The Himalayas and the Tibetan Plateau region (HTP), despite being a remote and sparsely populated area, is regularly exposed to polluted air masses with significant amounts of aerosols including ...black carbon. These dark, light-absorbing particles are known to exert a great melting potential on mountain cryospheric reservoirs through albedo reduction and radiative forcing. This study combines ground-based and satellite remote sensing data to identify a severe aerosol pollution episode observed simultaneously in central Tibet and on the southern side of the Himalayas during 13-19 March 2009 (pre-monsoon). Trajectory calculations based on the high-resolution numerical weather prediction model COSMO are used to locate the source regions and study the mechanisms of pollution transport in the complex topography of the HTP. We detail how polluted air masses from an atmospheric brown cloud (ABC) over South Asia reach the Tibetan Plateau within a few days. Lifting and advection of polluted air masses over the great mountain range is enabled by a combination of synoptic-scale and local meteorological processes. During the days prior to the event, winds over the Indo-Gangetic Plain (IGP) are generally weak at lower levels, allowing for accumulation of pollutants and thus the formation of ABCs. The subsequent passing of synoptic-scale troughs leads to southwesterly flow in the middle troposphere over northern and central India, carrying the polluted air masses across the Himalayas. As the IGP is known to be a hotspot of ABCs, the cross-Himalayan transport of polluted air masses may have serious implications for the cryosphere in the HTP and impact climate on regional to global scales. Since the current study focuses on one particularly strong pollution episode, quantifying the frequency and magnitude of similar events in a climatological study is required to assess the total impact.
Climate change may have an impact on air quality (ozone, particulate matter) due to the strong dependency of air quality on meteorology. The effect is often studied using a global climate model (GCM) ...to produce meteorological fields that are subsequently used by chemical transport models. However, climate models themselves are subject to large uncertainties and fail to reproduce the present-day climate adequately. The present study illustrates the impact of these uncertainties on air quality. To this end, output from the SRES-A1B constraint transient runs with two GCMs, i.e. ECHAM5 and MIROC-hires, has been dynamically downscaled with the regional climate model RACMO2 and used to force a constant emission run with the chemistry transport model LOTOS-EUROS in a one-way coupled run covering the period 1970–2060. Results from the two climate simulations have been compared with a RACMO2-LOTOS-EUROS (RLE) simulation forced by the ERA-Interim reanalysis for the period 1989–2009. Both RLE_ECHAM and RLE_MIROC showed considerable deviations from RLE_ERA for daily maximum temperature, precipitation and wind speed. Moreover, sign and magnitude of these deviations depended on the region. The differences in average present-day concentrations between the simulations were equal to (RLE_MIROC) or even larger than (RLE_ECHAM) the differences in concentrations between present-day and future climate (2041–2060). The climate simulations agreed on a future increase in average summer ozone daily maximum concentrations of 5–10 μg m−3 in parts of Southern Europe and a smaller increase in Western and Central Europe. Annual average PM10 concentrations increased 0.5–1.0 μg m−3 in North-West Europe and the Po Valley, but these numbers are rather uncertain: overall, changes for PM10 were small, both positive and negative changes were found, and for many locations the two climate runs did not agree on the sign of the change. This illustrates that results from individual climate runs can at best indicate tendencies and should therefore be interpreted with great care.
In this study the sensitivity of the model performance of the chemistry transport model (CTM) LOTOS-EUROS to the description of the temporal variability of emissions was investigated. Currently the ...temporal release of anthropogenic emissions is described by European average diurnal, weekly and seasonal time profiles per sector. These default time profiles largely neglect the variation of emission strength with activity patterns, region, species, emission process and meteorology. The three sources dealt with in this study are combustion in energy and transformation industries (SNAP1), nonindustrial combustion (SNAP2) and road transport (SNAP7). First of all, the impact of neglecting the temporal emission profiles for these SNAP categories on simulated concentrations was explored. In a second step, we constructed more detailed emission time profiles for the three categories and quantified their impact on the model performance both separately as well as combined. The performance in comparison to observations for Germany was quantified for the pollutants NO2, SO2 and PM10 and compared to a simulation using the default LOTOS-EUROS emission time profiles. The LOTOS-EUROS simulations were performed for the year 2006 with a temporal resolution of 1 h and a horizontal resolution of approximately 25 × 25km2. In general the largest impact on the model performance was found when neglecting the default time profiles for the three categories. The daily average correlation coefficient for instance decreased by 0.04 (NO2), 0.11 (SO2) and 0.01 (PM10) at German urban background stations compared to the default simulation. A systematic increase in the correlation coefficient is found when using the new time profiles. The size of the increase depends on the source category, component and station. Using national profiles for road transport showed important improvements in the explained variability over the weekdays as well as the diurnal cycle for NO2. The largest impact of the SNAP1 and 2 profiles were found for SO2. When using all new time profiles simultaneously in one simulation, the daily average correlation coefficient increased by 0.05 (NO2), 0.07 (SO2) and 0.03 (PM10) at urban background stations in Germany. This exercise showed that to improve the performance of a CTM, a better representation of the distribution of anthropogenic emission in time is recommendable. This can be done by developing a dynamical emission model that takes into account regional specific factors and meteorology.
