Environmental Kuznets curve for CO2 emissions in China: A spatial panel data approach

Different from previous studies which mainly focused on conventional estimation techniques, this paper examines the CO₂ EKC hypothesis of China using a spatial panel data model to avoid the coefficient estimation error covering the period of 1997–2012. Furthermore, a comparative analysis of the turning points between the non-spatial panel model and spatial panel model is conducted. The results show that the relationship between economic growth and CO₂ emissions shapes as an inverted-N trajectory. Spatial spillovers effects are confirmed to affect the shape of the CO₂ environmental Kuznets curve. There exists an apparent block distribution in spatial structure of China's provincial CO₂ emissions. Specifically, CO₂ emissions have a relatively sharp increase from the eastern regions to the central and the western regions of China. It has also been found that urbanization and coal combustion are main factors on increasing CO₂ emissions. While the trade openness contributes to slight decrease in CO₂ emissions. The government should make targeted carbon-reduction policies for CO₂ emission reduction.     

The energy-environment efficiency of road and railway sectors in China: Evidence from the provincial level

The transportation sector, particularly the road and the railway sectors, is an important source of CO₂ emissions in China. This study combines the non-radial data envelopment analysis (DEA) model with window analysis to measure the energy-environment efficiency of the road and railway sectors of 30 provinces in China, then uses the Tobit regression model to analyze the factors affecting the energy-environment efficiency. The findings suggest that, first of all, although these two sectors are both with high energy-environment efficiency, there is a higher probability for railway sector to improve its energy-environment efficiency than that of road sector, with the average energy-environment efficiency 0.9307 and 0.9815, respectively. Second, the road sector in eastern China with the highest average energy-environment efficiency, lower in the western region, and lowest in the central region. As for the railway sector, the western region has the highest average energy-environment efficiency, followed by the central and the eastern regions. Third, the relationship between energy-environment efficiency and income level in the road and railway sectors follow the U-shaped and inverted U-shaped curves, respectively.     

Panel estimation for the impacts of population-related factors on CO2 emissions: A regional analysis in China

A large accumulation of carbon dioxide emission have attracted much attention recently. The existing researches mainly focused on such impact factors of carbon dioxide emission as population, economy, technology and others. However, there is little specific guidance for the subdivision of demographic factors. This paper employed STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model to examine the impact of population size, per capita consumption, energy intensity, urbanization and aging population on CO₂ emissions by adopting panel data of 30 provinces from 1997 to 2012. Taking the climate change as a control variable, we can get the result that the population size, per capita consumption and energy intensity have strong explanatory power on CO₂ emissions in the three regions. The urbanization level has a positive influence on carbon emissions in the western region and has a negative effect in the central region, while it is not statistically significant in the eastern region. Aging population increases emissions in the eastern region, while decreases emissions in the central region and the western region.     

中国电力行业CO2减排潜力及其贡献因素

电力行业低碳转型是中国低碳经济转型进程中关键行业之一,如何科学分析电力行业的碳减排潜力,确定操作性强的低碳转型路线、提出有效的政策措施是中国政府亟待解决的焦点问题之一。考虑终端电力消费、低碳能源发电占比、火力发电结构、火力发电效率、线损率等因素,构建了自底向上的电力行业CO2排放核算模型,在此基础上,利用情景分析方法探索中国电力行业2015和2020年的CO2减排潜力,进一步利用对数平均权重分解法(LMDI,Logarithmic Mean weight Divisia Index method)对电力行业CO2减排影响因素的贡献度做了归因分析。结果显示,相比基准情景,在当前政策情景和低碳政策情景下,电力行业将分别带来27.0亿t和36.9亿t的CO2减排量。低碳能源发电和火力发电效率是未来对CO2减排最重要的两个贡献因素。终端电力消费量一直是促进电力行业CO2排放增长最重要的贡献因素,因此通过电力需求侧管理等手段控制电力消费量对电力行业的低碳发展至关重要。最后结合减排贡献因素分析的结果为中国电力行业低碳发展提出了相应的政策建议。     

