Fluorescence detection of malachite green and cations (Cr3+, Fe3+ and Cu2+) by a europium-based coordination polymer.

Due to remarkable fluorescence characteristics, lanthanide coordination polymers (CP) have been widely employed in fluorescence detection, but it is rarely reported that they act as multifunctional luminescent probes dedicated to detecting malachite green (MG) and various metal ions. A europium-based CP fluorescent probe, Eu(PDCA)2(H2O)6 (PDCA = 2,6-pyridinedicarboxylic acid), has been synthesized and exhibited excellent recognition ability for malachite green and metal cations (Cr3+, Fe3+ and Cu2+) among 11 metal cations, 13 anions and six other compounds. The recognition was achieved by fluorescence quenching when MG, Cr3+, Fe3+ and Cu2+ were added to a suspension of Eu(PDCA)2(H2O)6 respectively. Eu(PDCA)2(H2O)6 is a multifunctional luminescent probe, and displayed high quenching efficiencies K sv (2.10 × 106 M-1 for MG; 1.46 × 105 M-1 for Cr3+; 7.26 × 105 M-1 for Fe3+; 3.64 × 105 M-1 for Cu2+), and low detection limits (MG: 0.039 µM; Cr3+: 0.539 µM; Fe3+: 0.490 µM; Cu2+: 0.654 µM), presenting excellent selectivity and sensitivity, especially for MG. In addition, Eu(PDCA)2(H2O)6 was also made into fluorescent test strips, which can rapidly and effectively examine trace amounts of MG, Cr3+, Fe3+ and Cu2+ in aqueous solutions. This work provides a new perspective for detecting malachite green in fish ponds and heavy metal ions in waste water.

Mapping typical salt-marsh species in the Yellow River Delta wetland supported by temporal-spatial-spectral multidimensional features.

The native salt marsh plants of the Yellow River Delta wetland such as Suaeda salsa and Phragmites australis, providing significant habitats for rare waterfowl, are the key to conserve biodiversity and enhance habitats of this critical wetland. These plants are undergoing severe degradation due to rapid invasion of Spartina alterniflora, which has been a major growing threat to the livelihood of waterfowl and the sustainability of the Yellow River Delta wetland. Monitoring the spatial pattern of salt marsh species is fundamental to the conservation and restoration of the ecological functions in the Yellow River Delta wetland. The development of remote sensing technologies is making a leap forward, particularly the high resolution synthetic aperture radar (SAR), which holds the potential to map heterogeneous wetland regardless of weather. In this study, we developed an innovative framework to map the distribution of salt marsh species with the integration of optical (Sentinel-2) and SAR (Sentinel-1) images. Within this framework, a comprehensive set of features including spectral, spatial and temporal features were considered, and the best feature combination was selected and applied in a random forest classification model to obtain the final map. The results show that the temporal-spectral features combined with the spatial-temporal features of the SAR data can effectively improve the separability of Suaeda salsa, Phragmites australis, and Spartina alterniflora. Compared with using optical or SAR data alone, the combination of optical and SAR data improved the kappa coefficient and the overall classification accuracy by 0.10-0.19 and 6.04-11.61%, respectively. The spatial distribution of the two main native plants and the invasive plant can facilitate ecological restoration of the Yellow River Delta wetland. The framework developed by this study can be efficiently replicated and transferred by similar studies. Our approach lays a solid foundation for intelligent monitoring and management of coastal wetland.

Scale-dependent biogeomorphic feedbacks control the tidal marsh evolution under Spartina alterniflora invasion.

The mechanisms of biogeomorphic feedbacks and its influencing factors have been extensively studied for pioneer species colonization in tidal environment. However, biogeomorphic impacts of alien species over the entire invasion process coupled with hydro-geomorphologic processes and ecoengineering traits still lack sufficient understanding to forecast salt marsh succession. In this study, we developed a bio-hydrogeomorphic model to account for the tidal platform evolution and vegetation distribution under Spartina alterniflora invasion in the Yellow River Delta, China. Our field observation and modelling results revealed that salt marsh transformed from a stabilized to a self-organized system due to the significant geomorphic-biological feedback under Spartina alterniflora invasion. Tidal channels took shape differently along the elevation gradient of the intertidal platform. Patch-scale feedbacks promoted the channel initiation in the low-elevated zone during early colonization phase. While landscape-scale feedbacks dominated channel incision in the middle to high platform during the mature phase. Specifically, the channel initiation in the middle-elevated ecotone could be attributed to the change from homogenous sheet flow to concentrated channel flow along the marsh edge, which was determined by tidal prism and discrepancy in organism traits. Hence, our study showed that scale-dependent feedback and gaps in ecoengineering capacity of organism determined the morphological variation in the invasive ecosystem. This would provide the insights into biogeomorphic impacts of invasive species and scientific conservation for native ecosystems.

