Absolute Carbon Research Articles

Surface matters: Decarburising wootz crucible steel ingots

Wootz, the Indian crucible steel, is a hypereutectoid iron–carbon alloy and famous for its outstanding qualities. Due to the paucity of archaeological and historical ingot finds and conservative sampling strategies, discussions of the homogeneity of such ingots and the microstructural representativeness of samples have remained generic and assumptive. Thus two major shortcomings in the study of crucible steel ingots include the determination of their absolute carbon content and its relative distribution across the ingots. The recent discovery of a large hoard of wootz ingots from Telangana (Jaikishan et al. 2021) offered a unique opportunity to study their microstructure and determine their carbon content.Reports based on traditional metallography suggest a wide carbon range, from 1 to 2 wt% carbon, for similar ingots (Scott 2013). Recent work based on image analysis (Desai and Rehren 2023) offered narrower carbon estimates (about 1.8 wt%) for several of the recently discovered ingots, with some variation in concentration towards the edge of the samples. As a collaborative effort to determine absolute carbon values and potential uneven distribution of the carbon in the Telangana ingots, traditional metallography was coupled with laser-induced breakdown spectroscopy (LIBS). Beyond documenting the microstructure across several ingots, the study provides macrostructural evidence of rim decarburisation, which we believe to be intentional. This study presents the micro- and macrostructure of two of the hypereutectoid Telangana ingots, highlighting the skill of the craftsmen in decarburising the outer surfaces of their ingots, potentially for ease of subsequent forging.

Environmental benefits of ozonated water for sustainable grapevine disease control: A life cycle and carbon sequestration analysis

The oxidative capacity of ozone makes it a highly effective biocide, widely used in the food and processing industry, as well as in drinking water plants. In a context of tighter restrictions on the use of synthetic plant protection products at the regulatory level, wineries are looking for alternative methods to control diseases, making the application of ozonated water an option to consider. To determine the environmental sustainability of this alternative vineyard disease control treatment, an environmental impact assessment was conducted using the Life Cycle Assessment (LCA) methodology. The assessment was carried out in a vineyard located in the D.O. Rías Baixas of Galicia, located in northwestern Spain. The analysis was conducted on the basis of two functional units: i) 1 kg of grapes and ii) 1 ha of land managed and using a cradle-to-gate boundary system. Ten impact categories were assessed using the ReCiPe method, except for the water scarcity indicator, which was quantified using AWARE.The environmental sustainability of the vineyard was further analyzed by measuring its carbon sequestration potential to obtain a more complete environmental profile. The RothC-26.3 model was chosen to estimate absolute carbon sequestration and annual sequestration rate from 2020 to 2040. Since the ozone-only scenarios lost all harvest, no environmental assessment was performed for such scenarios. For the remaining scenarios, the findings suggest that those using a combination of ozonated water and fungicides have the worst environmental performance due to notable reductions in grape yield and more frequent disease control interventions, particularly in certain scenarios. When evaluating environmental performance per hectare of land managed, the scenario using ozonated water with a limited number of disease control interventions exhibited the most favorable environmental profile, primarily due to reduced use of fungicides and disease control passes. In addition, the main contributors to the vineyard environmental profile identified were diesel fuel combustion during field operations, fertilizer use and production, and irrigation. In addition, the research indicates that the vineyard sequesters carbon annually, but this alone is insufficient to offset its greenhouse gas emissions. However, it is estimated that through the application of more appropriate soil management practices, the vineyard could achieve carbon neutrality and potentially increase soil carbon stocks over time.

Carbon allocation dynamics of Spartina alterniflora in Georgia saltmarsh, USA

We developed a phenology-based growth model(PG model) for Spartina alterniflora that incorporates the effects of light, temperature, and salinity on plant production. The PG model is the first to quantify carbon translocation between both above- and below-ground biomass across three phenological periods: growth, senescence, and dormancy periods. This model, fitted to field data from short, medium, and tall S. alterniflora types, estimates physiological parameters such as mass-specific rates of carbon translocation. Once parameterized, the model is applied in forward mode to predict whole-plant production, growth, respiration, mortality, and translocation. Model results reveals that short forms allocate 82 % of photosynthate to below-ground biomass during the growing season, compared to tall (52 %) and medium (22 %) types. However, tall forms, with extensive above-ground biomass, show the highest absolute carbon translocation to below-ground tissues during growth(ave. 3940 g dry weight m−2) and senescence(ave. 265 g dry weight m−2) period. An average mortality rate of 52 % of net production in the tall form below-ground biomass throughout the year indicates a substantial contribution to organic carbon sequestration within the habitat sediment. Model results also reveal that the carbon translocation from below- to above-ground tissues may not be required for survival during winter in milder climate like Sapelo Island, Georgia.

