Oil Extraction Areas Research Articles

Remote sensing inversion on heavy metal content in salinized soil of Yellow River Delta based on Random Forest Regression—a case study of Gudao Town

To explore the potential of using the mineral alteration information extracted by remote sensing technology to indirectly estimate the heavy metal content of salinized soil, 23 sampling points were uniformly set up in the town of Gudao in the Yellow River Delta as the research area in 2022. The concentrations of seven heavy metals, Cr, Cu, Pb, Zn, As, Mn and Ni, at the sampling points were determined in laboratory tests. Spectral derivative indices, topographic factors, and mineral alteration information (iron staining, hydroxyl, and carbonate ions) were extracted and screened as modeling factors using Sentinel 2 imagery. An inverse model of heavy metal content was constructed using the random forest algorithm, and the model accuracy was evaluated using the cross-validation method. The results of the study show that: (1) Hydroxyl and carbonate ion alteration can be effectively used for the inversion of soil As and Ni content in this study area. Iron-stained alteration can be used as a modeling factor in the inversion of Cr, Cu, Pb, Zn, and Mn concentrations. (2) The inclusion of alteration information improves the accuracy of heavy metal content inversion. The Cu concentration was verified to be the best predictor, with an RMSE of 3.309, MAPE of 11.072%, and R2 of 0.904, followed by As, Ni, and Zn; the predictive value of Mn, Cr and Pb was average. (3) Based on the results of concentration inversion, the high concentration areas of As, Ni, and Mn are primarily distributed on both sides of the river and around lakes and ponds. The high-concentration areas of Zn were mainly distributed in the farmland areas on both sides of the river. Areas with high concentrations of Cu were mainly distributed in the eastern oil extraction area, both sides of the rivers, and around lakes.

68 Urinary Biomarkers of Benzene Exposure and Oxidative Damage in Residents of the Oil Extraction Area of Muanda, Dr Congo

Abstract The territory of Muanda, on the Atlantic coastline of the DR Congo, is an area of off-shore and on-shore oil extraction. Following concerns of the local population about the possible environmental and health consequences of these activities, a pilot study was performed in December 2015 to assess, among other issues, the exposure of residents of various relevant locations to oil-derived chemicals. We measured metabolites of benzene (t,t-Muconic Acid, MA, and S-Phenylmercapturic acid, S-PMA) by LC-MS and 8-hydroxy-2’-deoxyguanosine (8-OHdG, as an indicator of DNA damage) by ELISA, in urine spot samples of 53 volunteers (34 adults, 19 children, recruited by convenience sampling) living within areas of oil extraction with flaring (n=27), in an area where petroleum products were handled (n=14), and in a control area in the Mangroves National Park (n=12). Concentrations of both MA and S-PMA were increased among residents of the oil extraction areas (0.23±0.05 mg/L, 1.04±0.30 µg/L, respectively) and petroleum products area (0.32±0.08 mg/L, 1.74±0.63 µg/L, respectively) compared with controls (0.06±0.01 mg/L, 0.40±0.13 µg/L, respectively). Concentrations of of MA and S-PMA correlated with levels of 8-OHdG (RSpearman = 0.37, p<0.01). Our biomonitoring study revealed a low degree of benzene exposure among residents living in the oil extraction and petroleum handling areas compared to a control area. Although the levels of benzene metabolites were low, the positive correlation with 8-OHdG possibly indicates that pollution by hydrocarbons induced oxidative damage in this study population.

Levels of Arsenic, Cadmium, and Mercury in Urine of Indigenous People Living Close to Oil Extraction Areas in the Peruvian Amazon.

Levels of Arsenic, Cadmium, and Mercury in Urine of Indigenous People Living Close to Oil Extraction Areas in the Peruvian Amazon.

