Regional Sustainability最新文献_第6页

Driving factors of CO2 emissions in South American countries: An application of Seemingly Unrelated Regression model 南美国家CO2排放的驱动因素：一个看似不相关回归模型的应用

Q1 Social Sciences

Regional Sustainability

Pub Date : 2024-12-01 Epub Date: 2024-12-20 DOI: 10.1016/j.regsus.2024.100182

Gadir Bayramli , Turan Karimli

Carbon emissions have become a critical concern in the global effort to combat climate change, with each country or region contributing differently based on its economic structures, energy sources, and industrial activities. The factors influencing carbon emissions vary across countries and sectors. This study examined the factors influencing CO₂ emissions in the 7 South American countries including Argentina, Brazil, Chile, Colombia, Ecuador, Peru, and Venezuela. We used the Seemingly Unrelated Regression (SUR) model to analyse the relationship of CO₂ emissions with gross domestic product (GDP), renewable energy use, urbanization, industrialization, international tourism, agricultural productivity, and forest area based on data from 2000 to 2022. According to the SUR model, we found that GDP and industrialization had a moderate positive effect on CO₂ emissions, whereas renewable energy use had a moderate negative effect on CO₂ emissions. International tourism generally had a positive impact on CO₂ emissions, while forest area tended to decrease CO₂ emissions. Different variables had different effects on CO₂ emissions in the 7 South American countries. In Argentina and Venezuela, GDP, international tourism, and agricultural productivity significantly affected CO₂ emissions. In Colombia, GDP and international tourism had a negative impact on CO₂ emissions. In Brazil, CO₂ emissions were primarily driven by GDP, while in Chile, Ecuador, and Peru, international tourism had a negative effect on CO₂ emissions. Overall, this study highlights the importance of country-specific strategies for reducing CO₂ emissions and emphasizes the varying roles of these driving factors in shaping environmental quality in the 7 South American countries.

碳排放已成为全球应对气候变化努力中的一个关键问题，每个国家或地区根据其经济结构、能源来源和工业活动做出不同的贡献。影响碳排放的因素因国家和部门而异。本研究考察了影响阿根廷、巴西、智利、哥伦比亚、厄瓜多尔、秘鲁和委内瑞拉等7个南美国家二氧化碳排放的因素。基于2000 - 2022年的数据，采用看似不相关回归（SUR）模型分析了CO2排放与GDP、可再生能源使用、城市化、工业化、国际旅游、农业生产力和森林面积的关系。根据SUR模型，我们发现GDP和工业化对CO2排放有中等的正向影响，而可再生能源的使用对CO2排放有中等的负向影响。国际旅游总体上对CO2排放有正向影响，而森林面积有减少CO2排放的趋势。不同的变量对南美7国的二氧化碳排放有不同的影响。在阿根廷和委内瑞拉，国内生产总值、国际旅游业和农业生产率显著影响二氧化碳排放。在哥伦比亚，国内生产总值和国际旅游业对二氧化碳排放有负向影响。在巴西，二氧化碳排放主要由GDP驱动，而在智利、厄瓜多尔和秘鲁，国际旅游对二氧化碳排放有负向影响。总体而言，本研究强调了减少二氧化碳排放的具体国家战略的重要性，并强调了这些驱动因素在形成7个南美国家环境质量方面的不同作用。

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引用次数: 0

Application of Cellular Automata and Markov Chain model for urban green infrastructure in Kuala Lumpur, Malaysia 元胞自动机和马尔可夫链模型在马来西亚吉隆坡城市绿色基础设施中的应用