Retrieval and Evaluation of Chlorophyll-a Concentration in Reservoirs with Main Water Supply Function in Beijing, China, Based on Landsat Satellite Images.

Remote sensing retrieval is an important technology for studying water eutrophication. In this study, Guanting Reservoir with the main water supply function of Beijing was selected as the research object. Based on the measured data in 2016, 2017, and 2019, and Landsat-8 remote sensing images, the concentration and distribution of chlorophyll-a in the Guanting Reservoir were inversed. We analyzed the changes in chlorophyll-a concentration of the reservoir in Beijing and the reasons and effects. Although the concentration of chlorophyll-a in the Guanting Reservoir decreased gradually, it may still increase. The amount and stability of water storage, chlorophyll-a concentration of the supply water, and nitrogen and phosphorus concentration change are important factors affecting the chlorophyll-a concentration of the reservoir. We also found a strong correlation between the pixel values of adjacent reservoirs in the same image, so the chlorophyll-a estimation model can be applied to each other.

Parameterizing the Yellow River Delta tidal creek morphology using automated extraction from remote sensing images.

The tidal creek is an important part of the intertidal zone, which maintains the balance between depositional processes and a given hydrodynamic environment. Much can be inferred about the development and evolution of a tidal creek by examining its morphometry characteristics; this information can also provide scientific decision support for the development and utilization of coastal tidal flats. In this study, we propose a complete system of large-scale tidal creek morphometry characteristic extraction algorithms. This system improved the intelligence of the node classification and the accuracy of the grading, as well as mitigates the interference of island-shaped tidal creeks in the automatic iterative classification process. And this system solves the problem of low post-processing efficiency due to the existence of a large number of discontinuous tidal creek arcs, and greatly reduces the error in the calculation of morphology characteristics. After accuracy verification, using this algorithm, the classification accuracy of tidal creek nodes is 92.22%, and the order and flow direction information of nearly a thousand tidal creeks can be quickly and automatically defined, and the classification is error-free. The whole process is fully automatic, and it is better than previous algorithms in terms of efficiency and accuracy. It's greatly improved. After quantifying tidal creek morphometry characteristics such as the order, number, length, sinuosity ratio, bifurcation rate, and density, we identified the factors that affect the development of the tidal creek network with respect to its seawater intrusion and vegetation distribution. Our conclusions are as follows: (1) The order and number of the tidal creeks increase from north to south and from west to east. And the average length of the tidal creek increases with the order of the tidal creek. The sinuosity ratio of the tidal creek on the land side is greater than that on the sea side. The density of the order 4 tidal creek system is greater than other tidal creek systems. The differences in these characteristics are mainly related to vegetation distribution and seawater erosion. (2) Seawater erosion promotes rapid changes in the tidal creek sinuosity ratio, bifurcation rate, and density. However, due to the shrinkage of the tidal flat catchment area, the rate of change of the tidal creek morphology characteristics has slowed. However, excessive erosion has narrowed the tidal flat catchment area, resulting in a slowdown in the variation of tidal creek morphology characteristics. The changes in the morphology characteristics of the tidal creeks on the west side of the Old Yellow River Estuary are affected by seawater erosion, showing obvious stages: various morphology characteristics increased rapidly before 2016, and the growth rate slowed after 2016. (3) At present, due to the vegetation gathering on the northern and southern sides of the Yellow River estuary, most of the tidal creeks have achieved equilibrium. The bifurcation ratio of the tidal creek system at all orders showed an increasing trend, but the increasing rate slowed down, from large-scale bifurcation to local etching. Our algorithm represents a significant step forward in the high-precision quantitative detection of tidal creek morphology characteristics, and our results provide evaluable insight into the necessity of monitoring the status and evolution of tidal flats.

