MRV of Microalgae-Based Carbon Removal in Wastewater Treatment

Climate change remains one of the most pressing global challenges due to rising atmospheric concentrations of greenhouse gases (GHGs) such as carbon dioxide (CO?). These GHGs trap heat in the Earth's atmosphere, leading to temperature increases, extreme weather events, rising sea levels, and other adverse environmental impacts. To mitigate these effects and meet international climate goals, it is crucial not only to reduce emissions at the source but also to actively remove carbon from the atmosphere. Carbon removal strategies, including carbon capture and storage (CCS), nature-based solutions like afforestation, and technological innovations, play a central role in achieving net-zero emissions targets. Effective carbon removal can offset residual emissions from hard-to-abate sectors, stabilize the climate system, and potentially reverse some climate impacts.

Role of Wastewater Treatment in Reducing Carbon Emissions and Decarbonization

Wastewater treatment is essential for maintaining public health, preserving water resources, and reducing environmental pollution. Beyond its primary function of treating water, wastewater treatment processes have significant potential to contribute to climate change mitigation through carbon management. Conventional wastewater treatment often generates carbon emissions through the degradation of organic matter, methane (CH?) release, and energy-intensive operations. However, advances in sustainable treatment technologies can transform these processes into net carbon sinks by incorporating systems that capture and store carbon. Integrating microalgae cultivation into wastewater treatment exemplifies this approach by simultaneously reducing carbon emissions and enhancing water quality.

Microalgae-Based Systems for Carbon Capture

Microalgae-based systems for carbon capture offer a promising solution to mitigate climate change due to their high efficiency in converting CO? into biomass through photosynthesis. Microalgae can sequester carbon at rates much higher than terrestrial plants, making them an attractive option for carbon capture projects. In wastewater treatment, microalgae utilize the nutrients in wastewater (e.g., nitrogen, phosphorus) to grow, which not only improves water quality but also enhances carbon capture potential. The biomass generated can be harvested for various applications, such as biofuels, animal feed, and bio-based materials. By coupling microalgae cultivation with wastewater treatment, these systems can deliver dual benefits—effective carbon sequestration and improved water treatment, making them a pivotal technology in climate action strategies.

Purpose of MRV for Microalgae-Based Carbon Removal

Measurement, Reporting, and Verification (MRV) is a critical process that underpins the credibility, accuracy, and effectiveness of carbon removal projects. For microalgae-based systems, MRV ensures that the carbon captured and removed through microalgae cultivation is accurately quantified, transparently reported, and independently verified. This robust framework is essential for earning carbon credits, demonstrating compliance with climate commitments, and building confidence among stakeholders, including policymakers, investors, and the scientific community. MRV for microalgae-based carbon removal also supports adaptive management by identifying operational inefficiencies and optimizing system performance over time.?

Microalgae-Based Carbon Removal in Wastewater Treatment

Mechanism of Carbon Removal

Microalgae-based systems for carbon removal are highly effective in sequestering carbon from the atmosphere and integrating it within a controlled wastewater treatment framework. Microalgae, a diverse group of photosynthetic microorganisms, possess a rapid growth rate and high carbon uptake capacity, making them well-suited for large-scale carbon capture operations. The fundamental mechanism involves the absorption of carbon dioxide (CO?) from the surrounding environment (air and dissolved CO? in water) and its conversion into organic biomass during photosynthesis. This biomass, rich in carbon, serves as a temporary carbon store. In wastewater treatment systems, the microalgae use nutrients (such as nitrogen and phosphorus) present in the wastewater to support their growth, which leads to improved water quality through nutrient removal while capturing atmospheric carbon.

The captured carbon in the biomass can be further processed, converted into valuable bio-products (e.g., biofuels, animal feed, or bio-based polymers), or subjected to sedimentation for permanent carbon storage. The sedimentation process can lead to the sequestration of carbon in the form of stable organic carbon compounds in sediment layers. This process is essential for achieving long-term carbon storage and is a key part of quantifying net carbon removal under MRV frameworks. According to the provided methodology (SCM0007 v1.1), treatment-induced biomass sedimentation is a validated mechanism for achieving measurable carbon removal.

Biological and Chemical Processes Involved :

Microalgae-based systems rely on several biological and chemical processes to facilitate carbon removal:

• Photosynthesis: Microalgae absorb light energy and utilize CO? and water to synthesize carbohydrates and other organic compounds, releasing oxygen as a byproduct. This process occurs primarily in the photic zone (upper layer) of water bodies where light is available. The photosynthetic equation can be summarized as:

6CO2+6H2O+Light→C6H12O6(Glucose)+6O2

This conversion of inorganic carbon to organic carbon is central to the microalgal carbon capture process.

• Nutrient Absorption and Biomass Growth: Microalgae utilize dissolved nutrients such as ammonium (NH??), nitrate (NO??), and phosphate (PO?3?) in wastewater. These nutrients, often present at elevated levels in untreated wastewater, serve as essential inputs for microalgal growth and biomass accumulation. Efficient nutrient uptake by microalgae contributes to water quality improvement by reducing nutrient loading, which can otherwise cause harmful algal blooms (HABs).
• Biomineralization and Carbon Storage: The methodology also references processes such as biomineralization, where microalgal cells may contribute to the formation of carbonates like calcium carbonate (CaCO?) under certain conditions. This process leads to the formation of stable, long-term carbon stores. Biomineralization contributes to the burial efficiency of the captured carbon, as outlined in the methodology (SOCIALCARBON SCM0007 v1.1).
• Programmed Cell Death (PCD) and Sedimentation: The methodology specifies the role of programmed cell death in microalgae (induced during treatment events) as a mechanism to enhance carbon removal. Upon cell death, biomass sinks to the bottom of water bodies, where it may undergo sedimentation and form long-term carbon stores in the sediment. This process minimizes the risk of carbon re-release into the atmosphere.

