Characterization of CDOM in saline and freshwater lakes across China using spectroscopic analysis

Colored dissolved organic matter (CDOM) is a major component of DOM in waters, and plays a vital role in carbon cycling in inland waters. In this study, the light absorption and three-dimensional excitation-emission matrix spectra (EEMs) of CDOM of 936 water samples collected in 2014–2017 from 234 lakes in five regions across China were examined to determine relationships between lake water sources (fresh versus saline) and their fluorescence/absorption characteristics. Results indicated significant differences regarding DOC concentration and aCDOM(254) between freshwater (6.68 mg C L−1, 19.55 m-1) and saline lakes (27.4 mg C L−1, 41.17 m-1). While humic-like (F5) and fulvic-like (F3) compounds contributed to CDOM fluorescence in all lake waters significantly, their contribution to total fluorescence intensity (FT) differed between saline and freshwater lakes. Significant negative relationships were also observed between lake altitude with either F5 (R2 = 0.63, N = 306) or FT (R2 = 0.64, N = 306), suggesting that the abundance of humic-like materials in CDOM tends to decrease with increased in lakes altitude. In high-altitude lakes, strong solar irradiance and UV exposure may have induced photo-oxidation reactions resulting in decreased abundance of humic-like substances and the formation of low molecular weight compounds. These findings have important implications regarding our understanding of C dynamics in lacustrine systems and the contribution of these ecosystems to the global C cycle

Dissolved carbon in a large variety of lakes across five limnetic regions in China

Dissolved carbon in lakes play a vital role in the global carbon cycling. The concentration and dynamics of lake dissolved carbon can be influenced by both the surrounding landscape and a combination of physical, chemical and biological processes within the lakes themselves. From 2009 to 2016, we conducted a large-scale assessment of dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) in 249 lakes across a diverse range of climatic, geopedologic, topographical and hydrological conditions in five Chinese limnetic regions: the East Limnetic Region (ELR), the Northeast Limnetic Region (NLR), the Inner Mongolia-Xinjiang Limnetic Region (MXR), the Yungui Limnetic Region (YGR), and the Tibet-Qinghai Limnetic Region (TQR). We found that the density of the organic matter in the soil in the surrounding landscape plays an important role in the DOC and DIC in lake water, as was evidenced by the high DOC and DIC levels in the NLR, where the soil is respectively organically rich. Conditions in the arid and semi-arid environments (i.e. TQR and MXR) have created a number of brackish/saline lakes and here we found that, DOC and DIC levels (median: 21.79 and 93.72 mg/L, respectively) are significantly higher than those in the freshwater lakes (median: 5.80 and 29.38 mg/L). It also appears to be the case that the trophic state of freshwater lakes influences the spatial variation of DOC. This can be seen in the relationships between DOC and trophic state index (TSI) in agriculturally-dominated regions such as the ELR (R2 = 0.59, p < 0.01), NLR (R2 = 0.65, p < 0.001), and YGR (R2 = 0.78, p < 0.001). Additionally, a close relationship between DOC and DIC can be found in lake waters with different trophic states (eutrophic: slp = 0.63, R2= 0.69; mesotrophic: slp = 1.03, R2 = 0.65; oligotrophic: slp = 1.00, R2 = 0.64). This indicates that human activities influence the quantity and quality of dissolved carbon in inland water across China. This study is able to provide insights regarding the potential effects of climate change and changes in land-use upon the amount of dissolved carbon in lake water

Industrial steam consumption analysis and prediction based on multi-source sensing data for sustainable energy development

Centralized heating is an energy-saving and environmentally friendly way that is strongly promoted by the state. It can improve energy utilization and reduce carbon emissions. However, Centralized heating depends on accurate heat demand forecasting. On the one hand, it is impossible to save energy if over producing, while on the other hand, it is impossible to meet the heat demand of enterprises if there is not enough capacity. Therefore, it is necessary to forecast the future trend of heat consumption, so as to provide a reliable basis for enterprises to reasonably deploy fuel stocks and boiler power. At the same time, it is also necessary to analyze and monitor the steam consumption of enterprises for abnormalities in order to monitor pipeline leakage and enterprise gas theft. Due to the nonlinear characteristics of heat load, it is difficult for traditional forecasting methods to capture data trend. Therefore, it is necessary to study the characteristics of heat loads and explore suitable heat load prediction models. In this paper, industrial steam consumption of a paper manufacturer is used as an example, and steam consumption data are periodically analyzed to study its time series characteristics; then steam consumption prediction models are established based on ARIMA model and LSTM neural network, respectively. The prediction work was carried out in minutes and hours, respectively. The experimental results show that the LSTM neural network has greater advantages in this steam consumption load prediction and can meet the needs of heat load prediction

Variations in the light absorption coefficients of phytoplankton, non-algal particles and dissolved organic matter in reservoirs across China

Reservoirs were critical sources of drinking water for many large cities around the world, but progress in the development of large-scale monitoring protocols to obtain timely information about water quality had been hampered by the complex nature of inland waters and the various optical conditions exhibited by these aquatic ecosystems. In this study, we systematically investigated the absorption coefficient of different optically-active constituents (OACs) in 120 reservoirs of different trophic states across five eco-regions in China. The relationships were found between phytoplankton absorption coefficient at 675 nm (aph (675)) and Chlorophyll a (Chla) concentration in different regions (R2:0.60-0.82). The non-algal particle (NAP) absorption coefficient (aNAP) showed an increasing trend for reservoirs with trophic states. Significant correlation (p < 0.05) was observed between chromophoric dissolved organic matter (CDOM) absorption and water chemical parameters. The influencing factors for contributing the relative proportion of OACs absorption including the hydrological factors and water quality factors were analyzed. The non-water absorption budget from our data showed the variations of the dominant absorption types which underscored the need to develop and parameterize region-specific bio-optical models for large-scale assessment in water reservoirs

