2022 International Conference on Environmental Science and Green Energy (ICESGE)最新文献_第3页

Research on the Evaluation Method of Emission Reduction Value of Power System Investment 电力系统投资减排价值评价方法研究

2022 International Conference on Environmental Science and Green Energy (ICESGE) Pub Date : 2022-12-09 DOI: 10.1109/ICESGE56040.2022.10180314

Xue Tan, Yuheng Sha, Yanming Jin, Xiaoqing Yan, Tingting Li

{"title":"Research on the Evaluation Method of Emission Reduction Value of Power System Investment","authors":"Xue Tan, Yuheng Sha, Yanming Jin, Xiaoqing Yan, Tingting Li","doi":"10.1109/ICESGE56040.2022.10180314","DOIUrl":"https://doi.org/10.1109/ICESGE56040.2022.10180314","url":null,"abstract":"The new power system can promote the green transformation of the energy system and reduce upstream and downstream pollutants and carbon emissions. In order to better evaluate the significant environmental value of investing in new power systems, this study proposed a method combining environmental science, energy planning, technology and economy to more clearly reflect the extensive environmental value of investing in power systems. This study took into consideration the potential of complementary power generation between regions, industry driving force, and the emission reduction effect of adopting new energy downstream and constructed a value accounting method system of upstream and downstream collaborative emission reduction. First, the energy system planning and optimization method was adopted to predict future power consumption and fossil energy conservation. Second, methods of environmental science were used to estimate the emissions of carbon dioxide and different major pollutants. Last, the investment scale and structure of the new power system were considered to calculate the return on new power system investment per unit in reducing upstream and downstream pollutants and carbon emissions. It is estimated that each 10,000 yuan investment in a new power system will encourage the reduction of 6.14 tons of carbon dioxide emissions, 0.74 tons of sulfur dioxide emissions, 0.4 tons of nitrogen oxide emissions, and 1.08 tons of flue gas emissions upstream and downstream during the “14th Five-Year Plan” period.","PeriodicalId":120565,"journal":{"name":"2022 International Conference on Environmental Science and Green Energy (ICESGE)","volume":"448 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128601226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influence of Magnetic Pole Ovality on the Unbalanced Magnetic Pull of a 1000 MW Hydro-generator Unit Installed with High Precision 磁极椭圆度对1000mw高精度水轮发电机组不平衡磁拉力的影响

2022 International Conference on Environmental Science and Green Energy (ICESGE) Pub Date : 2022-12-09 DOI: 10.1109/ICESGE56040.2022.10180380

Zhenwei Ji, Jiwen Zhang, Zhiwei Hu, Xingxing Huang, Tianyu Zhao, Zhengwei Wang

引用次数: 0

Prediction and Analysis of Ambient Air Quality in Harbin Based on Time Series Analysis Model 基于时间序列分析模型的哈尔滨市环境空气质量预测与分析

2022 International Conference on Environmental Science and Green Energy (ICESGE) Pub Date : 2022-12-09 DOI: 10.1109/ICESGE56040.2022.10180313

Zhihao Zhang, Yanan Li, Jiazhuo Qi, Jun-jian Ma, Xiaoyan Wang, Miao Zhou

引用次数: 0

Chronologically-Ordered Quantitative Global Targets for the Energy-Emissions-Climate Nexus, from 2021 to 2050 能源-排放-气候关系的时间顺序定量全球目标，从2021年到2050年

2022 International Conference on Environmental Science and Green Energy (ICESGE) Pub Date : 2022-12-09 DOI: 10.1109/ICESGE56040.2022.10180322

Osama A. Marzouk

{"title":"Chronologically-Ordered Quantitative Global Targets for the Energy-Emissions-Climate Nexus, from 2021 to 2050","authors":"Osama A. Marzouk","doi":"10.1109/ICESGE56040.2022.10180322","DOIUrl":"https://doi.org/10.1109/ICESGE56040.2022.10180322","url":null,"abstract":"This work aims to organize selected global targets set by the two international organizations: IEA (International Energy Agency) and IRENA (International Renewable Energy Agency), to form pathways for stopping the accumulation of carbon dioxide (CO2) in the atmosphere, and for reaching a condition of net-zero CO2 emissions through accelerating the transition to clean-energy consumption, thereby decelerating the rate of climate change. In achieving this aim, three energy-emissions-climate (EEC) outlook scenarios are discussed and selected targets from them are listed here after being grouped chronologically, from 2021 to 2050. The majority of these targets (54 total) belong to the years 2030 (23 targets) and 2050 (16 targets). However, the years 2021, 2025, 2035, 2040, and 2045 have one or more targets as well. The outlook scenarios considered here are: (1) Net-Zero Emissions by 2050 Scenario (NZE) of IEA, (2) Sustainable Development Scenario (SDS) of IEA, and (3) 1.5°C Scenario by IRENA. The IEA-NZE and IRENA-1.5°C scenarios both imply limiting the global temperature increase to 1.5°C, and reaching global net-zero CO2 emissions by 2050. The IEA-SDS scenario is less strict, allowing a slightly-higher global temperature increase of 1.65°C and having a later deadline of 2070 for reaching global net-zero CO2 emissions.","PeriodicalId":120565,"journal":{"name":"2022 International Conference on Environmental Science and Green Energy (ICESGE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131465955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Correlation Research between Blue-green Algae and Water Quality Indicators Using Unmanned Surface Vehicle 基于无人水面航行器的蓝藻与水质指标相关性研究

2022 International Conference on Environmental Science and Green Energy (ICESGE) Pub Date : 2022-12-09 DOI: 10.1109/ICESGE56040.2022.10180367

Yichen Wei, Zixian Zhang, Xiaohui Zhu, Yong Yue

{"title":"Correlation Research between Blue-green Algae and Water Quality Indicators Using Unmanned Surface Vehicle","authors":"Yichen Wei, Zixian Zhang, Xiaohui Zhu, Yong Yue","doi":"10.1109/ICESGE56040.2022.10180367","DOIUrl":"https://doi.org/10.1109/ICESGE56040.2022.10180367","url":null,"abstract":"The harmful algal blooms in fresh waters have led to severe environmental problems such as mass mortalities of wild and cultured fish and shellfish, and human illnesses, which hamper the sustainability of fisheries and aquaculture. Blue-green algae (BGA) are commonly the dominant species in harmful algal blooms. Thus, studying the correlation between BGA and water quality indicators can contribute to establishing data-driven models when predicting the outbreaks of BGA. Previous studies typically used data from fixed-point sampling for correlation analysis. For specific waters, fixed-point sampling has the defects of small coverage, low sampling frequency, and poor flexibility, which is one of the reasons affecting the reliability of the analysis results. This paper uses an unmanned surface vehicle (USV) for water quality data collection. Spearman's correlation coefficient and statistical methods are used to conduct correlation analysis between BGA biomass (measured by phycocyanin) and water quality indicators. The results show a significant positive correlation between BGA biomass and chlorophyll-a, pH, water temperature, and dissolved oxygen. The results are consistent with most correlation studies and demonstrate the feasibility of using the massive sampling data collected by unmanned surface vehicle to analyze the correlation between BGA and water quality indicators.","PeriodicalId":120565,"journal":{"name":"2022 International Conference on Environmental Science and Green Energy (ICESGE)","volume":"113 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131879793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0