Which pollutants and sources should be prioritized for control in multi-pollutants complex contaminated areas?

Risk assessment and source identification of multi-pollutants are essential for accurate control of soil contamination. However, complexity in pollutant properties and diversity in source types raise challenges to the target. Therefore, this study constructed a hierarchical ecological risk quantification method combined with risk ranking, risk of single pollutant using potential affected fraction (PAF), and joint risk of multi-pollutants employing msPAF. Taking regional contamination in South China as a case, the risk ranking was determined, while single and joint effects showed msPAF reaching 79.4 %, with risk as heavy metals (HMs) > per- and polyfluoroalkyl substances (PFASs) > polycyclic aromatic hydrocarbons (PAHs). Meanwhile, an integrated source apportionment method was established from three layers by principal component analysis to classify source types, multiple linear regression of distance to identify key sources, and positive matrix factorization to track omitted sources. Consequently, key sources were captured, with 80.8 %-93.2 % contribution of farmland and electroplating to three main HMs, 52.2 %-69.4 % contribution of roads to three main PAHs, and 71.1 %-73.2 % contribution of electroplating to two main PFASs. Further, omitted sources were tracked with contribution of 31.2 %-84.1 % to eight pollutants. The established methods can identify control targets, including high-risk pollutants and their key sources.

Machine learning-derived dose-response relationships considering interactions in mixtures: Applications to the oxidative potential of particulate matter.

Conventional environmental health research is primarily focused on isolated chemical exposures, neglecting the complex interactions between multiple pollutants that may synergistically or antagonistically influence toxicity, thereby posing unexpected health risks. In this study, we address this knowledge gap by introducing an explainable machine learning (ML) approach with Feature Localized Intercept Transformed-Shapley Additive Explanations (FLIT-SHAP) designed to extract the dose-response relationships of specific pollutants in mixtures. In contrast to traditional SHAP, FLIT-SHAP can localize the global intercept to elucidate mixture effects, which is crucial for understanding the oxidative potential (OP) of ambient particulate matter (PM). Assessing multi-pollutant OP using FLIT-SHAP revealed both synergistic (55-63 %) and antagonistic (25-42 %) effects in laboratory-controlled OP data, but an antagonistic (33-66 %; lower OP) effect in ambient PM. Notably, the FLIT-SHAP approach demonstrated higher prediction accuracy (R2 = 0.99) compared to the additive model (R2 = 0.89) when evaluated against real-world PM samples. Quinones, such as phenanthrenequinone, play a more significant role in PM2.5 than previously recognized. Through this study, we highlighted the potential of FLIT-SHAP to enhance toxicity predictions and aid decision-making in the field of environmental health.

Recyclable Au@R-Fe3O4/g-C3N4 substrates for rapid SERS detection and degradation of multiple pollutants.

Developing a Surface-enhanced Raman spectroscopy (SERS) method with excellent detecting ability, good recyclability and analyzing multiple pollutants rapidly are critical for evaluation of water quality in emergency pollution affairs. While constructing a multifunctional substrate with these characteristics to realize the application of SERS in water quality monitoring remains a challenge. In this work, a reusable Au@R-Fe3O4/g-C3N4 SERS substrate is prepared by loading Au nanoparticles (Au NPs) on Fe3O4 nanorings (R-Fe3O4) and the formed Au@R-Fe3O4 is further combined with g-C3N4 nanosheets through a simple electrostatic assembly method. The Au@R-Fe3O4/g-C3N4 nanocomposite presents multifunction of magnetic enrichment, SERS signal enhancement, multiple pollutants analyzing, and photocatalytic activity, which achieves quantitative detection of rhodamine B (RhB), tetracycline hydrochloride (TC), and 4-chlorophenol (4-CP), with detection limits of 5.30 × 10-9, 7.50 × 10-8, 7.69 × 10-8 mol/L, respectively. Furthermore, the recyclable detection capability of Au@R-Fe3O4/g-C3N4 for multi components is demonstrated by the strong SERS signal after 9 cycles of "detection-degradation" processes. Combined with good uniformity and stability, this SERS method based on Au@R-Fe3O4/g-C3N4 substrate provides a new strategy for the multi-pollutants detection and degradation in water environment.

