Quantifying Greenhouse Gas Research Articles

A spatially explicit inventory scaling approach to estimate urban CO2 emissions

Appropriate techniques to quantify greenhouse gas emission reductions in cities over time are necessary to monitor the progress of these efforts and effectively inform continuing mitigation. We introduce a scaling factor (SF) method that combines aircraft measurements and dispersion modeling to estimate urban emissions and apply it to 9 nongrowing season research aircraft flights around New York City (NYC) in 2018–2020. This SF approach uses a weighting function to focus on an area of interest while still accounting for upwind emissions. We estimate carbon dioxide (CO2) emissions from NYC and the Greater New York Area (GNA) and compare to nested inversion analyses of the same data. The average calculated CO2 emission rates for NYC and the GNA, representative of daytime emissions for the flights, were (49 ± 16) kmol/s and (144 ± 44) kmol/s, respectively (uncertainties reported as ±1σ variability across the 9 flights). These emissions are within ∼15% of an inversion analysis and agree well with inventory estimates. By using an ensemble, we also investigate the variability introduced by several sources and find that day-to-day variability dominates the overall variability. This work investigates and demonstrates the capability of an SF method to quantify emissions specific to particular areas of interest.

Simulation of N2O emissions from greenhouse vegetable production under different management systems in North China

Quantifying greenhouse gas emissions from greenhouse vegetable production systems (GVPS) is helpful to direct carbon sequestration and greenhouse gas emissions reduction. The objectives of this study were to (i) evaluate the performance of the improved WHCNS-Veg model (soil Water Heat Carbon Nitrogen Simulation for Vegetable) in simulating nitrous oxide (N2O) emissions under different GVPS and (ii) analyze the impact of different management systems on N2O emissions from the GVPS. Greenhouse vegetable experiments were carried out under different management systems, including conventional (CON), integrated (INT) and organic (ORG), in Quzhou County, Hebei province from 2013 to 2015. Field observations of soil water content, soil nitrate concentration and N2O emissions were used to calibrate and validate the WHCNS-Veg model. The sensitivity analysis results showed that the effects of soil hydraulic parameters on N2O emissions were higher than those of N transformation and vegetable genetic parameters. The improved WHCNS-Veg model simulated soil water content, soil nitrate concentration and N2O emissions well under different GVPS. The average N2O emissions in the spring-summer season (16.3 kg N ha−1) were about 2.5 times higher than the autumn-winter season (6.4 kg N ha−1). Among the four seasons, the average N2O emissions of CON, ORG and INT were 13.5, 11.3 and 9.3 kg N ha−1, respectively, accounting for 1.4–1.7% of the total fertilizer input. The N2O emissions of the INT and ORG systems were 31.1% and 16.3% lower than the CON treatment, respectively. The results indicated that the improved WHCNS-Veg model can be used to simulate and analyze N2O emissions under different management systems and substituting organic manure for chemical fertilizer could effectively reduce the N2O emissions in the GVPS.

Implementación de la técnica de medición y primer registro de gases de efecto invernadero (CO2, CH4 y N2O) en la interfase sedimento-agua en el embalse Rincón del Bonete, Uruguay

This work represents the first report carried out in Uruguay on the implementation of the technique to quantify greenhouse gases (GHG) and their diffusive fluxes through the sediment-water interface. The study was carry out in the Rincón del Bonete reservoir, located on the Río Negro. The applied technique made it possible to determine the GHG (CH4, CO2 and N2O) concentrations in the sediments. The CO2 and CH4 were the gases with the highest concentration per m2 of sediment. Regarding its diffusive fluxes, CO2 (max. = 1.198 mg/m2/d) was higher than CH4 (max. = 0.194 mg/m2/d) and N2O (max. = 0.02 mg/m2/ d). Although the values ​​determined are low if compared to other systems, it would be necessary to deepen the temporal and spatial studies to better assess the magnitude of the GHG flows. Due to the increase in the intensity of human activities and the effects of climate change that would promote the increase and intensity of algal blooms, it expected that, after their decomposition, the release of GHG in the reservoir would increase in the future.