Q1 Social Sciences

Regional Sustainability

Pub Date : 2024-12-01 Epub Date: 2024-12-20 DOI: 10.1016/j.regsus.2024.100179

Jafarpour Ghalehteimouri Kamran, Che Ros Faizah, Rambat Shuib

Kuala Lumpur of Malaysia, as a tropical city, has experienced a notable decline in its critical urban green infrastructure (UGI) due to rapid urbanization and haphazard development. The decrease of UGI, especially natural forest and artificial forest, may reduce the diversity of ecosystem services and the ability of Kuala Lumpur to build resilience in the future. This study analyzed land use and land cover (LULC) and UGI changes in Kuala Lumpur based on Landsat satellite images in 1990, 2005, and 2021and employed the overall accuracy and Kappa coefficient to assess classification accuracy. LULC was categorized into six main types: natural forest, artificial forest, grassland, water body, bare ground, and built-up area. Satellite images in 1990, 2005, and 2021 showed the remarkable overall accuracy values of 91.06%, 96.67%, and 98.28%, respectively, along with the significant Kappa coefficient values of 0.8997, 0.9626, and 0.9512, respectively. Then, this study utilized Cellular Automata and Markov Chain model to analyze the transition of different LULC types during 1990–2005 and 1990–2021 and predict LULC types in 2050. The results showed that natural forest decreased from 15.22% to 8.20% and artificial forest reduced from 18.51% to 15.16% during 1990–2021. Reductions in natural forest and artificial forest led to alterations in urban surface water dynamics, increasing the risk of urban floods. However, grassland showed a significant increase from 7.80% to 24.30% during 1990–2021. Meanwhile, bare ground increased from 27.16% to 31.56% and built-up area increased from 30.45% to 39.90% during 1990–2005. In 2021, built-up area decreased to 35.10% and bare ground decreased to 13.08%, indicating a consistent dominance of built-up area in the central parts of Kuala Lumpur. This study highlights the importance of integrating past, current, and future LULC changes to improve urban ecosystem services in the city.

马来西亚吉隆坡作为一个热带城市，由于城市化的快速发展和无序发展，其关键的城市绿色基础设施（UGI）显著下降。UGI的减少，特别是天然林和人工林的减少，可能会降低生态系统服务的多样性和吉隆坡未来建立恢复力的能力。本研究基于1990年、2005年和2021年的Landsat卫星影像，分析了吉隆坡土地利用和土地覆盖（LULC）和UGI的变化，并采用总体精度和Kappa系数评价分类精度。LULC主要分为天然林、人工林、草地、水体、裸地和建成区6种类型。1990年、2005年和2021年卫星影像总体精度分别为91.06%、96.67%和98.28%，Kappa系数分别为0.8997、0.9626和0.9512。然后，利用元胞自动机和马尔可夫链模型分析了1990-2005年和1990-2021年不同LULC类型的转变，并预测了2050年的LULC类型。结果表明：1990-2021年间，天然林从15.22%减少到8.20%，人工林从18.51%减少到15.16%；天然林和人工林的减少导致城市地表水动态的变化，增加了城市洪水的风险。1990-2021年，草地比例从7.80%显著增加到24.30%。与此同时，光秃秃的土地面积从27.16%增加到31.56%，建成区面积从30.45%增加到39.90%。2021年，建成区面积下降到35.10%，裸地面积下降到13.08%，这表明吉隆坡中心地区的建成区一直占据主导地位。本研究强调了整合过去、现在和未来LULC变化对改善城市生态系统服务的重要性。

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引用次数: 0

Livelihood vulnerability of indigenous people to climate change around the Kerinci Seblat National Park in Bengkulu, Indonesia 印度尼西亚明古鲁Kerinci Seblat国家公园周围土著人民生计对气候变化的脆弱性

Q1 Social Sciences

Regional Sustainability

Pub Date : 2024-12-01 Epub Date: 2024-12-20 DOI: 10.1016/j.regsus.2024.100181

Septri Widiono , Ekawati Sri Wahyuni , Lala M. Kolopaking , Arif Satria

Indigenous people around the Kerinci Seblat National Park (KSNP), Indonesia, have a high dependence on forest resources as their main source of livelihood. This study addressed the vulnerability of Rejang indigenous people around the KSNP to climate change. The popular livelihood vulnerability index (LVI) model was adapted by adding and modifying subcomponents suitable for the study area. Primary data were collected through household surveys in two communities: Embong and Topos. In total, 146 samples were selected for this study using stratified random sampling. The results showed that Embong was more vulnerable to climate change than Topos. Embong exhibited a higher level of vulnerability to the effects of socio-demographic profile, social network, health, and natural disasters and climate variability, whereas Topos was more vulnerable to livelihood strategy, food, and water. Furthermore, Embong was more exposed to natural disasters and climate variability than Topos, but it demonstrated higher adaptive capacity and lower sensitivity than Topos. Nevertheless, socio-demographic profile influenced adaptive capacity in both communities. Sensitivity was influenced most by health in Embong, and sensitivity was influenced most by food in Topos. Although the vulnerability levels were not high in the two communities, several subcomponents must be specifically considered. Overall, this study can help the government make informed decisions to enhance adaptive capacity of the KSNP to climate change.

