Environmental Monitoring and Assessment

Monitoring and predicting land use/cover changes in the Aksu-Tarim River Basin, Xinjiang-China (1990–2030) Abstract Land use/cover (LCLU) is considered as one of the most serious environmental challenges that threatens developed and less developed countries. LCLU changes' monitoring using the integration of remote sensing (RS) and geographical information systems (GIS) and their predicting using an artificial neural network (ANN) in the western part of the Tarim River Basin (Aksu), north-western Xinjiang-China, from 1990 to 2030 have been investigated first time through satellite imageries available. The imageries of 1990, 2000, 2005, 2010, and 2015 were downloaded from GLCF and USGS websites. After digital image processing, the object-oriented image classification approach was applied. The ANN method with MOLUSCE Plugin was used to simulate the LCLU changes in 2020, 2025, and 2030. GIS has also been used to calculate the distance from the road and water and etc. The simulation results of 2010 and 2015 were validated using classification data with Kappa coefficient. The results showed high accuracy of the classification and prediction as the validation of simulated 2010 and 2015 maps to the referenced maps have high accuracy of Kappa 84 and 88%, respectively. The results revealed that the land cover classes forest-, grass-, wet-, and barren land have been decreased from 50.01, 13.06, 8.24, and 1.06% in 1990 to 32.03, 3.06, 6.26, and 0.97% in 2015, respectively, while the land use classes, crop or farm land, and urban land have been increased almost double from 25.5 and 2.13% in 1990 to 53.71 and 3.86% from the total area in 2015, respectively. For the prediction, forest- and wetlands will loss more than half of their areas by 2030, the grass land will be cleared completely to be only 1.3% from the total study area, while the urban land will be increased to be 4.4% or the double of 1990. These results are attributed to population growth and expanding of agriculture land on the grass land, but the effect of climate was weak as the rainfall increased during the study period. Causes and effects of the LCLU changes were briefly discussed. The output of the study serves as useful tools for policy and decision makers combatting natural resources misused in arid lands.

Methane emissions from abandoned coal and oil and gas developments in New Brunswick and Nova Scotia Abstract Energy reserves have been exploited in the Atlantic Canadian provinces since the early 1600s, and many fossil fuel extraction sites have been abandoned over this long history of energy development. Oil, natural gas, and coal extraction sites are a source of greenhouse gas emissions, particularly for methane (CH4). In this study, we used multiple sampling methods to measure CH4 from abandoned coal mine openings in Nova Scotia and a legacy oilfield in New Brunswick. Atmospheric and shallow soil gases were sampled around legacy sites using flux rate chamber measurements (spatial and temporal) and plot-scale atmospheric gas surveys, in addition to regional gas screening surveys over larger populations of sites to confirm whether small-scale observations were reflected regionally. Only one oil and gas site (2.4 ± 3.1⋅ 102 mg m− 2 day− 1) and one abandoned coal mine opening (1.0 ± 1.1⋅ 102 mg m− 2 day− 1) were affected by soil CH4 migration, though rates of leakage were minimal and would rank as low severity on industrial scales. Plot-scale atmospheric gas screening showed super-ambient CH4 concentrations at 5 sites in total (n = 16), 2 coal adits and 3 abandoned oil and gas wells. Regional gas screening surveys suggest that 11% of legacy oil and gas sites have some emission impacts, compared with 1–2% of legacy coal sites. These frequencies are close, albeit lower than the 15% of legacy oil and gas sites and 10% of abandoned coal mine openings flagged from our aggregated small-scale observations. These sites may emit less than other developments studied to date either because more time has elapsed since extraction, or because differences in regional geology reduce the likelihood of sustained emissions. This study provides valuable information to help understand the methane emission risks associated with legacy energy sites.

Exposure to toxic and essential trace elements through the intake of processed and meat cuts (beef and chicken) in southeastern Brazil Abstract The present study evaluated the concentration of six trace elements in processed meat products and in meat cuts. We also assessed the risk associated with the consumption of these foods based on the estimated daily intake (EDI) of these elements. Fifty-eight processed meat and 148 meat cuts samples were analyzed using ICP-OES. As and Cd were not detected in any sample of processed meat. The highest mean level of lead was observed in frankfurters (0.056 μg g−1), which is half the maximum permissible level. For Cr, the highest mean concentrations were detected in chicken nuggets and beef hamburger (0.121 and 0.105 μg g−1, respectively), which are above the allowed limit. The comparison between the impact of a diet restricted to processed meats with a diet restricted to meats cuts showed that the individuals following the latter are exposed to higher amounts of the trace elements analyzed.

