肯尼亚基苏木县太阳能光伏系统扩散的空间格局

Joyce Mwangi, Paul Obade
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 Methodology: The study adopted a Quasi-Experimental research design to explore various social phenomena, aiming to identify key facts. Utilizing statistical evidence, we conducted numerical comparisons and statistical inferences to validate or refute the research questions. Locational information on households utilizing small home systems was extracted from a secondary Solar Database. This data underwent georeferencing, enhancing our comprehension of the actual geographical distribution of households and facilitating the achievement of our research objectives. In the process of data analysis, we employed inferential statistics, specifically regression analysis, conducted using ArcGIS PRO powered by ESRI. The utilization of ArcGIS Pro extended to the creation of an empirical model. This model was designed to probe into the factors influencing the observed spatial diffusion patterns, providing a robust analytical framework for our investigation.
 Findings: In the initial objective, cluster and outlier analysis unveiled a distinct low-high cluster pattern for solar home systems (SHS). The optimized hotspot analysis consistently identified SHS hotspots and cold spots within the region, particularly aligning with urban areas, notably Kisumu. The second objective exposed factors influencing diffusion, revealing negative correlations with population density, household density, and poverty rate, indicating diminished adoption in densely populated and impoverished areas. Conversely, positive correlations with income, education, and electrification rates signaled heightened adoption in wealthier, educated communities. Despite consistent diffusion trends, an empirical model underscored the substantial impact of income and electricity on SHS diffusion. The third objective disclosed that between 2016-2021, SHS diffusion contributed to the mitigation of 268,581.6 metric tons of carbon emissions.
 Unique Contribution to Theory, Practice and Policy: This research makes a distinctive contribution to theory by delving into the impact of solar home systems (SHS) in Kenya, particularly within the context of the country's commitment to reduce greenhouse gas (GHG) emissions. The theoretical foundation lies in addressing the existing gap in understanding the spatial distribution and diffusion patterns of SHS and their role in GHG reduction, aligning with Kenya's focus on renewable energy adoption.","PeriodicalId":92380,"journal":{"name":"International journal of environmental sciences","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatial Patterns of Solar Photovoltaic System Diffusion Kisumu County, Kenya\",\"authors\":\"Joyce Mwangi, Paul Obade\",\"doi\":\"10.47604/ijes.2160\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose: This research aligns with Sustainable Development Goal 7, contributing to the progress outlined in the 2030 Agenda for Sustainable Development and the commitments of the Paris Climate Agreement. Specifically, this study focuses on the spatial analysis of solar photovoltaic (PV) systems, offering valuable insights for academic exploration and informing public policy decisions related to the widespread adoption of this increasingly vital renewable energy technology. The outcomes of this project transcend academic significance, extending to practical applications for energy practitioners, policymakers, academics, and future researchers. The meticulous tracking of solar PV system spatial patterns in Kisumu County yields data that not only benefits its residents but also serves as a valuable resource for the entire nation. This information will be instrumental for current energy practitioners, policymakers, academicians, and prospective researchers seeking to advance the collective knowledge in this field.
 Methodology: The study adopted a Quasi-Experimental research design to explore various social phenomena, aiming to identify key facts. Utilizing statistical evidence, we conducted numerical comparisons and statistical inferences to validate or refute the research questions. Locational information on households utilizing small home systems was extracted from a secondary Solar Database. This data underwent georeferencing, enhancing our comprehension of the actual geographical distribution of households and facilitating the achievement of our research objectives. In the process of data analysis, we employed inferential statistics, specifically regression analysis, conducted using ArcGIS PRO powered by ESRI. The utilization of ArcGIS Pro extended to the creation of an empirical model. This model was designed to probe into the factors influencing the observed spatial diffusion patterns, providing a robust analytical framework for our investigation.
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引用次数: 0

