Greenhouse Gas Measurements Research Articles

The Apples and Oranges of Measuring Greenhouse Gases in Croplands

CSA NewsVolume 68, Issue 6 p. 3-7 FEATURES The Apples and Oranges of Measuring Greenhouse Gases in Croplands Kristen Coyne, Kristen CoyneSearch for more papers by this author Kristen Coyne, Kristen CoyneSearch for more papers by this author First published: 29 May 2023 https://doi.org/10.1002/csan.21050Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Volume68, Issue6June 2023Pages 3-7 RelatedInformation

Development of a Module for the Detection and Measurement of Greenhouse Gases

Development of a Module for the Detection and Measurement of Greenhouse Gases

Mandatory Reporting of Emissions to Achieve Net-Zero Health Care

(N Engl J Med. 2022;387:2469–2476) Threats to human health from climate instability include food and water shortages, heat, modified disease-vector ranges and active seasons, wildfires, and severe weather-related events, all of which have the potential to disrupt health care delivery as well. With awareness of the contribution of greenhouse gasses and toxic emissions by the health care sector—~8.5% of emissions in the United States and 5% globally—many health care systems are prioritizing initiatives to achieve “net zero.” This refers to individual institution-led structures that support offsetting the release of greenhouse gas emissions by providing the means to neutralize their effect on the atmosphere. While many government organizations and consulting bodies to health care call for pledges to reduce greenhouse gas emissions, voluntary initiatives will fall short of net-zero health care goals. A consensus is growing for the need to develop a standardized metric for reporting, promoting accountability, quantifying progress, and recognizing best practices. It is recommended that all health care delivery organizations (HCOs)—all inpatient, outpatient, residential, and support services—be required to report and measure greenhouse gas emissions, in step with the climate goals of other leading organizations to achieve net-zero emissions over the coming decades.

CO2 and CH4 fluxes from forest soil in the northern Da Xing’anling Mountains in Northeast China during the freezing and thawing periods of near-surface soil in 2018–2019

ABSTRACT Under a warming climate, the studies on effects of seasonal freeze–thaw cycles on soil respiration are key to understanding the soil carbon cycles and ecosystem responses and resilience at mid- and high latitudes. In this study, the effluxes of soil surface CO2 and absorption rates of CH4 were measured in the Xing'an larch (Larix gmelinii) forest in the northern Da Xing’anling Mountains, Northeast China using an automatic multichannel soil greenhouse gas measurement system (dynamic gas chamber method) during the periods of October–November 2018 and April–May 2019. The results showed that during the freezing period of near-surface soil, CO2 and CH4 fluxes significantly declined, approaching zero, at the end of November. During the thawing period of near-surface soil, CO2 and CH4 fluxes from surface soil fluctuated markedly at first and then rose rapidly. The respective Q10 values of 3.86 and 4.89 during the freezing and thawing periods of near-surface soil, respectively, indicate the important role of ground freeze–thaw cycles in the modifications of CO2 and CH4 fluxes. The results of this study could help assess the stability of the soil carbon pool and carbon flux strength in taiga-forested permafrost regions in the northern Da Xing’anling Mountains, Northeast China.

Greenhouse gas emissions from hydroelectric reservoirs: mechanistic understanding of influencing factors and future prospect

Rising need for various renewable and non-renewable energy resources became vital for developing countries to meet their rapid economic growth under an exponentially growing population scenario. The primary goal of COP-26 for climate change mitigation is to reduce greenhouse gas (GHG) emissions from different sectors. Because of their significant contribution to global warming, GHG emissions from hydroelectric reservoirs have been a contentious topic of discussion since the pre-industrial age. However, the exact methodology for quantification of GHG and important parameters affecting emission rate is difficult due to limited equipment facilities, techniques for GHG measurement, uncertainties in GHG emissions rate, insufficient GHG database, and significant spatio-temporal variability of emission in the global reservoirs. This paper discusses the current scenario of GHG emissions from renewable energy, with a focus on hydroelectric reservoirs, methodological know-how, the interrelationship between parameters impacting GHG emissions, and mitigation techniques. Aside from that, significant methods and approaches for predicting GHG emissions from hydroelectric reservoirs, accounting for GHG emissions, life cycle assessment, uncertainty sources, and knowledge gaps, have been thoroughly discussed.

