Elevated toxins in soybeans extensively threaten Asian residents and over one billion vegetarians worldwide. An integrated dataset of toxic trace metal(loid)s especially cadmium (Cd) analysis in soybean grain samples (n = 5217) from 12 countries/regions of origin was compiled for risk analysis. Worldwide grain Cd averaged 0.093 mg kg⁻¹, but mean values varied 16-fold between regions, with South China (0.32 mg kg⁻¹) > Argentina (0.15 mg kg⁻¹) = German (0.13 mg kg⁻¹) > Japan (0.11 mg kg⁻¹) > the United States (0.064 mg kg⁻¹) > Central-North China (0.020–0.60 mg kg⁻¹) ≥ Iran (0.042 mg kg⁻¹) = Brazil (0.023 mg kg⁻¹) = South Korea (0.020 mg kg⁻¹). Regression analysis suggested widespread contamination and acidic soil features significantly contributed the elevated food Cd contamination worldwide. Arsenic (As) and lead (Pb) are also of concern because excessive levels were often observed in grains. Given that soil Cd bioavailability is generally low in alkaline pH ranges, the feasibility of producing safe food from contaminated land was investigated by greenhouse experiments with one low-Cd soybean cultivar grown on 20 contaminated calcareous soils. Equilibrium-based approaches i.e., 0.01 M CaCl₂ and in-situ porewater extractions, and diffusion-based diffusive gradients in thin-films technique were used to determine the plant-available fractions of soil metal(loid)s to explain the bioaccumulation variation. The results suggested that soybean grains bioaccumulated mean 0.76 mg Cd kg⁻¹, ranging from 0.16 to 2.1 mg kg⁻¹, whereas As and Pb bioaccumulation was low. Cadmium accumulation was closely correlated with plant-available Cd fractions especially the 0.01 M CaCl₂-extractable Cd, but negatively correlated with soil pH. Even in the alkaline pH range, a slight decrease of soil pH would increase grain Cd significantly. Study region and those arable lands that have similar soil conditions are not recommended for growing soybean unless novel remediation strategies are developed.

In this work, a sand and dust storm vulnerability mapping (SDS-VM) approach is developed to model the vulnerability of urban blocks to SDS using GIS spatial analysis and a range of geographical data. The SDS-VM was carried out in Ahvaz, IRAN, representing one of the most dust-polluted cities in West Asia. Here, vulnerability is defined as a function of three components: exposure, sensitivity, and adaptive capacity of the people in the city blocks to sand and dust storms. These components were formulated into measurable indicators (i.e. GIS layers) including: PM₂.₅, wind speed, distance from dust emission sources, demographic statistics (age, gender, family size, education level), number of building floors, building age, land surface temperature (LST), land use, percentage of literate population, distance from health services, distance from city facilities (city center, shopping centers), distance from infrastructure (public transportation, main roads and highways), distance from parks and green spaces, and green area per capita. The components and the indicators were weighted using analytical hierarchy process (AHP). Different levels of risks for the components and the indicators were defined using ordered weighted averaging (OWA). Urban SDS vulnerability maps at different risk levels were generated through spatial multi-criteria data analysis procedure. Vulnerability maps, with different risk levels, were validated against field-collected data of 781 patients hospitalized for dust-related diseases (i.e. respiratory, cardiovascular, and skin). Results showed that (i) SDS vulnerability map, obtained from the developed methodology, gives an overall accuracy of 79%; (ii); regions 1 and 5 of Ahvaz are recognized with the highest and lowest vulnerabilities to SDS, respectively; and (iii) ORness equal to 0 (very low risk) is the optimum SDS-VM risk level for decision-making to mitigate the harmful impacts of SDS in the deposition areas of Ahvaz city.

Traffic emissions are a complex and variable cocktail of toxic chemicals. They are the major source of atmospheric pollution in the parts of cities where people live, commute and work. Reducing exposure requires information about the distribution and nature of emissions. Spatially and temporally detailed data are required, because both the rate of production and the composition of emissions vary significantly with time of day and with local changes in wind, traffic composition and flow. Increasing computer processing power means that models can accept highly detailed inputs of fleet, fuels and road networks. The state of the science models can simulate the behaviour and emissions of all the individual vehicles on a road network, with resolution of a second and tens of metres. The chemistry of the simulated emissions is also highly resolved, due to consideration of multiple engine processes, fuel evaporation and tyre wear. Good results can be achieved with both commercially available and open source models. The extent of a simulation is usually limited by processing capacity; the accuracy by the quality of traffic data. Recent studies have generated real time, detailed emissions data by using inputs from novel traffic sensing technologies and data from intelligent traffic systems (ITS). Increasingly, detailed pollution data is being combined with spatially resolved demographic or epidemiological data for targeted risk analyses.

To evaluate BPA's potential risk to health, it is important to know human daily intake. This study describes a simple but effective method to estimate the levels of human BPA intake among four different populations based on urinary concentration data. Nationally, of the 30 countries examined, the top ten countries for adult intake were Italy, Sweden, Denmark, France, Cyprus, Australia, Israel, Ghana, Jamaica, and Belgium. When the urinary excretion sample size was large enough and over 1000, it was found that the national estimated BPA daily intakes in the child group among countries, showed a good linear relationship with those of their corresponding adult group. Except the infant group with limited data, the global estimated BPA daily intakes for children and pregnant women were 2 and 1.4 times that of the adult group. Although the national and global estimated BPA daily intakes were generally below the temporary tolerable daily intake (tTDI) recommended by the European Food Safety Authority (EFSA), but some normal individuals' daily intakes exceeded the tTDI.

