Quantification of CO_(2) Emissions from Three Power Plants in China Using OCO-3 Satellite Measurements

Coal-fired power plants are a major carbon source in China. In order to assess the evaluation of China's carbon reduction progress with the promise made on the Paris Agreement, it is crucial to monitor the carbon flux intensity from coal-fired power plants. Previous studies have calculated CO_(2) emissions from point sources based on Orbiting Carbon Observatory-2 and-3(OCO-2 and OCO-3) satellite measurements, but the factors affecting CO_(2) flux estimations are uncertain. In this study, we employ a Gaussian Plume Model to estimate CO_(2) emissions from three power plants in China based on OCO-3 XCO_(2) measurements. Moreover, flux uncertainties resulting from wind information, background values,satellite CO_(2) measurements, and atmospheric stability are discussed. This study highlights the CO_(2) flux uncertainty derived from the satellite measurements. Finally, satellite-based CO_(2) emission estimates are compared to bottom-up inventories.The satellite-based CO_(2) emission estimates at the Tuoketuo and Nongliushi power plants are ~30 and ~10 kt d^(-1) smaller than the Open-Data Inventory for Anthropogenic Carbon dioxide(ODIAC) respectively, but ~10 kt d^(-1) larger than the ODIAC at Baotou.

Regulatory potential of soil available carbon,nitrogen,and functional genes on N_(2)O emissions in two upland plantation systems

Dynamic nitrification and denitrification processes are affected by changes in soil redox conditions,and they play a vital role in regulating soil N_(2)O emissions in rice-based cultivation.It is imperative to understand the influences of different upland crop planting systems on soil N_(2)O emissions.In this study,we focused on two representative rotation systems in Central China:rapeseed–rice(RR)and wheat–rice(WR).We examined the biotic and abiotic processes underlying the impacts of these upland plantings on soil N_(2)O emissions.The results revealed that during the rapeseed-cultivated seasons in the RR rotation system,the average N_(2)O emissions were 1.24±0.20 and 0.81±0.11 kg N ha^(–1)for the first and second seasons,respectively.These values were comparable to the N_(2)O emissions observed during the first and second wheat-cultivated seasons in the WR rotation system(0.98±0.25 and 0.70±0.04 kg N ha^(–1),respectively).This suggests that upland cultivation has minimal impacts on soil N_(2)O emissions in the two rotation systems.Strong positive correlations were found between N_(2)O fluxes and soil ammonium(NH_(4)^(+)),nitrate(NO_(3)^(–)),microbial biomass nitrogen(MBN),and the ratio of soil dissolved organic carbon(DOC)to NO_(3)^(–)in both RR and WR rotation systems.Moreover,the presence of the AOA-amoA and nirK genes were positively associated with soil N_(2)O fluxes in the RR and WR systems,respectively.This implies that these genes may have different potential roles in facilitating microbial N_(2)O production in various upland plantation models.By using a structural equation model,we found that soil moisture,mineral N,MBN,and the AOA-amoA gene accounted for over 50%of the effects on N_(2)O emissions in the RR rotation system.In the WR rotation system,soil moisture,mineral N,MBN,and the AOA-amoA and nirK genes had a combined impact of over 70%on N_(2)O emissions.These findings demonstrate the interactive effects of functional genes and soil factors,including soil physical characteristics,available carbon and nitrogen,and their ratio,on soil N_(2)O emissions during upland cultivation seasons under rice-upland rotations.

Refining the Factors Affecting N_(2)O Emissions from Upland Soils with and without Nitrogen Fertilizer Application at a Global Scale

