PM10 Concentration Levels Research Articles

Synoptic weather evolution and climate drivers associated with winter air pollution in New Zealand

Particulate matter pollution of less than 10 μm in diameter (PM10) is a problem for some regional and urban centres across New Zealand during the winter period when solid fuel (wood and coal) fires are used for home heating. Elevated levels of PM10 concentrations occur during stable atmospheric conditions, when cool air temperatures and low wind speeds allow for a surface inversion to occur and trap PM10. This study examined the relationships between PM10 and local and large-scale synoptic conditions at daily and seasonal scales. Minimum temperature and wind speed were both negatively correlated with PM10 during the winter season, whilst the combination of the two can explain 30–54% of variability in average PM10. Synoptic-scale daily composites of high PM10 days showed the evolution of an anticyclone in the Tasman Sea, with an injection of cool air over New Zealand and persistent south-westerly winds leading to cold and stable conditions on the day of exceedance. Both of these results indicate that there is some potential for predicting days in which atmospheric conditions could favour elevated PM10 concentrations. Furthermore, at the seasonal scale, weaker westerly winds were found to be associated with winters with higher exceedance days, although the relationship is not straightforward. These characteristics can be associated with other, predictable large-scale climate drivers such as the El Niño-Southern Oscillation, and may aid in identifying years in which a higher risk of PM10 pollution events exists.

The Effects of Bus Ridership on Airborne Particulate Matter (PM10) Concentrations

Air pollution caused by rapid urbanization and the increased use of private vehicles seriously affects citizens’ health. In order to alleviate air pollution, many cities have replaced diesel buses with compressed natural gas (CNG) buses that emit less exhaust gas. Urban planning strategies such as transit-oriented development (TOD) posit that reducing private vehicle use and increasing public transportation use would reduce air pollution levels. The present study examined the effects of bus ridership on airborne particulate matter (PM10) concentrations in the capital region of Korea. We interpolated the levels of PM10 from 128 air pollution monitoring stations, utilizing the Kriging method. Spatial regression models were used to estimate the impact of bus ridership on PM10 levels, controlling for physical environment attributes and socio-economic factors. The analysis identified that PM10 concentration levels tend to be lower in areas with greater bus ridership. This result implies that urban and transportation policies designed to promote public transportation may be effective strategies for reducing air pollution.

Application of Step Wise Regression Analysis in Predicting Future Particulate Matter Concentration Episode

Particulate matter is an air pollutant that has resulted in tremendous health effects to the exposed populace. Air quality forecasting is an established process where air pollutants particularly, particulate matter (PM10) concentration is predicted in advance, so that adequate measures are implemented to reduce the health effect of PM10 to the barest level. The present study used daily average PM10 concentration and meteorological parameters (temperature, humidity, wind speed and wind direction) for 5 years (2006–2010) from three industrial air quality monitoring stations in Malaysia (Balok Baru, Tasek and Paka). Time series plot was used to assess PM10 pollution trend in the industrial areas. Additionally, step wise regression (SWR) analysis was used to predict next day PM10 concentrations for the three industrial areas. The SWR method was compared with a persistence model to assess its predictive capabilities. The results for the trend analysis showed that, Balok Baru (BB) had higher PM10 concentration levels, having high values in 2006, 2007 and 2009. These values were higher than the Malaysian Ambient Air Quality Guideline (MAAQG) of 150 μg/m3. Subsequently, the other two industrial areas Tasek (TK) and Paka (PK) had no record of violating the MAAQG. The results for the SWR analysis had significant R 2 values of 0.64, 0.66 and 0.60, respectively. The model performance results for variance inflation factor (VIF) were less than 5 and Durbin-Watson test (DW) had value of 2 for each of the study areas, which were significant. The comparative analysis between SWR and persistence model showed that the SWR had better capabilities, having lower errors for the BB, TK and PK areas. Using root mean square error (RMSE), the results showed error differences of 7, 12 and 16 %, and higher predictability using index of agreement (IA), having a difference of 17, 19 and 16 % for BB, TK, and PK areas, respectively. The results showed that SWR can be used in predicting PM10 next day average concentration, while the extreme event detection results showed that 100 μg/m3 were better detected than the 150 μg/m3 bench marked levels.