Satellite‐derived estimations of spatial and seasonal variation in tropospheric carbon dioxide mass over China

China has frequently been questioned about the data transparency and accuracy of its energy and emission statistics. Satellite‐derived remote sensing data potentially provide a useful tool to study the variation in carbon dioxide (CO₂) mass over areas of the earth's surface. In this study, Greenhouse gases Observing SATellite (GOSAT) tropospheric CO₂ concentration data and NCEP/NCAR reanalysis tropopause data were integrated to obtain estimates of tropospheric CO₂ mass variations over the surface of China. These variations were mapped to show seasonal and spatial patterns with reference to China's provincial areas. The estimates of provincial tropospheric CO₂ were related to statistical estimates of CO₂ emissions for the provinces and considered with reference to provincial populations and gross regional products (GRP). Tropospheric CO₂ masses for the Chinese provinces ranged from 53 ± 1 to 14,470 ± 63 million tonnes were greater for western than for eastern provinces and were primarily a function of provincial land area. Adjusted for land area troposphere CO₂ mass was higher for eastern and southern provinces than for western and northern provinces. Tropospheric CO₂ mass over China varied with season being highest in July and August and lowest in January and February. The average annual emission from provincial energy statistics of CO₂ by China was estimated as 10.3% of the average mass of CO₂ in the troposphere over China. The relationship between statistical emissions relative to tropospheric CO₂ mass was higher than 20% for developed coastal provinces of China, with Shanghai, Tianjin, and Beijing having exceptionally high percentages. The percentages were generally lower than 10% for western inland provinces. Provincial estimates of emissions of CO₂ were significantly positively related to provincial populations and gross regional products (GRP) when the values for the provincial municipalities Shanghai, Tianjin, and Beijing were excluded from the linear regressions. An increase in provincial GRP per person was related to a curvilinear increase in CO₂ emissions, this being particularly marked for Beijing, Tianjin, and especially Shanghai. The absence of detection of specific elevation of CO₂ mass in the troposphere above these municipalities may relate to the rapid mixing and dispersal of CO₂ emissions or the proportion of the depth of the troposphere sensed by GOSAT.     

中国区域间隐含碳排放转移

利用投入产出模型,对消费视角下碳排放的核算方法及国际贸易中隐含碳排放转移的研究是当前国际学术界碳排放研究的焦点问题之一。在梳理国内外相关研究进展的基础上,利用区域间投入产出模型构建了区域间隐含碳排放转移的核算方法,并计算了1997年和2007年中国8个主要区域间隐含的碳排放转移及其变化。结果显示,不管是在规模还是空间上,中国区域间隐含碳排放转移都发生了很大变化,总体上呈现向西部地区延伸的趋势,尤其是西北地区成为最大的碳排放承接区域。而京津和东南沿海地区始终是主要的碳转出地区,尤其是东南沿海地区因出口而导致的碳排放向中西部地区转移的增加最为明显。因此,调整东部地区的出口结构,优化投资和消费结构,避免落后淘汰产能通过区域转移进一步发展,提高节能技术的应用是我国节能减排工作的重要内容。     

CO2, economic growth,and energy consumption in China's provinces: Investigating the spatiotemporal and econometric characteristics of China's CO2 emissions

This study addresses the spatiotemporal variations at play in China's CO₂ emissions, based on an estimation of emission levels in the period 1995–2012 and an provincial analysis of the relationship of CO₂ emissions to economic growth and energy consumption. Using a series of econometric models and data on the combustion of fossil fuels and cement manufacturing, the study first estimated CO₂ emission levels during the study period, exploring their spatiotemporal pattern. The results indicate that both China's total and its per capita CO₂ emissions have increased significantly over the study period, with both measures evidencing a similar evolution (albeit one that is characterized by noticeable regional discrepancies at the provincial level and which displays properties of convergence). From a geographical perspective, we found both total and per capita CO₂ emissionsto be higher in China's eastern region than in the country's central and western regions. Panel data analysis was subsequently undertaken in order to quantify the dynamic casual relationship between economic growth, energy consumption, and CO₂ emissions. The empirical results indicated that the variables were in fact cointegrated and exhibited a long-run positive relationship. The results of further Granger causality tests indicated the existence of a bidirectional positive causality between economic growth and energy consumption, as well as between energy consumption and CO₂ emissions, and a unidirectional positive causality running from economic growth to CO₂ emissions. The findings of this study suggest that China is, in the long run, dependent on carbon energy consumption for its rapid economic growth, a dependency which is the cause of considerable increases in CO₂ emissions. China should therefore make greater efforts to develop low-carbon technologies and renewable energy, and improve energy efficiency in order to reduce emissions and achieve green economic growth.     