Nitrous oxide(N_(2)O)is a long-lived greenhouse gas that mainly originates from agricultural soils.More and more studies have explored the sources,influencing factors and effective mitigation measures of N_(2)O in recent decades.However,the hierarchy of factors influencing N_(2)O emissions from agricultural soils at the global scale remains unclear.In this study,we carry out correlation and structural equation modeling analysis on a global N_(2)O emission dataset to explore the hierarchy of influencing factors affecting N_(2)O emissions from the nitrogen(N)and non-N fertilized upland farming systems,in terms of climatic factors,soil properties,and agricultural practices.Our results show that the average N_(2)O emission intensity in the N fertilized soils(17.83 g N ha^(-1)d^(-1))was significantly greater than that in the non-N fertilized soils(5.34 g N ha^(−1) d^(−1))(p<0.001).Climate factors and agricultural practices are the most important influencing factors on N_(2)O emission in non-N and N fertilized upland soils,respectively.For different climatic zones,without fertilizer,the primary influence factors on soil N_(2)O emissions are soil physical properties in subtropical monsoon zone,whereas climatic factors are key in the temperate zones.With fertilizer,the primary influence factors for subtropical monsoon and temperate continental zones are soil physical properties,while agricultural measures are the main factors in the temperate monsoon zone.Deploying enhanced agricultural practices,such as reduced N fertilizer rate combined with the addition of nitrification and urease inhibitors can potentially mitigate N_(2)O emissions by more than 60%in upland farming systems.

A combination of straw incorporation and polymer-coated urea offsets soil ammonia and nitrous oxide emissions in winter wheat fields

The combined effects of straw incorporation(SI)and polymer-coated urea(PCU)application on soil ammonia(NH_(3))and nitrous oxide(N_(2)O)emissions from agricultural fields have not been comprehensively evaluated in Northwest China.We conducted a two-year field experiment to assess the effects of combining SI with either uncoated urea(U)or PCU on soil NH_(3)emissions,N_(2)O emissions,winter wheat yields,yield-scaled NH_(3)(/NH_(3)),and yield-scaled N_(2)O(/N_(2)O).Five treatments were investigated,no nitrogen(N)fertilizer(N_(0)),U application at 150 kg N ha-1 with and without SI(SI+U and S_(0)+U),and PCU application at 150 kg N ha^(-1) with and without SI(SI+PCU and S_(0)+PCU).The results showed that the NH_(3);emissions increased by 20.98-34.35%following Sl compared to straw removal,mainly due to increases in soil ammonium(NH_(4)^(+)-N)content and water-flled pore space(WFPS).SI resulted in higher N_(2)O emissions than under the So scenario by 13.31-49.23%due to increases in soil inorganic N(SIN)contents,WFPS,and soil microbial biomass.In contrast,the PCU application reduced the SIN contents compared to the U application,reducing the NH_(3)and N_(2)O emissions by 45.99-58.07 and 18.08-53.04%,respectively.Moreover,no significant positive effects of the SI or PCU applications on the winter wheat yield were observed.The lowest /NH_(3) and /N_(2)O values were observed under the S_(0)+PCU and SI+PCU treatments.Our results suggest that single PCU applications and their combination with straw are the optimal agricultural strategies for mitigating gaseous N emissions and maintaining optimal winter wheat yields in Northwest China.

Mitigating Carbon Emissions:A Comprehensive Analysis of Transitioning to Hydrogen-Powered Plants in Japan’s Energy Landscape Post-Fukushima

One of the impacts of the Fukushima disaster was the shutdown of all nuclear power plants in Japan,reaching zero production in 2015.In response,the country started importing more fossil energy including coal,oil,and natural gas to fill the energy gap.However,this led to a significant increase in carbon emissions,hindering the efforts to reduce its carbon footprint.In the current situation,Japan is actively working to balance its energy requirements with environmental considerations,including the utilization of hydrogen fuel.Therefore,this paper aims to explore the feasibility and implications of using hydrogen power plants as a means to reduce emissions,and this analysis will be conducted using the energy modeling of the MARKAL-TIMES Japan framework.The hydrogen scenario(HS)is assumed with the extensive integration of hydrogen into the power generation sector,supported by a hydrogen import scheme.Additionally,this scenario will be compared with the Business as Usual(BAU)scenario.The results showed that the generation capacities of the BAU and HS scenarios have significantly different primary energy supplies.The BAU scenario is highly dependent on fossil fuels,while the HS scenario integrates hydrogen contribution along with an increase in renewable energy,reaching a peak contribution of 2,160 PJ in 2050.In the HS scenario,the target of reducing CO_(2) emissions by 80%is achieved through significant hydrogen penetration.By 2050,the total CO_(2) emissions are estimated to be 939 million tons for the BAU scenario and 261 million tons for the Hydrogen scenario.In addition,the contribution of hydrogen to electricity generation is expected to be 153 TWh,smaller than PV and wind power.