Particle number and mass exposure concentrations by commuter transport modes in Milan, Italy

There is increasing awareness amongst the general public about exposure to atmospheric pollution while travelling in urban areas especially when taking active travelling modes such as walking and cycling. This study presents a comparative investigation of ultrafine particles (UFP), PM10, PM2.5, PM1 exposure levels associated with four transport modes (i.e., walking, cycling, car, and subway) in the city of Milan measured by means of portable instruments. Significant differences in particle exposure between transport modes were found. The subway mode was characterized by the highest PM mass concentrations: PM10, PM2.5, PM1 subway levels were respectively about 2-4-3 times higher than those of the car and open air active modes (i.e. cycling and walking). Conversely, these latter modes displayed the highest UFP levels about 2 to 3 times higher than the subway and car modes, highlighting the influence of direct traffic emissions. The car mode (closed windows, air conditioning and air recirculation on) reported the lowest PM and UFP concentration levels. In particular, the open-air/car average concentration ratio varied from about 2 for UFP up to 4 for PM1 and 6 for PM10 and PM2.5, showing differences that increase with increasing particle size. This work points out that active mode travelling in Milan city centre in summertime results in higher exposure levels than the car mode. Walkers’ and cyclists’ exposure levels is expected to be even higher during wintertime, due to the higher ambient PM and UFP concentration. Interventions intended to re-design the urban mobility should therefore include dedicated routes in order to limit their exposure to PM and UFP by increasing their distance from road traffic.

Investigation of Impacts of Mining and Transportation Activities on Ambient Air Quality of Dhanbad City

The present study was intended to emphasize the assessment of ambient air quality of Dhanbad city with respect to PM10, PM2.5, SO2 and NOX concentrations, in order to investigate the impact of mining and transportation activities. From the monitoring and analysis at four selected monitoring stations during winter and summer seasons, significant spatial variation in pollutant (PM10, PM2.5, SO2 and NOX) concentrations is quite evident. The concentrations of PM10 were observed highest in mining area (at Dhansar PS; 291 µg/m3), whereas the PM2.5 the concentrations were observed higher along traffic routes (especially, at Bank More; 218 µg/m3). Higher concentratios of PM10 in mining area indicates the substantial impact of dust emanated from mining and associated activities on air quality. Whereas, the higher PM2.5 concentration along the transportation routes shows the influence of transportation activities on the airshed of the area. The significant seasonal variation in pollution levels is also apparent, as the concentrations of every pollutant were observed higher during the winter, than the summer season, at all sites. The mean concentration levels of PM10 and PM2.5 were observed 267 µg/m3, 173 µg/m3 and 234 µg/m3, 108 µg/m3 during winter and summer seasons, respectively. From the calculated values of air quality index, it is evident that Dhansar PS and Bank More are most polluted sites and PM10 is the most alarming pollutant in the area under investigation.

INDOOR MICROBIAL CONTAMINATION THROUGH WATER MIST AEROSOL AT PUBLIC RESTAURANTS

In Malaysia and many other Asian countries, countless number of restaurants are made of open or semi-open air buildings. These restaurants are commonly located beside roads, factories, and construction sites. The foods are often exposed to the air, increasing their tendency to be contaminated due to poor indoor and outdoor air quality. There are very few studies characterising and comparing the levels of indoor air pollutants in restaurants. Other than that, scarce data are available on dining establishments especially in the presence and absence of water mist application system. Due to these reasons, no best practices or guidelines can be developed. Hence, this present study aimed (1) to assess and compare the physical indoor air quality (IAQ) characteristics and airborne pollutants between different types of restaurant settings; (2) to identify microbes isolated in the presence and absence of water mist system; (3) to analyse bacterial counting within and between the different restaurant settings; and (4) to determine the relationship between physical IAQ characteristics and airborne microbial contaminants. Instruments known as Dustmate and VelociCalc® Multi-Function Ventilation Meter 9565 were used to measure the physical IAQ characteristics and airborne particulate matters. On the other hand, Surface Air System Indoor Air Quality (SAS IAQ) was use to seize the microbial contaminants. All the data obtained were compared with the standard reference known as the Industrial Code of Practice on Indoor Air Quality (2010) constructed by the Department of Occupational Safety and Health (DOSH). This study later indicated that the level of indoor PM10 concentrations was influenced by changes of physical IAQ parameters at the two restaurants investigated. As the PM10 increased, the colony forming unit (CFU) counting also increased. Although microbial contaminations were found during both periods of exposure (i.e., in the presence and absence of water mist) at both restaurants, significant relationship between the parameters measured cannot be determined. The bacterial species obtained during the presence and absence of water mist application system for both of the restaurants were also identified. Gemella morbillorum was found as the most dominant species, followed by other species such as Aerococcus viridans, Globicatella sanguinis, Leuconostoc spp., and Proteus penneri.

