Local Monitoring Stations Research Articles

Comparison of two methods of calculating NO2 and PM10 transboundary pollution by CMAQ chemical transport model and the assessment of the non-linearity effect

The comparison of two methods in calculating transboundary concentrations of NO2 and PM10 using CMAQ chemical transport model is presented. The total mean annual concentrations for the pollutants were computed from the hourly outputs of the CMAQ model. The first method for calculating the transboundary concentrations is based on switching off the emissions from the studied country, while the remaining emissions are the same as in the full model run. The second method is based on running the model with the emissions from the studied country only. The resulting concentrations are then subtracted from the full model run concentrations. The result of this subtraction represents the transboundary air pollution together with pollution originating from the interaction of national and foreign sources. The pollution which cannot be attributed unambiguously to national or foreign sources is caused by the non-linear processes included in the model. It is evaluated as the difference between the two methods. It is shown that the non-linearity effect is more expressed for PM10 than for NO2 annual mean concentrations. It is estimated that the non-linearity effect for PM10 can reach values up to 2.7 μg/m3 in absolute value, or up to 16% of the total annual mean concentrations and up to 25% of the total estimated transboundary concentrations in the studied area. It is also demonstrated that this non-linearity effect is more important for both pollutants during some episodes than in the annual mean. The method of removing the bias from the calculated transboundary concentrations is presented, together with the proposed method of evaluation of the uncertainties of the transboundary concentration calculations. The estimated transboundary contribution is evaluated at the locations of Slovak air-quality monitoring stations. The impact of several emission reduction levels on the estimation of the transboundary contribution is also presented. The simulations are performed for the reference year of 2015 for Slovakia, but the proposed methods can by applied universally.

Environmental Particulate Matter Levels during 2017 Large Forest Fires and Megafires in the Center Region of Portugal: A Public Health Concern?

This work characterizes the dimension and the exceptionality of 2017 large- and mega-fires that occurred in the center region of Portugal through the assessment of their impact on the ambient levels of particulate matter (PM10 and PM2.5), retrieved from local monitoring stations, and the associated public health risks. PM10 and PM2.5 concentrations were increased during the occurrence of large fires and megafires, with daily concentrations exceeding the European/national guidelines in 7–14 and 1–12 days of 2017 (up to 704 µg/m3 for PM10 and 46 µg/m3 for PM2.5), respectively. PM10 concentrations were correlated with total burned area (0.500 < r < 0.949; p > 0.05) and with monthly total burned area/distance2 (0.500 < r < 0.667; p > 0.05). The forest fires of 2017 took the life of 112 citizens. A total of 474 cases of hospital admissions due to cardiovascular diseases and 3524 cases of asthma incidence symptoms per 100,000 individuals at risk were assessed due to exposure to 2017 forest fires. Real-time and in situ PM methodologies should be combined with protection action plans to reduce public health risks. Portuguese rural stations should monitor other health-relevant pollutants (e.g., carbon monoxide and volatile organic compounds) released from wildfires to allow performing more robust and comprehensive measurements that will allow a better assessment of the potential health risks for the exposed populations.

Seismic character and progression of explosive activity during the 2016–2017 eruption of Bogoslof volcano, Alaska

Bogoslof volcano, in the central Aleutian arc, experienced a major eruption between December 2016 and August 2017 that was characterized by explosive activity (Volcanic Explosivity Index 2 to 3) and the extrusion of lava domes. The Alaska Volcano Observatory tracked the activity in real time using seismicity observed on distant stations as well as infrasound, lightning, satellite data, and occasional visual observations. In this study, we measure the duration of seismic signals associated with individual explosive events to track their progression during the two explosive phases of the eruption. Seismic recordings of Bogoslof explosions show complex waveforms that suggest both individual explosive events and sequences of several explosions separated by lower amplitude tremor. The lack of local seismic monitoring (stations at distances of 1 km to 15 km distance) unfortunately limits our ability to closely observe seismicity and to interpret changing conditions at the vent such as position, the presence of a lava dome or plug, and the role of seawater associated with the eruption. We use the rate of explosive activity, seismic waveform character, and repose time between explosions to infer the conditions within the conduit.

