Eutrophication events are frequent in Inner Danish waters and critical loads are exceeded for much of the Danish sensitive terrestrial ecosystems. The Danish air quality monitoring program combines ...measurements and model calculations to benefit from the complementarities in data from these two sources. Measurements describe actual status, seasonal variation, and temporal trends. Model calculations extrapolate the results to the entire country and determine depositions to specific ecosystems. Measurements in 2016 show annual depositions between 7.5 and 11 kg N/ha to terrestrial ecosystems, and a load to marine waters of 5.3 kg N/ha. The deposition on Danish marine waters in 2016 was calculated to be 73,000 tons N with an average deposition of 6.9 kg N/ha. For terrestrial areas, the deposition was calculated to be 57,000 tons N with an average deposition of 13 kg N/ha. This is above critical loads for sensitive ecosystems. Long-term trends show a 35% decrease since 1990 in measured annual nitrogen deposition. At two out of four stations in nature areas, measured ammonia levels exceeded critical levels for lichens and mosses. Conclusions: Nitrogen loads and levels to Danish nature is decreasing, but critical loads and levels are still exceeded for sensitive ecosystems. Combining measurements and model calculations is a strong tool in monitoring.
A parameterization of the temporal variation of ammonia (NH3) emission into the atmosphere is proposed. The parameterization relies on several simple submodels reflecting emission from stores and ...barns, agricultural practice in application of manure, and emission from grown crops. Some of the submodels depend on a simple crop growth model, which again depends on temperature variations throughout the year. The parameterization reflects the differences in agricultural practices, differences in the climate due to latitude/longitude, and differences in meteorological conditions between years. Measured as well as modeled meteorology can be applied by the parameterization, which is developed for use down to single farm level as well as in large‐scale physical/statistical Eulerian and Lagrangian air pollution models. The parameterization is based on simple principles and is applied for northwestern Europe. The simple principles ensure that the parameterization may be adapted to other climatic conditions. The proposed parameterization is considered as a large improvement compared to previous simpler models with fixed seasonal variation.
Allergic diseases are prevalent in the working population, and work-related airborne pollen exposure might be substantial, especially among outdoor workers, resulting in work-exacerbated effects. ...Seasonal exposure to pollen may induce a priming effect on the allergic bronchial response resulting in exaggerated effects at the end of the natural pollen season. This was previously observed among people with asthma but may also be of importance for persons with allergic rhinitis. In this study, we examined the effect of seasonal priming on bronchial responsiveness among young adults with allergic rhinitis and no or mild asthma. In addition, we explored the association between the baseline characteristics of participants and the severity of bronchoconstriction. Finally, we evaluated the application of a novel non-linear regression model to the log-dose-response curves.
In a crossover design, 36 participants underwent specific inhalation challenges (SICs) with either grass or birch allergen outside and at the end of the pollen season. The differences in bronchial response were evaluated by comparing the dose-response profiles and PD
estimates derived by applying a non-linear regression model.
The results showed that 12 of the 19 grass pollen-exposed participants had a lower PD
at the end of the season compared with the outside season. For birch, this was true for nine out of the 17 participants. However, no statistically significant effects of the seasonal pollen exposure were found on neither the shape nor the magnitude of the modeled dose-response curves for either birch allergen,
= 0.77, or grass allergen,
= 0.45. The model depicted a good fit for the data. Among the baseline characteristics, only the size of the skin prick test for grass allergen was associated with PD
.
This study does not support a priming effect of pollen exposure on the bronchial response from the natural seasonal exposure levels of grass or birch allergens among young adults with allergic rhinitis.
In aerobiological studies it is often necessary to compare concentration data recorded with different models of sampling instrument. Sampler efficiency typically varies from device to device, and ...depends on the target aerosol and local atmospheric conditions. To account for these differences inter-sampler correction factors may be applied, however for many pollen samplers and pollen taxa such correction factors do not exist and cannot be derived from existing published work.
In this study, the relative efficiencies of the Burkard 7-Day Recording Volumetric Spore Trap, the Sampling Technologies Rotorod Model 20, and the Burkard Personal Volumetric Air Sampler were evaluated for Urticaceae and Poaceae pollen under field conditions. The influence of wind speed and relative humidity on these efficiency relationships was also assessed. Data for the two pollen taxa were collected during 2010 and 2011-2012, respectively.
