SEARCH · Search NASA

Results for “fugitive emissions”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Global methane emissions from coal mining to continue growing even with declining coal production

This paper presents projections of global methane emissions from coal mining under different coal extraction scenarios and with increasing mining depth through 2100. The paper proposes an updated methodology for calculating fugitive emissions from coal mining, which accounts for coal extraction method, coal rank, and mining depth and uses evidence-based emissions factors. A detailed assessment shows that coal mining-related methane emissions in 2010 were higher than previous studies show. This study also uses a novel methodology for calculating methane emissions from abandoned coal mines and represents the first estimate of future global methane emissions from those mines. The results show that emissions from abandoned mines increase faster than those from active ones. Using coal production data from six integrated assessment models, this study shows that by 2100 methane emissions from active underground mines increase by a factor of 4, while emissions from abandoned mines increase by a factor of 8. Abandoned mine methane emissions continue through the century even with aggressive mitigation actions.

coal mine methane, abandoned coal mine methane, em↗

DOE OSTI2024

Addressing Low-Cost Methane Sensor Calibration Shortcomings with Machine Learning

Quantifying methane emissions is essential for meeting near-term climate goals and is typically carried out using methane concentrations measured downwind of the source. One major source of methane that is important to observe and promptly remediate is fugitive emissions from oil and gas production sites but installing methane sensors at the thousands of sites within a production basin is expensive. In recent years, relatively inexpensive metal oxide sensors have been used to measure methane concentrations at production sites. Current methods used to calibrate metal oxide sensors have been shown to have significant shortcomings, resulting in limited confidence in methane concentrations generated by these sensors. To address this, we investigate using machine learning (ML) to generate a model that converts metal oxide sensor output to methane mixing ratios. To generate test data, two metal oxide sensors, TGS2600 and TGS2611, were collocated with a trace methane analyzer downwind of controlled methane releases. Over the duration of the measurements, the trace gas analyzer’s average methane mixing ratio was 2.40 ppm with a maximum of 147.6 ppm. The average calculated methane mixing ratios for the TGS2600 and TGS2611 using the ML algorithm were 2.42 ppm and 2.40 ppm, with maximum values of 117.5 ppm and 106.3 ppm, respectively. A comparison of histograms generated using the analyzer and metal oxide sensors mixing ratios shows overlap coefficients of 0.95 and 0.94 for the TGS2600 and TGS2611, respectively. Overall, our results showed there was a good agreement between the ML-derived metal oxide sensors’ mixing ratios and those generated using the more accurate trace gas analyzer. This suggests that the response of lower-cost sensors calibrated using ML could be used to generate mixing ratios with precision and accuracy comparable to higher priced trace methane analyzers. This would improve confidence in low-cost sensors’ response, reduce the cost of sensor deployment, and allow for timely and accurate tracking of methane emissions.

03 NATURAL GAS↗

DOE OSTI2024

Estimating Total Methane Emissions from the Denver-Julesburg Basin Using Bottom-Up Approaches

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic.

03 NATURAL GAS↗

DOE OSTI2024

PNNL-Sequim Campus Radionuclide Air Emissions Report for Calendar Year 2023

The U.S. Department of Energy Office of Science (DOE-SC) Pacific Northwest Site Office has oversight and stewardship duties associated with the Pacific Northwest National Laboratory Sequim campus. Some research projects have the potential to emit low levels of radioactive materials. This report is prepared to document compliance with the Code of Federal Regulation, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, "Radiation Protection–Air Emissions." Compliance is indicated by comparing the estimated effective dose equivalent (EDE) to the maximally exposed individual (MEI) member of the public with the 10 millirem per year (mrem/yr) U.S. Environmental Protection Agency (EPA) standard. The PNNL-Sequim campus has only fugitive emissions sources.