Greenhouse gas emissions from ant nests: A systematic review

Abstract Ant nests are ecologically important emission sources of CO2, CH4, and N2O. An updated review of the progress in studying greenhouse gas (GHG) flux from ant nests could provide a more comprehensive understanding of their role in this context. We evaluate the progress in assessing GHG flux assessment through a systematic review and identify factors responsible for higher GHG emissions from ant nests. The specific goals were to conduct a bibliographic analysis of the frequency and geographical distribution of scientific works addressing this topic, reported species, and methodologies; to relate the mean GHG flux to species‐specific characteristics of ant nests; and to identify patterns and biases responsible for reported higher GHG levels. More data is needed on the species and habitats studied. The most frequently examined gas was CO2, and the closed chamber system was the most used method, with a wide variation in chamber size and material. No relation was found between CO2 emissions and species‐specific characteristics, which can be explained by the fact that these data show a high variability, probably due to the abiotic factors in each study, different measurement methods, and their respective configurations. Our study underlines the need to standardise GHG measurement methods to allow for reliable comparisons between ant species and habitats. Furthermore, it signals the need to investigate more information to build appropriate global GHG emissions models. This progress will only be possible through collaborative studies by increasing interaction among researchers through projects on a continental or global scale.

Optical Methods of Methane Detection.

Methane is the most frequently analyzed gas with different concentrations ranging from single ppm or ppb to 100%. There are a wide range of applications for gas sensors including urban uses, industrial uses, rural measurements, and environment monitoring. The most important applications include the measurement of anthropogenic greenhouse gases in the atmosphere and methane leak detection. In this review, we discuss common optical methods used for detecting methane such as non-dispersive infrared (NIR) technology, direct tunable diode spectroscopy (TDLS), cavity ring-down spectroscopy (CRDS), cavity-enhanced absorption spectroscopy (CEAS), lidar techniques, and laser photoacoustic spectroscopy. We also present our own designs of laser methane analyzers for various applications (DIAL, TDLS, NIR).

Large numerical aperture off-axis reflective telescope design with a freeform mirror based on aperture expansion strategy.

Currently, the emission of greenhouse gases is one of humanity's leading threats. To accurately and efficiently measure greenhouse gas levels in the atmosphere, we must develop imaging spectrometer systems with larger numerical apertures (NAs). However, designing a telescope with a large NA is difficult in this system. This paper presents a design strategy for aperture expansion to create a freeform telescope with a large NA. We compared different off-axis reflective telescopes and chose the Korsch structure, which has obvious advantages because of its wide field of view (FoV), large NA, and low stray light. Moreover, based on the influence of the position of the freeform surface in the aberration correction, we propose to use a single freeform surface to reduce the cost and increase manufacturability. A freeform telescope with an effective focal length of 84mm, a large NA of 0.25, and a wide FoV of 20° is successfully designed. The modulation transfer function of the system is better than 0.62, the maximum distortion is controlled to be less than 0.486%, and the incident angle of the beam on the image plane is less than 10°. The design result shows that the instrument has wide FoV, large NA, low stray light, and high performance. At the same time, the design strategy in this paper provides an effective method for the telescope design of the imaging spectrometer with a large NA.

Standoff detection of backscattered light based on tunable diode laser absorption spectroscopy

Standoff detection is of great significance in greenhouse gas measurement monitoring, early warning security and leak detection. Variations in topographic characteristics and distances will undoubtedly increase background noise. However, the effect of real-time changes in the angle between the sensor and the target on dynamic detection is rarely studied. In this article, a portable laser sensor is developed to retrieve gas concentration of CH4 by collecting the backscattered light from a distant non-cooperative target. The experimental results show that “2f/1f” based on wavelength-locked wavelength modulation technique can effectively suppress the background interference caused by a change in the detection angle. Increasing the sampling frequency does not achieve denoising for static detection but can lead to significant noise reduction for dynamic detection. For a modulation frequency of 4 k Hz, the mean standard deviation of the gas concentration is improved to 42.8 % and 7.04 % of that at 1 k Hz and 250 Hz, respectively. Kalman filtering can significantly improve the denoising effect for dynamic detection. The background concentration perturbation is reduced by a factor of 4.19 ∼ 4.71 after applying Kalman filtering. Combined with Kalman filtering, the minimum detection limit for Allan variance prediction can reach 20.5 ppb@ (0.15 sec) at a modulation frequency of 4 k Hz.

