Rapid monitoring and discriminating different anthropogenic pollution is a key scientific issue. To detect the applicability and sensitivity of magnetic measurements for evaluating different industrial pollution in urban environment, characteristics of topsoil from three typical fast developing industrial cities (Jinchang, Baiyin and Jiayuguan in Gansu province, northwestern China) were studied by magnetic and geochemical analyses. The results showed that magnetic susceptibility was enhanced near industrial areas, and PSD-MD magnetite dominated the magnetic properties. Magnetic concentration parameters (χlf, SIRM, and χARM) showed different correlations with heavy metals and PLI in the three cities, indicating significantly different magnetic response to different pollution sources. Principal component analysis showed that ferrimagnetic minerals coexist with heavy metals of Fe, As, Cu, Pb, and Zn in Baiyin and Fe, V, Cu, Mn, Pb, and Cr in Jiayuguan. Fuzzy cluster analysis and regression analysis further indicated that the sensitivity of magnetic monitoring to fuel dust is higher than that to mineral dust near non-ferrous metal smelters, and fossil fuel consumption is an important factor for increasing magnetite content. In all the three cities, the sensitivity of magnetic monitoring to pollutants from steel plants is much higher than that from non-ferrous metal plants. Therefore, magnetic proxies provide a rapid means for detecting heavy metal contamination caused by multi-anthropogenic pollution sources in a large scale area, however, the sensitivity was controlled by pollution sources.

The air pollution contribution from highly industrialized areas has been a prominent issue in regional air quality control. Particular emphasis on local industrial emissions is necessary to understand the complexity of air pollution over highly industrialized areas. Baoshan District, one of the most important industrialized areas in China and the most competitive steel and iron production base worldwide, was selected as the study area in this work. The WRF/CMAQ modeling system with local emission profile was applied to study the impact of spatial resolution on air quality modeling. The simulation results for SO2, NO, NO2, CO and PM10 at both 3–km and 1–km resolutions were verified by ground level observations. The results showed that the allocation of the emission inventory is improved by using finer resolution grids, which allow the consideration of detailed emission features. The influence of model resolution was more significant for air quality than for meteorology simulation. The relative errors using the finer resolution method ranged from –25% to 59%, an obvious improvement over the error value of 26%–245% obtained using the coarse resolution method. The changing tendencies of air pollutants in urban and rural areas were generally better modeled at finer than coarser resolution. However, the detailed variation in the most heavily polluted areas was still difficult to capture, and the model performance was not evidently improved by the use of a fine resolution. To improve the model performance over highly industrialized areas for future studies, combining the dynamic emission profile with detailed industrial activities and accurate local meteorological fields is suggested.

To determine the chemical compositions and source identification of PM2.5 and PM2.5–10 fractions, airborne particulate matter (PM) samples were collected from May, 2011 through April, 2012 at three sites: up and downwind and within a scrap iron and steel smelting industry, Ife–Ibadan highway, south western Nigeria. Samples of PM2.5 (fine) and PM2.5–10 (coarse) were collected on Nuclepore polycarbonate filters using a low volume GENT sampler equipped with a stacked filter unit (SFU). A total of 200 samples were collected (100 of each fraction). The mass concentration of the sampled fine and coarse PM fraction ranged between 14.4–986.5μg/m3 and 11.2–3 250μg/m3, respectively. These values exceed the permissible daily limit (NAAQS) of 35μg/m3 for PM2.5 and 150μg/m3 for PM10. The samples were analyzed for black carbon (BC) using an optical transmissometer and for elemental concentrations using X–Ray Fluorescence (XRF). The size–resolved data sets were analyzed using Positive Matrix Factorization (PMF) to identify possible sources and estimate the contribution of these sources to the fine and coarse PM mass concentrations. Four source categories, providing stable profiles, were identified for both fine and coarse fractions. The identified sources and their contributions for the fine fraction are coking coal (83%), soil (10%), metallurgical industry (6%), and electronic waste processing (1%). For the coarse fraction, the identified sources are metallurgical production plus electronic waste (53%), suspended input materials (28%), soil (18%), and galvanized steel scrap with cadmium (1%). Conditional probability function (CPF) identified the local sources for both the fine and coarse PM samples. This work presents the first known major use of PMF in Nigeria for source identification in particulate matter (PM) studies.

