The present study has been conducted to determine the surface water quality of urban area in Savar, Dhaka, Bangladesh by determining some water quality parameters (Transparency, Temperature, pH, EC, Eh, DO, TSS, TDS, TS, BOD5, COD, TOC, Cl-, Br-, SO4-2, NO3-, NO2-, PO4-3, TP, HCO3- and Total alkalinity) as well as the status of phytoplankton’s community in the water from two lakes (Tiger Lake and AERE Lake) and one canal (Karnapara Canal). It has been shown that, with exception of BOD and COD, all water quality parameters of AERE Lake in the present study are within the acceptable limits, recommended by local and international standards. Among water quality parameters of Tiger Lake and Karnapara Canal, the concentration of transparency, temperature, EC, DO, TSS, TDS, BOD, COD, TOC, NO2-, and TP exceed the acceptable limits. Organic Pollution Index (OPI) demonstrate that the water bodies are severely polluted by organic matters. R mode Cluster Analysis (CA) suggests that common sources of water quality parameters are industrial, agricultural, and natural. The Principle Component Analysis/Factor Analysis (PCA/FA) identifies two dominant factors, responsible for data structure, explaining 100% of total variance in the data set. The PCA agrees with CA, suggesting that multiple anthropogenic and natural sources are responsible for the water quality parameters. The present study reflects the actual scenario of surface water quality of Savar urban area, thus helping the policy planers and makers of the People’s Republic of Bangladesh to take proper management and abatement strategies for the management of sustainable water resource in Bangladesh.

The properties and metal-binding abilities of dissolved organic matter (DOM) rely on its molecular weight (MW) structure. In this study, the spatial differences of DOM in compositions, MW structures, and binding mechanisms with copper (Cu²⁺) in Dongping Lake were investigated by applying excitation-emission matrix combining parallel factor analysis (EEM-PARAFAC), synchronous fluorescence (SF) spectra, two-dimensional correlation spectra (2D-COS), and Fourier transform infrared (FTIR) spectra. The EDOM for the entrance of the Dawen River and PDOM for the macrophyte-dominated region were divided from DOM of Dongping Lake based on hierarchical clustering analysis (HCA) and principal component analysis (PCA) and were size-fractioned into MW < 500 kDa and <100 kDa fractions. According to EEM-PARAFAC, Dongping Lake was dominated by tryptophan-like substances with MW < 500 kDa. The concentration of PDOM was higher than that of EDOM (p < 0.05). 2D-COS showed that protein-like components preceded humic-like components binding to Cu²⁺ regardless of sample type (215 nm > 285 nm > 310–360 nm). The Cu²⁺ binding capacity of DOM exhibited specific differences in space, components, and molecular weights. The humic-like component 1 (C1) and tryptophan-like component 4 (C4) of PDOM showed stronger binding abilities than those of EDOM. Endogenous tryptophan-like component 4 (C4) had a higher binding affinity for Cu²⁺ than humic-like components (logKₐ: C4 > C1 > C2) in PDOM irrespective of MW. Humic-like components with MW < 500 kDa displayed higher binding potentials for Cu²⁺. FTIR spectra showed that the main participants of DOM-Cu complexation included aromatic hydrocarbons, aliphatic groups, amide Ⅰ bands, and carboxyl functional groups. This study provides spatial-scale insights into the molecular weight structure of DOM in influencing the behavior, fate, and bioavailability of heavy metals in lakes.