Advantages and Limitations

Advantages

• High Carbon Sequestration Potential: Microalgae exhibit one of the highest carbon uptake rates among photosynthetic organisms, thanks to their rapid growth cycles and high surface-area-to-volume ratios. This makes them exceptionally efficient for carbon sequestration in wastewater treatment systems. By integrating microalgae-based systems, facilities can achieve a high rate of carbon capture while simultaneously processing wastewater.
• Water Quality Improvement: Microalgae-based systems offer a dual benefit by improving water quality during carbon removal. The absorption of nutrients like nitrogen and phosphorus not only supports biomass growth but also mitigates eutrophication in water bodies. This process helps prevent harmful algal blooms (HABs) that can negatively impact aquatic ecosystems and human health.
• Versatility and Scalability: Microalgae-based systems can be deployed in a range of wastewater treatment settings, from small-scale decentralized units to large-scale municipal facilities. Their modular nature allows for adaptability and customization to meet varying carbon capture and water treatment needs.
• Potential for By-Product Generation: The biomass generated through microalgae cultivation can be processed into a wide array of valuable products, including biofuels, fertilizers, animal feed, and bioactive compounds. This provides economic incentives and offsets operational costs, enhancing the financial viability of carbon removal projects.

Limitations

• Variability in Efficiency: The efficiency of microalgae-based carbon removal systems can be influenced by numerous factors, including light availability, temperature, nutrient concentrations, and water pH. Seasonal and geographic variations can lead to fluctuations in carbon sequestration rates, which may pose challenges for consistent carbon accounting and long-term planning.
• Environmental Dependency: The growth and carbon capture potential of microalgae depend on favorable environmental conditions. Factors such as cloud cover, water turbidity, and fluctuations in wastewater composition can impact their photosynthetic activity and nutrient uptake rates. This dependency necessitates adaptive management practices and robust monitoring systems.
• Resource Requirements: Microalgae-based systems may require significant resources, including land, water, energy, and specialized infrastructure, particularly when scaling up for large-scale deployment. The need for continuous monitoring and maintenance, as outlined in the methodology, further adds to operational complexity and costs. Achieving optimal growth conditions for microalgae may involve substantial energy inputs for mixing, lighting, or temperature regulation, potentially offsetting some of the carbon removal benefits.

MRV Framework for Microalgae-Based Carbon Removal

MRV stands for Monitoring or Measurement, Reporting, and Verification, a systematic process crucial for ensuring the credibility and transparency of carbon removal projects. In the context of microalgae-based carbon removal, MRV frameworks provide a structured approach to accurately measure and document the amount of carbon captured, processed, and stored through microalgal cultivation. It ensures that the data supporting carbon removal claims is robust, verifiable, and aligned with established protocols, such as the Social Carbon 's methodology for the treatment of harmful algal blooms (HABs).

Measurement focuses on collecting empirical data on microalgal biomass growth, nutrient uptake, greenhouse gas (GHG) emission reductions, and other relevant parameters.

Reporting entails documenting this data in a clear and standardized format for stakeholders, including project developers, regulators, and carbon market participants.

Verification involves an independent evaluation of reported data to confirm the accuracy and legitimacy of carbon removal claims, often conducted by third-party auditors. Together, these components ensure that the carbon removal benefits achieved by microalgae-based systems are transparent, measurable, and consistent with climate commitments.

Importance of Standardized MRV for Consistent and Accurate Reporting

Standardized MRV frameworks are critical for achieving consistent and accurate reporting of carbon removal activities. By adhering to a common set of protocols, projects can provide comparable data, reduce variability, and increase the trustworthiness of their carbon removal claims. In the case of microalgae-based systems, variations in biomass growth rates, environmental conditions, and operational practices can influence carbon capture performance. A standardized MRV framework helps address these complexities by defining uniform methodologies for data collection, analysis, and reporting, ensuring transparency and comparability across different projects.

Moreover, standardized MRV practices enhance the marketability of carbon removal credits, as potential buyers require confidence in the legitimacy of carbon sequestration claims. It also enables regulatory bodies to assess the compliance and effectiveness of carbon removal initiatives more effectively. By fostering credibility and transparency, standardized MRV practices ultimately promote greater investment in innovative carbon removal technologies, like microalgae-based systems, and drive climate action.

Components of MRV in Microalgae-Based Systems

Measurement:

Biomass Quantification and GHG Emission Reductions :

Measurement is the first and most critical step of the MRV framework, providing the data necessary to quantify the effectiveness of microalgae-based carbon removal systems. The measurement process encompasses several key activities:

Biomass Quantification: The carbon captured by microalgae is directly related to their biomass accumulation. To accurately measure biomass, project developers utilize various techniques, such as:

• Remote Sensing (RS): Satellite or drone-based imaging can estimate the surface area and biomass concentration of microalgae in a water body. Remote sensing data must be calibrated using in-situ measurements to ensure accuracy.
• In-Situ Sampling: Physical sampling of water and sediment is conducted to measure dry biomass concentration, nutrient uptake, and phytoplankton biodiversity. The SOCIALCARBON methodology outlines procedures for collecting and analyzing water samples, including the use of sediment corers for measuring carbon storage in sediments.
• Programmed Cell Death (PCD) and Sedimentation: Measurement also involves quantifying carbon storage resulting from the programmed cell death of microalgae, which leads to biomass sedimentation and long-term carbon sequestration.

