With rapid economic growth, urbanization and industrialization, fine particulate matter with aerodynamic diameters ≤ 2.5 µm (PM2.5) has become a major pollutant and shows adverse effects on both ...human health and the atmospheric environment. Many studies on estimating PM2.5 concentrations have been performed using statistical regression models and satellite remote sensing. However, the accuracy of PM2.5 concentration estimates is limited by traditional regression models; machine learning methods have high predictive power, but fewer studies have been performed on the complementary advantages of different approaches. This study estimates PM2.5 concentrations from satellite remote sensing-derived aerosol optical depth (AOD) products, meteorological data, terrain data and other predictors in 2015 in Shaanxi, China, using a combined genetic algorithm-support vector machine (GA-SVM) method, after which the spatial clustering pattern was explored at the season and year levels. The results indicated that temperature (r = −0.684), precipitation (r = −0.602) and normalized difference vegetation index (NDVI) (r = −0.523) were significantly negatively correlated with the PM2.5 concentration, while AOD (r = 0.337) was significantly positively correlated with the PM2.5 concentration. Compared to conventional land use regression (LUR) and SVM models and previous related studies, the GA-SVM method demonstrated a significantly better prediction accuracy of PM2.5 concentration, with a higher 10-fold cross-validation coefficient of determination (R2) of 0.84 and lower root mean square error (RMSE) and mean absolute error (MAE) of 12.1 μg/m3 and 10.07 μg/m3, respectively. Y-scrambling test shows that the models have no chance correlation. The central and southern parts of Shaanxi have high PM2.5 concentrations, which are mainly due to the pollutant emissions and meteorological and topographical conditions in those areas. There was a positive spatial agglomeration characteristic of regional PM2.5 pollution, and the spatial spillover effect of PM2.5 pollution for seasonal and annual variations does exist. In general, the GA-SVM method is robust and accurately estimates PM2.5 concentrations via a novel modeling framework application and high-quality spatiotemporal information. It also has great significance for the exploration of PM2.5 pollution estimation and high-precision mapping methods, especially early warning in high-risk areas. Finally, the prevention and control of atmospheric pollution should take pollution control measures from major cities and surrounding cities, and focus on the joint pollution control measures for plain cities.
•The combined genetic algorithm-support vector machine is a novel and robust method in estimating PM2.5 concentrations.•GA-SVM approach outperforms conventional land use regression model and SVM models and previous related studies.•Seasonal variation and spatial autocorrelation of PM2.5 concentrations in Shaanxi is evaluated.
•The boundary conditions of Fu's equations in Budyko Framework are highlighted.•Equilibrium evaporation coefficient was adjusted by Fu's equations' interrelation.•We improved the complementary ...principle function for better evaporation estimate.•Our blended function substantially enhances annual E estimation performance.•The improved method shows the highest improvement of daily E in extreme climates.
The complementary principle function presents a framework for estimating evaporation but faces long-term challenges in calibration with a free parameter-equilibrium evaporation coefficient. The blending the evaporation precipitation ratio with complementary principle function is proposed to provide a physical basis for estimation of the equilibrium evaporation coefficient within the Budyko framework; however, it overlooks the limited possible maximum evaporation and precipitation condition from Fu’s equations. In this study, we expanded the numerical ambiguity boundary conditions of Fu’s equations and introduced a new parameter γc into the blended function to fully capture the environmental conditions, aiming to mitigate errors related to extreme climates. The result indicated our improved blended function performed better than the original function. Compared to the original function, the estimated annual average evaporation across stations improved from 0.12 to 0.57 in coefficient of determination (R2) and from 322.83 mm to 172.47 mm in Root Mean Square Error. For daily evaporation estimation, the Nash-Sutcliffe Efficiency coefficient (NSE) increased from 0.32 to 0.47 and R2 increased from 0.38 to 0.48 in all validation sites. The modified blended method showed a better performance in most of the AmeriFLUX stations, especially with the highest improvement in extremely dry and wet sites. Our new approach represents a promising evaporation method in extreme climate conditions and provides support for future research to identify the rigorous equation constraints of Budyko equations.
