Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 20.718
Filtrar
1.
Ying Yong Sheng Tai Xue Bao ; 31(2): 399-406, 2020 Feb.
Artigo em Chinês | MEDLINE | ID: mdl-32476331

RESUMO

Understanding the changes and driving factors of forest fire can provide scientific basis for prevention and management of forest fire. In this study, we analyzed the changes and driving factors of forest fire in Zhejiang Province during 2001-2016 based on trend analysis and Logistic regression model with the MODIS satellite fire point data combined with meteorological (daily ave-rage wind speed, daily average temperature, daily relative humidity, daily temperature difference, daily cumulative precipitation), human activities (distance from road, distance from railway, distance from resident, population, per capita GDP), topographic and vegetation factors (elevation, slope, vegetation coverage). The results showed that the number of forest fires in spring and summer had significantly increased, while the forest fires in the autumn and winter increased first and then decreased. Forest fire in autumn significantly declined. The four seasons' fire occurrence prediction models had good prediction accuracy, reaching 75.8% (spring), 79.1% (summer), 74.7% (autumn) and 79.6% (winter). The meteorological, human activity, topographic and vegetation factors significantly affected fire occurrence in spring and summer, while meteorological factors were the main fire drivers in autumn and winter in Zhejiang. The focus of forest fire management should be on human activities. Fire prevention campaign should be done in spring and summer when high-risk forest fires were scattered in the study area. In autumn and winter, observatory and monitoring equipment could be built to facilitate fire management and detect in the area of high fire risk that was concentrated in the southwest region.


Assuntos
Fogo , Incêndios Florestais , China , Clima , Humanos , Estações do Ano
2.
Ying Yong Sheng Tai Xue Bao ; 31(2): 533-542, 2020 Feb.
Artigo em Chinês | MEDLINE | ID: mdl-32476347

RESUMO

The Wuyi Mountain National Nature Reserve (WYS), established in 1979, is the largest and most intact subtropical forest ecosystem in southeastern China. No study has assessed the vegetation coverage change along with its ecological effect after the protection of the reserve for almost 40 years. In this study, the NDVI data of Landsat Image was corrected using the NDVI data of MODIS, the fractional vegetation cover (FVC) and the remote sensing based ecological index (RSEI) were calculated to assess the change of FVC and ecological quality in WYS with five Landsat images representing a period from 1979 to 2017. The results showed that after protection for nearly 40 years the FVC of the reserve had been significantly increased from 73.6% in 1979 to 89.5% in 2017, which consequently improved ecological quality from 0.801 in 1988 to 0.823 in 2017. In 2017, the area with the good and excellent ecological quality grades accounted for 98.7% of the total. Spatially, the ecologically-improved areas mainly distributed in the northeast core area and the center of the southwest core area. The ecologically-declined areas mostly occurred along roadsides and peaks. Vertically, the highest FVC and ecological quality areas distributed in the elevations between 1300-1900 m. In general, the improvement of FVC and ecological quality in the Wuyi Mountain National Nature Reserve was due largely to the effective policies and the successful protection by local government and people, except for some special year that may be affected mainly by climate conditions.


Assuntos
Ecossistema , Tecnologia de Sensoriamento Remoto , China , Clima , Monitoramento Ambiental
3.
Ying Yong Sheng Tai Xue Bao ; 31(2): 674-684, 2020 Feb.
Artigo em Chinês | MEDLINE | ID: mdl-32476363

RESUMO

Affected by the unique geographical environment and climate, the hydrological cycle and the underlying mechanisms of the occurrence, migration, and transformation of non-point source pollution are more complicated in semi-arid and semi-humid watersheds. Non-point source pollution models are effective means for quantitatively describing the complex hydrological cycle and the process of pollutants migration and transformation, and thus served as important tools for watershed ecosystem management. Based on the unique climate, hydrological characteristics, and underlying surface conditions in semi-arid and semi-humid areas, we elaborated on the occurrence mechanism of non-point source pollution, and summarized the status, progress, and shortage of the research and application of solving water environmental problems by using non-point source pollution models. Moreover, the scheme for constructing non-point source pollution models applied to semi-arid and semi-humid areas was put forward. Finally, we discussed the development trend of non-point source pollution models.