Cultivable bacterial diversity, physicochemical profiles, and toxicity determination of car wash effluents Abstract Carwash effluents contain potentially toxic chemical and microbiological pollutants which may pose public health and ecotoxicological threats if directly discharged into surface waters. This work was aimed at determining the microbiological, physicochemical, and toxicological parameters of carwash effluents. Toxicity assays were determined using whole effluent toxicity (WET) using Danio rerio and Daphnia pulex. For microbiological analysis, sample aliquots were spread plated onto R2A Agar for the isolation of heterotrophic bacteria followed by DNA extraction from axenic cultures for sequencing analysis. The pH of effluent samples lay in the alkaline range, and ranged from pH 7 to pH 10. Sample salinity ranged from 0.2 to 0.3 g/Kg. Electrical conductivity values ranged from 274 to 554 μS/cm. Concentrations of Co, Pb, and Ni were < 1 mg/L in all samples while the concentrations of Cu ranged from 0.94 to 3.8 mg/L and Zn from 1.15 to 3 mg/L. Oil and grease concentrations ranged from 5 to 24 mg/L. The concentrations of TPH-GRO were low at < 1 mg/L in all samples. All the carwash effluents were categorised as acutely toxic, with ≥ 75% mortality recorded for both test organisms within the first 24 h of exposure to the test solutions. Heterotrophic bacteria counts ranged from 2800 to 4600 CFU/100 ml. Sequencing analysis revealed that 57% of the isolates were closely related to Aeromonas species, with 43% closely related to Pseudomonas species. We conclude that carwash effluents are veritable sources of microbiological contaminants and potentially toxic chemical pollutants of public health and ecotoxicological concern.

Polybrominated diphenyl ethers (PBDEs) pollution in soil of a highly industrialized region (Dilovasi) in Turkey: concentrations, spatial and temporal variations and possible sources Abstract In this study, polybrominated diphenyl ethers (PBDEs) levels in soil were studied for a whole year in highly industrialized region of Turkey (Dilovasi) at 23 sampling sites. Σ8PBDE concentrations were between 0.15 and 286 μg kg−1 and the overall average concentration was 14.45 ± 25.07 μg kg−1 (average ± SD). BDE-209 was the most abundant compound. PBDEs concentrations decreased spatially as follows: industrial/urban > urban > suburban > rural. However, there was not any significant seasonal trend except for some industrial/urban sites. In the region, calm weather conditions prevailed during the sampling periods, enhancing the impact of the industrial emissions on nearby soil concentrations by atmospheric deposition without being diluted by winds. All congeners had significant but weak correlations with soil organic matter content indicating the impact of nearby sources rather than soil properties on soil PBDEs concentrations at the sampling sites. Positive matrix factorization method was also used for the apportionment of the PBDEs sources in Dilovasi soil. Industrial activities (i.e., iron-steel production, metallurgical processes, and recycling of plastics), traffic, and residential areas were found to be the primary sources of the measured PBDEs in the soil.

Non-parametric tests and multivariate analysis applied to reported dengue cases in Brazil Abstract Dengue is among the largest public health problems in Brazil. Reported dengue cases via DATASUS were correlated with reanalysis data from NCEP (rainfall and air temperature) and Brazil's population data (2000 and 2010) from 1994 to 2014. The aim of this study was to evaluate relational patterns between climate variables together with population data from the last census and reported cases of dengue in Brazil from 1994 to 2014 by using statistical techniques. Several statistical methods [descriptive and exploratory statistics; simple and multiple linear regressions; Mann–Kendall (MK), Run, and Pettit nonparametric tests; and multivariate statistics via cluster analysis (CA)] were applied to time series. The highest percentages of Dengue cases were in Brazil's Southeast (47.14%), Northeast (29.86%), and Central West (13.01%). Upon CA of the Brazilian regions, three homogeneous dengue groups were formed: G1 (North and Central West), G2 (Southeast and Northeast), and G3 (South). Run testing indicated that the time series is homogenous and persistence free. MK testing showed a nonsignificant trend of increase of dengue cases in 23 states with positive trends and in four states with negative trends of Brazil. A significant increase in the magnitude of dengue at the regional level was recorded in the North, Southeast, South, and Central West regions. Statistical methods showed that dengue variability in Brazil is cyclical (2- to 3-year cycles), but not repetitive of El Niño-Southern Oscillation (ENSO) in the moderate, strong, and neutral categories. ENSO interferes with the action of weather systems, changing or intensifying rainfall and air temperatures in Brazil. The population increase in recent decades and the lack of effective public policies together with the action of ENSO contributed to the increase in dengue cases reported in Brazil.

Transformation and source identification of N in the upper reaches of the Han River basin, China: evaluated by a stable isotope approach Abstract Given the spatial and temporal variability in hydrological conditions and nitrogen (N) processes, it is of great uncertainty to identify the N sources and evaluate N transformation processes in the upper Han River. Investigations were conducted in November 2015 and January, April, and July 2016, using an isotopic method and water quality monitoring. The significant and positive correlation between NO3− concentrations and Cl− (p < 0.01) in most sampling months suggested that the great influence of human activities and sewage or manure was the dominant NO3− source. The δ15NO3− values and NO3−/Cl− variations indicated that riverine N mainly came from soil organic N and sewage in November. Fertilizer and sewage were the major N sources in January and April, respectively. In July, water was influenced by various N inputs. The nitrification process played an important role in the low δ15NO3− values in January, while both nitrification and plant uptake resulted in the increase in δ15NH4+ values in April. The simultaneous effect of N fixation and plant uptake maintained the stabilization of δ15NH4+ concentrations. Our study provides theoretical basis on N sources and transformations for controlling N pollution and improving water quality in the upper Han River in the near future.

