Long-term Pollution Research Articles

PATTERNS OF HEAVY METALS ACCUMULATION IN FISH IN LAKES OF THE FENNOSCANDIAN GREEN BELT (IN THE MURMANSK REGION)

The patterns of heavy metals (HM) accumulation in fish from lakes of the Murmansk Region within the Green Belt of Fennoscandia (GBF) exposed to long-term air-borne pol-lution associated with the operation of a non-ferrous metal processing enterprise have been studied. The detrimental effects of air-borne water pollution from the Kola GMK mine and smelter do not depend on the dominant wind directions. The reduction in emis-sions from the Nickel site of the Kola GMK in the past decades has not led to a significant decrease in the level of anthropogenic load. On the contrary, a long-term upward trend is observed in the content of Cu in the organs of whitefish, char, pike and perch in all the lakes studied. The accumulation of Cu and Ni in fish target organs tended to decrease along the distance gradient from the source of pollution. The revealed pattern is con-sistent with the intensity of pathologies development in whitefish organs. The common whitefish (Coregonuslavaretus(L., 1758)) is the most reliable test object that reflects the degree of pressure from long-term exposure to HM. The size of the catchment area is supposed to predetermine the intensity and rate of HM accumulation in fish organisms. The cumulative effect of persistent anthropogenic HM load on waterbodies in the study area, climate change processes, and man-induced eutrophication of waters can show in a decline in the biological diversity of the fish fauna in GBF, reduction in the number of valuable fish species. The identified patterns can be used in assessing the state both of existing and planned protected areas inside GBF.

Estimation of phosphorus flux into the sea through one reversing river using continuous turbidities and water quality modeling

Based on continuous turbidity values (T) and water quality modeling, one methodology was proposed to estimate phosphorus (P) flux into the sea through the river. There are three steps in the procedure: (1) analyzing the relationship of P and total suspended solid (TSS), TSS and T; (2) estimating P concentrations with high temporal and spatial density along the river; and (3) calculating the amount of phosphorus flux into the sea. From September 2014 to December 2016, 224 data sets were collected at eight sites along the Tonglv River which feeds into the Yellow Sea, China. The linear regression of TSS and T provided a fit with R2 = 0.944, and TP and TSS presented linear relationship with R2 = 0.884. It was estimated that about 30,227 kg total phosphorus (TP) flows from the river into the sea from September 2014 to August 2015. It is practicable and credible to use T values and water quality modeling to estimate the process of phosphorus flux. Besides, the procedure proposed could be also applied in analyzing the influence on TP fluxes brought by pollution loading changes. Thus, to facilitate long-term pollutants’ fluxes estimation, combining the regression models with water quality modeling might be an effective technique.

Natural Chlordecone Degradation Revealed by Numerous Transformation Products Characterized in Key French West Indies Environmental Compartments.

Production and use of the insecticide chlordecone has caused long-term environmental pollution in the James River area and the French West Indies (FWI) that has resulted in acute human-health problems and a social crisis. High levels of chlordecone in FWI soils, even after its ban decades ago, and the absence of detection of transformation products (TPs), have suggested that chlordecone is virtually nonbiodegradable in the environment. Here, we investigated laboratory biodegradation, consisting of bacterial liquid cultures and microcosms inoculated with FWI soils, using a dual nontargeted GC-MS and LC-HRMS approach. In addition to previously reported, partly characterized hydrochlordecones and polychloroindenes (families A and B), we discovered 14 new chlordecone TPs, assigned to four families (B, C, D, and E). Organic synthesis and NMR analyses allowed us to achieve the complete structural elucidation of 19 TPs. Members of TP families A, B, C, and E were detected in soil, sediment, and water samples from Martinique and include 17 TPs not initially found in commercial chlordecone formulations. 2,4,5,6,7-Pentachloroindene was the most prominent TP, with levels similar to those of chlordecone. Overall, our results clearly show that chlordecone pollution extends beyond the parent chlordecone molecule and includes a considerable number of previously undetected TPs. Structural diversity of the identified TPs illustrates the complexity of chlordecone degradation in the environment and raises the possibility of extensive worldwide pollution of soil and aquatic ecosystems by chlordecone TPs.