Detection of Anthropogenic CO_(2) Emission Signatures with TanSat CO_(2) and with Copernicus Sentinel-5 Precursor(S5P)NO_(2) Measurements:First Results

China’s first carbon dioxide(CO_(2))measurement satellite mission,TanSat,was launched in December 2016.This paper introduces the first attempt to detect anthropogenic CO_(2) emission signatures using CO_(2) observations from TanSat and NO_(2) measurements from the TROPOspheric Monitoring Instrument(TROPOMI)onboard the Copernicus Sentinel-5 Precursor(S5P)satellite.We focus our analysis on two selected cases in Tangshan,China and Tokyo,Japan.We found that the TanSat XCO_(2) measurements have the capability to capture the anthropogenic variations in the plume and have spatial patterns similar to that of the TROPOMI NO_(2) observations.The linear fit between TanSat XCO_(2) and TROPOMI NO_(2) indicates the CO_(2)-to-NO_(2) ratio of 0.8×10^(-16) ppm(molec cm^(-2))^(-1) in Tangshan and 2.3×10^(-16) ppm(molec cm^(-2))^(-1) in Tokyo.Our results align with the CO_(2)-to-NOx emission ratios obtained from the EDGAR v6 emission inventory.

Pancreatic neuroendocrine tumor detected by technetium-99m methoxy-2-isobutylisonitrile single photon emission computed tomography/computed tomography:A case report

BACKGROUND Pancreatic neuroendocrine tumors(NETs)account for about 1%–2%of pancreatic tumors and about 8%of all NETs.Computed tomography(CT),magnetic resonance imaging,and endoscopic ultrasound are common imaging modalities for the diagnosis of pancreatic NETs.Furthermore,somatostatin receptor imaging is of great value for diagnosing pancreatic NETs.Herein,we report the efficacy of technetium-99m methoxy-2-isobutylisonitrile(99mTc-MIBI)single photon emission CT(SPECT)/CT for detecting pancreatic NETs.CASE SUMMARY A 57-year-old woman presented to our hospital with a 1-d history of persistent upper abdominal distending pain.The distending pain in the upper abdomen was aggravated after eating,with nausea and retching.Routine blood test results showed a high neutrophil percentage,low leukomonocyte and monocyte percentages,and low leukomonocyte and eosinophil counts.Amylase,liver and kidney function,and tumor markers alpha-fetoprotein,carcinoembryonic antigen,and cancer antigen(CA)125,CA72-4,CA19-9,and CA153 were normal.Abdominal CT showed a mass,with multiple calcifications between the pancreas and the spleen.The boundary between the mass and the pancreas and spleen was poorly defined.Contrast-enhanced CT revealed that the upper abdominal mass was unevenly and gradually enhanced.99mTc-MIBI SPECT/CT revealed that a focal radioactive concentration,with mild radioactive concentration extending into the upper abdominal mass,was present at the pancreatic body and tail.The 99mTc-MIBI SPECT/CT manifestations were consistent with the final pathological diagnosis of pancreatic NET.CONCLUSION 99mTc-MIBI SPECT/CT appears to be a valuable tool for detecting pancreatic NETs.

超临界CO_(2)脉动压裂-渗流耦合试验系统研制与应用

【目的】为了有效强化煤层气抽采效果,将脉动压裂与超临界CO_(2)压裂相结合,提出了利用超临界CO_(2)脉动压裂煤(岩)的新思路。【方法】自主研发了超临界CO_(2)脉动压裂-渗流耦合真三轴试验系统,介绍了该试验系统的主要结构、特点和功能,然后开展了室内真三轴条件下超临界CO_(2)脉动压裂-渗流试验及超临界CO_(2)脉动压裂-声发射监测试验。该系统结合独立伺服系统与中央数字系统控制三向应力,采用双泵型恒速恒压泵脉动给压,具有高精度、全过程、真三轴、承载高温、高压及高应力的特点。【结果和结论】试验结果表明:超临界CO_(2)脉动压裂-渗流耦合真三轴试验系统可以实现良好的脉动压裂功能。超临界CO_(2)脉动压裂后,煤体渗透率较压裂前呈增大趋势,增大了2~9倍,且煤体渗透率皆呈现良好的指数变化规律。在声发射-超临界CO_(2)脉动压裂时期,煤体产生了新的裂隙通道,该通道由压裂孔中心直接贯穿至煤样表面,且可观测到超临界CO_(2)流体直接从煤中喷出,故超临界CO_(2)脉动压裂具有一定的扩展和连通裂隙的作用,能够有效提高煤层气的抽采效果。研究成果为强化深部低渗煤层增透技术提供了一定的试验支撑。

