Honey is both a complex food and medicine as well as a healthy alternative to refined sugar. Besides a complex mixture of carbohydrates, honey contains other minor substances which may threaten human ...health in excess concentrations. Several environmental conditions can affect the quality of honey. This research paper aims to measure the degree of heavy metals (Lead (Pb), Cadmium (Cd), Zinc (Zn), and Copper (Cu)) in some polyfloral honey from an industrial area of Romania, considered to be one of the most polluted regions in Eastern Europe. The samples were collected from six stationary apiaries and analysed using the atomic absorption spectrometry method. The content of Pb was higher in the sampling areas exposed directly to the polluted air masses. Cd concentration decreases exponentially while Cu concentration increases as the distance from the source of pollution increases. The checking of the quality of polyfloral honey from local producers is imperative because this product is intended to be consumed by the beekeeper's family or the local community without being sold to an authorised processor. The results of the study can help to set a threshold for the concentration of Pb and Cd in honey marketed in the European Union.
The impact of air pollution on forests, especially in urban areas, has been increasingly discussed recently. Many pollutants, including heavy metals, are released into the atmosphere from various ...sources, such as mining, non-ferrous metal processing plants, and fossil fuel combustion. These pollutants can adversely affect not only tree growth but also other species, including humans.
This study compared the concentrations of several elements in tree-ring wood from two conifer species (Silver fir, Abies alba; Norway spruce, Picea abies) growing in polluted and unpolluted areas. Two regions in northern Romania (Bicaz and Tarnița) that were subjected to historical pollution changes were selected. Two chemical analyses were used: inductively coupled plasma mass spectrometry (ICP-MS) and X-ray fluorescence spectrometry (XRF).
The silver fir trees from the intensively polluted area in the Tarnița region were negatively impacted by industrial pollution: the Mn concentrations were, on average, three times higher in polluted areas than in unpolluted areas (ca. 30 vs. 10 mg kg−1). This finding was consistent for both ICP-MS and XRF analyses. However, in Norway spruce, this difference was found only in the XRF data, which detected Mn concentrations seven times higher in trees from polluted areas than those from unpolluted areas (ca. 700 vs. 100 mg kg−1). In the Tarnița region, Norway spruce accumulated more heavy metals than silver fir, but the most pronounced differences between polluted and unpolluted areas were found in silver fir.
The two analytical methods are commonly used to determine metal concentrations in wood, and they complement each other, with ICP-MS having a low detection limit for some elements and XRF having higher detection limits and better accuracy. Each method has its advantages and disadvantages, and the optimal method depends on many factors, such as the type of heavy metal analyzed, its concentration in wood, sample type, cost, analysis time, and sample preparation.
Display omitted
•Trees have the ability to accumulate heavy metals from the pollution caused by local industries.•Heavy metal concentrations in tree rings decrease over time as pollution decreases.•Higher concentrations of heavy metals are found in trees close to factories.
Discharge of urban domestic pollution has risen sharply during China's extensive urbanization. Together with understanding the complexity of influencing factors underpinning this rise, it has become ...a pressing issue to estimate total discharge and illustrate its driving mechanism scientifically. This paper reports on the monitoring of discharge from 36 sampling sites in selected residential districts in the heavily polluted Taihu Basin, China. The data were used to estimate the total amount of discharge, to develop corresponding urban domestic pollutant discharge coefficients and to analyse associated spatial patterns. Data from a questionnaire survey of over 1000 households in downtown, suburb and market town areas were then used to apply an econometric model in order to distinguish driving mechanisms. The urban domestic pollutant discharge coefficients developed in this paper are generally smaller than those reported nationally for China, based on more generalised data, decaying from city centres to the urban periphery. This study quantifies the amount of discharge and also demonstrates that urban domestic pollutant discharge is driven by multiple factors. For example, urban domestic pollution discharge rates were positively correlated with income and female-dominated households also tend to discharge more wastewater. Other factors were found to have negative correlations, such as sewage treatment rates, awareness of environmental protection, age and degree of education. As well as providing new and refined data on urban pollution discharge characteristics, the research in this paper also demonstrates the utility of combining household questionnaire and sample monitoring data in order to yield greater insights into the causes of typical polluting behaviour in Chinese neighbourhoods.
•The customized coefficient of urban domestic pollutant discharge is smaller.•The coefficient of pollutant discharge decays from city centres to urban periphery.•Urban domestic pollutant discharge is driven by multiple factors.•Higher incomes residents and female-dominated families lead to higher discharge.•Environmental awareness, age, education level and treatment rate play negative roles.