White Clover (Trifolium repens L.) Cultivation as a Means of Soil Regeneration and Pursuit of a Sustainable Food System Model

Background: Currently, in the face of constant climate change and the development of the mining industry, recovering soils degraded by industry for agricultural production and ensuring more food security for the world has become more difficult. Soil contamination is of particular concern as it affects not only human health but also vegetation growth and the biological environment. The aim: The aim of our research is to develop an appropriate cultivation technology in the area of former and present oil extraction areas and monitor their recovery for agricultural purposes and, thus, for food production. Methods: Experimental, descriptive, laboratory, and comparative methods were used. Results: A significantly decreased content of PAHs in the tested soil under the influence of the “Green technology” was observed just in the third year of the research. Eight years after the introduction of “green technology”, the sum of PAHs in the soil degraded by the oil extraction industry was more than 2-fold reduced. Therefore, there is a need to develop a nature-friendly and cost-effective method of removing and minimizing the effects of soil contamination by oil and its products. Conclusions: T. repens turned out to be a species that significantly prevents the degradation of the agricultural environment and restores soil for agricultural use, consequently encouraging the production of food safe for humans. The immeasurable effect of the use of “Green technology” was to ensure the biodiversity of the grasslands and to return the sources of natural nitrogen bound by bacteria of the genus Rhizobium in coexistence with plants from the Fabaceae family.

Black Carbon Seasonal Trends and Regional Sources on Bely Island (Arctic)

The impact of aerosol sources on the pollution of the Russian sector of the Arctic is now strongly underestimated. A new polar aerosol station was arranged in August 2019 on Bely Island (Kara Sea), on the pathway of air mass transport from industrial regions of Western Siberia to the Arctic. Continuous aethalometer measurements of a short-lived climate tracer, i.e., black carbon, (from December to April 2019 and from January to November 2020) showed its seasonal variations with high values (60–92 ng/m3) in December–April and low values (18–72 ng/m3) in June–September. Pollution periods are identified. Regional distribution of fossil fuel and biomass combustion sources are obtained using the black carbon concentration weight trajectory model. The impact of gas flaring from oil and gas extraction areas of Western Siberia, the Volga region, the Urals, and the Komi Republic is found to be most pronounced during the cold period, and the impact from wildfire smoke emissions is found to be maximal in the warm season. A marker of biomass burning impact, determined from the difference between the black carbon concentrations measured in a broad wavelength spectrum, indicated the predominant effects from residential wood combustion in the cold period and agricultural and forest fires in the warm season.

Spatial distribution and driving factors of groundwater chemistry and pollution in an oil production region in the Northwest China

Concerns have been raised on the deterioration of groundwater quality associated with anthropogenic impacts such as oil extraction and overuse of fertilizers. However, it is still difficult to identify groundwater chemistry/pollution and driving forces in regional scale since both natural and anthropogenic factors are spatially complex. This study, combining self-organizing map (SOM, combined with K-means algorithm) and principal component analysis (PCA), attempted to characterize the spatial variability and driving factors of shallow groundwater hydrochemistry in Yan'an area of Northwest China where diverse land use types (e.g., various oil production sites and agriculture lands) coexist. Based on the major and trace elements (e.g., Ba, Sr, Br, Li) and total petroleum hydrocarbons (TPH), groundwater samples were classified into four clusters with obvious geographical and hydrochemical characteristics by using SOM - K-means clustering: heavily oil-contaminated groundwater (Cluster 1), slightly oil-contaminated groundwater (Cluster 2), least-polluted groundwater (Cluster 3) and NO3− contaminated groundwater (Cluster 4). Noteworthily, Cluster 1, located in a river valley with long-term oil exploitation, had the highest levels of TPH and potentially toxic elements (Ba, Sr). Multivariate analysis combined with ion ratios analysis were used to determine the causes of these clusters. The results revealed that the hydrochemical compositions in Cluster 1 were mainly caused by the oil-related produced water intrusion into the upper aquifer. The elevated NO3− concentrations in Cluster 4 were induced by agricultural activities. Water-rock interactions (e.g., carbonate as well as silicate dissolution and precipitation) also shaped the chemical constituents of groundwater in clusters 2, 3, and 4. In addition, SO42−-related processes (redox, precipitation of sulfate minerals) also affected groundwater chemical compositions in Cluster 1. This work provides the insight into the driving factors of groundwater chemistry and pollution which could contribute to groundwater sustainable management and protection in this area and other oil extraction areas.

