Quantifying Local to Regional Emissions of Methane Using UAV-based Atmospheric Concentration Measurements

The uncertainty in methane (CH4) emissions that go into the global methane cycle is significant, and accurate atmospheric measurements and quantification of CH4 is of vital importance to reduce this uncertainty. This thesis explores the use of an unmanned aerial vehicle (UAV) in combination with a high accuracy methane sampling tool to measure and quantify CH4 emissions. First, a suitable instrument capable of accurate measurements of greenhouse gases (GHGs) is developed and tested. Second, using this newly developed instrumentation, a technique for quantifying methane emissions from a point source is developed. Finally, this instrumentation and technique is used to sample and quantify the regional CH4 emissions from a large industrial coal mining region. The results coming from this thesis has helped progress the use of mobile unmanned aerial vehicles for atmospheric trace gas research, and shows that quantification techniques using UAVs can be a powerful tool to make accurate measurements of CH4 and other trace gases, and further help in lowering the overall uncertainty on the atmospheric carbon cycle

Effectiveness of a resistance training program on physical function, muscle strength, and body composition in community-dwelling older adults receiving home care: A cluster-randomized controlled trial

Background: Aging is associated with reduced muscle mass and strength leading to impaired physical function. Resistance training programs incorporated into older adults’ real-life settings may have the potential to counteract these changes. We evaluated the effectiveness of 8 months resistance training using easily available, low cost equipment compared to physical activity counselling on physical function, muscle strength, and body composition in community-dwelling older adults receiving home care. Methods: This open label, two-armed, parallel group, cluster randomized trial recruited older adults above 70 years (median age 86.0 (Interquartile range 80–90) years) receiving home care. Participants were randomized at cluster level to the resistance training group (RTG) or the control group (CG). The RTG trained twice a week while the CG were informed about the national recommendations for physical activity and received a motivational talk every 6th week. Outcomes were assessed at participant level at baseline, after four, and 8 months and included tests of physical function (chair rise, 8 ft-up-and-go, preferred- and maximal gait speed, and stair climb), maximal strength, rate of force development, and body composition. Results: Twelve clusters were allocated to RTG (7 clusters, 60 participants) or CG (5 clusters, 44 participants). The number of participants analyzed was 56–64 (6–7 clusters) in RTG and 20–42 (5 clusters) in CG. After 8 months, multilevel linear mixed models showed that RTG improved in all tests of physical function and maximal leg strength (9–24%, p = 0.01–0.03) compared to CG. No effects were seen for rate of force development or body composition. Conclusion: This study show that resistance training using easily available, low cost equipment is more effective than physical activity counselling for improving physical function and maximal strength in community-dwelling older adults receiving home care.publishedVersio

Quantifying methane emissions from coal mining ventilation shafts using an unmanned aerial vehicle (UAV)-based active AirCore system

A large quantity of CH4 is emitted to the atmosphere via ventilation shafts of underground coal mines. According to the European Pollutant Release and Transfer Register (E-PRTR), hard coal mines in the Upper Silesia Coal Basin (USCB) are a strong contributor (447 kt CH4 in 2017) to the annual European CH4 emissions. However, atmospheric emissions of CH4 from coal mines are poorly characterized, as they are dispersed over large areas. As part of the Carbon Dioxide and CH4 Mission (CoMet) pre-campaign, a study of the USCB's regional CH4 emissions took place in August 2017. We flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 mole fractions downwind of a single coal mining ventilation shaft. Besides CH4, we also measured CO2, CO, atmospheric temperature, pressure, and relative humidity. Wind-speed and wind-direction measurements were made using a lightweight balloon-borne radiosonde. Fifteen UAV flights were performed flying perpendicular to the wind direction at several altitude levels, to effectively build a ‘curtain’ of CH4 mole fractions in a two-dimensional plane at a distance between 150 and 350 m downwind of a single ventilation shaft. Furthermore, we have developed an inverse Gaussian approach for quantifying CH4 emissions from a point source using the UAV-based observations, and have applied it as well as the mass balance approach to both simulated data and actual flight data to quantify CH4 emissions. The simulated data experiments revealed the importance of having multiple transects at different altitudes, appropriate vertical spacing between the individual transects, and proper distance between the center height of the plume and the center flight transect. They also showed that the inverse Gaussian approach performed better than the mass balance approach. Our estimate of the CH4 emission rates from the sampled shaft ranges from 0.5 to 14.5 kt/year using a mass balance approach, and between 1.1 and 9.0 kt/year using an inverse Gaussian method. The average difference between the mass balance and the inverse Gaussian approach was 2.3 kt/year. Based on the observed correlation between CO2 and CH4 (R-squared > 0.69), the CO2 emissions from the shaft were estimated to be between 0.3 and 9.8 kt/year. This study demonstrates that the UAV-based active AirCore system provides an effective way of quantifying coal mining shaft emissions of CH4 and CO2

