Energy production and CO2 emissions: The case of coal fired power plants under China Pakistan economic corridor

Ali, Qurat ul Ain; Khayyam, Umer; Nazar, Umair

doi:10.1016/j.jclepro.2020.124974

Cited by 34 publications

(7 citation statements)

References 17 publications

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“…Further, Shabbir and Ahmad, 2016 [101] found water resources in the Rawalpindi region vulnerable to climatic and socio-economic factors. Similarly, studies for Multan, Sahiwal, and Lahore have reported their problems (e.g., crops productivity, floods, CO 2 discharge, land-use change, and pollution) [102][103][104][105][106][107]. The rest of the 32 districts have zero or negligible values in the 'very high' vulnerability zone.…”

Section: District Wise Comparison Of Eva Resultsmentioning

confidence: 99%

Investigating Eco-Environmental Vulnerability for China–Pakistan Economic Corridor Key Sector Punjab Using Multi-Sources Geo-Information

Kamran

Bian

et al. 2021

IJGI

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China-Pakistan economic corridor (CPEC), a critical part of the Belt and Road initiative (BRI), is subjected to rapid infrastructure development, which may lead to potential eco-environmental vulnerability. This study uses multi-source geo-information, and the multi-criteria decision-making (MCDM)-based best–worst method (BWM) to quantify the baseline eco-environmental vulnerability of one key CPEC sector—the Punjab province. The Punjab province is an important connection between northern and southern CPEC routes in Pakistan. In this study, we have established an indicator system consisting of twenty-two influential factors in a geospatial database to conduct eco-environmental vulnerability analysis. The overall setup is supported by a geographic information system (GIS) to perform spatial analysis. The resulting map was categorized into five vulnerability levels: very low, low, medium, high, and very high. The results revealed that the overall eco-environmental health of the Punjab province is reasonably good as 4.64% and 59.45% area of the key sector lies in ‘very low’ and ‘low’ vulnerability categories; however, there also exist highly vulnerable areas, particularly in the proximity of CPEC projects. Although high vulnerability areas constitute a very small percentage, only 0.08% of the Punjab province, still, decision-makers need to be aware of those regions and make corresponding protection strategies. Our study demonstrated that the MCDM-BWM-based EVA model could be effectively used to quantify vulnerability in other areas of CPEC. The findings of the study emphasize that management policies should be aligned with research-based recommendations for ecological protection, natural resource utilization, and sustainable development in regions participating in Belt and Road Initiative (BRI).

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Section: District Wise Comparison Of Eva Resultsmentioning

confidence: 99%

Investigating Eco-Environmental Vulnerability for China–Pakistan Economic Corridor Key Sector Punjab Using Multi-Sources Geo-Information

Kamran

Bian

et al. 2021

IJGI

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“…In the province of Sindh (Pakistan), the desert of Tharparker, a large deposit of coal reserves with 175 billion tons of good quality has been found. However, several factors have hindered the development of the thar coal reserves, including the depth and moisture level of the lignite reserves, a scarcity of fresh water, and a lack of road and power infrastructure 10,11 . Khan and Dessouky noted that biomass in Pakistan is gaining interest because it produces a similar type of fuel extracted from crude oil.…”

Section: Introductionmentioning

confidence: 99%

“…However, several factors have hindered the development of the thar coal reserves, including the depth and moisture level of the lignite reserves, a scarcity of fresh water, and a lack of road and power infrastructure. 10,11 Khan and Dessouky noted that biomass in Pakistan is gaining interest because it produces a similar type of fuel extracted from crude oil. Since biomass energy only depends on the availability of cheap raw materials.…”

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confidence: 99%

Artificial intelligence model of fuel blendings as a step toward the zero emissions optimization of a 660 MWe supercritical power plant performance

Amjad¹,

Ashraf

Uddin

et al. 2023

Energy Science & Engineering

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Accurately predicting fuel blends' lower heating values (LHV) is crucial for optimizing a power plant. In this paper, we employ multiple artificial intelligence (AI) and machine learning‐based models for predicting the LHV of various fuel blends. Coal of two different ranks and two types of biomass is used in this study. One was the South African imported bituminous coal, and the other was lignite thar coal extracted from the Thar Coal Block‐2 mine by Sind Engro Coal Mining Company, Pakistan. Two types of biomass, that is, sugarcane bagasse and rice husk, were obtained locally from a sugar mill and rice mill located in the vicinity of Sahiwal, Punjab. Bituminous coal mixture with other coal types and both types of biomass are used with 10%, 20%, 30%, 40%, and 50% weight fractions, respectively. The calculation and model development procedure resulted in 91 different AI‐based models. The best is the Ridge Regressor, a high‐level end‐to‐end approach for fitting the model. The model can predict the LHV of the bituminous coal with lignite and biomass under a vast share of fuel blends.

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“…It increases the amount of money paid by individuals for their electricity tariffs. This is coupled with increased energy consumption and a resulting emission increase from the power plants during power generation [8][9][10]. This is achieved when the rate at which heat is produced is equivalent to the rate at which it is dissipated.…”

Section: Introductionmentioning

confidence: 99%

An Overview of Thermal Insulation Material for Sustainable Engineering Building Application

Okokpujie¹,

Essien²,

Ikumapayi³

et al. 2022

IJDNE

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Residential buildings help to facilitate the occupants against solar radiation and adverse weather conditions. However, the growing increase in climate change in our environment has resulted in different side effects on human’s health mostly in the northern region of Nigeria and other parts of the world where high radiation from the sun are experience. This has resulted to the key interests of this research on possible thermal insulation materials that can help resist or absorb the solar radiation effects that can cause damage to lives in our community. This literature review of thermal insulation materials aims to proffer a sustainable solution by evaluating the thermal performance of building materials to provide an eco-friendly environment for building occupants. This research also discusses the Application of Thermal Insulation Materials for Developing Roofing sheets. The classification of thermal insulation materials, heat transfer in insulation materials, factors that influence the choice of building materials and thermal conductivity, resistivity, resistance, and conductance. Advantages of building insulation materials on economic, comfort, and environmental were also studied, and the reviewing of previous and incorporating thermal insulation materials with roofs. From the critical review, the application of insulating materials for developing building materials is highly recommended due to the provision of an eco-friending environment with reduced energy consumption during applications of home appliances.

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Energy production and CO2 emissions: The case of coal fired power plants under China Pakistan economic corridor

Cited by 34 publications

References 17 publications

Investigating Eco-Environmental Vulnerability for China–Pakistan Economic Corridor Key Sector Punjab Using Multi-Sources Geo-Information

Investigating Eco-Environmental Vulnerability for China–Pakistan Economic Corridor Key Sector Punjab Using Multi-Sources Geo-Information

Artificial intelligence model of fuel blendings as a step toward the zero emissions optimization of a 660 MWe supercritical power plant performance

An Overview of Thermal Insulation Material for Sustainable Engineering Building Application

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