Emission Intensity Research Articles

Optical emission spectroscopy of breaking arc plasma between consumable electrodes

The investigation focuses on the optical emission spectroscopy of plasma generated by breaking arc between single-component Cu and composite Cu-W electrodes manufactured using shock sintering technology at temperature of 750°C. The electrodes were subjected to arc currents of 4, 50, and 104 A. Optical emission spectroscopy with high spectral and temporal resolution was employed to investigate the plasma with copper and tungsten vapour admixtures. The temporal evolution of temperature in the plasma was determined by the Boltzmann plot technique based on the emission intensities of Cu I spectral lines. Temporal evolution of electron densities were determined from the full width at half maximum of Cu I 515.3 nm spectral line. These initial plasma parameters integrated over the volume of breaking arc were utilized to calculate the temporal evolution of plasma compositions and contents of metal vapours admixtures in discharge gap.

Uncertainty in determining carbon dioxide removal potential of biochar

Abstract A quantitative and systematic assessment of uncertainty in life-cycle assessment is critical to informing sustainable development of carbon dioxide removal (CDR) technologies. Biochar is the most commonly sold form of CDR to date, and it can be used in applications ranging from concrete to agricultural soil amendments. Previous analyses of biochar rely on modeled or estimated life-cycle data and suggest a cradle-to-gate range of 0.20–1.3 kg CO2 net removal per kg of biomass feedstock, driven by differences in energy consumption, pyrolysis temperature, and feedstock sourcing. Herein, we quantify the distribution of CDR possible for biochar production with a compositional life-cycle inventory model paired with scenario-aware Monte Carlo simulation in a “best practice” (incorporating lower transportation distances, high pyrolysis temperatures, high energy efficiency, recapture of energy for drying and pyrolysis energy requirements, and co-generation of heat and electricity) and “poor practice” (higher transportation distances, lower pyrolysis temperatures, low energy efficiency, natural gas for energy requirements, and no energy recovery) scenarios. In the best-practice scenario, cradle-to-gate CDR (which is representative of the upper limit of removal across the entire life cycle) is highly certain, with a median removal of 1.4 kg of CO2e / kg biomass and results in net removal across the entire distribution. In contrast, the poor-practice scenario results in median net emissions of 0.090 kg CO2e / kg biomass. Whether this scenario emits (66% likelihood) or removes (34% likelihood) carbon dioxide is highly uncertain. The emission intensity of energy inputs to the pyrolysis process and whether the bio-oil co-product is used as a chemical feedstock or combusted are critical factors impacting the net carbon dioxide emissions of biochar production, together responsible for 98% of the difference between the best- and poor-practice scenarios.

Unveiling the dynamic flows and spatial inequalities arising from agricultural methane and nitrous oxide emissions

Tracing the spatial transfer and heterogeneity of agricultural methane (CH4) and nitrous oxide (N2O) emissions in China is a prerequisite for the sustainable transformation of agricultural systems. In this study, we established a research framework for evaluating agricultural CH4 and N2O flows and convergence. Using this framework, we established an inventory of China's agricultural CH4 and N2O emissions calculated according to the IPCC inventory guidelines, built a food trade model to simulate the spatial transfer, and revealed the regional differences. Finally, we analyzed the influence mechanism by combining extended Kaya identity and the logarithmic mean divisia index (LMDI) model. We found that inter-regional transfer of agricultural CH4 and N2O emissions in China have intensified, increasing from 56.14 % of total transfers in 2000 to 67.28 % in 2019. The spatial inequalities of agricultural CH4 and N2O increased, and emission intensity varied more within regions than between regions, with per capita emissions showing a club convergence with “intragroup convergence and intergroup divergence”. Although the contribution of agricultural CH4 and N2O emissions varies across provinces, controlling emissions intensity and land use intensity while maintaining GDP per capita is the key to emission mitigation. Our study provides theoretical support for prioritizing policies to mitigate agricultural CH4 and N2O emissions.