Nowadays, heavy metals are regarded as the most significant contaminants due to industrial activities and have an impact on their presence in milk. The presence of heavy metals in milk could have a ...serious negative impact on public health. The current study aims to determine the amount of various heavy metals (Pb, Cu, Co, Cd, Cr, Ni, Fe, and Zn) in raw Awassi ewe’s milk collected from Kwashe industrial area, Duhok province, Kurdistan Region, Iraq. The sheep were grazed in Sulaivany plain contaminated by drains of industrial effluents of several crude oil refineries and other 200 different factories. Atomic absorption spectrophotometer was utilized to analyze the milk specimens after wet digestion. Results displayed that the heavy metals concentration was in the range of 3.64-4.27 mg/L for Pb, 0.59-1.13 mg/L for Cu, 0.01-0.09 mg/L for Co, 0.12-1.46 mg/L for Cd, 0.24-0.29mg/L for Cr, 0.89-0.99 mg/L for Ni, 0.89-0.94 mg/L for Fe and 3.99-6.13 mg/L for Zn. Statistical analyses showed that excusing Cr, and all other studied heavy metals concentrations were higher than the human-health safety recommended. Furthermore, among the heavy metals in the current study, the Zn was the highest mean value recorded (4.99 mg/L) and it exceeded the limited value (3.8 mg/L) by WHO/FAO, (1999). The permissible level of pb in milk is 0.05 mg/L, and the mean concentration of pb in the milk sample (3.99 mg/L) was significantly higher than the permissible value. Moreover, the mean value of Cd (0.75 mg/L), Cu (0.79 mg/L), Co (0.038 mg/L), Ni (0.948 mg/L), and Fe (0.91 mg/L) were above the limited value (0.01 mg/L) for Cd, 0.03 mg/l for Cu, (0.001-0.008) for Co, (0.1mg/L) for Ni and 0.1 for Fe, respectively. While the Cr concentration (0.27 mg/L) was lower than the recommended level (0.3 mg/L). Therefore, it was observed that the amount of heavy metals in the sheep milk utilized in this investigation possesses a health risk. Hence, it is always needful to persuade the pollutants in milk in the current area.
This study aimed to measure lead (Pb) and cadmium (Cd) exposure levels in residents living near a zinc (Zn) smelter in Seokpo-myeon, Bonghwa-gun, South Korea, and identify factors affecting exposure. ...Residents aged ≥20 years living within 3 km and ≥30 km away from the smelter were classified as the exposure group (
= 549), and the control group (
= 265), respectively. Data were obtained through a questionnaire survey. Blood Pb levels in the exposure group (4.19 µg/dL) were higher than in the control group (2.70 µg/dL). The exposure group (1.32 µg/L) also had higher urinary Cd concentrations than the control group (0.80 µg/L). Male sex, older age, previous work at the smelter, smoking, and proximity to the smelter were associated with higher blood Pb levels on multivariate analysis; urinary Cd concentration was significantly higher in women, those who were older, those with experience of working in a Zn smelter or mine, those with proximity to the Zn smelter, and those who consumed locally grown vegetables. In conclusion, Zn smelters are major source of Pb and Cd pollution and require ongoing public health management to prevent potential adverse health effects.
Display omitted
•WALSPMF,EPAPMF,APCA/MLR,andUNMIXwereappliedto quantify PTEs sources.•Thefourmodelsyieldedsimilarsourcecontributions of each factor.•SGCSfacilitated to identify the natural and human ...sources.•Integrated methodology proved an effective tool for source apportionment.
Adequately understanding the source characteristic of potentially toxic elements (PTEs) in soils plays an important role in soil environmental protection and regulation. To improve the accuracy of quantifying source contributions, US-EPA positive matrix factorization (EPAPMF), weighted alternating least squares positive matrix factorization (WALSPMF), absolute principal component analysis/multiple linear regression (APCA/MLR), and UNMIX were applied and compared. Spatial distribution maps were delineated by using sequential Gaussian cosimulation (SGCS) with a linear model of coregionalization (LMC) fitting, and can be used to demarcate natural or polluted sources through superposing with auxiliary environmental data. Polluted area of PTEs exceeding a given threshold was determined using uncertainty analysis. The combination of receptor models and SGCS was used to a dataset consisting of As, Cd, Cr, Hg, Ni, Pb, and Zn as a case study. The four receptor models yielded three factors with comparable contributions to seven PTEs, but APCA/MLR produced some negative contributions. The average contributions were calculated based on EPAPMF, WALSPMF, and UNMIX. 85.3% of As, 81.3% of Cr, and 86.7% of Ni originated from natural source, and these three PTEs indicated consistent distributions with parent material map. Cd, Pb, and Zn were contributed by both industrial-traffic emissions and parent materials, with hotspots related to pollution sources and lacustrine deposits. Hg exhibited large-scale high value area around industrial sites, and exclusively derived from atmospheric deposition. A critical probability of 0.95 was adopted to determine polluted areas with PTE content exceeding 1.5 times its background. More than 40.0% of the total area was classified as contaminated for Hg, followed by Cd (3.1%) and Pb (2.9%). The combination of receptor models and SGCS proved to be an effective integrated approach for source apportionment.