摘要

目的:本研究与可持续发展目标7相一致,有助于实现《2030年可持续发展议程》所概述的进展和《巴黎气候协定》的承诺。具体而言,本研究侧重于太阳能光伏(PV)系统的空间分析,为学术探索提供有价值的见解,并为与广泛采用这一日益重要的可再生能源技术相关的公共政策决策提供信息。该项目的成果超越了学术意义,扩展到能源从业者、政策制定者、学者和未来研究人员的实际应用。对基苏木县太阳能光伏系统空间模式的细致跟踪,不仅使其居民受益,而且为整个国家提供了宝贵的资源。这些信息将有助于当前的能源从业者、政策制定者、学者和未来的研究人员寻求推进这一领域的集体知识。研究方法:本研究采用准实验研究设计,探索各种社会现象,旨在找出关键事实。利用统计证据,我们进行数值比较和统计推断来验证或反驳研究问题。利用小型家庭系统的家庭的位置信息是从二级太阳能数据库中提取的。这些数据进行了地理参考,增强了我们对家庭实际地理分布的理解,促进了我们研究目标的实现。在数据分析的过程中,我们使用ESRI驱动的ArcGIS PRO进行推理统计,特别是回归分析。利用ArcGIS Pro扩展到经验模型的创建。该模型旨在探讨影响观测到的空间扩散模式的因素,为我们的研究提供一个强大的分析框架。 结果:在最初的目标中,聚类和离群值分析揭示了太阳能家庭系统(SHS)的明显低-高聚类模式。优化后的热点分析一致地识别出了区域内的SHS热点和冷点,特别是与城市区域一致,尤其是基苏木。第二个客观分析揭示了影响传播的因素,揭示了与人口密度、家庭密度和贫困率的负相关关系,表明人口密集和贫困地区的收养减少。相反,与收入、教育和电气化率的正相关表明,在较富裕、受教育程度较高的社区,采用率较高。尽管有一致的扩散趋势,但实证模型强调了收入和电力对SHS扩散的实质性影响。第三个目标披露,2016-2021年期间,SHS扩散有助于减少268,581.6公吨的碳排放。对理论、实践和政策的独特贡献:本研究通过深入研究太阳能家庭系统(SHS)在肯尼亚的影响,特别是在该国承诺减少温室气体(GHG)排放的背景下,对理论做出了独特的贡献。理论基础在于解决在理解SHS的空间分布和扩散模式及其在温室气体减排中的作用方面存在的差距,并与肯尼亚对可再生能源采用的关注保持一致。
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Spatial Patterns of Solar Photovoltaic System Diffusion Kisumu County, Kenya
Purpose: This research aligns with Sustainable Development Goal 7, contributing to the progress outlined in the 2030 Agenda for Sustainable Development and the commitments of the Paris Climate Agreement. Specifically, this study focuses on the spatial analysis of solar photovoltaic (PV) systems, offering valuable insights for academic exploration and informing public policy decisions related to the widespread adoption of this increasingly vital renewable energy technology. The outcomes of this project transcend academic significance, extending to practical applications for energy practitioners, policymakers, academics, and future researchers. The meticulous tracking of solar PV system spatial patterns in Kisumu County yields data that not only benefits its residents but also serves as a valuable resource for the entire nation. This information will be instrumental for current energy practitioners, policymakers, academicians, and prospective researchers seeking to advance the collective knowledge in this field. Methodology: The study adopted a Quasi-Experimental research design to explore various social phenomena, aiming to identify key facts. Utilizing statistical evidence, we conducted numerical comparisons and statistical inferences to validate or refute the research questions. Locational information on households utilizing small home systems was extracted from a secondary Solar Database. This data underwent georeferencing, enhancing our comprehension of the actual geographical distribution of households and facilitating the achievement of our research objectives. In the process of data analysis, we employed inferential statistics, specifically regression analysis, conducted using ArcGIS PRO powered by ESRI. The utilization of ArcGIS Pro extended to the creation of an empirical model. This model was designed to probe into the factors influencing the observed spatial diffusion patterns, providing a robust analytical framework for our investigation. Findings: In the initial objective, cluster and outlier analysis unveiled a distinct low-high cluster pattern for solar home systems (SHS). The optimized hotspot analysis consistently identified SHS hotspots and cold spots within the region, particularly aligning with urban areas, notably Kisumu. The second objective exposed factors influencing diffusion, revealing negative correlations with population density, household density, and poverty rate, indicating diminished adoption in densely populated and impoverished areas. Conversely, positive correlations with income, education, and electrification rates signaled heightened adoption in wealthier, educated communities. Despite consistent diffusion trends, an empirical model underscored the substantial impact of income and electricity on SHS diffusion. The third objective disclosed that between 2016-2021, SHS diffusion contributed to the mitigation of 268,581.6 metric tons of carbon emissions. Unique Contribution to Theory, Practice and Policy: This research makes a distinctive contribution to theory by delving into the impact of solar home systems (SHS) in Kenya, particularly within the context of the country's commitment to reduce greenhouse gas (GHG) emissions. The theoretical foundation lies in addressing the existing gap in understanding the spatial distribution and diffusion patterns of SHS and their role in GHG reduction, aligning with Kenya's focus on renewable energy adoption.
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