能源活动CO2排放不同核算方法比较和减排策略选择

能源活动CO₂排放是温室气体排放的最重要部分,这部分CO₂排放量的核算是温室气体清单编制和减排方案制定的关键和基础。采用直接法、电热终端法和隐含终端法核算了2009年中国能源消费的CO₂排放量,对不同核算法的CO₂排放部门分布、部门排放强度进行了比较,明确不同核算方法的差异和适用范围。采用电热终端法的核算结果定量分析了各产业部门和工业行业的经济增长和排放强度变化对中国能源活动CO₂排放增长的影响。结果表明,中国2009年隐含终端CO₂排放量为65.6亿t,略高于直接和电热终端CO₂排放量62.2亿t。3种核算方法的CO₂排放部门分布和排放强度有明显的差异:电、热力生产与供应业的直接排放占比为45.2%,而电热终端CO₂排放仅占4.5%;制造业的直接法、电热终端法和隐含终端法核算的CO₂排放占比分别为35.3% 、61.1%和65.5%,是终端能源消费CO₂排放最主要的部门;制造业、电热力生产与供应业和交通运输业的电热终端CO₂排放强度分别为2.166、1.72和1.622 t CO₂/万元GDP,是排放强度较高的部门。在产业部门中,制造业的色金属冶炼及压延加工业、非金属矿物制品业等5个行业以9.8%的经济增长贡献,排放了52.4%的CO₂,是产业结构调整、技术和工程减排的重点;服务业以7.2%的CO₂排放,贡献了38.4%的经济增长,应作为中国低碳经济优先发展的产业。     

The elasticity of the potential of emission reduction to energy saving: Definition,measurement, and evidence from China

Based on energy and CO₂ emission efficiencies, this paper proposes a definition of the elasticity of the potential of emission reduction to energy saving (E_peres), and measures the elasticity in China’s 30 provincial regions. Although E_peres is a relative definition, it can be used (1) to measure the amount of reduced CO₂ emissions per unit fossil energy saving, (2) to reflect the effectiveness of fossil energy saving for CO₂ emission reduction in different regions, and (3) to provide decision-making criteria for selecting pathways for emission reductions in different regions. The results show that compared with energy saving, emission reduction is a more serious issue in China. This indicates that energy saving policies have been highly effective since their implementation during the 11th “Five-Year Plan”. With respect to provincial disparities, the emission reductions caused by fossil energy saving are not significant in Beijing, Shanghai, and Guangdong. Fujian province has significant E_peres, indicating that emission reduction causing by fossil energy saving is effective. E_peres has been increasing over time in Hunan and Hubei. Hainan’s E_peres has remained less than 1, indicating that its emission-reduction effect of fossil energy saving is worse than in other provinces. Moreover, the elasticity of Eastern China is greater than that of Central China and Western China. This finding sheds light on pathway selection for energy saving and emission reduction in China: it would be more appropriate to encourage fossil energy saving in Eastern China, and to promote clean energy use (e.g., water electricity and solar energy) in Central China and Western China.     