Use, calibration and verification of agroecological models for boreal environments: A review

AbstractPast assessments report negative impacts of the climate crisis in boreal areas; but milder and shorter winters and elevated atmospheric CO2may provide opportunities for agricultural productivity potentially playing a significant role in future food security. Arable cropping systems are expanding in boreal areas, but the regional mainstay will likely continue to be livestock production. Agroecological models can when appropriately calibrated and evaluated, facilitate improved productivity while minimising environmental impacts by identifying system interactions, and quantifying greenhouse gas emissions, soil carbon stocks and fertiliser use. While models designed for temperate and tropical zones abound, few are developed specifically for boreal zones, and there is uncertainty around the performance of existing models in boreal areas. We reviewed model performance across boreal environments and management systems. We identified a dearth of modelling studies in boreal regions, with the publication of three or less papers per year since the year 2000, constituting a significant research gap. Models IFSM and BASGRA_N performed best in grassland production, DNDC best in predicting soil N2O and NH3emissions. No model outperformed all others, strengthening the case for ensemble modelling. Existing agroecological models would be worthy of further evaluation, providing model improvements designed for boreal systems.

Sediment Disturbance Negatively Impacts Methanogen Abundance but Has Variable Effects on Total Methane Emissions.

Methane emissions from aquatic ecosystems are increasingly recognized as substantial, yet variable, contributions to global greenhouse gas emissions. This is in part due to the challenge of modeling biologic parameters that affect methane emissions from a wide range of sediments. For example, the impacts of fish bioturbation on methane emissions in the literature have been shown to result in a gradient of reduced to enhanced emissions from sediments. However, it is likely that variation in experimental fish density, and consequently the frequency of bioturbation by fish, impacts this outcome. To explore how the frequency of disturbance impacts the levels of methane emissions in our previous work we quantified greenhouse gas emissions in sediment microcosms treated with various frequencies of mechanical disturbance, analogous to different levels of activity in benthic feeding fish. Greenhouse gas emissions were largely driven by methane ebullition and were highest for the intermediate disturbance frequency (disturbance every 7 days). The lowest emissions were for the highest frequency treatment (3 days). This work investigated the corresponding impacts of disturbance treatments on the microbial communities associated with producing methane. In terms of total microbial community structure, no statistical difference was observed in the total community structure of any disturbance treatment (0, 3, 7, and 14 days) or sediment depth (1 and 3 cm) measured. Looking specifically at methanogenic Archaea however, a shift toward greater relative abundance of a putatively oxygen-tolerant methanogenic phylotype (ca. Methanothrix paradoxum) was observed for the highest frequency treatments and at depths impacted by disturbance (1 cm). Notably, quantitative analysis of ca. Methanothrix paradoxum demonstrated no change in abundance, suggesting disturbance negatively and preferentially impacted other methanogen populations, likely through oxygen exposure. This was further supported by a linear decrease in quantitative abundance of methanogens (assessed by qPCR of the mcrA gene), with increased disturbance frequency in bioturbated sediments (1 cm) as opposed to those below the zone of bioturbation (3 cm). However, total methane emissions were not simply a function of methanogen populations and were likely impacted by the residence time of methane in the lower frequency disturbance treatments. Low frequency mechanical disruption results in lower methane ebullition compared to higher frequency treatments, which in turn resulted in reduced overall methane release, likely through enhanced methanotrophic activities, though this could not be identified in this work. Overall, this work contributes to understanding how animal behavior may impact variation in greenhouse gas emissions and provides insight into how frequency of disturbance may impact emissions.