Fine particulate matter samples (PM2.5) were collected from three locations around the Denver–Metropolitan area to study the impacts of the ground–level light rail on airborne metal concentrations. Size–segregated PM was collected on board the trains, at the side of the tracks, and at a background location in downtown Denver. Results from this study showed highest crustal enrichment factors of metals in samples collected on board the train, despite lower concentrations of total PM2.5. Metals commonly found in steel such as Fe, Cr, Mn, and Ni, all exhibited elevated concentrations relating to train activity over the background site. Iron in the PM2.5 at track–side and on board the trains was above the background by a factor of 1.89 and 1.54, respectively. For Mn, the ratios were 1.34 for the track–side and 0.94 for the on board samples. Cr and Ni exhibited higher ratios over the background only in samples collected on board the trains at 1.59 (Cr) and 1.26 (Ni). Soluble metals were measured with Ni (53–71%), Cu (52–81%), and Zn (30–81%) exhibiting the highest solubilities across the different sites. Soluble Fe ranged from 8–15% for the total measured Fe, indicating a non–crustal source of Fe. Soluble Fe was also characterized as Fe(II) and Fe(III) with 87–90% of the soluble Fe being Fe(II), similar to results from studies in Los Angeles, CA and East St. Louis, IL but higher than in Atlanta, GA and Waukesha, WI.

Electric arc furnace (EAF) dust and slag, materials which contain high metals in their composition, were improperly disposed in an industrial steel mill site between 1963 and 1999. Previous environmental investigations identified anomalous concentrations of metals in local groundwater but failed to relate these abnormalities to the disposed material or to natural geochemical processes. Aiming to identify the origin of such abnormalities, exploratory and spatial data analysis (EDA-SDA) method was applied on a hydrogeochemical data set obtained through 5 sampling campaigns in 32 groundwater monitoring wells installed upstream and downstream of the area impacted by the steel mill activities. Boxplot class-based and Eh vs. pH maps of physicochemical log-transformed data identified that wells located under the influence of EAF slag deposits in topographic hollows had lower Eh potential and increased electrical conductivity and pH, when compared to wells in the topographical nose of the surveyed area. Metal distribution maps showed that Al, Ca, K, Mg, Na, and Sr were consistently higher in topographic hollows while concentrations of Co, Cu, Cr, and Li were higher near the former steel-making plant, located in the topographical nose. Ba, Fe, Mn, and Zn, important indicators of EAF slag and dust, were observed in both topographic settings. Variable clustering was able to capture the relations among metals and thus validate the log-normalized data structure to be used into wells clustering. Clustering through the mclust algorithm carried out for two and three clusters allowed the distinction among localities that received an input of metals from dust or slag and those not influenced by either residue. This paper demonstrates that EDA-SDA is an effective method to identify areas under the influence of contamination from industrial activities from areas not affected by anthropogenic contamination.

The aim of this study is to develop a process that combines electrocoagulation and electroperoxidation (EC-EP) and to evaluate its performance in treating domestic wastewaters (DWW). Electrolysis was performed using a parallelepipedic electrolytic cell (0.5 L) containing one sacrificial anode (mild steel or aluminum) and one cathode (vitreous carbon). The effects of the treatment time, current density, and type of anode electrode on the process performance were examined. The experimental results revealed that a current density of 4.0 mA cm⁻² was beneficial for DWW treatment. There was a decrease in the chemical oxygen demand (COD), suspended solid (SS), turbidity, color, and total phosphorus (Pₜₒₜ) by 67 ± 9, 98 ± 2, 55 ± 10, 61 ± 9, and 97 ± 0 %, respectively, for a treatment time of 60 min in the electrolysis cell in the presence of mild steel (anode) and vitreous carbon (cathode) electrodes. The process was also determined to be effective for removing pathogens (99 ± 1 % removal), such as fecal coliform (the log-inactivation was higher than 2 units).