Combined pollution characteristics and ecological risks of multi-pollutants in Poyang Lake.

Poyang Lake, the largest freshwater lake in China, faced severe ecological degradation in the past decade. Combined pollution of multi-pollutants may be one of the contributing factors. However, the characteristics of combined pollution and the ecological risks are still not clear. In this study, we used Polar Organic Chemical Integrative Sampler (POCIS), In Situ Bioassay Passive Sampling Device (ISBPSD) and conventional sampling methods, to study the toxic pollutants levels and the combined biological toxicity effects. The results showed that high levels of organochlorine pesticides (OCPs, averaged 162 ng/g) and polycyclic musk (PCM, averaged 53.6 ng/g) residues, as well as some metals such as nickel (Ni), lead (Pb) concentrations exceeded the relevant standard level in the sediment. The risk of combined pollution in the water was relatively low, but high risk was found in the sediments. According to the ISBPSD studies, the survival rates of species in the water and sediments were only 10.0-45.0% and 1.67-11.7% respectively, which was much lower than that reported in other typical basins of China. OCPs, PCMs, and certain metals such as Pb and Ni may be the key toxic pollutants causing biological toxicity effects in Poyang Lake.

Indirect catalytic oxidation of multi-pollutants in diesel exhaust by ozone/micro-nano bubbles system.

Wet oxidation absorption is an efficient and promising method of exhaust gas treatment. When the micro-nano bubbles collapse, they can generate hydroxyl radicals with strong oxidising ability, which can oxidise a variety of pollutants in diesel exhaust. Ozone has strong oxidising properties, and the coupling of ozone and micro-nano bubbles can improve the oxidation and removal effects of polluted gases. In this study, the ozone micro-nano bubbles system was used to oxidise NOx, SO2, and CO to gases that were more readily dissolved in water, such as NO2, SO3, and CO2, and the gases were removed through the absorbent solution. The effects of surfactant, catalyst, urea, pH value, and salinity on the removal efficiency of NOx, SO2, and CO from diesel exhaust were investigated. Through experiments, it was found that the removal efficiency of pollutants was enhanced and then weakened with the increasing concentrations of surfactants, catalysts, and salinity, and continued to decrease with increasing concentrations of urea. When the pH value was < 7, the removal efficiency increased first and then weakened with the increase of the pH value. When the pH value was > 7, it mainly depended on the absorption of acid gas by the alkali solution. Under optimal conditions, the removal efficiencies were 86.3% for NO, 92.1% for SO2, and 65.4% for CO. This study could provide important theoretical support for the industrial application of this technology.

Levels of organic pollutants and metals/metalloids in infant formula marketed in Brazil: Risks to early-life health.

Infant formula intake is recommended to ensure comprehensive nutritional and caloric fulfillment when exclusive breastfeeding is not possible. However, similarly to breast milk, infant formulas may also contain pollutants capable of inducing endocrine-disrupting and neurotoxic effects. Thus, considering the sensitivity of their developing physiological systems and that infants have heightened susceptibility to environmental influences, this study was aimed at assessing the contents of essential elements, and inorganic and organic pollutants in infant formulas marketed in Brazil. Additionally, health risk assessments for selected contaminants were also performed. Measured contents of essential elements (Ca, Fe, Mg, Mn, Cu, Se, and Zn) were congruent with label information. Nevertheless, some toxic elements (Pb, Cd, As, Ni, and Al) were also detected. Notably, in the upper-bound scenario, Pb and Cd surpassed established threshold values when comparing the estimated daily intake (EDI) and tolerable daily intake (TDI - 3.57 and 0.36 µg/kg bw, respectively). Bisphenol P (BPP) and benzyl butyl phthalate (BBP) were frequently detected (84 % detection rate both) with elevated contents (BPP median = 4.28 ng/g and BBP median = 0.24 ng/g). Furthermore, a positive correlation (0.41) was observed between BPP and BBP, implying a potential co-occurrence within packaging materials. Methyl-paraben also correlated positively with BBP (0.57), showing a detection rate of 53 %. The cumulative PBDE contents ranged from 0.33 to 1.62 ng/g, with BDE-154 and BDE-47 the dominant congeners. When comparing EDI values with TDIs, all organic pollutants remained below the thresholds across all exposure scenarios. Moreover, non-carcinogenic risks were below the threshold (HQ > 1) when dividing the EDIs by the respective reference doses for chronic exposure. While the current findings may suggest that infant formula intake poses no immediate risk in terms of the evaluated chemicals, it remains imperative to conduct further research to safeguard the health of infants considering other chemicals, as well as their potential cumulative effects.