Evaluating the use of an Unmanned Aerial Vehicle (UAV)-based active AirCore system to quantify methane emissions from dairy cows

Enteric fermentation and manure methane emissions from livestock are major anthropogenic greenhouse gas emissions. In general, direct measurements of farm-scale methane emissions are scarce due to the source complexity and the limitations of existing atmospheric sampling methods. Using an innovative UAV-based active AirCore system, we have performed accurate atmospheric measurements of CH4 mole fractions downwind of a dairy cow farm in the Netherlands on four individual days during the period from March 2017 to March 2019. The total CH4 emission rates from the farm were determined using the UAV-based mass balance approach to be 1.1-2.4 g/s. After subtracting estimated emission factors of manure onsite, we derived the enteric emission factors to be 0.20-0.51 kgCH4/AU/d (1 AU = 500 kg animal weight) of dairy cows. We show that the uncertainties of the estimates were dominated by the variabilities in the wind speed and the angle between the wind and the flight transect. Furthermore, nonsimultaneous sampling in the vertical direction of the plume is one of the main limiting factors to achieving accurate estimate of the CH4 emissions from the farm. In addition, a N2O tracer release experiment at the farm was performed when both a UAV and a mobile van were present to simultaneously sample the N2O tracer and the CH4 plumes from the farm, improving the source quantification with a correction factor of 1.04 and 1.22 for the inverse Gaussian approach and for the mass balance approach, respectively. The UAV-based active AirCore system is capable of providing useful estimates of CH4 emissions from dairy cow farms. The uncertainties of the estimates can be improved when combined with accurate measurements of local wind speed and direction or when combined with a tracer approach

Local-to-regional methane emissions from the Upper Silesian Coal Basin (USCB) quantified using UAV-based atmospheric measurements

Coal mining accounts for ~12% of the total anthropogenic methane (CH4) emissions worldwide. The Upper Silesian Coal Basin (USCB), Poland, where large quantities of CH4 are emitted to the atmosphere via ventilation shafts of underground hard coal (anthracite) mines, is one of the hot spots of methane emissions in Europe. However, coal bed CH4 emissions into the atmosphere are poorly characterized. As part of the carbon dioxide and CH4 mission 1.0 (CoMet 1.0) that took place in May-June 2018, we flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 and CO2 mole fractions 150-300m downwind of five individual ventilation shafts in the USCB. In addition, we also measured δ13C-CH4, δ2H-CH4, ambient temperature, pressure, relative humidity, surface wind speed, and surface wind direction. We used 34 UAV flights and two different approaches (inverse Gaussian approach and mass balance approach) to quantify the emissions from individual shafts. The quantified emissions were compared to both annual and hourly inventory data and were used to derive the estimates of CH4 emissions in the USCB. We found a high correlation (R2Combining double low line0.7-0.9) between the quantified and hourly inventory data-based shaft-averaged CH4 emissions, which in principle would allow regional estimates of CH4 emissions to be derived by upscaling individual hourly inventory data of all shafts. Currently, such inventory data is available only for the five shafts we quantified. As an alternative, we have developed three upscaling approaches, i.e., by scaling the European Pollutant Release and Transfer Register (E-PRTR) annual inventory, the quantified shaft-averaged emission rate, and the shaft-averaged emission rate, which are derived from the hourly emission inventory. These estimates are in the range of 256-383ktCH4yr-1 for the inverse Gaussian (IG) approach and 228-339ktCH4yr-1 for the mass balance (MB) approach. We have also estimated the total CO2 emissions from coal mining ventilation shafts based on the observed ratio of CH4/CO2 and found that the estimated regional CO2 emissions are not a major source of CO2 in the USCB. This study shows that the UAV-based active AirCore system can be a useful tool to quantify local to regional point source methane emissions.</p