Fabrication of Eu2O3 doped in high density and transparent silicoborate scintillating glass for synchrotron X-ray radiographic imaging application

In this work, the glass system, xEu2O3 - 10SrO - 20La2O3 - 10Ta2O5 - 10SiO2 - (50-x)B2O3, where x = 0, 1, 3, 5, 7, 9, 11 mol%, was fabricated using the high-temperature melt quenching method. The physical, optical, and luminescence properties of the glass were investigated to determine its suitability as a scintillation material. The transparent glass sample showed a high density and molar volume up to 4.72 g/cm3 and 40.57 cm3/mol, respectively, reflecting that higher NBOs in glass matrix. This result is also supported by X-rays photoelectron spectroscopy (XPS) spectra. Absorption spectra represented peaks in the ultraviolet to near infrared regions, which can be confirmed the presenting of Eu3+ ion in glass matrix. Under UV excitation, the glass doped with 3 mol% of Eu2O3 shows highest intensity while scintillation light (X-rays induced luminescence) was highest performed at 7 mol%. The integral intensity of radioluminescence of glass is 26 % that of commercial BGO scintillator. The photoluminescence quantum yield (PLQY) was measured and the highest PLQY was correspond with emission intensity. The glass scintillator was used for X-ray imaging at beamline 1.2, Synchrotron Light Research Institute (SLRI), Thailand and the spatial resolution was evaluated. Due to the strong light emission at 615 nm from 5D0 → 7F2 transition of Eu3+, this developed scintillating glass has a potential for X-ray imaging material in radiographic application.

Optimizing ventilation systems considering operational and embodied emissions with life cycle based method

Efforts to enhance the energy efficiency of Heating, Ventilation, and Air Conditioning (HVAC) systems have been bolstered by technical advancements and stringent regulations. However, HVAC systems not only emit during operation due to energy consumption but also have significant embodied emissions, which recent studies show can exceed those of the operational phase. This study introduces an optimization framework aimed at minimizing lifetime emissions—both operational and embodied—for ventilation systems, an area previously underexplored. The optimization framework incorporates detailed calculations of pressure drop, fan power and newly developed life cycle ventilation inventory data with a life cycle assessment perspectiveA case study of ventilation ductwork in a “BREEAM Excellent” certified energy-efficient building in Norway applies this optimization framework. Findings indicate that for this case, optimizing ductwork dimensions can reduce lifetime emissions of the ventilation system by 15 %, compared to the existing designs with an emission intensity of 0.3 kg CO2/kWh. Further, the study examines how the emission intensity of electricity generation and service lifetime influence total emissions, highlighting the growing importance of embodied emissions as electricity generation becomes cleaner. This underscores the necessity of considering both operational and embodied emissions in design decisions. This study presents an optimization tool for low-emissions ventilation design, capable of processing diverse layouts and aiding in decarbonizing ventilation systems towards achieving zero-emission buildings. Future integration with building information modeling (BIM) and artificial intelligence (AI) could further enhance autonomous low-carbon design and decision-making.

Can Big Data Aggregation Help Businesses Save Energy and Reduce Emissions? Quasi-Natural Experiment in Big Data Comprehensive Test

Aggregating big data pieces is critical for increasing enterprise resource allocation efficiency, reducing energy usage, and lowering carbon emissions intensity. This research aims to investigate the impact of big data aggregation on energy efficiency and carbon emission intensity among Chinese enterprises. To this end, it employs primary financial data from Chinese listed companies from 2009 to 2021 and carbon emissions data disclosed in social responsibility reports, sustainable development reports, and environmental reports. The findings revealed that the aggregation of big data elements dramatically reduces the intensity of carbon emissions in firms in the pilot regions. The decrease effect is more effective in economically developed places and regions with higher degrees of digitization, particularly for organizations in high-energy-consuming industries, and it is more robust for small and non-state-owned businesses. The aggregation of big data elements mainly aids firms in pilot regions in lowering energy consumption and emissions by increasing technical innovation and energy usage efficiency. To create a new national competitive advantage, we should actively promote the gradual expansion of the comprehensive pilot zone for big data, advance the in-depth application of big data in environmental governance, and better capitalize on the dividends of big data aggregation.

