MAX-DOAS measurements of tropospheric NO2_{2} and HCHO in Munich and the comparison to OMI and TROPOMI satellite observations

We present two-dimensional scanning Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of nitrogen dioxide (NO$_{2}$) and formaldehyde (HCHO) in Munich. Vertical columns and vertical distribution profiles of aerosol extinction coefficient, NO$_{2}$ and HCHO are retrieved from the 2D MAX-DOAS observations. The measured surface aerosol extinction coefficients and NO$_{2}$ mixing ratios derived from the retrieved profiles are compared to in situ monitoring data, and the surface NO$_{2}$ mixing ratios show a good agreement with in situ monitoring data with a Pearson correlation coefficient (R) of 0.91. The aerosol optical depths (AODs) show good agreement as well (R = 0.80) when compared to sun photometer measurements. Tropospheric vertical column densities (VCDs) of NO$_{2}$ and HCHO derived from the MAX-DOAS measurements are also used to validate Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) satellite observations. Monthly averaged data show a good correlation; however, satellite observations are on average 30 % lower than the MAX-DOAS measurements. Furthermore, the MAX-DOAS observations are used to investigate the spatiotemporal characteristic of NO$_{2}$ and HCHO in Munich. Analysis of the relations between aerosol, NO$_{2}$ and HCHO shows higher aerosol-to-HCHO ratios in winter, which reflects a longer atmospheric lifetime of secondary aerosol and HCHO during winter. The analysis also suggests that secondary aerosol formation is the major source of these aerosols in Munich

TROPOMI/S5P Total Column Water Vapor validation against AERONET ground-based measurements

Water vapor plays an important role in the greenhouse effect, rendering it an atmospheric constituent that requires continuous and global monitoring by different types of remote sensing instruments. The TROPOspheric Monitoring Instrument Sentinel-5 Precursor (TROPOMI/S5P) Total Column Water Vapor (TCWV) is a new product retrieved from the visible blue spectral range (435–455 nm), using an algorithm that was originally developed for the GOME-2/MetOp sensors. For the purposes of this work, 2.5 years of continuous satellite observations at high spatial resolution are validated against co-located (in space and in time) precipitable water Level 2.0 (quality-assured) ground-based measurements from the NASA AERONET (AErosol RObotic NETwork). The network uses Cimel Sun photometers located at approximately 1300 stations globally to monitor precipitable water among other products. Based on data availability, 369 of the stations were used in this study. The two datasets, satellite- and ground-based, were co-located, and the relative differences of the comparisons were calculated and statistically analyzed. The Pearson correlation coefficient of the two products is found to be 0.91, and the mean bias of the overall relative percentage differences is of the order of −2.7 %. For the Northern Hemisphere midlatitudes (30–60∘ N), where the density of the ground-based stations is high, the mean relative bias was found to be −1.8 %, while in the tropics (±15∘) the TROPOMI TCWV product has a relative dry bias of up to −10 %. The effect of various algorithm and geophysical parameters, such as air mass factor, solar zenith angle, clouds and albedo, is also presented and discussed. It was found that the cloud properties affect the validation results, leading the TCWV to a dry bias of −20 % for low cloud heights (cloud top pressure (CTP) >800 hPa). Moreover, cloud albedo introduces a wet bias of 15 % when it is below 0.3 and a dry bias up to −25 % when the clouds are more reflective. Overall, the TROPOMI/S5P TCWV product, on a global scale and for moderate albedo and cloudiness, agrees well at  % with the AERONET observations but probably within about −8 % to −13 % with respect to the “truth”

Some pattern recognitions for a recommendation framework for higher education students’ generic competence development using machine learning

The project presented in this paper aims to formulate a recommendation framework that consolidates the higher education students’ particulars such as their academic background, current study and student activity records, their attended higher education institution’s expectations of graduate attributes and self-assessment of their own generic competencies. The gap between the higher education students’ generic competence development and their current statuses such as their academic performance and their student activity involvement was incorporated into the framework to come up with a recommendation for the student activities that lead to their generic competence development. For the formulation of the recommendation framework, the data mining tool Orange with some programming in Python and machine learning models was applied on 14,556 students’ activity and academic records in the case higher education institution to find out three major types of patterns between the students’ participation of the student activities and (1) their academic performance change, (2) their programmes of studies, and (3) their English results in the public examination. These findings are also discussed in this paperPeer Reviewe

Spatial and temporal representativeness of point measurements for nitrogen dioxide pollution levels in cities

