Fogs and hazes broke out many times in winter and spring of 2012-2013 in Beijing, inducing severe pollution of respirable particulate matters (PM10). As a fine particle component in PM10, PM2.5 would cause more severe air pollution if the proportion of PM2.5 to PM10 is high. Based on this, 30 monitoring stations recording the concentration of PM2.5 and PM1.0 all over Beijing were selected, and the contamination characteristics of particulate matters were analyzed, which further served to determine the characteristics of temporal and spatial pollution variations of PM2.5 and PM10. The distribution of PM2.5 and PM10 mass concentration in winter and spring in Beijing were derived by the Original Kriging interpolation method, and it was depicted from the figure that the concentration of particulate matters gradually increased from the northern mountain area to the southern part of Beijing; in the central urban area, the particulate concentration of the western region was generally higher than that of the eastern region, with certain differences between urban and rural area within some local areas. Monthly variation curve of PM2.5 and PM10 mass concentration showed single peak-valley pattern: the maximum was in January and the minimum was in April; daily variation indicated a good correlation between PM2.5 and PM10, both of which were significantly influenced by meteorological conditions; diurnal variation curve showed a double peak-valley type. Meteorological factors such as daily average temperature (degrees C), relative humidity (%), wind speed (wind scale), precipitation (mm) were chosen and their individual relationships with concentrations of PM10 and PM2.5 were investigated using Spearman rank correlation analyses. It was demonstrated that the concentrations of PM10 and PM2.5 were positively correlated with temperature and relative humidity, respectively, and strongly negatively correlated with wind speed; wind speed and relative humidity were two key factors affecting the distributions of PM2.5 and PM10 concentration.
It has important scientific value and practical significance for urban atmospheric air pollution control and people health protection to carry out health risk assessment as well as impaired value assessment of short-term high concentrations of air pollution. Using the Poisson regression model and environmental valuation method, this study estimated the health risks and impaired values of Beijing residents in a consecutive high-level PM2.5 exposure during the heavy haze pollution occurred from January 10th to 15th, 2013. The results show that, substantial health risks due to PM2.5 air pollution were occurred in six pollution days, including 201 cases of premature deaths, 1,056 and 545 cases of hospital admissions for respiratory and cardiovascular diseases, 7,094 and 16,881 cases of pediatric and internal outpatients each, 10,132 cases of acute bronchitis and 7643 cases of asthma respectively. Correspondingly, approximate 489 (95% CI: 204-749) million RMB health-related economic loss was evaluated, of which more than 90% was attributable to premature deaths, acute bronchitis and asthma. It is recommended that health risks and economic losses can be reduced through early health warning and timely medical intervention for various groups of people with different health endpoints.
A total of 87 daily PM samples were collected in the urban area of Suzhou city during 2015, representing spring, summer, autumn, winter, respectively. Mass concentration of PM was analyzed gravimetrically. Water-soluble inorganic ions, including F , Cl , NO , SO , Na , NH , K , Mg and Ca , were determined by ion chromatography. The average mass concentration of PM was (74.26±38.01) μg·m . The seasonal variations of PM concentrations decreased in the order of winter > spring > autumn > summer. The average total mass concentrations of 9 ions was (43.95±23.60) μg·m , and the order of concentration of ions was NO > SO > NH > Na > Cl > K > Ca > F > Mg . Seasonal variation of ion concentrations was significant, with the highest concentration observed in winter and the lowest in summer. The secondary inorganic species, including SO , NO and NH (SNA) were the major components of the water-soluble ions in PM . SNA's correlations with each other were significant. SO , NO and NH were probably in the form of NH NO and (NH ) SO . The [NO ]/[SO ] ratio approaching to 1 implied that mobile sources were as important as stationary sources. Ion balance calculations indicated strong correlations between anion and cation equivalents. The PM was acidic. Industrial emission, combustion process, secondary formation and fugitive dust were the major sources of the water-soluble ions in PM .