GHG Emission Reductions: Microalgae-based systems contribute to GHG emission reductions by sequestering atmospheric CO? and mitigating the release of methane (CH?) and nitrous oxide (N?O) typically generated in conventional wastewater treatment processes. Emissions from project operations, such as energy use and transport, are accounted for in scope 1 and 2 emissions. Calculations must adhere to internationally recognized GHG protocols, ensuring comprehensive coverage of emissions.

Reporting:

Data Logging and Compliance Documentation Once data has been measured, it must be accurately documented and reported. Reporting practices include:

• Data Logging: Detailed records of all measurement activities, including raw data, calibration procedures, and data processing steps, must be maintained. For example, timestamped satellite imagery, field sample data, and laboratory analysis results must be recorded as part of the project documentation. This ensures traceability and allows stakeholders to assess the integrity of data over time.
• Compliance Documentation: Reports generated through the MRV process must adhere to regulatory and project-specific guidelines. Compliance documentation may include project boundary descriptions, baseline scenario assessments, emission reduction calculations, and project activity summaries. Consistent and accurate reporting builds transparency and supports the credibility of carbon removal claims, facilitating the issuance of carbon credits or meeting climate commitments.

Verification:

Independent Validation and QA/QC Measures:

Verification is essential for ensuring the accuracy and reliability of reported data. Independent validation by qualified third-party auditors provides a critical layer of accountability, confirming that MRV processes have been properly conducted and that reported results reflect actual project outcomes. Verification steps include:

Independent Validation:

Third-party auditors review the MRV framework, data collection methods, and reported results to verify compliance with established protocols. This process often involves on-site visits, interviews with project staff, and an examination of documentation. Verified projects gain credibility and are more likely to secure carbon credits and other forms of recognition.

Quality Assurance and Quality Control (QA/QC):

QA/QC measures are implemented throughout the MRV process to minimize errors and enhance data integrity. QA/QC practices may include:

• Calibration of Measurement Instruments: Ensuring that remote sensing devices, field sampling equipment, and laboratory instruments are calibrated according to recognized standards.
• Replication of Measurements: Conducting multiple measurements at different times and locations to reduce variability and improve data reliability.
• Data Audits: Periodic reviews of data collection, processing, and reporting practices to identify and address potential discrepancies or inaccuracies.

Methodological Details for MRV of Microalgae-Based Carbon Removal

Applicability and Boundaries

Conditions for Project Eligibility :

To ensure the effectiveness and relevance of MRV practices for microalgae-based carbon removal, the SCM0007 v1.1 methodology outlines specific applicability conditions for project eligibility. These conditions help determine whether a project qualifies for carbon removal accounting and subsequent certification:

• Treatment Solution Approval: The treatment solution used for controlling harmful algae blooms (HABs) and promoting microalgal carbon capture must be approved by recognized regulatory authorities, such as the United States Environmental Protection Agency (EPA) or an equivalent body. It must also meet the NSF/ANSI/CAN 60 standards for drinking water.
• Demonstrated Effectiveness: The treatment solution must have a proven track record of effectively treating HABs, with supporting evidence from prior pilot studies or implementations. This includes documented improvements in water turbidity, reductions in cyanotoxin levels, and increases in phytoplankton biodiversity.
• Water Body Characteristics: The methodology applies to natural and man-made freshwater and brackish water bodies, such as lakes, ponds, and reservoirs, with a mean depth of at least one meter. Saltwater bodies are excluded.
• Programmed Cell Death (PCD) Induction: The treatment must trigger significant levels of PCD in the algal bloom (at least 99.9% of cells), leading to biomass sedimentation without lysis.
• Performance Criteria: The treatment must achieve specific water quality improvements, including reducing cyanotoxins below 6 parts per billion (ppb) and enhancing water clarity.

Project Boundaries, Including Included and Excluded Carbon Pools :

Project boundaries are critical for defining the spatial and functional scope of a microalgae-based carbon removal project. Accurate boundary definitions ensure that only relevant carbon fluxes and pools are accounted for in the MRV process:

• Spatial Boundaries: Project boundaries encompass the geographical area of the water body undergoing treatment, including areas where microalgae cultivation and sedimentation occur. This boundary is delineated using GIS tools, satellite imagery, and ground survey data, ensuring precise coverage of the treatment area.
• Carbon Pools Included: The primary carbon pool considered in this methodology is the water-surface biomass, which refers to the biomass generated by the harmful algae bloom. This pool is central to carbon removal calculations, as it represents the captured carbon that will either be processed or stored through sedimentation.
• Carbon Pools Excluded: Carbon pools not directly relevant to the treatment process, such as aboveground woody biomass, belowground biomass, deadwood, litter, and soil organic carbon, are excluded from the project boundary. This exclusion aligns with the focus on microalgal biomass as the primary carbon removal mechanism.