Submerged harbor steel structures often employ cathodic protection using galvanic anodes to guard against corrosion. A laboratory experiment, with three different cathodic protection configurations by galvanic aluminum-based anodes, was performed to evaluate the potential metal transfer from the anodic alloy dissolution into the surrounding marine water. The anode dissolution rate is proportional to the imposed current demands and induced a significant Al, In, and Zn transfer in the dissolved and particulate fractions of the corrosion product layers covering the anode surface. These layers were poorly adherent, even under low hydrodynamic conditions. Consequently, at the anode vicinity, the suspended particle matter and dissolved fraction of surrounding marine waters showed strong enrichments in Al and Zn, respectively, the values of which could potentially affect the adjacent biota. After the anode activation period, however, the metal inputs from galvanic anode dissolution are rapidly diluted by seawater renewal. At regional scale, these metal fluxes should be negligible compared to river and wastewater fluxes. These results also showed that it is difficult to assess the impact of the anode dissolution on the concentrations of metals in the natural environment, especially for metals included in trace amounts in the anode alloy (i.e., Cu, Fe, In, Mn, and Si) in the aquatic compartment.

In the present study, 28 polycyclic aromatic hydrocarbons (PAHs) were investigated in four sediment cores collected from the main river estuaries of Chaohu Lake, one of the severely polluted lakes in China. The results indicate that elevated concentrations of total PAHs (Σ₂₈PAH) were found in the samples from the estuary of Nanfei River (ENF), considering BaP-based total toxicity equivalent (TEQ-BaP) and toxic unit (TU) results; there are potential adverse environmental implications. The total organic carbon (TOC) played an important role on the accumulation of PAHs at ENF and the estuary of Tongyang River (ETY). The predominant PAHs are high molecular weight (HMW) homologous for all samples; as a result, industrial wastewater from a steel company is expectedly the key source of PAHs in ENF, while coke consumption would be the important source of PAHs at other three sampling sites. Vertical distribution of PAHs in the sediment cores could be explained by the local social and economic activities. Furthermore, a minor variation of PAH composition in the sediment core could be justified by the stable structure of energy consumption in the Anhui Province. These results justify the need for further enhancement of industrial wastewater treatment and development of renewable energies which are the key factors on the control of PAH pollution in China.

In this study, As-, Pb-, and Cu-contaminated soil was stabilized using calcined oyster shells (COS) and steel slag (SS). The As-contaminated soil was obtained from a timber mill site where chromate copper arsenate (CCA) was used as a preservative. On the other hand, Pb- and Cu-contaminated soil was obtained from a firing range. These two soils were thoroughly mixed to represent As-, Pb-, and Cu-contaminated soil. Calcined oyster shells were obtained by treating waste oyster shells at a high temperature using the calcination process. The effectiveness of stabilization was evaluated by 1-N HCl extraction for As and 0.1-N HCl extraction for Pb and Cu. The treatment results showed that As, Pb, and Cu leachability were significantly reduced upon the combination treatment of COS and SS. The sole treatment of SS (10 wt%) did not show effective stabilization. However, the combination treatment of COS and SS showed a significant reduction in As, Pb, and Cu leachability. The best stabilization results were obtained from the combination treatment of 15 wt% COS and 10 wt% SS. The SEM-EDX results suggested that the effective stabilization of As was most probably achieved by the formation of Ca-As and Fe-As precipitates. In the case of Pb and Cu, stabilization was most probably associated with the formation of pozzolanic reaction products such as CSHs and CAHs.