印度尼西亚Kerinci Seblat国家公园（KSNP）周围的土著居民高度依赖森林资源作为其主要生计来源。本研究探讨了KSNP周围reang土著居民对气候变化的脆弱性。对流行的生计脆弱性指数（LVI）模型进行了添加和修改，使之适合研究区。主要数据是通过在两个社区（Embong和Topos）进行住户调查收集的。本研究采用分层随机抽样，共选取146份样本。结果表明，恩峰比托波斯更容易受到气候变化的影响。恩奉在社会人口状况、社会网络、健康、自然灾害和气候变化的影响下表现出更高的脆弱性，而托波斯则更容易受到生计战略、食物和水的影响。Embong比Topos更容易受到自然灾害和气候变率的影响，但其适应能力高于Topos，敏感性低于Topos。然而，社会人口状况影响了两个社区的适应能力。Embong地区受健康因素影响最大，Topos地区受食物因素影响最大。虽然这两个社区的脆弱程度不高，但必须特别考虑几个子组成部分。总体而言，本研究可以帮助政府做出明智的决策，以提高KSNP对气候变化的适应能力。

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引用次数: 0

Relationship between drought and soil erosion based on the normalized differential water index (NDWI) and revised universal soil loss equation (RUSLE) model 基于归一化差分水分指数（NDWI）和修正通用水土流失方程（RUSLE）模型的干旱与土壤侵蚀关系

Q1 Social Sciences

Regional Sustainability

Pub Date : 2024-12-01 Epub Date: 2024-12-20 DOI: 10.1016/j.regsus.2024.100183

Muhammad Rendana , Wan Mohd Razi Idris , Febrinasti Alia , Supli Effendi Rahim , Muhammad Yamin , Muhammad Izzudin

The Langat River Basin in Malaysia is vulnerable to soil erosion risks because of its exposure to intensive land use activities and its topography, which primarily consists of steep slopes and mountainous areas. Furthermore, climate change frequently exposes this basin to drought, which negatively affects soil and water conservation. However, recent studies have rarely shown how soil reacts to drought, such as soil erosion. Therefore, the purpose of this study is to evaluate the relationship between drought and soil erosion in the Langat River Basin. We analyzed drought indices using Landsat 8 satellite images in November 2021, and created the normalized differential water index (NDWI) via Landsat 8 data to produce a drought map. We used the revised universal soil loss equation (RUSLE) model to predict soil erosion. We verified an association between the NDWI and soil erosion data using a correlation analysis. The results revealed that the southern and northern regions of the study area experienced drought events. We predicted an average annual soil erosion of approximately 58.11 t/(hm²•a). Analysis of the association between the NDWI and soil erosion revealed a strong positive correlation, with a Pearson correlation coefficient of 0.86. We assumed that the slope length and steepness factor was the primary contributor to soil erosion in the study area. As a result, these findings can help authorities plan effective measures to reduce the impacts of drought and soil erosion in the future.

马来西亚的兰加特河流域容易受到土壤侵蚀的风险，因为它暴露在集约土地利用活动中，而且它的地形主要由陡坡和山区组成。此外，气候变化经常使该流域遭受干旱，这对水土保持产生了不利影响。然而，最近的研究很少显示土壤对干旱的反应，例如土壤侵蚀。因此，本研究的目的是评估朗加特河流域干旱与土壤侵蚀的关系。利用2021年11月的Landsat 8卫星图像分析干旱指数，并利用Landsat 8数据建立归一化差水指数（NDWI），生成干旱图。我们使用修正的通用土壤流失方程（RUSLE）模型来预测土壤侵蚀。我们使用相关分析验证了NDWI与土壤侵蚀数据之间的关联。结果表明，研究区南部和北部地区经历了干旱事件。我们预测年均土壤侵蚀约为58.11 t/（hm2•a）。NDWI与土壤侵蚀呈显著正相关，Pearson相关系数为0.86。我们认为坡长和坡度因子是研究区土壤侵蚀的主要影响因子。因此，这些发现可以帮助当局制定有效的措施，以减少未来干旱和土壤侵蚀的影响。

