The Station for Measuring Ecosystem–Atmosphere Relations (SMEAR) II is well known among atmospheric scientists due to the immense amount of observational data it provides of the Earth–atmosphere ...interface. Moreover, SMEAR II plays an important role for the large European research infrastructure, enabling the large scientific community to tackle climate- and air-pollution-related questions, utilizing the high-quality long-term data sets recorded at the site. So far, this well-documented site was missing the description of the seasonal variation in aerosol chemical composition, which helps understanding the complex biogeochemical and physical processes governing the forest ecosystem. Here, we report the sub-micrometer aerosol chemical composition and its variability, employing data measured between 2012 and 2018 using an Aerosol Chemical Speciation Monitor (ACSM). We observed a bimodal seasonal trend in the sub-micrometer aerosol concentration culminating in February (2.7, 1.6, and 5.1 µg m−3 for the median, 25th, and 75th percentiles, respectively) and July (4.2, 2.2, and 5.7 µg m−3 for the median, 25th, and 75th percentiles, respectively). The wintertime maximum was linked to an enhanced presence of inorganic aerosol species (ca. 50 %), whereas the summertime maximum (ca. 80 % organics) was linked to biogenic secondary organic aerosol (SOA) formation. During the exceptionally hot months of July of 2014 and 2018, the organic aerosol concentrations were up to 70 % higher than the 7-year July mean. The projected increase in heat wave frequency over Finland will most likely influence the loading and chemical composition of aerosol particles in the future. Our findings suggest strong influence of meteorological conditions such as radiation, ambient temperature, and wind speed and direction on aerosol chemical composition. To our understanding, this is the longest time series reported describing the aerosol chemical composition measured online in the boreal region, but the continuous monitoring will also be maintained in the future.
To study the association between overweight and lumbar disc degeneration.
Population-based 4-y follow-up magnetic resonance imaging (MRI) study.
The subjects were 129 working middle-aged men selected ...to the baseline magnetic resonance imaging (MRI) study from a cohort of 1832 men representing three occupations: machine drivers, construction carpenters, and office workers. The selection was based on the paticipants' age (40-45 y) and place of residence. MR images of the lumbar spines were obtained at baseline and at 4-y follow-up.
Signal intensity of the nucleus pulposus of the discs L2/L3-L4/L5 was visually assessed by two readers using the adjacent cerebrospinal fluid as an intensity reference. The weight (at age 25 and 40-45 y) and height of the subjects, history of car driving, smoking, and back injuries were assessed by questionnaire.
Multiple regression analyses allowing for occupation, history of car driving, smoking, and back injuries showed that persistent overweight (body mass index (BMI) > or =25 kg/m(2) at both ages) associated strongly with an increased risk of the number of lumbar discs with decreased signal intensity of nucleus pulposus at follow-up, adjusted odds ratio (OR) being 4.3 (95% confidence intervals (95% CIs) 1.3-14.3). Overweight at young age (risk ratio (RR) 3.8; 95% CI 1.4-10.4) was a stronger predictor of an increase in the number of degenerated discs during follow-up than overweight in middle age (RR 1.3; 95% CI 0.7-2.7).
The study provides evidence that the BMI above 25 kg/m(2) increases the risk of lumbar disc degeneration. Overweight at young age seems to be particularly detrimental.
Based on a hypothesis that interleukin 1 (IL-1) activity is associated with low back pain (LBP), we investigated relationships between previously described functional IL-1 gene polymorphisms and LBP. ...The subjects were a subgroup of a Finnish study cohort. The IL-1alpha(C(889)-T), IL-1beta(C(3954)-T) and IL-1 receptor antagonist (IL-1RN)(G(1812)-A, G(1887)-C and T(11100)-C) polymorphisms were genotyped in 131 middle-aged men from three occupational groups (machine drivers, carpenters and office workers). A questionnaire inquired about individual and lifestyle characteristics and the occurrence of LBP, the number of days with pain and days with limitation of daily activities because of pain, and pain intensity, during the past 12 months. Lumbar disc degeneration was determined with magnetic resonance imaging. Carriers of the IL-1RNA(1812) allele had an increased risk of LBP (OR 2.5, 95% CI 1.0-6.0) and carriers of this allele in combination with the IL-1alphaT(889) or IL-1betaT(3954) allele had a higher risk of and more days with LBP than non-carriers. Pain intensity was associated with the simultaneous carriage of the IL-1alphaT(889) and IL-1RNA(1812) alleles (OR 3.7, 95% CI 1.2-11.9). Multiple regression analyses allowing for occupation and disc degeneration showed that carriage of the IL-1RNA(1812) allele was associated with the occurrence of pain, the number of days with pain and days with limitations of daily activities. Carriage of the IL-1betaT(3954) allele was associated with the number of days with pain. The results suggest a possible contribution of the IL-1 gene locus polymorphisms to the pathogenesis of LBP. The possibility of chance findings cannot be excluded due to the small sample size.
