Energy Consumption and Energy-Related CO2 Emissions from China’s Petrochemical Industry Based on an Environmental Input-Output Life Cycle Assessment

Ling, Meng; Sager, Jalel

doi:10.3390/en10101585

Cited by 15 publications

(9 citation statements)

References 13 publications

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“…Recently, Meng and Sager (2017) provided a global view of China's petrochemical industry's energy consumption and CO 2 emissions by using an EIO-LCA model from both production and demand perspectives. The method permits the authors to calculate not only the direct energy consumption and energy-related CO 2 emissions, but also the indirect amounts that can be tracked throughout the supply chain.…”

Section: Eio-lca Applied To Chemicalsmentioning

confidence: 99%

The Availability of Suitable Datasets for the LCA Analysis of Chemical Substances

Righi

Pozzo

Tugnoli

et al. 2020

Life Cycle Assessment in the Chemical Product Chain

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The practicality of adopting Life Cycle Assessment to support decision-making can be limited by the resource-intensive nature of data collection and Life Cycle Inventory modelling.The number of chemical products increases continuously and long-term analyses show that overall growth of chemicals demand and production as well as faster growth in emerging regions is a trend that is expected to continue in the future. Regrettably, chemical inventories are typically among the most challenging to model because of the lack of available data and the large number of material and energy flows. This explains why it is so important for the Life Cycle Assessment community to have effective methods to implement life cycle inventories of chemicals available.This chapter deals with the issues of Life Cycle Inventory analysis for chemical processes and the related lack of data concerning inventories of basic and fine chemicals substances. The overall aim of the chapter is to illustrate the different possibilities/approaches that the scientific Life Cycle Assessment community has developed in order to overcome such a lack of data concerning the inventories of a specific (basic and/or fine) chemical substance both for input and output flows. Their main advantages and drawbacks are identified and discussed briefly.

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Section: Eio-lca Applied To Chemicalsmentioning

confidence: 99%

The Availability of Suitable Datasets for the LCA Analysis of Chemical Substances

Righi

Pozzo

Tugnoli

et al. 2020

Life Cycle Assessment in the Chemical Product Chain

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show abstract

“…Life cycle assessment (LCA) is a system-oriented tool to control and monitor all project phases and processes over the project life cycle. The process-based LCA method (P-LCA) [42], EIO-LCA method [43], and hybrid LCA methods [44] are three common methods to environmental assess the impacts of projects. The P-LCA is commonly applied according to guidelines and principles proposed by the International Standards Organization (ISO) while the EIO-LCA is a top-down approach.…”

Section: Green Roofs Scharf and Kraus (2019) [3]mentioning

confidence: 99%

Building a Decision-Making Support Framework for Installing Solar Panels on Vertical Glazing Façades of the Building Based on the Life Cycle Assessment and Environmental Benefit Analysis

et al. 2020

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Glazing is considered as a preferred solution for the buildability, aesthetic, and comfort of commercial buildings since glass cover can protect occupants from external environmental conditions, ensure the light transmission, and provide view and ventilation. At the same time, in the context of climate change and global warming, the use of renewable solar energy, such as solar and wind power, are encouraged to be utilized. Specifically, solar energy has become a renewable energy source that is clean and endless, at reasonable cost, to contribute to energy security as well as ensure sustainable development. Therefore, the study proposes a method for supporting the decision making in installing solar panels on vertical glazing façades of the building in the worst case that the remaining radiant energy from the sun was only transferred to the inside of the building. The Life Cycle Assessment and the Life Cycle Costing methodologies are applied to consider both environmental and economic aspects. The proposed method can (1) minimize the project cost (including initial investment cost and operation cost) during the building lifetime; (2) analyze the optimal budget to minimize the total life-cycle cost of the building over its lifespan and maximize the renewable energy generated from the sunlight entering buildings in different directions. The results show that with different initial investments, the investor will have a corresponding solution for choosing an optimal installation ratio for each type of glass combined with the installation ratio of solar panels on the façades to reach the optimal energy efficiency as well as environmental performance. This study is beneficial for investors in selecting energy-saving solutions in office buildings in the beginning phase of the project life cycle.

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“…Substantial CO 2 emissions can bring about adverse effects on the natural environment. Moreover, the use of fossil fuel is the main origin of CO 2 emissions, which poses significant challenges to environmental protection in the context of securing worldwide energy supplies [6].…”

Section: Introductionmentioning

confidence: 99%

Decomposition and Forecasting of CO2 Emissions in China’s Power Sector Based on STIRPAT Model with Selected PLS Model and a Novel Hybrid PLS-Grey-Markov Model

Cui

Zhao

2018

Energies

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China faces significant challenges related to global warming caused by CO2 emissions, and the power industry is a large CO2 emitter. The decomposition and accurate forecasting of CO2 emissions in China’s power sector are thus crucial for low-carbon outcomes. This paper selects seven socio-economic and technological drivers related to the power sector, and decomposes CO2 emissions based on two models: the extended stochastic impacts by regression on population, affluence and technology (STIRPAT) model and the partial least square (PLS) model. Distinguished from previous research, our study first compares the effects of eliminating the multicollinearity of the PLS model with stepwise regression and ridge regression, finding that PLS is superior. Further, the decomposition results show the factors’ absolute elasticity coefficients are population (2.58) > line loss rate (1.112) > GDP per capita (0.669) > generation structure (0.522) > the urbanization level (0.512) > electricity intensity (0.310) > industrial structure (0.060). Meanwhile, a novel hybrid PLS-Grey-Markov model is proposed, and is verified to have better precision for the CO2 emissions of the power sector compared to the selected models, such as ridge regression-Grey-Markov, PLS-Grey-Markov, PLS-Grey and PLS-BP (Back propagation neutral network model). The forecast results suggest that CO2 emissions of the power sector will increase to 5102.9 Mt by 2025. Consequently, policy recommendations are proposed to achieve low-carbon development in aspects of population, technology, and economy.

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Energy Consumption and Energy-Related CO2 Emissions from China’s Petrochemical Industry Based on an Environmental Input-Output Life Cycle Assessment

Cited by 15 publications

References 13 publications

The Availability of Suitable Datasets for the LCA Analysis of Chemical Substances

The Availability of Suitable Datasets for the LCA Analysis of Chemical Substances

Building a Decision-Making Support Framework for Installing Solar Panels on Vertical Glazing Façades of the Building Based on the Life Cycle Assessment and Environmental Benefit Analysis

Decomposition and Forecasting of CO2 Emissions in China’s Power Sector Based on STIRPAT Model with Selected PLS Model and a Novel Hybrid PLS-Grey-Markov Model

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