RESUMO
Recently, the Hf2Cl4-type materials as functional materials have attracted broad interest because of their enormous potential in thermoelectric (TE) applications. However, relevant investigations are still scarce up to now. To explore the Hf2Cl4-type materials with excellent TE properties, we focus on the TE properties of Zr2Cl4monolayer and calculate the TE parameters based on first-principles calculations and Boltzmann transport equation. Although, as compared to some typical TE materials, it exhibits better heat transport and thus higher lattice thermal conductivity, the figure of merits (ZT) of both p-type and n-type Zr2Cl4reach an unexpectedly high value of 3.90 and 3.60, respectively, owing to the larger electrical conductivity and higher power factor. Additionally, owing to the prominent difference in electrical conductivity between thex- andy-direction, strong anisotropy inZTvalues is observed. Our study reveals that both n-type and p-type Zr2Cl4monolayers have the potential for future TE applications.
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It is crucial to investigate the distribution and origin of black carbon (BC) in the environment for evaluating human inputs and developing pollution control strategies. This study analyzed BC in coastal river sediments from Haizhou Bay, Eastern China. The concentrations (dry weight) of the BC, char, soot, and total organic carbon (TOC) in coastal river sediments flowing into Haizhou Bay were 0.11-4.68, 0.06-4.24, 0.04-0.70, and 0.15-2.29 mg/g, respectively. Char and soot accounted for 38.54-90.70% and 9.30-61.46% of BC, with an average of 68.95% and 31.05%, respectively. The results show that the spatial variation of char was markedly presented in river sediment (108.27%), followed by that of BC (89.25%), TOC (58.69%), and soot (55.85%). The BC was mainly distributed in the Shawang River and the Shiliang River, soot was distributed primarily in the Shawang River, and char was mainly distributed in the Shiliang River. This finding supports the presence of anthropogenic activity sources in coastal rivers. The grey correlation analysis results show that industrial and agricultural activities greatly influenced BC emissions, as the influence degree of four socio-economic variables on BC contamination decreased as follows: regional total production value, population density, total agricultural production value, and total industrial production value. The char/soot ratio, an index to discriminate the source of BC contamination in sediments, was found to range from 0.63 to 9.75 with an average of 2.75. The result indicates that BC in Haizhou Bay was contributed from mixed sources including transportation emissions, fossil fuel combustion, and biomass combustion. The study demonstrates that BC could be an effective indicator for the degree and spatial distribution of organic pollutants in coastal river sediments.
Assuntos
Rios , Fuligem , Humanos , Fuligem/análise , Baías , Monitoramento Ambiental/métodos , Carbono/análise , Sedimentos Geológicos/análise , ChinaRESUMO
The Haizhou Bay in eastern China, for a long time, is seriously polluted with heavy metals (HMs) due to intensive anthropic pressure. The river runoff is the dominant pathway of HM transport in the coastal region. However, the information on HM pollution in coastal rivers flowing into Haizhou Bay was still limited, and potential risks and possible sources raised by HMs in this area were neglected up to now. To fully understand the distribution and ecological risks of sediments in seven rivers along the bay, surface sediments were collected and seven HMs (Cr, Mn, Ni, Cu, Zn, Cd, and Pb) were investigated. The results showed that HM concentrations generally met the primary standard criteria of China (marine sediment quality), except for Cu and Zn. On the other hand, Zn and Cu tended to exhibit probable adverse biological effects in the Shawang River comparison with some sediment quality guidelines (SQGs). Moreover, the enrichment factor and geo-accumulation index demonstrated that there was no or slight contamination to be found for Cr, Mn, Ni, Cu, Zn, and Pb and moderate pollution for Cd. The contamination factor (Cfi), integrated contamination degree (CF), modified degree of contamination (mCd), and modified pollution index (MPI) revealed individual metal contamination in localized areas. In these river sediments, the potential ecological risk (RI) was low to moderate, except Cd posted a considerable ecological risk because of its high enrichment. Furthermore, the Shawang River and Linhong River were seriously polluted with HMs among seven rivers. These results provided a new direction for controlling HM pollution in Haizhou Bay which suggested substantial measures should be implemented to alleviate the potential risk of HMs, to these rivers sediments.
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Metais Pesados , Poluentes Químicos da Água , Baías , Cádmio , China , Monitoramento Ambiental/métodos , Sedimentos Geológicos , Chumbo , Metais Pesados/análise , Medição de Risco , Rios , Poluentes Químicos da Água/análiseRESUMO
Urban river runoff carrying various anthropogenic sources of heavy metals (HMs) is the most important input pathways for HM pollutions in the coastal region, apportioning sources of environmental pollutants is key to controlling coastal HM pollution. In the study, surface sediments were collected from seven urban rivers flowing through Lianyungang City and discharging into Haizhou Bay, Eastern China. The concentrations of HMs of the river sediments were, in mg/kg (mean value ± standard deviation): Mn (550 ± 227) > Zn (67 ± 61) > Cr (33 ± 12) > Ni (21 ± 8.5) > Cu (16 ± 7.6) > Pb (15 ± 5.6) > Cd (0.11 ± 0.06), which were slightly to moderately polluted. As important outlets for municipal and industrial sewages, the Shawang River and Linhong River were the most polluted. Based on the multivariate statistical analysis, HMs were attributed to anthropogenic source (industrial, domestic, and agricultural discharges) and natural source (soil parent materials and atmospheric deposition). Based on isotope source apportionment, Pb was mainly from natural source, exhausts of leaded gasoline vehicles, and coal combustion, with the mean contributions of 39.3%, 23.7%, and 37.0%, respectively, and Sr originated from natural source and anthropogenic source, with mean contributions of 31.8% and 68.2%, respectively. Pb-Sr isotopes illustrated that anthropogenic inputs were the dominant source for HMs in urban river sediments flowing into Haizhou Bay, and the isotope tracing results make up the discriminating deficiency of the multivariate statistical analysis.
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Metais Pesados , Poluentes Químicos da Água , Baías , China , Cidades , Monitoramento Ambiental , Sedimentos Geológicos , Isótopos , Chumbo , Metais Pesados/análise , Medição de Risco , Rios , Poluentes Químicos da Água/análiseRESUMO
Seven heavy metals (Cr, Mn, Co, Ni, Cu, Zn, Pb) were measured in surface sediments from the Lishui River watershed, an area with increased soil erosion in China. The mean concentrations of heavy metals were 61.20 mg/kg (Cr), 757.15 mg/kg (Mn), 9.39 mg/kg (Co), 25.31 mg/kg (Ni), 22.84 mg/kg (Cu), 91.66 mg/kg (Zn), and 40.19 mg/kg (Pb), respectively. The spatial distribution of heavy metals was site-specific, exhibiting a remarkably high level in the sampling stations with intense agricultural activities (Lixian) and industrial activities (Jinshi). Contamination indexes including contamination factor, pollution load index, nemerow multi-factor index, potential ecological risk index, and human health risk were used to assess the pollution degree of the river sediments. The results indicated the pollution degree of heavy metals decreased in the order of Mn>Pb>Zn>Cr>Cu>Ni>Co. Heavy metals resulted in non-pollution to moderate pollution, with low ecological risk and an acceptable carcinogenic risk caused by Cr and Ni for children and adults. Person's correlation analysis and principal component analysis, coupled with cluster analysis, revealed that the sediments from the Lishui River were mainly influenced by two sources. Cr, Co, Ni, and Cu were mainly derived from natural sources, while Mn, Zn, and Pb originated from agricultural and industrial activities, mining, and vehicular traffic.