Perceived fairness and public acceptability of carbon pricing: a review of the literature

While carbon pricing is widely seen as a crucial element of climate policy and has been implemented in many countries, it also has met with strong resistance. We provide a comprehensive overview of public perceptions of the fairness of carbon pricing and how these affect policy acceptability. To this end, we review evidence from empirical studies on how individuals judge personal, distributional and procedural aspects of carbon taxes and cap-and-trade. In addition, we examine preferences for particular redistributive and other uses of revenues generated by carbon pricing and their role in instrument acceptability. Our results indicate a high concern over distributional effects, particularly in relation to policy impacts on poor people, in turn reducing policy acceptability. In addition, people show little trust in the capacities of governments to put the revenues of carbon pricing to good use. Somewhat surprisingly, most studies do not indicate clear public preferences for using revenues to ensure fairer policy outcomes, notably by reducing its regressive effects. Instead, many people prefer using revenues for ‘environmental projects’ of various kinds. We end by providing recommendations for improving public acceptability of carbon pricing. One suggestion to increase policy acceptability is combining the redistribution of revenue to vulnerable groups with the funding for environmental projects, such as on renewable energy.

Key policy insights

• If people perceive carbon pricing instruments as fair, this increases policy acceptability and support.

• People’s satisfaction with information provided by the government about the policy instrument increases acceptability.

• While people express high concern over uneven distribution of the policy burden, they often prefer using carbon pricing revenues for environmental projects instead of compensation for inequitable outcomes.

• Recent studies find that people’s preferences shift to using revenues for making policy fairer if they better understand the functioning of carbon pricing, notably that relatively high prices of CO₂-intensive goods and services reduce their consumption.

• Combining the redistribution of revenue to support both vulnerable groups and environmental projects, such as on renewable energy, seems to most increase policy acceptability.

     

碳市场顶层设计路线图

中国正面临着低碳减排和保持经济增速的双重挑战。为利用碳排放权交易机制以最低的社会成本实现减排目标,我国自2013年起开始建设碳排放权交易试点,并于2017年12月起宣布正式启动全国碳市场。然而碳市场的顶层设计不可一蹴而就,需要在我国宏观经济改革的大背景下分阶段逐步推进。短期（2020年前）碳市场建设重在强化产权制度建设,完善市场交易基础。中期（2021—2030年）碳市场建设要形成活跃的市场氛围,充分降低我国的温室气体达峰成本。长期（2031—2050年）碳市场建设要形成稳定上升的碳价趋势,为我国的低碳转型提供长期动力。     

Carbon cycling in a high-arctic marine ecosystem – Young Sound, NE Greenland

Young Sound is a deep-sill fjord in NE Greenland (74°N). Sea ice usually begins to form in late September and gains a thickness of 1.5 m topped with 0–40 cm of snow before breaking up in mid-July the following year. Primary production starts in spring when sea ice algae begin to flourish at the ice–water interface. Most biomass accumulation occurs in the lower parts of the sea ice, but sea ice algae are observed throughout the sea ice matrix. However, sea ice algal primary production in the fjord is low and often contributes only a few percent of the annual phytoplankton production. Following the break-up of ice, the immediate increase in light penetration to the water column causes a steep increase in pelagic primary production. Usually, the bloom lasts until August–September when nutrients begin to limit production in surface waters and sea ice starts to form. The grazer community, dominated by copepods, soon takes advantage of the increased phytoplankton production, and on an annual basis their carbon demand (7–11 g C m⁻²) is similar to phytoplankton production (6–10 g C m⁻²). Furthermore, the carbon demand of pelagic bacteria amounts to 7–12 g C m⁻² yr⁻¹. Thus, the carbon demand of the heterotrophic plankton is approximately twice the estimated pelagic primary production, illustrating the importance of advected carbon from the Greenland Sea and from land in fuelling the ecosystem.In the shallow parts of the fjord (<40 m) benthic primary producers dominate primary production. As a minimum estimate, a total of 41 g C m⁻² yr⁻¹ is fixed by primary production, of which phytoplankton contributes 15%, sea ice algae <1%, benthic macrophytes 62% and benthic microphytes 22%. A high and diverse benthic infauna dominated by polychaetes and bivalves exists in these shallow-water sediments (<40 m), which are colonized by benthic primary producers and in direct contact with the pelagic phytoplankton bloom. The annual benthic mineralization is 32 g C m⁻² yr⁻¹ of which megafauna accounts for 17%. In deeper waters benthic mineralization is 40% lower than in shallow waters and megafauna, primarily brittle stars, accounts for 27% of the benthic mineralization. The carbon that escapes degradation is permanently accumulated in the sediment, and for the locality investigated a rate of 7 g C m⁻² yr⁻¹ was determined.A group of walruses (up to 50 adult males) feed in the area in shallow waters (<40 m) during the short, productive, ice-free period, and they have been shown to be able to consume <3% of the standing stock of bivalves (Hiatella arctica, Mya truncata and Serripes Groenlandicus), or half of the annual bivalve somatic production. Feeding at greater depths is negligible in comparison with their feeding in the bivalve-rich shallow waters.     