Data from: Identifying litchi (Litchi chinensis Sonn.) cultivars and their genetic relationships using single nucleotide polymorphism (SNP) markers

Litchi is an important fruit tree in tropical and subtropical areas of the world. However, there is widespread confusion regarding litchi cultivar nomenclature and detailed information of genetic relationships among litchi germplasm is unclear. In the present study, the potential of single nucleotide polymorphism (SNP) for the identification of 96 representative litchi accessions and their genetic relationships in China was evaluated using 155 SNPs that were evenly spaced across litchi genome. Ninety SNPs with minor allele frequencies above 0.05 and a good genotyping success rate were used for further analysis. A relatively high level of genetic variation was observed among litchi accessions, as quantified by the expected heterozygosity (He = 0.305). The SNP based multilocus matching identified two synonymous groups, ‘Heiye’ and ‘Wuye’, and ‘Chengtuo’ and ‘Baitangli 1’. A subset of 14 SNPs was sufficient to distinguish all the non-redundant litchi genotypes, and these SNPs were proven to be highly stable by repeated analyses of a selected group of cultivars. Unweighted pair-group method of arithmetic averages (UPGMA) cluster analysis divided the litchi accessions analyzed into four main groups, which corresponded to the traits of extremely early-maturing, early-maturing, middle-maturing, and late-maturing, indicating that the fruit maturation period should be considered as the primary criterion for litchi taxonomy. Two subpopulations were detected among litchi accessions by STRUCTURE analysis, and accessions with extremely early- and late-maturing traits showed membership coefficients above 0.99 for Cluster 1 and Cluster 2, respectively. Accessions with early- and middle-maturing traits were identified as admixture forms with varying levels of membership shared between the two clusters, indicating their hybrid origin during litchi domestication. The results of this study will benefit litchi germplasm conservation programs and facilitate maximum genetic gains in litchi breeding programs

Data from: Identifying litchi (Litchi chinensis Sonn.) cultivars and their genetic relationships using single nucleotide polymorphism (SNP) markers

Litchi is an important fruit tree in tropical and subtropical areas of the world. However, there is widespread confusion regarding litchi cultivar nomenclature and detailed information of genetic relationships among litchi germplasm is unclear. In the present study, the potential of single nucleotide polymorphism (SNP) for the identification of 96 representative litchi accessions and their genetic relationships in China was evaluated using 155 SNPs that were evenly spaced across litchi genome. Ninety SNPs with minor allele frequencies above 0.05 and a good genotyping success rate were used for further analysis. A relatively high level of genetic variation was observed among litchi accessions, as quantified by the expected heterozygosity (He = 0.305). The SNP based multilocus matching identified two synonymous groups, ‘Heiye’ and ‘Wuye’, and ‘Chengtuo’ and ‘Baitangli 1’. A subset of 14 SNPs was sufficient to distinguish all the non-redundant litchi genotypes, and these SNPs were proven to be highly stable by repeated analyses of a selected group of cultivars. Unweighted pair-group method of arithmetic averages (UPGMA) cluster analysis divided the litchi accessions analyzed into four main groups, which corresponded to the traits of extremely early-maturing, early-maturing, middle-maturing, and late-maturing, indicating that the fruit maturation period should be considered as the primary criterion for litchi taxonomy. Two subpopulations were detected among litchi accessions by STRUCTURE analysis, and accessions with extremely early- and late-maturing traits showed membership coefficients above 0.99 for Cluster 1 and Cluster 2, respectively. Accessions with early- and middle-maturing traits were identified as admixture forms with varying levels of membership shared between the two clusters, indicating their hybrid origin during litchi domestication. The results of this study will benefit litchi germplasm conservation programs and facilitate maximum genetic gains in litchi breeding programs

Spatial Distribution of Diffuse Attenuation of Photosynthetic Active Radiation and Its Main Regulating Factors in Inland Waters of Northeast China

Light availability in lakes or reservoirs is affected by optically active components (OACs) in the water. Light plays a key role in the distribution of phytoplankton and hydrophytes, thus, is a good indicator of the trophic state of an aquatic system. Diffuse attenuation of photosynthetic active radiation (PAR) (Kd(PAR)) is commonly used to quantitatively assess the light availability. The PAR and the concentration of OACs were measured at 206 sites, which covered 26 lakes and reservoirs in Northeast China. The spatial distribution of Kd(PAR) was depicted and its association with the OACs was assessed by grey incidences(GIs) and linear regression analysis. Kd(PAR) varied from 0.45 to 15.04 m−1. This investigation revealed that reservoirs in the east part of Northeast China were clear with small Kd(PAR) values, while lakes located in plain areas, where the source of total suspended matter (TSM) varied, displayed high Kd(PAR) values. The GIs and linear regression analysis indicated that the TSM was the dominant factor in determining Kd(PAR) values and best correlated with Kd(PAR) (R2 = 0.906, RMSE = 0.709). Most importantly, we have demonstrated that the TSM concentration is a reliable measurement for the estimation of the Kd(PAR) as 74% of the data produced a relative error (RE) of less than 0.4 in a leave-one-out cross validation (LOO-CV) analysis. Spatial transferability assessment of the model also revealed that TSM performed well as a determining factor of the Kd(PAR) for the majority of the lakes. However, a few exceptions were identified where the optically regulating dominant factors were chlorophyll-a (Chl-a) and/or the chromophroic dissolved organic matter (CDOM). These extreme cases represent lakes with exceptionally clear waters