Using bivariate linear mixed models to monitor the change in spatial distribution of heavy metals at the site of a historic landfill Abstract To improve accuracy and efficiency of monitoring remediated sites, the current study proposed the use of bivariate linear mixed modelling and subsequent hypothesis testing to determine significant change in contaminant concentrations over time. The modelling method integrated soil heavy metal (arsenic–As, lead–Pb and zinc–Zn) concentrations obtained from Bicentennial Park, Sydney, Australia, in the years 1990 (n = 144) and 2015 (n = 60), alongside potential influencing factors as predictor variables. Following variable selection, significant predictors included As (1990)—plan curvature, land cover change; As (2015)—multi-resolution ridge top flatness (MRRTF); Pb (1990)—elevation, MRRTF, type of nearest road; Pb (2015)—land cover change; Zn (1990)—distance to the nearest road and road type; and for Zn (2015)—aspect and land cover change. Model quality statistics (standardised squared prediction error; SSPE) indicated relatively good estimates of the prediction variance (mean ~ 1.0 for all metals, median = 0.512 for As (1990), 0.420 for As (2015), 0.417 for Pb (1990), 0.388 for Pb (2015), 0.342 for Zn (1990) and 0.263 for Zn (2015)), however Lin's concordance correlation coefficient indicated poor prediction of point estimates (LCCC = 0.263 for As (1990), 0.414 for As (2015), 0.250 for Pb (1990), 0.166 for Pb (2015), 0.233 for Zn (1990) and 0.408 for Zn (2015)). Pb in 1990 exceeded the Australian guide value of 600 mg kg−1 in small, isolated areas of the park, and by 2015, these 'hotspots' had significantly diminished (P < 0.05). Concentrations of As were low in both 1990 and 2015, not exceeding the 300 mg kg−1 guide; yet, in 2015, As had significantly increased in the south of the study area (P < 0.2). Zn concentrations in 1990 were elevated but did not exceed the guide value of 30,000 mg kg−1. Overall, the models exhibited good estimation of prediction variance and therefore are suitable for hypothesis testing; however, they exhibited poor prediction quality at times. Despite this, bivariate linear mixed modelling is worth exploring as it provides an advantage over modelling single time points and can assist with tracking potential contaminant sources before they cause harm.

Concentrations of some metals in the nearshore marine sediments of Western Australia's Pilbara Region Abstract Concentrations of arsenic, nickel and chromium in sediments of the nearshore Pilbara Region of Western Australia's mid -north coast have caused concerns to regulators issuing ocean disposal permits for many years. A meta-analysis of data from a large number of surveys, conducted in support of permit applications over many years and across hundreds of kilometres of coastline, shows that, when assessed as total metal concentrations, chromium and nickel occur routinely at concentrations above those recommended as screening triggers by national guidelines and arsenic more rarely. Arsenic was concentrated in surface sediments, consistent with an organic origin. Concentrations of nickel and chromium were higher in deeper sediment layers, consistent with a natural geological origin. However, sediment particle sizing was a major determinant of total metal concentrations of all three metals, and bioavailability was always much lower and within recommended guidelines. Past dredging activity for channels and berths in the large ports of the Pilbara has most likely led to an elevation of fine fractions of surface sediments within operating port areas, when compared to the undisturbed surrounding areas, and may also have increased the proportion of sediment from deeper substrates at the surface. Whilst total concentrations of chromium and nickel commonly exceed screening guidelines throughout the nearshore Pilbara Region, their bioavailability was low and these metals present a little threat to biota.

Time-series analysis of satellite-derived fine particulate matter pollution and asthma morbidity in Jackson, MS Abstract In order to examine associations between asthma morbidity and local ambient air pollution in an area with relatively low levels of pollution, we conducted a time-series analysis of asthma hospital admissions and fine particulate matter pollution (PM2.5) in and around Jackson, MS, for the period 2003 to 2011. Daily patient-level records were obtained from the Mississippi State Department of Health (MSDH) Asthma Surveillance System. Patient geolocations were aggregated into a grid with 0.1° × 0.1° resolution within the Jackson Metropolitan Statistical Area. Daily PM2.5 concentrations were estimated via machine-learning algorithms with remotely sensed aerosol optical depth and other associated parameters as inputs. Controlling for long-term temporal trends and meteorology, we estimated a 7.2% (95% confidence interval 1.7–13.1%) increase in daily all-age asthma emergency room admissions per 10 μg/m3 increase in the 3-day average of PM2.5 levels (current day and two prior days). Stratified analyses reveal significant associations between asthma and 3-day average PM2.5 for males and blacks. Our results contribute to the current epidemiologic evidence on the association between acute ambient air pollution exposure and asthma morbidity, even in an area characterized by relatively good air quality.

Alexandros Sfakianakis
Anapafseos 5 . Agios Nikolaos
Crete.Greece.72100
2841026182

6948891480

alsfakia@gmail.com