Accelerating the penetration of clean electricity to promote the low carbonization of high-speed railways: A probabilistic framework

Transitioning from carbon-intensive travel modes to high-speed railways (HSR) is widely recognized as a crucial pathway to achieving the ‘carbon peak and carbon neutrality’ goals in the transport sector. However, it remains unclear whether HSR can meet carbon peak goals on time, under the high uncertainty of future electricity development. This study integrates scenario analysis and Monte Carlo simulation into life cycle assessment, proposing a probabilistic framework for dynamically simulating the carbon dioxide (CO2) emissions over the entire life cycle of HSR. Monte Carlo simulation-Latin hypercube sampling method is introduced to model the uncertainty in the development of electricity. The results show that with the gradual increase in the proportion of clean electricity, the time when the CO2 emission intensity of HSR is lower than that of electric cars and electric coaches is most probable to occur in the 2nd–3rd years and the 5th–14th years of operation, respectively. The emission trend of HSR is primarily influenced by the passenger growth rate and the depth of transition to clean electricity, with minimal impact from the loading factor and initial passenger volume. When the passenger growth rate reaches 5 % by 2030, transitioning solely to clean electricity can peak CO2 emissions from HSR by 2030. However, with passenger growth rates of 6 %, 7 %, 8 %, and 9 %, the peak time is most probable to be delayed by 6–7 years, 13–14 years, 16 years, and 19 years, respectively. These findings suggest that achieving CO2 emission peak goals in the transport system requires collaborative efforts across multiple sectors, including transport, energy, and industry sectors. The results contribute to a deeper understanding of the pathways for achieving carbon peak in the transport sector.

Investigating the impacts of the Dual Carbon Targets on energy and carbon flows in China

As the world’s largest carbon emitter, China has committed to ambitious “Dual Carbon Targets” to address climate change. To investigate the impact of the Dual Carbon Targets on energy consumption and carbon dioxide (CO2) emissions, CO2 emissions were calculated, and Sankey diagrams of energy and CO2 flows for 2018-2022 were drawn based on the latest energy statistics. This study finds that China’s primary energy supply was 5.429 Gtce, with terminal energy consumption at 3.801 Gtce in 2022. CO2 emissions reached 12.01 Gt, marking a 12.24% increase since 2018. Emission intensity varies regionally, being higher in the north and lower in the south, with a national average of 0.1 kg/CNY. Coal continues to dominate energy consumption at 64%, though its share of emissions is declining, particularly in transportation and residential sectors. By 2060, electricity is expected to become the primary energy source, significantly lowering carbon emissions, with Carbon Capture, Utilization, and Storage technologies playing a crucial role in achieving the targets. This analysis provides critical insights into China’s transition to a low-carbon economy, serving as a valuable resource for policymakers to optimize the energy structure and meet environmental goals.

Energy efficiency and economic performance of a low-temperature heating system combining double-layer pipe-embedded wall and ground source heat pump

Reducing heating energy consumption in buildings is a crucial step towards a low-carbon future. The energy efficiency of heat pump heating systems can be improved by reducing the water supply temperature of terminals. However, existing terminals are limited in using lower-temperature hot water and leaves potential for energy savings. Therefore, this study proposes a double-layer pipe-embedded wall heating system coupled to a ground source heat pump. The outer pipes use shallow geothermal energy to reduce envelope load, whereas the inner pipes use water produced by the heat pump to provide heating. Energy, economic, and carbon emission analysis models of the proposed system are developed. A residential heating case study is conducted in Harbin, Shenyang, Beijing, Zhengzhou, and Shanghai to investigate the performance of the proposed system. The results show that the proposed system achieves much lower-temperature heating than the reference floor heating system. The seasonal energy savings of the proposed system in the selected cities are 12%–18%, with a SCOP of 4.0–5.8. The dynamic payback period of the proposed system is 1.6–4.3 years and the CO2 emission intensity is reduced by 1.2–3.2 kg/m2. This study provides an insight into the application of DPEW heating systems.