Abstract Purpose We evaluate for the first time the associations of brain white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) with neuropsychological variables among middle-aged ...bipolar I (BPI), II (BPII) and major depressive disorder (MDD) patients and controls using a path model. Methods Thirteen BPI, 15 BPII, 16 MDD patients, and 21 controls underwent brain MRI and a neuropsychological examination. Two experienced neuroradiologists evaluated WMHs on the MRI scans. We constructed structural equation models to test the strength of the associations between deep WMH (DWMH) grade, neuropsychological performance and diagnostic group. Results Belonging in the BPI group as opposed to the control group predicted higher DWMH grade (coefficient estimate 1.13, P = 0.012). The DWMH grade independently predicted worse performance on the Visual Span Forward test (coefficient estimate −0.48, P = 0.002). Group effects of BPI and MDD were significant in predicting poorer performance on the Digit Symbol test (coefficient estimate −5.57, P = 0.016 and coefficient estimate −5.66, P = 0.034, respectively). Limitations Because of the small number of study subjects in groups, the negative results must be considered with caution. Conclusions Only BPI patients had an increased risk for DWMHs. DWMHs were independently associated with deficits in visual attention.
Objectives. To investigate the effect of mechanical stress on finger osteoarthritis (OA) by comparing women from two occupations with different hand load but the same socio-economic grade, and to ...investigate whether hand load may affect the pattern of joint involvement in OA. Methods. Radiographs of both hands of 295 dentists and 248 teachers were examined. Each interphalangeal (distal, proximal and thumb interphalangeal) and the metacarpophalangeal joints were graded (0 = no OA, 4 = severe OA) separately by using reference images. The co-involvement of different hand joints was analysed by logistic regression. Results. The distal interphalangeal joints were the most frequently involved joints. The non-dominant hand was more frequently affected by OA of grade 2 or more than the dominant hand. The prevalence of OA of grade 2 or more in any finger joint and also in any distal interphalangeal joint was higher among the teachers compared with the dentists (59 vs 48%, P = 0.020 and 58 vs 47%, P<0.010 respectively). Finger OA showed more clustering in the ring and little fingers and more row clustering and symmetry in the teachers than in the dentists age-adjusted odds ratio (OR) = 1.57, 95% confidence interval (CI) 1.10–2.23, OR = 1.84, 95% CI 1.28–2.64, and OR = 1.98, 95% CI 1.38–2.86 respectively. The OR of more severe OA (grade 3 or more) in the right-hand thumb and the index and middle fingers was significantly elevated among the dentists compared with the teachers (OR 2.61, 95% CI 1.03–6.59). Conclusion. Our findings indicate that finger OA in middle-aged women is highly prevalent and often polyarticular. Hand use may have a protective effect on finger joint OA, whereas continuing joint overload may lead to joint impairment.
Mechanical load has been proposed as a risk factor for hand osteoarthritis. Dentists produce high manual forces in their work tasks. We studied whether the pattern of dental work tasks was associated ...with finger osteoarthritis. Radiographs of both hands of 291 middle-aged female dentists were examined for the presence of osteoarthritis. Patterns of dental work tasks during work history were empirically defined by cluster analysis. Three patterns emerged reflecting high, moderate, and mild task variation. Age, specialization, years in clinical work, various activities requiring hand use, family history of Heberden’s nodes, body mass index, and smoking were accounted for in logistic regression analyses. The dentists with a history of low task variation had a greater prevalence of osteoarthritis in the thumb, index, and middle fingers compared with dentists with high variation (OR 2.22; 95%CI 1.04–4.91). The pattern of dental work task history is associated with the localization of osteoarthritis in the fingers.