New perspective, more rational decoupling: A case study of China

Scholars usually unconsciously employ the Tapio decoupling model with a static perspective and results-oriented philosophy, which often leads to errors. Therefore, we propose an improved Tapio decoupling model that adopts a dynamic perspective and process-oriented philosophy. Taking China, the world's largest carbon emitter, as a case study, we investigate the decoupling of its provincial industrial carbon emissions (ICE) from industrial value-added (IVA) during 2005–2020 using both the conventional and improved decoupling model, followed by a comparative analysis of their results. Our findings are as follows: (1) Both China's ICE and IVA exhibited a general upward trend during the study period, with non-linear annual ICE and IVA variations observed across all provinces. (2) Overall, China's provincial IVA increasingly decoupled from ICE, with some provinces achieving a strong decoupling state during 2015–2020; however, from the long-term perspective spanning the entire study period, most provinces remained in a weak decoupling state. (3) The conventional decoupling model tends to yield overly optimistic results in empirical study of China, with the decoupling indices during the periods of 2005–2010 and 2005–2020 determined by the conventional model even had significant statistical difference between those determined by the improved model. (4) To ensure equity, differentiated carbon reduction policies should be tailored to each province, considering factors such as absolute carbon emissions, short-term decoupling states, and long-term decoupling states. The improved Tapio decoupling model is proposed as a valuable framework for researchers engaged in related studies.

Switch to pollution control bonds, else carbon risk will switch us: Evidence from the U.S. electric utility firms

This study explores the implications and effectiveness of pollution control bonds (PCBs) in reducing carbon risk, focusing on a sample of 242 U S. electric utility firms from 2012 to 2022. The research investigates the association of PCB issuances with (i) absolute (unscaled) carbon emissions levels and their three scopes; and (ii) carbon emissions intensity and its three scopes. Using quantile regressions covering the 5th, 25th, 50th, 75th, and 90th quantiles, along with the Propensity Score Matching (PSM) methodology (where the treatment group includes firms using PCBs and the control group comprises firms that do not opt for PCBs), the findings show a significant reduction in carbon emissions due to PCB issuance. Substantial differences were observed between the treatment group and the control group across various quantiles of carbon emissions, particularly for companies with medium to high carbon footprints, both in terms of overall CO2 emissions and scope 2 CO2 emissions. Moreover, disparities between the two groups were notable across all quantiles of scope 1 CO2 emissions. Additionally, among the companies using PCBs, those with lower risk profiles exhibited a smaller carbon footprint, measured by scope 3 CO2 emissions, in comparison to their counterparts. Furthermore, the study highlights a more pronounced impact of PCBs issuance during the second phase of the Kyoto Protocol and the commitment period of the Paris Agreement. The results remain robust when alternative measures of carbon risk are applied. These findings carry significant implications for municipal and financing authorities, as well as investors within the U.S. electric utility industry. This research contributes novel insights to the field of electric utility management.

Evaluation and analysis of carbon neutralization capacity in the Yangtze River Economic Belt: Based on time weighted-rough set and unascertained model

The carbon neutralization process continues to be a significant concern in China, particularly in the Yangtze River Economic Belt. This study defines carbon neutrality and presents a regional capacity measurement index system that includes 12 indicators across four dimensions: production reduction, lifestyle reduction, ecological removal, and technological removal. To assess the relative and absolute levels of carbon neutrality capacity in the Yangtze River Economic Belt, the study uses the time-weighted rough set theory and the uncertain measurement model. Additionally, the study also uses Kernel density estimation, Dagum Gini coefficient decomposition, and convergence analysis to examine the development differences in the relative capacity of carbon neutrality in the region. The findings indicate that from 2013 to 2021, the relative capacity of carbon neutrality in the Yangtze River Economic Belt exhibited an upward trend with fluctuations, and there were significant disparities in development between the upper, middle, and lower reaches of the region. However, these differences showed signs of convergence and a general convergence trend. Moreover, the production reduction and lifestyle reduction aspects in the Yangtze River Economic Belt region are currently at a moderate level, while there is still considerable room for improvement in terms of ecological reduction and technological reduction. Furthermore, there are obvious regional differences in the absolute carbon neutral capacity of the Yangtze River Economic Belt region: the upstream region of the Yangtze River Economic Belt is primarily driven by carbon emissions reduction, the middle reaches are driven by production reduction and the downstream region is driven by carbon removal. Consequently, it is crucial to consider the regional development characteristics of the Yangtze River Economic Belt and implement targeted strategies tailored to local conditions.

