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.

The presence of pharmaceuticals and personal care products in coastal waters has caused concern over the past decade. Sulfadiazine (SD) is a very common antibiotic widely used as human and fishery medicine, and dissolved organic matter (DOM) plays a significant role in the indirect photodegradation of SD; however, the influence of DOM compositions on SD indirect photodegradation is poorly understood. The roles of reactive intermediates (RIs) in the indirect photolysis of SD were assessed in this study. The reactive triplet states of DOM (³DOM∗) played a major role, whereas HO· and ¹O₂ played insignificant roles. DOM was divided into four components using excitation-emission matrix spectroscopy combined with parallel factor analysis. The components included three allochthonous humic-like components and one autochthonous humic-like component. The allochthonous humic-like components contributed more to RIs generation and SD indirect photolysis than the autochthonous humic-like component. A significant relationship between the indirect photodegradation of SD and the decay of DOM fluorescent components was found (correlation coefficient, 0.99), and the different indirect photodegradation of SD in various DOM solutions might be ascribed to the different components of DOM. The indirect photolysis rate of SD first increased and then decreased with increasing pH. SD photolysis was enhanced by low salinity but remained stable at high salinity. The increased carbonate concentration inhibited SD photolysis, whereas nitrate showed almost no effect in this study.

The interpretation of large air pollution datasets involves a great deal of complexity. To gain a better understanding of the complicated relationships and patterns within datasets, we perform factor analysis. Between December 2015 and December 2017, fine particulate matter (PM₂.₅) samples were collected at a suburban site northeast of the Houston metropolitan area, TX. A total of 233 filter samples were analyzed for chemical composition. The average of all PM₂.₅ samples consisted of 38.1% inorganic ions, 28.9% elements, 29.1% organic carbon, and 3.7% elemental carbon and other organic materials. Principal component analysis and positive matrix factorization were utilized to identify eight factors: regional aerosols, biomass burning, gasoline combustion, industry, crustal material, incineration, marine dust, and fireworks. The first three contributed more than 70% of the total PM₂.₅ mass. The receptor models also captured the impact of fireworks and classified it as a source of PM₂.₅ over Houston. To identify the origins of air masses transporting PM₂.₅ to the site, we applied the NOAA hybrid single-particle Lagrangian integrated trajectory model and performed a cluster analysis of back trajectories and determined six cluster source regions: the Gulf of Mexico, the Southeast, two midwestern clusters, the Pacific Northwest, and the Southwest. The results of our analysis show that during the summer months, marine and crustal sources were often associated with an onshore flow from the Gulf of Mexico and that four clusters covering 38% of the West Liberty area were strongly influenced by trajectories originating from biomass burning. The results of this study represented a variety of sources that affect the PM₂.₅ over the Houston metropolitan area. The quantified contributions of these sources could provide policymakers with useful information for developing more efficient control systems and making more effective decisions to cope with the harmful effects of ambient air pollution.

Uncertainty assessment of parameters associated with non-point source pollution mechanism modeling are crucial for improving the effectiveness of pollution controlling. In this study, an approach based on Bayesian inference and integrated Markov chain Monte Carlo and multilevel factorial analysis has been developed, and it can not only apply straightforward Bayesian inference to assess parameter uncertainties, but also quantitatively investigate the main and interactive effects of multiple parameters on the model response variables by measuring the specific variations of model outputs. Its applicability and advantages are presented through the application of the Soil and Water Assessment Tool to Shitoukoumen Reservoir Catchment in northeast China. This study investigated the uncertainties of a set of sensitive parameters and their multilevel effects on model response variables, including average annual runoff (AAR), average annual sediment (AAS) and average annual total nitrogen (AAN). Results revealed that (i) soil conservation service runoff curve number for moisture condition II (CN2) had a positive effect on all response variables; (ii) available water capacity of the soil layer (SOL_AWC) had a negative effect on all response variables; (iii) the universal soil loss equation support practice (USLE_P) had a positive effect on AAS and AAN, and little effect on AAR; while the nitrate percolation coefficient (NPERCO) had a positive effect on AAN, and little effect on AAS and AAR; and (iv) the interactions amongst parameters had obvious interdependent effects on the model response variables, for example, the interaction between CN2 and SOL_AWC had a major impact on AAR. The above findings can improve the simulating and predicting capabilities of non-point source pollution mechanism model. Overall, this study highlights that the proposed approach represents a promising solution for uncertainty assessment of model parameters in non-point source pollution mechanism modeling.