利用反射GPS信号遥感土壤湿度

在水文、气候、农业等问题的研究中,土壤湿度信息十分重要。近年来,利用GPS系统进行遥感的新方法,已经越来越多地引起研究者们的关注。特别是GPS卫星广播的L1（1.57542GHz）频率信号,是土壤湿度遥感的最佳频率。反射GPS信号功率是土壤介电常数的函数,而土壤介电常数又和土壤湿度有关。根据这一原理,美国国家航空与航天局于2002年进行了基于地表面反射GPS信号的遥感土壤湿度实验。结果证明反射GPS信号对土壤湿度特性十分敏感,由于植被的影响对反射率进行了修正,并用此方法模型与其它方法进行了比较。在利用GPS遥感土壤湿度方面,研制高增益天线,更好的修正信号波动的影响,发展更加完善的遥感土壤湿度方法等是今后在此项研究中所要解决的问题。     

中国土壤有机质含量变异性与空间尺度的关系

以中国土种志资料为基础,分析了土壤有机质含量变异与空间尺度的关系及土类内和土类间的变异程度,探讨了不同空间尺度单元下,土壤有机质平均含量与土壤性质的相关性。结果表明,以土壤剖面为单元,随着土壤剖面数的增加,土壤有机质含量的变异系数增大;行政区域尺度单元内部土壤有机质变异程度大于单元间土壤有机质含量的变异程度。以土壤分类单元为空间单元,土类内的有机质含量变异程度小于土类间的变异程度。随着统计单元空间尺度的增大,土壤有机质含量与土壤性质之间的相关性减弱。因此,采用网格法或行政区划分空间区域,获得空间区域单元内土壤有机质含量或贮量的精确估算需要较多的剖面,但外推至数据不足的空间区域时,估算的不确定较小;采用土壤分类单元为空间区域单元,结果则相反。     

利用气象要素计算五道梁地区土壤热流量的试验

根据五道梁地区1994—1997年的热流板测量土壤热流值,初步分析了该地区土壤热流随时间的变化特征。利用1994—1996年的月平均资料分别分析了总辐射、地表温度、地表温度和80 cm深度温度差和2 cm、10 cm深度的土壤热流的相关性,并建立了相应的回归方程;利用得到的回归方程对1997年的土壤热流作计算检验,就月平均资料来说,用总辐射和地温差来计算浅层土壤热流结果是比较可靠的。     

陆表自然和人文要素相互作用——“全球变化及应对”重点专项研究进展

在国家重点研发计划支持下,项目提出了陆表不均一性检测和订正的新方法,解决了渐变型不均一性检测和订正的难题,构建了中国地表太阳辐射、气温、地温、风速和降水等参数均一化站点和格点数据集,修订了关于中国地表风速变化趋势、增温格局及其形成机制的结论。融合多源数据,构建并验证了千米级、流域级或县域级的电厂、人口、生物质能、取水量、氮排放、二氧化碳排放等影响自然系统的关键人文要素历史和未来预估数据集。构建了未来关键人文要素情景,研制了碳中和目标下甲烷和氧化亚氮排放情景和用于驱动全球模式的未来情景,预估了中国碳中和战略的实施对全球变暖的减缓作用,发现中国碳中和对远期和中期全球变暖的减缓作用显著。给出了中国各省份水体氮排放安全阈值及超越时间,阐明了中国粮食产量与氮施肥的关系,提出了在保障粮食安全的前提下减少水体氮排放的有效途径,指出重构城乡养分循环体系是同时保障粮食安全和恢复水质的必要途径。发现全球饱和水汽压差的年际变化与大气二氧化碳浓度上升速率的年际变化显著相关,阐明了饱和水汽压差变化在调控生态系统生产力中的重要角色以及多因素耦合作用在生态系统生产力变化中的复杂影响。建议更全面细致地评估中国各种碳中...     

土氡测量在海口市活动断层探测中的初步应用

运用土壤氡射气(土氡)测量方法对海口市的六条隐伏断层进行探测,检验土壤氡射气(土氡)测量在海口市地区的有效性,结果表明,土氡测量探测晚更新世(Q3)和全新世(Q4)隐伏断层具有较好的效果,可以作为海口市活动断层探测一种有效手段。     

Analysis of resistance factors for LRFD of soil nail pullout limit state using default FHWA load and resistance models

Abstract

Resistance factors for load and resistance factor design (LRFD) of pullout limit state of both permanent and temporary soil nails are calibrated against a wide design space using the current Federal Highway Administration (FHWA) nail load and resistance models. The calculated resistance factors were shown to scatter broadly among design scenarios that differ in wall face batter, soil friction angle, nail ultimate bond strength, and surcharge live load. An important lesson learned from the analysis results is that the current practice of using a single resistance factor for LRFD of nail pullout limit state could not result in uniform reliabilities across different design scenarios. Simple artificial neural network (ANN) models were developed for computation of resistance factors. Design examples demonstrated the ability of the ANN models in providing resistance factors that yield satisfactory and consistent reliabilities in different nail pullout designs.     

Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.