This study focused on the syngenetic control of polychlorinated-ρ-dibenzodioxins and dibenzofurans (PCDD/Fs) and heavy metals by field stabilization/solidification (S/S) treatment for municipal solid waste incineration fly ash (MSWIFA) and multi-step leachate treatment. Modified European Community Bureau of Reference (BCR) speciation analysis and risk assessment code (RAC) revealed the medium environment risk of Cd and Mn, indicating the necessity of S/S treatment for MSWIFA. S/S treatment significantly declined the mass/toxic concentrations of PCDD/Fs (i.e., from 7.21 to 4.25 μg/kg; from 0.32 to 0.20 μg I-TEQ/kg) and heavy metals in MSWIFA due to chemical fixation and dilution effect. The S/S mechanism of sodium dimethyldithiocarbamate (SDD) and cement was decreasing heavy metals in the mild acid-soluble fraction to reduce their mobility and bioavailability. Oxidation treatment of leachate reduced the PCDD/F concentration from 49.10 to 28.71 pg/L (i.e., from 1.60 to 0.98 pg I-TEQ/L) by suspension absorption or NaClO oxidation decomposition, whereas a so-called “memory effect” phenomena in the subsequent procedures (adsorption, press filtration, flocculating settling, slurry separation, and carbon filtration) increased it back to 38.60 pg/L (1.66 pg I-TEQ/L). Moreover, the multi-step leachate treatment also effectively reduced the concentrations of heavy metals to 1–4 orders of magnitude lower than the national emission standards. Furthermore, the PCDD/Fs and heavy metals in other multiple media (soil, landfill leachate, groundwater, and river water) and their spatial distribution characteristics site were also investigated. No evidence showed any influence of the landfill on the surrounding liquid media. The slightly higher concentration of PCDD/Fs in the soil samples was ascribed to other waste management processes (transportation and unloading) or other local source (hazardous incineration plant). Therefore, proper management of landfills and leachate has a negligible effect on the surrounding environment.

Selenium (Se) radioactive wastes can be disposed through stabilization/solidification (S/S) based on the cementitious matrix on hydration products, where hydrocalumite (Ca₂Al-LDH) is expected to play an important role in the retention of SeO₄²⁻. Natural organic matters (NOMs) are known to be a risk to affect the transportation and mobility of undesirable chemical species in the pedosphere which receives the low level radioactive wastes (LLW). In the present work, five amino acids were selected as the simplified models of NOMs in the pedosphere to explore their effects on the stability of Ca₂Al-LDH after immobilized SeO₄²⁻ under alkaline conditions. As the loading amount of amino acids on Ca₂Al-LDH increasing, release of SeO₄²⁻ was enhanced in HGly, H₂Asp, and H₂Cys series, while no enhancement was observed in HPhe and HTrp series. Density functional theory (DFT) calculation predicted ion-exchange of amino acids and CO₃²⁻ with SeO₄²⁻ in a unit cell of LDH model. The intercalation of Asp²⁻ and CO₃²⁻ caused 003 peaks in XRD sharper and d₀₀₃ decreased from 8.15 Å to 7.70 Å which is assigned to Ca₂Al-LDH(Asp, CO₃). In H₂Cys series, the 003 peaks were kept broad and SeO₄²⁻ was still relatively maintained in LDH which was caused by the lower amounts of intercalated CO₃²⁻ in the presence of H₂Cys. Amino acids in the interlayer of Ca₂Al-LDH have several possible configurations, where the most stable one is prone to be in a horizontal direction through hydrogen bonds and Ca–O chemical bonds. This provides an insight on the stability of selenate immobilized in hydrocalumite, which can be produced in cement disposing in the pedosphere for a long term of burying. Not only carbonate but also small molecular organic matters like amino acids possibly give environmental impact on the mobility of low level anionic radionuclides in LDH.

Vehicular non-exhaust emissions account for a significant share of atmospheric particulate matter (PM) pollution, but few studies have successfully quantified the contribution of non-exhaust emissions via real-world measurements. Here, we conduct a comprehensive study combining tunnel measurements, laboratory dynamometer and resuspension experiments, and chemical mass balance modeling to obtain source profiles, real-world emission factors (EFs), and inventories of vehicular non-exhaust PM emissions in Chinese megacities. The average vehicular PM₂.₅ and PM₁₀ EFs measured in the four tunnels in four megacities (i.e., Beijing, Tianjin, Zhengzhou, and Qingdao) range from 8.8 to 16.0 mg km⁻¹ veh⁻¹ and from 37.4 to 63.9 mg km⁻¹ veh⁻¹, respectively. A two-step source apportionment is performed with the information of key tracers and localized profiles of each exhaust and non-exhaust source. Results show that the reconstructed PM₁₀ emissions embody 51–64% soil and cement dust, 26–40% tailpipe exhaust, 7–9% tire wear, and 1–3% brake wear, while PM₂.₅ emissions are mainly composed of 59–80% tailpipe exhaust, 11–31% soil and cement dust, 4–10% tire wear, and 1–5% brake wear. Fleet composition, road gradient, and pavement roughness are essential factors in determining on-road non-exhaust emissions. Based on the EFs and the results of source apportionment, we estimate that the road dust, tire wear, and brake wear emit 8.1, 2.5, and 0.8 Gg year⁻¹ PM₂.₅ in China, respectively. Our study highlights the importance of non-exhaust emissions in China, which is essential to assess their impacts on air quality, human health, and climate and formulating effective controlling measures.