THE PERFORMANCE OF KUALA LUMPUR’S CARBON EMISSIONS IN THE CONTEXT OF URBAN PLANNING

Cities are responsible for 70% of greenhouse gas (GHG) emissions on a global scale, and cities play an important role in reducing GHG emissions. It is essential for Kuala Lumpur to consider reducing the city's GHG emissions. The city's GHG emission inventory can track and monitor the effectiveness of the climate action plans that has been implemented. The aim of this study is to identify the performance level of GHG emissions in Kuala Lumpur between 2010 and 2019. It is also to identify the performance of Kuala Lumpur's GHG emissions in 2019 in comparison to the global and Malaysian level. Data is calculated using the Global Protocol for Community-Scale Greenhouse Gas Emissions Inventory (GPC), which is recognised and utilised globally. Secondary data for the years 2010 and 2019 was analysed as well as the performance of the Kuala Lumpur GHG emission profile in 2019. With three (3) identified sources of emissions, Kuala Lumpur managed to reduce its GHG emission intensity from 2010 by 74.07% in 2019. The city's GHG emission was recorded at 15,675 ktCO2eq in 2019. The stationary energy sector contributes higher GHG emission than other sector, with 12,043 ktCO2eq (76.83%), followed by the transportation sector with 3,180 ktCO2eq (20.29%) and the waste sector with 452 ktCO2eq (2.88%). As of 2019, Kuala Lumpur's absolute carbon contribution to the global average is 0.03%, whereas Malaysia's absolute carbon contribution is 4.74%. Additionally, the city contributes just 0.07 kgCO2eq/RM (30.17%) to Malaysia's total GHG emission intensity.

Four-quadrant modelling of carbon inequality in international trade and accounting for carbon compensation

In global trade, there is a phenomenon that the “economic gains” and “ecological damages” of some countries and regions are not consistent. Using the multi-regional input-output model (MRIO), this study measures the transfer of embodied carbon and value-added in trade among 16 countries or regions, including the European Union, the United States and other countries from 1995 to 2022. On this basis, we use the four-quadrant analysis method to classify the carbon inequality in international trade, and construct the carbon inequality index to quantify the carbon inequality situation in bilateral trade. The results indicate that carbon inequality between international trade can be divided into three categories: victims of absolute carbon inequality, relative carbon equality and beneficiaries of absolute carbon inequality. Carbon inequality in bilateral trade exists between developed and developing countries, as well as between developing countries. Finally, a carbon compensation accounting model is constructed to measure the monetary value of cross-regional carbon offset, which provides data support for international carbon emission reduction cooperation. Our study contributes to contemplating the impacts of international trade and provide recommendations for global equity and sustainable development.

Ritual schedule and worshippers’ origin at an ancient Maya ritual cave site, Las Cuevas, Belize: a pilot study of jute snail shell sclerochemistry

Sequential stable carbon and oxygen isotope data were measured on 15 jute snail shells (Pachychilus sp.) excavated from the Cave at Las Cuevas, a ritual cave site in western Belize. The shells were found intact in the undisturbed, excavated ritual activity area, suggesting they were left as offerings, not as food waste. The offering of jute snails is thought to be associated with ancient Maya concern for rainfall needed for agriculture, thus the interpretation of the isotope data focused on assessing if the shells were offered in rainy or dry periods. Seven of the shell profiles did not contain oscillations in isotope profiles, and so could not be interpreted for wet or dry season of capture. The remaining shells’ isotope profiles indicate some were captured in rainy, dry, and intermediate conditions. Significant variation in the ranges in absolute carbon and oxygen isotope values suggest they were collected from two or more locations, therefore at least some of the snails were brought in from a distance rather than collected locally prior to offering. More detailed conclusions cannot be confidently made without additional method validation studies, but this project supports the potential utility of jute shell sclerochronology in Maya archaeology.