County-level and monthly resolution multi-pollutant emission inventory for residential solid fuel burning in Fenwei Plain, China.

The Fenwei Plain (FWP) in central China is the fourth largest plain nationwide. This region has experienced severe air pollution during the past decades, largely due to residential solid fuel burning. A regional-scale emission inventory covering multi-pollutants was currently unavailable for this area due to the lack of localized emission factors (EFs) from various sources. In this study, localized EFs derived from previous in situ measurements and detailed county-level activity data were used to develop an emission inventory of particulate and gaseous pollutants for the source sector of five residential solid fuels in the FWP in 2020. Emissions of particulate matter with an aerodynamic diameter of ≤2.5 µm (PM2.5), organic carbon (OC), elemental carbon (EC), ions, polycyclic aromatic hydrocarbons (PAHs), carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), and volatile organic compounds (VOCs) were estimated to be 230-290, 89-160, 20-29, 31-54, 0.93-22, 2100-3600, 64-87, 9.3-12, and 45-92 Gg/yr, respectively. The county-level distribution characteristics differed between pollutant species due to their different EFs and consumption patterns of solid fuels. Shouyang County emitted most for all pollutants (2.66%-4.91% of the region total) except PM2.5 and SO2, for which Xiangfen and Hongtong County emitted the most (2.64% and 2.90%), respectively. Emissions were higher in cold (SO2 during November to January, other pollutants during November to February) than warm months. Uncertainties in this newly developed emission inventory were estimated to be 25.2%-69.8%, much lower than those of existing ones, demonstrating the reliability of this inventory. Gini coefficients indicated that EC, PAHs, NOx, and VOC emissions exhibited evident regional disparities, e.g., Yuncheng and Jinzhong had high pollution levels despite low economic output. Future emission control policies should first focus on developing regions with high pollution in FWP.

A new approach of air pollution regionalization based on geographically weighted variations for multi-pollutants in China.

Air pollution regionalization is a key and necessary action to identify pollution regions for implementing control measures. Here we present a new approach called Geographically Weighted Rotation Empirical Orthogonal Function (GWREOF) for air pollution regionalization in China. Compared with previous methods, such as EOF, REOF, and K-mean, GWREOF better accounts for the variability of air pollution conditions driven by emission patterns and meteorology with centralized spatial locations. We apply GWREOF to multiple air pollutants (such as PM2.5, O3, and other monitored air pollutants) and air quality metrics using their measured spatial and temporal variations in 337 Chinese cities over 2015-2020. We find that the regionalization results for different air pollutants are highly similar, primarily determined by topography and meteorological conditions in China. Therefore, we propose an integrated regionalization result, which identifies 18 air pollution control regions in China and can be applied to multiple pollutants and different years. We further analyze PM2.5, O3, and OX (O3 + NO2) pollution levels and their correlations in these regions. PM2.5 and O3 correlations are generally strongly positive in southern China while negative in northern China. However, PM2.5 and OX correlations are broadly positive in China, reflecting the crucial role of atmospheric oxidizing capacity. Regional-specific and coordinated control measures are in need as China's air pollution strategy transits from PM2.5-focused to PM2.5-O3 synergic control.