Baseline Scenario Determination

Non-Treatment Scenario and Historical Data Requirements :

Establishing a robust baseline scenario is essential for quantifying net carbon removals achieved by a microalgae-based project. The baseline scenario represents the "business-as-usual" condition in which no treatment is applied to control harmful algae blooms. The baseline is characterized by HAB oscillations, nutrient cycling, and seasonal variations in algal biomass without intervention. Key requirements for establishing the baseline scenario include:

• Historical Data Collection: Project proponents must obtain at least three years of historical data on HAB occurrences within the water body. This data, collected through remote sensing imagery with a minimum frequency of 52 images per year, provides evidence of historical bloom patterns, including volume and growth rates.
• Baseline Demonstration: Projects must demonstrate that harmful algae blooms have been a persistent issue over the past three years, posing risks to human and environmental health. In cases where treatment was applied in the past three years, data from prior treatment events must be used to establish a pre-treatment baseline.
• Data Quality Standards: Data sources must meet stringent quality requirements, including spatial and temporal resolution standards, to ensure accurate baseline characterization.

Reference Methods for Establishing Baseline Carbon Emissions :

Baseline carbon emissions are established by calculating the GHG emissions that would occur in the absence of the microalgae-based treatment project. The methodology assumes no net baseline removals, as cyanobacterial biomass typically survives adverse conditions through its pelagic–benthic life cycle. Emissions from uncontrolled HABs, such as methane (CH?) emissions due to biomass decomposition, must be accounted for, providing a reference for quantifying net GHG reductions.

Additionality Criteria

Regulatory Surplus and Additionality Assessments :

The additionality of a microalgae-based carbon removal project is determined using the project method outlined in the SCM0007 v1.1 methodology. Additionality demonstrates that the project achieves emissions reductions beyond those that would occur under business-as-usual conditions or are required by regulation. Key steps include:

• Regulatory Surplus Test: Project proponents must demonstrate that their project exceeds regulatory requirements for environmental and water quality management. This ensures that the carbon removal benefits are not mandated by existing laws and regulations, highlighting the project's voluntary and impactful nature.
• Pro Bono Deployment: If the treatment solution is deployed free of charge to communities or areas with limited resources, the project automatically qualifies as additional. This provision encourages public health and environmental initiatives in underserved regions.
• Investment and Barrier Analysis: For projects not deployed pro bono, an analysis of financial and non-financial barriers must be conducted. This may involve assessing economic viability, technical challenges, and market conditions to confirm that the project would not have occurred without carbon market incentives or other support mechanisms.

Demonstration of Project Impacts Beyond Business-as-Usual Scenarios:

To demonstrate additionality, project proponents must present compelling evidence that their interventions lead to significant, measurable carbon removals that would not have occurred under a baseline scenario. This includes highlighting unique aspects of the microalgae-based system, such as improved nutrient management, enhanced carbon storage through sedimentation, and reductions in GHG emissions. The additionality assessment supports the credibility and environmental integrity of carbon removal claims, providing confidence to stakeholders and potential buyers of carbon credits.

Quantification of GHG Emission Removals

Baseline Removals Calculation :

Methodology for Calculating Carbon Removal Under Non-Intervention Scenarios

The calculation of baseline removals is critical to establish a reference against which the carbon sequestration potential of the microalgae-based project is measured. The baseline scenario represents the condition without project intervention, where harmful algae blooms (HABs) continue their natural cycle, causing ecological and GHG emissions impacts without any deliberate management.

The SCM0007 v1.1 methodology assumes that in the absence of treatment, there is no net carbon removal from the waterbody, as cyanobacteria and algae contribute to a continuous cycle of growth, decay, and methane (CH?) emissions from anaerobic decomposition. This means that the baseline emissions predominantly comprise methane emissions due to the natural decomposition of algal biomass, and any carbon capture and storage in the sediment is negligible or non-permanent. Project proponents must demonstrate these baseline conditions using at least three years of historical data to accurately capture the seasonal variations, growth cycles, and GHG emissions trends of HABs in the absence of intervention.

In specific cases, baseline calculations must exclude any avoided emissions from methane production unless well-supported by evidence. The aim is to provide a conservative baseline estimate that does not overstate the GHG emissions avoided through the project.

Project Removals and Equations:

Key Formulas and Parameters for Quantifying Emission Removals

The project removals refer to the actual amount of carbon dioxide equivalent (CO?e) sequestered as a result of implementing microalgae-based treatment interventions. The SCM0007 v1.1 methodology outlines specific formulas for calculating total emission removals during the monitoring period:

Total Emission Removals Calculation (TER?):

The following equation is used to quantify the total emission removals achieved through microalgae-based treatment:

TERt=ΔHABt×0.48×1244×d×a

Where,

• TER?: Total emission removals during monitoring period ttt (in metric tonnes of CO?e).
• ΔHAB?: Change in dry biomass of the harmful algae bloom following treatment (tonnes).
• 0.48: Conversion factor for dry biomass to carbon content (representing 48% carbon content of algal biomass).
• 44/12: Conversion factor for carbon (tC) to carbon dioxide equivalent (tCO?e).
• d: Burial efficiency factor, representing the fraction of organic carbon that becomes permanently buried.
• a: Correlation constant for remote sensing estimates, accounting for uncertainty in biomass measurements.

The total dry biomass change (ΔHABt) is determined by comparing pre- and post-treatment biomass data using remote sensing and in-situ sampling. This ensures accurate quantification of carbon captured and stored through the treatment process.

Biomass Model Calculation:

The biomass of the harmful algae bloom is modeled using the following equation:

ΔHABt=∑FBnti[Rrs(λ)n]?∑FBnti?1[Rrs(λ)n]

Where:

• FB??? and FB?????: Calibrated biomass models of the HAB post- and pre-treatment respectively.
• R??(\lambda): Remote sensing reflectance values.