中国钢铁行业CO_(2)排放特征和减排路径研究——基于ARIMA-LEAP模型

为了消除对于未来粗钢、钢材以及生铁产量预测主观性,基于时间序列中的ARIMA模型,对未来相关产量进行客观预测,构建了中国钢铁行业ARIMA-LEAP模型,并以2020年为基准年,每5a为时间节点,研究了2020~2030年中国钢铁行业不同情景下全流程及各工序的CO_(2)排放情况.在技术进步中考虑了氢还原炼铁技术,在能源结构调整中考虑了发电方式调整,在此基础上分别设置了4种单一情景和4种组合情景来研究其减排潜力.结果表明,4种组合情景下的含有规模减排的3种组合情景CO_(2)减排潜力均高于单一情景.其中SUR+TER､SUR+STR和综合减排情景可以在2030年实现达峰,达峰年均为2021年,达峰时CO_(2)排放量分别为13.225亿t､13.359亿t和13.289亿t.单一情景中相较于基准情景CO_(2)减排量由高到低依次为:规模减排情景(SUR)、结构减排情景(STR)、技术减排情景(TAR),在2030年相对于基准情景的减排量分别为493.1Mt、247.8Mt以及105.1Mt.借助LEAP模型的能源核算以及CO_(2)排放核算功能,研究了综合减排情景下2020~2030年不同工序,不同能源的CO_(2)排量,其中CO_(2)排放较多的3个工序为炼铁､轧钢以及烧结工序,产生CO_(2)较多的4种能源为洗精煤、喷煤粉、电力以及焦炭,其中洗精煤CO_(2)排放量更是达到10Bt级,而其余3种能源也达到Bt级.确定了中国钢铁行业CO_(2)排放特征.对技术减排以及结构减排成本进行简单比较,制定中国钢铁行业CO_(2)减排路径.

Effects of Reduced Nitrogen Fertilization and Biochar Application on CO_2 and N_2O Emissions from a Summer Maize-Winter Wheat Rotation Field in North China

This experiment was conducted in Xinxiang, Henan from June 2013 to June 2014. Total four treatments were designed including farmers ’ common practice （F, 250 kg/hm^2）, 80% F （LF, 200 kg/hm^2）, 80% F＋biochar （LFC） and no fertilizer （CK） to measure the dynamic emissions of CO2 and N2O from a summer maize-winter wheat field by static chamber-gas chromatography method. The results showed that the soil CO2 emission was 21.8-1 022.7 mg/（m^2·h）, and was mainly influenced by soil temperature and moisture content. During the growth of summer maize, the soil CO2 emission was more significantly affected by soil moisture con-tent; and in winter wheat growing season, it was more significantly affected by soil temperature in the top 5 cm. The LF and LFC treatments significantly reduced the soil cumulative CO2 emission, especial y during the growth of winter wheat. Fertiliza-tion and irrigation were the main factors influencing the soil N2O emission. The soil N2O emission during the fertilization period accounted for 73.9%-74.5% and 40.5%-43.6% of the soil cumulative N2O emission during the summer maize-and winter wheat-growing season, respectively. The peak of emission fluxes was determined by fertilization amount, while the occurrence time of emission peak and emission re-duction effect were influenced by irrigation. The LF treatment reduced the soil cu-mulative N2O emission by 15.7%-16.8% and 18.1%-18.5% during the growth period of summer maize and winter wheat, respectively. Reduced nitrogen fertilization is an effective way for reducing N2O emission in intensive high-yielding farmland. Under a suitable nitrogen level （200 kg/hm^2）, the application of biochar showed no significant effect on the soil N2O emission in a short term. The N2O emission factors of the L and LF treatments were 0.60% and 0.56%, respectively. ln the intensive high-yield-ing farmland of North China, reducing the nitrogen application amount is an appro-priate measure to mitigate greenhouse gas emissions without crop yield loss.