In this study, we present results from 12 years of black
carbon (BC) measurements at 14 sites around the Helsinki metropolitan area (HMA)
and at one background site outside the HMA. The main local ...sources of BC in
the HMA are traffic and residential wood combustion in fireplaces and sauna
stoves. All BC measurements were conducted optically, and therefore we refer
to the measured BC as equivalent BC (eBC). Measurement stations were located
in different environments that represented traffic environment, detached
housing area, urban background, and regional background. The measurements of
eBC were conducted from 2007 through 2018; however, the times and the
lengths of the time series varied at each site. The largest annual mean eBC
concentrations were measured at the traffic sites (from 0.67 to 2.64 µg m−3) and the lowest at the regional background sites (from 0.16 to
0.48 µg m−3). The annual mean eBC concentrations at the detached
housing and urban background sites varied from 0.64 to 0.80 µg m−3 and from 0.42 to 0.68 µg m−3, respectively. The
clearest seasonal variation was observed at the detached housing sites
where residential wood combustion increased the eBC concentrations during
the cold season. Diurnal variation in eBC concentration in different urban
environments depended clearly on the local sources that were traffic and
residential wood combustion. The dependency was not as clear for the typically measured air quality parameters, which were here NOx concentration and mass concentration of particles smaller that 2.5 µm in diameter (PM2.5). At four sites which had at least a 4-year-long time series available, the
eBC concentrations had statistically significant decreasing trends that
varied from −10.4 % yr−1 to −5.9 % yr−1. Compared to trends determined at
urban and regional background sites, the absolute trends decreased fastest
at traffic sites, especially during the morning rush hour. Relative
long-term trends in eBC and NOx were similar, and their concentrations
decreased more rapidly than that of PM2.5. The results indicated that
especially emissions from traffic have decreased in the HMA during the last
decade. This shows that air pollution control, new emission standards, and a
newer fleet of vehicles had an effect on air quality.
Aerosol optical properties (AOPs) describe the ability of
aerosols to scatter and absorb radiation at different wavelengths. Since
aerosol particles interact with the sun's radiation, they impact the
...climate. Our study focuses on the long-term trends and seasonal variations
of different AOPs measured at a rural boreal forest site in northern Europe.
To explain the observed variations in the AOPs, we also analyzed changes in
the aerosol size distribution. AOPs of particles smaller than 10 µm
(PM10) and 1 µm (PM1) have been measured at SMEAR II, in southern
Finland, since 2006 and 2010, respectively. For PM10 particles, the median
values of the scattering and absorption coefficients, single-scattering
albedo, and backscatter fraction at λ=550 nm were 9.8
Mm−1, 1.3 Mm−1, 0.88, and 0.14. The median values of scattering and
absorption Ångström exponents at the wavelength ranges 450–700
and 370–950 nm were 1.88 and 0.99, respectively. We found statistically
significant trends for the PM10 scattering and absorption coefficients,
single-scattering albedo, and backscatter fraction, and the slopes of these
trends were −0.32 Mm−1, −0.086 Mm−1, 2.2×10-3, and
1.3×10-3 per year. The tendency for the extensive AOPs to decrease
correlated well with the decrease in aerosol number and volume
concentrations. The tendency for the backscattering fraction and
single-scattering albedo to increase indicates that the aerosol size
distribution consists of fewer larger particles and that aerosols absorb less
light than at the beginning of the measurements. The trends of the
single-scattering albedo and backscattering fraction influenced the aerosol
radiative forcing efficiency, indicating that the aerosol particles are
scattering the radiation more effectively back into space.
The Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II, located within the boreal forest of Finland, is a unique station in the world due to the wide range of long-term measurements ...tracking the Earth-atmosphere interface. In this study, we characterize the composition of organic aerosol (OA) at SMEAR II by quantifying its driving constituents. We utilize a multi-year data set of OA mass spectra measured in situ with an Aerosol Chemical Speciation Monitor (ACSM) at the station. To our knowledge, this mass spectral time series is the longest of its kind published to date. Similarly to other previously reported efforts in OA source apportionment from multi-seasonal or multi-annual data sets, we approached the OA characterization challenge through positive matrix factorization (PMF) using a rolling window approach. However, the existing methods for extracting minor OA components were found to be insufficient for our rather remote site. To overcome this issue, we tested a new statistical analysis framework. This included unsupervised feature extraction and classification stages to explore a large number of unconstrained PMF runs conducted on the measured OA mass spectra. Anchored by these results, we finally constructed a relaxed chemical mass balance (CMB) run that resolved different OA components from our observations. The presented combination of statistical tools provided a data-driven analysis methodology, which in our case achieved robust solutions with minimal subjectivity.
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