Characteristics of groundwater discharge to river and related heavy metal transportation in a mountain mining area of Dabaoshan, Southern China

Groundwater discharge to river and the related heavy metal transportation were estimated for Dabaoshan, a mountain mining area where extensive mining activities had been conducted over 40 years. In the lower reach of the mining area, shallow aquifers were contaminated by varies heavy metals due to the discharge of acid mine drainage. Polluted aquifers act as long-term pollution sources to the surrounding gaining rivers, even after the mining activities were stopped. The natural tracer 222Rn was measured for river water of the Hengshi River and groundwater adjacent to the river channel in both wet and dry seasons. The total groundwater discharge rate was estimated to be 17.4–26.7 × 103 m3 day−1 in wet season and 1.9–2.1 × 103 m3 day−1 in dry season; and the river recharge was 5.6 ± 1.0 × 103 m3 day−1 in wet season and 2.1 ± 1.0 × 103 m3 day−1 in dry season. Compared with other mining and natural/artificial factor influenced areas, groundwater discharge rate in Dabaoshan was much lower, but the magnitudes of groundwater-borne Cu, Zn, Mn and Co fluxes were comparable or even much higher. This suggested that groundwater-derived heavy metal fluxes were significant pollution sources to river in the mountain mining area. Meanwhile, the results also suggested that concentrations of Cd, Pb, Cu, Ni, Mn, Fe, Zn and Tl in groundwater increased where the recharge of river water to groundwater occurred, suggesting the recharge of river water can affect heavy metal concentrations of the beneath aquifers, even in a gaining river.

Application of Fuzzy Optimization Model Based on Entropy Weight Method in Atmospheric Quality Evaluation: A Case Study of Zhejiang Province, China

A fuzzy optimization model based on the entropy weight method for investigating air pollution problems in various cities of Zhejiang Province, China has been proposed in this paper. Meanwhile, the air quality comprehensive evaluation system has been constructed based on the six major pollutants (SO2, NO2, CO, PM10, PM2.5 and O3) involved in China’s current air quality national standards. After analyzing the monthly data of six pollutants in 11 cities of Zhejiang Province from January 2015 to April 2018 by the above method, the authors found that, although the air quality of cities in Zhejiang Province did not reach the long-term serious pollution of Beijing, Tianjin, and Hebei, the air quality changes in the northern cities of Zhejiang were worse than those in southern Zhejiang. For example, the air quality of Shaoxing in northern Zhejiang has dropped by 14.85% in the last study period when compared with that of the beginning period, and Hangzhou, the provincial capital of Zhejiang, has also seen a decrease of 6.69% in air quality. The air quality of Lishui, Zhoushan and Wenzhou in southern Zhejiang has improved by 8.04%, 4.67% and 4.22% respectively. Apart from the geographical influence, the industrial structure of these cities is also an important cause for worse air quality. From the local areas in southern Zhejiang, cities have developed targeted air pollution control measures according to their own characteristics, including adjusting the industrial structure, changing the current energy consumption structure that heavily relies on coal, and improving laws and regulations on air pollution control, etc. In the four cities in central Zhejiang, the air quality at the end of the period (April 2018) has decreased from the beginning of the period (January 2015), given that there were no fundamental changes in their industrial structure and energy pattern.