신축목조주택의 실내공기질 특성 및 관련요인 분석

The purpose of this research is to analyze characteristics and related factors of IAQ (Indoor Air Quality) in newly built wooden houses by measuring pre and post occupancy. The subjects were five wooden houses which were built with similar materials and completed from July to December 2013. Measuring factors were TVOC, HCHO, PM10, , CO, indoor temperature, and relative humidity. As result of pre occupancy measuring, houses that revealed lowest TVOC concentration or HCHO concentration were satisfied with the standard for newly built apartment houses. Therefore, IAQ by wooden structures is considered to be in good condition. However, in cases of partial value exceeded standard, reason is analyzed to be materials of molding, wrapping doors, built-in closet, or kitchen furniture, etc. rather than structure materials. Most PM10 concentration level showed slightly below the standard for occupied multi-use facilities. Remaining of construction dust was considered to be reason. As result of post occupancy measuring, every value except of one subject`s TVOC concentration was lower than pre occupancy, explaining importance of natural ventilation.

Identification of sources of atmospheric particulate matter and trace metals in Constantine, Algeria

Very few previous investigations of respirable PM have been undertaken in the city of Constantine, Algeria. In general, air quality in Algeria and other Maghreb countries has not been extensively studied because of the insufficient number of researchers involved in this field and the unreliability of the few air quality monitoring networks installed in Algeria. It is therefore of utmost importance to address this problem in order to estimate the concentration levels of PM10 and their origins. The purpose of this study was to identify the different sources of PM10 and some chemical elements (Pb, Cu, Zn, Fe, K, Ca, Na, Mg) at a traffic site at Zouaghi, in the south of Constantine, using different statistical methods: factor analysis (FA) to categorise the different trace elements according to their origin, and the enrichment factor (EF) to identify terrigenous elements and those having a marine origin. We also used back-trajectories clustering to identify potential distant sources that contribute to particulate pollution and metallic elements in our site.

PM10 concentration levels at an urban and background site in Cyprus: The impact of urban sources and dust storms

Air quality in Cyprus is influenced by both local and transported pollution, including desert dust storms. We examined PM10 concentration data collected in Nicosia (urban representative) from April 1, 1993, through December 11, 2008, and in Ayia Marina (rural background representative) from January 1, 1999, through December 31, 2008. Measurements were conducted using a Tapered Element Oscillating Micro-balance (TEOM). PM10 concentrations, meteorological records, and satellite data were used to identify dust storm days. We investigated long-term trends using a Generalized Additive Model (GAM) after controlling for day of week, month, temperature, wind speed, and relative humidity. In Nicosia, annual PM10 concentrations ranged from 50.4 to 63.8 μg/m3 and exceeded the EU annual standard limit enacted in 2005 of 40 μg/m3 every year. A large, statistically significant impact of urban sources (defined as the difference between urban and background levels) was seen in Nicosia over the period 2000–2008, and was highest during traffic hours, weekdays, cold months, and low wind conditions. Our estimate of the mean (standard error) contribution of urban sources to the daily ambient PM10 was 24.0 (0.4) μg/m3. The study of yearly trends showed that PM10 levels in Nicosia decreased from 59.4 μg/m3 in 1993 to 49.0 μg/m3 in 2008, probably in part as a result of traffic emission control policies in Cyprus. In Ayia Marina, annual concentrations ranged from 27.3 to 35.6 μg/m3, and no obvious time trends were observed. The levels measured at the Cyprus background site are comparable to background concentrations reported in other Eastern Mediterranean countries. Average daily PM10 concentrations during desert dust storms were around 100 μg/m3 since 2000 and much higher in earlier years. Despite the large impact of dust storms and their increasing frequency over time, dust storms were responsible for a small fraction of the exceedances of the daily PM10 limit.ImplicationsThis paper examines PM10 concentrations in Nicosia, Cyprus, from 1993 to 2008. The decrease in PM10 levels in Nicosia suggests that the implementation of traffic emission control policies in Cyprus has been effective. However, particle levels still exceeded the European Union annual standard, and dust storms were responsible for a small fraction of the daily PM10 limit exceedances. Other natural particles that are not assessed in this study, such as resuspended soil and sea salt, may be responsible in part for the high particle levels.