Carbon leakage or carbon reduction? Carbon emission effect of the production relocation of metal smelting industry in China

AbstractThe metal smelting industry (MSI) is one of the major carbon emission sectors in China, and it is of great significance to clarify the mechanism and truth of the carbon effect of production relocation (PR) of MSI for reducing national carbon emissions. Based on this thinking and previous studies, we proposed two concepts of relative carbon emission effect (RCE) and absolute carbon emission effect (ACE) of PR, then developed models to explore the impact of PR of MSI (PRM) on national carbon emission between 30 provincial administrative units in China from 2007 to 2017. The study demonstrates that the PRM and its ACE and RCE is divergent across provinces and regions. Overall, the PRM is beneficial to national carbon reduction under both relative and absolute scenarios. Specifically, the transfer‐in PRM of most provinces in central regions is beneficial to national carbon reduction, while the transfer‐out PRM of many provinces in coastal areas has worst carbon leakage effect.

China’s climate governance for carbon neutrality: regulatory gaps and the ways forward

The realisation of global carbon neutrality is crucial for combating climate change. As the largest emitter, China declared to achieve carbon neutrality by 2060. However, substantial changes in the energy structure are far from being achieved. Using time series data from 2001 to 2019 and the ARDL-ECM method, this paper explored the effectiveness of climate policies in controlling China’s carbon emissions. The results show that economic and technical factors such as economic growth and energy structure are the determinants of carbon emissions. A green paradox is shown since increasing climate policy density does not significantly reduce carbon emissions. The main regulatory gaps in China’s climate governance include weaknesses in the rule of law, lack of accountability, and insufficient arrangements for equitable energy transitions. A binding legal system is necessary to realise absolute reduction and secure carbon neutrality, especially one including specific climate change legislation, binding reduction targets, and combining energy justice with regulatory efficiency.

Macroeconomic policy at the end of the age of abundance

Progressive policy proposals influenced by post-Keynesian economics emphasise the use of fiscal policy and income redistribution to maintain aggregate demand at levels which achieve full employment. Given persistent evidence of weak demand, excess capacity and unemployment in rich economies since around 1980, expansion of demand would have been appropriate over much of this period. Tighter supply constraints – both short-run constraints due to disruption caused by climate change and geopolitical tensions, and longer-run constraints due to absolute carbon budgets – impose additional challenges in designing policy. In order to increase investment sufficiently to achieve net zero goals, constraints on consumption may be required. Such constraints would weaken the multiplier mechanisms emphasised by post-Keynesian analysis, implying lower growth and higher public debt stocks. Traditional progressive policy proposals will need updating to reflect these constraints. New institutional arrangements will be required to implement updated policy packages.

Green corporate image: Assessing the effects of climate change management practices on corporate reputation

AbstractThe overarching aim of this study is to determine how distinct climate change management practices (CMPs), ranging from the establishment of carbon targets to the adoption of renewable energy and carbon assurance, resonate in the realm of corporate reputation (CR). The study sample comprises US S&P 500 companies (2016–2018). Reputation insights are obtained from the Global RepTrak® Pulse of the Reputation Institute, and data on the adoption of various CMPs are extracted from Carbon Disclosure Project reports. Logistic regression analysis shows that the findings underscore the pivotal role of absolute carbon and renewable energy use targets in enhancing CR. However, the effects of CMPs on CR vary with carbon trading regulations and intensive sector affiliation. The main findings hold after the Heckman selection model is used as an endogeneity technique. This research offers valuable insights to corporations that seek to strategically manage their reputation amidst the challenges of climate change.

Energy management and sizing of a stand-alone hybrid renewable energy system for community electricity, fresh water, and cooking gas demands of a remote island

Research into the off-grid hybrid energy system to provide reliable electricity to a remote community has extensively been done. However, simultaneous meeting electric, freshwater, and gas demands from the off-grid hybrid energy sources are very scarce in literature. Power- to-X (PtX) is gaining attention in recent days in the energy transition scenarios to generate green hydrogen, the primary product of the process as an energy carrier, which is deemed to replace conventional fuels to reach absolute carbon neutrality. In this study, renewable–based hybrid energy is developed to simultaneously meet the electricity, freshwater, and gas (cooking gas via methanation process) demands for a remote Island in Bangladesh. In this process, an energy management strategy has been developed to use the excess energy to generate both freshwater and the hydrogen, where hydrogen is then converted to natural gas via methanation process. The PV, wind turbine, diesel generator, battery, and fuel cell have been optimized using non-dominating sorting algorithm-II (NSGA-II) to offer reliable, cost-effective solutions of electricity, freshwater, and cooking gas for the end users. Results reported that the PV/WT/DG/Batt configuration has been found the most economic configuration with the lowest COE (0.1724 $/kWh) which is 9 % lower than PV/WT/Batt configuration which has the second lowest COE. The cost of water (COW) and cost of gas (COG) of the PV/WT/DG/Batt system are also the lowest among all the four configurations and have been found 1.185 $/m3 and 3.978 $/m3, respectively.

