Soil moisture has a strong impact on the fluorescence intensity of PAHs, which is undoubtedly posing a challenge for the development of rapid real-time fluorescence detection technology of PAHs in soil. In this work, NIR diffuse reflectance spectroscopy was used to correct the fluorescence spectra of PAHs in order to reduce the effect of the soil moisture. To establish the correction method, eight soil samples with different moisture contents and a given phenanthrene concentration (8 mg/g) were prepared. The fluorescence and NIR diffuse reflectance spectra were collected for of all samples. It was found that the fluorescence spectra of the soil samples that vary with the moisture content together with the NIR diffuse reflectance spectra were considered for the correction of the fluorescence intensity of phenanthrene related to the moisture content. The results showed that the ratio of the fluorescence intensity at 384 nm to the NIR diffuse reflectance spectrum absorbance at 5184 cm⁻¹ can be used as a correction factor to reduce the effect of the soil moisture on the fluorescence intensity of phenanthrene in the soil. The validity of the correction method was verified by the quantitative analysis of PAHs with different concentrations and soil moisture contents. The results showed better linearity between the fluorescence intensity and the concentration of PAHs after the correction (with a correlation coefficient R of 0.99) than before the correction (with R of 0.86). The relative prediction errors for three unknown samples decreased from 19%, 51% and 40% before the correction to 5%, 13% and 0.44% after the correction, respectively, indicating the feasibility of the detection of PAHs in the soil by the combination of fluorescence and NIR diffuse reflectance spectroscopy.

Dissolved oxygen (DO) is an effective indicator for water pollution. However, since DO is a non-optically active parameter and has little impact on the spectrum captured by satellite sensors, research on estimating DO by remote sensing at multiple spatiotemporal scales is limited. In this study, the support vector regression (SVR) models were developed and validated using the remote sensing reflectance derived from both Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data and synchronous DO measurements (N = 188) and water temperature of Lake Huron and three other inland waterbodies (N = 282) covering latitude between 22–45 °N. Using the developed models, spatial distributions of the annual and monthly DO variability since 1984 and the annual monthly DO variability since 2000 in Lake Huron were reconstructed for the first time. The impacts of five climate factors on long-term DO trends were analyzed. Results showed that the developed SVR-based models had good robustness and generalization (average R² = 0.91, root mean square percentage error = 2.65%, mean absolute percentage error = 4.21%), and performed better than random forest and multiple linear regression. The monthly DO estimates by Landsat and MODIS data were highly consistent (average R² = 0.88). From 1984 to 2019, the oxygen loss in Lake Huron was 6.56%. Air temperature, incident shortwave radiation flux density, and precipitation were the main climate factors affecting annual DO of Lake Huron. This study demonstrated that using SVR-based models, Landsat and MODIS data could be used for long-term DO retrieval at multiple spatial and temporal scales. As data-driven models, combining spectrum and water temperature as well as extending the training set to cover more DO conditions could effectively improve model robustness and generalization.

Herein, we report the optimization of nitrogen (N) doping in TiO₂ nanotubes to achieve the enhanced photocatalytic efficiencies in degradation of dye and H₂ gas evolution under solar light exposure. TiO₂ nanotubes have been produced via hydrothermal process and N doping has been tuned by varying the concentration of urea, being the source for N, by solid-state dispersion process. The structural analysis using XRD showed the characteristic occupancy of N into the structure of TiO₂ and the XPS studies showed the existence of Ti–N–Ti network in the N-doped TiO₂ nanotubes. The obtained TEM images showed the formation of 1D tube-like structure of TiO₂. Diffuse reflectance UV–Vis absorption spectra demonstrated that the N-doped TiO₂ nanotubes can efficiently absorb the photons of UV–Vis light of the solar light. The optimized N-doped TiO₂ nanotubes (TiO₂ nanotubes vs urea @ 1:1 ratio) showed the highest degradation efficiency over methyl orange dye (∼91% in 90 min) and showed the highest rate of H₂ evolution (∼19,848 μmol h⁻¹.g⁻¹) under solar light irradiation. Further, the recyclability studies indicated the excellent stability of the photocatalyst for the durable use in both the photocatalytic processes. The observed efficiency was ascribed to the optimized doping of N-atoms into the lattices of TiO₂, which enhanced the optical properties by forming new energy levels of N atoms near the valence band maximum of TiO₂, thereby increased the overall charge separation and recombination resistance in the system. The improved reusability of photocatalyst is attributed to the doping-induced structural stability in N-doped TiO₂. From the observed results, it has been recognized that the established strategy could be promising for synthesizing N-doped TiO₂ nanotubes with favorable structural, optical and photocatalytic properties towards dye degradation and hydrogen production applications.