Due to the strong relation between meteorology and air quality, a changing climate is anticipated to significantly impact air pollution. To investigate this effect a synoptic situation in the past ...which is expected to occur more often in future is analyzed in terms of air quality. In this study the effect of the meteorological conditions in the extreme summer 2003 on the concentration of PM10 and its components is investigated over Europe. To this end measurements of the EMEP network in Europe of the summer 2003 were compared to the average of the summers of a five years period (2003–2007). Furthermore simulation runs were performed with the German chemistry transport model REM-Calgrid and the Dutch model LOTOS-EUROS, to analyze whether state-of-the-art chemistry transport models are able to reproduce the observed concentrations during this episode.
The synoptic situation in summer 2003 resulted in 1–10 μg m−3 higher observed PM10 concentrations compared to the five years average. This increase was not reproduced to the same extent by the two models at most of the stations and the two models show evident differences in their PM10 simulations. The correlation between PM10 concentrations and meteorological parameters indicates that observed concentrations increase during weather conditions with high daily maximum temperature. The same holds for elemental carbon which is chosen as an example for a primary component. Low horizontal transport and the absence of wet deposition as a result of low wind speed and little precipitation associated with conditions with high temperatures favour the accumulation of pollutants in the lower troposphere. Although these conditions are reflected in the meteorological input data of the chemistry transport models used in this study, the models were not able to reproduce this relationship; they underestimate the observed high concentrations. This indicates that the underestimation of the variability of PM with meteorology is due to missing but important components and associated emissions or uncertainties therein, e.g. mineral dust, secondary organic aerosols and wild fires. To improve the simulation performance of the chemistry transport models as function of meteorological conditions these emission sources and the formation of secondary organic aerosols have to be included or improved and the dependency of anthropogenic emissions on meteorological conditions should be explicitly taken into account. These are essential issues for the simulation of such extreme conditions.
► The extreme summer 2003 had an increasing effect on observed PM concentrations. ► Two chemistry transport models underestimate this variability of PM with meteorology. ► The two models (LOTOS-EUROS and RCG) show evident differences in their PM simulation. ► A better representation of primary components and SOA in the models is necessary. ► Model emission should be explicitly related to the meteorology.
Pollution levels in urban areas and their surrounding rural regions differ due to different sources and density of emissions, different composition of pollutants as well as specific meteorological ...effects. These concentration differences for PM10 are investigated and compared in this study for three different north-west European urban agglomerations: The German Ruhr area, the Dutch Randstad and the German city of Berlin. Measurement data for PM10 for the years 2003–2008 at urban and rural background stations are selected from the AirBase database to specify the PM10 concentration difference between these urban areas and their surrounding rural regions, here defined as the urban increment. Whereas the absolute and relative measured urban increment averaged over the years 2003–2008 for the Ruhr area (7.4 μg m−3, 35%) and Berlin (8.5 μg m−3, 46%) are comparable in magnitude, a significantly smaller value is found for the Randstad (3.1 μg m−3, 12%). To analyze whether the regional chemistry transport model LOTOS-EUROS is able to reproduce the measured urban increment simulation runs were performed for 2003–2008 on a 0.5° × 0.25° lon-lat grid covering Europe and for the year 2008 on a finer grid of 0.125° × 0.0625° covering the Netherlands and Germany, both with ECMWF meteorology as input. Although the model underestimates the absolute PM10 urban increment averaged over the years 2003–2008 for the Ruhr area (3.3 μg m−3, 33%), the Randstad (1.5 μg m−3, 12%) and Berlin (1.7 μg m−3, 27%), the relative urban increment for the Ruhr area and the Randstad is in general agreement with the measurements. The tested increase of the horizontal resolution gives no systematic improvement of the simulated urban increment. However, an even higher resolution than used here seems to be more appropriate to capture the urban increment (especially for Berlin).