Oil-contaminated soils resulted from drilling activities can cause significant damages to the environment, especially for living organisms. Treatment and management of these soils are the necessity for environmental protection. The present study investigates the field study of seven oil-contaminated soils treated by different stabilization/solidification (S/S) methods, and the selection of the best treated site and treatment method. In this study, first, the ratios of consumed binders to the contaminated soils (w/w) and the treatment times for each unit of treated soils were evaluated. The ratios of consumed binders to the contaminated soils were between 6 and 10% and the treatment times for each unit of treated soils were between 4.1 and 18.5 min/m³. Physicochemical characteristics of treated soils were also determined. Although S/S methods didn’t change the water content of treated soils, they increased the porosity of soils. Unexpectedly, the cement-based S/S methods didn’t increase the pH of the treated soils. The highest and the lowest leaching of petroleum hydrocarbons was belonging to S/S using diatomaceous earth (DE) and the combination of Portland cement, sodium silicate and DE (CS-DE), respectively. The best acid neutralization capacity was obtained for soils treated using the combination of Portland cement and sodium silicate (CS). Based on the best-worst multi-criteria decision-making method (BWM-MCDM), the soils treated using CS-DE was select as the best. The BWM-MCDM can be used as an effective tool for the selection of the best alternative in all areas of environmental decontamination.

Hardpans are massively indurated layers formed at the top layer of sulfidic tailings dams, which develop cementation structures and result in heavy metal immobilization. However, the micro-structural and complex forms of the cementing materials are not fully understood, as well as the mechanisms by which Zn and Pb are stabilized in the hardpans. The present study deployed synchrotron-based X-ray fluorescence microscopy (XFM) to have characterized the cementing structures, examined the distribution of Fe, Zn and Pb, and obtained laterally-resolved speciation of Zn within the hardpans using fluorescence X-ray absorption near-edge structure (XANES) imaging. The XFM analyses revealed that the Fe-rich cement layers consisted of Fe (oxyhydr)oxides coupled with amorphous Si materials, immobilizing Zn and Pb. Through laterally-resolved XANES imaging analyses, Zn-ferrihydrite-like precipitates were predicted to account for >76% of the total Zn within the Fe-rich cement layers. In contrast, outside of the cement layers, 9–63% of the Zn was estimated as labile ZnSO4.7H2O, with the remainder in the form of Zn-sulfide. These findings demonstrated that the Fe-rich cement layers were critical in immobilizing Zn and Pb within hardpans via mineral passivation and encapsulation, as the basis for long-term geochemical stability in the hardpan layer of sulfidic mine tailings.

Concrete, a cement-based product is the highest manufactured and second highest consumed product after water on earth. Across the world, production of cement is the most energy and emission intensive industry hence, the cement industry is currently under pressure to reduce greenhouse gases emissions (GHGEs). However, reducing the GHGEs of the cement industry especially for developing country like India is not an easy task. Cement manufacturing industry needs to focus on significant climate change mitigation strategies to reduce the GHGEs to sustain its production. This study aims at identifying significant climate change mitigation strategies of the cement manufacturing industry in the context of India. Extant literature review and expert opinion are used to identify climate change mitigation strategies of the cement manufacturing industry. In the present study, a model projects by applying both AHP and DEMATEL techniques to assess the climate change mitigation strategies of the cement industry. The AHP technique help in establishing the priorities of climate change mitigation strategies, while the DEMATEL technique forms the causal relationships among them. Through AHP, the results of this research demonstrate that Fuel emission reduction is on top most priority while the relative importance priority of the main remaining factors is Process emission reduction - Electric energy-related emission - Emission avoidance and reduction - Management mitigation measures. The findings also indicate that the main factors, Process emission reduction, and Fuel emission reduction are categorized in cause group factors, while the remaining factors, Electric energy-related emission, Emission avoidance and reduction and Management mitigation measures are in effect group factors. Present model will help supply chain analysts to develop both short-term and long-term decisive measures for effectively managing and reducing GHGEs.