Burial Efficiency: Burial efficiency represents the fraction of the organic carbon from algal biomass that becomes buried in sediments and remains sequestered for the long term. This factor accounts for processes such as sedimentation and potential release of GHGs during degradation.

Project Emissions Accounting:

Scope 1 and 2 Emissions Considerations

To accurately assess net carbon removal, it is essential to account for the emissions generated as part of the project’s implementation. These are categorized as Scope 1 (direct emissions) and Scope 2 (indirect emissions) under international GHG protocols:

• Scope 1 Emissions: These include emissions directly associated with project activities, such as: Fuel combustion for on-site equipment used during treatment and monitoring activities. GHG emissions resulting from the transport of materials, equipment, and personnel. Any direct emissions from the treatment process itself.
• Scope 2 Emissions: These are emissions related to purchased energy used for project implementation, including: Electricity consumption for treatment systems, aerators, pumps, monitoring sensors, and data processing. Energy usage for off-site laboratory analyses and biomass processing.

Emissions During Implementation, Transport, Energy Usage, etc.

The project proponent must comprehensively track and calculate all relevant emissions sources associated with project implementation and monitoring. This includes emissions from transportation logistics, energy consumption for monitoring equipment (e.g., remote sensing devices), and emissions related to the production and deployment of treatment solutions. Emissions calculations must comply with internationally recognized protocols, ensuring a transparent and consistent approach.

Leakage and Uncertainty:

Addressing Potential Project Leakages

Leakage refers to the unintended displacement of GHG emissions outside the project boundary as a result of project activities. The SCM0007 v1.1 methodology specifies that leakage risks are minimal for microalgae-based carbon removal projects due to the localized nature of treatment and carbon sequestration. However, any potential leakages, such as emissions from changes in land use around the water body, must be identified, monitored, and reported to ensure that the project’s net impact is accurately represented.

Accounting for Uncertainties in Measurements

Uncertainty is an inherent aspect of carbon quantification, particularly when relying on variable data sources such as remote sensing and in-situ sampling. The methodology prescribes specific measures to address uncertainties, including:

• Calibration and Ground Truthing: Regular calibration of remote sensing models with on-site measurements is required to maintain accuracy in biomass quantification. A minimum correlation coefficient (r2 > 0.7) must be achieved to validate data accuracy.
• Uncertainty Constants: An uncertainty discount factor is applied to the total emission removal calculation, depending on the reliability of the correlation between remote sensing estimates and ground truth data. For example, an r2 value of 0.8 or higher defines an uncertainty constant a=1a = 1a=1, whereas lower correlation values require a downward adjustment.

Monitoring Plan and Procedures

Data Collection and Parameters :

Description of Key Data Points (e.g., Surface Area, Depth, Biodiversity Index)

Effective monitoring of microalgae-based carbon removal projects relies on accurate data collection of several critical parameters, as specified by the SCM0007 v1.1 methodology. These parameters help quantify changes in carbon capture, biodiversity, and water quality, providing a foundation for MRV (Measurement, Reporting, and Verification) efforts. Key data points include:

• Surface Area (HABArea,t): The surface area of the harmful algae bloom (HAB) is a crucial parameter for assessing the extent of algal growth before and after treatment. This area must be measured using remote sensing technologies such as drones or satellite imagery, which can provide accurate spatial coverage of the waterbody.
• Water Body Depth: The mean depth of the water body (Ponds, Lakes, Rivers, Oceans, Estuaries,etc.)influences light penetration, nutrient availability, and biomass distribution. Accurate depth measurements are necessary for calculating biomass volume and assessing burial efficiency.
• Biodiversity Index: The phytoplankton biodiversity index, typically measured using the Shannon Index, provides insights into the ecological health and species diversity within the treated waterbody. This index is calculated from samples collected pre- and post-treatment and processed using methods such as eDNA analysis or flow cytometry by independent laboratories.
• Cyanotoxin Levels: Monitoring the concentration of cyanotoxins is essential for ensuring that the treatment effectively reduces harmful toxins to safe levels (e.g., below 6 parts per billion). Cyanotoxin levels are measured at defined intervals before and after treatment.
• Water Turbidity: Turbidity measurements, often performed using a Secchi disk or other appropriate tools, provide information on water clarity, indicating the effectiveness of treatment in reducing suspended particles.
• Dry Biomass: Accurate measurement of algal biomass, including both dry weight and sedimented biomass, is critical for calculating carbon sequestration.

Techniques for Accurate and Consistent Data Collection

Consistency and accuracy in data collection are essential for maintaining the credibility and reliability of MRV processes. The following techniques ensure high-quality data:

• Remote Sensing Techniques: The use of satellite imagery, drones, and other remote sensing technologies provides large-scale, consistent monitoring of HAB surface areas, water quality, and other parameters. Data obtained through remote sensing must be geo-referenced with precise coordinates and timestamps.
• In-Situ Sampling: Physical sampling is conducted at pre-defined locations and depths. The methodology outlines protocols for water and sediment sample collection, including the use of sediment corers for measuring carbon storage and GPS tagging for accurate location identification. All field sampling must comply with documented standard operating procedures to minimize variability and maximize data reliability.
• Standardized Procedures for Sample Analysis: Laboratory analysis of collected samples, such as phytoplankton biodiversity and cyanotoxin concentration, must follow established protocols. Analytical techniques include eDNA or microscopy for biodiversity assessments and commercially available kits for cyanotoxin measurement.