Assessing the accuracy of long-term air pollution estimates produced with temporally adjusted short-term observations from unstructured sampling

More commonly air pollution observations are obtained with unstructured monitoring, where either a research grade monitor or low-cost sensor is irregularly relocated throughout the study area. This unstructured data is commonly observed in community science programs. Often the objective is to apply these data to estimate a long-term concentration, which is achieved using a temporal adjustment to correct for the irregular sampling. Temporal adjustments leverage information from a stationary continuous reference monitor, in combination with short-term monitoring data, to estimate long-term pollutant concentrations. We assess the performance of temporal adjustment approaches to predict long-term pollutant concentrations using data representing unstructured sampling. A series of monitoring campaigns are simulated from air pollution data obtained from regulatory monitoring networks in four different cities (Paris, France; Taipei, Taiwan; Toronto, Canada; and Vancouver, Canada) for eight different pollutants (CO, NO, NOx, NO2, O3, PM10, PM2.5, and SO2). These simulated campaigns have randomized monitoring locations and sampling times to simulate the irregular nature of crowd sourced or mobile monitoring data. The number of consecutive samples reported, and selection of the reference monitor used to adjust observations, are varied in this study. The accuracy of estimates is assessed by comparing the estimated long-term concentration to the observed long-term concentration from the complete regulatory monitoring dataset. This study found that a common temporal adjustment applied in research performed significantly worse than other adjustments including a Naïve Temporal Approach where no data adjustment occurred. Increasing the sample size improved the accuracy of estimates, which showed decreasing benefit with increased sample lengths. Lastly, controlling for land use conditions of the reference monitor did not consistently improve the long-term estimates, which suggests that land use pairing of mobile and reference monitors does not significantly influence the predictive power of temporal adjustment approaches. Temporal adjustments can reduce the error in long-term concentration estimates of air pollution using incomplete data, but this benefit cannot be assumed across all approaches, pollutants or sampling programs.

Physiological Parameters of Bream (Abramis brama L.) in Parts of the Rybinsk Reservoir of Different Types

The specific features of accumulation of fat, protein, mineral, and nitrogen-free extractive substances in the skeletal muscles of bream (Abramis brama L.) from areas of the Rybinsk reservoir subjected to different degrees of anthropogenic load have been studied. Data on the bream forage base and feeding in the reservoir are presented. It is shown that, in the areas of the Sheksninskii Reach with high food capacity located in the zone of long-term local anthropogenic pollution, the feeding intensity of bream decreases. This leads to a decrease in fish conditions and amount of fat and mineral substances in their muscle tissues when compared with specimens from conditionally clean stations in the Mologa and Volga reaches with high food capacity.

Palynological insights into global change impacts on Arctic vegetation, fire, and pollution recorded in Central Greenland ice

Arctic environments may respond very sensitively to ongoing global change, as observed during the past decades for Arctic vegetation. Only little is known about the broad-scale impacts of early and mid 20th-century industrialization and climate change on remote Arctic environments. Palynological analyses of Greenland ice cores may provide invaluable insights into the long-term vegetation, fire, and pollution dynamics in the Arctic region. We present the first palynological record from a Central Greenland ice core (Summit Eurocore ’89, 72°35’N, 37°38’W; the location of Greenland Ice Core Project GRIP) that provides novel high-resolution microfossil data on Arctic environments spanning AD 1730–1989. Our data suggest an expansion of birch woodlands after AD 1850 that was abruptly interrupted at the onset of the 20th century despite favorable climatic conditions. We therefore attribute this Betula woodland decline during the 20th century to anthropogenic activities such as sheep herding and wood collection in the sub-Arctic. First signs of coal burning activities around AD 1900 coincide with the onset of Arctic coal mining. The use of coal and fire activity increased steadily until AD 1989 resulting in microscopic-size pollution of the ice sheet. We conclude that human impact during the 20th century strongly affected (sub)-Arctic environments. Moreover, ecosystems have changed through the spread of adventive plant species (e.g. Ranunculus acris, Rumex) and the destruction of sparse native woodlands. We show for the first time that optical palynology allows paleoecological reconstructions in extremely remote sites >500 km from potential sources, if adequate methods are used.