Estimation of chlorophyll a content in inland turbidity waters using WorldView-2 imagery: a case study of the Guanting Reservoir, Beijing, China.

Complex optical properties, such as non-pigment suspension and colored dissolved organic matter (CDOM), make it difficult to achieve accurate estimations of remotely sensed chlorophyll a (Chla) content of inland turbidity. Recent attempts have been made to estimate Chla based on red and near-infrared regions where non-pigment suspension and CDOM have little effect on water reflectance. The objective of this study is to validate the applicability of WV-2 imagery with existing effective estimation methods from MERIS when estimating Chla content in inland turbidity waters. The correlation analysis of measured Chla content and WV-2 imagery bands shows that the Chla sensitive bands of WV-2 are red edge, NIR 1, and NIR 2. The coastal band is designed for seawater Chla detection. However, the high correlation with turbidity data and low correlation with Chla made coastal band unsuitable for estimating Chla in inland waters. The high-resolution water body images were extracted by combining the spectral products (NDWI) with the spatial morphological products (sobel edge detection). The estimation results show that the accuracy of the single band and NDCI is not as good as the two-band method, three-band method, stepwise regression algorithm (SRA) and support vector machines (SVM). The SVM estimation accuracy was the highest with an R2, RMSE, and URMSE of 0.8387, 0.4714, and 19.11%, respectively. This study demonstrates that the two-band and three-band methods are effective for estimating Chla in inland water for WV-2 imagery. As a high-precision estimation method, SVM has great potential for inland turbidity water Chla estimation.

Fine Particulate Matter Pollution and Hospital Admissions for Respiratory Diseases in Beijing, China.

Fine particulate matter has become the premier air pollutant of Beijing in recent years, enormously impacting the environmental quality of the city and the health of the residents. Fine particles with aerodynamic diameters of 0~0.3 µm, 0.3~0.5 µm, and 0.5~1.0 µm, from the yeasr 2007 to 2012, were monitored, and the hospital data about respiratory diseases during the same period was gathered and calculated. Then the correlation between respiratory health and fine particles was studied by spatial analysis and grey correlation analysis. The results showed that the aerial fine particulate matter pollution was mainly distributed in the Zizhuyuan sub-district office. There was a certain association between respiratory health and fine particles. Outpatients with respiratory system disease in this study area were mostly located in the southeastern regions (Balizhuang sub-district office, Ganjiakou sub-district office, Wanshoulu sub-district office, and Yongdinglu sub-district office) and east-central regions (Zizhuyuan sub-district office and Shuangyushu sub-district office) of the study area. Correspondingly, PM1 (particulate matter with aerodynamic diameter smaller than 1.0 um) concentrations in these regions were higher than those in any other regions. Grey correlation analysis results showed that the correlation degree of the fine particle concentration with the number of outpatients is high, and the smaller fine particles had more obvious effects on respiratory system disease than larger particles.

Dustfall Heavy Metal Pollution During Winter in North China.

In order to study heavy metal pollution in dustfall during Winter in North China, forty-four dustfall samples were collected in North China Region from November 2013 to March 2014. Then forty trace elements content were measured for each sample by inductively coupled plasma-mass spectrometry. Finally, the contamination characteristics of the main heavy metals were studied through a multi-method analysis, including variability analysis, Pearson correlation analysis and principal component analysis. Results showed that the relative contents of cadmium (Cd), zinc (Zn), copper (Cu), bismuth (Bi), lead (Pb) exceeded the standards stipulated in Chinese soil elements background values by amazing 4.9 times. In this study, conclusions were drawn that dustfall heavy metal pollution in the region was mainly caused by transport pollution, metallurgy industrial pollution, coal pollution and steel industrial pollution.

[Estimating total nitrogen content in reclaimed water based on hyperspectral reflectance information from emergent plants: a case study of Mencheng Lake Wetland Park in Beijing, China].

