An intensive monitoring campaign of PAHs for assessing the impact of a steel plant

A sensing network involving citizens for high spatio-temporal resolution monitoring of fugitive emissions from a petroleum pre-treatment plant

In this study an innovative sensing network consisting of eight photoionization detectors, meteorological sensors, a video camera and a telephonic system able to systematize the population complaints was developed for the monitoring of odor emissions. The development of monitoring approaches with high temporal and spatial resolution and actively involving citizens, is strategic in areas where relevant and also short-term emissive events frequently occur and the conventional approaches fail due to the high variability of fugitive emissions. Moreover, even if unpleasant odors are not necessarily direct triggers of health effects, they could be associated with the release of other harmful compounds. Monitoring approaches also involving citizens are thus strategic tools because odors annoyance perceived by population may be a potential health risk warning. Therefore, the developed sensing network was set up in Val d'Agri (Basilicata, Italy) where a petroleum pre-treatment plant (COVA) rises in a rural and inhabited area. The data collected during the monitoring campaign from the 16th February to the 30th July 2017, showed Total Volatile Organic Compounds (TVOCs) concentrations decreasing moving away from the plant and up to five times higher than levels registered in the closest municipality (Viggiano). Moreover, recurrent short-term critical events characterized by concentration values far above the average of the period and with maximum values ranging from 0.92 to 1.89 ppm, were registered in correspondence with high levels of benzene (up to 23.9 μg/m³) and anemometric conditions able to transport pollutants from COVA to each receptor site. The spatial and temporal distribution of TVOC concentrations proved to be affected by the distance from COVA, wind direction and industrial activities verified using video reportage and citizen claims. Therefore, the developed approach has proven to be a useful tool to credit people's perception of odors and also to quantify citizen exposure to VOCs during short-term events.

Environment impact and probabilistic health risks of PAHs in dusts surrounding an iron and steel enterprise

Dust can be regarded as environmental medium that indicates the level and spatial distribution of polycyclic aromatic hydrocarbons (PAHs) coming from different pollution sources. In this study, samples including road dust, roof dust, and bare soil near an iron and steel enterprise (ISE) in Laiwu city of North China were collected. To assess the environment impact, atmosphere particulates and one flue dust from a coking plant were simultaneously sampled. Sixteen USEPA PAHs were detected quantitatively by Gas Chromatography Mass Spectrometry (GC-MS). A laser particle size analyzer was used to obtain the grain size of the dust particle samples. The results showed that PAH concentrations displayed great variability in the dust samples. The ∑₁₆PAHs concentration was found to be between 0.460 and 46.970 μg/g (avg ± sd 10.892 ± 1.185 μg/g) in road dust, between 0.670 and 17.140 μg/g (avg ± sd 6.751 ± 0.692 μg/g) in roof dust, and 13.990 ± 1.203 μg/g in bare soil. In the environment atmosphere sites, the ∑₁₆ PAHs value in PM_2.5 constituted a very large proportion of PM₁₀, indicating that PAHs in finer particle sizes should be given greater emphasis. The ∑₁₆PAHs concentration was relatively high in the area close to the ISE because of the great impact of the ISE industrial activities. PAH concentration curves were similar, and the most abundant individual PAHs in the atmosphere sites were BbF, BkF, and Flu, and BbF, BkF, and Chry in dusts. Toxicity analysis revealed that PAHs with four rings, including carcinogenic PAHs, were the dominant pollutants in the studied area. The toxic equivalency value (TEQ_BaP), the carcinogenic health risk assessment value recommended by the US EPA, was calculated for seven carcinogenic PAHs, revealing that they account for more than 93.0% of the total TEQ_Bap of the 16 PAHs and indicating the major toxic equivalent concentration contributor. Incremental lifetime cancer risk (ILCR) estimation results showed that PAHs tended to bring about great health risks through skin contact, followed by ingestion and inhalation. By comparison, road dust exhibited greater carcinogenic risks than roof dust, and bare soil may undergo heavier pollution. Therefore, the results of this study would be helpful in the effort to understand the PAHs pollution from the steel industry, which will provide some guidance for the probabilistic assessment of local health risks.