High greenhouse gas emissions after grassland renewal on bog peat soil

Drained agriculturally used peatlands are hotspots for greenhouse gas (GHG) emissions, especially carbon dioxide (CO2) and nitrous oxide (N2O). To reduce GHG emissions and simultaneously maintain intensive grassland use, raising water levels by subsurface irrigation (SI) is controversially discussed. Both, intensive grassland use and installations of SI may require grassland renewal. We investigated an experimental intervention site (INT) (SI target water levels: -0.30 m) and a deeply drained reference site (REF), both intensive grassland on deep bog peat. After installation of the SI system, a mechanical grassland renewal took place at INT. At both sites, CO2 (eddy covariance), N2O and methane (manual closed chamber technique) were measured. Additionally, soil water was analyzed for nitrogen species. Here, we report on the initial year of GHG measurements including grassland renewal and rising water levels. Overall, GHG emissions were strongly influenced by grassland renewal at INT. Despite progressively rising water levels, soil moisture in the upper centimeters was low and thus grass growth was slow, resulting in an almost complete loss of harvest. This resulted in a net ecosystem carbon balance (NECB) of 4.64 ± 1.03 t C ha−1 containing only 0.57 ± 0.09 t C ha−1 harvest at INT, while NECB at REF was 6.08 ± 1.74 t C ha−1 including harvest from five grass cuts. Methane fluxes were negligible at both sites. Nitrous oxide emissions dominated the GHG balance at INT. With 144.5 ± 45.5 kg N2O–N ha–1 a–1, they were much higher than at REF (3.9 ± 3.1 kg N2O–N ha–1 a–1) and any other values published so far. Peak fluxes occurred when nitrate concentrations in soil water were extremely high, soil moisture was increased, and vegetation development was struggling. This study highlights the risk of grassland renewals on peat soils regarding yield losses as well as high GHG emissions.

Modelling CH4 emission from rice ecosystem: A comparison between existing empirical models

Rice is a staple food for more than three billion people and accounts for up to 11% of the global methane (CH4) emissions from anthropogenic sources. With increasing populations, particularly in less developed countries where rice is a major cereal crop, production continues to increase to meet demand. Implementing site-specific mitigation measures to reduce greenhouse gas emissions from rice is important to minimise climate change. Measuring greenhouse gases is costly and time-consuming; therefore, many farmers, supply chains, and scientists rely on greenhouse gas accounting tools or internationally acceptable methodologies (e.g., Intergovernmental Panel on Climate Change) to estimate emissions and explore mitigation options. In this paper, existing empirical models that are widely used have been evaluated against measured CH4 emission data. CH4 emission data and management information were collected from 70 peer-reviewed scientific papers. Model input variables such as soil organic carbon (SOC), pH, water management during crop season and pre-season, and organic amendment application were collected and used for estimation of CH4 emission. The performance of the models was evaluated by comparing the predicted emission values against measured emissions with the result showing that the models capture the impact of different management on emissions, but either under- or overestimate the emission value, and therefore are unable to capture the magnitude of emissions. Estimated emission values are much lower than observed for most of the rice-producing countries, with R correlation coefficient values varying from −0.49 to 0.87 across the models. In conclusion, current models are adequate for predicting emission trends and the directional effects of management, but are not adequate for estimating the magnitude of emissions. The existing models do not consider key site-specific variables such as soil texture, planting method, cultivar type, or growing season, which all influence emissions, and thus, the models lack sensitivity to key site variables to reliably predict emissions.