SURFACE DEFORMATION MONITORING AND DRIVING FORCE ANALYSIS IN THE YELLOW RIVER DELTA BASED ON PS-INSAR TECHNOLOGY

Abstract. Aiming at the land subsidence in the Yellow River Delta region, based on the Sentinel-1A data of 52 scenes from 2020 to February 2022, Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) were adopted to extract the surface deformation information of the Yellow River Delta region. Firstly, the deformation characteristics of typical subsidence feature points are analyzed, and then the correlation between groundwater, precipitation and land subsidence are analyzed. The result show that the settlement area distribution of the Yellow River Delta is not uniform, mainly distributed in underground brine mining area and oil extraction area, the maximum settlement center is located in Yongan Town, the settlement amount reaches −302.7 mm, the main reason of the settlement is excessive exploitation of underground brine salt. By analyzing the correlation between groundwater, precipitation and land subsidence in the Yellow River Delta, it can be seen that the effect of groundwater content change on land subsidence was the most serious, and the correlation coefficient is 0.875. In general, the subsidence of the Yellow River Delta is mainly caused by the over-exploitation of underground fluids such as fresh water, brine and oil without timely compensation.

Effect of plant waste addition as exogenous nutrients on microbial remediation of petroleum-contaminated soil

PurposeThis study investigates the feasibility of bio-enhanced microbial remediation of petroleum-contaminated soil, and analyzes the effect of different plant wastes as exogenous stimulants on microbial remediation of petroleum-contaminated soil and the effect on soil microbial community structure, in order to guide the remediation of soil in long-term petroleum-contaminated areas with nutrient-poor soils.MethodsThe study was conducted in a representative oil extraction area in the Loess Hills, a typical ecologically fragile area in China. Through indoor simulated addition tests, combined with the determination of soil chemical and microbiological properties, the degradation efficiency of petroleum pollutants and the response characteristics of soil microbial community structure to the addition of different plant wastes in the area were comprehensively analyzed to obtain the optimal exogenous additive and explore the strengthening mechanism of plant wastes on microbial remediation of petroleum-contaminated soil.ResultsCompared with the naturally decaying petroleum-contaminated soil, the addition of plant waste increased the degradation rate of petroleum pollutants, that is, it strengthened the degradation power of indigenous degrading bacteria on petroleum pollutants, among which the highest degradation rate of petroleum pollutants was achieved when the exogenous additive was soybean straw; compared with the naturally decaying petroleum-contaminated soil, the addition of soybean straw and dead and fallen leaves of lemon mallow made the microbial species in the contaminated soil significantly reduced and the main dominant flora changed, but the flora capable of degrading petroleum pollutants increased significantly; the addition of exogenous nutrients had significant effects on soil microbial diversity and community structure.ConclusionsSoybean straw can be added to the contaminated soil as the optimal exogenous organic nutrient system, which improves the physicochemical properties of the soil and gives a good living environment for indigenous microorganisms with the function of degrading petroleum pollutants, thus activating the indigenous degrading bacteria in the petroleum-contaminated soil and accelerating their growth and proliferation and new city metabolic activities, laying a foundation for further obtaining efficient, environmentally friendly and low-cost microbial enhanced remediation technology solutions. The foundation for further acquisition of efficient, environmentally friendly, and low-cost microbial-enhanced remediation technology solutions. It is important for improving soil remediation in areas with long-term oil contamination and nutrient-poor soils.