铜-硫共存对稻田土壤CH_(4)和N_(2)O排放的影响及其机制

为探究酸性稻田土壤中铜(Cu)和硫(S)共存对温室气体排放的影响,本研究模拟土壤淹水环境开展室内培养实验,以尿素为氮源分别设置CK、CuCl_(2)和CuSO_(4)(5,50,100mgCu/kg)、KCl和K_(2)SO_(4)(阴离子浓度分别与6种Cu处理一致)13种处理,考虑重金属在土壤中充分老化,共培养128d.结果表明:在长期淹水条件下,酸性土壤显著促进铜硫处理中有效Cu和易溶S释放(<0.05),释放量与初始Cu^(2+)和SO_(4)2-添加量成正比,Cu-S共存降低了彼此有效性.与CK相比,CH_(4)和N_(2)O排放在5mg/kg Cu处理、不同浓度KCl和K_(2)SO_(4)处理中均降低,降幅分别为19.4%~56.2%和36.1%~84.5%;在50和100mg/kg Cu处理下显著升高且与Cu浓度成正比(<0.05),增幅分别为28.9%~615.2%和97.5%~337.4%.与KCl处理相比,N_(2)O排放在中、高浓度K_(2)SO_(4)处理中显著降低(<0.05),分别减少74.1%和69.6%,CH_(4)排放未受影响(>0.05).与CuCl_(2)处理相比,CH_(4)和N_(2)O排放在中、高浓度CuSO_(4)处理中显著降低(<0.05),分别减少46.0%、66.0%和17.7%、37.3%.Cu-S作用机制表现为:与Cu单一处理相比,Cu-S共存在CH_(4)排放过程中通过降低产甲烷古菌功能基因(mcrA)和产甲烷细菌功能基因(16S rRNA-CH_(4))丰度减少CH_(4)产生;在N_(2)O排放过程中于培养前期(0~35d)增加氨单加氧酶功能基因(AOB amoA)丰度促进硝化过程N_(2)O产生,培养后期(35~128d)提高氧化亚氮还原酶功能基因(nosZ)丰度促进N_(2)O还原减少了N_(2)O排放.本研究表明变价阴离子可显著影响重金属阳离子参与的温室气体产生的微生物过程,该交互过程的研究对正确评价重金属污染背景下的农田土壤温室气体排放具有重要意义.

基于CEEMDAN-LSTM模型的污水处理厂N_(2)O排放预测研究

在我国实行“双碳”战略的背景下,污水处理厂N_(2)O排放预测对于污水处理厂的碳中和有积极意义。现有的污水处理厂N_(2)O排放预测研究通常直接采用基于包含噪声的N_(2)O排放量数据进行建模预测,导致模型预测精度不高。采用自适应噪声完备集合经验模态分解-长短期记忆网络(CEEMDAN-LSTM)模型,通过引入CEEMDAN方法缓解数据中噪声对模型的影响以提高模型预测精度,对污水处理厂N_(2)O排放进行预测并在预测验证集上验证模型。与LSTM、门控循环单元(GRU)、人工神经网络(ANN)和支持向量机(SVM)模型相比,CEEMDAN-LSTM预测精度最高,均方误差(MSE)、平均绝对误差(MAE)和平均绝对百分比误差(MAPE)分别为5 497.11、56.55和1.22%,能够更高精度地预测N_(2)O排放量,为污水处理厂采取合适的碳中和策略提供理论支撑。