Assuntos
Poluição Difusa , China , Clima , Ecossistema , Monitoramento Ambiental , Hidrologia
4.
Sci Total Environ ; 736: 139487, 2020 Sep 20.
Artigo em Inglês | MEDLINE | ID: mdl-32479958

RESUMO

It is essential to know the environmental parameters within which the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can survive to understand its global dispersal pattern. We found that 60.0% of the confirmed cases of coronavirus disease 2019 (COVID-19) occurred in places where the air temperature ranged from 5 °C to 15 °C, with a peak in cases at 11.54 °C. Moreover, approximately 73.8% of the confirmed cases were concentrated in regions with absolute humidity of 3 g/m3 to 10 g/m3. SARS-CoV-2 appears to be spreading toward higher latitudes. Our findings suggest that there is an optimal climatic zone in which the concentration of SARS-CoV-2 markedly increases in the ambient environment (including the surfaces of objects). These results strongly imply that the COVID-19 pandemic may spread cyclically and outbreaks may recur in large cities in the mid-latitudes in autumn 2020.


Assuntos
Clima , Infecções por Coronavirus/transmissão , Pneumonia Viral/transmissão , Temperatura , Betacoronavirus , Cidades , Humanos , Pandemias
5.
J Environ Manage ; 268: 110709, 2020 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-32510443

RESUMO

Model evaluation is a critical component in the development and applications of environmental modeling systems. Conventional metrics such as Pearson product-moment correlation coefficient (r), root-mean-square error (RMSE), and mean absolute error (MAE), albeit process-based and limited to point-to-point statistical comparison, have been widely used in model evaluations. In this study, we propose a network-based toolkit for evaluation of model performance and multi-model comparisons with applications to weather prediction and climate modeling. The model outputs are topologically quantified through a range of network metrics to provide a holistic measure of system dynamics. We first use this toolkit to evaluate the performance of air temperature simulated by the Weather Research and Forecasting model with station measurements over the contiguous United States (CONUS). Results of network analysis suggest a good match between simulation and measurement, as indicated by conventional metrics (r, RMSE, and MAE) as well. The sensitivity of these network metrics is then analyzed based on CONUS station measurements with additive random errors using Monte Carlo simulations. Network metrics show more sensitive and highly nonlinear responses to increasing random errors as compared to conventional ones. Moreover, we use the new toolkit for intercomparison of the downscaled historical air temperature outputs from four global climate models. The similarity in both metrics and spatial structure highlights the capability of network analysis for capturing system dynamics in models alike. The network theory is therefore promising for evaluation and intercomparison of various environmental modeling systems with complex dynamics.


Assuntos
Clima , Tempo (Meteorologia) , Previsões , Temperatura
6.
J Environ Manage ; 268: 110732, 2020 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-32510452

RESUMO

Evaluation of energy performance of a proposed lightweight concrete, a structural component, in a building application is a novel approach and significant attempt for the future of energy-efficient buildings. Buildings are one of the largest energy consumers in the world. Thermal protection in a building is the most effective way for energy saving. Many stimulatory measures for the spreading of energy savings technologies have been recently applied into the building sectors. In this study, an investigation was carried out based upon an experimental investigation to decide the thermal properties of the lightweight concrete with different ratios of vermiculite. Moreover, analytical simulation to evaluate the energy consumption in a real building application was carried out for various fuels and different climate regions of Turkey. The results show that the most significant reduction in the total heat need occurs in the 4th region, with about 5.6 kWh/m2-year for a thickness of 0.2 m. An energy-saving of 7.5% can be achieved in the 1st region. The proposed concrete can provide a significant reduction in energy consumption and can reduce the carbon emission related to the lower energy need of the buildings. The annual saving can increase to 0.61 $/m2 for LPG in the 4th region. The payback period varies between 1.4 years and 9 years, depending on the fuel. Many OECD countries having a high population pay higher prices for electricity and natural gas compared to Turkey. It means that such an energy-efficient material can save more price due to their higher fuel cost.