The variability of the PM10 urban increment with weather is tested by means of the summer 2003, such an extreme synoptic situation is expected to occur more often in future. Measured and simulated PM10 concentrations in summer 2003 were compared to the summer average of 2003–2008. The response of the observed urban increment was found to depend on the urban area. In general the model reproduces the main features for the Randstad and Berlin.
In order to investigate the impact of a changing climate on the PM10 urban increment, simulations were performed with the off-line coupled model system RACMO2 (regional climate model) – LOTOS-EUROS (air quality model) over Europe. Different sets of simulations were carried out using RACMO2 meteorology with ECHAM5 A1B and with MIROC3.2-hires A1B boundary conditions for the time period 1970–2060, as well as with ERA-interim boundary conditions for the time period 1989–2009. Anthropogenic emissions were kept constant in the LOTOS-EUROS simulations. Simulated concentrations differ between the runs using ECHAM and MIROC boundary conditions and both runs differ from the present-day simulations with ERA-interim forcing. The impact of climate change on the modeled PM10 concentrations and the urban increment was found to be small in both scenario runs. However the concentration differences between the simulations forced by either ECHAM or MIROC indicate that PM10 concentration levels are sensitive to circulation patterns rather than temperature change alone, and that PM10 concentration levels may thus change when circulation patterns change in the future.
•PM10 urban increments were quantified as differences between urban and rural regions.•Different measured PM10 urban increments were found for three urban areas in Europe.•These urban increments were also investigated using a chemistry transport model.•Model simulations showed a small impact of climate change on the urban increment.
Evidence suggests that chiropractic manipulation might exert positive effects in osteoporotic patients. The aim of this study was to evaluate the effects of chiropractic manipulation on bone ...structure and skeletal muscle in rats with bone loss caused by ovariectomy (OVX). The 6-month old Sprague-Dawley rats at 10 weeks following OVX or sham operation (Sh) did not suffer chiropractic manipulation (NM group) or were submitted to true chiropractic manipulation using the chiropractic adjusting instrument Activator V
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three times/week for 6 weeks as follows: Force 1 setting was applied onto the tibial tubercle of the rat right hind limb (TM group), whereas the corresponding left hind limb received a false manipulation (FM group) consisting of ActivatorV
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firing in the air and slightly touching the tibial tubercle. Bone mineral density (BMD) and bone mineral content (BMC) were determined in long bones and L3–L4 vertebrae in all rats. Femora and tibia were analyzed by μCT. Mechano growth factor (MGF) was detected in long bones and soleus, quadriceps and tibial muscles by immunohistochemistry and Western blot. The decrease of BMD and BMC as well as trabecular bone impairment in the long bones of OVX rats vs Sh controls was partially reversed in the TM group versus FM or NM rats. This bone improvement by chiropractic manipulation was associated with an increased MGF expression in the quadriceps and the anterior tibial muscle in OVX rats. These findings support the notion that chiropractic manipulation can ameliorate osteoporotic bone at least partly by targeting skeletal muscle.
In this study 1 year of ceilometer measurements taken in the Kathmandu Valley, Nepal, in the framework of the SusKat project (A Sustainable Atmosphere for the Kathmandu Valley) were analysed to ...investigate the diurnal variation of the mixing layer height (MLH) and its dependency on the meteorological conditions. In addition, the impact of the MLH on the temporal variation and the magnitude of the measured black carbon concentrations are analysed for each season. Based on the assumption that black carbon aerosols are vertically well mixed within the mixing layer and the finding that the mixing layer varies only little during night time and morning hours, black carbon emission fluxes are estimated for these hours and per month. Even though this method is relatively simple, it can give an observationally based first estimate of the black carbon emissions in this region, especially illuminating the seasonal cycle of the emission fluxes. The monthly minimum median MLH values typically range between 150 and 200 m during night and early morning hours, the monthly maximum median values between 625 m in July and 1460 m in March. Seasonal differences are not only found in the absolute MLHs, but also in the duration of the typical daytime maximum ranging between 2 and 3 h in January and 6–7 h in May. During the monsoon season a diurnal cycle has been observed with the smallest amplitude (typically between 400 and 500 m), with the lowest daytime mixing height of all seasons (maximum monthly median values typically between 600 and 800 m), and also the highest night-time and early morning mixing height of all seasons (minimum monthly median values typically between 200 and 220 m). These characteristics can mainly be explained with the frequently present clouds and the associated reduction in incoming solar radiation and outgoing longwave radiation. In general, the black carbon concentrations show a clear anticorrelation with MLH measurements, although this relation is less pronounced in the monsoon season. The daily evolution of the black carbon diurnal cycle differs between the seasons, partly due to the different meteorological conditions including the MLH. Other important reasons are the different main emission sources and their diurnal variations in the individual seasons. The estimation of the black carbon emission flux for the morning hours show a clear seasonal cycle with maximum values in December to April. Compared to the emission flux values provided by different emission databases for this region, the estimated values here are considerably higher. Several possible sources of uncertainty are considered, and even the absolute lower bound of the emissions based on our methodology is higher than in most emissions datasets, providing strong evidence that the black carbon emissions for this region have likely been underestimated in modelling studies thus far.