中国农业系统近40年温室气体排放核算

基于排放因子法构建了包含种植业和牲畜养殖业的农业系统温室气体排放核算体系,系统核算了1980-2020年我国全国尺度上的农业系统温室气体排放总量和变化趋势,并在区县级尺度下对1980、2000、2011年的中国农业系统的温室气体排放量进行核算,对比不同阶段农业系统温室气体排放变化的时空异质性规律。研究发现：1980-2020年我国农业系统温室气体排放量呈波动增长趋势,增长了近46%。CH₄是农业系统排放贡献最大的温室气体,占总排放量的47.33%。我国农业系统温室气体排放与不同地区农业生产方式有关,CH₄排放量高的地区主要位于我国主要水稻产区以及旱地作物产区。CO₂排放量高的地区主要位于东北、西北等地区以及华东地区。N₂O排放量较高地区主要位于西北的主要畜牧养殖地区,以及我国农业经济发展水平高的中南部地区。研究有助于揭示我国农业温室气体排放的动态特征,现状规律,以及空间差异性特征,从农业减排角度为实现双碳目标提供科学参考。     

CO2 emissions from the Chinese cement sector: Analysis from both the supply and demand sides

China is the largest producer and consumer of cement worldwide, and cement production entails the release of substantial carbon dioxide (CO₂) emissions. As the cement sector is a crucial sector of the Chinese economy, understanding the role of supply‐ and demand‐side factors may help accelerate efforts to mitigate CO₂ emissions. However, few studies have analyzed the critical factors affecting CO₂ emissions in the sector based on a combined supply‐ and demand‐side perspective. In this study, we developed an integrated framework that included eleven indicators covering both the supply and demand sides. Results revealed that improving cement production technology cannot offset CO₂ emissions from the growth in demand for cement. Improving technology on the supply side would considerably reduce CO₂ emissions from Chinese cement production; nevertheless, the combination of rapid urbanization, GDP growth, and an ultra‐high fixed capital formation ratio on the demand side increased CO₂ emissions nearly 25‐fold from 1990 to 2015. Notably, some demand‐side factors also had an effect that reduced CO₂ emissions. The in‐use stock per unit of fixed capital formation and output per in‐use stock reduced CO₂ emissions by 332 million metric tons, which is comparable to the contribution of technological progress. Based on these results, we examine why these demand‐side factors substantially influence CO₂ emissions in the Chinese cement sector, and we provide recommendations for policy‐makers on carbon‐reduction measures in this CO₂‐intensive sector.     

How do 28 European Union Member States perform in agricultural greenhouse gas emissions? It depends on what we look at: Application of the multi-criteria analysis

European Union (EU) Member States have agreed to limit their greenhouse gas (GHG) emissions from sectors not covered by the EU Emissions Trading Scheme, including emissions from agricultural sector. The aggregated GHG emission rate (i.e. t CO₂ eq. from agricultural sector per country) is commonly used to measure the overall size of agriculture’s influence on climate. And indeed, since 2005, EU has managed to decrease its aggregated GHG emissions by 3.1%. However, the question is—does that mean that EU’s agriculture has become less emission intensive? This paper answers the question by providing a different perspective for the assessment and comparison of the agricultural GHG emissions in 28 EU Member States. It is done by applying three different approaches, including creation of derived indicators and application of multi-criteria analysis (TOPSIS), which is a novel approach for comparison of agricultural GHG emission mitigation performance. The results show that each EU Member State performs very differently in emission intensities. Even more, the emission intensity results show an alarming tendency of increase in most of the EU Member States, which indicates that the measured changes in aggregate agricultural GHG emission rates are misleading. Therefore, the paper suggests reconsidering the policy targets for GHG emission limits.     

Environmental regulation and CO2 emissions: Based on strategic interaction of environmental governance

In order to reduce carbon emissions and improve environmental governance, the paper discusses the interactive forms of environmental regulation based on the two-regime spatial Durbin model. The effects of environmental regulation and interactive behavior of environmental regulation on carbon dioxide (CO₂) emissions are explored by using the spatial lag of X (SLX) model. It is found that there is a diversified competitive behavior in the enforcement of environmental regulation among local governments in China. And the diversified competitive behavior results in the nearby transfer of pollution, which increases local CO₂ emissions. In addition, there is an inverted "U" curve between environmental regulation and CO₂ emissions, and China is still in the "green paradox" stage. Furthermore, it is found that the environmental regulation mainly affects CO₂ emissions through industrial structure and technological progress. Also, there are differences in the spatial spillover effect of environmental regulation due to the existence of regional heterogeneity, and its impact on CO₂ is particularly significant in the western region. The findings indicate that the central government should strengthen targeted supervision and adaptive incentives for local governments to implement environmental regulation so that joint emission reduction can be promoted.     