All-cause mortality and long-term exposure to low level air pollution in the ‘45 and up study’ cohort, Sydney, Australia, 2006–2015

BackgroundEpidemiological studies show that long-term exposure to ambient air pollution reduces life expectancy. Most studies have been in environments with relatively high concentrations such as North America, Europe and Asia. Associations at the lower end of the concentration-response function are not well defined. ObjectivesWe assessed associations between all-cause mortality and exposure to annual average particulate matter <2.5 μm (PM2.5) and nitrogen dioxide (NO2) in Sydney, Australia, where concentrations are relatively low. MethodsThe ‘45 and Up Study’ comprises a prospective longitudinal cohort from the state of New South Wales, Australia with 266,969 participants linked to death registry data. We analyzed data for the participants who resided in Sydney at baseline questionnaire (n = 75,268). Exposures to long-term pollution were estimated using annual averages from a chemical transport model (PM2.5), and a satellite-based land-use regression model (NO2). Socio-demographic information was extracted from the baseline questionnaire. Cox proportional hazard models were applied to estimate associations, while adjusting for covariates. ResultsIn our cohort mean annual PM2.5 was 4.5 μg/m3 and mean NO2 was 17.8 μg/m3. The mortality rate was 4.4% over the 7 years of follow up. Models that adjusted for individual-level and area-level risk factors resulted in a detrimental non statistically significant hazard ratio (HR) of 1.05 (95% CI: 0.98–1.12) per 1 μg/m3 increase in PM2.5, and 1.03 (95% CI: 0.98–1.07) per 5 μg/m3 increase in NO2. ConclusionsWe found evidence that low-level air pollution exposure was associated with increased risk of mortality in this cohort of adults aged 45 years and over, even at the relatively low concentrations seen in Sydney. However, a clear determination of the association with mortality is difficult because the results were sensitive to some covariates. Our findings are supportive of emerging evidence that exposure to low levels of air pollution reduces life expectancy.

A study on the concentration of heavy metals and histopathological changes in Persian jirds (Mammals; Rodentia), affected by mining activities in an iron ore mine in Iran.

Mining activity constitutes a potential source of heavy metal pollution in the environment. Long-term exposure to heavy metals (e.g., cadmium) has adverse health effects. Rodents frequently serve as bioindicators to monitor the levels of heavy metals in the environment. In the present study, concentrations of 10 heavy metals (Cd, Co, Cr, Cu, Fe, Mo, Ni, Pb, Sb, and Zn) in kidney, liver, and muscle tissue of the Persian jird (Meriones persicus) were evaluated. This is the first study to examine the histopathological changes in Persian jird tissues caused by the bioaccumulation heavy metals. The samples were taken at location that surrounded by Sangan Iron Ore Mine (SIOM) mining activities, in northeastern Iran. The results show that the highest concentrations for the metals were observed in kidney and liver, whereas lowest concentrations were found in muscle of Persian jirds. The concentration of Pb was below the limit of detection. Sex and age were two factors that could explain the different levels of heavy metal bioaccumulation, which affects the concentration of some metals. Adults had significantly higher Cu and Cd levels compared to juveniles. Males bioaccumulated more Zn in their kidneys than females, whereas females bioaccumulated more Fe in their livers. As expected, heavy metals affected various organs of the studied specimens. Hyperemia, hemorrhage, necrosis, and degenerative damage to the epithelial cells of the tubules, the presence of hyaline casts, and in one case, mononuclear leukocyte infiltration, were observed in samples of renal tissue. Hemorrhage and hepatocyte vacuolization were the most common histopathological changes found in samples of hepatic tissue. These effects and the concentrations of heavy metals in the studied specimens indicate the need for monitoring and frequent sampling to evaluate long-term persistent pollutants.