Methane, carbon dioxide, hydrogen sulfide, and isotopic ratios of methane observations from the Permian Basin tower network

Abstract. We describe the instrumentation, calibration, and uncertainty of the network of ground-based, in situ, cavity ring down spectroscopy (CRDS) greenhouse gas (GHG) measurements deployed in the Permian Basin. The primary goal of the network is to be used in conjunction with atmospheric transport modeling to determine methane emissions of the Delaware sub-basin of the Permian Basin oil and natural gas extraction area in Texas and New Mexico. Four of the measurements are based on tall communications towers, while one is on a building on a mountain ridge, with the recent addition of a small tower at that site. Although methane (CH4) is the primary species of interest, carbon dioxide (CO2), hydrogen sulfide (H2S), and the isotopic ratio of methane (δ13CH4) are also reported for a subset of the sites. Measurements were reported following the WMO X2004A scale for CH4 and the WMO X2019 scale for CO2. CRDS instruments were calibrated for CH4 and CO2 in the laboratory prior to deployment. For H2S, data were offset-corrected using the minimum 40 min running mean value of the day, and for δ13CH4, calibrations were based on laboratory data. We describe the characteristics of the dataset with a set of illustrative analyses. Methane and carbon dioxide showed strong seasonality, with a well-defined diurnal cycle during the summer, which was opposed to the winter, when a diurnal cycle was absent. CH4 enhancements to the background, during the winter, are up to twice the summer values, which is attributed to the changes in boundary layer depth and wind speed. The largest CH4 enhancements occurred when winds blow from the center of the Delaware sub-basin, where most of the methane emissions come from. The magnitude of enhancements of CO2 did not present seasonality. H2S enhancements indicated a potential source northeast of the tower (Hobbs, New Mexico) where the inlet is installed. Isotopic ratios of methane indicated that oil and natural gas extraction is the source of local methane in the region. The hourly-averaged data, starting on 1 March 2020 and described in this paper, are archived at The Pennsylvania State University Data Commons at https://doi.org/10.26208/98y5-t941 (Monteiro et al., 2021).

An XFEM-based approach for 3D hydraulic fracturing simulation considering crack front segmentation

Hydraulic fracturing is a commonly adopted and effective well stimulation technique in the oil and gas extraction area. Under a mixed I/III loading condition, the crack front segmentation (i.e., the parent crack segments into echelon-shaped daughter cracks) usually occurs, which highly complicates the paths of fluid-driven cracks. This paper presents an efficient numerical model for 3D hydraulic fracturing simulation considering crack front segmentation on basis of the extended finite element method (XFEM). Solutions of the momentum balance equation and the fluid flow equation are simultaneously determined by the Newton-Raphson method along with a reduction technique. In the XFEM framework, a robust local mesh-refinement scheme of the tip-enriched elements is designed to enhance the resolution of the near-front stress field which is crucial for the determination of crack segmentation and propagation behaviors. The locally refined tip-enriched elements are then divided into a series of tetrahedra to perform high-accuracy numerical integration. After verification of the proposed approach, the effects of several critical parameters in hydraulic fracturing treatments are investigated. Results show that crack front segmentation has significant effects on the resulting crack paths and crack aperture distribution. The propagation of hydraulic fractures will be depressed on account of the stress shadow induced by overlapped segments, leading to higher pumping pressure compared to the case without considering front segmentation. The sensitivity analyses indicate that larger elastic modulus of rock formation, larger fluid viscosity, higher fluid pumping rate, and smaller fluid leak-off coefficient can alleviate the influence of crack front segmentation on the pumping pressure. Larger elastic modulus, larger fluid viscosity, higher fluid pumping rate, and greater fluid leak-off coefficient lead to smaller twisting angles of the segments and smaller overlapping ratios.

