The global plasticizer market is projected to increase from $17 billion in 2022 to $22.5 billion in 2027. Various emerging/alternative plasticizers entered the market following the ban on several phthalate plasticizers because of their harmful effects. However, there are limited data (especially peer-reviewed) on emerging plasticizers’ toxicity and environmental impact. This review compiles available data on toxicity, exposure, environmental effects, and safe production of emerging plasticizers. It identifies gaps in scientific research and provides evidence that emerging plasticizers are potential cases of regrettable substitution. Several alternative plasticizers, such as acetyl tributyl citrate (ATBC), diisononyl cyclohexane-1,2 dicarboxylate (DINCH), tris-2-ethylhexyl phosphate (TEHP), tricresyl phosphate (TCP), tris-2-ethylhexyl phosphate (TPHP), bis-2-ethylhexyl terephthalate (DEHT), and tris-2-ethylhexyl trimellitate (TOTM), show potential endocrine-disrupting properties and other toxic characteristics. Some chemicals like bis-2-ethylhexyl adipate (DEHA), diisobutyl adipate (DIBA), ATBC, DINCH, bis-2-ethylhexyl sebacate (DOS), diethylene glycol dibenzoate (DEGDB), DEHT, and phosphate esters showed the potential to cause toxicity in aquatic species. Plus, there is great lack of information on compounds like diisononyl adipate (DINA), dibutyl adipate (DBA), diisodecyl adipate (DIDA), dipropylene glycol dibenzoate (DPGDB), dibutyl sebacate (DBS), alkylsulfonic phenyl ester (ASE), trimethyl pentanyl diisobutyrate (TXIB), DEGDB and bis-2-ethylhexyl sebacate (DOS). Some compounds like epoxidized soybean oil (ESBO), castor-oil-mono-hydrogenated acetate (COMGHA), and glycerin triacetate (GTA) are potentially safer or less toxic. Alternative plasticizers such as adipates (log K_ow 4.3–10.1), cyclohexane dicarboxylic acids (log K_ow 10), phosphate esters (log K_ow 2.7–9.5), sebacates (log K_ow 6.3–10.1), terephthalates (log K_ow 8.4), and vegetable oil derivatives (log K_ow 6.4–14.8) have log K_ow values that are comparable to phthalate plasticizers (log K_ow 7.5–10.4), indicating potential bioaccumulation and health consequences. Field studies have demonstrated that phosphate esters can undergo bioaccumulation and biomagnification, but there is a lack of bioaccumulation studies for other compounds. We also discuss the metabolism of emerging plasticizers, though data are limited. Our article highlights that numerous alternative compounds display potential health and ecological risks, indicating they might not be suitable substitutes for legacy plasticizers. There is also a lack of scientific data on most emerging plasticizers. This way, we call for increased research and timely regulatory action to prevent global contamination and health risks. Finally, this study presents a scientifically robust protocol to avoid harmful substitutions and ensure the production of safer chemicals.

Decaying algal blooms in eutrophic lakes can introduce organic matter into the water and change nutrient concentrations in the water column. The spatial distribution and composition characteristics, sources, and contribution to eutrophication of dissolved organic matter (DOM) in the overlying water of Lake Taihu, a typical eutrophic lake in China, were analyzed by ultraviolet–visible spectra and three-dimensional fluorescence excitation–emission matrix spectra combined with the statistical decomposition technique, parallel factor analysis. The concentration of DOM was represented by dissolved organic carbon (DOC), and DOC in overlying water of Lake Taihu was 2.86–11.83 mg/L. The colored DOM (CDOM) was characterized by an absorption coefficient at 280 nm (a₂₈₀) and 350 nm (a₃₅₀), which were 6.63–29.87 and 1.84–10.41 m⁻¹, respectively. These values showed an increasing trend from southeast to northwest, and the high values were concentrated in the northwest and northern lake areas. The parallel factor analysis (PARAFAC) identified two protein-like (C1: tyrosine-like and C2: tryptophan-like) and one humic-like (C3: humic acid and fulvic acid) fluorescence components for fluorescent DOM (FDOM). The most dominant components were protein-like components (C1 + C2), whose fluorescence intensity contributed 87.55% ± 3.39% to the total fluorescence intensity (F_t) of FDOM (3.38 R.U.). The mean value of the fluorescence index (FI) and index of recent autochthonous contribution (BIX) of DOM was 1.77 and 0.92, and DOC, a₂₈₀ and fluorescence intensities of FDOM components were all significantly and positively correlated with chl. a, indicating that DOM, CDOM, and FDOM were all mainly derived from algal activities and metabolites. The average humification index of the DOM was 0.66, which indicated a low humification degree. The protein-like DOM was correlated with DON and DOP, and might make great contributions to the continuous occurrence of algal blooms.

Information about the growth, productivity, and distribution of vegetation, which are highly relied on and sensitive to natural and anthropogenic factors, is essential for agricultural production management and eco-environmental sustainability in the Amur River Basin (ARB). In this paper, the spatial–temporal trends of vegetation dynamics were analyzed at the pixel scale in the ARB for the period of 1982–2013 using remotely sensed data of long-term leaf area index (LAI), fractional vegetation cover (FVC), and terrestrial gross primary productivity (GPP). The spatial autocorrelation characteristics of the vegetation indexes were further explored with global and local Moran’s I techniques. The spatial–temporal relationships between vegetation and climatic factors, land use/cover types and hydrological variables in the ARB were determined using a geographical and temporal weighted regression (GTWR) model based on the observed meteorological data, remotely sensed vegetation information, while the simulated hydrological variables were determined with the soil and water assessment tool (SWAT) model. The results suggest that the variation in area-average annual FVC was significant with an increase rate of 0.0004/year, and LAI, FVC, and GPP all exhibited strong spatial heterogeneity trends in the ARB. For LAI and FVC, the most significant changes in local spatial autocorrelation were recognized over the Sanjiang Plain, and the low–low agglomeration in the Sanjiang Plain decreased continuously. The GTWR model results indicate that natural and anthropogenic factors jointly took effect and interacted with each other to affect the vegetated regime of the region. The decrease in the impact of precipitation to vegetation growth over the Songnen Plain was determined as having started around 1991, which was most likely attributed to dramatic changes in water use styles induced by local land use changes, and corresponded to the negative correlation between pasture areas and vegetation indexes during the same period. The analysis results presented in this paper can provide vital information to decision-makers for use in managing vegetation resources.