Tracking the source of air pollution plumes and monitoring the air quality during emergency events in real-time is crucial to support decision-makers in making an appropriate evacuation plan. ...Internet of Things (IoT) based air quality tracking and monitoring platforms have used stationary sensors around the environment. However, fixed IoT sensors may not be enough to monitor the air quality in a vast area during emergency situations. Therefore, many applications consider utilizing Unmanned Aerial Vehicles (UAVs) to monitor the air pollution plumes environment. However, finding an unhealthy location in a vast area requires a long navigation time. For time efficiency, we employ deep reinforcement learning (Deep RL) to assist UAVs to find air pollution plumes in an equal-sized grid space. The proposed Deep Q-network (DQN) based UAV Pollution Tracking (DUPT) is utilized to guide the multi-navigation direction of the UAV to find the pollution plumes’ location in a vast area within a short duration of time. Indeed, we deployed a long short-term memory (LSTM) combined with Q-network to suggest a particular navigation pattern producing minimal time consumption. The proposed DUPT is evaluated and validated using an air pollution environment generated by a well-known Gaussian distribution and kriging interpolation. The evaluation and comparison results are carefully presented and analyzed. The experiment results show that our proposed DUPT solution can rapidly identify the unhealthy polluted area and spends around 28% of the total time of the existing solution.
Nitrogen dioxide (NO2) is an important pollutant related to human activities, which has short-term and long-term effects on human health. An ensemble learning model was constructed and applied to ...estimate daily NO2 concentrations in the Beijing–Tianjin–Hebei region between 2010 and 2016. A variety of predictive variables included satellite-based troposphere NO2 vertical column concentration, meteorology, elevation, gross domestic product (GDP), population, land-use variables, and road network. The ensemble learning model achieved two things: a 0.01° × 0.01° grid resolution and the estimation of historical data for the years 2010–2013. The ensemble model showed good performance, whereby the R2 of tenfold cross-validation was 0.72 and the R2 of test validation was 0.71. Meteorological hysteretic effects were incorporated into the model, where the one-day lagged boundary layer height contributed the most. The annual NO2 estimation showed little change from 2010 to 2016. The seasonal NO2 estimation from highest to lowest occurred in winter, autumn, spring, and summer. In the annual maps and seasonal maps, the NO2 estimations in the northwest region were lower than those in the southeast region, and there was a heavily polluted band in the south of the Taihang Mountains. In coastal areas, the annual NO2 estimations were higher than the NO2 monitored values. The drawback of the model is underestimation at high values and overestimation at low values. This study indicates that the ensemble learning model has excellent performance in the simulation of NO2 with high spatial and temporal resolution. Furthermore, the research framework in this study can be a generally applied for drawing implications for other regions, especially for other cities in China.
Exposure to cadmium (Cd) via food is supposed to affect life prognosis of inhabitants of Cd-polluted area in Japan. However, there have been few reports demonstrating a significant relationship ...between the amount of Cd intake and mortality. We aimed to investigate the relationship between mortality and individual lifetime Cd intake (LCd) in inhabitants of the polluted Jinzu River basin, Toyama, Japan.
We conducted a 26-year follow-up survey in 2407 inhabitants (1208 men and 1199 women) who participated in health examinations for screening of renal dysfunction from 1979 to 1984. The calculation of LCd in each inhabitant was based on the formula of Nogawa (Nogawa et al., 1989): (mean Cd concentration in rice of the present hamlet × 333.5 g/day + 34 μg/day) × 365 days/year × number of years of residence in the present hamlet + 50 μg/day × 365 days/year × number of years living in Cd non-polluted regions. In this formula, 333.5 g/day is the 1970 average daily intake of rice in this area, 34 µg/day is the Cd intake from foods other than rice in this area, and 50 μg/day is the average intake of Cd in non-polluted areas in Japan. Mortality risk ratios of LCd for all and specific causes were estimated after adjustments for age at baseline, smoking status, and history of hypertension using a Cox hazard model or Fine and Gray competing risks regression model.
The mortality risk ratios of LCd (+ 1 g) for all causes in women were significantly dose-dependently increased (risk ratio: 1.08). Relative risk of LCd for kidney and urinal tract disease, renal diseases, renal failure and toxic effects of cadmium were significantly higher in women.
The present study documents that individual LCd dose-dependently decreased life prognosis over long-term observation in women. LCd was significantly related to the increased mortality for renal disease and toxic effect of Cd in women. The result provides clear evidence that life prognosis was adversely affected by Cd-exposure, especially in women.
•The mortality risk ratios of LCd (+1 g) for all causes in women were dose-dependently increased (risk ratio: 1.08).•Relative risk of LCd for kidney and urinal tract disease, renal diseases and renal failure were higher in women.•Life prognosis was adversely affected by Cd-exposure, especially in women.
PDF