In this study, size-fractionated particulate matters (PM) down to ultrafine (PM₀.₁) particles were collected using a cascade air sampler with a PM₀.₁ stage, in Hat Yai city, Songkhla province, southern Thailand during the year 2018. The particle-bound carbonaceous aerosols (CA) as elemental carbon (EC) and organic carbon (OC) were quantified with the thermal/optical reflectance method following the IMPROVE_TOR protocol. The concentrations of different temperature carbon fractions (OC1-OC4, EC1-EC3 and PyO) in the size-fractionated PM were evaluated to discern OC and EC correlations as well as those between char-EC and soot-EC. The results showed that biomass burning, motor vehicle, and secondary organic aerosols (SOC) all contributed to the size-fractionated PM. The OC/EC ratios ranged from 2.90 to 4.30 over the year, with the ratios of PM₂.₅₋₁₀ being the highest, except during the open biomass burning period. The concentration of CA was found to increase during the pre-monsoon season and had its peak value in the PM₀.₅₋₁.₀ fraction. The long-range transport of PMs from Indonesia, southwest of Thailand toward southern Thailand became more obvious during the pre-monsoon season. Transported plumes from biomass burning in Indonesia may increase the concentration of OC and EC both in the fine (PM₀.₅₋₁.₀ and PM₁.₀₋₂.₅) and coarse (PM₂.₅₋₁₀ and PM>₁₀) fractions. The OC fraction in PM₀.₁ was also shown to be significantly affected by the transported plumes during the pre-monsoon season. Good OC and EC correlations (R² = 0.824–0.915) in the fine particle fractions indicated that they had common sources such as fossil fuel combustion. However, the lower and moderate correlations (R² = 0.093–0.678) among the coarser particles suggesting that they have a more complex pattern of emission sources during the dry and monsoon seasons. This indicates the importance of focusing emission control strategies on different PM particle sizes in southern Thailand.

The continuous release of persistent iron-cyanide (Fe-CN) complexes from various industrial sources poses a high hazard to the environment and indicates the necessity to analyze a considerable amount of samples. Conventional flow injection analysis (FIA) is a time and cost consuming method for cyanide (CN) determination. Thus, a rapid and economic alternative needs to be developed to quantify the Fe-CN complexes. 52 soil samples were collected at a former Manufactured Gas Plant (MGP) site in order to determine the feasibility of diffuse reflectance infrared Fourier spectroscopy (DRIFTS). Soil analysis revealed CN concentrations in a range from 8 to 14.809 mg kg−1, where 97% was in the solid form (Fe4[Fe(CN)6]3), which is characterized by a single symmetrical CN band in the range 2092–2084 cm−1. The partial least squares (PLS) calibration-validation model revealed IR response to CNtot which exceeds 2306 mg kg−1 (limit of detection, LOD). Leave-one-out cross-validation (LOO-CV) was performed on soil samples, which contained low CNtot (<900 mg kg−1). This improved the sensitivity of the model by reducing the LOD to 154 mg kg−1. Finally, the LOO-CV conducted on the samples with CNtot > 900 mg kg−1 resulted in LOD equal to 3751 mg kg−1. It was found that FTIR spectroscopy provides the information concerning different CN species in the soil samples. Additionally, it is suitable for quantifying Fe-CN species in matrixes with CNtot > 154 mg kg−1. Thus, FTIR spectroscopy, in combination with the statistical approach applied here seems to be a feasible and quick method for screening of contaminated sites.

In urban areas, the demand for local assessment of air quality is high. The existing monitoring stations cannot fulfill the needs. This study assesses the potential of hyperspectral tree leaf reflectance for monitoring traffic related air pollution. Hereto, 29 Carpinus betulus saplings were exposed to an environment with either high or low traffic intensity. The local air quality was estimated by leaf saturation isothermal remanent magnetization (SIRM). The VIS-NIR leaf reflectance spectrum (350–2500 nm) was measured using a handheld AgriSpec spectroradiometer (ASD Inc.). Secondary, leaf chlorophyll content index (CCI), specific leaf area (SLA) and water content (WC) were determined. To gain insight in the link between leaf reflectance and air quality, the correlation between SIRM and several spectral features was determined. The spectral features that were tested are plain reflectance values, derivative of reflectance, two-band indices using the NDVI formula and PCA components. Spectral reflectance for wavelength bands in the red and short wave IR around the red edge, were correlated to SIRM with Pearson correlations of up to R = −0.85 (R² = 0.72). Based on the spectral features and combinations thereof, binomial logistic regression models were trained to classify trees into high or low traffic pollution exposure, with classification accuracies up to 90%. It can be concluded that hyperspectral reflectance of C. betulus leaves can be used to detect different levels of air pollution within an urban environment.

