The cement industry is the second largest source of anthropogenic mercury (Hg) emissions in Europe, accounting for 11% of global anthropogenic Hg emissions. The main objective of this study was to examine the influence of Hg emissions from the Salonit Anhovo cement plant on Hg levels measured in the ambient air at Vodarna, 1 km downwind from the flue gas chimney. The findings reveal that the plant raw mill operational status plays an important role in Hg concentrations in the flue gas emitted from the plant. Emitted total gaseous mercury was, on average, higher (49.4 μg/m³) when raw mills were in the direct mode (both raw mills-off) and lower (23.4 μg/m³) in the combined mode (both raw mills-on). The average Hg concentrations in Vodarna were 3.14 ng/m³ for gaseous elemental mercury, 53.7 pg/m³ for gaseous oxidised mercury, and 41.9 pg/m³ for particulate bound mercury for the whole measurement period. Atmospheric Hg speciation in Vodarna, coupled with plant emissions and wind data, has revealed that the total gaseous mercury emitted from the cement plant is clearly related to all Hg species measured in Vodarna. Wind blowing from the northeastern quadrant (mostly NE, ENE) is responsible for the elevated Hg levels in Vodarna, where gaseous oxidised mercury levels are highly linked to the cement plant emissions. However, elevated levels of Hg species in the absence of northeastern winds indicate potential inputs from other unknown local sources as well as inputs from regional and global transport mechanisms.

Red mud and phosphogypsum are voluminous industrial by-products worldwide. They have long been disposed of in landfills or open storage, leading to a waste of resource and environmental pollution. This study provides a novel approach to recycle these industrial by-products as sustainable red mud-phosphogypsum-Portland cement (RPPC) binders for stabilization/solidification (S/S) of multimetal-contaminated soil. The physical strength, metal leachability and microstructure of S/S soil were investigated after 7-day and 28-day curing, as well as freezing-thawing (F-T) cycle and wetting-drying (W-D) cycle. The results show that the strength of soil treated by all binders fulfilled the uniaxial compressive strength requirement (350 kPa) of S/S waste in landfills. Microstructural analyses show that the main hydration products of the RPPC S/S soil are ilmenite, ettringite, anhydrite and hydrated calcium silicate. The 10% and 15% RPPC binders have a competitive metal immobilization ability compared with 10% PC, but the immobilization priority is different: Pb > Zn > Cd in RPPC system and Zn > Cd > Pb in PC system, respectively, probably due to the precipiataion of Pb²⁺ with the abundant SO₄²⁻ in phosphogypsum in RPPC system. The strength of RPPC and PC treated soil was still higher than 350 kPa except for RPPC7.5 after 10 freeze-thaw or 10 wetting-drying cycles. The RPPC binder performed worse than PC binder after both freeze-thaw and wetting-drying cycles, especially at a lower dosage. Only the metal leaching concentrations of samples treated by RPPC15 and PC10 could fulfil the Chinese standards for hazardous wastes.

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.

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.

Cement-solidification and chelator-stabilisation of municipal solid waste incineration fly ash (MSWI-FA) are two main treatment techniques to immobilise heavy metals. Differences in the long-term stabilities of those two methods of heavy-metal immobilisation were explored to aid in determining the better MSWI-FA treatment. However, few comparative studies have been conducted on 6-year-old cement-solidified FA (Ce-6-FA) and chelator-stabilised FA (Ch-6-FA). In this study, we compared the physicochemical and heavy metal leaching characteristics of Ce-6-FA and Ch-6-FA. The chemical speciation of heavy metals was modelled using geochemical software to assess long-term stability. The results showed weaker long-term stability in Pb immobilisation under the chelating system. The leaching concentrations of target heavy metals, acetic acid leaching tests, acid neutralising capacity, and pH-dependent leaching results indicated that Ce-6-FA had higher long-term stability than Ch-6-FA. A column experiment indicated that the cumulative release rates of Pb in Ce-6-FA and Ch-6-FA were 2.49% and 4.72%, respectively. The phase-controlled leaching of Pb in Ce-6-FA mainly occurred through Pb2(OH)3Cl and chloropyromorphite (Pb5(PO4)3Cl), whereas that in Ch-6-FA mainly occurred through Pb5(PO4)3Cl. The decomposition of heavy metal chelates in Ch-6-FA and salt generation in this process led to the release of Pb via the inorganic complex.

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.

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.

The aim of this study was to assess, for the first time, the concentrations, sources, dry deposition and human health risks of polycyclic aromatic hydrocarbons (PAHs), aliphatic hydrocarbons (AHs), polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) in total suspended particle (TSP) samples collected in Bizerte city, Tunisia (North Africa), during one year (March 2015–January 2016). Concentrations of PAHs, AHs, PCBs and OCPs ranged 0.5–17.8 ng m−3, 6.7–126.5 ng m−3, 0.3–11 pg m−3 and 0.2–3.6 pg m−3, respectively, with higher levels of all contaminants measured in winter. A combined analysis revealed AHs originating from both biogenic and petrogenic sources, while diesel vehicle emissions were identified as dominant sources for PAHs. PCB potential sources included electronic, iron, cement, lubricant factories located within or outside Bizerte city. The dominant OCP congeners were p,p′-DDT and p,p′-DDE, reflecting a current or past use in agriculture. Health risk assessment showed that the lifetime excess cancer risk from exposure to airborne BaP was negligible in Bizerte, except in winter, where a potential risk to the local population may occur.

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.

Source samples including crustal dust, cement dust, coal combustion were sampled and ambient samples of PM₂.₅ and PM₁₀ were synchronously collected in Hefei from April to December 2014. The size distributions of the markers in the measured source profiles were incorporated into ME-2 solution to develop a new method, called the SDABB model (an advanced ABB three-way factor analysis model incorporating size distribution information). The performance of this model was investigated using three-way synthetic and ambient dataset. For the synthetic tests, the size distributions of markers estimated by the SDABB model were more consistent with true condition. The AAEs between estimated and observed contributions of the SDABB ranged from 15.2% to 29.0% for PM₁₀ and 19.9%–31.6% for PM₂.₅, which is lower than those of PMF2. For the ambient PM, six source categories were identified by SDABB for both sizes, although the profiles were different. The source contributions were sulphate (33.33% and 24.53%), nitrate and SOC (22.33% and 18.16%), coal combustion (19.01% and 18.23%), vehicular exhaust (12.99% and 12.07%), crustal dust (10.69% and 19.40%) and cement dust (1.65% and 5.39%) for PM₂.₅ and PM₁₀ respectively. In addition, the estimated ratios of Al, Si, Ti and Fe in CRD were 0.76, 0.84, 1.10 and 0.85; those of Al and Si in CC were 0.42 and 0.66; Ca and Si in CD were 0.95 and 1.10; NO₃⁻ and NH₄⁺ in nitrate were 1.11 and 1.01; and SO₄²⁻ and NH₄⁺ in sulphate were 0.96 and 1.16. These modeled ratios were consistent with the measured ratios. The size distribution of contributions also came close to reality. Thus, the advanced SDABB three-way model can better capture the characteristics of sources between sizes by effectively incorporating the size distributions of the markers as physical constraints.