The financial entanglements of local energy projects

There is currently an expansion of local energy initiatives, underpinned by the desire to reduce energy-related carbon emissions and in recognition of the importance of the local arena to achieving such change. Much of the research on these initiatives has been framed by a conventional economic approach, identifying barriers, drivers and incentives to explain their emergence (or not). Here a new economic sociological approach is taken which sees markets as socio-materially constructed and points to the importance of tracing exchange flows and determining modalities of valuation for such exchanges. Artefacts or market devices are seen to play a particular role in connecting actors and technologies within coordinating institutional arrangements and offer the potential for making innovative projects conventional. These aspects are explored in four international case-studies from Wales, Sweden, Germany and USA, mapping relations, identifying exchange flows, pinpointing how artefacts coordinate and showing the multiple modalities of valuation involved in each case. Conclusions concerning the importance of negotiation against a market backdrop and rendering exchange flows more certain are drawn.     

绿色气候基金在全球气候治理体系中的作用和展望

作为《联合国气候变化框架公约》(简称公约）和《巴黎协定》资金机制最大运营实体,绿色气候基金(GCF)不仅是发达国家兑现1000亿美元长期资金承诺的重要平台,亦是公约和《巴黎协定》目标达成的关键因素。文中系统总结了GCF在推进气候变化国际合作进程、为发展中国家应对气候变化提供资金支持、推动私营部门参与应对气候变化行动等方面的积极作用。提出在当前多边合作面临挑战的复杂背景下,GCF亦面临美国退群、缺乏有效决策机制、项目质量及秘书处能力有待提高等系列问题。文章认为,一个持续有效运营的GCF是国际社会落实《巴黎协定》实施细则的重要保障,各方应尽快凝聚政治共识,推动GCF在全球气候治理体系中继续发挥积极作用。首先,应通过引入投票权决策机制、完善政策缺口、创新业务模式等措施提升基金治理和运营效率;其次,通过尽快完成正式增资进程、拓宽资金渠道、加强剩余资金管理等方式确保充足及可持续的资金来源;最后,还应通过强化与现有气候基金的协调互补、加大与多边发展银行的合作等途径与各方资金形成合力,推动资金流向低碳和气候韧性发展领域。文章还提出,中国应在有效发挥发达国家和发展中国家桥梁作用的基础上,引导GCF投票权改革以消除政治因素对GCF长远发展的负面影响,同时通过积极争取获得下届董事席位,推进与GCF全方位合作、参与GCF正式增资进程等举措,服务生态文明建设及全球应对气候变化目标。     

Which policy instruments attract foreign direct investments in renewable energy?

Reducing GHG emissions and mitigating climate change would require significant investments in renewable energy technologies. Foreign direct investments (FDI) in renewable energy (RE) have increased over the last years, contributing to the diffusion of RE globally. In the field of climate policy, there are multiple policy instruments aimed at attracting investments in renewable energy. This article aims to map the FDI flows globally including source and destination countries. Furthermore, the article investigates which policy instruments attract more FDI in RE sectors such as solar, wind and biomass, based on an econometric analysis of 137 Organisation for Economic Co-operation and Development (OECD) and non-OECD countries. The results show that Feed in Tariffs (FIT) followed by Fiscal Measures (FM), such as tax incentives and Renewable Portfolio Standards (RPS), are the most significant policy instrument that attract FDI in the RE sector globally. Regarding carbon pricing instruments, based on our analysis, carbon tax proved to be correlated with high attraction of FDI in OECD countries, whereas Emissions Trading Schemes (ETS) proved to be correlated with high attraction of FDI mainly in non-OECD countries.

Key policy insights

• Feed in Tariffs is the most significant policy instrument that attracts FDI in the Renewable Energy sector globally.

• Fiscal Measures (FM), such as tax incentives, show a significant and positive impact on renewable energy projects by foreign investors, and particularly on solar energy.

• Carbon pricing instruments, such as carbon taxation and emissions trading, proved to attract FDI in OECD and non-OECD countries respectively.

• Public investments, such as government funds for renewable energy projects, proved not as attractive to foreign private investors, perhaps because public funds are not perceived as stable in the long run.