•A novel vector length stability index (VLSI or wVLSI) was introduced.•The VLSI or wVLSI is a naturally normalized, dimensionless index.•The VLSI or wVLSI would be a substitute for commonly used MWD.
...Soil aggregate stability is an important soil characteristic which can represent the improvement of soil structure after revegetation. Due to the high heterogeneity of soil, large-scale sampling is usually necessary to estimate the spatial variation of aggregate stability across landscapes. Although there are many methods and corresponding indices for analysis of aggregate stability, many of them are not suitable for investigations with a large number of samples due to time-consuming experimental practices. To avoid unnecessary costs of time and labor in the long-term land degradation and restoration monitoring across large regional scales, simple indices of aggregate stability would help monitoring across large regional scales. For this reason, we introduced a new, simple, and normalized index, the vector length stability index (VLSI) and its weighted form (wVLSI) to describe soil aggregate stability. The VLSI shares key information of aggregate size distribution with mean weight diameter (MWD), but it is naturally normalized and dimensionless. This new index was tentatively tested to describe soil aggregate stability of the 0–30 cm soil layers under artificial plantations, natural grassland, abandoned farmland, and farmland in production in a small watershed located in the Loess Plateau of China. The results showed that the aggregate stability of the 0–20 cm layers in abandoned farmland could be recovered near to the condition under artificial plantations just after 2-year abandonment, but the aggregate stability hardly changed in the 20–30 cm layer. The aggregate stability of the 0–10 cm layer in natural recovered grassland is close to that in top soil layers under artificial plantations, but the stability in the 10–30 layers appeared as low as that in farmland. Because of its simple form and low data requirements, the VLSI could be an alternative efficient tool for soil aggregate stability evaluation when a large number of samples are needed.
Information about groundwater residence times is essential for evaluating appropriate groundwater abstraction rates and aquifer vulnerabilities and hence for sustainable groundwater management in ...general. Naturally occurring radionuclides are suitable tools for related investigations. While the applicability of several long-lived radionuclides for the investigation of long-term processes has been demonstrated frequently, residence times of less than one year are only scarcely discussed in the literature. That is due to the rather small number of applicable radionuclides that show adequately short half-lives. A promising approach for investigating sub-yearly residence times applies radioactive sulphur. 35S is continuously produced in the upper atmosphere from where it is transferred with the rain to the groundwater. As soon as the water enters the subsurface its 35S activity concentration decreases with an 87.4 day half-life. This makes 35S suitable for investigating sub-yearly groundwater residence times. However, the low 35S activities in natural waters require sulphate pre-concentration for 35S detection by means of liquid scintillation counting (LSC). That is usually done by sulphate extraction from large water samples with an anion-exchange resin (Amberlite IRA400, Cl-form), elution from the resin with NaCl, and precipitation as BaSO4. Our study aimed at optimizing the standard sample preparation procedure by avoiding the laborious precipitation step. We suggest (i) sulphate extraction using the exchange resin Amberlite IRA67 (OH-form), (ii) elution with ammonium hydroxide, (iii) evaporation of the eluate and (iv) dissolving the resulting dry precipitate in 2 ml H2O. In contrast to the standard approach our method results in a final sample solution of low ionic strength, which allows applying the water miscible scintillation cocktail Hionic-Fluor®. Since Hionic-Fluor accepts only aqueous solutions of low ionic strength the approach is applicable for waters with high 35S/32SO42− ratios, i.e., low total sulphate sample loads (e.g. rainwater).
•Sustainable groundwater resources management requires knowledge of groundwater ages.•35S has great potential as tracer for detecting groundwater ages of less than one year.•State-of-the-art approach for 35S liquid scintillation counting includes BaSO4 precipitation.•An approach is introduced that allows avoiding the labor-intensive BaSO4 precipitation step.•The approach is applicable for low-sulphate waters (loads of up to about 100 mg).