The three devices were found to record significantly different concentrations for both pollen taxa, with the exception of the 7-Day and Rotorod samplers for Poaceae pollen. Under the range of conditions present during the study, wind speed was found to only have a significant impact on inter-sampler relationships involving the vertically-orientated Burkard Personal sampler, while no interaction between relative efficiency and relative humidity was observed.
Data collected with the three models of sampler should only be compared once the appropriate correction has been made, with wind speed taken into account where appropriate.
Ambient particulate air pollution assessed as outdoor concentrations of particulate matter < or = 2.5 microm in diameter (PM(2.5)) has been associated with an increased cancer risk. However, outdoor ...PM(2.5) concentrations may not be the best measure of the individual particle exposure that is a sum of many sources besides outdoor particle levels, e.g., environmental tobacco smoke and cooking. We measured personal PM(2.5) and black smoke exposure in 50 students four times over 1 year and analyzed for biomarkers of different types of DNA damages. Ambient PM(2.5) concentrations were also measured. Exposure was measured for 48 h, after which blood samples were collected and analyzed for DNA damage in lymphocytes in terms of 7-hydro-8-oxo-2'-deoxyguanosine (8-oxodG), strand breaks, endonuclease III- and fapyguanine glycosylase-sensitive sites, and polyaromatic hydrocarbon adducts. Twenty-four-h urine collections were analyzed for 8-oxodG and 1-hydroxypyrene. Personal PM(2.5) exposure was found to be a predictor of 8-oxodG in lymphocyte DNA with an 11% increase in 8-oxodG/10 microg/m(3) increase in personal PM(2.5) exposure (P = 0.007). No other associations between exposure markers and biomarkers could be distinguished. The genotype of glutathione S-transferase M1 (GSTM1), T1 (GSTT1), and P1 (GSTP1) and NADPH:quinone reductase was also determined, but there were no effects of genotype on DNA polyaromatic hydrocarbon adducts or oxidative damage. The results suggest that moderate exposure to concentrations of PM can induce oxidative DNA damage and that personal PM(2.5) exposure is more important in this aspect than is ambient PM(2.5) background concentration.
Epidemiological studies have found negative associations between human health and particulate matter in urban air. In most studies outdoor monitoring of urban background has been used to assess ...exposure. In a field study, personal exposure as well as bedroom, front door and background concentrations of PM(2.5), black smoke (BS), and nitrogen dioxide (NO(2)) were measured during 2-day periods in 30 subjects (20-33 years old) living and studying in central parts of Copenhagen. The measurements were repeated in the four seasons. Information on indoor exposure sources such as environmental tobacco smoke (ETS) and burning of candles was collected by questionnaires. The personal exposure, the bedroom concentration and the front door concentration was set as outcome variable in separate models and analysed by mixed effect model regression methodology, regarding subject levels as a random factor. Seasons were defined as a dichotomised grouping of outdoor temperature (above and below 8 degrees C). For NO(2) there was a significant association between personal exposure and both the bedroom, the front door and the background concentrations, whereas for PM(2.5) and BS only the bedroom and the front door concentrations, and not the background concentration, were significantly associated to the personal exposure. The bedroom concentration was the strongest predictor of all three pollution measurements. The association between the bedroom and front door concentrations was significant for all three measurements, and the association between the front door and the background concentrations was significant for PM(2.5) and NO(2), but not for BS, indicating greater spatial variation for BS than for PM(2.5) and NO(2). For NO(2), the relationship between the personal exposure and the front door concentration was dependent upon the "season", with a stronger association in the warm season compared with the cold season, and for PM(2.5) and BS the same tendency was seen. Time exposed to burning of candles was a significant predictor of personal PM(2.5), BS and NO(2) exposure, and time exposed to ETS only associated with personal PM(2.5) exposure. These findings imply that the personal exposure to PM(2.5), BS and NO(2) depends on many factors besides the outdoor levels, and that information on, for example, time of season or outdoor temperature and residence exposure, could improve the accuracy of the personal exposure estimation.
Currently, very simple parameterizations for the seasonal variation of the ammonia (NH3) emissions are used in most air pollution models. This limits the capability to reproduce observed seasonal ...variations in the NH3 concentrations in rural regions with agricultural activity. A dynamical parameterization of the temporal variation of NH3 emission for application into air pollution models has therefore been proposed. The obtained improvements are demonstrated by implementing a dynamical NH3 emission parameterization into the large‐scale air pollution model ACDEP. Meteorology, information about agricultural practice, and a simple crop growth model are the basis for the parameterization. Fifteen additive functions are used to describe the different parts of the NH3 emissions from agriculture, and a 16th function is used to describe NH3 emission from catalysts used in road traffic. The new parameterization is tested by comparison of model results with NH3 measurements from Danish monitoring stations situated in agricultural areas during the years 1999–2001. Improvements in correlation coefficient of calculated diurnal mean concentrations from 0.42 to 0.70 have been achieved, and a monthly correlation coefficient up to 0.98 has been obtained for the Tange station in 2000. This validation shows that the new parameterization gives a substantial improvement in the model calculations of the NH3 concentrations in areas with high agricultural activities. Finally, the validation showed that optimum results are obtained by including a temperature correction on the gauss functions representing the emission sources.
