industries and climate change, especially toward the carbon dioxide neutrality target or net-zero emission target. The boundary of land-based industries is vague, and the linkages between land-based sectors and carbon dioxide are not well understood. To narrow the research gaps, this paper examined the correlation between land-based industries and climate change as a result of climate change's transition toward carbon neutrality. This report provides a more complete picture of the relationship between land use and climate change.
Source link: https://doi.org/10.3303/CET2294092
This paper presents a BP neural network model for forecasting building CO2 emissions in light of previous studies of energy use and building CO 2 pollution from 1995 to 2019. The practical way to achieve the peak in building CO 2 emissions is explored by the scenario modeling technique. This paper therefore builds the estimation model of building carbon dioxide emissions and forecasts the future carbon emission value through the BP neural network in order to prevent the error caused by the nonlinear relationship between influencing factors and estimated value.
Source link: https://doi.org/10.3390/en15144950
However, the consequences of China's electricity trading on carbon dioxide have yet to be fully explored due to a lack of complete and balanced inter-provincial power transmission data. In the present study, the electricity generation model, logarithmic mean Divisia index model, and random forest clustering algorithm within a general framework were used to determine the effect of electricity trading on carbon dioxide levels, which was used to investigate the effect of electricity trading on carbon emissions. These findings provide a basis for decision makers to determine the contributions of electricity trading to the rise in carbon dioxide emissions from electricity generation, as well as a fund to investigate feasible carbon emission mitigation strategies in the power industry.
Source link: https://doi.org/10.3390/en15103601
Under this background, determining the carbon footprint of UMESs considering varying life cycle phases and carbon flow characteristics is vital for carbon reduction and environmental protection. The carbon flow matrixes of EHs are used in conjunction with the energy flow model to map the distribution of life-cycle carbon pollution in UMESs, according to this source. In addition, various assessment metrics, such as the device carbon distribution factor and customer carbon distribution coefficient, are also included to measure the carbon dioxide emissions of products and consumers in UMESs. About 60% of carbon emissions are delivered to electricity plants and EH systems, according to the test results, and nearly 35% of total carbon emissions at some periods account for nearly 35% of total carbon dioxide emissions at certain periods.
Source link: https://doi.org/10.3390/en15082946
PV installed capacity is forecast to reach 43. 7 GW in 2030, representing 52% of the 2030 domestic electricity production. While also achieving a 10% rise in overall EROI, the results also show that such energy transition policy may be highly effective at lowering California's domestic electricity grid mix carbon pollution by half and reducing demand for non-renewable primary energy by 66%.
Source link: https://doi.org/10.3390/en13153934
Taxis are significant contributors to carbon dioxide pollution due to their regular use, but new studies into taxi carbon emissions is insufficient. This report uses taxi GPS data to reconstruct taxi routes in Beijing. To get the dynamic spatiotemporal distribution of carbon dioxide emissions, we then use the carbon emission estimation model built on a taxi fuel consumption algorithm and the carbon dioxide emission factor. To calculate emissions and apply a visualization software called kernel density analysis. The Airport Expressway, Ring Roads, and major intersections within the 5th Ring Road network in the United States all produce more carbon dioxide than other areas.
Source link: https://doi.org/10.3390/en11030500
The most significant cause of airport air pollution is aircraft emissions. Optimizing aircraft taxiing paths is one of the key to reducing airport energy conservation and emission reductions. The traditional optimization technique based on the shortest taxi time is to model the aircraft under the assumption of uniform speed taxiing. This paper investigates the aircraft's taxiing distance, the number of big steering times, and collision avoidance in the taxi, and creates a path optimization tool for aircraft taxi taxiing at the airport surface in the shortest total taxi time as the target, in light of all of this. The total fuel consumption and emissions of the aircraft have been reduced by 35 percent and 46%, respectively, before optimization, and taxi time has been greatly reduced, thereby avoiding the taxiing conflict and minimizing emissions during the taxiing phase.
Source link: https://doi.org/10.3390/en12091649
SOC-regulated Soil organic carbon products multiple ecosystem services, including a sequestering service. Using information from the State Soil Geographic database, this report sought to determine the value of SOC stocks, based on the avoided SC-CO 2, in the contiguous United States by soil order, soil depth, land resource area, state, and region. Between $ 4. 64T : Mollisols, 2 Histosols $ 2. 31T, and 3 Alfisols $ 1. 48T is the total estimated monetary value for SOC storage in the contiguous United States. 2 Vertisols $ 21. 58 m u22122, 2 Vertisols $ 2. 26 m u22122, and 3 Mollisols $ 2. 08 m u22122. SOC standards normalized by area within soil order boundaries were ranked 1 Histosols $ 21. 58 m u22122 m u22122 yr22122 u22122 m u22122 y o y m y u22122 m u22122 m u22122 yu22122 ya ti22122 u22122 ya yu22122 ya tiyaz m u22122122122122122122122122122122122122122122122122122122122122122122122122122122122122122122122122122122122122122 According to the depth interval 100 -u22120 cm, the soil depth interval with the highest midpoint values of SOC storage and content was 20u2212100 cm $ 6. 18T and $ 0. 84 m u22122, respectively, while the depth interval 100 cm $ 6. 18 T and content $ 0. 39 million u22122. The LRRs with the highest midpoint SOC storage values were 1 M 20812 Central Feed Grains and Crop Region, 1 M T 1. 8 T 1. 1 T u2212, and 3 K u2212 Northern Lake State Forest and Forage Region $ 1. 16 T. 3 Midwest $ 3. 17T, 2 Southeast $ 2. 44T, and 3 Northern Plains $ 2. 35T were among the top midpoint values of SOC storage in the Midwest.
Source link: https://doi.org/10.3390/resources8030153
This report aims to investigate the drag effect of carbon emissions on China's economic growth by including carbon dioxide as an endogenous variable in an economic growth forecast and lowering the expectation that the size of the economy will remain unchanged. Carbon pollution's drag effect on urbanization is based on the inherent link between economic growth and urban growth, which is based on the inherent connection of urbanization. The drag effect of carbon pollution between 2003 and 2016 has a certain negative effect on China's urbanization process.
Source link: https://doi.org/10.3390/pr8091171
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