Regulation of temperature distribution in fixed bed reactor for CO2 methanation through “CHESS” monolith structure catalyst

CO2 methanation suffers from the problem of temperature runaway phenomenon due to its exothermic nature. To mitigate this issue, optimizing catalyst structure becomes crucial. This work established numerical models to investigate the CO2 methanation reaction and heat/mass transfer process in the reactor with porous pellet and monolithic catalysts. Results show that the reactor with porous pellets has the lowest carbon conversion per unit pressure drop due to its large total pressure drop. In contrast, the reactor with monolith exhibits a much larger carbon conversion per unit pressure drop but a smaller absolute carbon conversion. Based on this, an improved “CHESS” monolith structure was proposed and improved, which not only maintains a high absolute carbon conversion (62.6 %) but also enhances the heat transfer process in CO2 methanation. Moreover, compared with the reactor with porous pellets, the maximum temperature in the improved “CHESS” monolith was decreased by around 11.09 %.

Are environmental, social and governance (ESG) ratings reliable indicators of emissions outcomes? A case study of the airline industry

AbstractWe analyse environmental ratings and emissions scores for commercial airlines from several major environmental, social and governance ratings providers. Specifically, we investigate whether emissions scores capture and predict absolute carbon emissions and emissions intensity levels, and whether scores are consistent across providers. This builds on existing literature by evaluating the predictive ability of ratings over significantly longer periods than past studies, examining within‐industry ratings disagreement for carbon emissions scores, and using an industry‐specific emissions intensity metric. Data covers 57 airlines from 2012 to 2021. Cross‐sectional and panel regressions are estimated to investigate whether ratings capture and predict carbon emissions data. We find no evidence that emissions scores capture or predict reported carbon emissions, and find that scores from different providers diverge substantially. Persistent shortcomings may undermine trust in the ratings industry, create trade‐offs between emissions abatement and ratings improvement, and hinder the incorporation of climate‐related information in capital allocation decisions.

Carbon footprint and sustainability assessment of wood utilisation in Hungary

Forest management allows the sustained removal of significant amounts of carbon from the atmosphere. Within different activities in the forest, wood utilisation has the most significant man-made environmental impact which affects the carbon balance, which is important to know, to be able to accurately identify its role in climate change. This study aims to determine the carbon footprint of logging during utilisation based on scenario analysis in national default and theoretical assortment structures (11 additional scenarios for each forest stand) within the entire life cycle of raw wood products. Based on a common functional unit (100 m3 of cut wood), a comparative environmental life cycle analysis (LCA) for intermediate and final cutting was performed in shortwood forestry work systems in beech (Fagus spp.), oak (Quercus spp.), spruce (Picea spp.), black locust (Robinia pseudoacacia), and hybrid poplar (Populus x euramericana) stands in Hungary. After obtaining the results, the present study calculated the carbon footprint order for the utilisation life cycle phases and the entire tree utilisation life cycle. The distribution of absolute carbon footprint (ACF: considered emitted CO2 from fossil and biotic origins together) by final cutting exhibited the following order: hybrid poplar (6%)—spruce (8%)—beech (26%)—oak (27%)—black locust (33%). The ACF ranking for the whole technological life cycle (intermediate and final cutting, 400 m3 of cut wood) was hybrid poplar– spruce—oak—beech–black locust. The carbon footprint rankings of the studied stands were expanded to the national level.

The evaluation of government subsidy policies on carbon emissions in the port collection and distribution network: a case study of Guangzhou Port

The collection and distribution network of ports is the main cause of carbon emissions. The carbon peak is a basic policy in China, and the subsidy policy is one of the common measures used by the government to incentivize carbon reduction. We analyzed the transportation methods and the flow direction of a port and proposed a carbon emission calculation method based on emission factors. Based on the transportation time and the cost, a generalized transportation utility function was constructed, and the logit model was used to analyze the impacts of subsidy policies on transportation, thus calculating the effects of the subsidies on carbon reduction. We used Guangzhou Port as a case study, and calculated the carbon reduction effects in six different subsidy policy scenarios and concluded that the absolute carbon reduction value was proportional to the subsidy intensity. In addition, we constructed a subsidy carbon reduction efficiency index and found that the Guangzhou Port collection and distribution network had higher subsidy carbon reduction efficiency in low-subsidy scenarios. Finally, a sensitivity analysis was conducted on the subsidy parameters, and scenario 8 was found to have the highest subsidy carbon reduction efficiency. This achievement can provide decision support for the carbon emission strategy of the port collection and distribution network.