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引用次数: 0

Impact of geopolitical risk, GDP, inflation, interest rate, and trade openness on foreign direct investment: Evidence from five Southeast Asian countries 地缘政治风险、GDP、通货膨胀、利率和贸易开放对外国直接投资的影响：来自东南亚五国的证据

Q1 Social Sciences

Regional Sustainability

Pub Date : 2024-12-01 Epub Date: 2024-12-20 DOI: 10.1016/j.regsus.2024.100177

Md. Shaddam Hossain, Liton Chandra Voumik, Tahsin Tabassum Ahmed, Mehnaz Binta Alam, Zabin Tasmim

Historically, geopolitical risk (GPR) has posed significant challenges to international economic, social, and political frameworks. This study investigated how internal GPR in the selected five Southeast Asian countries (Indonesia, South Korea, Malaysia, the Philippines, and Thailand) influences foreign direct investment (FDI) during 1996–2019. The stationarity of the data was assessed using the Augmented Dickey-Fuller (ADF) unit root test, which shows that the data became stationary after the first difference. The Kao, Pedroni, and Westerlund cointegration tests were employed to examine long-term cointegration among the selected variables (FDI, GPR index (GPRI), gross domestic product (GDP), inflation, interest rate, and trade openness (TOP)). The results indicated that these variables have a long-term cointegration. Consequently, regression analysis using the Pooled Ordinary Least Squares (OLS) regression, fixed effect, random effect, Arellano-Bond dynamic panel-data estimation, and system generalized moment method (GMM) revealed that GPRI and TOP negatively impacted FDI in the selected five Southeast Asian countries. At the same time, GDP, inflation, and interest rate positively influenced FDI in these countries. Because FDI is crucial to shaping a country’s macroeconomic structure, this study recommends that governments and central banks of the selected five Southeast Asian countries should implement policies and strategies to encourage foreign investments.

历史上，地缘政治风险（GPR）对国际经济、社会和政治框架构成了重大挑战。本研究调查了1996-2019年期间选定的五个东南亚国家（印度尼西亚、韩国、马来西亚、菲律宾和泰国）的内部GPR如何影响外国直接投资（FDI）。采用增广Dickey-Fuller （ADF）单位根检验对数据的平稳性进行了评估，结果表明，在第一次差分后，数据变得平稳。采用Kao、Pedroni和Westerlund协整检验来检验所选变量（FDI、GPR指数（GPRI）、国内生产总值（GDP）、通货膨胀、利率和贸易开放度（TOP））之间的长期协整关系。结果表明，这些变量具有长期的协整性。因此，采用OLS回归、固定效应、随机效应、Arellano-Bond动态面板数据估计和系统广义矩法（GMM）进行回归分析发现，GPRI和TOP对所选的五个东南亚国家的FDI产生了负面影响。同时，GDP、通货膨胀和利率对这些国家的FDI也有正向影响。由于外国直接投资对塑造一个国家的宏观经济结构至关重要，本研究建议选定的五个东南亚国家的政府和中央银行应实施鼓励外国投资的政策和战略。

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引用次数: 0

Climate change vulnerability assessment in the new urban planning process in Tanzania 坦桑尼亚新城市规划过程中的气候变化脆弱性评估

