TROPOspheric Monitoring Instrument (TROPOMI), on-board the Sentinel-5 Precurser satellite, is a nadir-viewing spectrometer measuring reflected sunlight in the ultraviolet, visible, near-infrared, and shortwave infrared. From these spectra several important air quality and climate-related atmospheric constituents are retrieved, including nitrogen dioxide (NO2) at unprecedented spatial resolution from a satellite platform. We present the first retrievals of TROPOMI NO2 over the Canadian Oil Sands, contrasting them with observations from the Ozone Monitoring Instrument satellite instrument, and demonstrate TROPOMI's ability to resolve individual plumes and highlight its potential for deriving emissions from individual mining facilities. Further, the first TROPOMI NO2 validation is presented, consisting of aircraft and surface in situ NO2 observations, and ground-based remote-sensing measurements between March and May 2018. Our comparisons show that the TROPOMI NO2 vertical column densities are highly correlated with the aircraft and surface in situ NO2 observations, and the ground-based remote-sensing measurements with a low bias (15-30 %); this bias can be reduced by improved air mass factors. Plain Language Summary Nitrogen dioxide (NO2) is a pollutant that is linked to respiratory health issues and has negative environmental impacts such as soil and water acidification. Near the surface the most significant sources of NO2 are fossil fuel combustion and biomass burning. With a recently launched satellite instrument (TROPOspheric Monitoring Instrument [TROPOMI]), NO2 can be measured with an unprecedented combination of accuracy, spatial coverage, and resolution. This work presents the first TROPOMI NO2 measurements near the Canadian Oil Sands and shows that these measurements have an outstanding ability to detect NO2 on a very high horizontal resolution that is unprecedented for satellite NO2 observations. Further, these satellite measurements are in excellent agreement with aircraft and ground-based measurements.
ABSTRACT Tag quality is an important factor to the success of social tagging systems and platforms. Users' domain expertise may influence they perceive tag quality. This study aims to explore how users of different domain experience (frequent user, occasional user, and non-user) perceive the quality of the same tags. We examined an online video community, Bilibili, which specializes in Anime, Comic and Games (ACG) subculture. We asked 60 users to watch 15 videos and rate the 95 tags of these videos, and found that: 1) Users with more domain expertise give higher ratings for tags' relevance to the videos and their retrieval value; 2) Occasional users have the lowest understandability rating, followed by non-users, and frequent users; 3) users think high-frequency tags are less suitable for retrieval. These results may provide insights to high quality tag selection for personalized recommendation and retrieval.
A system based on incoherent broadband cavity-enhanced absorption spectroscopy (IBBCEAS) has been developed for simultaneous measurement of nitrogen dioxide (NO2), glyoxal (GLY), and methylglyoxal (MGLY). In this system, the measured light absorption at around 460 nm is spectrally resolved. The concentration of absorbers is determined from a multicomponent fit. At an integration time of 100 s, the measurement sensitivity (2 sigma) for NO2, GLY, and MGLY is 18, 30, and 100 ppt, respectively. The measurement uncertainty, which mainly originates from path length calibration, sampling loss, and uncertainty of absorption cross sections is estimated to be 8% for NO2, 8% for GLY, and 16% for MGLY. When deploying the instrument during field observations, we found significant influence of NO2 on the spectra fitting for retrieving GLY and MGLY concentrations, which is caused by the fact that NO2 has a higher absorption cross section and higher ambient concentration. In order to minimize such an effect, a NO2 photolytic convertor (NPC), which removes sampled NO2 at an efficiency of 76 %, was integrated on the IBBCEAS system. Since sampled GLY and MGLY are mostly (>= 95 %) conserved after passing through the NPC, the quality of the spectra fitting and the measurement accuracy of ambient GLY and MGLY under NO2-rich environments could be improved.