CLASSIFICATION OF HIGH AND LOW LEVEL OF PM10 CONCENTRATIONS IN KLANG AND SHAH ALAM, MALAYSIA

Particulate matter (PM) comprises of a complex mixture of small solid or liquid particles of organic and inorganic elements that floats freely in air. PM10 is defined as a particulate matter with an aerodynamic diameter of 10 m or less. The main objective of this paper is to classify the level of PM10 in selected locations in Peninsular Malaysia using discriminant analysis. Two important components considered in this study, namely; the meteorological factors and pollutant factors. The meteorological factors comprise of wind speed, wind direction, humidity and temperature while pollutant factors consist of Carbon Monoxide (CO), Sulphur Dioxide (SO2), Nitrogen Dioxide (NO2) and Ozone (O3). The classification of high or low level of PM10 concentrations was based on the Malaysia Ambient Air Quality Guideline (MAAQG). The findings indicated that the classification equation differs from location to location due to different levels of PM10 concentrations, location of monitoring stations and factors affecting air pollution in that location. The simulation data also verified that the classification of PM10 concentration was almost similar to the real condition that occurred in Klang in October 2015.

Environmental effect of decentralization on water quality near the border of cities: Evidence from China’s Province-managing-county reform

This study examines the environmental effects of decentralization on water quality in Chinese counties near the border of cities using data from local monitoring stations. Applying the generalized difference-in-difference-in-differences method, this analysis takes the province-managing-county reform as a quasi-natural experiment for decentralization and shows that four indexes of water quality in reformed counties near city borders are 10%–20% better than that of otherwise identical counties. This study suggests that the reform has a positive effect on environments near borders, which is attributed to the mitigation effect of increased public revenue, the mechanization effect of mechanized agriculture, and the home market effect of a narrowed market. By providing an intensive analysis of the three mechanisms, the paper implies that a well-designed decentralization reform can benefit the environment in addition to meeting its economic goals.

A Case-Crossover Study to Investigate the Effects of Atmospheric Particulate Matter Concentrations, Season, and Air Temperature on Accident and Emergency Presentations for Cardiovascular Events in Northern Italy.

Atmospheric particulate matter (PM) has multiple adverse effects on human health, high temperatures are also associated with adverse health outcomes, and the frequency of cardiovascular events (CVEs) varies with season. We investigated a hypothesized increase in PM-related accident and emergency (A&E) presentations for CVE with high temperature, warm season, days of high influenza incidence, and in people with a cancer diagnosis, using a time-stratified case-crossover study design. Outcomes were associations of A&E presentation for CVE with atmospheric PM ≤ 10 μm (PM10), season, and air temperature. PM10 levels in the municipality of residence (exposure variable) were estimated by modeling data from local monitoring stations. Conditional logistic regression models estimated odds ratios (OR) with 95% confidence intervals (CI) for presentations in relation to supposed influencers, adjusting for confounders. Study participants were all who presented at the A&E of a large hospital near Milan, Italy, for a CVE (ICD-9: 390–459) from 1st January 2014 to 31st December 2015. There were 1349 A&E presentations for CVE in 2014–2015 and 5390 control days. Risk of A&E presentation was significantly increased on hot days with OR 1.34 (95%CI 1.05–1.71) per 10 μg/m3 PM10 increment (as mean PM10 on day of presentation, and 1 and 2 days before (lags 0–2)), and (for lag 0) in autumn (OR 1.23, 95%CI 1.09–1.37) and winter (OR 1.18, 95%CI 1.01–1.38). Risks were also significantly increased when PM10 was on lag 1, in people with a cancer diagnosis in the spring and summer months (1.88, 95%CI 1.05–3.37), and on days (lags 0–2) of high influenza incidence (OR 2.34, 95%CI 1.01–5.43). PM10 levels exceeded the 50 μg/m3 “safe” threshold recommended by the WHO and Italian legislation for only 3.8% of days during the warm periods of 2014–2015. Greater risk of A&E presentation for CVE in periods of high PM10 and high temperature suggests that “safe” thresholds for PM10 should be temperature-dependent and that the adverse effects of PM10 will increase as temperatures increase due to climate change.