Q1 Social Sciences

Regional Sustainability

Pub Date : 2024-09-01 Epub Date: 2024-09-30 DOI: 10.1016/j.regsus.2024.100155

Issa Nyashilu , Robert Kiunsi , Alphonce Kyessi

Climate change vulnerability assessment is an essential tool for identifying regions that are most susceptible to the impacts of climate change and designing effective adaptation actions that can reduce vulnerability and enhance long-term resilience of these regions. This study explored a framework for climate change vulnerability assessment in the new urban planning process in Jangwani Ward, Tanzania. Specifically, taking flood as an example, this study highlighted the steps and methods for climate change vulnerability assessment in the new urban planning process. In the study area, 95 households were selected and interviewed through purposeful sampling. Additionally, 10 respondents (4 females and 6 males) were interviewed for Focus Group Discussion (FGD), and 3 respondents (1 female and 2 males) were selected for Key Informant Interviews (KII) at the Ministry of Lands, Housing and Human Settlements Development. This study indicated that climate change vulnerability assessment framework involves the assessment of climatic hazards, risk elements, and adaptive capacity, and the determination of vulnerability levels. The average hazard risk rating of flood was 2.3. Socioeconomic and livelihood activities and physical infrastructures both had the average risk element rating of 3.0, and ecosystems had the average risk element rating of 2.9. Adaptive capacity ratings of knowledge, technology, economy or finance, and institution were 1.6, 1.9, 1.4, and 2.2, respectively. The vulnerability levels of socioeconomic and livelihood activities and physical infrastructure were very high (4.0). Ecosystems had a high vulnerability level (3.8) to flood. The very high vulnerability level of socioeconomic and livelihood activities was driven by high exposure and sensitivity to risk elements and low adaptive capacity. The study recommends adoption of the new urban planning process including preparation, planning, implementation, and monitoring-evaluation-review phases that integrates climate change vulnerability assessment in all phases.

气候变化脆弱性评估是一项重要工具，可用于确定最易受气候变化影响的地区，并设计有效的适应行动，以降低这些地区的脆弱性并提高其长期适应能力。本研究探讨了坦桑尼亚 Jangwani Ward 新城市规划过程中的气候变化脆弱性评估框架。具体而言，以洪水为例，本研究强调了在新城市规划过程中进行气候变化脆弱性评估的步骤和方法。通过有目的的抽样调查，在研究区域内选取了 95 户家庭进行访谈。此外，10 名受访者（4 名女性和 6 名男性）接受了焦点小组讨论 (FGD) 访谈，3 名受访者（1 名女性和 2 名男性）在土地、住房和人类住区发展部接受了关键信息提供者访谈 (KII)。这项研究表明，气候变化脆弱性评估框架包括对气候灾害、风险要素和适应能力的评估，以及脆弱性等级的确定。洪水的平均危害风险等级为 2.3。社会经济和生计活动以及有形基础设施的平均风险要素评级均为 3.0，生态系统的平均风险要素评级为 2.9。知识、技术、经济或金融以及机构的适应能力评级分别为 1.6、1.9、1.4 和 2.2。社会经济和生计活动以及有形基础设施的脆弱性水平非常高（4.0）。生态系统对洪水的脆弱程度较高（3.8）。社会经济和生计活动的极高脆弱性水平是由对风险要素的高暴露度和敏感度以及低适应能力造成的。研究建议采用新的城市规划流程，包括准备、规划、实施和监测-评估-审查阶段，在所有阶段都纳入气候变化脆弱性评估。

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引用次数: 0

Understanding factors affecting non-participants’ interest in community-supported agriculture 了解影响非参与者对社区支持农业兴趣的因素

Q1 Social Sciences

Regional Sustainability

Pub Date : 2024-09-01 Epub Date: 2024-09-30 DOI: 10.1016/j.regsus.2024.100160

Maula Fadhilata Rahmatika, Agus Suman, Wildan Syafitri, Sri Muljaningsih

Community-supported agriculture (CSA) has emerged as a viable solution for addressing the agricultural challenges faced by countries like Indonesia. This study uses the well-established unified theory of acceptance and use of technology (UTAUT2) model to examine the interest in CSA of potential customers in Indonesia. A standardized questionnaire was distributed to 1200 respondents, and the data were analyzed using structural equation model-partial least square (SEM-PLS) in SmartPLS 4.0 software. The results capture potential CSA consumer interest and will help to improve CSA development strategies in Indonesia. The model explains 44.4% of customers’ intentions, and identifies performance expectancy as the decisive factor in customers’ willingness to participate in CSA. Performance expectancy (0.292), hedonic motivation (0.262), social influence (0.259), and facilitating conditions (0.086) positively influence customers’ interest in participating in a CSA program. The adoption of CSA programs by both farmers and customers could be increased by implementing regulations that provide tax incentives and subsidies, offering training on sustainable farming practices, facilitating the establishment of distribution channels, and establishing guidelines for fair price and quality standards. This study shows the high potential for the implementation of CSA in Indonesia. It could also be used as a foundation for the development of new policies regarding sustainable agriculture markets in Indonesia.