40 CFR 61 Subpart H↗

DOE OSTI2021

Smart Methane Emission Detection System Development Final Report

03 NATURAL GAS↗

DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real-time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: Run in real-time on the edge (≥ 12 Hz), Classification: Achieve less than 5% false positive detection, Classification: Achieve ≥ 95% methane plume detection rate, Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time. In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗

DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy’s National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI’s Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: 1. Run in real-time on the edge (≥ 12 Hz) 2. Classification: Achieve less than 5% false positive detection 3. Classification: Achieve ≥ 95% methane plume detection rate 4. Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗

DOE OSTI2025

Review of the potential and challenges of MOF-based adsorption heat pumps for sustainable cooling and heating in the buildings

Heat pumps are regarded as the most suitable means to meet the future demand of heating and cooling in the building, as they require small input of electrical energy and output high thermal energy. Vapor compression heat pump (VCHP) and transcritical-CO 2 heat pump are the two major heat pump technologies currently dominating the market. However, VCHP system suffers from its fugitive emission of hydrofluorocarbon (HFC) refrigerants, and transcritical-CO 2 system requires high operating pressure (typically 9–13 MPa). For low-to-medium temperature heating and cooling applications thermally driven adsorption heat pump (AHP) provides a better alternative to VCHP and transcritical-CO 2 system as AHP uses natural refrigerants and operates at a much lower pressure. But currently available AHP technology has the limitation of low coefficient of performance (COP). Advances in synthesizing metal-organic frameworks (MOF) with high gas adsorption capacity have created an opportunity to address the problem of low COP of current AHP technology. Here, this article reviews the progress made in the past decade in utilizing MOF and conventional adsorbents with different working fluids in AHP technology and compares their performance. The article also summarizes the key challenges for the MOF-based AHP technology and provides the authors’ perspective to address these challenges.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2025

Process and environmental safety of thermochemical conversion of biomass

Biomass presents a promising opportunity for converting waste into valuable energy, fuels, and chemicals through various thermochemical processes, including hydrothermal carbonization, hydrothermal liquefaction, pyrolysis, gasification, and combustion. However, these processes operate under extreme conditions, introducing significant safety hazards that necessitate meticulous management to prevent accidents. This review discusses potential hazards, risk mitigation strategies, and safety management practices, emphasizing the importance of integrated safety measures into the design and operation of these processes. It also highlights the critical need for robust safety engineering and environmental management strategies tailored to each thermo-chemical process. As these processes transition from laboratory to industrial scale, there is an imperative to develop a clear and concise pathway for emerging industries to achieve regulatory compliance, achieve safety certification, and enable effective stewardship of potential fugitive emissions. By addressing safety and environmental concerns, stakeholders can optimize economic benefits, rural development, and achieve sustained domestic energy generation benefits offered by biomass conversion technologies. Further research on plant design optimization, operational safety, environmental evaluation standardization, and innovative waste management solutions will support the safe and effective scaling of these technologies, ultimately contributing to sustainable management and resource recovery.

09 - BIOMASS FUELS↗

DOE OSTI2024

Biohydrogen: prospects for industrial utilization and energy resiliency in rural communities

Biohydrogen (bioH 2 ) production in rural regions of the United States leveraged from existing biomass waste streams serves two extant needs: rural energy resiliency and decarbonization of heavy industry, including the production of ammonia and other H 2 -dependent nitrogenous products. We consider bioH 2 production using two different strategies: (1) dark fermentation (DF) and (2) anaerobic digestion followed by steam methane reforming of the biogas (AD-SMR). Production of bioH 2 from biomass waste streams is a potentially ‘greener’ pathway in comparison to natural gas-steam methane reforming (NG-SMR), especially as fugitive emissions from these wastes are avoided. It also provides a decarbonizing potential not found in water-splitting technologies. Based on literature on DF and AD of crop residues, woody biomass residues from forestry wastes, and wastewaters containing fats, oils, and grease (FOG), we outline scenarios for bioH 2 production and displacement of fossil fuel derived methane. Finally, we compare the costs and carbon intensity (CI) of bioH 2 production with those of other H 2 production pathways.