Overview, chronology, and impacts of the 2016–2017 eruption of Bogoslof volcano, Alaska

The 2016–2017 eruption of Bogoslof volcano, a back-arc shallow submarine volcano in Alaska’s Aleutian arc, began in December 2016 and included 70 explosive events and at least two episodes of subaerial dome building. Because the volcano had no local monitoring stations during the eruption, a combination of distant seismic stations, regional infrasound sensors, lightning detection, a variety of satellite data and observer reports, and a field visit in 2018, were used to recreate the events that occurred during the nine-month eruption. Following precursory seismicity that started in September 2016, the eruption began in December 2016 with a series of explosive events that persisted through mid-March 2017. After a 6-week hiatus, activity resumed on May 17 and lasted through the end of August 2017 and consisted of additional explosions and two short-lived subaerial lava domes that formed in June and August. For most of the eruption, Bogoslof’s vent was submerged in shallow seawater, though during several of the longer events a subaerial edifice grew, and the vent migrated above sea level resulting in more ash-rich volcanic clouds. Eruptive products, geophysical signals, and eruptive style are all broadly consistent with vulcanian activity where slow magma ascent led to repetitive dome or plug formation, overpressurization in the upper conduit, and sudden release during short-lived explosions. Infiltration of seawater may have prohibited large domes from forming especially in the first half of the eruption when explosions were closely spaced in time. The largest four explosions in the sequence occurred after inter-event times of 10 days or more. Three events produced ashfall on nearby communities and mariners east and south of Bogoslof and the eruption resulted in dozens of flight cancelations and flight diversions around the volcano and its ash clouds.

IoT-Based Real Time Air Pollution Monitoring System

Humans can be adversely affected by exposure to air pollutants in ambient air. Hence, health-based standards and objectives for a number of pollutants in the air are set by each country. Detection and measurement of contents of the atmosphere are becoming increasingly important. Careful planning of measurements is essential. One of the major factors that influence the representativeness of data collected is the location of monitoring stations. The planning and setting up of a monitoring station are complex and incurs a huge expenditure. An IoT-based real time air pollution monitoring system is proposed to monitor the pollution levels of various pollutants in Coimbatore city. The geographical area is classified as industrial, residential and traffic zones. This article proposes an IoT system that could be deployed at any location and store the measured value in a cloud database, perform pollution analysis, and display the pollution level at any given location.

Anthropogenic or non-anthropogenic particulate matter: Which one is more dangerous and how to differentiate between the effects?

The authors have observed that the function linking health outcomes with exposure to particulate-matter (PM) follows a biphasic pattern. It peaks around levels of PM10≤100 μg/m3, then weakens and rises again at PM10 levels in the range of hundreds. This could be due to a different nature of PM, the first peak reflecting a stronger anthropogenic and the second - weaker non-anthropogenic particles' effect. The current analysis is focused at the biphasic pattern on the association between PM levels with BG and asthma exacerbations. Pollutants were assessed by local monitoring stations and a satellitebased model. Local weekends/holidays were used to define nonanthropogenic levels of pollutants featured by lower Nitrogen Dioxide, the proxy for anthropogeneity. The association of PM10 with health outcomes within 24-48h lag was explored using spline functions of generalized additive models. Analysis of 546,420 BG tests (43,569 subjects) showed an almost linear association of PM10 with asthma with BG during the days with anthropogenic activity and no trend on other days. Analysis of asthmatic exacerbations within 1576 children showed no heterogeneity in association with PM10 by anthropogeneity levels, possibly indicating a mechanical impact on alveolar as the main trigger for exacerbations rather than PM10 chemical composition.