激光熔覆Co-2%Ti_(3)SiC_(2)复合涂层在不同温度及载荷下的摩擦学性能

为了提高304不锈钢的耐磨减摩性能,采用激光熔覆技术在其表面制备了Co-2%Ti_(3)SiC_(2)复合涂层。通过扫描电镜(SEM)、能谱仪(EDS)和X射线衍射仪(XRD)对Co-2%Ti_(3)SiC_(2)复合涂层的微观结构进行表征,并分析了304不锈钢基体与Co-2%Ti_(3)SiC_(2)复合涂层在等温摩擦实验(25和600℃)中不同载荷(2、5和8 N)下的摩擦学性能和磨损机理。结果表明:Co-2%Ti_(3)SiC_(2)复合涂层主要由γ-Co固溶体,硬质相Fe_(2)C、Cr_(7)C_(3)和TiC及润滑相Ti_(3)SiC_(2)组成。Co-2%Ti_(3)SiC_(2)复合涂层的平均显微硬度为358.61 HV0.5,约是304不锈钢基体(239.32 HV0.5)的1.5倍。在等温摩擦实验中,Co-2%Ti_(3)SiC_(2)复合涂层的磨损率均随着载荷的增加而减少,而摩擦系数在室温下随载荷的增加先增大后减小,在高温(600℃)下随载荷的增加而减小。在不同温度及载荷下,Co-2%Ti_(3)SiC_(2)复合涂层的磨损机理略有不同。

Research on the impact of manufacturing servitization on environmental pollution:spatial econometric analysis of sulfur dioxide based on 284 prefecture-level cities

Using China’s regional input–output table,the paper constructs indicators of manufacturing servitization,matches manufacturing servitization at the regional level with city data,and uses spatial econometrics to empirically analyze the impact of manufacturing servitization on urban sulfur dioxide(SO_(2))emissions within the classical Environmental Kuznets Curve(EKC)framework.The results show that manufacturing servitization can reduce SO_(2) emissions.Producer servitization and consumptive services can both significantly reduce industrial SO_(2) emissions.Transportation and warehousing servitization,information servitization,leasing,and commercial servitization,technology research and development servitization significantly reduce SO_(2) emissions;technology research and development servitization,in particular,have the largest influence coefficient,while the reduction effect of servitization in the wholesale and retail and finance sectors is not significant.The study also found that servitization reduced the SO_(2) emissions through technological innovation and industrial structure upgrading.

Recent progress in the applications of presynaptic dopaminergic positron emission tomography imaging in parkinsonism

Nowadays,presynaptic dopaminergic positron emission tomography,which assesses deficiencies in dopamine synthesis,storage,and transport,is widely utilized for early diagnosis and differential diagnosis of parkinsonism.This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism.We conducted a thorough literature search using reputable databases such as PubMed and Web of Science.Selection criteria involved identifying peer-reviewed articles published within the last 5 years,with emphasis on their relevance to clinical applications.The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis.Moreover,when employed in conjunction with other imaging modalities and advanced analytical methods,presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker.This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion.In summary,the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials,ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.

计及动态碳排放因子的多H_(2)-IES双层优化运行方法

在“双碳”目标背景下,能源系统的低碳转型是其未来的发展方向.近年来,高热值、低污染的氢能受到广泛重视.基于碳排放流理论提出一种计及动态碳排放因子的多含氢综合能源系统(H_(2)-IES)双层优化运行模型.在上层模型中,上级能源网基于效益最优原则建立经济调度模型,确定各园区的能源价格与碳排放因子并下发给下层;在下层模型中,基于纳什谈判理论建立了多园区低碳合作运行模型,并采用自适应交替方向乘子法分布式求解,确定各园区的能源需求量并反馈给上层;所提模型在多次迭代互动中实现上下层协同优化.为了实现对多园区合作收益的合理分配,提出一种基于综合议价能力的收益分配方法.算例分析表明,该双层优化方法可实现上下层间的协同运行,同时兼顾多园区运行的低碳性与经济性,通过合理分配合作收益,保证园区参与合作的积极性.

Revisiting the nexus between fiscal decentralization and CO_(2)emissions in South Africa:fresh policy insights

