Evaluation of Water Vapor Product from TROPOMI and GOME-2 Satellites against Ground-Based GNSS Data over Europe

A novel integrated water vapor (IWV) product from TROPOspheric Monitoring Instrument (TROPOMI) is validated together with a Global Ozone Monitoring Instrument-2 (GOME-2) standard product. As reference, ground-based Global Navigation Satellite Systems (GNSS) IWV data in 235 European stations from May 2018 to May 2019 are used. Under cloud free situations, a general comparison is carried out. It suggests that TROPOMI IWV exhibits less bias than GOME-2 and better results in the dispersion and regression parameters. Moreover, TROPOMI presents more homogeneous results along the different stations. However, TROPOMI is found to be overestimating the IWV uncertainties and being, therefore, too conservative in the confidence interval considered. The dependence of satellite product performance on several variables is also discussed. TROPOMI IWV shows wet bias of 5.7% or less for IWV 25 mm. In addition, relative standard deviation (rSD) increases as IWV increases. In addition, the dependence on solar zenith angle (SZA) was also analyzed, as solar radiation bands are used in the retrieval algorithm of both instruments. Relative mean bias error (rMBE) shows positive values for GOME-2, slightly increasing with SZA, while TROPOMI shows more stable values. However, under high SZA, GOME-2 IWV exhibits a steep increase in rMBE (overestimation), while TROPOMI IWV exhibits a moderate decrease (underestimation). rSD is slightly increasing with SZA. The influence of cloudiness on satellite IWV observations is such that TROPOMI tends to overestimate IWV more as cloudiness increases, especially for high IWV. In the case of GOME-2, the rSD slightly increases with cloudiness, but TROPOMI rSD has a marked increase with increasing cloudiness. TROPOMI IWV is an important source of information about moisture, but its algorithm could still benefit from further improvement to respond better to cloudy situations. View Full-Text In this paper we present a novel algorithm for the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) from UVN sensors; the algorithm is based on the full-physics inverse learning machine (FP_ILM) retrieval. Radiances are simulated using a radiative transfer model that takes into account the satellite-viewing geometry, and the inverse problem is solved using machine learning techniques to obtain the GE_LER from satellite measurements. The GE_LER retrieval is optimized not only for trace gas retrievals employing the DOAS algorithm, but also for the large amount of data from existing and future atmospheric Sentinel satellite missions. The GE_LER can either be deployed directly for the computation of air mass factors (AMFs) using the effective scene approximation or it can be used to create a global gapless geometry-dependent LER (G3_LER) daily map from the GE_LER under clear-sky conditions for the computation of AMFs using the independent pixel approximation. The GE_LER algorithm is applied to measurements of TROPOMI launched in October 2017 on board the EU/ESA Sentinel-5 Precursor (S5P) mission. The TROPOMI GE_LER/G3_LER results are compared with climatological OMI and GOME-2 LER datasets and the advantages of using GE_LER/G3_LER are demonstrated for the retrieval of total ozone from TROPOMI

Patent applications for using DNA technologies to authenticate medicinal herbal material

Herbal medicines are used in many countries for maintaining health and treating diseases. Their efficacy depends on the use of the correct materials, and life-threatening poisoning may occur if toxic adulterants or substitutes are administered instead. Identification of a medicinal material at the DNA level provides an objective and powerful tool for quality control. Extraction of high-quality DNA is the first crucial step in DNA authentication, followed by a battery of DNA techniques including whole genome fingerprinting, DNA sequencing and DNA microarray to establish the identity of the material. New or improved technologies have been developed and valuable data have been collected and compiled for DNA authentication. Some of these technologies and data are patentable. This article provides an overview of some recent patents that cover the extraction of DNA from medicinal materials, the amplification of DNA using improved reaction conditions, the generation of DNA sequences and fingerprints, and the development of high-throughput authentication methods. It also briefly explains why these patents have been granted

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

MAX-DOAS measurements of tropospheric NO2 and HCHO in Nanjing and a comparison to ozone monitoring instrument observations

In this paper, we present long-term observations of atmospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) in Nanjing using a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. Ground-based MAX-DOAS measurements were performed from April 2013 to February 2017. The MAX-DOAS measurements of NO2 and HCHO vertical column densities (VCDs) are used to validate ozone monitoring instrument (OMI) satellite observations over Nanjing. The comparison shows that the OMI observations of NO2 correlate well with the MAX-DOAS data with Pearson correlation coefficient (R) of 0.91. However, OMI observations are on average a factor of 3 lower than the MAX-DOAS measurements. Replacing the a priori NO2 profiles by the MAX-DOAS profiles in the OMI NO2 VCD retrieval would increase the OMI NO2 VCDs by similar to 30% with correlation nearly unchanged. The comparison result of MAX-DOAS and OMI observations of HCHO VCD shows a good agreement with R of 0.75 and the slope of the regression line is 0.99. An age-weighted backward-propagation approach is applied to the MAX-DOAS measurements of NO2 and HCHO to reconstruct the spatial distribution of NO2 and HCHO over the Yangtze River Delta during summer and winter time. The reconstructed NO2 fields show a distinct agreement with OMI satellite observations. However, due to the short atmospheric lifetime of HCHO, the backward-propagated HCHO data do not show a strong spatial correlation with the OMI HCHO observations. The result shows that the MAX-DOAS measurements are sensitive to the air pollution transportation in the Yangtze River Delta, indicating the air quality in Nanjing is significantly influenced by regional transportation of air pollutants. The MAX-DOAS data are also used to evaluate the effectiveness of air pollution control measures implemented during the Youth Olympic Games 2014. The MAX-DOAS data show a significant reduction of ambient aerosol, NO2 and HCHO (30 %-50 %) during the Youth Olympic Games. Our results provide a better understanding of the transportation and sources of pollutants over the Yangtze River Delta as well as the effect of emission control measures during large international events, which are important for the future design of air pollution control policies