The aim of this work is to understand the effects of straw and biochar return in soil on the content, distribution, stability, and relative contribution rate of organic carbon for soil aggregates, which could be used to better understanding the stability of the soil carbon pool and the protection mechanisms under straw and biochar return. In this study, a field experiment was conducted to study the effects of straw and biochar return on soil aggregates and carbon sequestration characteristics in a rape-maize rotation planting system. Five treatments, including a control (no organic material added, CK), straw (CS), straw and microorganism (CSD), Biochar (BC), half straw and half biochar (CSBC), were used. The results indicated that ① Straw and biochar could improve the content of soil organic carbon, and the BC and CSBC treatments increased it by 16.88-17.37 g·kg , values higher than those with the CS and CSD treatments (13.76-14.68 g·kg ); ② Compared with the CK treatment, CS and CSD treatments could increase the stability of the aggregates through significantly increasing the content of macro-aggregate by 94.00%-117.78% and significantly increasing the mean weight diameter (MWD), geometric mean diameter (GMD), and R of water stable aggregates, but reducing the D value ( <0.05); and ③ With the increase in aggregate particle size, the content of organic carbon in the aggregates decreased first and then increased. The contribution rate of soil organic carbon in silt and clay was the highest (29.61%-42.18%), and the contribution rate of organic carbon in the macro-aggregate was the lowest (9.19%-17.81%). In addition to the CSD treatment, the CS, BC, and CSBC treatments reduced the contribution of larger aggregates (2-0.25 mm) and micro-aggregates (0.25-0.053 mm). In general, the benefit of straw return was better than that of biochar in promoting soil aggregation. However, the application of biochar was better than straw in improving the aggregates organic carbon content. The newly generated carbon from straw degradation was mainly distributed in large aggregates. Straw with microorganisms could promote the combination of carbon by different components in the larger aggregates. The carbon from biochar and straw with biochar treatments were mainly concentrated in micro-aggregates.
The present paper takes the coal mining area of Longkou City as the research area. Thirty-six topsoil (0-20 cm) samples were collected and the contents of 5 kinds of heavy metals were determined, including Cd, As, Ni, Ph, Cr. Geo-statistics analysis was used to analyze the spatial distribution of heavy metals. Principal component analysis (PCA) was used to explore the pollution sources of heavy metals and the degree of heavy metals pollution was evaluated by weighted average comprehensive pollution evaluation method. The results showed that enrichment phenomenon was significant for the 5 kinds of heavy metals. Taking secondary standard of National Environment Quality Standard for Soil as the background value, their exceed standard rates were 72.22%, 100%, 100%, 91.67%, 100%, respectively. Average contents of heavy metals in the soil samples were all over the national standard level two and were 1.53, 11.86, 2.40, 1.31, 4.09 times of the background value. In addition, the average contents were much higher than the background value of the topsoil in the eastern part of Shandong Province and were 9.85, 39.98, 8.85, 4.29, 12.71 times of the background value. According to the semivariogram model, we obtained the nugget-effects of 5 kinds of heavy metals and their values were in the order of As (0.644) > Cd (0.627) > Cr (0.538) > Ni (0.411) > Pb (0.294), all belonging to moderate spatial correlation. On the whole, the central part of the Sangyuan Coal Mine and its surrounding areas were the most seriously polluted, while the pollution of heavy metals in the east and west of the study area was relatively light. Principal component analysis suggested that the enrichment of Cd, As, Ni, Cr was due to irrigation of wastewater, the discharge of industry and enterprise, and the industrial activity. Automobile exhaust and coal combustion were the main pollution sources of Pb. The single-factor assessment of heavy metals pollution showed that the degree of different heavy metals pollution was in the order of As > Cr > Ni > Cd > Pb. Simultaneously, comprehensive pollution evaluation showed that the degree of heavy metals pollution in the study area was very serious, with comprehensive pollution index ranging from 2.17 to 4.66, among which, the numbers of moderate and heavy pollution samples were 10 and 26, respectively. Areas with heavy pollution were mainly distributed in the Sangyuan Coal Mine, Beizao Coal Mine, Liuhai Coal Mine; and the areas with moderate pollution covered Wali Coal Mine, Liangjia Coal Mine, and other regions. The results of this paper will provide data reference and theoretical support for the study of ecological risk assessment in the study area.