Techno-Economic Assessment of Offshore Wind Energy in the Philippines

The technical and economic assessments for emerging renewable energy technologies, specifically offshore wind energy, is critical for their improvement and deployment. These assessments serve as one of the main bases for the construction of offshore wind farms, which would be beneficial to the countries gearing toward a sustainable future such as the Philippines. This study presents the technical and economic viability of offshore wind farms in the Philippines. The analysis was divided into four phases, namely, application of exclusion criteria, technical analysis, economic assessment, and sensitivity analysis. Arc GIS 10.5 was used to spatially visualize the results of the study. Exclusion criteria were applied to narrow down the potential siting for offshore wind farms, namely, active submerged cables, local ferry routes, marine protected areas, reefs, oil and gas extraction areas, bathymetry, distance to grid, typhoons, and earthquakes. In the technical analysis, the turbines SWT-3.6-120 and 6.2 M126 Senvion were considered. The offshore wind speed data were extrapolated from 80 m to 90 m and 95 m using power law. The wind power density, wind power, and annual energy production were calculated from the extrapolated wind speed. Areas in the Philippines with a capacity factor greater than 30% and performance greater than 10% were considered technically viable. The economic assessment considered the historical data of constructed offshore wind farms from 2008 to 2018. Multiple linear regression was done to model the cost associated with the construction of offshore wind farms, namely, turbine, foundation, electrical, and operation and maintenance costs (i.e., investment cost). Finally, the levelized cost of electricity and break-even selling price were calculated to check the economic viability of the offshore wind farms. Sensitivity analysis was done to investigate how LCOE and price of electricity are sensitive to the discount rate, capacity factor, investment cost, useful life, mean wind speed, and shape parameter. Upon application of exclusion criteria, several sites were determined to be viable with the North of Cagayan having the highest capacity factor. The calculated capacity factor ranges from ~42% to ~50% for SWT-3.6-120 and ~38.56% to ~48% for 6.2M126 turbines. The final regression model with investment cost as the dependent variable included the minimum sea depth and the plant capacity as the predictor variables. The regression model had an adjusted R2 of 90.43%. The regression model was validated with existing offshore wind farms with a mean absolute percentage error of 11.33%. The LCOE calculated for a 25.0372 km2 offshore area ranges from USD 157.66/MWh and USD 154.1/MWh. The breakeven electricity price for an offshore wind farm in the Philippines ranges from PHP 8.028/kWh to PHP 8.306/kWh.

Blood lead levels in indigenous peoples living close to oil extraction areas in the Peruvian Amazon

BackgroundHigh blood lead levels (BLLs) have been previously reported in indigenous people living in communities in the northern Peruvian Amazon. Oil extraction activities have been conducted in the area since the 1970s and have been identified as a source of lead exposure. ObjectiveMeasure BLL and assess risk factors associated with BLL among indigenous populations from four river basins of the northern Peruvian Amazon. MethodsParticipants from 39 communities were selected using a two-stage stratified random selection strategy and were visited between May and June 2016. Information on risk factors was collected using structured questionnaires and blood samples were taken. Overall, complete information was available from 1047 individuals (309 < 12 years old, 738 ≥ 12 years). BLL was determined using atomic absorption spectrophotometry in a graphite chamber. Weighted linear logistic regression models were used to study the association between socio-demographic variables, self-reported life-style factors, environmental, geographical and occupational exposures and BLLs. ResultsGeometric mean (95% CI) BLL was 4.9 (4.5, 5.4) µg/dL in participants <12 years and 5.7 (5.4, 6.0) µg/dL in older participants. There were marked differences in BLL between river basins with the highest levels observed in the Corrientes river basin [8.1 (7.2, 9.1) µg/dL <12 years and 8.8 (8.0, 9.6) µg/dL older participants]. High BLL was associated with older age, being male, living in the Pastaza, Tigre or Corrientes river basins and consumption of fish offal in children and adults. Increased Euclidean distance between residence and oil production facilities was associated with a small reduction in BLL. ConclusionBLLs that pose a health risk were detected in the study population of a non-industrialized and remote area of the Amazon. The highest BLLs were observed in those river basins where relative oil extraction activity and environmental levels of contaminants have been reported to be greatest.