Characterizing the joint effects of pesticide exposure and criteria ambient air pollutants on pediatric asthma morbidity in an agricultural community.

Environmental contributions to pediatric asthma morbidity have been studied extensively in urban settings; exposures characteristic of agricultural and rural communities have received less attention despite a comparable burden of morbidity. We obtained repeated urine samples (n = 139) from 16 school-age children with asthma in the Yakima Valley of Washington State between July and October 2012. Biomarkers of organophosphate (OP) pesticide exposure (dialkyl phosphates [DAPs]) and asthma exacerbation (leukotriene E4 [LTE4]) were analyzed in samples. Corresponding 24-hour average particulate matter <2.5 μg (PM2.5) and maximum 8-hour ozone concentration data for the study period were available from local monitoring stations. We evaluated the independent and multi-pollutant associations between LTE4 and exposure to ambient air pollutants and DAPs using generalized estimating equations. For multi-domain and multi-pollutant models, we created categorized pollution combination levels and estimated the relative health impact of exposure to pollutant mixtures. In single-pollutant models, an interquartile range increase in exposures to DAPs was associated with increase in LTE4 levels (β: 4.1 [0.6-7.6] pg/mg). PM2.5 and ozone were also associated with increase in LTE4, though confidence intervals contained the null value. Increase in LTE4 levels was consistently associated with increase in median-dichotomized multi-pollutant combination exposures; the highest effect estimates were observed with joint highest (vs. the lowest) category of the three-pollutant exposure (PM2.5, ozone, and OP; β: 53.5, 95% confidence interval = 24.2, 82.8 pg/mg). Concurrent short-term exposure to criteria air pollutants and OPs in an agricultural community was associated with an increase in a marker of asthma morbidity.

Determination of the physical domain for air quality monitoring stations using the ANP-OWA method in GIS.

Air pollution is a major concern in some megacities of Iran. Specific cities in the country have reached an extremely harmful level of air pollution which poses a serious risk to the daily lives of Iranians. According to news reports, the air quality index of the city of Tehran hovers around 159, which is more than three times the World Health Organization's advised maximum. For the purpose of air pollution abatement, it is necessary to precisely know the air pollution distribution in the area. In order to obtain this figure, it is necessary to properly locate the city's air quality monitoring stations that measure the spatial pollutant distribution. According to various reports, the city must have at least 56 air quality monitoring stations to properly measure Tehran's air quality. However, there are currently only 20 stations within the city. Thus, the main purpose of this study was to identify the most sufficient areas for deploying new air quality monitoring stations. This study provided an integration of hybrid multi-criteria decision-making (MCDM) theories and geographical information system (GIS) processes in order to determine suitable areas to establish air quality monitoring stations. Unlike traditional models, the proposed MCDM method, ANP-OWA, is an efficient decision analysis which considers dependencies between criteria and defines different scenarios between pessimistic and optimistic conditions for decision makers. This method was applied to several parameters such as point, area, and line sources; population density; sensitive receptors; distance from current air quality stations; prediction error; and spatial distribution of CO, NO2, SO2, and PM10 pollutants. The output results specified several suitable locations to establish air pollution monitoring stations within Tehran Province. The stability and reliability of the output results were evaluated with a robust sensitivity analysis method. Moreover, the results demonstrated that the proposed method can produce stable results. Obtaining knowledge regarding population density, distance from current air quality stations, and spatial distribution of CO pollutant criteria is essential when selecting locations for air quality monitoring stations.