Homogeneous land-use sequences in heterogeneous small-scale systems of Central Kenya: Land-use categorization for enhanced greenhouse gas emission estimation

The current understanding of the link between land management practices and GHG (greenhouse gas) emissions is limited in the small-scale farm sector of sub-Sahara regions due to insufficient or fragmented land-use data. Land-use categories recognized in the national GHG inventories in Kenya are coarse. Therefore, they do not adequately account for the diversity in small-scale land uses. Characterization of land-use and knowledge of key drivers of land-use change is necessary to improve national GHG inventories in the SSA (Sub-Sahara Africa) region. We implemented a cross-sectional survey to characterize land-use and determine factors which influenced changes in land use within small-scale farms of Tharaka-Nithi County, Kenya. We sampled 300 farmers using multistage sampling and collected crop sequence recall data at plot level for three years (seven seasons). We grouped crop sequences into clusters using the ‘TraMineR’ R package. We derived four clusters including banana, tea, and declining fallows (cluster 1, 19.2% of plots), cereal-legume systems (cluster 2, 55.1%), fodder (cluster 3, 11.7%) and coffee (cluster 4, 14.0%). We observed higher N application rates in perennial cropping systems, than in annual crops, including cereal-legume systems. We observed that farmers in higher potential agro-ecological zones, male-managed farms, with higher per capita land area, higher remittances and higher total house-hold incomes, were associated with a higher propensity to adjust crop enterprises, leading to more unstable land-use sequences. Contrariwise, farmers with higher education, credit access, secure land tenure, increasing slope, good soil fertility, and longer farming experiences recorded a lower propensity to adjust their land uses, resulting in more stable crop sequences. Farmer socio-demographic characteristics influenced land-use change, which is directly linked with soil GHG emissions. Our findings propose the adoption of Tier II GHG quantification approaches which disaggregate between annual and perennial crop enterprises. GHG emissions are likely to be more generalizable in stable perennial crop systems than annual systems. Thus, better disaggregation of GHG sampling in annual crop systems is needed due to high diversity in crop and soil fertility management, and the dynamic nature of C and N cycling in these systems.

Predicting methane emissions from paddy rice soils under biochar and nitrogen addition using DNDC model

Methane (CH4) is a second largest contributor of global warming after carbon dioxide (CO2), and it is crucial to understand how management practices affect CH4 emissions. Among field crops, paddy rice alone has accounted for about 10–12% of the total CH4 emission in 2010. The process-based DeNitrification and DeComposition (DNDC) model can be applied to quantify greenhouse gas (GHG) emissions from agricultural soils. Capturing both the daily time-scale and cumulative growing season CH4 fluxes by DNDC may help to devise appealing mitigation approaches for better rice management. In this study, DNDC was calibrated with a parameter-adjustment approach under two treatments: 140 kg N ha−1 without biochar and 140 kg N ha−1 with 2% biochar. Simulation results show that the model predicted the daily CH4 fluxes in good agreement with measurements under both treatments. Next, DNDC was validated with the adjusted parameters against the remaining biochar and N treatments, and the model performed well in prediction of CH4 fluxes as indicated by several statistical indexes: RMSE ranged from 6.74 to 7.62 g CH4 ha−1d − 1, the d-index varied between 0.92 to 0.98, and MPD and nRMSE were at 10.94–17.43% and 17.54–24.52%, respectively. In terms of cumulative growing season CH4 efflux, DNDC under-simulated all treatments except the control. Further DNDC predicted above-ground dry weights and volumetric water contents in good agreement with the measurements. Moreover, model poorly predicted soil temperature, pH, and soil moisture content. The value of the d-index varied from 0.12 to 0.38 for both soil temperature and pH. Subsequently, DNDC successfully identified the significant impact of biochar on CH4 emission, and model error was strongly correlated with pH of soils with no biochar amendments. In conclusion, the DNDC model can capture the daily time-scale as well as annual-scale CH4 fluxes, though DNDC must be validated by intensive measurements of additional soil variables, including dissolved organic carbon (DOC) and microbial composition under different biochar types.