A GIS model for personal exposure to PM10 for Dublin commuters

The goal of the research presented here is to generate a Geographic Information Systems (GIS) model for personal exposure to particulate matter (PM10) experienced by the inhabitants of Dublin while commuting to work. The pollutants concentrations in the Great Dublin area are calculated with various modelling tools built-in in a GIS environment. The inclusion of various pollutants dispersion models into a GIS platform aims to provide Local Authorities with a tool to calculate concentration levels of PM10 and to correlate these with other thematic layers, such as land use and population density, in order to link localised peaks in air pollutants with particular activities. The GIS model has been validated by modelling the personal exposure to particulate matter of commuters travelling to and from work in Dublin city centre using different routes and different transport modes and by comparing the modelled data with measured datasets obtained with mobile sensors (Aerocet-531) and GPS units. The correlation between the modelled and measured PM10 concentrations is calculated also for a range of different transport modes: the correlation is found to be high for the bus, bicycle and walking modes, but low for the train mode.

Low Air Pollution and Cardiovascular Mortality: a Population Based Case-Crossover Study

Background: The aim was to study short-term associations of NO2, O3, PM10, SO2, and H2S concentrations and cardiovascular mortality in Reykjavik capital area. Methods: Data on daily mortality were obtained from the National Cause-of-Death Registry, Statistics Iceland, during 2003 to 2009. One hour measures of NO2, O3, PM10, SO2, and H2S were obtained from the Environment Agency of Iceland for the same time period. A time-stratified case-crossover design was used to estimate the possible effect of short-term exposure of air pollution and cardiovascular mortality. Results: The total number of deaths due to cardiovascular causes over the study period was 2,070 cases. The inter-quartile range (IQR) of the 24-hour concentration levels of NO2, O3, PM10, SO2, and H2S over the study period was 17 µg/m3, 20 µg/m3, 13 µg/m3, 2 µg/m3, 2 µg/m3, respectively. The association for IQR increases of the pollutants and cardiovascular mortality were not statistically significant (confidence interval: 95%) at any time lag, with odds ratios near unity. Conclusion: The pollution concentration levels in Reykjavik are generally low in an international perspective, but peaks of pollutants, such as PM10, may exceed peaks occurring in other European cities. Previous studies have implied that air pollution in Reykjavik could increase consumption of medicament against asthma and angina pectoris. However, there were no short-term associations between air pollution and cardiovascular mortality in the present study, contrary to what has been found elsewhere.

A method for integrating occupational indoor air quality with building information modeling for scheduling construction activities

The occupational indoor air quality during construction plays a role in determining workers’ health as construction activities frequently generate airborne pollutants. This paper presents a methodology to predict the concentration of air pollutants during construction activities using building information modeling (BIM) and schedule the activities to limit the pollutant concentration within acceptable limits. This method allows the stakeholders to determine and predict the indoor air quality at the construction site before actual construction work. The proposed method was applied to predict the concentration of PM10 during dry wall sanding in a new residence as a case study. Using BIM technology PM10 concentration was predicted during drywall sanding, which ranged from 12.8 to 29.5 mg/m3. Also the hourly PM10 concentration level and the production rate of the drywall activity was adjusted to reduce the concentration level from 20 mg/m3 to the applicable standard of 10 mg/m3. The unique contribution of this research compared to previous research on indoor air quality and BIM is the development of a new method that integrates occupational indoor air quality with building information modeling for the assessment of the occupational environment for construction workers. More specifically, this paper uses BIM to assess the occupational indoor air quality and schedule construction activities to limit the exposure of workers to prescribed guidelines.