Advances in the treatment of multi-pollutant flue gas in China's building materials industry.

In most of the world's building material industries, the control of flue gas pollutants mainly focuses on a single pollutant. However, given the large capacity and high contribution of China's building materials industry to global air pollution, the need to develop multi-pollutant emission reduction technology is urgent. Recently, China has focused on reducing the emissions of flue gas pollutants in the building materials industry, established many key research and development projects, and gradually implemented more stringent pollutant emission limits. This project focuses on the most recent advances in flue gas emission control technology in China's building materials industry, including denitration, dust removal, desulfurization, synergistic multi-pollutant emission reduction, and the construction of pilot research and demonstration projects for pollutant removal in several building material industries. On this basis, revised pollutant limits in flue gas emitted in China's building material industry are proposed.

Application of biochar activated persulfate in the treatment of typical azo pigment wastewater.

With the increase of the azo pigment wastewater, it is necessary to seek an efficient and sustainable treatment method to address issues of damaging water ecosystems and human health. In this work, organic representing azo dye Acid Orange 7 (AO7), heavy metal representing hexavalent chromium (Cr(VI)), and inorganic representing ammonia nitrogen (NH4+-N) were selected to roughly simulate the azo pigment wastewater. The simultaneous decontamination of multi-target pollutants by 700 °C pyrolyzed peanut shell biochar (BC) with persulfate (PDS) was evaluated. The results showed that AO7, Cr(VI) and NH4+-N could finally reach 100%, 85% and 30% removal ratios separately in the BC/PDS/mixed pollutants system under certain basic conditions. Functional groups (hydroxyl groups (C-OH) and carboxylic ester/lactone groups (O-C=O)) were found by XPS as competing sites for adsorption and activation and were gradually consumed as the reaction proceeded. Combining a series of experiments results and EPR analysis, it was found that AO7 removal worked best and it relied on both the radical pathway (including SO4•-, •OH, O2-•, but not 1O2) and adsorption. Cr(VI) was mainly adsorbed and reduced by BC surface to form Cr(OH)3 and Cr2O3, and the remaining part could be reduced by O2-•, followed by •OH. NH4+-N was removed primarily by the radical same as AO7. Meanwhile, the three target pollutants have a co-competitive mechanism. Specifically, they competed for radicals and adsorption sites simultaneously, while the presence of AO7 and NH4+-N would consume the generated oxidizing radicals and further promote the removal of Cr(VI). The fixed-bed reactor simulated the continuous treatment of wastewater. Various anions (chloride (Cl-), nitrate (NO3-), carbonate (CO32-), and hydrogen phosphate (HPO42-)) interfered differently with the pollutant removal. These findings demonstrate a new dimension of BC potential for decontamination of azo pigment wastewater.

Fabrication of Magnetic Al-Based Fe3O4@MIL-53 Metal Organic Framework for Capture of Multi-Pollutants Residue in Milk Followed by HPLC-UV.

The efficient capture of multi-pollutant residues in food is vital for food safety monitoring. In this study, in-situ-fabricated magnetic MIL-53(Al) metal organic frameworks (MOFs), with good magnetic responsiveness, were synthesized and applied for the magnetic solid-phase extraction (MSPE) of chloramphenicol, bisphenol A, estradiol, and diethylstilbestrol. Terephthalic acid (H2BDC) organic ligands were pre-coupled on the surface of amino-Fe3O4 composites (H2BDC@Fe3O4). Fe3O4@MIL-53(Al) MOF was fabricated by in-situ hydrothermal polymerization of H2BDC, Al (NO3)3, and H2BDC@Fe3O4. This approach highly increased the stability of the material. The magnetic Fe3O4@MIL-53(Al) MOF-based MSPE was combined with high-performance liquid chromatography-photo diode array detection, to establish a novel sensitive method for analyzing multi-pollutant residues in milk. This method showed good linear correlations, in the range of 0.05-5.00 µg/mL, with good reproducibility. The limit of detection was 0.004-0.108 µg/mL. The presented method was verified using a milk sample, spiked with four pollutants, which enabled high-throughput detection and the accuracies of 88.17-107.58% confirmed its applicability, in real sample analysis.