08 HYDROGEN↗

DOE OSTI2020

Remediation of Temporary Storage Sites in Support of the Port Hope Area Initiative - 20295

The Port Hope Area Initiative is a community-based solution for the long-term management of historic low level radioactive waste (LLRW) resulting from 60 years of uranium and radium processing operations in the Town of Port Hope which is located in Ontario, Canada. The Eldorado refinery, on the north shore of Lake Ontario, began refining radium-226 from pitchblende ore, later transitioning to the refining of uranium. Through the history of the operation, LLRW was deposited throughout the town of Port Hope as a result of fugitive emissions from the plant and/or through the re-use of process residues as building material and backfill. Historical clean-up activities conducted in the late 1970's involved the remediation of approximately 400 properties and the relocation of 100,000 cubic metres of contaminated soil to a disposal facility in Chalk River operated by Atomic Energy of Canada Limited (AECL). Owing to space limitations at that disposal facility, any LLRW identified through construction monitoring since that time has been stored in the community at three temporary storage sites located throughout the town. These include: the Centre Pier mound that contained approximately of 19,800 m{sup 3} of LLRW-impacted soil that originated from the construction of a new water treatment plant; two mounds located at a licensed storage facility containing LLRW obtained from residential clean-up activities (11,000 m{sup 3}); and a small pad adjacent to the municipal sewage treatment plant containing 2200 m{sup 3} of LLRW-containing sludge. With the construction of a new long-term waste management facility (LTWMF) that has been designed to house all of the LLRW identified within Port Hope, the three sites were early candidates for remediation. The clean-up of the three temporary storage sites was a significant milestone for the Port Hope Area Initiative. After a decade of planning and consultation, this work represents the first sites in the municipality to be remediated with the waste being safety removed and transferred to the newly constructed LTWMF. This paper discusses the challenges associated with the clean-up activities for these three sites and the strategies employed to address those challenges. These included weather-related challenges, owing to the seasons over which the work was conducted as well as those associated with working within a closely-knit community. Canadian Nuclear Laboratories (CNL), working on behalf of the federal government, has worked diligently to develop a positive and trusting relationship with the community. Consequently, the successful execution of this project needed to be sensitive to, and respectful of the needs of the community. In addition to the usual Health, Safety and Environment training, project staff received community awareness training that spoke to the history of this community-based initiative and the expected behavior when working within the community. Transportation routes were defined based on safety and the need to minimize disruption to local traffic while haul-times where scheduled around school bus hours to enhance public safety. The successful completion of this first of many remediation projects to be completed under the Port Hope Area Initiative reflected years of careful planning. Nevertheless, there were a number of 'lessons learned' that have been applied on other ongoing projects be completed under the Port Hope Area Initiative. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Comparison of Sub-Ppm Instrument Response Suggests Higher Detection Limits Could Be Used to Quantify Methane Emissions from Oil and Gas Infrastructure

Quantifying and controlling fugitive methane emissions from oil and gas facilities remains essential for addressing climate goals, but the costs associated with monitoring millions of production sites remain prohibitively expensive. Current thinking, supported by measurement and simple dispersion modelling, assumes single-digit parts-per-million instrumentation is required. To investigate instrument response, the inlets of three trace-methane (sub-ppm) analyzers were collocated on a facility designed to release gas of known composition at known flow rates between 0.4 and 5.2 kg CH 4 h –1 from simulated oil and gas infrastructure. Methane mixing ratios were measured by each instrument at 1 Hertz resolution over nine hours. While mixing ratios reported by a cavity ring-down spectrometer (CRDS)-based instrument were on average 10.0 ppm (range 1.8 to 83 ppm), a mid-infrared laser absorption spectroscopy (MIRA)-based instrument reported short-lived mixing ratios far larger than expected (range 1.8 to 779 ppm) with a similar nine-hour average to the CRDS (10.1 ppm). We suggest the peaks detected by the MIRA are likely caused by a micrometeorological phenomenon, where vortex shedding has resulted in heterogeneous methane plumes which only the MIRA can observe. Further analysis suggests an instrument like the MIRA (an optical-cavity-based instrument with cavity size ≤10 cm3 measuring at ≥2 Hz with air flow rates in the order of ≤0.3 slpm at distances of ≤20 m from the source) but with a higher detection limit (25 ppm) could detect enough of the high-concentration events to generate representative 20 min-average methane mixing ratios. Even though development of a lower-cost, high-precision, high-accuracy instrument with a 25 ppm detection threshold remains a significant problem, this has implications for the use of instrumentation with higher detection thresholds, resulting in the reduction in cost to measure methane emissions and providing a mechanism for the widespread deployment of effective leak detection and repair programs for all oil and gas infrastructure.