Climate Risks and Economic Consequences of Rising Global CO2 Emissions in Aviation, Shipping, and Heavy-Duty Transport

This study examines methods to lessen the environmental consequences of global CO2 emissions from the hard-to-abate transport sector. The paper analyzed historical and projected trends in global CO2 emissions from the hard-to-abate transport industry under two scenarios: the stated policy scenario (STEPS) and the announced pledged scenario (APS). The study covered the historical period from 2010 to 2022 and projected emissions up to 2050. The analysis revealed that the compound annual growth rate (CAAGR) of STEP exceeded that of APS in 2030 and 2050 for challenging emissions from heavy- duty vehicles, aircraft, and shipping when compared to the baseline year of 2022. The aviation industry has a higher CAAGR of 5.3% and 2.5% for 2030 and 2050, respectively, compared to heavy-duty vehicles at 1.6% and 0.9% for 2030 and 2050, respectively, and shipping at 0.7% and 0.9% for 2030 and 2050, respectively, under STEPS. Under the APS scenario, shipping showed a negative CAAGR of -0.8% and -2.8% for 2030 and 2050, respectively, and 0.4% and -1.8% for 2030 and 2050, respectively, for heavy-duty trucks. In comparison, the aviation industry had CAAGRs of 4.5% and 0.8% for 2030 and 2050, respectively. The data shows that the aviation industry is expected to see a far greater CAAGR in emissions than heavy-duty vehicles and shipping in both STEPS and APS scenarios. Targeted efforts are necessary to mitigate the environmental effects of air travel in the upcoming decades. The paper also examined 56 publicly traded international transportation companies and their corresponding carbon emission targets. Only seven companies, or 12.5%, have established goals for reducing emissions from 2023 to 2050; 10 companies, accounting for 17.9%, have committed to achieving carbon neutrality by 2040 to 2060; five corporations, representing 8.9%, have set targets for reducing emission intensity from 2025 to 2034; and 34 global corporations, making up 60.7%, have committed to achieving net zero emissions between 2040 and 2050. Despite some progress in setting emission reduction targets in the air travel industry, many companies still need to set carbon footprint reduction goals.

Assessing and Predicting Spatiotemporal Alterations in Land-Use Carbon Emission and Its Implications to Carbon-Neutrality Target: A Case Study of Beijing-Tianjin-Hebei Region

Optimizing land use and management are pivotal for mitigating land use-related carbon emissions. Current studies are less focused on the influence of development policies and spatial planning on carbon emissions from land use. This research employs the future land use simulation (FLUS) model to project land-use alterations under the business-as-usual (BAU) and low-carbon ecological security (LCES) scenarios. It assesses and predicts spatiotemporal characteristics of land-use carbon emissions in the Beijing-Tianjin-Hebei (BTH) region across urban agglomerations, cities, counties, and grids from 2000 to 2030. The influence of low-carbon policy is assessed by comparing the land-use carbon emissions between scenarios. The findings demonstrate that: (1) Urban agglomeration-wise, Beijing’s land-use carbon emissions and intensities peaked and declined, while Tianjin and Hebei’s continued to rise. (2) City-wise, central urban areas generally have higher carbon emissions intensities than non-central areas. (3) County-wise, in 2030, high carbon-intensity counties cluster near development axes. Still, the BAU scenario has a larger carbon emission intensity and a greater range of higher intensities. (4) Grid-wise, in 2030, the BAU scenario shows a clear substitution of heavy carbon emission zones for medium ones, and the LCES scenario shows a clear substitution of carbon sequestration zones for light carbon emission zones. Our methodology and findings can optimize spatial planning and carbon reduction policies in the BTH urban agglomeration and similar contexts.