Aims: To discover possible relationships between CXCL12 single nucleotide polymorphisms (SNPs) and type 2 diabetes mellitus (T2DM) and its risk factors. Methods: The present sib-pair study was conducted in a rural community of Beijing, China. SNPs rs2297630, rs1746048, and rs1801157 located within or nearby the CXCL12 gene were genotyped using the allele-specific polymerase chain reaction method. Haseman-Elston regression was used to investigate linkages between these SNPs and T2DM. A generalized estimating equation logistic regression model was used to discover associations between the SNPs, T2DM, and its risk factors. Results: A total of 3171 participants were recruited, comprising 2277 sib pairs. After Bonferroni correction (alpha = 0.016), rs2297630 was found to be significantly linked to (p = 0.003) and associated with T2DM (AA vs. GG/GA: OR = 2.26, 95% CI: 1.31-3.88, p = 0.003). There were interactions between rs2297630 and dyslipidemia (p < 0.001) and between rs1746048 and hypertension (p = 0.011). Compared to dyslipidemia-free subjects with rs2297630 GG/GA genotypes, dyslipidemia patients with rs2297630 AA had a higher risk of T2DM (OR = 4.15, 95% CI: 2.24-7.67, p < 0.001). Compared to hypertension-free subjects with rs1746048 CC genotypes, hypertension-free subjects with rs1746048 CT/TT had a decreased risk of T2DM (OR = 0.77, 95% CI: 0.60-0.99, p = 0.045). Conclusions: A novel linkage and association was found between rs2297630 and T2DM. Moreover, novel interactions were found between rs2297630 and dyslipidemia as well as rs1746048 and hypertension. These findings will help identify individuals at higher risk of developing T2DM.
To discover possible relationships between single nucleotide polymorphisms (SNPs) and type 2 diabetes mellitus (T2DM) and its risk factors. The present sib-pair study was conducted in a rural community of Beijing, China. SNPs rs2297630, rs1746048, and rs1801157 located within or nearby the gene were genotyped using the allele-specific polymerase chain reaction method. Haseman-Elston regression was used to investigate linkages between these SNPs and T2DM. A generalized estimating equation logistic regression model was used to discover associations between the SNPs, T2DM, and its risk factors. A total of 3171 participants were recruited, comprising 2277 sib pairs. After Bonferroni correction ( = 0.016), rs2297630 was found to be significantly linked to ( = 0.003) and associated with T2DM (AA vs. GG/GA: OR = 2.26, 95% CI: 1.31-3.88, = 0.003). There were interactions between rs2297630 and dyslipidemia ( < 0.001) and between rs1746048 and hypertension ( = 0.011). Compared to dyslipidemia-free subjects with rs2297630 GG/GA genotypes, dyslipidemia patients with rs2297630 AA had a higher risk of T2DM (OR = 4.15, 95% CI: 2.24-7.67, < 0.001). Compared to hypertension-free subjects with rs1746048 CC genotypes, hypertension-free subjects with rs1746048 CT/TT had a decreased risk of T2DM (OR = 0.77, 95% CI: 0.60-0.99, = 0.045). A novel linkage and association was found between rs2297630 and T2DM. Moreover, novel interactions were found between rs2297630 and dyslipidemia as well as rs1746048 and hypertension. These findings will help identify individuals at higher risk of developing T2DM.
