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The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm retrieves vertical dust concentration profiles from cloud-free Infrared Atmospheric Sounding Interferometer (IASI) thermal infrared (TIR) radiances using Rodgers' optimal estimation method (OEM). We describe the new version 4.1 and evaluation results. Main differences with respect to previous versions are the Levenberg–Marquardt modification of the OEM, the use of the logarithm of the concentration in the retrieval and the use of Radiative Transfer for TOVS (RTTOV) for in-line radiative transfer calculations. The dust aerosol concentrations are retrieved in seven 1 km thick layers centered at 0.5 to 6.5 km. A global data set of the daily dust distribution was generated with MAPIR v4.1 covering September 2007 to June 2018, with further extensions planned every 6 months. The post-retrieval quality filters reject about 16 % of the retrievals, a huge improvement with respect to the previous versions in which up to 40 % of the retrievals were of bad quality. The median difference between the observed and fitted spectra of the good-quality retrievals is 0.32 K, with lower values over oceans. The information content of the retrieved profiles shows a dependence on the total aerosol load due to the assumption of a lognormal state vector. The median degrees of freedom in dusty scenes (min 10 µm AOD of 0.5) is 1.4. An evaluation of the aerosol optical depth (AOD) obtained from the integrated MAPIR v4.1 profiles was performed against 72 AErosol RObotic NETwork (AERONET) stations. The MAPIR AOD correlates well with the ground-based data, with a mean correlation coefficient of 0.66 and values as high as 0.88. Overall, there is a mean AOD (550 nm) positive bias of only 0.04 with respect to AERONET, which is an extremely good result. The previous versions of MAPIR were known to largely overestimate AOD (about 0.28 for v3). A second evaluation exercise was performed comparing the mean aerosol layer altitude from MAPIR with the mean dust altitude from Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP). A small underestimation was found, with a mean difference of about 350 m (standard deviation of about 1 km) with respect to the CALIOP cumulative extinction altitude, which is again considered very good as the vertical resolution of MAPIR is 1 km. In the comparisons against AERONET and CALIOP, a dependence of MAPIR on the quality of the temperature profiles used in the retrieval is observed. Finally, a qualitative comparison of dust aerosol concentration profiles was done against lidar measurements from two ground-based stations (M'Bour and Al Dhaid) and from the Cloud–Aerosol Transport System (CATS) instrument on board the International Space Station (ISS). MAPIR v4.1 showed the ability to detect dust plumes at the same time and with a similar extent as the lidar instruments. This new MAPIR version shows a great improvement of the accuracy of the aerosol profile retrievals with respect to previous versions, especially so for the integrated AOD. It now offers a unique 3-D dust data set, which can be used to gain more insight into the transport and emission processes of mineral dust aerosols.
2019
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.
2019
Source apportionment of circum-Arctic atmospheric black carbon from isotopes and modeling
Black carbon (BC) contributes to Arctic climate warming, yet source attributions are inaccurate due to lacking observational constraints and uncertainties in emission inventories. Year-round, isotope-constrained observations reveal strong seasonal variations in BC sources with a consistent and synchronous pattern at all Arctic sites. These sources were dominated by emissions from fossil fuel combustion in the winter and by biomass burning in the summer. The annual mean source of BC to the circum-Arctic was 39 ± 10% from biomass burning. Comparison of transport-model predictions with the observations showed good agreement for BC concentrations, with larger discrepancies for (fossil/biomass burning) sources. The accuracy of simulated BC concentration, but not of origin, points to misallocations of emissions in the emission inventories. The consistency in seasonal source contributions of BC throughout the Arctic provides strong justification for targeted emission reductions to limit the impact of BC on climate warming in the Arctic and beyond.
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Assessment of transboundary pollution by toxic substances: Heavy metals and POPs
Meteorological Synthesizing Centre ‐ East
2019
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Diurnal cycle of iodine, bromine, and mercury concentrations in Svalbard surface snow
Sunlit snow is highly photochemically active and plays a key role in the exchange of gas phase species between the cryosphere and the atmosphere. Here, we investigate the behaviour of two selected species in surface snow: mercury (Hg) and iodine (I). Hg can deposit year-round and accumulate in the snowpack. However, photo-induced re-emission of gas phase Hg from the surface has been widely reported. Iodine is active in atmospheric new particle formation, especially in the marine boundary layer, and in the destruction of atmospheric ozone. It can also undergo photochemical re-emission. Although previous studies indicate possible post-depositional processes, little is known about the diurnal behaviour of these two species and their interaction in surface snow. The mechanisms are still poorly constrained, and no field experiments have been performed in different seasons to investigate the magnitude of re-emission processes Three sampling campaigns conducted at an hourly resolution for 3 d each were carried out near Ny-Ålesund (Svalbard) to study the behaviour of mercury and iodine in surface snow under different sunlight and environmental conditions (24 h darkness, 24 h sunlight and day–night cycles). Our results indicate a different behaviour of mercury and iodine in surface snow during the different campaigns. The day–night experiments demonstrate the existence of a diurnal cycle in surface snow for Hg and iodine, indicating that these species are indeed influenced by the daily solar radiation cycle. Differently, bromine did not show any diurnal cycle. The diurnal cycle also disappeared for Hg and iodine during the 24 h sunlight period and during 24 h darkness experiments supporting the idea of the occurrence (absence) of a continuous recycling or exchange at the snow–air interface. These results demonstrate that this surface snow recycling is seasonally dependent, through sunlight. They also highlight the non-negligible role that snowpack emissions have on ambient air concentrations and potentially on iodine-induced atmospheric nucleation processes.
2019
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
2019
<i>Background</i> - Concerns have been raised that extensive use of personal care products that contain endocrine disrupting compounds increase the risk of hormone sensitive cancers.<p> <p><i>Objective</i> - To assess the effect of skincare product use on the risk of pre- and postmenopausal breast cancer, estrogen receptor positive (ER+) and negative (ER-) breast cancer and cancer of the endometrium.<p> <p><i>Methods</i> - We used data from 106,978 participants in the population-based Norwegian Women and Cancer cohort. Participants were categorized into non-, light, moderate, frequent and heavy users of skincare products based on self-reported use of hand and facial cream and body lotion. Cancer incidence information from the Cancer Registry of Norway was linked to individual data through the unique identity number of Norwegian citizens. Multivariable Cox proportional hazard regression was used to assess the effect of skincare product use on the risk of cancer of the breast and endometrium. We used multiple imputation by chained equations to evaluate the effect of missing data on observed associations.<p> <p><i>Results</i> - We found no associations between use of skincare products and incidence of premenopausal breast cancer (frequent/heavy versus non−/light use: hazard ratio [HR] =1.10, 95% confidence interval [CI]: 0.92–1.32), postmenopausal breast cancer (heavy versus light use: HR = 0.87, 95% CI: 0.65–1.18, frequent versus light use: HR = 0.97, 95% CI: 0.88, 1.07) or endometrial cancer (frequent/heavy versus non−/light use: HR = 0.97, 95% CI: 0.79–1.20). Use of skincare products did not increase the risk of ER+ or ER- breast cancer and there was no difference in effect across ER status (0.58 ≤ <sub>pheterogeneity</sub> ≤ 0.99). The magnitude and direction of the effect estimates based on complete case analyses and multiple imputation were similar.<p> <p><i>Conclusion</i> Heavy use of skincare products, i.e. creaming the body up to two times per day during mid-life, did not increase the risk of cancer of the breast or endometrium.
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