The knowledge of groundwater residence times in (vulnerable) aquifers is essential for the sustainable management of the associated groundwater resources. A powerful tool for related investigations ...is the application of naturally occurring radioisotopes as water age indicators. However, due to the limited number of suitable (i.e. omnipresent, short-lived and easily detectable) radionuclides only few studies focus on groundwater ages below one year. A natural radionuclide that does have the potential to cover this time range is 35S (87.4 day half-life). 35S is continually produced in the upper atmosphere and transferred with the rain to the groundwater. Since no natural sources of 35S exist in the subsurface the decrease of the 35S activity concentration in such young groundwater can be used for the determination of its age. Still, 35S activities in precipitation (and hence even more in groundwater) are very low and necessitate appropriate analytical protocols based on liquid scintillation counting (LSC). This turns out to be challenging due to the required large sample volumes and due to potentially high SO42− loads of the samples, both limiting the range of possible applications of 35S as indicator for short groundwater residence times. In the paper we present an improved straightforward LSC based approach for the detection of 35S in natural water samples. We recommend using Insta-Gel Plus as scintillation cocktail for allowing a homogeneous suspension of 35S-containing BaSO4 in the cocktail. The recommended improvements in instrument setting concern the LSC (TriCarb 3170 Tr/SL) counting window, the pulse decay discriminator setting and the delay before burst setting. The settings allow measuring low activity concentrations of 35S, which was previously pre-concentrated from natural water samples, containing SO42− loads of up to 1500 mg with a reasonably high statistical reliability.
•Sustainable groundwater resources management requires knowledge of groundwater ages.•Naturally occurring radioisotopes are suitable as water age indicators.•35S has great potential to cover the time of up to one year.•Appropriate protocols for liquid scintillation counting (LSC) are required.•Suggestions are given for optimized LSC counting window, PDD setting and DBB value.
Blind-testing is an important tool that should be used by all analytical fields as an approach for validating method. Several fields do this well outside of archaeological science. It is unfortunate ...that many applied methods do not have a strong underpinning built on, what should be considered necessary, blind-testing. Historically lithic microwear analysis has been subjected to such testing, the results of which stirred considerable debate. However, putting this aside, it is argued here that the tests have not been adequately exploited. Too much attention has been focused on basic results and the implications of those rather than using the tests as a powerful tool to improve the method. Here the tests are revisited and reviewed in a new light. This approach is used to highlight specific areas of methodological weakness that can be targeted by developmental research. It illustrates the value in having a large dataset of consistently designed blind-tests in method evaluation and suggests that fields such as lithic microwear analysis would greatly benefit from such testing. Opportunity is also taken to discuss recent developments in quantitative methods within lithic functional studies and how such techniques might integrate with current practices.
•A review of blind-tests in lithic microwear analysis to-date.•Presentation of a framework for blind-test use in the development of technique.•Examples of weak areas within the method.•Suggestions for the integration of traditional and novel quantitative methods.•Examples of novel quantitative techniques improving areas of weakness.
•Application of solute geothermometer often yield large uncertainties (up to 200 K).•Improvement approach of SiO2 and Na-K geothermometers using laboratory experiments and numerical ...modeling.•Correction of site-dependet effects (reservoir lithology, pH value, dilution).•Strongly converging SiO2 and Na-K temperatures (≤10 K).
Solute geothermometry often leads to a broad range and often inconsistent calculated reservoir temperatures, in particular when exploring geothermal systems, where only limited information (geology, borehole data etc.) is available. The application of different Na-K and SiO2 geothermometer, the most widely used methods, not uncommonly lead to deviations of results by up to 200 K for one sample.
In this study, the most effective interfering factors for these geothermometer applications are identified. A multi-step approach is proposed, combining experimental and numerical methods with specific fluid characterization to quantify these factors and to transfer these findings to the natural system enabling the correction of temperatures to realistic in-situ values.