Hyperspectral reflectance information is a crucial method to detect total nitrogen content in plant leaves, meanwhile, vegetation nitrogen content has a strong relationship with nitrogen in water. Taking Mencheng Lake Wetland Park supplied with reclaimed water as study area, the vegetation hyperspectral data (Phragmites australis and Typha angustifolia), and the content of total nitrogen in water were detected to investigate the feasibility of estimating total nitrogen content in reclaimed water based on hyperspectral reflectance information from emergent plants. We established simple linear regression model, stepwise multiple linear regression model and partial least square regression model based on four hyperspectral indices (spectral indices, normalized difference indices, trilateral parameters, absorption feature parameters), respectively. The accuracy of these models was coefficient of determination (R2) and root mean square error (RMSE). The results showed that stepwise multiple linear regression model and partial least square regression model predicted more accurately than simple linear regression model, and the accuracy of prediction models based on P. australis reflectance spectra was higher than those on T. angustifolia. Partial least square regression model was the most useful explorative tool for unraveling the relationship between spectral reflectance of P. australis and total nitrogen content in water with R2 of 0.854 and RMSE of 0.647. 500-700 nm was the best band range for detecting water total nitrogen content. The reflectance ratio of green peak and red valley could be effectively predicted by the absorption feature parameters.

[Study on influence of traffic and meteorological factors on inhalable particle matters of different size].

To study the effects of meteorological and traffic factors on the PM2.5 and PM10 concentrations, 28 samples were taken in the Third Ring Road of Beijing, and dust fall weight, velocity of vehicle, traffic volume, temperature, humidity, wind speed, PM2.5 and PM10 concentration data were collected for these samples. Analysis of the collected data on dust fall weight indicated that the traffic had a significant impact on the air quality. The average dust fall weights in the road and away from the traffic source were 0. 284g and 0. 016 g, respectively. The results of the partial experiment indicated that concentrations of PM2.5 and PM10 in residential areas were lower than those in road, furthermore, the PM2.5 at night was often higher than that during daytime, and the mean values of the difference in PM2.5 and PM10 were 101074 n.(cf)-1 and 15386 n.(cf)-1, respectively. Through analysis using the best subset prediction model, it was indicated that PM2.5 and PM10 were both most significantly influenced by temperature and humidity, followed by wind speed, velocity of vehicle and traffic volume. Comparing with PM10, the velocity of vehicle, traffic volume and wind speed had a more significant influence on PM2.5.

[Spatial distribution of inhalable particulate and association with respiratory disease in Beijing City].

Inhalable particulate has become the premier pollutant of Beijing, which has enormous influence on the environmental quality of the city and health of the residents. Inhalable particle pollutants (particulate matter of 0.3, 0.5, 3.0 and 5.0 microm) during the heating period and the non-heating period in 2008 and 2009 were collected, and spatial analysis was used to study the spatial distribution of each pollutant. Meanwhile, the hospital data about respiratory disease during the same time was gathered and counted. Then the relativity between inhalable particulate pollutants and respiratory disease was studied by grey correlation analysis on the base of regression analysis. The results showed that spatial distribution of fine particle was diverse but the pattern of coarse particle was similar. There was certain association between respiratory disease and inhalable particle pollutants. Heating period was the highest incidence period of respiratory disease. The prevalence of respiratory disease was higher in heating period than non-heating period. The concentration of fine particle was higher than that of coarse particle both in heating and non-heating periods, and fine particle had more effects on the respiratory system disease than coarse particle.

[Typical plant spectral characteristics analysis in wild duck lake along water environment gradient].

Typical submerged plants, floating plants, emerged plants, hygrophyte plants, and mesophyte plants were chosen, and derivative method and continuum removal method were used to analyze the spectral characteristics and changing trend of plants along water environment gradient. Emerged plants and hygrophyte plants have the highest reflectance value; floating plants have lower value, while submerged plants take the lowest reflectance value due to the effect of water surface. Derivative method could emphasize the changed trends of original spectral curve, thus more characteristic bands could take on. Spectral curves reached the fastest increasing points around 520 and 710 nm, which could be considered as characteristics bands to distinguish submerged plants and others. Emerged plants and hygrophyte plants have the peak green value. According to water environment gradient from high to low, the red edges of submerged plants, floating plants and emerged plants increase, while hygrophyte plants and mesophyte plants have lower red edge value. Original spectral curves were translated to absorption curves by continuum removal, the absorption depth changes from low to high as follows: submerged plants < floating plants < merged plants < hygrophyte plants, while that is lower for mesophyte plants compared to hygrophyte plants. Absorption area increased along water environment gradient from high to low except mesophyte plants.