社区支持农业（CSA）已成为印尼等国应对农业挑战的可行解决方案。本研究采用成熟的技术接受和使用统一理论（UTAUT2）模型来研究印度尼西亚潜在客户对社区支持农业的兴趣。向 1200 名受访者发放了标准化问卷，并使用 SmartPLS 4.0 软件中的结构方程模型--部分最小二乘法（SEM-PLS）对数据进行了分析。分析结果捕捉到了潜在 CSA 消费者的兴趣，有助于改进印尼 CSA 发展战略。该模型解释了 44.4% 的客户意向，并确定绩效预期是客户参与 CSA 意愿的决定性因素。绩效预期（0.292）、享乐动机（0.262）、社会影响（0.259）和便利条件（0.086）对客户参与 CSA 项目的兴趣产生了积极影响。通过实施提供税收激励和补贴的法规、提供有关可持续农业实践的培训、促进分销渠道的建立以及制定公平价格和质量标准的指导方针，可以提高农民和顾客对 CSA 项目的采用率。本研究表明，印度尼西亚实施 CSA 的潜力很大。它还可作为印尼制定可持续农业市场新政策的基础。

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引用次数: 0

Characteristics and drivers of the soil multifunctionality under different land use and land cover types in the drylands of China 中国旱地不同土地利用和土地覆盖类型下土壤多功能性的特征和驱动因素

Q1 Social Sciences

Regional Sustainability

Pub Date : 2024-09-01 Epub Date: 2024-09-30 DOI: 10.1016/j.regsus.2024.100162

Song Boyi , Zhang Shihang , Lu Yongxing , Guo Hao , Guo Xing , Wang Mingming , Zhang Yuanming , Zhou Xiaobing , Zhuang Weiwei

The drylands of China cover approximately 6.6×10⁶ km² and are home to approximately 5.8×10⁸ people, providing important ecosystem services for human survival and development. However, dryland ecosystems are extremely fragile and sensitive to external environmental changes. Land use and land cover (LULC) changes significantly impact soil structure and function, thus affecting the soil multifunctionality (SMF). However, the effect of LULC changes on the SMF in the drylands of China has rarely been reported. In this study, we investigated the characteristics of the SMF changes based on soil data in the 1980s from the National Tibetan Plateau Data Center. We explored the drivers of the SMF changes under different LULC types (including forest, grassland, shrubland, and desert) and used structural equation modeling to explore the main driver of the SMF changes. The results showed that the SMF under the four LULC types decreased in the following descending order: forest, grassland, shrubland, and desert. The main driver of the SMF changes under different LULC types was mean annual temperature (MAT). In addition to MAT, pH in forest, soil moisture (SM) and soil biodiversity index in grassland, SM in shrubland, and aridity index in desert are crucial factors for the SMF changes. Therefore, the SMF in the drylands of China is regulated mainly by MAT and pH, and comprehensive assessments of the SMF in drylands need to be performed regarding LULC changes. The results are beneficial for evaluating the SMF among different LULC types and predicting the SMF under global climate change.

中国旱地面积约 6.6×106 平方公里，人口约 5.8×108 人，为人类生存和发展提供了重要的生态系统服务。然而，旱地生态系统极其脆弱，对外部环境变化非常敏感。土地利用和土地覆盖（LULC）的变化会极大地影响土壤结构和功能，从而影响土壤多功能性（SMF）。然而，LULC 变化对中国旱地土壤多功能性的影响却鲜有报道。在本研究中，我们基于国家青藏高原数据中心 20 世纪 80 年代的土壤数据，研究了 SMF 变化的特征。我们探讨了不同 LULC 类型（包括森林、草地、灌木林地和荒漠）下 SMF 变化的驱动因素，并利用结构方程模型探讨了 SMF 变化的主要驱动因素。结果表明，四种 LULC 类型下的 SMF 降幅依次为：森林、草地、灌木林地和荒漠。不同 LULC 类型下 SMF 变化的主要驱动因素是年平均温度（MAT）。除平均年气温外，森林的 pH 值、草地的土壤湿度（SM）和土壤生物多样性指数、灌木林的土壤湿度（SM）和荒漠的干旱指数也是影响 SMF 变化的关键因素。因此，中国旱地的SMF主要受MAT和pH的调控，需要针对LULC的变化对旱地的SMF进行综合评估。研究结果有助于评估不同土地利用、土地利用变化和土地利用类型之间的SMF，预测全球气候变化下的SMF。