PM10and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set

BackgroundThe chemical composition of aerosols and particle size distributions are the most significant factors affecting air quality. In particular, the exposure to finer particles can cause short and long-term effects on human health. In the present paper PM10 (particulate matter with aerodynamic diameter lower than 10 μm), CO, NOx (NO and NO2), Benzene and Toluene trends monitored in six monitoring stations of Bari province are shown. The data set used was composed by bi-hourly means for all parameters (12 bi-hourly means per day for each parameter) and it’s referred to the period of time from January 2005 and May 2007. The main aim of the paper is to provide a clear illustration of how large data sets from monitoring stations can give information about the number and nature of the pollutant sources, and mainly to assess the contribution of the traffic source to PM10 concentration level by using multivariate statistical techniques such as Principal Component Analysis (PCA) and Absolute Principal Component Scores (APCS).ResultsComparing the night and day mean concentrations (per day) for each parameter it has been pointed out that there is a different night and day behavior for some parameters such as CO, Benzene and Toluene than PM10. This suggests that CO, Benzene and Toluene concentrations are mainly connected with transport systems, whereas PM10 is mostly influenced by different factors.The statistical techniques identified three recurrent sources, associated with vehicular traffic and particulate transport, covering over 90% of variance. The contemporaneous analysis of gas and PM10 has allowed underlining the differences between the sources of these pollutants.ConclusionsThe analysis of the pollutant trends from large data set and the application of multivariate statistical techniques such as PCA and APCS can give useful information about air quality and pollutant’s sources. These knowledge can provide useful advices to environmental policies in order to reach the WHO recommended levels.

Spatio-temporal semiparametric models for NO2 and PM10 concentration levels in Athens, Greece

Background and aimsStudies of air pollution effects on health are often based on ecological measurements. Our aim was to develop spatio-temporal models that estimate daily levels of NO2 and PM10 at every point in space, within the greater Athens area. MethodsWe applied a semiparametric approach using spatial and temporal covariates and a bivariate smooth thin plate function. We evaluated the predictions of our models against the exposure estimates that are typically used in health studies. For model validation we used a temporal and a spatial approach. ResultsThe adjusted-R2 of the developed exposure models was 0.53 and 0.75 for PM10 and NO2 respectively; the spatial terms in our models explained 41.5% and 64.5% and the temporal explained 52.85% and 32.0% of the variability in PM10 and NO2, respectively. There was no temporal or spatial left over autocorrelation in the residuals. We performed a leave-one-out cross validation and the adjusted-R2 were 0.41 for PM10 and 0.71 for NO2. The developed model showed good validity when comparing predicted and observed measures for the 2010 data. Our models performed better compared to the “ecological” estimates and estimates based on the “nearest monitoring site”. ConclusionsOur spatio-temporal model makes valid predictions, it introduces substantial geographical variability, it reduces the bias when compared with the “ecological” estimates and the estimates based on the “nearest monitoring site” and it can be used for a more personalized exposure assessment in health studies.

The contribution of Saharan dust in PM10 concentration levels in Anatolian Peninsula of Turkey

Sahara-originated dust is the most significant natural source of particulate matter; however, this contribution is still unclear in the Eastern Mediterranean especially in Western Turkey, where significant industrial sources and metropolitan areas are located. The Real-time Air Quality Modeling System (RAQMS) is utilized to explore the possible effects of Saharan dust on high levels of PM10 measured in Turkey. RAQMS model is compared with 118-air quality stations distributed throughout Turkey (81 cities) for April 2008. MODIS aerosol product (MOD04 for Terra and MYD04 for Aqua) is used to see columnar aerosol loading of the atmosphere at 550nm (Aerosol optical depth (AOD) values found to be between 0.6 and 0.8 during the episode). High-resolution vertical profiles of clouds and aerosols are provided from CALIOP, on board of CALISPO satellite. The results suggest a significant contribution of Sahara dust to high levels of PM10 in Turkey with RAQMS and in situ time series showing similar patterns. The two data sets are found to be in agreement with a correlation of 0.87.

Evaluation of a Numerical Methodology to Estimate Pedestrians’ Energy Consumption and PM Inhalation

The aim of this research work is to define and evaluate a new methodology for pedestrians, in order to evaluate the total PM potential inhaled dose (PPID) and the energy consumption for different trips, according to PM concentration levels, pedestrian activity (external power requirements) and minute ventilation, considering street topography (slope), walking speed and pedestrian characteristics (weight, age, gender).This work introduces the Pedestrian Specific Effort (PSE) modal analysis. It is based on real-world measurements of urban trips to discretize VE and VO2 according to external power requirements due to speed and slope. Trip segmentations is also introduced. Each segment has similar attributes for pedestrian speed, traffic characterization or road grade and also similar power requirements which enables the establishment of a relationship between external power and minute ventilation.This methodology was applied to a case study in Lisbon and the results were validated with experimental data. A portable laboratory was used to acquire the necessary information to characterize pedestrian trips (instant speed, PM concentration, GPS coordinates, etc.).Results show, as far as this methodology is concerned, good estimates of PM potential inhaled dose and energy consumption, when compared to in situ measurements, on a second by second basis, varying between -6 to 6% in PPID and -9% to 8% regarding energy consumption. These results indicate that the discretization performed (using PSE and segments) constitutes a good approach to translate real-world trips.