Local-to-regional methane emissions from the Upper Silesian Coal Basin (USCB) quantified using UAV-based atmospheric measurements

Coal mining accounts for ~12% of the total anthropogenic methane (CH4) emissions worldwide. The Upper Silesian Coal Basin (USCB), Poland, where large quantities of CH4 are emitted to the atmosphere via ventilation shafts of underground hard coal (anthracite) mines, is one of the hot spots of methane emissions in Europe. However, coal bed CH4 emissions into the atmosphere are poorly characterized. As part of the carbon dioxide and CH4 mission 1.0 (CoMet 1.0) that took place in May-June 2018, we flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 and CO2 mole fractions 150-300m downwind of five individual ventilation shafts in the USCB. In addition, we also measured δ13C-CH4, δ2H-CH4, ambient temperature, pressure, relative humidity, surface wind speed, and surface wind direction. We used 34 UAV flights and two different approaches (inverse Gaussian approach and mass balance approach) to quantify the emissions from individual shafts. The quantified emissions were compared to both annual and hourly inventory data and were used to derive the estimates of CH4 emissions in the USCB. We found a high correlation (R2Combining double low line0.7-0.9) between the quantified and hourly inventory data-based shaft-averaged CH4 emissions, which in principle would allow regional estimates of CH4 emissions to be derived by upscaling individual hourly inventory data of all shafts. Currently, such inventory data is available only for the five shafts we quantified. As an alternative, we have developed three upscaling approaches, i.e., by scaling the European Pollutant Release and Transfer Register (E-PRTR) annual inventory, the quantified shaft-averaged emission rate, and the shaft-averaged emission rate, which are derived from the hourly emission inventory. These estimates are in the range of 256-383ktCH4yr-1 for the inverse Gaussian (IG) approach and 228-339ktCH4yr-1 for the mass balance (MB) approach. We have also estimated the total CO2 emissions from coal mining ventilation shafts based on the observed ratio of CH4/CO2 and found that the estimated regional CO2 emissions are not a major source of CO2 in the USCB. This study shows that the UAV-based active AirCore system can be a useful tool to quantify local to regional point source methane emissions

Local to regional methane emissions from the Upper Silesia Coal Basin (USCB) quantified using UAV-based atmospheric measurements

Coal mining accounts for ~ 12 % of the total anthropogenic methane emissions worldwide. The Upper Silesian Coal Basin, Poland, where large quantities of CH4 are emitted to the atmosphere via ventilation shafts of underground hard coal (anthracite) mines, is one of the hot spots of methane emissions in Europe. However, coalbed CH4 emissions into the atmosphere are poorly characterized. As part of the Carbon Dioxide and CH4 mission 1.0 (CoMet 1.0) that took place in May – June 2018, we flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 and CO2 mole fractions 150–300 m downwind of five individual ventilation shafts in the USCB. In addition, we also measured δ13C-CH4, δ2H-CH4, ambient temperature, pressure, relative humidity, surface wind speeds and directions. We have used 34 UAV flights and two different approaches (inverse Gaussian approach and mass balance approach) to quantify the emissions from individual shafts. The quantified emissions were compared to both annual and hourly inventory data, and were used to derive the estimates of CH4 emissions in the USCB. We found a high correlation (R2 = 0.7 – 0.9) between the quantified and hourly inventory data-based shaft-averaged CH4 emissions, which in principle would allow regional estimates of CH4 emissions to be derived by upscaling individual hourly inventory data of all shafts. Currently, such inventory data is available only for the five shafts we quantified though. As an alternative, we have developed three upscaling approaches, i.e., by scaling the E-PRTR annual inventory, the quantified shaft-averaged emission rate, and the shaft-averaged emission rate that are derived from the hourly emission inventory. These estimates are in the range of 325 – 447 kt CH4/year for the inverse Gaussian approach and 268 – 347 kt CH4/year for the mass balance approach, respectively. This study shows that the UAV-based active AirCore system can be a useful tool to quantify local to regional point source methane emissions