Remote Sensing and In-Situ Calibration:

Utilization of Remote Sensing for Biomass Measurement

Remote sensing plays a pivotal role in monitoring microalgae-based carbon removal projects. By capturing large-scale spatial data, remote sensing technologies provide valuable insights into the distribution and density of HABs across waterbodies. Specific aspects of remote sensing include:

• Remote Sensing Reflectance (Rrs): Satellite or drone-based systems measure reflectance values at specific wavelengths to estimate algal biomass. These measurements are then processed using calibration coefficients to generate biomass models, as outlined in the SCM0007 v1.1 methodology.
• Integration with GIS Tools: Remote sensing data is often combined with geographic information systems (GIS) for spatial analysis, enabling precise mapping of HAB distribution and changes over time. This integration supports accurate measurement and visualization of carbon capture and water quality improvements.

Ground Truthing and Calibration Methodologies

Ground truthing involves on-site data collection to validate and calibrate remote sensing models. Accurate calibration ensures that remote sensing estimates reflect actual conditions within the waterbodies.

Key ground truthing steps include:

• Physical Sampling for Biomass Calibration: In-situ measurements of biomass are collected using standardized sampling procedures. The dry weight of microalgae is measured and correlated with remote sensing data to establish calibration coefficients (FcalF_{cal}Fcal) that convert remote sensing reflectance values into biomass estimates.
• Correlation Analysis: A correlation coefficient (r2) of 0.7 or higher must be achieved between remote sensing estimates and physical sample data to ensure accuracy. Lower correlation values require re-evaluation of the remote sensing algorithm or adjustments to in-situ data collection procedures.
• Periodic Calibration Checks: Ground truthing must be performed regularly to maintain data accuracy. Calibration coefficients may need adjustments based on environmental changes, seasonal variations, or shifts in waterbody characteristics.

QA/QC Measures

Quality Assurance and Control Procedures Quality assurance (QA) and quality control (QC) procedures are essential for ensuring that data collected through MRV processes is accurate, consistent, and reliable. Key QA/QC measures include:

• Calibration of Instruments: All field and laboratory instruments, including remote sensing devices, water sampling equipment, and laboratory analyzers, must be calibrated according to the manufacturer’s guidelines before use. Calibration ensures accurate readings and minimizes systematic errors.
• Replication of Measurements: Multiple measurements and samples are taken at different locations and times to account for natural variability and ensure data consistency. This replication helps identify and correct anomalous data points.
• Data Validation and Review: Data collected during field sampling and laboratory analysis is subject to independent review to ensure that it meets established quality standards. Data validation checks include comparisons with historical data, consistency checks, and statistical analyses.

Independent Verification and Validation Steps Independent verification provides a critical layer of accountability in the MRV framework. Verification is conducted by qualified third-party auditors who assess the accuracy and completeness of reported data, adherence to protocols, and overall project integrity. Key steps include:

• On-Site Audits: Third-party auditors may conduct on-site visits to verify data collection procedures, inspect equipment, and interview project staff. These audits ensure that field operations align with documented protocols.
• Review of Documentation: All data logs, calibration records, and analytical results are subject to independent review. Auditors may request additional data or clarifications as part of the verification process.
• Issuance of Verification Statements: Verified projects receive certification or verification statements, providing assurance to stakeholders that reported results are credible and accurate.

By adhering to robust monitoring plans and procedures, microalgae-based carbon removal projects can ensure data accuracy, demonstrate compliance with established protocols, and maintain transparency and accountability in their MRV processes. This ultimately strengthens the credibility of their carbon removal claims and supports climate action goals.

Application of MRV Methodology on a Sample Microalgae-Based Project

The project involves the treatment of a large, natural freshwater lake with a significant history of HABs, driven by nutrient pollution and seasonal variations. The primary objectives of the project are to reduce the prevalence of harmful algal blooms, sequester carbon through microalgal biomass accumulation, and improve water quality through nutrient uptake. The treatment solution used is certified for drinking water and approved by the relevant regulatory authorities.

Monitoring Phases and Methodological Steps

Baseline Scenario Determination :

The baseline scenario assumes no intervention to control HABs, leading to periodic algal blooms that contribute to methane (CH?) emissions through biomass decay. Historical data from remote sensing imagery over the past three years was used to establish a reference for HAB growth and volume, demonstrating a persistent presence that poses risks to human and ecological health.

Data Collection and Monitoring Surface Area Measurement:

The total area of the lake affected by HABs was determined using drone-based remote sensing, with data validated through in-situ sampling points. Measurements captured pre- and post-treatment conditions, enabling accurate quantification of HAB surface area.

• Water Depth and Biomass Quantification: The mean depth of the water body was measured to assess the distribution and burial potential of algal biomass. Biomass quantification involved the collection of water samples to measure dry biomass concentrations before and after treatment, using filtration and drying techniques.
• Biodiversity Assessment: Pre- and post-treatment phytoplankton biodiversity was measured using the Shannon Index, with samples analyzed by an independent laboratory using eDNA procedures. Results demonstrated increased biodiversity following treatment, indicating ecosystem health improvements.
• Cyanotoxin Levels and Water Turbidity: Cyanotoxin concentrations were monitored using both laboratory analysis and field kits, confirming reductions below 6 ppb post-treatment. Water turbidity was assessed using Secchi disk measurements.