Assessment of contribution to PM10 concentrations from long range transport of pollutants using WRF/Chem over a subtropical urban airshed

A regional chemical transport model was implemented to simulate the Respirable Suspended Particulate Matter (PM10) concentration in order to study the impact of long–range transport of air pollutants over megacity Delhi with due consideration to different geographical domains extending up to entire Asia and corresponding emissions. PM10 concentration levels over megacity Delhi remain persistently high, often exceeding the ambient air quality standards. A chemical transport model namely Weather Research and Forecasting (WRF) model Version 3.2 coupled with chemistry module (WRF/Chem) was utilized with nested domains for this purpose, subsequent to model evaluation for the period during June, 2010 that includes extremely high PM10 concentrations. A highly satisfactory model performance was interpreted based on the several statistical parameters as per the current state of the science and their recommended values. Based on model simulations representing different geographical domains encompassing Asia, India, North India and Delhi and their corresponding emissions, it was clearly reflected that contributions due to emissions of the megacity Delhi alone is 11%–41% and thus remaining (59%–89%) proportion is expected to be contributed from the sources outside of the Delhi region which is significant. It is demonstrated that the WRF/Chem model performs well for a sub–tropical urban airshed though there is scope of improvement for the consistent under– prediction with more refined emission inventories. Nevertheless, this model could be implemented to assess the long– range transport of pollutants so as to adequately address the influence of the remote sources outside the urban airshed. This can serve as an important tool towards planning and implementing the regulatory policies for air pollution control for more effective outcomes.

Survey of airborne particulate matter concentration at a marble processing facility - workers’ exposure assessment

The scope of the present work was to examine exposure to airborne particulate matter (PM) at a marble cutting and treatment facility. Measurements were conducted inside all sections of the facility, as well as at selected outdoor locations. PM10 concentrations were monitored continuously, with a 1-min time resolution, by the use of DustTrak (Model 8520, TSI, Inc.). Mean PM10 concentration levels during cutting operations were measured equal to 997 μg m-3, when all machines were in use and 710 μg m-3, when only half of the machines were functioning. Higher levels were measured at the artistic department, where marble is cut and processed manually (mean PM10 concentration equal to 3,860 during a heavy cutting procedure and 1,000 μg m-3during a light duty period). When sampling was conducted next to the workers during the cutting process, mean personal exposure reached up to 63,000 μg m-3. The use of water during cutting operation was found to effectively decrease PM emissions. Significant concentrations were also measured at the different administrative offices. The highest levels (mean concentration equal to 220 μg m-3) were measured at the accounting office which is located at ground level, in close vicinity to the cutting section.

Differences in particulate matter concentrations between urban and rural regions under current and changing climate conditions

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.

Modeling tourism impacts on air pollution: The case study of PM10 in Mallorca

Tourism has begun to be acknowledged as being a significant contributor to the increase in environmental externalities, especially to climate ch ange. Various studies have started to estimate and compute the role of the different tourism sectors that contribute to greenhouse gas (GHG) emissions. These estimations have been made from a sectorial perspective, assessing the contribution of air transport, accommodation or other tourism-related economic sectors. In contrast with this and in order to evaluate the impact of tourism on air pollution from a joint perspective, this paper explores the relationship between daily concentrations of PM10 and the number of tourists in Mallorca (Spain). The results show that the daily stock of tourists is not only a significant predictor of air pollution concentration levels but also a variable whose inclusion improves the standard specification of urban air pollution models that have the common feature of using weather conditions as main explanatory variables. Furthermore, by using a Generalized Additive Model in its semi-parametric form it is shown that a 1% increase in tourist numbers can be related to up to a 0.45% increase in PM10 concentration levels.