Travel behaviour and greenhouse gas emissions during the COVID-19 pandemic: A case study in a university setting

The year 2020 was characterized by a marked shift in daily travel patterns due to the COVID-19 pandemic. While we know that overall travel decreased, less is known about modal shift among those who continued to travel during the pandemic or about the impact of these travel-behaviour changes on transport-related greenhouse gas emissions. Focusing on a university setting and drawing from a travel survey conducted in Fall 2020 in Montreal, Canada (n = 3358), this study examines modal shifts and quantifies greenhouse gas emissions at three time periods in the year 2020: pre-pandemic, early pandemic, and later pandemic. The pandemic resulted in a sharp reduction in travel to campus. Among those who continued to travel to campus (n = 1580), car-to-final destination mode share almost tripled at the start of the pandemic. The largest modal shift seen was the transition from walking, cycling, and transit, to driving at the beginning of the pandemic. Reductions in overall travel resulted in lower overall transport-related greenhouse gas emissions. However, if modal changes persist once students, staff, and academics return to campus, the transport carbon footprint is projected to increase above pre-pandemic levels. These results highlight the importance of putting in place policies that support a return to sustainable modes as universities and businesses reopen for in-person activities.

Oportunidades de redução das emissões de GEE na indústria gráfica brasileira através de um plano de mitigação

Abstract The Graphics Industry has existed for many years and its operations include digital printing services, visual communication, packaging supplies and advertising materials, while being involved in the trade of goods and services worldwide. This unprecedented study presents the quantification of greenhouse gas (GHG) emissions from a printing industry in Brazil over the three years 2016, 2017 and 2018. From the results of these three years, the base year was defined as the reference for analyzing the results of a GHGs mitigation plan. The simulated Mitigation Plan foresees a potential reduction of up to 50.3 % of these emissions. The methodology follows the recommendations of the Intergovernmental Panel on Climate Change (IPCC). The work aims to encourage the study of opportunities for a low-carbon economy and production, to improve performance in good sustainability practices in the face of environmental demands to contain the intensification of the greenhouse effect and global warming.

Quantifying greenhouse gas abatement delivered by alternative computer operating system displacement strategies

End user computing generates 1% of global greenhouse gas emissions caused by production processes and subsequent electricity consumption during use. The concept of displacement has the potential to reduce this environmental impact by repurposing computers at the end of their perceived useful lifespan to extend longevity. Doing so removes the immediate requirement for new devices to be manufactured, therefore potentially slowing global demand and reducing embodied emissions proportionately. However, existing research implies that a combination of improving energy consumption efficiency experienced by new devices, plus ongoing inefficiency associated with aging devices, may be sufficient to counter the abatement gains achieved by displacement. Such energy efficiency gains are due to both continuing hardware and software innovation. As an example, recent research substantiates that alternative operating systems, such as Google Chrome OS, reduce electricity consumption when compared to other popular operating systems. As such, it is reasonable to suggest that repurposing legacy Microsoft Windows computing devices with a version of Chrome OS software will counter the new device efficiency theory and deliver abatement via the process of displacement. Consequently, the objective of this research is to test this hypothesis by quantifying greenhouse gas abatement values delivered by alternative computer operating system displacement strategies and compare the result to the impact of new device manufacture and use. This is achieved via a field experiment measuring the electricity consumption of two legacy notebooks operated in the workplace before and after repurposing occurs. To enable comparison with a new device strategy, two contemporary notebooks are also measured and the embodied carbon footprint contribution recorded. When compared, the results determine two key outcomes. Firstly, a 19% average electricity consumption reduction is experienced further to repurposing the legacy Windows devices with Chrome OS Flex, enabling the notebooks to exhibit energy efficiency equivalent to new devices. Secondly, the earliest point at which the legacy ongoing electricity consumption emissions and combined new device manufacturing emissions plus use phase emissions intersect, is during the 91st year of new ownership. Consequently, as almost a century must pass to compensate for manufacturing emissions, then displacement utilising alternative operating systems should be prioritised, where feasible, if global end user computing emissions are to be meaningfully addressed.