Based on anthropogenic source activity data and emission factors for the Sichuan Province, the 1 km×1 km-gridded atmospheric air pollutant emission inventory of 2015 was developed in combination with GIS technology and the combined "bottom-up" and "top-down" construction method. The results show that the total emission of SO , NO , CO, PM , PM , BC, OC, VOCs, and NH in Chengdu is 444.9×10 , 820.0×10 , 3773.1×10 , 1371.6×10 , 537.5×10 , 28.7×10 , 53.1×10 , 923.6×10 , and 988.0×10 t, respectively. Power plants and other industrial combustion boilers contribute more than 95% of the SO emissions. Mobile, fossil fuel combustion, and industrial process sources contribute 54%, 23%, and 20% of the NO emissions, respectively. The industrial process of steel production and building materials manufacturing contribute 20% PM of the emissions and take up 34% PM of the emissions. Fugitive dust and road fugitive dust contributes 60% PM and 35% PM of the emissions, respectively. Biomass combustion contributes 33% BC and 51% OC of the emissions, respectively. The solvent use of mechanical processing, building decoration, electronic equipment manufacturing, and printing and furniture industry contribute 46% of the VOCs of the emissions. The NH emissions mainly orginate from the sources of livestock feeding and nitrogen fertilizers, accounting for 70% and 25% of the NH emissions, respectively. The spatial distribution of the emissions shows that high emissions are mainly distributed in the most densely populated, agricultural, and industrial more developed areas in Panzhihua and the Sichuan Basin. The urban agglomerations of the Chengdu Plain, represented by Chengdu, Deyang, and Mianyang, are the areas with emission concentration in the Sichuan Basin. The emissions inventory in this study has uncertainties. More fundamental studies on activity data should be conducted and the emission factors of typical emission sources should be further localized to improve the emission inventory and prevention and control of complex air pollution in the Sichuan Province and provide scientific support.
Heavy metal pollution of farmland soils in China has been identified as a threat to ecosystem safety and human health. A total of 3006 soil samples were analyzed from arable lands in five grain producing regions of China, which included data from published studies from 2000 up to now. An additional 656 historical samples were derived from the 1980s by a digitizing grained point sites map (Cd, Pb, As, Ni, Cu, Zn, Cr, and Hg) from the PRC Atlas of Soil Environmental Background Values. A GIS-based approach and single factor index method were employed to identify the current status and spatial distribution of heavy metal (Cd, Pb, As, Ni, Cu, Zn, Cr, and Hg) contamination in agricultural soils, and these were then compared with historical data to explore contamination trends over time. Then, based on the I method and the effects of the surrounding environment on contamination rates, pollution sources were analyzed. Results showed that 21.49% of the agricultural soil samples exceeded the environmental quality standard set by the Ministry of Environmental Protection. The proportions of slight, moderate, and severe pollution were 13.97%, 2.50%, and 5.02%, respectively. Pollution is more extensive in the south compared with the north. Exceedance percentages in the Sichuan Basin (SC), Yangtze River Middle Plain and Jianghuai Plain (CJ), Huang-Huai-Hai Plain (HHH), Songnen Plain (SN), and Sanjiang Plain (SJ), were 43.55%, 30.64%, 12.22%, 9.35%, and 1.67%, respectively. The main pollutants were Cd, Ni, Cu, Zn, and Hg, with exceedance percentages of 17.39%, 8.41%, 4.04%, 2.84%, and 2.56%, respectively. Since the 1980s, heavy metal pollution has increased by 14.91%. The proportion of Cd, Ni, Cu, Zn, and Hg increased by 16.07%, 4.56%, 3.68%, 2.24%, and 1.96%, respectively. Except for SJ, exceedance percentages in cultivated land increased significantly, while the exceedance percentages of Cd, Ni, and Cu in the southern areas were higher than for the northern areas-although the growth rate of Hg and Cr in the south was lower than that in the north. The main sources of Cd and Hg were anthropogenic pollution, while the other six heavy metals were from predominantly natural sources. However, about 20.00% of Pb, Zn, and Cu were affected by anthropogenic activities. Mining, industry, and sewage water were the main sources of pollution. In addition to the larger impact of sewage irrigation in the north, other sources of pollution showed greater influence in the south. Mining mainly caused pollution by Cd, Hg, Ni, Cr, and Cu, while excessive levels of Cd, Ni, Cu, Zn, and Hg was the signature of industrial pollution. Irrigation with sewage effluent causes excessive Cd, Ni, and Zn. Results from this study provide valuable information for agricultural soil management and food safety in China.
