Fant 9896 publikasjoner. Viser side 122 av 396:
2015
Large stocks of soil carbon (C) and nitrogen (N) in northern permafrost soils are vulnerable to remobilization under climate change. However, there are large uncertainties in present-day greenhouse gas (GHG) budgets. We compare bottom-up (data-driven upscaling and process-based models) and top-down (atmospheric inversion models) budgets of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) as well as lateral fluxes of C and N across the region over 2000–2020. Bottom-up approaches estimate higher land-to-atmosphere fluxes for all GHGs. Both bottom-up and top-down approaches show a sink of CO2 in natural ecosystems (bottom-up: −29 (−709, 455), top-down: −587 (−862, −312) Tg CO2-C yr−1) and sources of CH4 (bottom-up: 38 (22, 53), top-down: 15 (11, 18) Tg CH4-C yr−1) and N2O (bottom-up: 0.7 (0.1, 1.3), top-down: 0.09 (−0.19, 0.37) Tg N2O-N yr−1). The combined global warming potential of all three gases (GWP-100) cannot be distinguished from neutral. Over shorter timescales (GWP-20), the region is a net GHG source because CH4 dominates the total forcing. The net CO2 sink in Boreal forests and wetlands is largely offset by fires and inland water CO2 emissions as well as CH4 emissions from wetlands and inland waters, with a smaller contribution from N2O emissions. Priorities for future research include the representation of inland waters in process-based models and the compilation of process-model ensembles for CH4 and N2O. Discrepancies between bottom-up and top-down methods call for analyses of how prior flux ensembles impact inversion budgets, more and well-distributed in situ GHG measurements and improved resolution in upscaling techniques.
American Geophysical Union (AGU)
2024
2010
2014
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2018
2012
2012
Performance assessment of a low-cost PM2.5 Sensor for a near four-month period in Oslo, Norway
The very low-cost Nova particulate matter (PM) sensor SDS011 has recently drawn attention for its use for measuring PM mass concentration, which is frequently used as an indicator of air quality. However, this sensor has not been thoroughly evaluated in real-world conditions and its data quality is not well documented. In this study, three SDS011 sensors were evaluated by co-locating them at an official, air quality monitoring station equipped with reference-equivalent instrumentation in Oslo, Norway. The sensors’ measurement results for PM2.5 were compared with data generated from the air quality monitoring station over almost a four-month period. Five performance aspects of the sensors were examined: operational data coverage, linearity of response and accuracy, inter-sensor variability, dependence on relative humidity (RH) and temperature (T), and potential improvement of sensor accuracy, by data calibration using a machine-learning method. The results of the study are: (i) the three sensors provide quite similar results, with inter-sensor correlations exhibiting R values higher than 0.97; (ii) all three sensors demonstrate quite high linearity against officially measured concentrations of PM2.5, with R2 values ranging from 0.55 to 0.71; (iii) high RH (over 80%) negatively affected the sensor response; (iv) data calibration using only the RH and T recorded directly at the three sensors increased the R2 value from 0.71 to 0.80, 068 to 0.79, and 0.55 to 0.76. The results demonstrate the general feasibility of using these low cost SDS011 sensors for indicative PM2.5 monitoring under certain environmental conditions. Within these constraints, they further indicate that there is potential for deploying large networks of such devices, due to the sensors’ relative accuracy, size and cost. This opens up a wide variety of applications, such as high-resolution air quality mapping and personalized air quality information services. However, it should be noted that the sensors exhibit often very high relative errors for hourly values and that there is a high potential of abusing these types of sensors if they are applied outside the manufacturer-provided specifications particularly regarding relative humidity. Furthermore, our analysis covers only a relatively short time period and it is desirable to carry out longer-term studies covering a wider range of meteorological conditions
MDPI
2019
2007
2006
Perfluorooctane sulfonate (PFOS) and related compounds in a Norwegian Arctic marine food chain. NILU PP
2005
2005
2005
Perfluorocyclobutane (PFC-318, c-C4F8) in the global atmosphere
We reconstruct atmospheric abundances of the potent greenhouse gas c-C4F8 (perfluorocyclobutane, perfluorocarbon PFC-318) from measurements of in situ, archived, firn, and aircraft air samples with precisions of ∼1 %–2 % reported on the SIO-14 gravimetric calibration scale. Combined with inverse methods, we found near-zero atmospheric abundances from the early 1900s to the early 1960s, after which they rose sharply, reaching 1.66 ppt (parts per trillion dry-air mole fraction) in 2017. Global c-C4F8 emissions rose from near zero in the 1960s to 1.2±0.1 (1σ) Gg yr−1 in the late 1970s to late 1980s, then declined to 0.77±0.03 Gg yr−1 in the mid-1990s to early 2000s, followed by a rise since the early 2000s to 2.20±0.05 Gg yr−1 in 2017. These emissions are significantly larger than inventory-based emission estimates. Estimated emissions from eastern Asia rose from 0.36 Gg yr−1 in 2010 to 0.73 Gg yr−1 in 2016 and 2017, 31 % of global emissions, mostly from eastern China. We estimate emissions of 0.14 Gg yr−1 from northern and central India in 2016 and find evidence for significant emissions from Russia. In contrast, recent emissions from northwestern Europe and Australia are estimated to be small (≤1 % each). We suggest that emissions from China, India, and Russia are likely related to production of polytetrafluoroethylene (PTFE, “Teflon”) and other fluoropolymers and fluorochemicals that are based on the pyrolysis of hydrochlorofluorocarbon HCFC-22 (CHClF2) in which c-C4F8 is a known by-product. The semiconductor sector, where c-C4F8 is used, is estimated to be a small source, at least in South Korea, Japan, Taiwan, and Europe. Without an obvious correlation with population density, incineration of waste-containing fluoropolymers is probably a minor source, and we find no evidence of emissions from electrolytic production of aluminum in Australia. While many possible emissive uses of c-C4F8 are known and though we cannot categorically exclude unknown sources, the start of significant emissions may well be related to the advent of commercial PTFE production in 1947. Process controls or abatement to reduce the c-C4F8 by-product were probably not in place in the early decades, explaining the increase in emissions in the 1960s and 1970s. With the advent of by-product reporting requirements to the United Nations Framework Convention on Climate Change (UNFCCC) in the 1990s, concern about climate change and product stewardship, abatement, and perhaps the collection of c-C4F8 by-product for use in the semiconductor industry where it can be easily abated, it is conceivable that emissions in developed countries were stabilized and then reduced, explaining the observed emission reduction in the 1980s and 1990s. Concurrently, production of PTFE in China began to increase rapidly. Without emission reduction requirements, it is plausible that global emissions today are dominated by China and other developing countries. We predict that c-C4F8 emissions will continue to rise and that c-C4F8 will become the second most important emitted PFC in terms of CO2-equivalent emissions within a year or two. The 2017 radiative forcing of c-C4F8 (0.52 mW m−2) is small but emissions of c-C4F8 and other PFCs, due to their very long atmospheric lifetimes, essentially permanently alter Earth's radiative budget and should be reduced. Significant emissions inferred outside of the investigated regions clearly show that observational capabilities and reporting requirements need to be improved to understand global and country-scale emissions of PFCs and other synthetic greenhouse gases and ozone-depleting substances.
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