Combined Fertilization Could Increase Crop Productivity and Reduce Greenhouse Gas Intensity through Carbon Sequestration under Rice-Wheat Rotation

Quantifying greenhouse gas intensity (GHGI) and soil carbon sequestration is a method to assess the mitigation potential of agricultural activities. However, the effects of different fertilizer amendments on soil carbon sequestration and net GHGI in a rice-wheat cropping system are poorly understood. Here, fertilizer treatments including PK (P and K fertilizers); NPK (N, P and K fertilizers), NPK + OM (NPK plus manure), NPK + SR (NPK plus straw returning), and NPK + CR (NPK plus controlled-release fertilizer) with equal N input were conducted to gain insight into the change of soil organic carbon (SOC) derived from the net ecosystem carbon budget (NECB), net global warming potential (GWP), and GHGI under rice-wheat rotation. Results showed that compared with NPK treatment, NPK + OM significantly increased wheat yield and NPK + SR caused significant increase in rice yield. Meanwhile, NPK + SR and NPK + CR treatments reduced net GWP by 30.80% and 21.83%, GHGI by 36.84% and 28.07%, respectively, which suggested that improved grain production could be achieved without sacrificing the environment. With the greatest C sequestration, lowest GHGI, the NPK plus straw returning practices (NPK + SR) might be the best strategy to mitigate net GWP and improve grain yield and NUE in the current rice-wheat rotation system.

Case Study on Developing a Comprehensive Voluntary Environmental Performance and Process Standard for Alpine Resorts Using Four Business Management Principles

In 2018, Jackson Hole Mountain Resort (JHMR) in Teton Village, WY, USA, discontinued its International Standards Organization 14001 environmental management system. JHMR needed a replacement voluntary environmental program (VEP) that would empower resort employees to directly mitigate climate change, reduce waste and pollution, minimize water use, and restore biodiversity, along with improving building, education, and purchasing. I developed the Model for Alpine Resort Sustainability (MARS) based on 2 research objectives of improving existing industry-specific VEPs and empowering employees to directly mitigate resort environmental impacts through their work. MARS involves 4 business management principles: (1) use ski industry-specific criteria to drive accountability comprehensively across 25 resort departments; (2) quantify greenhouse gas emissions, using both absolute and intensity or normalized bases, and apply quantification to solid waste production and water consumption; (3) employ modern management techniques and software to focus on action over documentation; and (4) strategically align with the core business objective of alpine resorts to provide profitable outdoor recreation by decreasing costs and increasing revenues. MARS provides the most comprehensive, research-based accounting to date of alpine resort environmental impacts and mitigation indicators. MARS could be applied to larger resorts receptive to change.

Методология оценки выбросов парниковых газов от цехов судостроительного предприятия

The article provides a general overview of the methodological approach to quantifying greenhouse gas emissions from any workshop of a shipbuilding enterprise, in general. The approach consists in collecting information on the economic and economic activities of the enterprise and products, the production of which is accompanied by the emission of greenhouse gases, the collection of parametric indicators that determine the specific value of greenhouse gas emissions per unit of activities performed or products manufactured.

Assessment of the applicability of methodological guidelines and guidelines for the quantitative determination of greenhouse gas emissions

The article deals with the problem of climate change. The aim of the study is to analyze and improve methodological recommendations for calculating greenhouse gas emissions. The urgency of reducing the volume of greenhouse gas emissions has been substantiated. Statistical data of emissions volumes are analyzed, the reason for the growth of emissions and the main contributors are determined. The main gases that give the greenhouse effect are identified, and their brief characteristics are given. The need to improve the monitoring and reporting system of greenhouse gas emissions at the global level has been substantiated. The goal of a perfect system for accounting and reporting of greenhouse gas emissions is to timely obtain relevant data for the systematic reduction of greenhouse gas emissions. The methodological tools for quantifying greenhouse gas emissions, approved by the Ministry of Natural Resources and Environment of Russia, are analyzed from the point of view of their applicability by organizations. Measures for their improvement are proposed, based on the international experience of building guidelines for the IPCC greenhouse gas inventory. The results obtained may be of interest to energy companies when developing corporate guidelines for quantifying greenhouse gas emissions.