Indication and Quantitative Assessment of Polyarene Sources in Soils by Statistical Modeling (Oil and Gas Extraction Area, Volgograd Region)

Indication and Quantitative Assessment of Polyarene Sources in Soils by Statistical Modeling (Oil and Gas Extraction Area, Volgograd Region)

Land Subsidence Monitoring in Cepu Block Area Using PS-Insar Technique

Land subsidence can be caused by many factors, from natural through anthropogenic processes. Land subsidence due to anthropogenic factors results from such as fluid withdrawal, like oil and gas extraction. Cepu block is one of the oil and gas extraction areas that become Indonesia’s largest oil producer. This paper employs the Permanent Scatterers Interferometry Synthetic Aperture Radar (PS-InSAR) with C-Band Sentinel-1A imagery data to monitor the land subsidence phenomena. The PS-InSAR method is chosen because it can measure small movements in an area over time with millimeters DEM accuracy. The processing result showed deformation in the form of land subsidence in almost all of the blocks, except for Block D, with the mean velocity ranging from -27,75 to -9,78 mm/yr. An uplift phenomenon is also achieved in the eastern part of Block E. These PS-InSAR results are in the form of Line Of Sight (LOS). This paper correlates the land subsidence with geological maps to better understand the phenomena’ causes.

黄河三角洲石油化工区农田土壤-玉米体系PAHs的分布特征及风险评价

PDF HTML阅读 XML下载 导出引用 引用提醒 黄河三角洲石油化工区农田土壤-玉米体系PAHs的分布特征及风险评价 DOI: 10.5846/stxb202003270714 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划项目（2016YFC0503604） Distribution characteristics and risk assessment of polycyclic aromatic hydrocarbons in farmland soil-corn system from oil mining area of Yellow River Delta Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:为明确黄河三角洲石油开采区表层土壤和玉米中多环芳烃（PAHs）的含量及其污染水平，采集农田土壤和玉米各71个样品，检测农田土壤和玉米各部位中16种PAHs含量，并采用内梅罗指数法和健康风险评价模型评估了农田土壤中多环芳烃的生态健康风险。结果表明，农田土壤、玉米根、茎和叶中多环芳烃的含量分别为256.6-1936、291.4-680.9、324.9-527.9、289.5-2400 μg/kg。农田土壤中多环芳烃以4-6环为主。多环芳烃在玉米根茎叶富集系数大小排序为：叶 > 茎 > 根。玉米不同组织中PAHs浓度与相应农田土壤中PAHs浓度的进行相关分析结果表明，农田土壤中PAHs含量与玉米根、茎中PAHs含量均存在极显著正相关关系，相关系数分别为0.98（P<0.01）、0.98（P<0.01），表明玉米根和茎的多环芳烃主要来源于农田土壤中，农田土壤中PAHs的含量影响着PAHs在玉米根茎中的积累和分布。玉米叶中PAHs含量与农田土壤中PAHs含量与玉米根、茎中PAHs含量不存在相关关系，表明玉米叶中多环芳烃并非来自土壤中PAHs的迁移，可能来源于大气。内梅罗指数结果表明，农田土壤PAHs达到了中度污染，其中BaA、Pyr和BbF达到了偏重污染；健康风险评价结果表明，农田土壤PAHs对儿童和成人的平均非致癌风险分别为0.44和0.12（均小于1），表明农田土壤多环芳烃对成人和儿童的非致癌风险是可接受；农田土壤PAHs对儿童和成人的平均致癌风险分别为3.6×10-5、9.0×10-6，没有超过致癌风险水平上限（10-4），致癌风险尚在可接受范围内。3种暴露途径中，皮肤接触是土壤PAHs的最主要暴露方式，其次是经口摄食，吸入暴露途径甚微，可忽略不计。PAHs对儿童健康的威胁风险要大于成人，所以应尽可能避免儿童直接接触或误食土壤等其他介质的污染物。 Abstract:To investigate the residual levels of polycyclic aromatic hydrocarbons (PAHs) in topsoil and corns in the Yellow River Delta oil extraction area, total 71 samples of farmland soils and 71 samples of corns were collected. The content of 16 PAHs in soils and spinach were detected. The Nemerow pollution index method and the health risk assessment model were used to assess the ecological health risks of PAHs in farmland soil. The results showed that the contents of PAHs in farmland soil, corn roots, stems, and leaves were 256.6-1936 μg/kg, 291.4-680.9 μg/kg, 324.9-527.9 μg/kg, and 289.5-2400 μg/kg, respectively. The results showed that PAHs in farmland soils were dominated by 4-6 rings. The order of PAHs enrichment coefficients in root, stem and leaf was leaf > stem > root. The correlation analysis results of the PAHs concentration in different corn tissues and the PAHs concentration in the corresponding farmland soil showed that there was very significantly positive correlation between the PAHs content in the farmland soil and the PAHs content in the corn root and stem, and the correlation coefficients were 0.98 (P<0.01), 0.98 (P<0.01), respectively. It indicates that the PAHs of corn roots and stems are mainly from farmland soil, and the content of PAHs in farmland soil affects the accumulation and distribution of PAHs in corn roots and stems. There is no correlation between PAHs content in corn leaves and PAHs content in farmland soil and PAHs content in corn roots and stems, which indicating that PAHs in corn leaves do not come from the migration of PAHs in soil, but may come from the atmosphere. The Nemerow index results showed that the PAHs in farmland soils have reached moderate pollution, and BaA, Pyr, and BbF have reached heavy pollution. The health risk assessment results showed that the average non-carcinogenic risk of PAHs in farmland soils to children and adults was 0.44<1, 0.12 <1, indicating that the non-carcinogenic risk of PAHs in farmland soils is acceptable for adults and children. The average carcinogenic risk of PAHs in farmland soils for children and adults was 3.6×10-5 and 9.0×10-6, respectively, which was less than the upper limit of acceptable cancer risk of 10-4. Among the three exposure routes, skin contact is the most important way of exposure to soil PAHs, followed by oral ingestion, and the inhalation exposure route is negligible. The risk of PAHs to children's health is greater than that of adults, so it is necessary to avoid children's direct contact with or ingestion of soil and other pollutants by mistake. 参考文献 相似文献 引证文献