Taking into account dilution with surface water, a chlorofluorocarbon concentration based mixing model was set up to correct analysed SiO2 concentrations to original in-situ concentrations. A numerical model was used to determine the in-situ pH, which is highly sensitive to silica solubility. Results from long-term laboratory equilibration experiments were evaluated to identify the reservoir type dependent equilibrated SiO2 polymorph.
In the case of the Na-K geothermometer, it is shown that the Na+/K+ concentration ratio in fluids is obviously not unequivocally controlled by temperature but is also dependent upon reservoir rock composition. Thus, different reservoir lithologies lead to different equilibration states in terms of Na+/K+. This is obviously one reason for the existence of the large number of different Na-K geothermometers. By modelling the stability of the Na+/K+ ratio governing feldspars, albite and orthoclase, we suggest a method that reveals the Na+/K+ equilibration state for each fluid supporting the allocation of the appropriate geothermometer equation.
The improvement procedure is demonstrated in a case study evaluating fluid data of geothermal springs from the Villarrica geothermal system, Southern Chile. It is shown that initially highly scattered results strongly converge after corrections, leading to a substantial improvement in in-situ temperature estimations with small deviations of ≤10 K between SiO2 and Na-K geothermometers. Also absolute temperature calculated for each spring in the study area, ranging from 84 to 184 °C agree well (within ΔT <20 K) with results of multicomponent geothermometry temperatures reported in a previous work.
Subfossil chironomids are regarded as a useful biological proxy for palaeoenvironmental research, but picking chironomid head capsules from aquatic sediments is extremely time-consuming. This is ...often the case for finding and isolating small head capsules from the deflocculated sediment. In this study, two stains (aniline blue and cotton blue) were used to dye chironomid head capsules in lake and peat sediments to improve the traditional pretreatment method and boost the picking efficiency. The results suggested that: (1) there were sharp contrasts between chironomids and residues after staining, which could shorten picking time for both lake and peat samples; (2) different parts of head capsules showed distinctive colour in stained samples and thus facilitated identification and taxonomy of subfossil chironomids; (3) the dyeing effects of two stains were comparable and no significant effect of staining on chironomid composition has been observed compared with unstained samples. This study demonstrates that aniline blue and cotton blue stain can promote picking efficiency of subfossil chironomids, and can be widely applied to pretreatment of sedimentary chironomids in palaeoenvironmental studies on lakes and peatlands.
To determine the amount of the explosives 1,3-dinitrobenzene, 2,4-dinitrotoluene, 2,4,6-trinitrotoluene, and its metabolites in marine samples, a toolbox of methods was developed to enhance sample ...preparation and analysis of various types of marine samples, such as water, sediment, and different kinds of biota. To achieve this, established methods were adapted, improved, and combined. As a result, if explosive concentrations in sediment or mussel samples are greater than 10 ng per g, direct extraction allows for time-saving sample preparation; if concentrations are below 10 ng per g, techniques such as freeze-drying, ultrasonic, and solid-phase extraction can help to detect even picogram amounts. Two different GC-MS/MS methods were developed to enable the detection of these explosives in femtogram per microliter. With a splitless injector, limits of detection (LODs) between 77 and 333 fg/µL could be achieved in only 6.25 min. With the 5 µL programmable temperature vaporization-large volume method (PTV-LVI), LODs between 8 and 47 fg/µL could be achieved in less than 7 min. The detection limits achieved by these methods are among the lowest published to date. Their reliability has been tested and confirmed by measuring large and diverse sample sets.
The storm water management model (SWMM) is widely used in urban rainfall runoff simulations, but there are no clear rules for the division of its sub catchment areas. At present, the popular sub ...catchment area division method takes the average slope as the slope parameter of the sub catchment area, which brings errors to the model in mechanism. Based on the current method, this paper proposes a new method to further subdivide the sub catchment area of the SWMM model, according to the Digital Elevation Model (DEM) data of underlying surface, slope and aspect information. By comparing with the previous methods, it was found that the division method based on slope and aspect can make the setting of model parameters and hydraulic exchange conditions clearer, and improve the accuracy of the model on a certain level.
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