Cross-continental importance of CH4 emissions from dry inland-waters

Despite substantial advances in quantifying greenhouse gas (GHG) emissions from dry inland waters, existing estimates mainly consist of carbon dioxide (CO2) emissions. However, methane (CH4) may also be relevant due to its higher Global Warming Potential (GWP). We report CH4 emissions from dry inland water sediments to i) provide a cross-continental estimate of such emissions for different types of aquatic systems (i.e., lakes, ponds, reservoirs, and streams) and climate zones (i.e., tropical, continental, and temperate); and ii) determine the environmental factors that control these emissions. CH4 emissions from dry inland waters were consistently higher than emissions observed in adjacent uphill soils, across climate zones and in all aquatic systems except for streams. However, the CH4 contribution (normalized to CO2 equivalents; CO2-eq) to the total GHG emissions of dry inland waters was similar for all types of aquatic systems and varied from 10 to 21%. Although we discuss multiple controlling factors, dry inland water CH4 emissions were most strongly related to sediment organic matter content and moisture. Summing CO2 and CH4 emissions revealed a cross-continental average emission of 9.6 ± 17.4 g CO2-eq m−2 d−1 from dry inland waters. We argue that increasing droughts likely expand the worldwide surface area of atmosphere-exposed aquatic sediments, thereby increasing global dry inland water CH4 emissions. Hence, CH4 cannot be ignored if we want to fully understand the carbon (C) cycle of dry sediments.

Quantifying greenhouse gas emissions from decommissioned oil and gas steel structures: Can current policy meet NetZero goals?

To help achieve global aims to reach Net Zero greenhouse gas (GHG) emissions, a clearly structured method for calculating emissions from decommissioning oil and gas structures is required. In order to understand the GHG consequences of recycling secondary steel from decommissioned structures, this paper presents a new methodology in decommissioning, based on the UN’s International Resource Panel (IRP)’s Value Retention method that combines life cycle assessment principles, the waste hierarchy and the circular economy to holistically calculate GHG emissions produced as a consequence of manufacturing primary and secondary steel, manufacturing a product from this steel and the associated transport emissions. The Value Retention Model presented here combines the concept of material value and product value to obtain realistic GHG emission calculations based on end-of-use and end-of-life scenarios, including recycling and reuse options. The results show that reusing a steel jacket structure in situ will retain 55,040 tCO2(eq) in GHG emissions, not including removal operations or transport emissions. New regulation is urgently required to update the current outdated emissions calculation guidelines, enable the provision of both realistic baseline emissions figures and to provide a mechanism for reporting ‘after operations’ figures.

Single photon Lidar gas imagers for practical and widespread continuous methane monitoring

The accurate and comprehensive identification and quantification of greenhouse gas (GHG) emissions is an essential part of the management and mitigation of climate change. We are developing a novel remote gas imaging sensor for the detection, visualisation, and quantification of methane emissions. The sensor uses a new technique we call Tunable Diode Lidar (TDLidar) which combines aspects of Tunable Diode Laser Absorption Spectroscopy (TDLAS) with Differential Absorption Lidar (DIAL) and Time Correlated Single Photon Counting (TCSPC) to enable remote spectroscopy and ranging with low power semiconductor diode lasers. Our first TDLidar methane sensors use diode lasers with wavelengths around the CH4 absorption line at 1.6509 μm and Peltier-cooled Single Photon Avalanche Diode (SPAD) detectors in a Random Modulation Continuous Wave (RM-CW) Lidar system. Here we characterise our TDLidar methane sensor performance with calibrated gas cells and controlled gas release trials and we demonstrate quantification of leak rates as low as 0.012 g/s and detection at distances over 90 m. The accuracy, speed, and practicality of the sensor, combined with an expectation of low-cost in volume, offers the potential that these sensors can be effectively applied for widespread continuous and autonomous monitoring of industrial methane emissions.