In order to exhaustively investigate the physical and chemical mechanisms of heavy metal immobilization in sludge incineration residue (SIR)-based magnesium potassium phosphate cement (MKPC), this work investigated the influence of Pb²⁺ and Zn²⁺ on the compressive strength and microstructure of SIR-based MKPC, and the efficiency of Pb and Zn immobilization. Taking the difference of Ksp (solubility product) of different heavy metal compounds as the entry point, the physical and chemical mechanisms of Pb and Zn immobilization, and the competitive mechanism between coexisting ions, were comprehensively analyzed. It was discovered that Pb²⁺ is in the form Pb₃(PO₄)₂, and Zn²⁺ is immobilized in the form Zn₂(OH)PO₄ [Zn₃(PO₄)₂ is preferentially formed, when the pH > 7, Zn₃(PO₄)₂ is converted to Zn₂(OH)PO₄]. The low solubility of heavy metal phosphates is the main reason that Pb²⁺ and Zn²⁺ are well immobilized. The preferential formation of Pb₃(PO₄)₂ (Kₛₚ = 8 × 10⁻⁴³) and Zn₃(PO₄)₂ (Kₛₚ = 9.0 × 10⁻³³) reduced the amount of MgKPO₄·6H₂O (Kₛₚ = 2.4 × 10⁻¹¹), resulting in a decrease in compressive strength. Besides, coexisting Pb²⁺ and Zn²⁺ has a competitive effect: Pb²⁺ will weaken the immobilization efficiency of Zn²⁺. The new exploration of these mechanisms provide a theoretical basis for rationally adjusting the Magnesia/Phosphate ratio to enhance the compressive strength and improve the efficiency of heavy metals immobilization.

PM₂.₅ is one of the most studied atmospheric pollutants due to its adverse impacts on human health and welfare and the environment. An improved model (the chemical mass balance gas constraint-Iteration: CMBGC-Iteration) is proposed and applied to identify source categories and estimate source contributions of PM₂.₅. The CMBGC-Iteration model uses the ratio of gases to PM as constraints and considers the uncertainties of source profiles and receptor datasets, which is crucial information for source apportionment. To apply this model, samples of PM₂.₅ were collected at Tianjin, a megacity in northern China. The ambient PM₂.₅ dataset, source information, and gas-to-particle ratios (such as SO₂/PM₂.₅, CO/PM₂.₅, and NOx/PM₂.₅ ratios) were introduced into the CMBGC-Iteration to identify the potential sources and their contributions. Six source categories were identified by this model and the order based on their contributions to PM₂.₅ was as follows: secondary sources (30%), crustal dust (25%), vehicle exhaust (16%), coal combustion (13%), SOC (7.6%), and cement dust (0.40%). In addition, the same dataset was also calculated by other receptor models (CMB, CMB-Iteration, CMB-GC, PMF, WALSPMF, and NCAPCA), and the results obtained were compared. Ensemble-average source impacts were calculated based on the seven source apportionment results: contributions of secondary sources (28%), crustal dust (20%), coal combustion (18%), vehicle exhaust (17%), SOC (11%), and cement dust (1.3%). The similar results of CMBGC-Iteration and ensemble method indicated that CMBGC-Iteration can produce relatively appropriate results.

Airborne particulate matter (PM) was collected in Beijing between 24 February and 12 March 2014 to investigate chemical characteristics and potential industrial sources of aerosols along with health risk of haze events. Results showed secondary inorganic aerosol was the major contributor to PM2.5 during haze days. Utilizing specific elements, including Fe, La, Tl and As, as fingerprinting tracers, four emission sources, namely iron and steel manufacturing, petroleum refining, cement plant, and coal combustion were explicitly identified; their elevated contributions to PM during haze days were also estimated. The average cancer risk from exposure to inhalable PM toxic metals was 1.53 × 10⁻⁴ on haze days, which is one order of magnitude higher than in other developed cities. These findings suggested heavy industries emit large amounts of not only primary PM but also precursor gas pollutants, leading to secondary aerosol formation and harm to human health during haze days.

Heavy metals (Cr, Co, Ni, As, Cd, and Pb) can be bound to PM adversely affecting human health. Quantifying the source impacts on heavy metals can provide source-specific estimates of the heavy metal health risk (HMHR) to guide effective development of strategies to reduce such risks from exposure to heavy metals in PM2.5 (particulate matter (PM) with aerodynamic diameter less than or equal to 2.5 μm). In this study, a method combining Multilinear Engine 2 (ME2) and a risk assessment model is developed to more effectively quantify source contributions to HMHR, including heavy metal non-cancer risk (non-HMCR) and cancer risk (HMCR). The combined model (called ME2-HMHR) has two steps: step1, source contributions to heavy metals are estimated by employing the ME2 model; step2, the source contributions in step 1 are introduced into the risk assessment model to calculate the source contributions to HMHR. The approach was applied to Huzou, China and five significant sources were identified. Soil dust is the largest source of non-HMCR. For HMCR, the source contributions of soil dust, coal combustion, cement dust, vehicle, and secondary sources are 1.0 × 10−4, 3.7 × 10−5, 2.7 × 10−6, 1.6 × 10−6 and 1.9 × 10−9, respectively. The soil dust is the largest contributor to HMCR, being driven by the high impact of soil dust on PM2.5 and the abundance of heavy metals in soil dust.