Road traffic noise is the most pervasive source of ambient outdoor noise pollution in Europe. Traffic noise prediction models vary in parameterisation and therefore may produce different estimates of ...noise levels depending on the geographical setting in terms of emissions sources and propagation field. This paper compares three such models: the European standard, Common Noise Assessment Methods for the EU Member States (hereafter, CNOSSOS), Nord2000 and Traffic Noise Exposure (TRANEX) model based on the UK methodology, in terms of their source and propagation characteristics. The tools are also compared by analysing estimated noise (LAeq) from CNOSSOS, Nord2000 (2006 version), and TRANEX for more than one hundred test cases (N = 111) covering a variety of source and receiver configurations (e.g. varying source to receiver distance). The main aim of this approach was to investigate the potential pattern in differences between models’ performance for certain types of configurations. Discrepancies in performance may thus be linked to the differences in parameterisations of the CNOSSOS, Nord2000, and TRANEX (e.g. handling of diffraction, refraction). In most cases, both CNOSSOS and TRANEX reproduced LAeq levels of Nord2000 (2006 version) within three to five dBA (CNOSSOS: 87%, TRANEX: 94%). The differences in LAeq levels of CNOSSOS, compared to Nord2000, can be related to several shortcomings of the existing CNOSSOS algorithms (e.g. ground attenuation, multiple diffractions, and mean ground plane). The analyses show that more research is required in order to improve CNOSSOS for its implementation in the EU. In this context, amendments for CNOSSOS proposed by an EU Working Group hold significant potential. Overall, both CNOSSOS and TRANEX produced similar results, with TRANEX reproducing Nord2000 LAeq values slightly better than the CNOSSOS. The lack of measured noise data highlights one of the significant limitations of this study and needs to be addressed in future work.
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•First-time in-depth comparison of CNOSSOS-EU, Nord2000 and TRANEX.•Evaluation of source and propagation features as well as noise estimates.•CNOSSOS and TRANEX reproduced LAeq levels of Nord2000 (2006 version) within 3–5 dBA.•Correlation was R = 0.96 (CNOSSOS vs Nord2000), and R = 0.97 (TRANEX vs Nord2000).•Significant potential to further improve CNOSSOS for its implementation in Denmark.
Physical activity reduces, whereas exposure to air pollution increases, the risk of premature mortality. Physical activity amplifies respiratory uptake and deposition of air pollutants in the lung, ...which may augment acute harmful effects of air pollution during exercise.
We aimed to examine whether benefits of physical activity on mortality are moderated by long-term exposure to high air pollution levels in an urban setting.
A total of 52,061 subjects (50-65 years of age) from the Danish Diet, Cancer, and Health cohort, living in Aarhus and Copenhagen, reported data on physical activity in 1993-1997 and were followed until 2010. High exposure to air pollution was defined as the upper 25th percentile of modeled nitrogen dioxide (NO2) levels at residential addresses. We associated participation in sports, cycling, gardening, and walking with total and cause-specific mortality by Cox regression, and introduced NO2 as an interaction term.
In total, 5,534 subjects died: 2,864 from cancer, 1,285 from cardiovascular disease, 354 from respiratory disease, and 122 from diabetes. Significant inverse associations of participation in sports, cycling, and gardening with total, cardiovascular, and diabetes mortality were not modified by NO2. Reductions in respiratory mortality associated with cycling and gardening were more pronounced among participants with moderate/low NO2 hazard ratio (HR) = 0.55; 95% CI: 0.42, 0.72 and 0.55; 95% CI: 0.41, 0.73, respectively than with high NO2 exposure (HR = 0.77; 95% CI: 0.54, 1.11 and HR = 0.81; 95% CI: 0.55, 1.18, p-interaction = 0.09 and 0.02, respectively).
In general, exposure to high levels of traffic-related air pollution did not modify associations, indicating beneficial effects of physical activity on mortality. These novel findings require replication in other study populations.
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