Impactos Ambientais dos Teleacoplamentos do Sistema de Consumo Urbano de Alimentos Orgânicos

Abstract The environmental impacts of the food system, especially the distances covered, are not clear to the final consumer. The aim was to evaluate and calculate the urban telecoupling and the environmental impacts and calculate the energy consumption and the environmental emissions of the organic foods. Through the calculation of quantities, distances, losses and the analysis of telecouplings, we measured Greenhouse Gas (GG) emissions, as well as the energy and carbon footprints of organic foods traded at the CEASA/PR, Curitiba. Emissions had a low environmental impact because the largest quantities of transported organics originate from production sites located within the greater Curitiba region. The study showed a consumption pattern supporting food produced in regions adjacent to the trading center in safe and healthy and safe way, which may be associated with a greater awareness of the environmental impacts resulting from the distances covered.

Centennial Assessment of Greenhouse Gases Emissions of Young and Old Hydroelectric Reservoir in Mediterranean Mainland

The quantities of emitted greenhouse gases (GHG) from hydroelectric reservoirs around the world, especially in warm latitudes, have tarnished the green credentials of hydroelectric energy. The accurate measurement and evaluation of the emitted GHG, which is a critical element in climate change policy, present a significant challenge. Many works have been focused on GHG emissions assessment from reservoirs around the world, but there are no available data concerning reservoirs in Mediterranean countries. In this study, emitted GHG from a young and an old in line water reservoirs, located in Mediterranean mainland, were collected using a “static floating chamber”. Methane and carbon dioxide concentrations were measured and their specific emission rates were calculated. The data were used for the development of a mathematical prediction model, proposed for GHG emission assessment. Statistical correlation of GHG emissions and water physicochemical characteristics led to the interpretation of the biochemical processes taking place into the reservoirs. Furthermore, the impact of reservoir’s morphology on GHG emissions was recorded, enhancing its importance on decision making for "green" energy investments. The results of this study indicate that artificial reservoirs in Mediterranean mainland generally have lower GHG emissions than those located in tropical and subtropical climatic zones and higher than those in continental subarctic zones and approach the highest values of CO2 emissions and the mean CH4 emissions recorded in continental climatic zones. The applied methodology provides a comprehensive tool for the long term (centennial) emissions assessment and the assessment of reservoirs impacts on the environment.

Greenhouse gas emission analysis and measurement for urban rail transit: A review of research progress and prospects

Greenhouse gas emission analysis and measurement for urban rail transit: A review of research progress and prospects

Effect of deficit irrigation practices on greenhouse gas emissions in drip irrigation

One of the most important sources of greenhouse gas emissions resulting from human activities is agricultural activities. Many factors such as tillage, fertilizer use, irrigation, soil properties, etc. can affect greenhouse gas emissions. However, their effects on greenhouse gas emissions are still among the important research topics today. In this study, the effects of different irrigation levels on CO2, CH4, N2O emission in soil were investigated in silage maize irrigated with drip irrigation system. The study was carried out for two years, 4 different irrigation levels (S1:100%, S2:70%, S3:40%, S4:0) were applied. ADA 9516 silage mazie variety was used as the test plant. Static cylinders were used in each plot for greenhouse gas measurements. Greenhouse gas Cylinders (cells) consisting of 2 pieces made of PVC placed on trial plots were used in the research. Gas samples were analyzed with gas chromatograph (Agilent GC 7890A) and gas emission values of CO2, CH4 and N2O were calculated. In the study, the highest cumulative CO2 emission values by years were obtained for S1 with 1470.4 and 1129.6 kg ha−1, respectively (p<0.01) and the CO2 emission values measured after irrigation were found to be higher than the pre-irrigation emission values. The highest cumulative N2O emission values were obtained for S1 with 0.54 and 0.50 kg ha−1, respectively, over the years (p<0.001), N2O emission values were higher after irrigation. In CH4 analyzes, it was determined that the trial area soil behaved as a CH4 sink. The highest cumulative CH4 uptake in both years of the study occurred in S1 with -1.79 and -3.17 kg ha−1, respectively (p<0.01). Similarity was observed in CH4 flux values before and after irrigation. In the research, it was determined that irrigation practices increased greenhouse gas emission statistically. On the other hand, it has been determined that producing with irrigation using less agricultural land can help reduce greenhouse gas emissions.