In many cities around the world the overall air quality is improving, but at the same time nitrogen dioxide (NO2) trends show stagnating values and in many cases could not be reduced below air quality standards recommended by the World Health Organization (WHO). Many large cities have built monitoring stations to continuously measure different air pollutants. While most stations follow defined rules in terms of measurement height and distance to traffic emissions, the question remains of how representative are those point measurements for the city-wide air quality. The question of the spatial coverage of a point measurement is important because it defines the area of influence and coverage of monitoring networks, determines how to assimilate monitoring data into model simulations or compare to satellite data with a coarser resolution, and is essential to assess the impact of the acquired data on public health. In order to answer this question, we combined different measurement data sets consisting of path-averaging remote sensing data and in situ point measurements in stationary and mobile setups from a measurement campaign that took place in Munich, Germany, in June and July 2016. We developed an algorithm to strip temporal from spatial patterns in order to construct a consistent NO2 pollution map for Munich. Continuous long-path differential optical absorption spectroscopy (LP DOAS) measurements were complemented with mobile cavity-enhanced (CE) DOAS, chemiluminescence (CL) and cavity attenuated phase shift (CAPS) instruments and were compared to monitoring stations and satellite data. In order to generate a consistent composite map, the LP DOAS diurnal cycle has been used to normalize for the time of the day dependency of the source patterns, so that spatial and temporal patterns can be analyzed separately. The resulting concentration map visualizes pollution hot spots at traffic junctions and tunnel exits in Munich, providing insights into the strong spatial variations. On the other hand, this database is beneficial to the urban planning and the design of control measures of environment pollution. Directly comparing on-street mobile measurements in the vicinity of monitoring stations resulted in a difference of 48 %. For the extrapolation of the monitoring station data to street level, we determined the influence of the measuring height and distance to the street. We found that a measuring height of 4 m, at which the Munich monitoring stations measure, results in 16 % lower average concentrations than a measuring height of 1.5 m, which is the height of the inlet of our mobile measurements and a typical pedestrian breathing height. The horizontal distance of most stations to the center of the street of about 6 m also results in an average reduction of 13 % compared to street level concentration. A difference of 21 % in the NO2 concentrations remained, which could be an indication that city-wide measurements are needed for capturing the full range and variability of concentrations for assessing pollutant exposure and air quality in cities

Oral health of community dwelling elders in Hong Kong

Introduction: The world’s population is ageing and the elders are vulnerable to oral health problems. This project aimed to observe the oral health status of community dwelling elders in Hong Kong, investigate the oral health impact on their quality of life and nutritional status, and provide oral health education and preventive service. Methods: Community dwelling elders (65 or above) were recruited from five community centers. An interviewer-administered questionnaire was completed to collect information on their socio-demographic background and oral health perception/practice. Their oral health related quality of life (OHQoL) and nutritional status were measured by using the Geriatric Oral Health Assessment Index (GOHAI) and Mini-Nutritional Assessment (MNA), respectively. Their tooth and periodontal status, oral hygiene and soft tissues were examined. Individualized advice, oral health education and scaling were provided. Results: A total of 195 elders participated. Despite their sound knowledge on dental caries, their awareness of the causes and risk factors of periodontal diseases was low. Several misconceptions of oral health were common and their expectation towards oral health was low. Although 81% brush their teeth at least twice a day, over 75% did not perform interdental cleaning mainly due to unawareness of the necessity (32%) and lack of skills (42%). Their dental visits were treatment-driven and mainly for pain-relieving and emergency care. Only 19% were regular dental attendees. The mean (SD) DMFT was 8.9 (7.8). Over 60% had periodontal pockets; 6% were edentulous and 38% had fewer than 20 teeth. The mean (SD) total GOHAI score was 56.4 (8.0); 60% reported negative impact of oral health on their quality of life. The mean (SD) MNA score was 25.2 (2.9); 30% had malnutrition or were at risk. Multivariate analysis showed that tooth loss and untreated decayed teeth (DT) were significant determinants of poor OHQoL; older age, higher education level, and poorer OHQoL were significantly associated with higher risk of malnutrition (all p<0.05). Conclusions: Oral health problems are common among community dwelling elders in Hong Kong. Their oral health awareness and practice are yet to be improved. Tooth loss and unmet treatment need for dental caries significantly compromise elders’ quality of life, which in turn increases their risk for malnutrition. Outreach oral health education and service are well received by the community.published_or_final_versio

Economic transition and elections in Poland 1

Poland's economic and political transition, one of the most successful, has depended very heavily on job creation in new firms to replace the jobs lost in the formerly state-owned enterprises. This paper uses survey and aggregate data from three Polish elections to suggest that these de novo firms, the individuals they employ, and the residents in the local areas where they exist become an important constituency supporting pro-reform political parties and constraining the actions of parties less sympathetic to the reforms. The creation of this political constituency helps explain how countries can successfully pursue both economic and political reforms. JEL classification: D72, P26.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72227/1/1468-0351.00139.pd

The version 3 OMI NO2 standard product

We describe the new version 3.0 NASA Ozone Monitoring Instrument (OMI) standard nitrogen dioxide (NO2 /products (SPv3). The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/). The major improvements include (1) a new spectral fitting algorithm for NO2 slant column density (SCD) retrieval and (2) higher-resolution (1 degrees latitude and 1.25 degrees longitude) a priori NO2 and temperature profiles from the Global Modeling Initiative (GMI) chemistry-transport model with yearly varying emissions to calculate air mass factors (AMFs) required to convert SCDs into vertical column densities (VCDs). The new SCDs are systematically lower (by similar to 10-40 %) than previous, version 2, estimates. Most of this reduction in SCDs is propagated into stratospheric VCDs. Tropospheric NO2 VCDs are also reduced over polluted areas, especially over western Europe, the eastern US, and eastern China. Initial evaluation over unpolluted areas shows that the new SPv3 products agree better with independent satellite- and ground-based Fourier transform infrared (FTIR) measurements. However, further evaluation of tropospheric VCDs is needed over polluted areas, where the increased spatial resolution and more refined AMF estimates may lead to better characterization of pollution hot spots