Uptake and distributions of polycyclic aromatic hydrocarbons in cultivated plants around an E-waste disposal site in Southern China

Polycyclic aromatic hydrocarbons (PAHs) in air, soil, and cultivated plants at e-waste disposal sites in Taizhou, Zhejiang Province, were determined to allow PAH uptake by and distributions in plants to be investigated. The PAH distributions in air, rhizosphere soil, and surface soil were markedly different. This indicated that root morphology variations and root exudates may affect PAH compositions in soil around plants. The PAH concentrations in the plant samples were 29.7-2170 ng/g. The lowest PAH concentration was found in a peeled taproot sample. The PAH concentration gradients from the plant shoots to roots suggested that PAHs entered the plants through various pathways. The three- and four-ring PAHs were found to be absorbed more readily than the higher-molecular-weight (five- and six-ring) PAHs. This indicated that high-molecular-weight PAHs in soil can be prevented from entering plants, particularly taproots, via root exudates and the root peel. For most plants, the highest PAH concentrations were found in leaves, indicating that atmospheric deposition may strongly affect PAH concentrations in aerial plant parts. High-molecular-weight PAHs are more readily absorbed from ambient air by leaves than other parts. Lower PAH concentrations were found in fruits than other plant parts. This and the differences in PAH distributions between fruits and other aerial parts indicated that PAHs may be selectively absorbed by fruits.

[Contribution of Emissions from the Iron and Steel Industry to Air Quality in China]

Based on the data from a continuous emission monitoring systems network in 2015, this study analyzed the compliance rates of exhaust gas in the processes of China's iron and steel industry, and established a high-resolution steel plant emission inventory for China (HSEC, 2015), based on the bottom-up method. The contribution of emissions from the iron and steel industry to regional air quality was quantitatively simulated using a CAMx model. The results showed that in 2015, the total emissions of SO₂, NO_x, PM₁₀, PM_2.5, PCDD/Fs, VOCs, CO, BC, OC, EC, and F were 374800 t, 720500 t, 334800 t, 150300 t, 1.91 kg, 842900 t, 34788500 t, 6400 t, 8300 t, 800 t, and 7700 t, respectively. From a regional perspective, the iron and steel industry in Shanghai and Tianjin has the highest emission intensity per unit area and contributes a high proportion to regional air pollution. From a process perspective, in 2015, the exhaust concentration of flue gas in the main process gradually decreased, with a high compliance rate, and the emission factor significantly decreased to lower than that in the existing research results. From a species perspective, in 2015, NO_x emission from the steel industry contributed the most to regional air quality, and there is therefore a great emission reduction potential for NO_x.

Particle-Bound PAHs and Elements in a Highly Industrialized City in Southern Italy: PM2.5 Chemical Characterization and Source Apportionment after the Implementation of Governmental Measures for Air Pollution Mitigation and Control

The present study was aimed at determining airborne concentrations of PAHs, Nitro-/Oxy-PAHs and elements in industrial and urban areas of Taranto, a site of environmental risk in Southern Italy, after the issue of strategic measures for air pollution mitigation and control by the Italian Environment Ministry in 2012. A PM_2.5 sampling campaign was carried out from 9 to 28 December 2014 at eight receptor sites, two placed in the urban settlement and five included in the high spatial resolution fence monitoring network of the biggest European steel plant. The integration of collected data with meteorological parameters and source apportionment analysis by Positive Matrix Factorization and bivariate polar plots allowed to discriminate among emission sources and estimate their contributions. Evidence on the effect of distinct processes (homogenization, sintering) occurring inside the steel plant on airborne concentrations of PAHs and selected elements was provided. The impact of emissions from the steel plant “core” on the surrounding area was observed at receptor sites downwind to it. Moreover, the extent of the effectiveness of mitigation measures, partially applied at the moment of study’s beginning, was demonstrated by mean and peak pollutant concentrations at all receptor sites up to one order of magnitude lower than those documented prior to 2012.