Comparative metagenomics and functional profiling of crude oil-polluted soils in Bodo West Community, Ogoni, with other sites of varying pollution history

The impact of long-term crude oil pollution on soil microbial community structure in Bodo West Community, Ogoniland, Nigeria, was investigated to determine the amenability of the soil to microbial mediated remediation. Crude oil-polluted and pristine soil samples were collected approximately from 0 to 30 cm depth for both chemical and microbiological analyses. Total petroleum hydrocarbons (TPH) and polycyclic aromatic hydrocarbons (PAH) were determined using gas chromatograph–mass spectrophotometer (GC-MS). The soil microbiome was determined using the Illumina MiSeq platform. Results from this study were then compared with publicly available data from other oil-polluted sites. Taxonomic biomarkers and pathways associated with oil-polluted soils were detected using bioinformatics pipelines. TPH in the polluted and pristine soils were 7591 mg/kg and 199.70 mg/kg respectively, while the values of PAHs were significantly higher (p < 0.05) in the oil-polluted soil. Predictive functional and biomarker analysis demonstrated that microbes detected in the oil-polluted environment were involved in different metabolic pathways for degradation of a broad set of xenobiotic aromatic compounds. Established hydrocarbon degraders belonging to the families Alcanivoracaceae and Oceanospirillaceae were mostly detected in the oil-polluted soils. Sneathiella, Parvibaculum, Sphingobium, and Oceanicaulis were among biomarker taxa. The bacterial families Acidithiobacillaceae and Desulfobacteraceae were differentially more abundant in Bodo West spill site than any other site used for comparison. Furthermore, differentially represented species in our study site and other oil-polluted sites ranged from 21 to 42 bacterial families. The findings from this study revealed the bacterial community had a strong dependence on hydrocarbons and that acid-tolerant bacterial families can as well contribute significantly to biodegradation in the site and other polluted sites in Ogoniland usually known to have an acidic pH. Further research on Bodo West spill site will reveal the novel enzymes and pathways for enhanced microbial mediated eco-restoration.

A conceptual model of organochlorine fate from a combined analysis of spatial and mid- to long-term trends of surface and ground water contamination in tropical areas (FWI)

Abstract. In this study, we investigated the management of long-term environmental pollution by organic pollutants such as organochlorine pesticides. We set out to identify conditions that are conducive to reducing pollution levels for these persistent molecules and then propose a conceptual model of organochlorine fate in water. Our approach looked at spatio-temporal changes in pollutant contents in surface water (SW) and groundwater (GW) on a large scale, in order to decipher the respective roles of soil, geology, hydrology and past treatment practices. The case of chlordecone (CLD) on the island of Martinique (1100 km2) was selected given the sampling campaigns carried out since 2007 over more than 150 sites. CLD, its metabolite chlordecone-5b-hydro (5bCLD) and the metabolite-to-parent-compound ratio were compared. As regards the spatial variability of water contamination, our results showed that banana cropping areas explained the location of contaminated SW and GW, whereas the combination of soil and geology factors explained the main spatial variability in the 5bCLD∕CLD ratio. For temporal variability, these conditions defined a high diversity of situations in terms of the duration of pollution, highlighting two groups: water draining old geological formations and ferralsols or vertisols vs. recent geology and andosols. A conceptual leaching model provided some key information to help interpret downward trends in CLD and 5bCLD observed in water. Lastly, a conceptual model of organochlorine fate is proposed to explain the diversity of the 5bCLD∕CLD ratio in water. Our conclusions highlight the combined role of soil and groundwater residence time for differentiating between conditions that are more conducive, or not, to the disappearance of CLD from the environment. This paper presents a model that provides an overall perception of organochlorine pesticide fate in the environment.