基于GIS技术的1991-2000年中国农田化肥氮源一氧化二氮直接排放量估计

依据政府间气候变化专门委员会(IPCC)对农田N₂O排放因子的定义,将气候和种植制度等N₂O排放的主控因素引入到估算方法中,结合GIS技术估计了中国农田化肥氮导致的N₂O直接排放量的空间分布和年际变异.结果表明,在1991—2000年间由于化肥投入量的增加,中国农田化学氮源N₂O排放呈上升趋势.20世纪90年代的平均年排放量为204 Gg N₂O-N,变幅为159～269 Gg N₂O-N,排放量最高的年份出现在1998年,而1992年排放量为最低.估算结果的不确定性约为23％.受施氮量和降水的影响,N₂O排放通量表现出明显的地区差异,东部较高,西北偏低.     

Life cycle energy use and CO<Subscript>2</Subscript> emissions of small-scale gold mining and refining processes in the Philippines

Purpose

Gold is one of the most significant metals in the world, with use in various sectors including the electronic, health, and fashion industries. The Philippines has the world’s third largest known Au deposits and is ranked 20th in global gold production. Of the country’s annual production, about 80% is from the small-scale gold mining (SSGM) sector. This work estimates the first location-specific life cycle energy use and CO₂ emissions of SSGM establishments in the Philippines.

Methods

Process-based LCA was used with functional unit of 100 g Au and observed data from 2010 to 2011 for mining, comminution, recovery, and refining. Four gold production paths were observed in the provinces of Benguet and Camarines Norte, namely, amalgamation, cyanidation with carbon-in-leach (CIL), cyanidation with leaching with zinc, and combination of amalgamation and cyanidation with CIL.

Results and discussion

It was estimated that 3–18 g of Au was extracted for every ton of ore within 57–159 man-hours from mining to refining. Energy use estimates ranged from 3501 to 67,325 MJ/100 g Au, while CO₂ emission estimates ranged from 398 to 5340 kg CO₂/100 g Au. The combination of amalgamation and cyanidation with CIL processes was the least energy and carbon intensive, while cyanidation with CIL process was the most intensive. Electricity use accounted for 95–100% of total emissions, except in cyanidation with CIL where kerosene accounts for 77% of the total. Since SSGMs contributed 80% of the 40 tons of Au produced in the Philippines in 2014, the SSGM energy use was estimated to be between 1120 and 21,544 TJ and the CO₂ emissions to be between 129 and 1726 ktons CO₂. Energy estimates are most sensitive to refining process yield and electrical equipment efficiency.

Conclusions

The estimated life cycle emissions rate for SSGM in the Philippines is lower than available estimates of large-scale mining. Notwithstanding, given the sector’s reliance on fossil fuels for its energy needs and the Philippines’ pledge to reduce its CO₂ footprint by 70% in 2030, every effort to mitigate energy use and CO₂ emission counts. Three main recommendations toward energy consumption and CO₂ emissions reduction in SSGMs are proposed: (1) policy to promote technologies that are energy-efficient and processes that maximize gold process yield, (2) effective Minahang Bayan (SSGM mining zone mandated by law) implementation to ensure use of higher-grade ores, and (3) adoption of renewable energy in Minahang Bayans to promote energy independence and mitigate CO₂ emissions.