A fine-scale atlas reveals the systematic imbalance between carbon emissions and economic benefits along value chain within China

In efforts to achieve the aspiring carbon mitigation goals, China is actively seeking to reconcile the economic development and carbon reduction with diverse regional conditions. Here, we firstly integrated a national-wide atlas on the labor division of production, and decomposed value added and carbon emission along China's domestic value chain during 2007–2017. We found that the value chain roles lead to a systematic imbalance between value added and carbon emissions across regions. Over 70 % of sufferers of the inequality were located at the north, most of which were in the upstream position to supply resource and energy intermediate products of higher on-site emissions and relatively less value added in comparison to the downstream manufacturing and service products production at the coastal regions. As a result, the northern inland suffered a great deal while part of coastal regions and southern inland were beneficiaries in the participation in domestic value chain. In particular, several regions inevitably undertake industries with higher emission intensity and less gains in a sound domestic industrial chain. These strongly call for a systematically policy- or price-based mechanism to explore fair strategy for emission reduction.

Design of fluorescent sensors for the detection of human serum albumin structure employing nitrogen-by modulation of molecular containing heterocycles

Serum albumin is the most abundant protein in mammalian plasma. It occupies an extremely important position in organisms as an early indicator of the development of many diseases. The development of fluorescence sensing technology has revolutionized the drawbacks of traditional methods. In this strategy, we designed and synthesized three dual fluorophore organic sensors TPA-IPA-T1, TPA-QL-T2, and TPA-Py-T3 for the detection of serum albumin. The rotation of the C–C bond of sensors is restricted and the molecular structure forms a rigid plane that contributes to the fluorescent emission intensity of the sensor. The fluorescent skeletons were successfully constructed by triphenylamine composed the electron-withdrawing nitrogen-containing compounds benzopyrrole (indole), benzopyridine (quinoline), and pyridine, respectively, with piperazine as a rigid connecting bridge. The addition of human serum albumin (HSA) turned on the fluorescent emission of the sensor near 580–600 nm. The color of the sensor solution changed from colorless to pink and bright orange, respectively. The fluorescent intensity increased by 24, 67, and 31 fold, respectively. The sensors have the advantages of sensitivity and fast response, strong anti-interference ability, low detection limit and good water solubility. Drug experiments in artificial urine demonstrate the characteristics of sensors, which has a very high potential for biological feasibility and medical applications. The sensors facilitaty the binding of the HSA through electrostatic interactions. The sensors were explored to be able to efficiently bind the IB structural domain of HSA, which had a good meaningful of avoiding the interference of commonly drugs in clinical medicine and in artificial urine on the detection of HSA.

Innovative biogas energy system: Enhancing efficiency and sustainability through multigeneration integration

This research suggests using landfill gas, derived from landfilling operations, as a feasible alternative to fossil fuels. This study introduces a novel and all-encompassing method for utilizing landfill biogas. The proposed system utilizes a supercritical Brayton cycle with carbon dioxide as the working fluid, a transcritical CO2 cycle, two ammonia Rankine cycles, a single-effect desalination cycle, a proton exchange membrane electrolyzer, and an improved Kalina cycle. The system underwent evaluation using Aspen HYSYS software, enabling assessments in terms of energy, exergy, thermo-economic, and environmental variables. The examination of the findings indicates that the suggested solution has much higher energy efficiency compared to similar studies. The assessments determined the energy efficiency of the process in power generation, combined heat and power, combined cooling, heat and power, and multigeneration modes to be 23.62 %, 80.89%, 81.19%, and 82.72%, respectively. Furthermore, environmental research has revealed that the new process emits a total of 1743 kg/h of carbon dioxide and has an emission rate of 0.23 kg/kWh. The exergy analysis indicated that the fuel burner exhibited the greatest degree of irreversibility, accounting for 40%. Furthermore, a sensitivity analysis was performed on crucial parameters, including the temperature of the heat source in the single-effect desalination section and the rate at which water flows into the electrolyzer. The objective was to evaluate the influence of changes in these parameters on energy efficiency, exergy efficiency, carbon dioxide emission intensity, product production rate, and levelized energy cost. The economic analysis determined that the proposed scheme would have a total annual cost of 8,667,124 $ with a levelized energy cost of 0.17 $/kWh.