Evidence for multiple nucleosynthetic processes from carbon-enhanced metal-poor stars in the Carina dwarf spheroidal galaxy

Context. Carbon-enhanced metal-poor (CEMP) stars ([C/Fe] > 0.7) are known to exist in large numbers at low metallicity in the Milky Way halo and are important tracers of early Galactic chemical evolution. However, very few stars of this kind have been identified in the classical dwarf spheroidal (dSph) galaxies, and detailed abundances, including neutron-capture element abundances, have only been reported for 13 stars. Aims. We aim to derive detailed abundances of six CEMP stars identified in the Carina dSph and compare the abundances to CEMP stars in other dSph galaxies and the Milky Way halo. This is the largest sample of CEMP stars in a dSph galaxy analysed to date. Methods. One-dimensional local thermodynamic equilibrium (LTE) elemental abundances are derived via equivalent width and spectral synthesis using high-resolution spectra of the six stars obtained with the MIKE spectrograph at Las Campanas Observatory. Results. We derived abundances or upper limits for up to 27 elements from C to Os in the six stars. Our analysis reveals one of the stars to be a CEMP-no star with very low neutron-capture element abundances. In contrast, the other five stars all show enhancements in neutron-capture elements in addition to their carbon enhancement, classifying them as CEMP-s and -r/s stars. The six stars have similar α and iron-peak element abundances to other stars in Carina, except for the CEMP-no star, which shows enhancement in Na, Mg, and Si. We explored the absolute carbon abundances (A(C)) of CEMP stars in dSph galaxies and find similar behaviour to that seen for Milky Way halo CEMP stars, but highlight that CEMP-r/s stars primarily have very high A(C) values. We also compared the neutron-capture element abundances of the CEMP-r/s stars in our sample to recent i-process yields, which provide a good match to the derived abundances.

Ocean color algorithm for the retrieval of the particle size distribution and carbon-based phytoplankton size classes using a two-component coated-sphere backscattering model

Abstract. The particle size distribution (PSD) of suspended particles in near-surface seawater is a key property linking biogeochemical and ecosystem characteristics with optical properties that affect ocean color remote sensing. Phytoplankton size affects their physiological characteristics and ecosystem and biogeochemical roles, e.g., in the biological carbon pump, which has an important role in the global carbon cycle and thus climate. It is thus important to develop capabilities for measurement and predictive understanding of the structure and function of oceanic ecosystems, including the PSD, phytoplankton size classes (PSCs), and phytoplankton functional types (PFTs). Here, we present an ocean color satellite algorithm for the retrieval of the parameters of an assumed power-law PSD. The forward optical model considers two distinct particle populations: phytoplankton and non-algal particles (NAPs). Phytoplankton are modeled as coated spheres following the Equivalent Algal Populations (EAP) framework, and NAPs are modeled as homogeneous spheres. The forward model uses Mie and Aden–Kerker scattering computations, for homogeneous and coated spheres, respectively, to model the total particulate spectral backscattering coefficient as the sum of phytoplankton and NAP backscattering. The PSD retrieval is achieved via spectral angle mapping (SAM), which uses backscattering end-members created by the forward model. The PSD is used to retrieve size-partitioned absolute and fractional phytoplankton carbon concentrations (i.e., carbon-based PSCs), as well as particulate organic carbon (POC), using allometric coefficients. This model formulation also allows the estimation of chlorophyll a concentration via the retrieved PSD, as well as percent of backscattering due to NAPs vs. phytoplankton. The PSD algorithm is operationally applied to the merged Ocean Colour Climate Change Initiative (OC-CCI) v5.0 ocean color data set. Results of an initial validation effort are also presented using PSD, POC, and picophytoplankton carbon in situ measurements. Validation results indicate the need for an empirical tuning for the absolute phytoplankton carbon concentrations; however these results and comparison with other phytoplankton carbon algorithms are ambiguous as to the need for the tuning. The latter finding illustrates the continued need for high-quality, consistent, large global data sets of PSD, phytoplankton carbon, and related variables to facilitate future algorithm improvements.