Variation of wastewater contaminants in China and source identification using hierarchical clustering based on weighted factor scores

Human activities have huge impact on the aquatic environment. Knowledge on sources of the contaminants provides guidelines to determine the ideal location and maintenance of monitoring stations, thus advancing environmental monitoring and pollution control. Factor analysis (FA) may be the most popular method for source identification, but the results should be affirmed. Following this logic, in this research, firstly the potential sources were determined, and secondly the contaminant concentrations in the source regions and the non-source regions were compared. To identify the potential sources, 75 meteorological, economic and social indicators were used to group the study regions. FA was used to reduce dimensionality and factor scores were calculated. The grouping was based on the weighted factor scores while the weight was variance explained by each factor respectively. Each group was supposed to correspond to a factor; that is, a potential source. The results indicated that the concentrations of chemical oxygen demand (COD), ammonia nitrogen, phosphorus and arsenic in wastewater were significantly different between groups. Animal husbandry, mining and/or energy industry were the main sources of COD, ammonia nitrogen and phosphorus; animal husbandry, mining, energy industry, and/or heavy and chemical industry were the main sources of phosphorus; humid climate and/or secondary industry were the main sources of arsenic.

Performance evaluation of a photochemical model using different boundary conditions over the urban and industrialized metropolitan area of Vitória, Brazil.

Metropolitan areas may suffer with increase of air pollution due to the growth of urbanization, transportation, and industrial sectors. The Metropolitan Area of Vitória (MAV) in Brazil is facing air pollution problems, especially because of the urbanization of past years and of having many industries inside the metropolitan area. Developing air quality system is crucial to understand the air pollution mechanism over these areas. However, having a good input dataset for applying on photochemical models is hard and requires quite of research. One input file for air quality modeling which can play a key role on results is the lateral boundary conditions (LBC). This study aimed to investigate the influence of LBC over CMAQ simulation for particulate matter and ozone over MAV by applying four different methods as LBC during August 2010. The first scenario (M1) is based on a fixed, time-independent boundary conditions with zero concentrations for all pollutants; the second scenario (M2) used a fixed, time-independent concentration values, with average values from local monitoring stations; the third CMAQ nesting scenario (M3) used the nested boundary conditions varying with time from a previous simulation with CMAQ over a larger modeling domain, centered on MAV; and finally, the fourth GEOS-Chem scenario (M4) used the boundary conditions varying with time from simulations of global model GEOS-Chem. All scenarios runs are based on the same meteorology conditions and pollutant emissions. The air quality simulations were made over a domain 61 × 79km centered on coordinates - 20.25° S, - 40.28° W with a resolution of 1km. The results were evaluated with the measured data from the local monitoring stations. Overall, significant differences on concentrations and number of chemical species between the LBC scenarios are shown across all LBC scenarios. The M3 and M4 dynamic LBC scenarios showed the best performances over ozone estimates while M1 and M2 had poor performance. Although no LBC scenarios do not seem to have a great influence on total PM10 and PM2.5 concentrations, individual PM2.5 species like Na, NO3-, and NH4+concentrations are influenced by the dynamic LBC approach, since those hourly individual PM2.5 species from CMAQ nesting approach (M3) and GEOS-Chem model (M4) were used as an input to LBC.

Correlations between air pollutant concentrations in selected urban and rural areas in Poland

Correlations between concentrations of selected air pollutants were analyzed in different areas in central Poland from 2012-2016. Three neighboring voivodeships (Lower Silesian, Lodz, and Masovian), were selected for which specific measurement locations were designated in urban and rural areas. The characteristics of the location of monitoring stations allowed to distinguish the following types of measurement stations: “urbantransport”, “urban-background", "suburban-background", "town-background", and "rural-background". Therefore, using the Pearson's linear correlation coefficient, it was possible to analyze the interrelations between the occurrence of air pollution in various types of areas. It was found that the coefficient changed along with the type of area. Moreover, it turned out that the coefficient decreased in each voivodeship along with a decrease in the population density of the analyzed areas. In addition, concentrations of various air pollutants in given areas were compared. Also, it was observed that the strongest correlations occur between the results of calculations from measurement stations located in the same province.