Project Emission Removals Calculation Change in Biomass:

The change in dry biomass (ΔHAB?) was calculated using the difference in pre- and post-treatment biomass values. The total emission removals (TER?) were then quantified using the formula provided in the methodology:

TERt=ΔHABt×0.48×1244×d×a

Here, the burial efficiency (ddd) and correlation constant (aaa) were determined through sediment core sampling and remote sensing calibration, respectively. Biomass burial in sediment was verified through sediment core analysis, demonstrating long-term carbon storage.

Project Emissions Accounting:

Emissions generated during project implementation, including transportation of equipment, on-site energy usage, and other operational activities, were accounted for under scope 1 and 2 emissions. Calculations followed internationally recognized GHG protocols to ensure comprehensive and transparent accounting.

Quality Assurance and Control (QA/QC):

Calibration of instruments and independent verification by third-party auditors ensured the reliability of data collection and analysis. Remote sensing data was periodically calibrated with in-situ measurements to maintain accuracy.

Quantified GHG Removals :

The project demonstrated significant GHG removals through the quantified reduction of HAB biomass and subsequent carbon sequestration in sediments. Monitoring data showed an increase in phytoplankton biodiversity, reduced cyanotoxin levels, and improvements in water clarity, validating the effectiveness of the treatment intervention. Total GHG removals were reported in metric tonnes of CO? equivalent (tCO?e) based on the calculated changes in biomass and verified burial efficiency.

Challenges and Recommendations

Technical Challenges:

Data Variability

One of the key challenges faced in the application of MRV (Measurement, Reporting, and Verification) frameworks for microalgae-based carbon removal is data variability. Microalgae cultivation and HAB (Harmful Algal Bloom) control are influenced by a wide range of environmental factors, such as light availability, water temperature, nutrient concentration, and seasonal changes. These variables lead to fluctuations in biomass production, carbon sequestration rates, and water quality improvements, making consistent and predictable outcomes challenging. For example, climate-driven variations can alter growth patterns, affecting carbon capture efficiency. This variability underscores the importance of robust data collection, adaptive monitoring, and accurate baseline establishment to properly quantify carbon removals and verify project performance.

Operational Complexities

The successful implementation of microalgae-based carbon removal systems involves complex operational requirements. Integrating microalgae cultivation within wastewater treatment systems requires precise control over parameters like nutrient dosing, water flow, aeration, and sedimentation. Balancing optimal microalgal growth conditions with system stability is critical, particularly in large-scale projects. Furthermore, consistent equipment maintenance (e.g., aerators, sensors, and monitoring devices) and adherence to rigorous treatment protocols can pose significant challenges. Issues such as equipment malfunctions, environmental changes, and logistical constraints in remote or decentralized locations may impact overall system performance.

Resource Constraints

Resource constraints present a significant barrier to the implementation and scalability of microalgae-based carbon removal projects. These include limitations on land, water, and energy resources, as well as financial constraints related to initial project establishment, ongoing operations, and long-term maintenance. High-precision monitoring equipment, laboratory analyses, and independent verification processes can be cost-prohibitive for smaller-scale projects, potentially limiting their participation in carbon markets or their ability to achieve measurable climate benefits. Additionally, human resource constraints, such as limited availability of skilled personnel with expertise in microalgae cultivation, wastewater management, and MRV practices, can hinder project performance.

Emerging Technologies for Monitoring

The integration of innovative monitoring technologies, such as smartphone camera-based water quality monitoring systems developed by Mechwat and Commalinn, offers an effective solution to some of these challenges. This technology leverages smartphones equipped with sensors and artificial intelligence (AI) algorithms to monitor parameters like water turbidity, nutrient levels, temperature, and algal biomass density. By capturing real-time data, this approach reduces the reliance on expensive remote sensing equipment and in-situ sampling, making water quality monitoring more accessible and cost-effective for both small and large-scale projects. However, integrating and calibrating such technologies with existing MRV frameworks can present its own challenges in terms of data accuracy, compatibility, and validation.

Recommendations for MRV Improvements:

Enhancing Data Precision :

To address challenges related to data variability and accuracy, several steps can be taken to enhance data precision:

• Investing in High-Resolution Monitoring Tools: Advanced remote sensing technologies such as high-resolution satellite imagery, drone-based surveys, and smartphone camera-based monitoring systems offer greater precision in assessing microalgal biomass, water quality, and carbon sequestration rates.
• Regular Calibration and Ground Truthing: Remote sensing data, including data from smartphone-based monitoring, must be regularly calibrated with in-situ measurements to maintain accuracy. Ground truthing performed at regular intervals validates data integrity and reduces uncertainties.
• Data Integration and Advanced Analytics: Integrating data from remote sensing, in-situ sampling, and smartphone-based monitoring into a centralized data platform improves data accuracy and trend analysis capabilities. AI-driven analytics can further optimize project performance by identifying patterns and adapting to changing environmental conditions.

Cost Reduction Strategies:

Cost reduction strategies are essential for increasing the accessibility and scalability of microalgae-based carbon removal projects:

• Automation and Digital Solutions: Automating data collection and reporting using smartphone-based technology and other digital solutions can reduce labor costs and minimize human error. Cloud-based platforms for data storage and analysis can streamline MRV workflows and enhance operational efficiency.
• Collaborative Efforts and Partnerships: Engaging in partnerships with academic institutions, research organizations, and private sector stakeholders, such as collaborations with Mechwat and Commalinn for monitoring solutions, can distribute the financial burden of MRV implementation. Collaborative research can also lead to the development of cost-effective monitoring technologies.
• Modular System Design: Developing modular microalgae-based carbon removal systems that can be easily scaled up or down according to project needs enables flexible and cost-effective deployment, particularly in decentralized applications.