A total of 106 samples were collected from surface soils in Gangcheng District, Laiwu city (a Typical industry-based city of Shandong Province, Eastern China), and the contents of 9 heavy metals including As, Cd, Co, Cr, Cu, Hg, Ni, Pb and Zn were determined. Multivariate analysis and geostatistics were,applied to examine the sources and spatial distributions of heavy metals in soils; and the assessment on ecological risk of heavy metals was carried out using Hakanson's method. The average concentrations of 9 heavy metals were higher than the background values of Shandong Province; in particular, the mean contents of Cd, Hg, Pb and Zn were 2.42, 4.69, 1.74 and 1.54 times of their respective background values, which indicated there were obvious accumulations of these heavy metals in surface soils. The results from multivariate analysis suggested that all the 9 heavy metals could be classified as 3 Principal Components (PCs). Cd, Pb and Zn, having high loads in PC1, were dominated by industrial, agricultural and traffic sources. PC2 including Co, Cr and Ni came from natural sources, and were controlled by parent materials. As and Hg with high loads in PC3, were originated from coal combustion and smelting. Cu had some loads on different PCs, and was affected by both natural and human sources. Assessment on ecological risk indicated that the study area suffered from a critical level between high and moderate risks. Hg was at the high ecological risk level, and Cd was at the moderate ecological risk level, while other metals had low ecological risk level.
To clarify the pollution characteristics of heavy metals in the surface sediments of rivers in economically developed areas, analysis of the contents of eight heavy metals, assessment of ecological risks, and identification of the source of heavy metals in surface sediments from typical rivers of Lake Taihu Basin were carried out in this study. The results showed that the average contents of Zn, Cr, Ni, Cu, Pb, As, Cd, and Hg in the surface sediments of Lake Taihu Basin were 163.62, 102.46, 45.50, 44.71, 37.00, 13.34, 0.479, and 0.109 mg·kg , respectively. Except for Hg, the average contents of other 7 heavy metals were higher than their background values. The geo-accumulation index indicated that Pb, Ni, Zn, Cu, and Cd amount to a low pollution state. According to the pollution load index, Pb, Ni, Zn, and Cu represent a moderately polluted state, while Cd, Cr, and As a low degree pollution state. Based on the potential ecological risk index, Cd and Hg represent moderate potential ecological risk, and the others low potential ecological risk. Source identification of heavy metals by multivariate statistical analysis showed that Pb was largely from non-point pollutions; Cr, Ni, and Zn stemmed from electroplating, alloy manufacturing industries, and nature; Cu and As were mainly from pesticides and discharge of industrial wastewater; Cd was dominantly from smelting industry; and Hg was mainly derived from fossil fuel combustion and petroleum products.