Evaluation of sampling techniques and influence of environmental variables on ants in forest fragments in an oil extraction area in the Amazon

Around the world, urban landscapes are environments modified by man, generally related to low diversity. The efficiency of a biodiversity inventory is linked to the choice of the sampling technique since the taxonomic and ecological responses of the taxons vary between methods. Here we investigate differences in the ant’s composition sampled using three different techniques in two fragments of the urban forest in the Brazilian Amazon. We also assessed whether the different techniques maintained the same ecological responses. We sampled 12 collection points at each fragment, at vegetation, and manual collection and Winkler extractor on the ground. At the same points, soil samples were collected to determine their granulometry, pH, and concentrations of organic matter, sodium, phosphorus, and potassium. We collected 115 taxa and 4720 ants. The Cururu was the richest site with more species in general, as well as in the techniques of manual collection and Winkler. We detected a complementary effect on sampling techniques, which collected different ants’ assemblages. The potassium concentration positively influenced the assemblage’s composition, but its effect varies according to the sampling techniques used. The studied fragments revealed diversity very similar to those registered in continuous Amazonian forests. The use of sampling techniques together improves the representation of the diversity of ants in the studied fragments. Edaphic environmental variables seem to have a predominant effect on ants, affecting their distribution in the landscape even in urban fragments. This highlights the importance of urban forest fragments and their inherent ecological processes.

The Distributional Justice of Oil Industry Social Development Projects and Oil Field Production Activities

In order to share the benefits of oil production with people living in extraction areas, the oil industry targets social development investments and projects to communities most affected by production activities. Yet, the effectiveness of industry-led community development projects remains unclear and under explored. In this study, we use a benefit-sharing, distributional justice framework to assess the efficacy of social development projects among 11 municipal governments and 114 local communities in the Tampico-Misantla Basin, a major oil extraction region in Mexico. To test for distributional justice, we use geospatial, rapid rural appraisal, and government data to compare the spatial overlap of oil production, pipelines, recent drilling activity, well counts, state-funded public works, and social marginalization indexes to social development infrastructure (e.g. paved roads, schools, bridges). We explain the uneven distribution of risks and benefits among some rural communities as the result of premature investments in social development projects, party politics, corruption, community capacity, and proximity to urban areas. This study contributes an empirical approach to evaluate distributional justice in oil extraction areas. It also provides insights into Mexico’s oil sector during a period of significant neoliberal restructuring, most recently with the 2014 Energy Reforms.