Increasing Project Scalability:

To maximize the impact of microalgae-based carbon removal systems, it is important to focus on increasing project scalability through targeted measures:

• Standardizing MRV Protocols: Developing standardized MRV protocols for projects of varying sizes and operational contexts simplifies implementation and reduces costs. Streamlined protocols can enable smaller-scale projects to participate in MRV processes while maintaining rigor and credibility.
• Training and Capacity Building: Providing training programs for personnel involved in project implementation and monitoring, including training on new technologies such as smartphone-based monitoring, ensures that staff have the necessary skills to implement MRV processes effectively. This builds project resilience and scalability.
• Incentivizing Participation in Carbon Markets: Facilitating access to carbon markets and providing financial incentives for projects that demonstrate measurable carbon removals increases the viability and appeal of microalgae-based carbon removal systems. Revenue generated through carbon credits can be reinvested in project expansion and further innovation

Conclusions

Summarization of Key MRV Steps and Their Implications for Carbon Removal

Microalgae-based carbon removal systems offer a transformative approach to mitigating greenhouse gas emissions, improving water quality, and supporting climate action goals. The effective deployment of these systems relies on a robust MRV (Measurement, Reporting, and Verification) framework that ensures the accurate quantification, transparent reporting, and independent validation of carbon sequestration activities. The key steps in the MRV process, as outlined in the SCM0007 v1.1 methodology, provide a structured approach to capturing and verifying the carbon removal potential of microalgae systems:

• Measurement: Accurate data collection is the cornerstone of MRV. This includes quantifying microalgal biomass, measuring water quality improvements, and assessing changes in GHG emissions. Tools such as high-resolution remote sensing, in-situ sampling, and emerging technologies like smartphone-based water quality monitoring provide the data needed to evaluate project outcomes.
• Baseline Scenario Determination: Establishing a robust baseline scenario is critical for measuring net carbon removal. Historical data on harmful algal bloom (HAB) occurrences, nutrient levels, and GHG emissions provide a reference against which project performance is assessed, ensuring that carbon removal claims reflect true project impacts.
• Reporting: Transparent and accurate reporting of data, including project boundary descriptions, baseline scenarios, and carbon removal calculations, builds credibility and accountability. Compliance documentation, data logs, and standardized formats enable stakeholders to assess project outcomes consistently.
• Verification: Independent verification of MRV processes ensures that reported data is accurate, reliable, and aligned with established protocols. This step provides an additional layer of credibility, fostering trust among stakeholders and supporting the issuance of carbon credits and other climate-related certifications.

The implications of these MRV steps extend beyond carbon removal; they also drive continuous improvement in project design, foster innovation, and enhance the scalability of microalgae-based systems. By ensuring accurate measurement and transparent reporting, projects can demonstrate their impact on carbon sequestration, support regulatory compliance, and generate financial incentives through carbon markets.

The Future Outlook of Microalgae-Based MRV Systems in Wastewater Treatment

The future of microalgae-based MRV systems in wastewater treatment is promising, with significant potential to address global environmental and climate challenges. As demand for sustainable and effective carbon removal solutions grows, microalgae-based systems are poised to play an increasingly vital role. Several key trends and developments are expected to shape their future:

• Technological Innovations: Advancements in remote sensing, artificial intelligence, and automation are enhancing the precision and cost-effectiveness of MRV processes. Technologies like smartphone-based water quality monitoring systems, developed in collaboration with organizations like Mechwat and Commalinn, are making real-time monitoring more accessible, reducing reliance on expensive equipment, and improving data accuracy. Continued innovation will drive the adoption and scalability of microalgae-based systems.
• Scalability and Cost Reduction: Standardized MRV protocols, modular system designs, and collaborative partnerships are making it easier to scale microalgae-based projects. Cost reduction strategies, such as automation and shared infrastructure, are further lowering barriers to entry, enabling small and medium-sized projects to participate in carbon markets and contribute to global climate goals.
• Policy and Regulatory Support: As governments and regulatory bodies prioritize climate action, the establishment of supportive policies and incentives for microalgae-based carbon removal projects is likely to increase. Regulatory frameworks that recognize and reward projects for their verified carbon removals will encourage greater investment and participation.
• Integration with Circular Economy Practices: Microalgae-based systems have the potential to generate valuable by-products, such as biofuels, fertilizers, and bio-based materials, creating additional revenue streams and enhancing project viability. Integrating these systems into broader circular economy practices will maximize their environmental and economic benefits.
• Collaboration and Knowledge Sharing: Collaboration among research institutions, industry stakeholders, and governments will drive the development of best practices, data sharing, and innovative solutions for MRV in microalgae-based projects. Knowledge sharing platforms and partnerships will accelerate progress and enhance project outcomes.

In conclusion, microalgae-based carbon removal systems, supported by a robust MRV framework, offer a scalable and effective solution for mitigating climate change and improving water quality in wastewater treatment settings. By addressing current challenges, embracing technological innovations, and fostering collaboration, these systems have the potential to play a transformative role in achieving global climate and sustainability targets. The continued evolution of MRV practices will ensure their long-term credibility, impact, and contribution to a more sustainable and resilient future.