In epidemiological studies on the toxic effects of prenatal exposure to hexachlorobenzene (HCB), researchers report HCB concentrations, either as wet-weight or per lipid weight basis, in matrices like breast milk, and maternal and cord blood. Conversion of exposures across matrices is needed for comparisons of concentrations and dose effect across cohorts. Using data from a birth cohort study in eastern Slovakia, we derived the maternal blood to cord blood HCB concentration ratio utilizing measured concentrations in 1027 paired maternal and cord blood samples, on a per-lipid basis. In addition to data from the Slovak study, the maternal milk to maternal serum ratio was summarized from 23 published studies on partitioning of HCB between human milk lipid and blood lipid. We identified two distinct groups of milk:blood ratios, those ≤0.45 and those ≥0.85. We assumed that using partition ratios ≤0.45 will underestimate HCB exposure estimates. Taking into account this precautionary measure, we suggest a conversion ratio of 1.21, which is the median of the 16 ratios identified in our literature review. We consider our estimate as conservative and providing appropriate safety in risk analysis.

We assessed the level of atmospheric contamination by S, N and metals before, during and after the installation of a new thermoelectric plant that provides power to an oil refinery in Cubatão, SE Brazil. We measured the foliar accumulation in Lolium multiflorum “Lema” with the aim of evaluating risks to the Atlantic Rainforest that grows in the region. Al, Co, Cr, Cu, K, N, Ni, S, V and Zn were appropriate markers of the new air contamination profile associated with the modern technology. With the exception of V, the leaf contents of these elements significantly increased between the pre-operation to post-operation phases (Al, Co, N, K, S), or only during the transition phase (Zn, Cu, Cr, Ni), and returned to the previous levels after the total shutdown of the old system. Therefore, the expected environmental gain was not achieved with the installation of the new technology.

The objective of this study was to report, for the first time, the presence of an invasive coral (Tubastraea tagusensis) in an oil platform on the Brazilian equatorial continental shelf. This structure is located more than 1200 km north from other oil and gas structures colonized by this coral. We also discussed the retirement and decommissioning of old biofouling-encrusted oil and gas platforms (~62 platforms) from decreased production and the current oil crisis, exacerbated by the COVID-19 pandemic. This presents an ecological concern due invasive coral range expansion and potential impacts to poorly studied ecosystems such as marginal shallow-water coral reefs and mesophotic ecosystems. It is imperative that mindful risk analysis and rigorous environmental studies must precede the installation of new oil and gas platforms. In addition, decommissioning of retired structures should take into consideration marine restoration and non-indigenous species dispersal, and more specifically, Tubastraea bioinvasion.

Diffuse pollution from oil spills is a widespread problem in port areas (as a result of fuel supply, navigation and loading/unloading activities). This article presents a method to assess the environmental risk of oil handling facilities in port areas. The method is based on (i) identification of environmental hazards, (ii) characterization of meteorological and oceanographic conditions, (iii) characterization of environmental risk scenarios, and (iv) assessment of environmental risk. The procedure has been tested by application to the Tarragona harbor. The results show that the method is capable of representing (i) specific local pollution cases (i.e., discriminating between products and quantities released by a discharge source), (ii) oceanographic and meteorological conditions (selecting a representative subset data), and (iii) potentially affected areas in probabilistic terms. Accordingly, it can inform the design of monitoring plans to study and control the environmental impact of these facilities, as well as the design of contingency plans.

Existing models estimating oil spill costs at sea are based on data from the past, and they usually lack a systematic approach. This make them passive, and limits their ability to forecast the effect of the changes in the oil combating fleet or location of a spill on the oil spill costs.In this paper we make an attempt towards the development of a probabilistic and systematic model estimating the costs of clean-up operations for the Gulf of Finland. For this purpose we utilize expert knowledge along with the available data and information from literature. Then, the obtained information is combined into a framework with the use of a Bayesian Belief Networks. Due to lack of data, we validate the model by comparing its results with existing models, with which we found good agreement.We anticipate that the presented model can contribute to the cost-effective oil-combating fleet optimization for the Gulf of Finland. It can also facilitate the accident consequences estimation in the framework of formal safety assessment (FSA).

In marine settings, anthropogenic disturbances and climate change increase the rate of biological invasions. Predicting still undescribed invasive alien species (IAS) is needed for preparing timely management responses. We tested a strategy for discovering new potential IAS using DNA in a trans-equatorial expedition onboard RV Polarstern. During one-month travel, species inside ballast water experienced oxygen depletion, warming, darkness and ammonium stress. Many organisms died but several phytoplankton and zooplankton survivors resisted and were detected through a robust combination of individual sampling, DNA barcoding and metabarcoding, new in ballast water studies. Ammonium was identified as an important influential factor to explain diversity changes in phytoplankton and zooplankton. Some species reproduced until the end of the travel. These species tolerant to travel stress could be targeted as potential IAS and prioritized for designing control measures. Introducing resistance to travel stress in biosecurity risk analysis would be recommended.