Total p-PAH Levels Nearby a Complex Industrial Area: A Tailored Monitoring Experiment to Assess the Impact of Emission Sources

In this study, data on the hourly concentrations of the total particle-bound Polycyclic Aromatic Hydrocarbons (p-PAHs) collected between 1 August 2013 and 31 August 2014 by the air quality fence monitoring network of the biggest European steel plant, were analyzed. In contrast with what was predicted, the total p-PAH concentration did not decrease with distance from the steel plant, and higher concentrations were registered at the Orsini site, in the urban settlement, relative to the Parchi site, which is nearest to the coke ovens. Therefore, in order to identify and explain the cause of these high concentrations, a tailored monitoring experiment was carried out on a specific monitoring pathway by using a total p-PAHs monitor placed onto a cart. The real-time monitoring of the total p-PAH concentration on the road revealed to be a useful tool, which identified vehicular traffic as an important source of p-PAHs and highlighted the possible high short-term effect that vehicular traffic sources could have on the health of the exposed human population. Moreover, the study focused attention on the importance of the spatial representativeness of fixed monitoring stations, especially in a highly complex industrial area such as Taranto (Southern Italy).

Distribution Pattern, Emission Characteristics and Environmental Impact of Polycyclic Aromatic Hydrocarbons (PAHs) in Download Ash and Dust from Iron and Steel Enterprise

Download ash and emission dust samples were collected from sintering, coking, ironmaking and steelmaking processes of iron and steel enterprises in Laiwu. Sixteen kinds of polycyclic aromatic hydrocarbons (PAHs) in the United States Environmental Protection Agency (USEPA) priority controlled lists were quantitatively analyzed using Gas Chromatography-Mass Spectrometer (GC-MS). Laser particle size analyzer was used to obtain the distribution pattern of download ash. It was found that the diameter distribution pattern from four production processes was quite different. The proportion of fine particulate (0–2.5 μm) was the highest (72.62%) in the steelmaking refining process, and was 28.962% in the ironmaking process. Moreover, the particle size in download ash from steelmaking refining is all less than 10 μm and that from the ironmaking process was 52.92%. The medium-sized particles (10–100 μm) were dominant in sinter and coking download ashes. The total PAHs (∑₁₆PAHs) mass concentration ranged from 0.49 ± 0.06 to 69.63 ± 5.57 μg·g⁻¹ in download ash samples, and varied from 2.815 ± 0.253 to 19.429 ± 2.545 μg·m⁻³ in emission dust samples. The ∑₁₆PAHs values were both largest in download ash and dust emission from the coking process (69.63 ± 5.57 μg·g⁻¹ and 19.429 ± 2.545 μg·m⁻³, respectively). The most abundant individual PAHs were benzo[b]fluoranthene, benzo[k]fluoranthene, phenanthrene, benzo[a]anthracene in ash samples, and benzo[a]anthracene, benzo[k]fluoranthene, benzo[b]fluoranthene and indeno[1,2,3-cd]pyrene in emission dust samples. Dominant compounds were high-molecular weight (four- to six-ring) PAHs in both ash and dust samples. The concentration order of individual compounds in PM₁₀ and PM_2.5 in ambient air around the steel plant was completely consistent with each other, and the concentration of ∑₁₆PAHs was the highest in the steel plant and lowest in Daqin village because of upwind of the steel plant. The concentrations of benzo[b]fluoranthene and fluoranthene in ambient air were comparatively high, and were in accordance with the higher concentration of the two monomers in the download ash samples, which suggested that the effect of the emission flue gas from the steel plant on ambient air was necessary to concern.