Improvement of Al2O3 on the multi-pollutant control performance of NOx and chlorobenzene in vanadia-based catalysts.

We compared the influences of Al2O3 and SiO2 on a traditional V2O5-MoO3/TiO2 for the simultaneous removal of NOx and chlorobenzene (CB). The Al2O3 doping catalyst considerably broadens the active temperature window with higher NOx reduction and CB oxidation efficiencies than the SiO2 doping one and the V2O5-MoO3/TiO2. Furthermore, its resistance to SO2 was preserved and the quantities of polychlorinated byproducts also decreased. The increase in activity at low temperatures could be due to the promotion of vanadia reducibility via interactions between V2O5 and Al2O3. Moreover, the high temperature activity could be due to the additional surface acidities provided by Al2O3, in which the Lewis acid sites played the predominant role in both NH3 adsorptions and CB de-chlorination compared to the Brønsted acid sites. Finally, we proposed that Al2O3 is an effective addition for vanadia-based catalyst in NOx and CB simultaneous removal from stationary sources.

BAYESIAN METHODS FOR MULTIPLE MEDIATORS: RELATING PRINCIPAL STRATIFICATION AND CAUSAL MEDIATION IN THE ANALYSIS OF POWER PLANT EMISSION CONTROLS.

Emission control technologies installed on power plants are a key feature of many air pollution regulations in the US. While such regulations are predicated on the presumed relationships between emissions, ambient air pollution, and human health, many of these relationships have never been empirically verified. The goal of this paper is to develop new statistical methods to quantify these relationships. We frame this problem as one of mediation analysis to evaluate the extent to which the effect of a particular control technology on ambient pollution is mediated through causal effects on power plant emissions. Since power plants emit various compounds that contribute to ambient pollution, we develop new methods for multiple intermediate variables that are measured contemporaneously, may interact with one another, and may exhibit joint mediating effects. Specifically, we propose new methods leveraging two related frameworks for causal inference in the presence of mediating variables: principal stratification and causal mediation analysis. We define principal effects based on multiple mediators, and also introduce a new decomposition of the total effect of an intervention on ambient pollution into the natural direct effect and natural indirect effects for all combinations of mediators. Both approaches are anchored to the same observed-data models, which we specify with Bayesian nonparametric techniques. We provide assumptions for estimating principal causal effects, then augment these with an additional assumption required for causal mediation analysis. The two analyses, interpreted in tandem, provide the first empirical investigation of the presumed causal pathways that motivate important air quality regulatory policies.

Effect of multi-pollutant state of ozone and sulfur dioxide on atmospheric corrosivity map of Guangdong Province.

Guangdong Province, which is located in southern China, has a tropical climate with high temperatures and humidity, making it extremely unfavourable for the corrosion resistance of various materials. Meanwhile, as a quickly developing region in China, Guangdong Province is also facing multi-pollutant conditions, which seriously affect the atmospheric degradation of the materials in this region. It is therefore necessary to identify the key air pollutants that affect the atmospheric corrosivity of Guangdong Province and to propose targets of air pollutant control. An analysis of the environmental data and corrosion rates in Guangdong Province showed that the atmospheric corrosivity of the entire region is closely related to the presence of sulfur dioxide (SO2) and ozone (O3). In addition, a superposition model was utilised to reflect the synergistic effect of SO2 and O3, and a superimposed map of both pollutants was drawn to demonstrate their amount. To control the corrosion rate of carbon steel and avoid exceeding the C2 classification in ISO 9223, the following targets of air pollutant control are proposed: an SO2 concentration of lower than 10 µg m-3 and an O3 level of lower than 85 µg m-3.