Microbial community structure is affected by both natural processes and human activities. In coastal area, anthropegenetic activity can usually lead to the discharge of the effluent from wastewater treatment plant (WWTP) to sea, and thus the water quality chronically turns worse and marine ecosystem becomes unhealthy. Microorganisms play key roles in pollutants degradation and ecological restoration; however, there are few studies about how the WWTP effluent disposal influences coastal microbial communities. In this study, sediment samples were collected from two WWTP effluent-receiving areas (abbreviated as JX and SY) in Hangzhou Bay. First, based on the high-throughput sequencing of 16S rRNA gene, microbial community structure was analyzed. Secondly, several statistical analyses were conducted to reveal the microbial community characteristics in response to the effluent disposal. Using PCoA, the significant difference of in microbial community structure was determined between JX and SY; using RDA, water COD and temperature, and sediment available phosphate and ammonia nitrogen were identified as the key environmental factors for the community difference; using LDA effect size analysis, the most distinctive microbes were found and their correlations with environmental factors were investigated; and according to detrended beta-nearest-taxon-index, the sediment microbial communities were found to follow “niche theory”. An interesting and important finding was that in SY that received more and toxic COD, many distinctive microbes were related to the groups that were capable of degrading toxic organic pollutants. This study provides a clear illustration of eco-environmental deterioration under the long-term human pressure from the view of microbial ecology.
Pores with sizes ranging from nanometers to micrometers are widely distributed in shale gas and shale oil formations. These pores are the sites for hydrocarbon accumulation and provide the flow paths for hydrocarbons during production. The Middle Bakken member is the main production zone of the Bakken Formation in North Dakota. In order to reveal the pore structures of the Middle Bakken, we employed field emission scanning electron microscopy (FE-SEM). After segmentation of the SEM images, we calculated the surface area and shape of the pores using image analysis and then quantified the complexity and heterogeneity of the pore structures by applying both fractal and multifractal analyses. Finally, we employed the fractal permeability model to estimate the permeability of the samples. The results showed that different pore types, such as interparticle and intraparticle pores exist in the Middle Bakken samples. Even under the same scale of the same sample, the pore parameters could be different. Sample 2 has the largest average porosity, followed by Sample 1 and Sample 3. The mean pore size of these samples is less than 31 nm indicating that the pores in Middle Bakken samples are very small. The pore structures in the Middle Bakken exhibited fractal and multifractal behavior. The fractal dimension from the entire size range of pores is the largest compared with the fractal dimension of the subdivided groups. The pore size distribution in Sample 2 is the most heterogeneous.
During the period 2012-2015, photolysis frequencies were measured at the Peking University site (PKUERS), a site representative of Beijing. We present a study of the effects of aerosols on two key photolysis frequencies, j((OD)-D-1) and j(NO2). Both j((OD)-D-1) and j(NO2) display significant dependence on aerosol optical depth (AOD; 380 nm) with a non-linear negative correlation. With the increase in AOD, the slopes of photolysis frequencies vs. AOD decrease, which indicates that the capacity of aerosols to reduce the actinic flux decreases with AOD. The absolute values of slopes are equal to 4.2-6.9x10(-6) and 3.4x10(-3) s(-1) per AOD unit for j((OD)-D-1) and j(NO2) respectively at a solar zenith angle (SZA) of 60 degrees and AOD smaller than 0.7, both of which are larger than those observed in a similar, previous study in the Mediterranean. This indicates that the aerosols in Beijing have a stronger extinction effect on actinic flux than absorptive dust aerosols in the Mediterranean. Since the photolysis frequencies strongly depended on the AOD and the SZA, we established a parametric equation to quantitatively evaluate the effect of aerosols on photolysis frequencies in Beijing. According to the parametric equation, aerosols lead to a decrease in seasonal mean j(NO2) by 24% and 30% for summer and winter, respectively, and a corresponding decrease in seasonal mean j((OD)-D-1) by 27% and 33 %, respectively, compared to an aerosol-free atmosphere (AOD = 0). Based on an observation campaign in August 2012, we used a photochemical box model to simulate the ozone production rate (P(O-3)). The simulation results shows that the monthly mean daytime net ozone production rate is reduced by up to 25% due to the light extinction of aerosols. Through further in-depth analysis, it was found that particulate matter concentra-tions maintain a high level under the condition of high concentrations of ozone precursors (volatile organic compounds, VOCs, and NOx), which inhibits the production of ozone to a large extent. This phenomenon implies a negative feedback mechanism in the atmospheric environment of Beijing.