Health risks caused by exposure to black carbon (BC) and nanoparticles (NP) are well studied, although no standard currently exists for them worldwide. Exposure to children may lead to serious health effects due to their increased vulnerability and longer time spend inside the classrooms, making it important to assess the factors that affect air quality in preschools. Thus, this work aims to evaluate indoor-outdoor (I/O) relationships of NPs in the 10–420 nm range, BC and volatile organic compounds (VOCs) at rural and urban preschools (aged 3–5 years) between May 2016 and July 2017. Factorial analysis was applied to identify the possible emission sources. Prior communalities were estimated by the squared multiple correlations with all other variables. We used the varimax rotation method and the criterion for factor selection was the number of eigenvalues greater than one. Results indicate that BC and NP were 4- and 3.2-times higher in urban outdoor caused by traffic emissions, respectively. Highest concentrations occurred during rush hours and during the pickup time of children. In urban school, BC was directly related to accumulation mode (N₄₉₋₂₀₅), while in the rural area, BC was related to local traffic and particles from pulp industries in the regional background. Nucleation mode (N₁₁₋₃₆) was related to traffic emissions in urban school, while in the rural school was related with secondary formation of particles. Mean I/O ratios of BC and NP in the urban (0.54; 0.51) and rural (0.71; 0.91) schools, respectively, suggested that their higher concentrations occurred in outdoors. VOCs were higher indoor in urban (I/O = 1.97) and rural (I/O = 2.22) sites, indicating these pollutants are generated inside, regardless of urban or rural sites. These findings suggest the necessity of improving ventilation and commuting styles to lower the exposure of children to air pollutants in and around school environments.

Five endocrine-disrupting compounds (EDCs) were determined in four urban wastewater treatment plants (WWTPs) of the Metropolitan Area of Monterrey (MAM) in two seasonal periods (winter and summer). The MAM, one of the most urbanized areas in Mexico, is characterized by high industrial activity and population density, leading to extensive use of several EDCs. In the MAM, ∼90% of urban and industrial wastewater is treated in WWTPs, where EDCs can be partially eliminated. In this work, dissolved levels of 17β-estradiol (E2), 17α-ethinyl estradiol (EE2), bisphenol A (BPA), 4-nonylphenol (4NP), and 4-tert-octylphenol (4TOP) in wastewater were determined. The EDCs’ determination was carried out through solid-phase extraction (SPE) and gas chromatography coupled to mass spectrometry (GC-MS). High EDCs levels (0.4–450 ng/L) were found in the influents of WWTPs, while concentrations in the effluents ranged from 0.2 to 26.8 ng/L, with E2, EE2, and 4TOP being the most persistent. The Spearman correlation analysis revealed the association between E2 and EE2 (r = 0.4835, p < 0.05), and between BPA and 4NP (r = 0.5180, p < 0.05), suggesting that these EDCs have similar sources. Also, E2, BPA, and 4TOP were positively correlated with the chemical oxygen demand (COD), biochemical oxygen demand (BOD), and total suspended solids (TSS) (r = 0.4080–0.5694, p < 0.05), indicating the association of the EDCs with the organic matter in the wastewater. The factor analysis confirmed the significant correlation of COD, BOD, TSS, temperature, and pH with the high occurrence of 4TOP during the summer. It was also confirmed that summer warmer temperatures favored the removal of BPA and 4NP in the studied WWTPs. Finally, the studied sites were classified by cluster analysis in three groups, revealing the impact that seasonality has on the behavior of the selected EDCs.

Human factors/errors (such as inappropriate actions by operators and unsafe supervision by organizations) are a primary cause of oil spill incidents. To investigate the influences of active operational failures and unsafe latent factors in offshore oil spill accidents, an integrated human factor analysis and decision support process has been developed. The system is comprised of a Human Factors Analysis and Classification System (HFACS) framework to qualitatively evaluate the influence of various factors and errors associated with the multiple operational stages considered for oil spill preparedness and response (e.g., oil spill occurrence, spill monitoring, decision making/contingency planning, and spill response); coupled with quantitative data analysis by Fuzzy Set Theory and the Technique for Order Preference by Similarity to Ideal Solution (Fuzzy-TOPSIS) to enhance decision making during response operations. The efficiency of the integrated human factor analysis and decision support system is tested with data from a case study to generate a comprehensive priority rank, a robust sensitivity analysis, and other theoretical/practical insights. The proposed approach improves our knowledge on the significance of human factors/errors on oil spill accidents and response operations; and provides an improved support tool for decision making.