In order to explore the effects of different amounts of biochar applied in purple paddy soil on greenhouse gas (GHG) emissions, potted experiments using a static opaque chamber and gas chromatography method were used to study the regulations and influences of biochar on soil greenhouse gas emission using five treatments:no fertilizer (CK), conventional fertilization (NPK), 10 t ·hm biochar+NPK (LBC), 20 t ·hm biochar+NPK (MBC), and 40 t ·hm biochar+NPK (HBC). ① Soil CH emission flux reduced significantly with all biochar application treatments; the emission flux followed the order, from large to small, of NPK > CK > LBC > MBC > HBC. The CH emission flux of each treatment showed a single peak curve, and the peak value was mainly concentrated in the late growth stage of the paddy cropland. During the entire observation period, the emission flux of CH was between -0.05 mg ·(m ·h) and 47.34 mg ·(m ·h) . The CO emission flux of each treatment was complicated and ranged from 32.95 mg ·(m ·h) to 1350.88 mg ·(m ·h) . The CO emission flux of the LBC and MBC treatments showed bimodal curves, and the CO emission flux of other treatments showed single peak curves. In addition, all biochar treatments delayed the peak time of the CO emission flux. The N O emission flux of each treatment ranged from -309.39 to 895.48 μg ·(m ·h) , and the N O emission flux of the LBC treatment showed a bimodal curve, while other treatments showed single peak curves. ② Compared with the CK treatment, biochar treatment can significantly reduce the cumulative emissions of CH and promote the cumulative emissions of CO and N O. The average amount of CH cumulative emissions followed the order CK > LBC > MBC > HBC, while the average amount of CO cumulative emissions followed LBC > MBC > HBC > CK, and the average amount of N O cumulative emissions followed HBC > MBC≈LBC > CK. Compared with conventional fertilization treatment, different application rates of biochar addition significantly reduced CH and CO emissions. As more biochar was added, CH and CO cumulative emissions were lower. Although the regulation of N O cumulative emissions on biochar addition was not obvious, the application of nitrogen fertilizer could promote the emission flux of N O to some extent. ③ Over the time scale of 100 years, the integrated global warming potentials (GWP) of CH and N O emission under different biochar treatment were decreased significantly, indicating that biochar combined with chemical fertilizer is an effective GHG emission reduction measure.
In order to understand the characteristics and sources of PM₂.₅ pollutant in Lanzhou City, two PM₂.₅ sampling sites were set up in Chengguan district and Xigu district, respectively. Samples were sampled during October (non-heating period) and December (heating period) 2013, and mass concentrations of PM₂.₅ and its 16 kinds of chemical components were analyzed. The results showed that the average mass concentration of PM₂.₅ during the sampling period was 129 µg · m⁻³. The sequence of mass concentrations of inorganic elements was: S > Ca > Fe > Al > Mg > Pb > Zn > Mn > Ti > Cu, while the mass concentrations of S, Ca, Fe, and Al, which were the major element compositions, exceeded 1 µg · m⁻³. The mass concentration of inorganic elements during heating period was higher than that during non-heating period, meanwhile, the mass concentration in Chengguan district was higher than that in Xigu district. The sequence of mass concentrations of water-soluble ions was: SO₄²⁻ > NO₃⁻ > NH₄⁺ > Cl⁻ > K⁺ > Na⁺, while the mass concentrations of SO₄²⁻, NO₃⁻, NH₄⁺, which were the main ion components, exceeded 10 µg · m⁻³. The mass concentration of water- soluble ions during heating period was higher than that during non-heating period, meanwhile, the mass concentration in Xigu district was higher than that in Chengguan district. The result of enrichment factor (EF) analysis showed that the EF values of Al, Ca, Mg and Ti were lower than 1, indicating the contribution of natural source, while the EF values of Cu, Pb, S and Zn were higher than 10, indicating the contribution of anthropogenic pollution. The result of principal component analysis showed that the sources of PM₂.₅ were mainly derived from traffic emission, biomass burning, soil and secondary particles.