Current state of atmospheric air pollution in Ukraine based on Sentinel-5P satellite data

Introduction. Industrial development and increasing traffic emissions cause air quality problems. The most accurate for air pollution analysis are ground-based data; however, it is very limited in space. Modelling could solve this problem, but huge amount of input information and limits of computational power make it difficult to analyze big territories with high resolution. Sentinel-5P satellite with TROPOMI instrument nowadays gives opportunities to monitor the air pollution with good spatial resolution. The purpose of the study is to analyse nitrogen dioxide, sulfur dioxide, carbon monoxide and formaldehyde spatial and temporal distribution over Ukraine and Black Sea and Azov Sea. Methods and raw data. There were selected Sentinel-5P data of NO2, SO2, CO and HCHO for the period from first data release in 2018 to June, 2019. Data processing implemented in Google Earth Engine using JavaScript programming in The Earth Engine Code Editor. Results and discussion. Joint analysis of NO2 tropospheric, stratospheric and total columns showed the prevailing of tropospheric NO2 content and therefore crucial role of anthropogenic emission sources. While background NO2 total column varies from 4·10-5 mol/m2 to 7·10-5 mol/m2, in the most polluted cities content exceeds 1·10-4 mol/m2. The highest values are observed in Kyiv and industrial cities in Donbas region. Some of them are situated in the area of Joint Forces Operation outside the demarcation line. Sentinel-5P data catch the large emissions from the local industries; however, no official confirmations about production volume are available. NO2 dispersion increase during winter with the values range from 1·10-5 mol/m2 to 3·10-5 mol/m2 over clean territories and 8·10-5 mol/m2 to 1·10-3 mol/m2 in industrial cities. Seasonal maximal observed during warm period in unpolluted regions and during winter in the cities. Cold seasonal NO2 content outbreaks in the mountains are the result of its transportation from industrial cities. Spatial distribution of CO total column over Ukraine is rather homogeneous because of CO lifetime in the atmosphere up to several months. It could be transported on the long distances, which makes identification of polluted regions difficult. However, several cities with maximal average values of more than 0.037mol/m2 prove the existence of extreme anthropogenic emissions. Overall background CO contents vary within 0.033–0.035 mol/m2. Coastal regions of the Black Sea and Azov Sea are more polluted by CO compared to the mainland, which could be the consequences of ships emissions. Temporal analysis of CO total column found 4 powerful emissions: three of them are anthropogenic in industrial cities and one is natural, connected with forest fires in Belarus and northern part of Rivne region in April, 2019. There is one location with huge SO2 emission in Ukraine, observed in Novyi Svit (Donetsk region) outside the demarcation line of Joint Forces Operation, which corresponds to Starobeshivska thermal power station. In general, higher SO2 contents are observed over Donetsk, Zaporizhia and Dnipro regions; also over the Black Sea and Azov Sea. For HCHO spatial distribution minimal values are typical for the Carpathians. It is well seen that SO2 content are higher in the Southern part of Ukraine than in the Western part. The research finds regularities in spatial distribution of pollutants over the sea area. During cold season higher concentrations could be observed over the main merchant vessels tracks in the Black Sea. In summer months, which coincide with the main tourist season, most polluted are shoreline area because of emissions from cabotage and fishing vessels. The study updates information about most polluted cities in Ukraine, especially in the regions with absence of ground-based measurements. Some of them are mentioned for the first time among other research. Air quality analysis in many industrial cities significantly changed over the last two years. It shows difficulties of long-term pollution forecast and scenarios based on historical data and observed trends. It is recommended to use ensemble modelling for this purpose with scenarios of emission reduction, increasing and temporal stability. Sentinel-5P data confirm the conclusions of previous research about dependence of NO2 annual cycle and seasonality phases shift from the level of anthropogenic load. Prospects for further research. Sentinel-5P spatial resolution expands the horizons for air pollution research. The most relevant are monitoring of short-term anthropogenic and natural emissions, pollutants’ seasonality changes in different macroclimatic conditions, research of ships emissions in Black Sea and Azov Sea, combination of satellite air pollution data with methods of “artificial intelligence” for individual emissions detection.