Dissolved organic matter (DOM) is recognized as a good indicator of water quality as its concentration is influenced by land use, rainwater, windborne material and anthropogenic activities. Recent technological advances make it possible to characterize fluorescent dissolved organic matter (FDOM), the fraction of DOM that fluoresces. Among these advances, portable fluorometers and benchtop fluorescence excitation and emission spectroscopy coupled with a parallel factor analysis (EEM-PARAFAC) have shown to be reliable. Despite their rising popularity, there is still a need to evaluate the extent to which these techniques can assess DOM dynamics at the watershed scale. We compare the performance of in-situ measurements of FDOM with laboratory measurements of fluorescence spectroscopy within the context of two distinct glacierized watersheds in Peru. Glacierized watersheds represent unique testing environments with contrasting DOM conditions, flowing from pristine, vegetation-free headwaters through locations with obvious anthropogenic influences. We used an in-situ fluorometer and a portable multimeter to take 38 measurements of FDOM, pH and turbidity throughout the two catchments. Additionally, samples were analyzed in the laboratory using the EEM-PARAFAC method. Results were compared to dissolved organic carbon (DOC) measurements using standard high-temperature catalytic oxidation. Our results show that the three techniques together were able to capture the DOM dynamics for both studied watersheds. Taken individually, all three methods allowed detection of the watershed DOM main points of sources but in a more limited way. Due to the narrow bandwidth of the portable fluorometer used in the study, FDOM measurements were almost non-detectable to protein-like substances. Indeed, the more demanding EEM-PARAFAC was able to both differentiate between potential sources of DOM and provide an estimate of relative concentrations of different organic components. Finally, similar to FDOM but to a lesser extent, the DOC measurements showed some limits where protein-like substances make up most of the DOM composition.

The Keban Dam Reservoir, located on the Euphrates River, is the second largest reservoir of Turkey. Water quality of this reservoir is of great importance because it is widely used for recreation, aquaculture production, fishing, and irrigation. In this study, discriminant analysis, principal component analysis (PCA), factor analysis (FA) and cluster analysis (CA) were conducted to evaluate the seasonal and spatial variations in surface water quality of the reservoir. Also, total phosphorus (TP) content in sediments, water type and trophic status of the reservoir were determined. For this, 19 water quality variables and TP in sediments were monitored seasonally at 11 sampling stations on the reservoir during one year. Hierarchical CA classified 11 stations into three groups, i.e., upstream (moderate polluted), midstream (low polluted) and downstream (clean) regions. PCA/FA allowed to group the variables responsible for variations in water quality, which are mainly related to mineral dissolution (natural), organic matter and nutrients (anthropogenic), and physical parameters (natural). Discriminant analysis (DA) gave better results for both data reduction and spatio-temporal analysis. Stepwise temporal DA identified eight variables: water temperature (WT), chemical oxygen demand (COD), nitrate nitrogen (NO₃–N), soluble reactive phosphorus (SRP), chlorophyll-a (Chl-a), potassium (K⁺), magnesium (Mg²⁺), and calcium (Ca²⁺), which are the most significant variables responsible for temporal variations in water quality of the reservoir, while stepwise spatial DA identified three variables: K⁺, chloride (Cl⁻), and sulphate (SO₄⁻²), which are the most significant variables responsible for spatial variations. According to Ontario sediment-quality guidelines, sediments of the reservoir can be considered as unpolluted in terms of mean TP content. The water type of the reservoir was calcium-bicarbonate. According to trophic state index values based on TP and Chl-a, upstream region (moderate polluted) of the reservoir was in the eutrophic status, whereas other regions were in the mesotrophic status.