Air pollution distribution in Telkom University: spatial interpolation map

Currently, air quality information in a region becomes an important thing to know. Some efforts have been conducted to show air quality in certain region. One of the efforts that has been done is information regarding air quality in several big cities in Indonesia which can be seen in the official website of the Ministry of Environment and Forestry that have several weaknesses. One of the problems to be overcome in this research is visualization of air quality data that is monitored at one point only in which that point is the placement location of air quality monitoring station. Because of that, we need an application that can display a map of air pollution distribution using the spatial interpolation method. The solution offered is the depiction of air quality by using heatmap on the map. The method used to produce heatmap with smooth result is natural cubic spline interpolation method. The production of heatmap uses API which is provided by Google Maps. The final result obtained is the map view with the coloration in the form of color gradation in accordance with the air quality value that is obtained.

Sources of indoor particulate matter (PM) and outdoor air pollution in China in relation to asthma, wheeze, rhinitis and eczema among pre-school children: Synergistic effects between antibiotics use and PM10 and second hand smoke

We studied indoor sources of indoor particulate matter (PM), outdoor air pollution and antibiotic use in relation to asthma, rhinitis and eczema among pre-school children and investigated synergistic effects between PM and antibiotics use. Children (3-6y) from randomly selected day care centres in seven cities across China were included (n = 39,782). Data on ambient temperature and air pollution were collected from local monitoring stations. Data on indoor PM sources (ETS, burning of incense or mosquito coils and biomass for cooking), antibiotics use and health (doctor diagnosed asthma and rhinitis, lifetime eczema, current wheeze and current rhinitis) were assessed by a parental questionnaire. Associations were calculated by multilevel logistic regression. Asthma diagnosis was associated with outdoor temperature, NO2 and burning mosquito coils. Rhinitis diagnosis was associated with NO2, ETS, gas cooking and burning biomass for cooking. Lifetime eczema was associated with temperature, PM10, NO2, ETS, biomass cooking and burning mosquito coils. Burning incense was associated with current wheeze and current rhinitis. Children using antibiotics had more asthma, wheeze, rhinitis, and eczema. Excluding children with respiratory infections did not change associations with antibiotics use. Antibiotics use enhanced the effects of ETS and PM10 (a synergistic effect). In conclusion, a warmer climate, outdoor NO2 and PM10, ETS, gas cooking and burning biomass, incense and mosquito coils can increase the risk of asthma, wheeze, rhinitis and eczema among pre-school children in China. Antibiotics use is a risk factor for childhood asthma, wheeze, rhinitis and eczema and ETS and outdoor PM10 can enhance the effect.

PEMODELAN SEBARAN BOD DI SUNGAI KAPUAS KECIL BAGIAN HILIR MENGGUNAKAN WASP

The Kapuas Kecil River must be maintained for its water quality so that it can still be utilized in accordance with its designation. The purpose of this study is to predict water quality changes due to incoming waste from various sources of pollutants to the concentration of BOD in Kapuas Kecil River using WASP model as an effort to water quality monitoring and water pollution control.The study area to be simulated is Kapuas Kecil River passing through Pontianak City over ± 22 km from upstream to downstream (estuary) that divided into 42 segments. Water quality data were collected from several monitoring station locations in Kapuas Kecil River downstream, Landak River, effluent trenches located within the administrative area of Pontianak City, as well as secondary data on industrial effluents located along the study area. Water sampling method refers to the SNI 03-7026-2004, sampling was done once at each sample point with variations of the rainy and dry season, and at high and low tide conditions. Hydrometry data and river discharge can be obtained from primary and secondary data.The results showed that domestic and non-domestic of urban discharges that entering the river is very dominant influence on the water quality of the river. BOD concentration in rivers during the dry season is higher than rainy season both in high and low tide conditions. The simulation results of spatial distribution with all scenarios show that the accumulation of BOD pollution load begins after a distance of 5 km from the upstream boundary and then a significant increase in concentration occur at segment 27 with loads originating from the Landak River and Pekong Trench. The BOD concentration then tends to fluctuate to a distance of 5 km before heading downstream, and after that it continues to decline towards the downstream.