The argument over fiscal decentralization and carbon dioxide emission(CO_(2))reduction has received much attention.However,evidence to back this claim is limited.Economic theory predicts that fiscal decentralization affects environmental quality,but the specifics of this relationship are still up for debate.Some scholars noted that fiscal decentralization might lead to a race to the top,whereas others contended that it would result in a race to the bottom.In light of the current debates in environmental and development economics,this study aims to provide insight into how this relationship may function in South Africa from 1960 to 2020.In contrast to the existing research,the present study uses a novel dynamic autoregressive distributed lag simulation approach to assess the positive and negative changes in fiscal decentralization,scale effect,technique effect,technological innovation,foreign direct investment,energy consumption,industrial growth,and trade openness on CO_(2)emissions.The following are the main findings:(i)Fiscal decentralization had a CO_(2)emission reduction impact in the short and long run,highlighting the presence of the race to the top approach.(ii)Economic growth(as represented by the scale effect)eroded ecological integrity.However,its square(as expressed by technique effect)aided in strengthening ecological protection,validating the environmental Kuznets curve hypothesis.(iii)CO_(2)emissions were driven by energy utilization,trade openness,industrial value-added,and foreign direct investment,whereas technological innovation boosted ecological integrity.Findings suggest that further fiscal decentralization should be undertaken through further devolution of power to local entities,particularly regarding environmental policy issues,to maintain South Africa’s ecological sustainability.South Africa should also establish policies to improve environmental sustainability by strengthening a lower layer of government and clarifying responsibilities at the national and local levels to fulfill the energy-saving functions of fiscal expenditures.

基于二萘并[2,3-B∶2′,3′-D]呋喃基团的高效窄发射蓝光OLED器件

高效率窄光谱蓝色有机电致发光器件(OLED)是柔性显示领域的研究重点之一。本文以二萘并[2,3-B∶2′,3′-D]呋喃为弱电子受体、N-(4-联苯基)-1-萘胺作为电子给体设计合成了一种D-A-D型蓝光分子DPF-NA,其在正己烷溶液中的发射峰位于441 nm。理论计算与光物理测试结果显示DPF-NA具有杂化局域电荷转移激发态(HLCT)特性,兼具局域态(LE)高发光效率与电荷转移态(CT)高激子利用率特征,在二氯甲烷溶液中的光致发光量子效率(PLQY)为81.2%。基于质量分数3%DPF-NA掺杂浓度的OLED器件电致发光(EL)峰位于455 nm,半峰宽(FWHM)仅为26 nm,CIE(x,y)坐标为(0.14,0.08),最大外量子效率(EQEmax)为6.76%。

Accelerating net-zero carbon emissions by electrochemical reduction of carbon dioxide

Electroreduction of CO_(2)shows great potential for global CO_(2)utilization and uptake when collaborated with renewable electricity.Recent advances have been achieved in fundamental understanding and electrocatalyst development for CO_(2)electroreduction.We think this research area has progressed to the stage where significant efforts can focus on translating the obtained knowledge to the development of largescale electrolyzers,which have the potential to accelerate the transition of the current energy system into a sustainable and zero-carbon emission energy structure.In this perspective paper,we first critically evaluate the advancement of vapor-feed devices that use CO_(2)as reactants,from the point of view of industry applications.Then,by carefully comparing their performance to the state-of-the-art water electrolyzers which are well-established technology providing realistic performance targets,we looped back and discussed the remaining challenges including electrode catalysts,reaction conditions,mass transporting,membrane,device durability,operation mode,and so on.Finally,we provide perspectives on the challenges and suggest opportunities for generating fundamental knowledge and achieving technological progress toward the development of practical CO_(2)electrolyzers for the goal of building lowcarbon or/and net carbon-free economies.

Modeling CO_(2)Emission in Residential Sector of Three Countries in Southeast of Asia by Applying Intelligent Techniques

Residential sector is one of the energy-consuming districts of countries that causes CO_(2)emission in large extent.In this regard,this sector must be considered in energy policy making related to the reduction of emission of CO_(2)and other greenhouse gases.In the present work,CO_(2)emission related to the residential sector of three countries,including Indonesia,Thailand,and Vietnam in Southeast Asia,are discussed and modeled by employing Group Method of Data Handling(GMDH)and Multilayer Perceptron(MLP)neural networks as powerful intelligent methods.Prior to modeling,data related to the energy consumption of these countries are represented,discussed,and analyzed.Subsequently,to propose a model,electricity,natural gas,coal,and oil products consumptions are applied as inputs,and CO_(2)emission is considered as the model’s output.The obtained R^(2) values for the generated models based on MLP and GMDH are 0.9987 and 0.9985,respectively.Furthermore,values of the Average Absolute Relative Deviation(AARD)of the regressions using the mentioned techniques are around 4.56%and 5.53%,respectively.These values reveal significant exactness of the models proposed in this article;however,making use of MLP with the optimal architecture would lead to higher accuracy.