Photoluminescence properties of Li3Sc1-x(BO3)2:xCr3+ phosphors and enhanced near-infrared emission and thermal stability by Yb3+ codoping

Cr3+ activated broadband near-infrared (NIR) emitting phosphors have attracted more attention worldwide as they are strongly expected to be promising light convertors for phosphor-converted NIR light sources for NIR spectroscopy and imaging technologies. Herein, a new broadband NIR emitting phosphor Cr3+-doped Li3Sc(BO3)2 (LSBO) is introduced. Microcrystalline powders of LSBO doped with different Cr3+ concentrations were synthesized by solid state reactions and show an NIR emission extending from 700 to 1100 nm with a peak at 830 nm upon excitation at 460 nm. The structure, concentration and temperature-dependent luminescence properties of LSBO:Cr3+ phosphors were discussed in detail. The optical properties of Cr3+ ions in LSBO were examined in terms of spectroscopic parameters. Moreover, efficient energy transfer from Cr3+ to Yb3+ is leveraged to significantly improve the NIR emission intensity and the thermal stability. The enhancement and energy transfer mechanisms have been discussed in detail. These results open up new ways to realize efficient NIR-emitting materials.

Red-emitting phosphors NaLiXF6:Mn4+ (X = Ti, Si) for white LEDs with high color rendering index and low correlated color temperature

White light-emitting diodes (WLEDs) are widely used in various lighting applications due to their high brightness and energy efficiency. However, commercial WLEDs, which typically combine YAG:Ce3+ phosphors with blue light-emitting diode chips, often lack red components, resulting in a high correlated color temperature (CCT) and a low color rendering index (CRI). To address this issue, two novel Mn4+-doped red-emitting phosphors, NaLiTiF6 and NaLiSiF6, were synthesized using an ion exchange method. Both phosphors exhibit strong red light with a pronounced zero-phonon line (ZPL) emission under blue light excitation. Optimal photoluminescence emission intensities were observed at Mn4+ concentrations of 6% for NaLiTiF6 and 9% for NaLiSiF6. When the temperature increased from 303 K to 413 K, both phosphors demonstrated outstanding brightness and chromatic stability. Integrated into phosphor-converted light-emitting diodes (pc-LEDs), the device incorporating NaLiTiF6:6%Mn4+ achieved a CRI of 95.1 and a CCT of 3172 K, while the device with NaLiSiF6:9%Mn4+ showed a CRI of 87.9 and a CCT of 3784 K. In addition, the luminous efficacy, CRI, and CCT of both prototype pc-LEDs maintained minimal variation with increasing driving current. These results indicate the stability and suitability of the synthesized phosphors for enhancing the performance of warm WLEDs applications.

Exploring the rhodanine universe: Design and synthesis of fluorescent rhodanine-based derivatives as anti-fibrillar and anti-oligomer agents against α-synuclein and 2N4R tau

Tau and α-synuclein (α-syn) are prone-to-aggregate proteins that coprecipitate in the brains of Alzheimer’s disease (AD) and Parkinson’s disease (PD) patients. The early-stage oligomers and protofibrils of tau are believed to be strongly linked to human cognitive impairment while the toxic α-syn oligomers are associated with behavioral motor deficits. Therefore, concurrent targeting of both proteinaceous aggregates and their lower dense oligomers are very challenging. Herein, rhodanine-based compounds were designed and synthesized to tackle the fibrils and oligomers of tau and α-syn proteins. In particular, the indole-containing rhodanines 5l and 5r displayed significantly high anti-aggregation activity towards α-syn fibrils by reduction of the thioflavin-T (ThT) fluorescence to lower than 5 %. Moreover, 5r showed a remarkable decrease in the fluorescence of thioflavin-S (ThS) when incubated with the non-phosphorylated tau 0N4R and 2N4R as well as the hyperphosphorylated tau isoform 1N4R, respectively. Transmission electron microscopy (TEM) analyses validated the powerful anti-fibrillar activity of 5l and 5r towards both protein aggregates. In addition, both 5l and 5r highly suppressed 0N4R tau and α-syn oligomer formation using the photo-induced cross-linking of unmodified Protein (PICUP) assay. The fluorescence emission intensity of 5l was quenched to almost half in the presence of both protein fibrils at 510 nm. 5r showed a similar fluorescence response upon binding to 2N4R fibrils while no quenching effect was observed with α-syn aggregates. Ex vivo disaggregation assay using extracted human Aβ plaques was employed to confirm the ability of 5l and 5r to disaggregate the dense fibrils. Both inhibitors showed no promising activity towards the cell-based α-syn inclusion formation. However, another indolyl derivative 5j prevented the α-syn inclusion at 5 µM. Collectively, the indolyl-rhodanine scaffold could act as a building block for further structural optimization to obtain dual targeting disease-modifying candidates for AD and PD.