Measurement of Black Carbon Concentration and Comparison with PM10 and PM2.5 Concentrations Monitored in Chungcheong Province, Korea

ABSTRACT Black carbon concentrations are closely related to global warming. To characterize the atmospheric aerosols in Chungcheong Province, Korea, we measured the concentrations of black carbon for about eight months (September 2015–April 2016) and compared them with PM10 and PM2.5 concentrations as well as various meteorological parameters (e.g., wind velocity and wind direction). We used a multi-angle absorption photometer to measure the black carbon; the PM10 and PM2.5 concentrations, wind velocity, and wind direction were obtained from local monitoring stations. The highest and lowest PM10, PM2.5, and BC concentrations were observed in spring and fall, respectively. The high concentrations in spring and winter were likely due to the dominance of westerly winds, which transported pollutants, whereas the low concentrations in fall were likely due to increased wind variations, which drove turbulent mixing. Overall, although BC concentrations exhibited directly proportional correlations with PM10 and PM2.5, the correlations were relatively low, probably because of differences between the sources of these three atmospheric pollutants. These results help clarify the characteristics of BC concentrations over the Korean Peninsula.

Real-Time Orbit Determination of Korean Navigation Satellite System based on Multi-GNSS Precise Point Positioning

This study proposes real-time orbit/clock determination of Korean Navigation Satellite System (KNSS), which employs the kinematic precise point positioning (PPP) solutions of multiple Global Navigation Satellite System (multi-GNSS) to compensate for receiver clock offset. Global visibility of KNSS satellites in terms of geometric coverage is first analyzed for the purpose of selecting optimal locations of KNSS monitoring stations among International GNSS Service (IGS) and Multi-GNSS Experiment (MGEX) network. While the receiver clock offset is obtained from multi-GNSS PPP clock solutions of real observation data, KNSS measurements are simulated from the dynamically propagated KNSS reference orbit and the receiver clock offset. The offset and drift of satellite clock are also generated based on two-state clock model considering atomic clock noise. Real-time orbit determination results are compared with an artificially generated true or bit, wihch show 0.4m and 0.5m of 3-dimensional root-mean-square (RMS) position errors for geostationary (GEO) and ellitically-inclined-geosynchronous-orbit (EIGSO) satellites, respectively. The overall results show that the real-time precise orbit determination of KNSS should be achievable in meter level by installing KNSS-compatible multi-GNSS receivers on the IGS and/or MGEX network. The overall process can be also used to verify integrity of KNSS monitoring stations.

Mobile Measurements of Particulate Matter in a Car Cabin: Local Variations, Contrasting Data from Mobile versus Stationary Measurements and the Effect of an Opened versus a Closed Window.

Air pollution of particulate matter (PM) from traffic emissions has a significant impact on human health. Risk assessments for different traffic participants are often performed on the basis of data from local air quality monitoring stations. Numerous studies demonstrated the limitation of this approach. To assess the risk of PM exposure to a car driver more realistically, we measure the exposure to PM in a car cabin with a mobile aerosol spectrometer in Frankfurt am Main under different settings (local variations, opened versus a closed window) and compare it with data from stationary measurement. A video camera monitored the surroundings for potential PM source detection. In-cabin concentrations peaked at 508 µg m−3 for PM10, 133.9 µg m−3 for PM2.5, and 401.3 µg m−3 for coarse particles, and strongly depended on PM size and PM concentration in ambient air. The concentration of smaller particles showed low fluctuations, but the concentration of coarse particles showed high fluctuations with maximum values on busy roads. Several of these concentration peaks were assigned to the corresponding sources with characteristic particle size distribution profiles. The closure of the car window reduced the exposure to PM, and in particular to coarse particles. The mobile measured PM values differed significantly from stationary PM measures, although good correlations were computed for finer particles. Mobile rather than stationary measurements are essential to assess the risk of PM exposure for car passengers.