Source apportionment of soil PAHs and human health exposure risks quantification from sources: the Yulin National Energy and Chemical Industry Base, China as case study

The Yulin National Energy and Chemical Industry Base is widely known for its rich mineral resources and multi-type fossil chemical industry, yet little is known regarding the level of contaminants. Therefore, this study investigates the spatial distributions and potential exposure risk of ubiquitous polycyclic aromatic hydrocarbons (PAHs) contamination in this region and apportions PAHs source and source-oriented risk using two mathematical models, principal component analysis-multiple linear regression (PCA-MLR) model and positive matrix factorization (PMF) model coupling human health exposure risk. Results showed that ∑₁₆PAHs concentrations ranged from 110 to 4934 μg/kg dw in 38 soil sampling sites. Compared with PCA-MLR model, PMF model is preferred method for source apportionment. Source apportionment results derived from PMF model indicated that the dominant contribution to ∑₁₆PAHs was from coal-derived sources (34% for coke oven emissions and 33% coal combustion source), followed by wood combustion (22%) and vehicular emission (11%). The human health exposure risk of each source category was quantitatively calculated for three exposure routes by combining the total carcinogenic risk (Total-CR) and total hazard index (Total-HI) values with identified source contributions. The results showed that increased Total-CR was highly apportioned from coke oven emissions source and coal combustion was identified as the major cause of increased Total-HI, even though it was less contributed to ∑₁₆PAHs. Moreover, the distributions of Total-CR and Total-HI apportionment for each source were significantly influenced by land utilization types.

Use of inorganic and organic markers associated with their directionality for the apportionment of highly correlated sources of particulate matter

Particulate matter source identification using receptor models is one of the tools applied in air quality management. These models have limitations such as the collinearity effects, hindering their application and interpretation. Positive Matrix Factorization (PMF) models use chemical markers for the definition of likely sources, leaving to users the factors interpretation. This can lead to biased interpretations, as chemical species can be markers for several sources, particularly when there is source similarity. The Region of Greater Vitória, located southeast of Brazil, is a complex site in which similar industrial activities are installed, such as a pelletizing plant and a steel plant, that produce iron pellets and sinter, both iron-agglomerates with similar chemical profiles. To minimize the effects of collinearity between those sources, a new PMF approach is proposed by using inorganic and organic chemical species and the directionality of pollutant using wind roses. The proposed methodology determines the following consolidated markers: elemental carbon (EC) and organic carbon (OC) for vehicular sources; chloride (Cl) and sodium (Na) for sea salt; iron (Fe) for industrial sources. This association was possible by identifying the directionality of the chemical species. Cl a typical sea salt marker also attributed to industrial sintering activities. Some PMF factors showed high OC loadings, a typical marker for both vehicular exhaust and coal burning. The definition of the most appropriate sources for those factors was only possible due to the assessment of the pollutant roses. Pollutant roses generally showed that higher concentrations of potassium (K), a marker of biomass burning, was predominantly associated with winds from an industrial park, and are most likely associated with sintering emissions. Results showed that combining both organic and inorganic markers with the pollutant roses for identification of the directionality of predominant sources improved the interpretation of PMF factor numbers in source apportionment studies.

Using multi-site data to apportion PM-bound metal(loid)s: Impact of a manganese alloy plant in an urban area