Watershed diffuse pollution dynamics and response to land development assessment with riverine sediments

Sediment cores can reflect diffuse pollution history due to the accumulation of pollutants over time, therefore, the quantitative relationship between the sedimentation flux of pollutants and diffuse loads can identify the historical change. Sediment cores were collected from two river reaches in a small agricultural watershed (143 km2), and the total nitrogen (TN) and total phosphorus (TP) concentrations were determined. The sediments were dated using 210Pb isotope radioactivity and the TN and TP sedimentation flux was calculated with Constant Rate of Supply (CRS) and Constant Initial Concentration (CIC) models. Watershed loss loads were simulated using the Soil and Water Assessment Tool (SWAT) in the same temporal period. As the similar natural condition in the post-depositional period of sediments, a linear regression model was used to analyze the relationship between TN and TP sedimentation flux and the hindcast model data. The TP sedimentation flux showed a clear positive relationship with its simulated load (R2 = 0.600 and 0.664) using the CRS model, and better reflected long-term diffuse pollution loss dynamics than nitrogen. The impacts of land use change on diffuse pollution loading were identified with the combination of sedimentation flux from different reaches and watershed modeling. During the expansion of paddy land in the lower reach, the difference of TP sedimentation flux between upper and lower reaches narrowed, while gap of TN sedimentation flux increased. Base on the lateral correlations of two sections, the sediment concentration of TP was more reliable for the long term diffuse pollution assessment under land development.

Support for Emissions Reductions Based on Immediate and Long-term Pollution Exposure in China

Reducing power sector emissions in China is a critical step toward mitigating climate change and lowering health damages from air pollution. We conduct a discrete choice survey (N = 1060) among urban residents from 10 Chinese cities, assessing how individuals compare electricity source, cost, and reduction of emissions related to climate change or air pollution. Using observed air quality data, we also evaluate how pollution levels affect respondents' support for different types of emissions reductions. We find that reductions targeting both climate change and human health benefits have stronger support than those which address only one of the two. Furthermore, respondents in cities with the highest annual concentrations of particulate matter are willing to pay 30% more to clean up the air when compared to individuals living in less polluted cities. The analysis suggests that the public values co-optimizing mitigation policy across climate and health objectives, and that making available information on long-term air quality may encourage sustained support for cleaner energy.

New energy, angle momentum and entropy balance approach to modelling climate and macroturbulent atmospheric dynamics, heat and mass transfer at macroscale. I. General Formalism

We present elements of a new non-stationary balance approach to modelling global mechanisms of climate and macro turbulent atmospheric low-frequency processes, including processes of heat-mass transfer at spatial and temporal macro scales, teleconnection effects etc. The main forming factor is a triplet of interacting solitons: planetary soliton of Hadley cells - the entire complex of atmospheric fronts - the Rossby soliton wave packet. The approach is based on the using balance relationships for entropy, energy and angular momentum, spectral theory of atmospheric macroturbulence, atmospheric moisture flow in further connection with the continuity of atmospheric circulation forms (teleconnection, genesis of fronts). Particular application is studying a spatial-temporal picture of the long-term atmospheric pollutants (including distribution of radionuclides after accidents at the nuclear power plant like Fukushima etc) in the atmosphere with accounting for the macro turbulent, circulation low-frequency processes .

Effects of environmental factors on benthic species in a coastal wetland by redundancy analysis

To elucidate the effects of environmental factors on the richness and diversity of benthic species, this study investigates the hydrology, water quality and physicochemical conditions of the soil around a coastal wetland in Central Taiwan. Samples were extracted monthly from 20 sites around the coastal wetland for one year and analyzed by redundancy analysis (RDA). The outcomes of this study reveal that the environmental parameters of the habitat govern different patterns of benthic species in wetlands. The properties of soil influence the pattern of benthic species, which has been changing in the study area owing to human activities, such as land reclamation, the building of bulwarks and the emission of pollution. The results reveal that heavy pollution loading near the local area with animal husbandry also reduced the richness and diversity of benthos. Principal Component Analysis (PCA) is used to identify all relevant environmental factors to explain the impact of economic and environmental behaviors on the distribution of benthic species. The PCA results demonstrate that short-term and long-term pollution differently influence patterns of benthic species.