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引用次数: 0

Climatic and non-climatic factors driving the livelihood vulnerability of smallholder farmers in Ahafo Ano North District, Ghana 加纳阿哈福阿诺北区小农生计脆弱性的气候和非气候因素

Q1 Social Sciences

Regional Sustainability

Pub Date : 2024-09-01 Epub Date: 2024-09-30 DOI: 10.1016/j.regsus.2024.100157

Frank Baffour-Ata , Louisa Boakye , Moses Tilatob Gado , Ellen Boakye-Yiadom , Sylvia Cecilia Mensah , Senyo Michael Kwaku Kumfo , Kofi Prempeh Osei Owusu , Emmanuel Carr , Emmanuel Dzikunu , Patrick Davies

Smallholder farmers in Ahafo Ano North District, Ghana, face multiple climatic and non-climatic issues. This study assessed the factors contributing to the livelihood vulnerability of smallholder farmers in this district by household surveys with 200 respondents and focus group discussions (FGDs) with 10 respondents. The Mann–Kendall trend test was used to assess mean annual rainfall and temperature trends from 2002 to 2022. The relative importance index (RII) value was used to rank the climatic and non-climatic factors perceived by respondents. The socioeconomic characteristics affecting smallholder farmers’ perceptions of climatic and non-climatic factors were evaluated by the binary logistic regression model. Results showed that mean annual rainfall decreased (P>0.05) but mean annual temperature significantly increased (P<0.05) from 2002 to 2022 in the district. The key climatic factors perceived by smallholder farmers were extreme heat or increasing temperature (RII=0.498), erratic rainfall (RII=0.485), and increased windstorms (RII=0.475). The critical non-climatic factors were high cost of farm inputs (RII=0.485), high cost of healthcare (RII=0.435), and poor condition of roads to farms (RII=0.415). Smallholder farmers’ perceptions of climatic and non-climatic factors were significantly affected by their socioeconomic characteristics (P<0.05). This study concluded that these factors negatively impact the livelihoods and well-being of smallholder farmers and socioeconomic characteristics influence their perceptions of these factors. Therefore, to enhance the resilience of smallholder farmers to climate change, it is necessary to adopt a comprehensive and context-specific approach that accounts for climatic and non-climatic factors.

加纳阿哈福阿诺北区的小农面临多种气候和非气候问题。本研究通过对 200 名受访者进行家庭调查和对 10 名受访者进行焦点小组讨论，评估了导致该地区小农生计脆弱性的因素。Mann-Kendall 趋势检验用于评估 2002 年至 2022 年的年平均降雨量和气温趋势。采用相对重要性指数 (RII) 值对受访者认为的气候和非气候因素进行排序。二元逻辑回归模型评估了影响小农对气候和非气候因素看法的社会经济特征。结果表明，从 2002 年到 2022 年，该地区的年平均降雨量有所下降（P>0.05），但年平均气温显著上升（P<0.05）。小农户认为的关键气候因素是极端高温或气温升高（RII=0.498）、降雨量不稳定（RII=0.485）和风灾增加（RII=0.475）。关键的非气候因素是农业投入成本高（RII=0.485）、医疗费用高（RII=0.435）和通往农场的道路状况差（RII=0.415）。小农对气候和非气候因素的看法受到其社会经济特征的显著影响（P<0.05）。本研究得出结论，这些因素对小农的生计和福祉产生了负面影响，而社会经济特征影响了他们对这些因素的看法。因此，为了提高小农对气候变化的适应能力，有必要采取一种全面的、针对具体情况的方法，考虑气候和非气候因素。