Hygienic assessment of health risks of the population living in the areas of intensive oil extraction

The purpose of the study was to establish hygienic procedures for reducing health risks of the population living and working near oil extraction sites. Based on the results obtained, we evaluated the quality of environmental settings in the oil extraction areas, studied working conditions of oil workers, and assessed public human health and occupational risks of the oil extraction industry. Oil extraction enterprises have been shown to be major sources of environmental and workplace pollution and to create a negative background causing adverse health effects.

Distribution Characteristics and Source Analysis of Polycyclic Aromatic Hydrocarbons in Salinized Farmland Soil from the Oil Mining Area of the Yellow River Delta

Eighty-nine soil samples were collected from the Binzhou oil mining area of the Yellow River Delta (including 83 farmland soil samples and 6 soil samples from an oil extraction area). A total of 16 US-EPA priority polycyclic aromatic hydrocarbons (PAHs) were measured by gas chromatography-mass spectrometry (GC-MS). Principal component analysis (PCA) and positive matrix factorization (PMF) were employed to investigate potential source apportionment of PAHs in the farmland soil. The total PAH concentrations ranged from 31.5 μg·kg-1 to 1399.4 μg·kg-1 (dry weight) with an arithmetic mean concentration of 119.4 μg·kg-1. The characteristics of PAHs showed that 4- to 6-ring PAHs were slightly dominant in this study area, and most of the PAHs were significantly correlated (P<0.01), which indicates that the sources of the PAHs had some similarities in this sampling area. Source apportionment results derived from two different models were similar, indicating that the sources of PAHs were coal combustion, biomass combustion, fossil fuel combustion, and diesel combustion. The results of the PMF were more detailed, with the following four factors being identified:gasoline combustion (24.05%), diesel combustion (6.17%), low-temperature pyrolysis processes (60.67%), and coal combustion (9.11%).

Background Contents of Heavy Metals in Soils and Bottom Sediments in the North of Western Siberia

Background concentrations of heavy metals (Cu, Zn, Ni, Co, Fe, Mn, Cr, Pb, Hg, Cd, Ba, Sr, and Sc) in soils and bottom sediments were determined for the background and anthropogenically disturbed (oil and gas extraction) areas in the north of Western Siberia on the basis of long-term studies (1993–2017). It was found that the soils are characterized by relatively low concentrations of heavy metals. The major factors affecting the variability of the chemical composition of the environmental components are the lithological and chemical composition of the parent materials and the zonal–azonal geochemical differentiation related to peat accumulation. The statistical analysis and the method of ranked geochemical spectra suggested that background element concentrations should be separately determined for organic soil horizons, for mineral (illuvial) horizons in coarse-textured and heavy-textured soils, and for peatlands. Minimum concentrations of most of the studied heavy metals were determined in peatlands: they were 2–8 times lower than the concentrations of these metals in the clayey and loamy illuvial horizons. Mercury and cadmium were the exceptions: their concentrations in the peatlands were 3–4 times higher than those in the illuvial mineral horizons. Background metal concentrations in bottom sediments were separately calculated for three categories: clay and peaty clay sediments, silts, and fine-grained sands. Metals concentrations in clay sediments were significantly higher than those in sandy sediments: by 11 times for Fe and Mn; by 8.5 times for Ni; by 6.5 times for Co; and by 5 times for Zn, Cu, Cr, and V. The concentrations of metals were determined by the ICP MS method. The obtained data on the background concentrations of heavy metals can be recommended for the assessment of technogenic impact on local soils and bottom sediments in the course of the environmental monitoring.