     

青藏高原东缘生态过渡带碳中和评估与预测

青藏高原东缘生态过渡带是我国重要的生态功能区和碳库,对该区域碳中和的评估和预测对于中国乃至亚洲的碳排放管理具有重要意义。基于率定的CASA模型估算了2001-2019年青藏高原东缘生态过渡带栅格尺度碳汇量,结合中国碳排放数据库分析近20年碳排放时空演变规律;然后,采用STIRPAT模型和岭回归建立碳排放与人口等6个社会经济指标的弹性关系,并讨论库兹涅兹曲线对碳排放的影响。之后采用情景分析法,设计包括绿色发展等5种不同经济发展情景预测研究区2020-2060年碳排放变化特征;最后,提出假性碳中和并进行定义,结合GM （1,1）模型预测所得碳汇量,探究青藏高原东缘生态过渡带净碳汇量未来不同情景演变趋势,预测与评估不同发展情景研究区碳中和状况。结果表明：研究区碳汇量在2001-2019年间呈波动缓慢上升趋势,研究区碳汇量东南部高西北部较低;而碳排放量增长速率迅速,于2019年达到108Mt左右,是2001年的3.07倍;近20年,研究区碳汇量均大于碳排放量,但二者差距呈减少趋势。STIRPAT模型岭回归系数表明,研究区内存在城镇化率环境库兹涅兹曲线（EKC）效应,随着城镇化率的提升,区域碳排放呈先增加后减少趋势,而对于富裕度无显著EKC效应;在6个影响因素中,人口变量对碳排放的影响最显著,每增加1%的人口,碳排放将增加1.03%左右;在预测的五种不同发展情景中,可持续发展情景（ST）与基准情景（BL）、节能情景（ES）与绿色发展情景（GD）分别在2050年、2040年实现碳达峰,碳达峰时间随着能耗的减少逐渐提前。粗放情景（ETS）在2060年仍未实现碳达峰,并且其碳排放将于2040年左右超过碳汇量,而其余四种情景预测2020-2060年碳汇量始终大于碳排放量,但其净碳汇量均呈先减少后增加的趋势。因此,青藏高原东缘生态过渡带具有较强固碳能力,但如采用不加管制的发展模式,其碳汇量将无法抵消其碳排放量。因此,在规划发展模式与保护生态的同时,应重点控制人口、畜牧业等因素,提高人民与产业的节能减排意识。     

我国典型城市化石能源消费CO2排放及其影响因素比较研究

城市是化石能源消费和CO₂排放的主要区域。分析典型城市化石能源消费CO₂排放特征,明确不同城市CO₂排放动态及主要影响因素的差异,是开展城市减排行动的重要科学依据。采用IPCC推荐方法及中国的排放参数核算11个典型城市2006—2015年间化石能源消费产生的CO₂排放量。根据各城市经济发展和CO₂排放特征将之分为四类:经济高度发达城市(北京、上海、广州)、高碳排放城市(重庆、乌鲁木齐、唐山)、低排放低增长城市(哈尔滨、呼和浩特和大庆)和低排放高增长城市(贵阳、合肥),并运用对数平均迪氏指数法(Logarithmic Mean Divisia Index,即LMDI分解法)对比分析了四类城市CO₂排放量的影响因素。结果表明:(1)研究期内大部分城市CO₂排放总量有所增加,仅北京和广州呈下降趋势,工业部门CO₂排放在城市排放总量及其变化中占据主导地位;四类城市的人均CO₂排放量表现出与排放总量相...     

An estimate of greenhouse gas (N2O and CO2) mitigation potential under various scenarios of nitrogen use efficiency in Chinese croplands

It is well recognized that improving nitrogen use efficiency (NUE) can directly reduce nitrous oxide (N₂O) emission in cropland and indirectly reduce carbon dioxide (CO₂) release from nitrogen (N) production, while such a reduction has not been well quantified in China. We estimated the greenhouse gas (GHG; N₂O and CO₂) mitigation potential (MP) from Chinese cropland and its regional distribution by quantifying NUE and determining the amount of over‐applied synthetic N under various scenarios of NUE. We estimated that synthetic NUE in the late 1990s was 31±11% (mean±SD) for rice, 33±13% for wheat, and 31±11% for maize cultivation. Improving NUE to 50% could cut 6.6 Tg of synthetic N use per year, accounting for 41% of the total used. As a result of this reduction, the direct N₂O emission from croplands together with CO₂ emission from the industrial production and transport of synthetic N could be reduced by 39%, equivalent to 60 Tg CO₂ yr^?1. The MP was probably underestimated because organic N supply was not taken into account when estimating NUE. It was concluded that improving N management can greatly reduce GHG (N₂O and CO₂) emissions in Chinese croplands, and mitigation in the Jiangsu, Henan, Shandong, Sichuan, Hubei, Anhui, and Hebei provinces should be given priority.     