03 NATURAL GAS↗

DOE OSTI2025

Methane Mitigator – Development of a Scalable Vent Mitigation Strategy to Simultaneously Reduce Methane Emissions and Fuel Consumption from the Compression Industry (Final Technical Report)

Researchers at West Virginia University completed a multi-year project under DE-FE0031865 entitled “Methane Mitigator – Development of a Scalable Vent Mitigation Strategy to Simultaneously Reduce Methane Emissions and Fuel Consumption from the Compression Industry”. An assessment of natural gas production site emission sources was completed to quantify the potential for emissions reductions and reductions in fuel consumption. The main sources of fugitive methane emissions at gas productions sites include condensate tanks, produced water tanks, gas compressor packing vents, pneumatic controller vents, and natural gas engine crankcase vents.

03 NATURAL GAS↗

DOE OSTI2023

Methane Emissions Produced by Pneumatic Devices and Produced Water Tanks on Natural Gas Wellsites

In recent years, more scrutiny has been placed on the release of greenhouse gasses (GHGs) by the oil and gas industry in North America as climate concerns increase. In the coming years, stricter regulations proposed by the Environmental Protection Agency (EPA) concerning the release of GHGs will further direct attention to GHG emissions quantification, modeling, and overall reduction. Active natural gas wellsites employ production equipment that routinely emits methane during normal operation. Production equipment often includes, but is not limited to, gas production units (GPUs), pneumatic controllers (PCs) and actuators powered by produced natural gas, and produced water storage tanks. This work details direct methane emission measurements taken at active natural gas wellsites originating from intermittent pneumatic controllers and produced water storage tanks. Efforts to model methane flows originating from these sources are also detailed, and those results are compared to direct measurement. The direct methane emissions measurement campaign collected flow data from two active dry wellsites in the Marcellus shale region. These measurement campaigns captured, in total, several weeks of continuous data from these sites. Data included multiple pneumatic device vent flowrate channels, a single channel monitoring total emissions vented from the produced water storage tanks, and corresponding site weather data. Periodic composition measurements were taken from flows vented from produced water tanks. Computational modeling efforts attempted to mimic a given site’s methane emissions behavior given limited input parameters. Direct measurement data and simulation data yielded, through reduction and analysis, apparent methane emissions factors, statistics on pneumatic device actuation events, important relationships between GPU parameters and pneumatic device actuation events, produced water storage tank vent flows and flow compositions, and parameters most contributing to the magnitude and frequency of these fugitive methane emissions. Measurements, considering data from a 72hr period, produced PC emissions factors from 0.008 to 0.03 SCFH per device with an average device emitting 0.026 SCFH at the first site. The second site produced PC emissions factors spanning from 0.05 to 25.47 SCFH with an average device emitting 1.93 SCFH not including the 25.47 SCFH device, which was assumed to be malfunctioning. Two unique water tank emission measurements were made, 618 g CH4 per hour and 32.6 g CH4 per hour. On a water basis, the water tank emissions factors were 0.66 and 0.042 kg CH4 per bbl of water, respectively.

03 NATURAL GAS↗

DOE OSTI2020

PNNL Richland Campus Radionuclide Air Emissions Report for Calendar Year 2019

This report documents radionuclide air emissions that result in the 2019 highest effective dose equivalent (EDE) to an offsite member of the public, referred to as the maximally exposed individual (MEI). The report has been prepared in compliance with the Code of Federal Regulations, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, “Radiation Protection–Air Emissions.” The dose to the PNNL Richland Campus MEI from routine major and minor point source emissions in 2019 from PNNL Richland Campus sources is 1.4E-5 mrem (1.4E-7 mSv) EDE. The dose from all fugitive sources is 1.3E-6 mrem (1.3E-8 mSv) EDE. The dose from radon emissions is 1.5E-10 mrem (1.5E-12 mSv) EDE. No nonroutine emissions occurred in 2019. The total radiological dose to the MEI from all PNNL Richland Campus radionuclide emissions, including fugitive emissions and radon, is 1.5E-5 mrem (1.5E-7 mSv) EDE, or more than 10,000 times less than the federal and state standard of 10 mrem/yr, with which the PNNL Richland Campus is in compliance.