Deciphering flows: Spatial correlation characteristics and factors influencing carbon emission intensity in the Yangtze River Delta

Deciphering flows: Spatial correlation characteristics and factors influencing carbon emission intensity in the Yangtze River Delta

Carbon emission reduction potential of land use in typical alpine meadow region in China

Alpine meadows are primarily situated in mountainous areas and plateaus, exhibiting a high sensitivity to both climate fluctuations and human activities. However, understanding the factors influencing land use carbon emissions change in these regions remains complex, with uncertain mechanisms. Thus, it is imperative to accurately grasp the factors affecting carbon emissions in alpine meadows. We conducted a study estimating land use carbon emissions in the Upper Yellow River in Gannan from 1990 to 2020, using the Logarithmic Mean Divisia Index decomposition model and the Tapio decoupling model to identify driving factors of land use carbon emissions. Additionally, we analyzed the correlation between these factors and economic growth. The findings showed that the land use efficiency in the Upper Yellow River in Gannan region improved substantially by 436 %. Particularly, construction land emerged as the primary source of carbon emissions. The land use carbon emission increased with the increase of carbon emission intensity of construction land and the expansion of the size of construction land. Moreover, economic development and land use carbon emissions are weak decoupled. These results suggest that economic development is considered the primary driving force behind the increase in land use carbon emissions in the region. To achieve the decoupling of economic development and land use carbon emissions, we propose to improve land use efficiency by adjusting the industrial structure as well as improving land use efficiency.

Spectroscopic Analysis of Tryptophan as a Potential Optical Biomarker for Estimating the Time of Death

The estimation of the time of death represents a highly complex and challenging task within the field of forensic medicine and science. It is essential to approach this matter with the utmost respect for human rights while acknowledging the inherent limitations of the current methods, which require continuous refinement and expansion. Forensic science recognizes the necessity to improve existing techniques and develop new, more accurate, and non-invasive procedures, such as physicochemical approaches, to enhance the precision and reliability of time of death determinations. This article proposes a novel, non-invasive method for estimating the time of death using a spectroscopic analysis of tryptophan. The initial phase of the study concerns the presentation of the spectroscopic properties of tryptophan at varying pH levels, with consideration given to the pH fluctuations that occur during the decomposition of cadavers. The findings confirm the stability of the spectroscopic properties at different environmental pH levels. Subsequently, preliminary trials were conducted on 15 healthy human volunteers, which demonstrated that tryptophan concentrations in fingerprint samples were within the detection limits using molecular spectroscopy techniques. The final objective was to ascertain whether the composition of the substance present on the skin surface of a deceased individual up to 48 h postmortem is comparable to that of the sweat–fatty substance in living individuals. This was confirmed by the absorption and emission spectral profiles, which showed overlapping patterns with those obtained from living volunteers. The most significant outcome at this stage was the demonstration of a considerable increase in emission intensity in the spectra for samples obtained approximately 48 h after death in comparison to that obtained from a sample taken approximately 24 h after death. This indicates a rise in the concentration of tryptophan on the skin surface as the postmortem interval (PMI) increases, which could serve as a basis for developing a tool to estimate the time of death.