     

Resilience through interlinkage: the green climate fund and climate finance governance

The Green Climate Fund (GCF) is a significant and potentially innovative addition to UNFCCC frameworks for mobilizing increased finance for climate change mitigation and adaptation. Yet the GCF faces challenges of operationalization not only as a relatively new international fund but also as a result of US President Trump’s announcement that the United States would withdraw from the Paris Agreement. Consequently the GCF faces a major reduction in actual funding contributions and also governance challenges at the levels of its Board and the UNFCCC Conference of the Parties (COP), to which it is ultimately accountable. This article analyzes these challenges with reference to the GCF’s internal regulations and its agreements with third parties to demonstrate how exploiting design features of the GCF could strengthen its resilience in the face of such challenges. These features include linkages with UNFCCC constituted bodies, particularly the Technology Mechanism, and enhanced engagement with non-Party stakeholders, especially through its Private Sector Facility. The article posits that deepening GCF interlinkages would increase both the coherence of climate finance governance and the GCF’s ability to contribute to ambitious climate action in uncertain times.

Key policy insights

• The Trump Administration’s purported withdrawal from the Paris Agreement creates challenges for the GCF operating model in three key domains: capitalization, governance and guidance.

• Two emerging innovations could prove crucial in GCF resilience to fulfil its role in Paris Agreement implementation: (1) interlinkages with other UNFCCC bodies, especially the Technology Mechanism; and (2) engagement with non-Party stakeholders, especially private sector actors such as large US investors and financiers.

• There is also an emerging soft role for the GCF as interlocutor between policy-makers and non-Party actors to help bridge the communication divide that often plagues cross-sectoral interactions.

• This role could develop through: (a) the GCF tripartite interface between the Private Sector Facility, Accredited Entities and National Designated Authorities; and (b) strengthened collaborations between the UNFCCC Technical and Financial Mechanisms.

     

基于学习曲线的中国未来制氢成本趋势研究

氢能是中国能源系统低碳转型和实现2060年前碳中和目标的重要技术选择之一。根据原料来源可以将氢分为绿氢、蓝氢和灰氢,其制备成本和碳排放强度存在较大差异。文中以中国氢能生产现状为基础,建立基于学习曲线的平准化制氢成本（LCOH）模型,测算不同制氢技术从2020年到2060年的成本变化趋势。结果表明：现阶段灰氢成本最低,绿氢成本最高;到2030年绿氢成本将下降至20~25元/kg;2050年后,绿氢将成为成本最低的制氢方式（含碳排放成本),而且PEM（质子交换膜）电解水制氢的成本将低于AE（碱性）电解水制氢,光伏+PEM电解水制氢成本将下降至12元/kg。电解槽和电力成本下降是未来绿氢成本下降的主要驱动因素。敏感性分析表明,运营维护成本和关键技术学习率是影响绿氢成本下降速度的重要参数。     

Combining UAV-based plant height from crop surface models,visible, and near infrared vegetation indices for biomass monitoring in barley

In this study we combined selected vegetation indices (VIs) and plant height information to estimate biomass in a summer barley experiment. The VIs were calculated from ground-based hyperspectral data and unmanned aerial vehicle (UAV)-based red green blue (RGB) imaging. In addition, the plant height information was obtained from UAV-based multi-temporal crop surface models (CSMs). The test site is a summer barley experiment comprising 18 cultivars and two nitrogen treatments located in Western Germany. We calculated five VIs from hyperspectral data. The normalised ratio index (NRI)-based index GnyLi (Gnyp et al., 2014) showed the highest correlation (R² = 0.83) with dry biomass. In addition, we calculated three visible band VIs: the green red vegetation index (GRVI), the modified GRVI (MGRVI) and the red green blue VI (RGBVI), where the MGRVI and the RGBVI are newly developed VI. We found that the visible band VIs have potential for biomass prediction prior to heading stage. A robust estimate for biomass was obtained from the plant height models (R² = 0.80–0.82). In a cross validation test, we compared plant height, selected VIs and their combination with plant height information. Combining VIs and plant height information by using multiple linear regression or multiple non-linear regression models performed better than the VIs alone. The visible band GRVI and the newly developed RGBVI are promising but need further investigation. However, the relationship between plant height and biomass produced the most robust results. In summary, the results indicate that plant height is competitive with VIs for biomass estimation in summer barley. Moreover, visible band VIs might be a useful addition to biomass estimation. The main limitation is that the visible band VIs work for early growing stages only.     