Pivoting to suppliers’ emissions

Apple declared 2 years ago that it had achieved carbon neutrality—a balance between carbon emitted and carbon absorbed—across its corporate operations. The claim appeared to position the tech giant as a leader among the many companies hoping to make the same announcement by 2050 as signatories to the Paris climate accords. Most companies realize, however, that corporate operations are only one source of their carbon emissions. Every Apple iPhone, iPad, Apple Watch, and Apple TV—indeed, every product the company sells—has a carbon footprint that is not figured into its claims regarding in-house activities. This leaves a lot out. By some estimates , as much as 80% of emissions associated with a company’s products, a measurement known as product carbon footprint (PCF), occur elsewhere along its supply chain. Industry efforts to measure greenhouse gas emissions date back to 1998, when a standard known as the Greenhouse Gas Protocol was introduced by

Critical method needs in measuring greenhouse gas fluxes

Reaching climate goals depends on appropriate and accurate methods to quantify greenhouse gas (GHG) fluxes and to verify that efforts to mitigate GHG emissions are effective. We here highlight critical advantages, limitations, and needs regarding GHG flux measurement methods, identified from an analysis of >13 500 scientific publications regarding three long-lived GHGs, carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). While existing methods are well-suited for assessing atmospheric changes and local fluxes, they are expensive and have limited accessibility. Further, we are typically forced to choose between methods for very local GHG sources and sinks and their regulation (m2-scaled measurements), or methods for aggregated net fluxes at >ha or km2 scales measurements. The results highlight the key need of accessible and affordable GHG flux measurement methods for the many flux types not quantifiable from fossil fuel use, to better verify inventories and mitigation efforts for transparency and accountability under the Paris agreement. The situation also calls for novel methods, capable of quantifying large scale GHG flux patterns while simultaneously distinguishing local source and sink dynamics and reveal flux regulation, representing key knowledge for quantitative GHG flux modeling. Possible strategies to address the identified GHG flux measurement method needs are discussed. The analysis also generated indications of how GHG flux measurements have been distributed geographically and across flux types, which are reported.

The Space Carbon Observatory (SCARBO) concept: assessment of XCO2 and XCH4 retrieval performance

Abstract. Several single-platform satellite missions have been designed during the past decades in order to retrieve the atmospheric concentrations of anthropogenic greenhouse gases (GHG), initiating worldwide efforts towards better monitoring of their sources and sinks. To set up a future operational system for anthropogenic GHG emission monitoring, both revisit frequency and spatial resolution need to be improved. The Space Carbon Observatory (SCARBO) project aims at significantly increasing the revisit frequency of spaceborne GHG measurements, while reaching state-of-the-art precision requirements, by implementing a concept of small satellite constellation. It would accommodate a miniaturised GHG sensor named NanoCarb coupled with an aerosol instrument, the multi-angle polarimeter SPEXone. More specifically, the NanoCarb sensor is a static Fabry–Pérot imaging interferometer with a 2.3×2.3 km2 spatial resolution and 200 km swath. It samples a truncated interferogram at optical path differences (OPDs) optimally sensitive to all the geophysical parameters necessary to retrieve column-averaged dry-air mole fractions of CO2 and CH4 (hereafter XCO2 and XCH4). In this work, we present the Level 2 performance assessment of the concept proposed in the SCARBO project. We perform inverse radiative transfer to retrieve XCO2 and XCH4 directly from synthetic NanoCarb truncated interferograms and provide their systematic and random errors, column vertical sensitivities, and degrees of freedom as a function of five scattering-error-critical atmospheric and observational parameters. We show that NanoCarb XCO2 and XCH4 systematic retrieval errors can be greatly reduced with SPEXone posterior outputs used as improved prior aerosol constraints. For two-thirds of the soundings, located at the centre of the 200 km NanoCarb swath, XCO2 and XCH4 random errors span 0.5–1 ppm and 4–6 ppb, respectively, compliant with their respective 1 ppm and 6 ppb precision objectives. Finally, these Level 2 performance results are parameterised as a function of the explored scattering-error-critical atmospheric and observational parameters in order to time-efficiently compute extensive L2 error maps for future CO2 and CH4 flux estimation performance studies.