共享社会经济路径下中国2020—2100年碳排放预测研究

碳排放和减碳经济代价研究日益受到学术界和决策者的关注,中国政府做出的关于争取在2060年前实现碳中和的表态引起了国际社会的热议。在此背景下,开展中国未来长时间序列碳排放的情景预测具有切实意义。基于可拓展的随机性环境影响评估模型（STIRPAT）评估了人口、经济和受教育程度对碳排放的影响,对比历史数据并验证了碳排放预测模型的准确性,结合共享社会经济路径（SSPs）情景的设定和模型参数,预测了5种情景下中国2020年至2100年的碳排放轨迹及经济代价。结果表明：（1）考虑碳排放达峰目标的实现,SSP3情景是中国未来发展的最佳情景,在此情景下,中国有望提前三年实现碳排放达峰目标;（2） SSP3情景可使中国年度总碳排放量和人均碳排放量处于相对其他四种情景的最低值,但需要付出累积GDP下降5.49%至8.80%的代价;（3）为完成在2060年前实现碳中和的承诺,中国政府在未来的40年需面对409.36-467.42 Gt的碳中和量;（4）2020年中国的碳排放强度将会较2005年水平下降40.52%至41.39%,2030年碳排放强度将会较2005年水平下降59.64%至60.75%。5种情境中,SSP5情景是降低碳排放强度的最佳情景,可最大程度地超额实现碳排放强度目标。未来,受经济发展、人口增长等重要因素影响,中国政府减碳压力将进一步加大。后疫情时代,考虑到能源供应的减少和高科技产业的发展,碳排放社会成本的上升将为中国创造一个使能源系统脱碳的机遇。中国应在"十四五"期间继续提升能源利用效率、升级产业结构、提倡低碳消费、实施隐含碳战略,以尽快实现碳减排目标。     

Comparison of Photosynthetic Performance in Triazine-Resistant and Susceptible Biotypes of Amaranthus hybridus

The rate of CO₂ reduction in the S-triazine-resistant biotype of smooth pigweed (Amaranthus hybridus L.) was lower at all levels of irradiance than the rate of CO₂ reduction in the susceptible biotype. The intent of this study was to determine whether or not the lower rates of CO₂ reduction are a direct consequence of the same factors which confer triazine resistance. The quantum yield of CO₂ reduction was 23 ± 2% lower in the resistant biotype of pigweed and the resistant biotype of pigweed had about 25% fewer active photosystem II centers on both a chlorophyll and leaf area basis. This quantum inefficiency of the resistant biotype can be accounted for by a decrease in the equilibrium constant between the primary and secondary quinone acceptors of the photosystem II reaction centers which in turn would lead to a higher average level of reduced primary quinone acceptor in the resistant biotype. Thus, the photosystem II quantum inefficiency of the resistant biotype appears to be a direct consequence of those factors responsible for triazine resistance but a caveat to this conclusion is discussed. The effects of the quantum inefficiency of photosystem II on CO₂ reduction should be overcome at high light and therefore cannot account for the lower light-saturated rate of CO₂ reduction in the resistant biotype. Chloroplast lamellar membranes isolated from both triazine-resistant and triazine-susceptible pigweed support equivalent rates of whole chain electron transfer and these rates are sufficient to account for the rate of light-saturated CO₂ reduction. This observation shows that the slower transfer of electrons from the primary to the secondary quinone acceptor of photosystem II, a trait which is characteristic of the resistant biotype, is nevertheless still more rapid than subsequent reactions of photosynthetic CO₂ reduction. Thus, it appears that the lower rate of light-saturated CO₂ reduction of the resistant biotype is not limited by electron transfer capacity and therefore is not a direct consequence of those factors which confer triazine resistance.