Rising tropospheric ozone concentrations in Asia necessitate the breeding of adapted rice varieties to ensure food security. However, breeding requires field-based evaluation of ample plant material, which can be technically challenging or very costly when using ozone fumigation facilities. The chemical ethylenediurea (EDU) has been proposed for estimating the effects of ozone in large-scale field applications, but controlled experiments investigating constitutive effects on rice or its suitability to detect genotypic differences in ozone tolerance are missing. This study comprised a controlled open top chamber experiment with four treatments (i) control (average ozone concentration 16 ppb), (ii) control with EDU application, (iii) ozone stress (average 77 ppb for 7 h daily throughout the season), and (iv) ozone stress with EDU application. Three contrasting rice genotypes were tested, i.e. the tolerant line L81 and the sensitive Nipponbare and BR28. The ozone treatment had significant negative effects on plant growth (height and tillering), stomatal conductance, SPAD value, spectral reflectance indices such as the normalized difference vegetation index (NDVI), lipid peroxidation, as well as biomass and grain yields. These negative effects were more pronounced in the a priori sensitive varieties, especially the widely grown Bangladeshi variety BR28, which showed grain yield reductions by 37 percent. EDU application had almost no effects on plants in the absence of ozone, but partly mitigated ozone effects on foliar symptoms, lipid peroxidation, SPAD value, stomatal conductance, several spectral reflectance parameters, panicle number, grain yield, and spikelet sterility. EDU responses were more pronounced in sensitive genotypes than in the tolerant L81. In conclusion, EDU had no constitutive effects on rice and partly offset negative ozone effects, especially in sensitive varieties. It can thus be used to diagnose ozone damage in field grown rice and for distinguishing tolerant (less EDU-responsive) and sensitive (more EDU-responsive) genotypes.

The xenobiotic nature and lack of degradability of polymeric materials has resulted in vast levels of environmental pollution and numerous health hazards. Different strategies have been developed and still more research is being in progress to reduce the impact of these polymeric materials. This work aimed to isolate and characterize polyester polyurethane (PU) degrading fungi from the soil of a general city waste disposal site in Islamabad, Pakistan. A novel PU degrading fungus was isolated from soil and identified as Aspergillus tubingensis on the basis of colony morphology, macro- and micro-morphology, molecular and phylogenetic analyses. The PU degrading ability of the fungus was tested in three different ways in the presence of 2% glucose: (a) on SDA agar plate, (b) in liquid MSM, and (c) after burial in soil. Our results indicated that this strain of A. tubingensis was capable of degrading PU. Using scanning electron microscopy (SEM), we were able to visually confirm that the mycelium of A. tubingensis colonized the PU material, causing surface degradation and scarring. The formation or breakage of chemical bonds during the biodegradation process of PU was confirmed using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy. The biodegradation of PU was higher when plate culture method was employed, followed by the liquid culture method and soil burial technique. Notably, after two months in liquid medium, the PU film was totally degraded into smaller pieces. Based on a comprehensive literature search, it can be stated that this is the first report showing A. tubingensis capable of degrading PU. This work provides insight into the role of A. tubingensis towards solving the dilemma of PU wastes through biodegradation.

The objective of this paper is to give an account of the evaluation of the effect of urban habitat quality on dorsi-ventral leaf reflectance asymmetry to bio-monitor urban habitat pollution. Reflectance in the RGB bands of a reflex camera is measured at the adaxial and abaxial sides of Carpinus betulus L. leaves for two contrasting urban habitats, e.g.; suburban green and industrial habitats in the city of Gent (Belgium). Abaxial leaf reflectance is consistently higher than adaxial leaf reflectance. We quantified leaf dorsi-ventral reflectance asymmetry with a newly defined Normalized Dorsi-ventral Asymmetry Index (NDAI). The NDAI is significantly higher in industrial habitats as opposed to suburban green ones. Our optical observations indicate that changes in Carpinus betulus L. leaf morphology are related to urban habitat quality. Hence, we suggest that leaf dorsi-ventral reflectance asymmetry allows the estimation of the magnitude and spatial extent of environmental pollution in urban environments.