Study on the influence of soil microbial community on the long-term heavy metal pollution of different land use types and depth layers in mine

To understand the importance of the response of soil microbial communities to the stress of heavy metals around mining areas by assessing the feedback of soil ecosystems in different soil habitats, this article selected different land use types (Mining area, Dressing area, Heap mine area, Tailings area and Vegetable field) and surface soil samples of different depths (0–10 cm, 10–20 cm, 20–30 cm) as the variables related to the mining activities in the Shizishan mining area in Tongling, Anhui Province, China. Soil physicochemical properties and heavy metal concentrations of the different land use types and soil depths were compared. Illumina MiSeq. 2500 Sequencing Technology was used to analyze the abundance and structural diversity of the microbial community in soil samples. The relationship between mine soil pollution characteristics and microbial community were investigated. The results showed that soil physicochemical properties and heavy metals significantly affected the microbial community. The microbial community structure was significantly variable in vertical soil depth-layer habitats. The relative abundance (1%) of the soil microbial community at the phylum level was represented by a total of 14 phyla, where the two most dominant phyla were Proteobacteria (41.71%) and Firmicutes (20.44%). The two bacteria were positively related with Cu, Zn, Pb, and pH but negatively associated with soil organic matter (SOM), available potassium (AK), and moisture content (MC). Therefore, Proteobacteria and Firmicutes were highly resistant to heavy metals. These results increased our understanding of microbial variation and assembly pattern under different land use types in heavy metals contaminated mining soils.

Long-Term River Water Quality Trends and Pollution Source Apportionment in Taiwan

The application of multivariate statistical techniques including cluster analysis and principal component analysis-multiple linear regression (PCA-MLR) was successfully used to classify the river pollution level in Taiwan and identify possible pollution sources. Water quality and heavy metal monitoring data from the Taiwan Environmental Protection Administration (EPA) was evaluated for 14 major rivers in four regions of Taiwan with the Erren River classified as the most polluted river in the country. Biochemical oxygen demand (6.1 ± 2.38), ammonia (3.48 ± 3.23), and total phosphate (0.65 ± 0.38) mg/L concentration in this river was the highest of the 14 rivers evaluated. In addition, heavy metal levels in the following rivers exceeded the Taiwan EPA standard limit (lead: 0.01, copper: 0.03, and manganese: 0.03) mg/L concentration: lead-in the Dongshan (0.02 ± 0.09), Jhuoshuei (0.03 ± 0.03), and Xinhuwei Rivers (0.02 ± 0.02) mg/L; copper: in the Dahan (0.036 ± 0.097), Laojie (0.06 ± 1.77), and Erren Rivers are (0.05 ± 0.158) mg/L; manganese: in all rivers. A total 72% of the water pollution in the Erren River was estimated to originate from industrial sources, 16% from domestic black water, and 12% from natural sources and runoff from other tributaries. Our research demonstrated that applying PCA-MLR and cluster analysis on long-term monitoring water quality would provide integrated information for river water pollution management and future policy making.

Functional traits of epiphytic lichens respond to alkaline dust pollution

Abstract Dust pollution has a harmful impact on the environment and human health. Lichen trait-based metrics are increasingly used to monitor effects of air pollution, but studies using this technique to monitor the effects of dust pollution are still scarce. Functional traits of lichens along a gradient of long-term alkaline dust pollution were investigated. Species composition was affected along this gradient according to two easily identifiable “soft” traits (growth form and main reproductive strategy) and one expert-assessed “hard” trait (species preference for substrate pH). Particularly, crustose species and lichens with sexual reproduction were related to the most polluted side of the gradient and higher pH, while foliose narrow-lobed species and lichens with asexual reproduction were associated with the opposite side.