40 CFR 61 Subpart H↗

DOE OSTI2021

PNNL Richland Campus Radionuclide Air Emissions Report for Calendar Year 2020

This report documents radionuclide air emissions that result in the 2020 highest effective dose equivalent (EDE) to an offsite member of the public, referred to as the maximally exposed individual (MEI). The report has been prepared in compliance with the Code of Federal Regulations, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, “Radiation Protection–Air Emissions.” The dose to the PNNL Richland Campus MEI from routine major and minor point source emissions in 2020 from PNNL Richland Campus sources is 1.5E-5 mrem (1.5E-7 mSv) EDE. The dose from all fugitive sources is 2.0E-6 mrem (2.0E-8 mSv) EDE. The dose from radon emissions is 9.3E-9 mrem (9.3E-11 mSv) EDE. No nonroutine emissions occurred in 2020. The total radiological dose to the MEI from all PNNL Richland Campus radionuclide emissions, including fugitive emissions and radon, is 1.7E-5 mrem (1.7E-7 mSv) EDE, or more than 100,000 times less than the federal and state standard of 10 mrem/yr, with which the PNNL Richland Campus is in compliance.

40 CFR 61 Subpart H↗

DOE OSTI2022

PNNL Richland Campus Radionuclide Air Emissions Report for Calendar Year 2021

This report documents radionuclide air emissions that result in the 2021 highest effective dose equivalent (EDE) to an offsite member of the public, referred to as the maximally exposed individual (MEI). The report has been prepared in compliance with the Code of Federal Regulations, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, “Radiation Protection–Air Emissions.” The dose to the PNNL Richland Campus MEI from routine major and minor point source emissions in 2021 from PNNL Richland Campus sources is 1.7E-5 mrem (1.7E-7 mSv) EDE. The dose from all fugitive sources is 1.2E-6 mrem (1.2E-8 mSv) EDE. The dose from radon emissions is 2.1E-9 mrem (2.1E-11 mSv) EDE. No nonroutine emissions occurred in 2021. The total radiological dose to the MEI from all PNNL Richland Campus radionuclide emissions, including fugitive emissions and radon, is 1.8E-5 mrem (1.8E-7 mSv) EDE, or more than 100,000 times less than the federal and state standard of 10 mrem/yr, with which the PNNL Richland Campus is in compliance.

40 CFR 61 Subpart H↗

DOE OSTI2023

PNNL-Richland Campus Radionuclide Air Emissions Report for Calendar Year 2022

This report documents radionuclide air emissions that result in the 2022 highest effective dose equivalent (EDE) to an offsite member of the public, referred to as the maximally exposed individual (MEI). The report has been prepared in compliance with the Code of Federal Regulations, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, “Radiation Protection–Air Emissions.” The dose to the PNNL Richland Campus MEI from routine major and minor point source emissions in 2022 from PNNL Richland Campus sources is 2.1E-5 mrem (2.1E-7 mSv) EDE. The dose from all fugitive sources is 1.2E-6 mrem (1.2E-8 mSv) EDE. The dose from radon emissions is 9.2E-9 mrem (9.2E-11 mSv) EDE. No nonroutine emissions occurred in 2022. The total radiological dose to the MEI from all PNNL Richland Campus radionuclide emissions, including fugitive emissions and radon, is 2.3E-5 mrem (2.3E-7 mSv) EDE, or more than 100,000 times less than the federal and state standard of 10 mrem/yr, with which the PNNL Richland Campus is in compliance.

40 CFR 61 Subpart↗