Air pollution resulting from rapid urbanization and associated human activities in the Kathmandu Valley of Nepal has been leading to serious public health concerns over the past 2 decades. These ...concerns led to a multinational field campaign SusKat-ABC (Sustainable atmosphere for the Kathmandu Valley – Atmospheric Brown Clouds) that measured different trace gases, aerosols and meteorological parameters in the Kathmandu Valley and surrounding regions during December 2012 to June 2013 to understand local- to regional-scale processes influencing air quality of the Kathmandu Valley. This study provides information about the regional distribution of ozone and some precursor gases using simultaneous in situ measurements from a SusKat-ABC supersite at Bode, Nepal, and two Indian sites: a high-altitude site, Nainital, located in the central Himalayan region and a low-altitude site, Pantnagar, located in the Indo-Gangetic Plain (IGP). The diurnal variations at Bode showed a daytime buildup in O3 while CO shows morning and evening peaks. Similar variations (with lower levels) were also observed at Pantnagar but not at Nainital. Several events of hourly ozone levels exceeding 80 ppbv were also observed at Bode. The CO levels showed a decrease from their peak level of about 2000 ppbv in January to about 680 ppbv in June at Bode. The hourly mean ozone and CO levels showed a strong negative correlation during winter (r2 = 0.82 in January and r2 = 0.71 in February), but this negative correlation gradually becomes weaker, with the lowest value in May (r2 = 0.12). The background O3 and CO mixing ratios at Bode were estimated to be about 14 and 325 ppbv, respectively. The rate of change of ozone at Bode showed a more rapid increase ( ∼ 17 ppbv h−1) during morning than the decrease in the evening (5–6 ppbv h−1), suggesting the prevalence of a semi-urban environ. The lower CO levels during spring suggest that regional transport also contributes appreciably to springtime ozone enhancement in the Kathmandu Valley on top of the local in situ ozone production. We show that regional pollution resulting from agricultural crop residue burning in northwestern IGP led to simultaneous increases in O3 and CO levels at Bode and Nainital during the first week of May 2013. A biomass-burning-induced increase in ozone and related gases was also confirmed by a global model and balloon-borne observations over Nainital. A comparison of surface ozone variations and composition of light non-methane hydrocarbons among different sites indicated the differences in emission sources of the Kathmandu Valley and the IGP. These results highlight that it is important to consider regional sources in air quality management of the Kathmandu Valley.
An evaluation of the meteorology simulated using the Weather Research and
Forecast (WRF) model for the region of south Asia and Nepal with a focus on the
Kathmandu Valley is presented. A particular ...focus of the model evaluation is
placed on meteorological parameters that are highly relevant to air quality
such as wind speed and direction, boundary layer height and precipitation.
The same model setup is then used for simulations with WRF including
chemistry and aerosols (WRF-Chem). A WRF-Chem simulation has been performed
using the state-of-the-art emission database, EDGAR HTAP v2.2, which is the Emission
Database for Global Atmospheric Research of the Joint Research Centre (JRC) of
the European Commission, in cooperation with the Task Force on Hemispheric Transport
of Air Pollution (TF HTAP) organized by the United Nations Economic Commission for
Europe, along with a sensitivity simulation using observation-based black carbon
emission fluxes for the Kathmandu Valley. The WRF-Chem simulations are
analyzed in comparison to black carbon measurements in the valley and to each
other. The evaluation of the WRF simulation with a horizontal resolution of 3×3 km2
shows that the model is often able to capture important
meteorological parameters inside the Kathmandu Valley and the results for
most meteorological parameters are well within the range of biases found in
other WRF studies especially in mountain areas. But the evaluation results
also clearly highlight the difficulties of capturing meteorological
parameters in such complex terrain and reproducing subgrid-scale processes
with a horizontal resolution of 3×3 km2. The measured black
carbon concentrations are typically systematically and strongly
underestimated by WRF-Chem. A sensitivity study with improved emissions in
the Kathmandu Valley shows significantly reduced biases but also underlines
several limitations of such corrections. Further improvements of the model
and of the emission data are needed before being able to use the model to
robustly assess air pollution mitigation scenarios in the Kathmandu region.
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