Benzo[a]pyrene (BaP) is a hazardous compound for human health and for environmental compartments. Its transfer and deposition through the atmosphere affects soil quality. In this context, we quantified the content of BaP and other Polycyclic Aromatic Hydrocarbons (PAHs) in the soils of a prominent Coal Region in Transition to test whether the soil screening levels in force are realistic and whether they reflect the complexity of regions closely linked to heavy industries and mining. In this regard, soil screening levels are thresholds often established without considering historical anthropogenic activities that affect soil (diffuse pollution). The 150 soil samples studied showed a notable content of high molecular weight PAHs, and BaP surpassed the threshold levels in practically the entire area. PAH-parent diagrams revealed a relatively homogenous fingerprint of four clusters obtained in a multivariate statistical study. In addition, molecular diagnostic ratios pointed to coal combustion as the main pollution source, whereas only some outliers appeared to be related to specific spills. A BaP threshold was calculated to be 0.24 mg kg⁻¹, over 10 times the limit established in Spain. Finally, a factor analysis revealed a positive correlation of BaP with elements usually emitted in coal combustion processes, such as Tl and V. This observation fosters the hypothesis of a historical and indelible pollution fingerprint in soils whose sources, characteristics and potential environmental and health concerns deserve further attention. All things considered, caution should be taken when using soil screening levels in regions associated with coal exploitation and heavy industry.

Concentrations of common pollutants in groundwater continue to increase, and emerging pollutants are also increasingly found worldwide, thereby increasingly impacting human activities. In this new situation, it is necessary, albeit more difficult, to once again recognize the hydrochemical genesis of groundwater and to subsequently screen the typical pollutants. Taking the groundwater of the Songnen Plain of Northeast China as an example, the hydrochemical genesis was identified using space interpolation, characteristic element ratio and factor analysis methods based on 368 groundwater samples. Subsequently, the typical pollutants with potential impacts on the health of the local residents were screened by the index system method newly established. All the measured hydrochemical compositions show an obvious spatial variation, with a uniform hydrochemical type of HCO3–Ca in the whole area. Both the major compositions (K, Na, Ca, Mg, HCO3, Cl and SO4) and trace compositions (Fe, Mn, Cu, Zn, Pb, As, F, I and Se) are mainly protogenetic in an environment impacted by the lixiviation of groundwater in the migration process in the strata, although these compositions have been impacted by human activities to varying degrees. The mass concentration of NO3–N has exceeded most of the major compositions except for HCO3 and Ca, which means the nitrogen pollution problem is already very serious; and this problem is mainly caused by the utilization of fertilizers and the discharge of industrial wastewater and domestic sewage. Human activities have obviously disrupted the natural dynamic balance of these chemicals between the environment and the groundwater, thereby intensifying the release of F, Fe and Mn from the environment. TDS, total hardness, tri-nitrogen, F, Fe, Mn, Pb and As in some parts are found to exceed the standards of groundwater quality to varying degrees. As, Pb, Fe, NO3–N, NO2–N, Mn, F and NH4–N are finally screened as the typical pollutants.

Precipitation samples were collected at five rural and one urban sites in the Three Gorges Reservoir Region (TGR), China from March 2014 to February 2016. The inorganic reactive nitrogen (Nr) contents were analysed to investigate their wet deposition flux, budget, and sources in the area. Annual Nr wet deposition varied from 7.1 to 23.4 kg N ha⁻¹ yr⁻¹ over the six sites during the two-year study campaign. The six-site average Nr wet deposition flux was 17.1 and 11.7 kg N ha⁻¹ yr⁻¹ in 2014 and 2015, respectively, with 71% from NH₄⁺ and 29% from NO₃⁻. Dry deposition flux was estimated using the inferential method, which combined the measured ambient concentrations and modelled dry deposition velocities. The total (dry + wet) Nr deposition fluxes were estimated to be 21.4 kg N ha⁻¹ yr⁻¹ in 2014 and 16.0 kg N ha⁻¹ yr⁻¹ in 2015 at rural sites, and 31.4 and 25.3 kg N ha⁻¹ yr⁻¹ at the urban site. Annual average volume weighted mean (VWM) concentrations in precipitation at all the six sites differed little for NO₃⁻ but up to a factor of 2.0 for NH₄⁺ with the highest value at the urban site. Industrial emissions, agricultural emissions, soil dust, and biomass burning were identified as potential sources of the major inorganic ions in precipitation using factor analysis and correlation analysis. Conditional probability function (CPF) analysis indicated that the urban site was predominantly affected by industrial emissions from a power plant, cement manufactory, and salt chemical facility located ∼13 km southeast of the sampling site.