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.

Aquatic macrophytes play a significant role in nutrients removal in constructed wetlands, yet nutrients could be re-released due to plant debris decomposition. In this study, Myriophyllum aquaticum was used as a model plant debris and three debris biomass levels of 3 g, 9 g dry biomass, and 20 g fresh biomass (D3, D9, and F20, respectively) were used to simulate 120-d plant debris decomposition in a sediment-water system. The biomass first-order decomposition rate constants of D3, D9, and F20 treatments were 0.0058, 0.0117, and 0.0201 d⁻¹, respectively with no significant difference of decomposition rate among three mass groups (p > 0.05). Plant debris decomposition decreased nitrate and total nitrogen concentrations but increased ammonium, organic nitrogen, and dissolved organic carbon (DOC) concentrations in overlying water. The parallel factor analysis confirms that three components of DOC in overlying water changed over decomposition time. Emission fluxes of methane and nitrous oxide in the plant debris treatments were several to thousands of times higher than the control group within the initial 0–45 d, which was mainly attributed to DOC released from the plant debris. Plant debris decomposition can affect the gas emission fluxes for relatively shorter time (30–60 d) than water quality (>120 d). The 16S rRNA, nirK, nirS and hazA gene abundance increased in the early stage for plant debris treatments, and then decreased to the end of 120-d incubation time while ammonia monooxygenase α-subunit A gene abundance of ammonia-oxidizing archaea and bacteria had no large variations during the entire decay time compared with no plant debris treatment. The results demonstrate that decomposition of M. aquaticum debris could affect greenhouse gas emission fluxes and microbial gene abundance in the sediment-water system besides overlying water quality.

The current study was conducted to (1) examine seasonal and spatial distribution of heavy metals and metalloid in sediment from the Saigon River and (2) apportion and quantify their pollution sources. Ninety-six sediment samples were taken in the rainy and dry season on 13 sampling sites, distributed over the lower reaches of the River, to analyze for exchangeable concentration of 11 heavy metals and metalloid (Al, B, Cd, Co, Fe, In, Mn, Ni, Pb, Sr, and Zn), pH, EC, organic carbon content, and particle-size distribution. Generally, the concentration of 11 elements was ranked in the order Mn > Al > Fe > Zn > Sr > In > B > Ni > Co > Pb > Cd. Hierarchical cluster analysis grouped 13 sampling sites into two parts based on the similar concentration of the 11 elements. Three-way analysis of variance showed that the total exchangeable concentration of 11 elements was significantly higher in the rainy season than in the dry season and in the upper part than in the lower part of the river. Principal component analysis/factor analysis and correlation analysis revealed that three pollution sources (PS) may contribute to enriching the 11 examined elements in the sediment. These sources included (PS1) from catchment through water erosion over natural areas, explaining 83%, (PS2) mixed sources from catchment through water erosion over agricultural fields and inside Ho Chi Minh City, accounting for 6%, and (PS3) mixed sources from lowland areas, explaining 7.8% of the total variance of the elements. In brief, the sediment concentration of 11 metals and metalloid varied with season and space and three major pollution sources from river catchment, inside Ho Chi Minh City, and lowland contributively enriched the elements in the sediment of the River.

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.

The inorganic content of the well-preserved 3.2-m record of Las Conchas bog (NW Spain), covering 8000 cal yr BP., was analysed. To study natural vs. human contributions, we applied an innovative approach, namely the sequential study of multivariate statistics (factor analysis followed by clustering of the factor score matrix) and enrichment factors (EFs). The increasing weight of potentially toxic elements (PTEs) such as the geochemical association of Zn, Pb and Cd (EFs higher than 10, 20 and 40 in the last two centuries) was revealed, and corroborated by the contrast between the contents of anthropogenic Pb and total Rare Earth Elements (a suitable proxy for natural geogenic supplies). Furthermore, elements such as Hg, Tl and As also showed enrichment in the most recent samples of the study core. Some of them are commonly associated with global atmospheric transport; however, in this case, their increasing contents could also be explained by nearby industrial and mining activities.In summary, severe pollution was observed in the uppermost part of the record, thereby pointing to an important environmental concern. Given that local and regional sources of PTEs, such as mining and heavy industry, especially Zn smelting, were probably the main historical causes of this contamination and that some of these industries are still active, we consider that our findings deserve further attention.