The identification and quantification of the PM emission sources influencing a specific area is vital to better assess the potential health effects related to the PM exposure of the local population. In this work, a multi-site PM₁₀ sampling campaign was performed in seven sites located in the southern part of the Santander Bay (northern Spain), an urban area characterized by the proximity of some metal(loid) industrial sources (mainly a manganese alloy plant). The total content of V, Mn, Fe, Ni, Cu, Zn, As, Mo, Cd, Sb and Pb was determined by ICP-MS. This multi-site dataset was evaluated by positive matrix factorization (PMF) in order to identify the main anthropogenic metal(loid) sources impacting the studied area, and to quantify their contribution to the measured metal(loid) levels. The attribution of the sources was done by comparing the factor profiles obtained by the PMF analysis with representative profiles from known metal(loid) sources in the area, included in both the European database SPECIEUROPE (V2.0) and the US database EPA-SPECIATE (V4.5) or calculated from literature data. In addition, conditional bivariate probability functions (CBPF)s were used to assist in the identification of the sources. Four metal(loid) sources were identified: Fugitive and point source emissions from the manganese alloy plant (49.9% and 9.9%, respectively), non-exhaust traffic emissions (38.3%) and a minor source of mixed origin (1.8%). The PMF analysis was able to make a clear separation between two different sources from the manganese alloy plant, which represented almost 60% of the total measured metal(loid) levels, >80% of these emissions being assigned to fugitive emissions. These results will be useful for the assessment of the health risk associated with PM₁₀-bound metal(loid) exposure and for the design of efficient abatement strategies in areas impacted by similar industries.

Composition of Metallic Elements and Size Distribution of Fine and Ultrafine Particles in a Steelmaking Factory

Background: The characteristics of aerosol, in particular particle size and chemical composition, can have an impact on human health. Particle size distribution and chemical composition is a necessary parameter in occupational exposure assessment conducted in order to understand possible health effects. The aim of this study was to characterize workplace airborne particulate matter in a metallurgical setting by synergistically using two different approaches; Methodology: Analysis of inhalable fraction concentrations through traditional sampling equipment and ultrafine particles (UFP) concentrations and size distribution was conducted by an Electric Low-Pressure Impactor (ELPI+™). The determination of metallic elements (ME) in particles was carried out by inductively coupled plasma mass spectrometry; Results: Inhalable fraction and ME concentrations were below the limits set by Italian legislation and the American Conference of Governmental Industrial Hygienists (ACGIH, 2017). The median of UFP was between 4.00 × 10⁴ and 2.92 × 10⁵ particles/cm³. ME concentrations determined in the particles collected by ELPI show differences in size range distribution; Conclusions: The adopted synergistic approach enabled a qualitative and quantitative assessment of the particles in steelmaking factories. The results could lead to a better knowledge of occupational exposure characterization, in turn affording a better understanding of occupational health issues due to metal fumes exposure.

Source profiles and contributions of biofuel combustion for PM2.5, PM10 and their compositions, in a city influenced by biofuel stoves

Source and ambient samples were collected in a city in China that uses considerable biofuel, to assess influence of biofuel combustion and other sources on particulate matter (PM). Profiles and size distribution of biofuel combustion were investigated. Higher levels in source profiles, a significant increase in heavy-biomass ambient and stronger correlations of K⁺, Cl^-, OC and EC suggest that they can be tracers of biofuel combustion. And char-EC/soot-EC (8.5 for PM_2.5 and 15.8 for PM₁₀ of source samples) can also be used to distinguish it. In source samples, water-soluble organic carbon (WSOC) were approximately 28.0%-68.8% (PM_2.5) and 27.2%-43.8% (PM₁₀) of OC. For size distribution, biofuel combustion mainly produces smaller particles. OC1, OC2, EC1 and EC2 abundances showed two peaks with one below 1 μm and one above 2 μm. An advanced three-way factory analysis model was applied to quantify source contributions to ambient PM_2.5 and PM₁₀. Higher contributions of coal combustion, vehicular emission, nitrate and biofuel combustion occurred during the heavy-biomass period, and higher contributions of sulfate and crustal dust were observed during the light-biomass period. Mass and percentage contributions of biofuel combustion were significantly higher in heavy-biomass period. The biofuel combustion attributed above 45% of K⁺ and Cl^-, above 30% of EC and about 20% of OC. In addition, through analysis of source profiles and contributions, they were consistently evident that biofuel combustion and crustal dust contributed more to cation than to anion, while sulfate & SOC and nitrate showed stronger influence on anion than on cation.