Risk assessment on use of Lactobacillus rhamnosus (LGG) as an ingredient in infant formula and baby foods (II)

publishedVersio

Risk assessment on use of Lactobacillus rhamnosus (LGG) as an ingredient in infant formula and baby foods (II)

Source at https://vkm.no/On 10. March 2006 , The Norwegian Food Safety Authority (Mattilsynet) decided that, on the basis of VKM’s previous risk assessment (2005), Nutramigen 1 with Lactobacillus rhamnosus GG (LGG) could not be marketed in Norway as medical foods for infants (0-4 months). In addition, The Norwegian Food Safety Authority (Mattilsynet) decided (08. November 2006) to withdraw permission for marketing ofNutramigen 2 with LGG, which is a milk supplement for infants aged between 4 and 6 months, with cow’s milk and soy protein allergy. On 13. December 2006, Mead Johnson Nutritionals appealed against this decision from The Norwegian Food SafetyAuthority (Mattilsynet). The Norwegian Food Safety Authority forwarded the appeal from the companies, asked the VKM Panel on biological hazards and the VKM Panel on nutrition, dietetic products, novel food and allergy, for a new risk assessment including the new data provided in the appeal.Basert på VKMs tidligere risikovurdering fra 2005, bestemte Mattilsynet 10. mars 2006 atNutramigen 1 med LGG ikke kunne markedsføres som næringsmiddel til spesielle medisinske formål (0-4 måneder) i Norge. I tillegg trakk Mattilsynet tilbake tillatelsen (08. november, 2006) til å markedsføre Nutramigen 2 med LGG, som er en melkeerstatning for spedbarn mellom fire og seks måneder som er allergiske mot kumelk og soyaproteiner. Den 13. desember 2006 Mead Johnson Nutritionals på vedtaket fra Mattilsynet. Mattilsynet videresendte klagen fra selskapene og ba VKMs faggrupper for hygiene og smittestoffer samt ernæring, dietetiske produkter, ny mat og allergi om å foreta en ny risikovurdering basert på nye data som er lagt frem i forbindelse med klagen

Local to regional methane emissions from the Upper Silesia Coal Basin (USCB) quantified using UAV-based atmospheric measurements

Coal mining accounts for ~ 12 % of the total anthropogenic methane emissions worldwide. The Upper Silesian Coal Basin, Poland, where large quantities of CH4 are emitted to the atmosphere via ventilation shafts of underground hard coal (anthracite) mines, is one of the hot spots of methane emissions in Europe. However, coalbed CH4 emissions into the atmosphere are poorly characterized. As part of the Carbon Dioxide and CH4 mission 1.0 (CoMet 1.0) that took place in May – June 2018, we flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 and CO2 mole fractions 150–300 m downwind of five individual ventilation shafts in the USCB. In addition, we also measured δ13C-CH4, δ2H-CH4, ambient temperature, pressure, relative humidity, surface wind speeds and directions. We have used 34 UAV flights and two different approaches (inverse Gaussian approach and mass balance approach) to quantify the emissions from individual shafts. The quantified emissions were compared to both annual and hourly inventory data, and were used to derive the estimates of CH4 emissions in the USCB. We found a high correlation (R2 = 0.7 – 0.9) between the quantified and hourly inventory data-based shaft-averaged CH4 emissions, which in principle would allow regional estimates of CH4 emissions to be derived by upscaling individual hourly inventory data of all shafts. Currently, such inventory data is available only for the five shafts we quantified though. As an alternative, we have developed three upscaling approaches, i.e., by scaling the E-PRTR annual inventory, the quantified shaft-averaged emission rate, and the shaft-averaged emission rate that are derived from the hourly emission inventory. These estimates are in the range of 325 – 447 kt CH4/year for the inverse Gaussian approach and 268 – 347 kt CH4/year for the mass balance approach, respectively. This study shows that the UAV-based active AirCore system can be a useful tool to quantify local to regional point source methane emissions