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引用次数: 0

Assessing the impact of climate change on agricultural production in central Afghanistan 评估气候变化对阿富汗中部农业生产的影响

Q1 Social Sciences

Regional Sustainability

Pub Date : 2024-09-01 Epub Date: 2024-09-30 DOI: 10.1016/j.regsus.2024.100156

Homayoon Raoufi , Hamidreza Jafari , Wakil Ahmad Sarhadi , Esmail Salehi

Afghanistan has faced extreme climatic crises such as drought, rising temperature, and scarce precipitation, and these crises will likely worsen in the future. Reduction in crop yield can affect food security in Afghanistan, where the majority of population and economy are completely dependent on agriculture. This study assessed the interaction between climate change and crop yield in Kabul of Afghanistan during the reference (1990–2020) and future (2025–2100) periods. Climate data (1990–2020) were collected from four meteorological stations and three local organizations, and wheat yield data (1990–2020) were acquired from the United States Agriculture Department. Data during the reference period (1990–2020) were used for the validation and calibration of the statistical downscaling models such as the Statistical Downscaling Model (SDSM) and Long Ashton Research Station Weather Generator (LARS-WG). Furthermore, the auto-regression model was used for trend analysis. The results showed that an increase in the average annual temperature of 2.15°C, 2.89°C, and 4.13°C will lead to a reduction in the wheat yield of 9.14%, 10.20%, and 12.00% under Representative Concentration Pathway (RCP)2.6, RCP4.5, and RCP8.5 during the future period (2025–2100), respectively. Moreover, an increase in the annual maximum temperature of 1.79°C, 2.48°C, and 3.74°C also causes a significant reduction in the wheat yield of 2.60%, 3.60%, and 10.50% under RCP2.6, RCP4.5, and RCP8.5, respectively. Furthermore, an increase in the annual minimum temperature of 2.98°C, 2.23°C, and 4.30°C can result in an increase in the wheat yield of 6.50%, 4.80%, and 9.30% under RCP2.6, RCP4.5, and RCP8.5, respectively. According to the SDSM, the decrease of the average monthly precipitation of 4.34%, 4.10%, and 5.13% results in a decrease in the wheat yield of 2.60%, 2.36%, and 3.18% under RCP2.6, RCP4.5, and RCP8.5, respectively. This study suggests that adaptation strategies can be applied to minimize the consequences of climate change on agricultural production.

阿富汗一直面临着干旱、气温升高和降水稀少等极端气候危机，这些危机在未来很可能会进一步恶化。作物减产会影响阿富汗的粮食安全，因为阿富汗的大部分人口和经济完全依赖农业。本研究评估了阿富汗喀布尔在基准期（1990-2020 年）和未来（2025-2100 年）气候变化与作物产量之间的相互作用。气候数据（1990-2020 年）来自四个气象站和三个地方组织，小麦产量数据（1990-2020 年）来自美国农业部。参考期（1990-2020 年）的数据用于统计降尺度模型（SDSM）和长阿什顿研究站天气生成器（LARS-WG）等统计降尺度模型的验证和校准。此外，自动回归模型还用于趋势分析。结果表明，在代表浓度途径（RCP）2.6、RCP4.5 和 RCP8.5 下，年平均气温上升 2.15°C、2.89°C 和 4.13°C 将导致未来（2025-2100 年）小麦产量分别减少 9.14%、10.20% 和 12.00%。此外，在 RCP2.6、RCP4.5 和 RCP8.5 条件下，年最高气温分别升高 1.79°C、2.48°C 和 3.74°C 也会导致小麦产量分别显著减少 2.60%、3.60% 和 10.50%。此外，在 RCP2.6、RCP4.5 和 RCP8.5 条件下，年最低气温上升 2.98°C、2.23°C 和 4.30°C 可使小麦产量分别增加 6.50%、4.80% 和 9.30%。根据 SDSM，在 RCP2.6、RCP4.5 和 RCP8.5 条件下，月平均降水量分别减少 4.34%、4.10% 和 5.13%，导致小麦产量分别减少 2.60%、2.36% 和 3.18%。这项研究表明，可以采用适应战略将气候变化对农业生产的影响降至最低。

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引用次数: 0