To investigate and evaluate the pollution levels of heavy metals in the soil around a large Municipal Solid Waste Incineration power plant (MSWIPP), a total of 29 soil samples were collected around the MSWIPP and away from the power plant area. The contents of 10 selected heavy metals (Cr, Mn, Ni, Cu, Zn, As, Ag, Cd, Hg, and Pb) were analyzed. The results showed that the content of each heavy metal element did not exceed the values for Soil Environmental Quality of Risk Control Standard for Soil Contamination of Agricultural Land (GB15618-2018) and Development Land (GB 36600-2018). The mean contents of Mn, Cu, and As were higher than their respective background values of Anhui Province, where As was 1.03 times the background value, and Cu was 1.07 times. Compared with the control points, the contents of Cr, Ni, Cd, Cu, and As were lower than the control points, and the difference was statistically significant ( ≤ 0.05). The spatial distribution of Hg was more obvious in the soil around the power plant, and other heavy metals were not obvious and uniform. The content of Hg was the highest in the 500 m soil of perennial dominant downwind and sub-dominant downwind. With increasing distance from the power plant, the content gradually decreased and it was lower than the level of the control point. The pollution degree of heavy metal elements in the soil around the power plant and in the plant area was mild. The Nemero comprehensive pollution index (PI) was 1.1-1.2, and the control point had also mild pollution (PI was 1.5). The potential ecological risk was slight, and the comprehensive potential ecological risk index (RI) of various heavy metal elements was 60.2-67.7. The contribution rate of Hg and As to RI were large, and the control point had medium ecological risk (RI was 116.8). Based on the results of principal component analysis, accompanied with the content, spatial distribution characteristics, Pearson's correlation, and hierarchical cluster analysis results, three groups of heavy metals with different spatial distribution were identified:①Ni, Cr, As, and Mn originated from lithological sources; ②Cu, Zn, Ag, Cd, and Pb affected by both lithological and human sources (e.g. agricultural and traffic sources); ③Hg likely originated from the diffusion sedimentation of MSWI flue gas and its accumulation in the soil. The above results indicated that the unique pollution characteristics of Hg deserve serious attention in pollution monitoring in soils surrounding solid waste incinerator.
A total of 234 surface soil samples (0-20 cm) were collected at the nodes of a 2×2 km grid from Gaoqing County (a typical area surrounding the Lower Yellow River) and analyzed for eight heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn). This study investigated the source of the heavy metals in this area based on a correlation analysis, PCA, and ANOVA using multivariate statistical analysis. In addition, the spatial variation and distribution characteristics of the heavy metals were determined by geostatistics based on GIS. The results provided the following conclusions. ① The mean concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn exceeded the background values (BV) of the Lower Yellow River, especially for As, Cu, and Hg (1.23, 1.20 and 1.29 times the BV, respectively), indicating that there was enrichment of the heavy metals in soils at different degrees. ② The results from the multivariate analysis suggested that all eight heavy metals could be classified by two principal components (PCs). The levels of As, Cd, Cr, Cu, Ni, Pb, and Zn were dominated by human activities and the parent soil material (PC1). However, Hg originated mainly from textile printing, petrochemical engineering, and plastic processing (PC2). ③ The differences in heavy metal contents between different land use types and parent soil materials were obvious. The eight elements were highest in land related to urban construction. In addition to Hg, the remaining seven heavy metals were highest in soils in the lacustrine deposit. ④ The spatial distributions of the heavy metals in the soil were different. The high value areas of As, Cd, Cr, Cu, Ni, Pb, and Zn were mainly concentrated in the central urban and southeastern areas, while the high value areas for Hg were concentrated in the southwestern and northeastern areas. This showed that industrial emissions and agricultural production activities caused the degree of heavy metal pollution in the soils while traffic emissions aggravated the levels.