Checking the progress of using the static chamber method for the measurement of greenhouse gases in Latin America

Manual static chamber is one of the most widespread methods for the quantification of greenhouse gases (GHGs) emissions from agricultural systems. But there are concerns about the reliability of measurements and a necessity to assess the static chambers used in the studies performed in the countries of Latin America. Thus, this study aims to investigate the quality of the characteristics from the static chamber methodology, the confidence level of the GHG measurements, and recommend what should be improved. We conducted a systematic review of databases to identify peer-reviewed articles that used the static chamber method in Latin America. A total of 90 articles were analyzed and separated according to the publication year (2000-2008, 2009-2015, 2016-2020). We evaluated eight design and deployment chamber characteristics. The depth of base insertion and type of storage vial received the lowest scores, and the number of samples received the highest score. The description and reporting of the methodological procedures in the studies should be improved. The percentage of articles with high and medium confidence levels increased within the time, and the number of articles with low and very low confidence levels reduced. Scientists/Researchers should continue to follow the protocols, especially the most updated ones.

Spatial Variability of Soil Organic Carbon and Total Nitrogen in Desert Steppes of China’s Hexi Corridor

Stock estimates are critical to quantifying carbon and nitrogen sequestration, quantifying greenhouse gas emissions, and understanding key biogeochemical processes (i.e., soil carbon and nutrient cycling). Many studies have assessed soil organic matter and nutrients in different ecosystems. However, the spatial distribution of carbon and nitrogen and the key influencing factors in arid desert steppe remain unclear. Here, we investigated the soil organic carbon (SOC) and soil total nitrogen (STN) to a depth of 100 cm at 126 sites in a desert steppe in northwestern China.SOCandSTNcontents decreased with increasing depth; the highest averageSOCandSTNcontents were 12.70 and 0.65 g kg−1in the surface 5 cm, and the lowest were from 80 to 100 cm (4.49 and 0.16 g kg−1, respectively).SOCdensity (SOCD) andSTNdensity (STND) to a depth of 100 cm averaged 8.94 and 0.45 kg m−2, respectively. The top 1 m of the soils stored approximately 1,041 TgSOCand 52 TgSTNin the study area. Geostatistical analysis showed strong and moderate spatial autocorrelation forSOCDin different soil layers, but the autocorrelation forSTNDgradually weakened with increasing depth.SOCDandSTNDdecreased from southwest to northeast in the study area, along an elevation gradient. Both were significantly positively correlated with topographic variables, precipitation, and the normalized-difference vegetation index, but negatively correlated with temperature and aridity. More than 40% of theSOCDandSTNDspatial variation was explained by elevation, which was the dominant factor. The data and high-resolution maps from this study will support future soil carbon and nitrogen analyses.

Detection, Identification, and Quantification of SF6 Point-Source Emissions Using Hyper-Cam LW Airborne Platform

Detection, identification, and quantification of greenhouse gases is essential to ensure compliance with regulatory guidelines and mitigate damage associated with anthropogenic climate change. Passive infrared hyperspectral imaging technology is among the solutions that can detect, identify and quantify multiple greenhouse gases simultaneously. The Telops Hyper-Cam Airborne Platform is an established system for aerial thermal infrared hyperspectral measurements for gas survey applications. In support of the Hypercam, is developing a suite of hyperspectral imaging data processing algorithms that allow for gas detection, identification, and quantification in real-time. In the Fall of 2020, the Hyper-Cam-LW Airborne platform was flown above a validated SF6 gas release system to collect hyperspectral data for gas quantification analysis. This measurement campaign was performed to document performance of the Hyper-Cam gas quantification capabilities against known quantities of released gas.