Snowmelt velocity predicts vegetation green-wave velocity in mountainous ecological systems of North America

The timing of spring initiates an important period for resource availability for large trophic webs within ecosystems, including forage for grazing animals, flowers for pollinators, and the higher trophic levels that depend on these resources. Spring timing is highly variable across space, being influenced strongly by the departure of snow cover (i.e. snowmelt timing, in locations with a seasonal snowpack), climate, weather, elevation, and latitude. When spring timing occurs along a gradient (e.g. spring arriving later in higher elevations of mountainous terrain), the organisms that rely on spring resources often migrate to maintain an optimal position for spring resources – a phenomenon known as ‘surfing the green wave.’ While this behavior has been observed by tracking animals, there have been no studies to quantify the green wave as a movement across space and time. Furthermore, considering that snowmelt timing has moderate power to explain green-up timing for a given location, we ask the question: does snowmelt velocity predict green wave velocity? Here, we introduce the first continental maps of snowmelt and green wave velocity for North America from 2001 to 2016 as derived from the MODIS MCD12Q2 phenology dataset. We show that both snowmelt and green wave velocities are influenced strongly by topography, including slope and aspect. Furthermore, we quantify the relationships between snowmelt and green wave velocities according to three variables: direction, speed, and distance traveled. We conclude that mountainous ecoregions, such as the western North American cordillera, have the highest correspondence between snowmelt and green wave velocities, compared to flatter regions such as the Great Plains and tundra. This work will be of interest to wildlife ecologists, biologists, and land managers who seek to conserve migratory animals and the ecosystems that support them.     

基于多主体模型的典型区域退耕还林工程实施空间模拟

土地利用变化是全球变化的重要驱动力,模拟是研究土地变化重要的方法。退耕还林是中国山区土地利用变化的重要原因。当前退耕还林模拟在综合社会与空间途径方面的不足限制了退耕还林模拟的空间精度及后续社会效益研究。结合社会和空间途径精确模拟退耕还林的空间过程可为该工程实施提供科学依据。本文以云南省东川区铜都镇为研究区,基于人口普查数据、地理环境数据、实地调研数据,综合考虑农民、农户和政府3类主体,基于多主体模型构建了退耕还林工程实施的空间模型,模拟了2010—2015年铜都镇具有空间特征的农户年收入、农户/政府退耕意愿和退耕还林工程空间实施过程。研究发现退耕还林工程实施主要与坡度、交通和农户收入有关,与土壤肥力相关性较小,坡度25°~30°的耕地占了81.47%,离道路0~2 km交通条件较好的地段占56.37%,农户年收入较低的区域退耕还林比例较高,且退耕还林工程的实施显著提高了铜都镇收入,2010—2015年户均收入提高了1475元。本文模拟结果空间精度为91.12%。本文构建的退耕还林工程实施空间模拟方法可为其它区域提供方法借鉴,以期为中国生态保护和精准扶贫等工程实施提供科学支撑。     

移动线源的Green函数求解及辐射能量分析:高铁地震信号简化建模

在基于人工主动源的勘探地震学中,往往采用固定位置和激发时间的点源数学模型来描述爆炸型震源或可控震源,因此就有了描述单点力源作用下的弹性全空间或半空间中弹性波传播的Green函数,成为了勘探地震学的重要理论基础.而如今,行进中的高速列车(高铁)是一种全新的主动源,其接近匀速的运行速度、确定的长度和荷载使其可以被重复利用.本文将行进中的高铁在数学上简化建模为一个移动线源来进行研究,给出了这一震源作用下的弹性半空间和全空间中Green函数的计算方法,并分别讨论了全空间中远场Green函数的频谱特征和空间辐射能量的方向性特点,以及半空间中Green函数与近场观测数据的对比结果,为高铁震源下的地震波传播规律和振动信号的研究与利用提供帮助.     

九寨沟MS7.0地震强地震动模拟及漳扎镇地震动强度预测

破坏性地震强度预测可用于工程领域抗震设防以及地震危险性分析评估,是防震减灾中一项很重要的基础工作.为了再现九寨沟地震的地震动强度,评估缺失强震记录的九寨章扎台站的地震动强度,本文用经验格林函数法对九寨沟地震进行了数值模拟.选取了震源周边地震动峰值加速度超过10 Gal的10个强震台站进行模拟.因未得到九寨沟地震的余震,初次尝试将汶川地震和定西地震的余震作为格林函数模拟九寨沟地震.模拟结果整体上可以反映各台站地震动的强度特征,尤其是地震动高频成份拟合较好.模拟值的地震动峰值加速度、时程数据、反应谱等与观测值拟合较好.预测结果显示漳扎镇的地震动峰值加速度值约为180~200 Gal.预测结果也表明在缺少大震的余震记录时,经验格林函数法使用其他大震的余震同样可以再现目标地震的强度特征.本研究也为经验格林函数方法在缺乏小震记录地区的使用积累了经验.最后总结了格林函数的选取标准,为经验格林函数方法来预测未来强震动特征积累了经验.