Four typical estuaries located in the Ruxi River, a tributary of the Yangtze River, were selected to investigate the possibility of mercury pollution in tributary estuaries from the Three Gorges reservoir water storage. Water samples were collected during the water storage period (September to October), the flooding period (November to December), the water withdrawal period (February to March), and the drying period (May to June) to determine the levels of mercury species including total mercury (THg), particulate mercury (PHg), dissolved mercury (DHg), reactive mercury (RHg), total methylmercury (TMeHg) and dissolved methylmercury (DMeHg). The results showed that the concentration of THg and TMeHg in the estuary of the Ruxi River was comparable with that of other reservoirs or natural waters in China. There was a significant difference in the concentration of DHg and TMeHg in the water at different depths, because DHg and TMeHg might be derived from the release of sediment to the overlying water. Comparing the concentrations of different mercury species in the four estuaries during the same period, it was found that the difference of water flow direction during the water storage period could lead to an uneven concentration distribution of THg and PHg in the estuary areas. During the water withdrawal period, the particles in the estuary water could adsorb and carry a large amount of PHg, resulting in higher THg concentration in the water in comparison with other periods. The concentration of TMeHg in the flooding and the drying periods was higher than in the other two periods, indicating that the stable water level might be conducive to the accumulation of methylmercury in the water, and the severe disturbance of the water level could significantly reduce the concentration of TMeHg in the water.
Microplastics and antibiotic resistance genes (ARGs) are emerging pollutants/contaminants, and are also the research hotspots concerning environmental health in the past few years. To explore the effects of microplastics on ARGs in estuarine sediment, three different microplastics were added to microcosm incubation experiments of sediments. Then, we investigated the persistence, abundance, diversity, and shifts of the ARGs in estuarine sediments by high-throughput quantitative polymerase chain reaction (PCR). The results showed that the microplastics significantly changed the structure of ARGs in the sediments. PVC and PE, which are hard to degrade, had significant effects on the structures and types of ARGs. However, the PVA, which is soluble, reduced the types and persistence of ARGs significantly. The abundance of ARGs in S_PVC, S_PE, and S_PVA were 4.1×10 , 8.1×10 , and 2.0×10 copies·g , respectively. The abundance of ARGs in sediments with added PE almost increased by one order of magnitude, implying that microplastics could significantly increase the abundance of ARGs in sediments. Furthermore, OLS regression analysis showed that ARGs are significantly correlated with transposon and integron, suggesting that mobile genetic elements (MGEs) may promote the transfer and dissemination of ARGs.
Excessive reclamation leads to rapid degradation of wetland ecosystems. Microbial changes in wetland soils under the influence of human activities can sensitively indicate degradation of soil quality and ecosystem functions. To study the effects of different land use patterns on microbial community structure of wetlands, the Sanjiang Wetland Protected Area of Fuyuan, Heilongjiang Province, was selected as the research area. Soil samples were collected from replanting legume crop area, rice wetland, and primitive peat wetland. Then, the bacterial community structure in the soil was investigated with high-throughput sequencing based on the 16S rRNA gene. The relationship between bacterial community and environmental factors was further explored. The results indicated that, based on the bacterial phylum, there are no significant differences between the microbial community structures of soils under different land use patterns. Nevertheless, at the genus level, higher abundance of , , and were detected in the legume rhizospheric soil. In the paddy soil, the relative abundances of , , and are higher, while in the peatand soil, the higher contents are of , , and . The results of Chao1 and Shannon index indicate that the microbial diversity of the paddy soil was higher than in the legume rhizospheric soil and peatland soils. However, no significant differences on bacterial diversity between the legume rhizospheric soil and peatland soils were observed. The results of the correlation analysis indicate that soil reclamation triggers a shift in microbial community mainly because of its influence on soil pH, moisture, and nutrients.