Measuring Greenhouse Gas Emissions from Point Sources with Mobile Systems

The traditional least squares method for the retrieval of CO2 emissions from CO2 emission sources is affected by the nonlinear characteristics of the Gaussian plume model, which leads to the optimal estimation of CO2 emissions easily falling into local minima. In this study, ACA–IPFM (ant colony algorithm and interior point penalty function) is proposed to remedy the shortcomings of the traditional least squares method, which makes full use of the global search property of the ant colony algorithm and the local exact search capability of the interior point penalty function to make the optimal estimation of CO2 emissions closer to the global optimum. We evaluate the errors of several parameters that are most likely to affect the accuracy of the CO2 emission retrieval and analyze these errors jointly. These parameters include wind speed measurement error, wind direction measurement error, CO2 concentration measurement error, and the number of CO2 concentration measurements. When the wind speed error is less than 20%, the inverse error of CO2 concentration emission is less than 1% and the uncertainty is less than 3%, when the wind direction error is less than 55 degrees, the inverse error is less than 1% and the uncertainty is less than 3%, when the CO2 concentration measurement error is less than 10%, the inverse error is less than 1% and the uncertainty is less than 3.3%, and when the measurement quantity is higher than 60, the inverse error is less than 1% and the uncertainty is less than 3%. In addition, we simulate the concentration observations on different paths under the same conditions, and invert the CO2 emissions based on these simulated values. Through the retrieval results, we evaluate the errors caused by different paths of measurements, and have demonstrated that different paths are affected by different emission sources to different degrees, resulting in different inversion accuracies for different paths under the same conditions in the end, which can provide some reference for the actual measurement route planning of the mobile system. Combined with the characteristics of the agility of the mobile system, ACA–IPFM can extend the monitoring of CO2 emissions to a wider area.

Air quality observations onboard commercial and targeted Zeppelin flights in Germany – a platform for high-resolution trace-gas and aerosol measurements within the planetary boundary layer

Abstract. A Zeppelin airship was used as a platform for in situ measurements of greenhouse gases and short-lived air pollutants within the planetary boundary layer (PBL) in Germany. A novel quantum cascade laser-based multi-compound gas analyzer (MIRO Analytical AG) was deployed to simultaneously measure in situ concentrations of greenhouse gases (CO2, N2O, H2O, and CH4) and air pollutants (CO, NO, NO2, O3, SO2, and NH3) with high precision at a measurement rate of 1 Hz. These measurements were complemented by electrochemical sensors for NO, NO2, Ox (NO2 + O3), and CO, an optical particle counter, temperature, humidity, altitude, and position monitoring. Instruments were operated remotely without the need for on-site interactions. Three 2-week campaigns were conducted in 2020 comprising commercial passenger as well as targeted flights over multiple German cities including Cologne, Mönchengladbach, Düsseldorf, Aachen, Frankfurt, but also over industrial areas and highways. Vertical profiles of trace gases were obtained during the airship landing and take-off. Diurnal variability of the Zeppelin vertical profiles was compared to measurements from ground-based monitoring stations with a focus on nitrogen oxides and ozone. We find that their variability can be explained by the increasing nocturnal boundary layer height from early morning towards midday, an increase in emissions during rush hour traffic, and the rapid photochemical activity midday. Higher altitude (250–450 m) NOx to CO ratios are further compared to the 2015 EDGAR emission inventory to find that pollutant concentrations are influenced by transportation and residential emissions as well as manufacturing industries and construction activity. Finally, we report NOx and CO concentrations from one plume transect originating from a coal power plant and compare it to the EURopean Air pollution Dispersion-Inverse Modell (EURAD-IM) model to find agreement within 15 %. However, due to the increased contribution of solar and wind energy and the impact of lockdown measures the power plant was operating at max. 50 % capacity; therefore, possible overestimation of emissions by the model cannot be excluded.