To evaluate the remediation potential of L. on cadmium (Cd) contaminated farmland soil, the Cd-containing plants and root were collected and analyzed by field investigation, original pot experiment, and field experiment. The enrichment factor and removal rate of L. was calculated. The results showed that the maximum Cd content in the leaves of s L. growing in soil of different lead-zinc mines was 77.01 mg·kg . In the high-concentration Cd soil treatment (T2), Cd content of the above-ground of L. was 69.71mg·kg , and Cd enrichment coefficient was 6.09. In the low-concentration Cd soil treatment (T1), the enrichment characteristics of Cd ( L.) are consistent with the enrichment characteristics of Cd under high concentration conditions. L. exhibits stable accumulation characteristics for Cd. In the field experiment, the average Cd content of L. was 21.13 mg·kg , and the enrichment coefficient was 6.93. The removal rate of the three planting L. per mu of soil using the L. to repair Cd contaminated soil was 13.2%-15.6%. The use of L. to repair Cd pollution in farmland has a good prospect for engineering application.
The allelopathic effects of on algal growth were investigated and potential allelochemicals secreted by were analyzed. were co-cultivated with different initial concentrations (10 , 10 , 10 , 10 , and 10 ind.·L ) of and . The optical density of each group was measured daily. The results showed that 2.5 g·(200 mL) of has significant inhibition effect on growth with initial concentrations of 10 ind.·L and 10 ind.·L . However, there was no significant inhibition on the growth of . Through solvent extraction and GC-MS analysis, hexadecanoic acid was extracted and determined as an allelochemical in . Additionally, three potentially novel allelochemical compounds secreted by were determined as follows:3-ethyl-3-methylheptane, triethyl phosphate and dibutyl phthalate.
Five surface sediment samples were collected every two months from the Shiwuli River along an urban-rural gradient, Chaohu Lake Basin, from July 2017 to May 2018. Sediment phosphorus fractions were investigated, and equilibrium phosphate concentration (EPC ) and its response to exogenous carbon (sodium acetate) addition were explored. Moreover, the risk of phosphorus release from sediment into water column was also evaluated. Results show that the Shiwuli River was seriously polluted by phosphorus. The average values of total phosphorus content in sediments ranged from 915.04 to 1205.31 mg·kg , and it decreased slowly along the urban-rural gradient, while the bio-available phosphorus content remained stable. Exogenous carbon addition not only reduced the EPC values of sediments (about 29%), but changed the order of EPC values among the five sampling sites as well. In general, the ratio of overlying water SRP (soluble reactive phosphorus) concentration to EPC value was 66.7%, and phosphorus adsorption-desorption equilibrium saturation EPC <-20% accounted for about 60.0%, indicating that the surface sediments in the Shiwuli River were dominated by phosphorus adsorption, namely, keeping the phosphorus "sink" state. The inputs of exogenous carbon addition increased the proportion of EPC <-20% from 60.0% to 73.3%, which lowered the risk of phosphorus release from sediments.
To analyze the characteristic of marine emission in Shenzhen City, activity-based and fuel-based approaches were utilized to develop the marine emission inventory for the year of 2010, using the vessel files from the Lloyd's register of shipping (LR) and vessel track data from the automatic identification system (AIS). The marine emission inventory was temporally (resolution: 1 hour) and spatially (resolution: 1 km x 1 km) allocated based on the vessel track data. Results showed that total emissions of SO2, NO(x), CO, PM10, PM2.5 and VOCs from marine vessels in Shenzhen City were about 13.6 x 10(3), 23.3 x 10(3), 2.2 x 10(3), 1.9 x 10(3), 1.7 x 10(3) and 1. x 10(3) t, respectively. Among various types of marine vessels, emission from container vessels was the highest; for different driving modes, hotelling mode was found with the largest mission. Marine emissions were generally higher in the daytime, with vessel-specific peaks. For spatial distributions, in general, marine emissions were zonally distributed with hot spots in the western port group, Dapeng Bay and the key waterway.