Assuntos
Clima , Eletricidade , Condutividade Térmica , Turquia
7.
Ying Yong Sheng Tai Xue Bao ; 31(4): 1250-1258, 2020 Apr.
Artigo em Chinês | MEDLINE | ID: mdl-32530200

RESUMO

Taiwan green jujube (Ziziphus mauritiana) is a new fruit variety, with remarkable economic benefit. To achieve high quality and high yield of jujube in Fujian Province, we quantified the climate suitability model parameters of the jujube in main production areas of Fujian, and analyzed climate suitability characteristics and change trend of main production areas, based on the yield and meteorological data, combined with literature and phenological observation data and agricultural climate suitability model. The results showed that the model based on the equal weight summation method had the highest reliability. The climate suitability of jujube in main production areas of Fujian was higher, with most years being suitable or much suitable. From 1996 to 2013, the influence of climate conditions on jujube growth was generally in a good trend, which was conducive to the development of jujube production. The suitability of the main production areas in the whole growing season was ranked as temperature suitability>comprehensive climate suitability>sunshine suitability>precipitation suitability. September and October are the key period of water management. Our results are important in guiding production management and long-term planning of Taiwan green jujube in Fujian Province.


Assuntos
Ziziphus , China , Clima , Reprodutibilidade dos Testes , Taiwan
8.
Ying Yong Sheng Tai Xue Bao ; 31(5): 1735-1745, 2020 May.
Artigo em Chinês | MEDLINE | ID: mdl-32530253

RESUMO

The bay is the most susceptible area in the marine to human interference. It is of significance for maintaining ecological security of the bay to build an assessment framework of losses of bay ecosystem services caused by the C9 leakage event and evaluate it quantitatively. This study used market value, alternative cost, carbon tax and emergy analysis methods to construct a monetary value evaluation model for the lossses of key ecosystem services (food production, gas regulation, climate regulation, waste treatment, human health, nutrient cycling, species diversity maintenance, and recreation entertainment) caused by C9 leakage accident, and analyzed the losses of x-Bay ecosystem services. The results showed that total value of the losses of ecosystem services caused by C9 spill was 1.93×108 yuan, and the monetary value of loss per unit area was 1.19×108 yuan·km-2, which was more than 2800 times of the general marine oil spill events. Among all the components, the loss of food production services accounted for 77.1% of the total, being much higher than the impact of the general marine oil spills on human production and life. Our results could provide references to the assessment of ecosystem services loss caused by toxic substances like C9, and to the government decision-making and national territory spatial planning.


Assuntos
Ecologia , Ecossistema , Baías , Clima , Conservação dos Recursos Naturais
9.
J Environ Manage ; 267: 110648, 2020 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-32421678

RESUMO

The Amery ice shelf (AIS) dynamics and mass balance play key role to decipher changes in the global climate scenario. The spatio-temporal changes in morphology of the AIS were studied into a number of transects at 5 km uniform intervals using multi-dated Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite data (2001-2016) of the austral summer months (January-March). Past ice shelf extents have been reconstructed and future ice shelf extents were estimated for 5- and 10-year time periods. The rate changes of AIS extent were estimated using the linear regression analysis and cross-validated with the coefficient of determination (R2) and root-mean-square error (RMSE) methods. Further, the changes in shelf extent were linked to prevailing factors viz. mass changes, Southern Annular Mode (SAM) index, and ocean-air temperatures. The study reveals that the AIS extent has been prograded at the rate of 994 m/year with an average 14.5 km increase in the areal extents during 2001-2016, as compared to the year 2001, whereas, the maximum advancement in ice shelf extent was recorded during the 2006-2016 period. Based on the linear regression analysis, the predicted ice shelf extents (i.e., the summer 2021 and 2016) show progradation in all the transects. About 52% of transects exhibit ±200 m RMSE values, indicating better agreement between the estimated and satellite-based ice-shelf position. The recent changes (2017-2019) observed in the ice shelf are cross validated with predicted ice self-extent rates. The eastern part of Mackenzie Bay to Ingrid Christensen coast recorded advancement in the ice shelf extents and mass which is the feedback of positive SAM along with a decrease in the temperatures (air temperature and sea surface temperature). The present study demonstrates that the combined use of satellite imagery and statistical techniques can be useful in quantifying and predicting ice shelf morphological variability.


Assuntos
Camada de Gelo , Água do Mar , Regiões Antárticas , Clima , Tecnologia de Sensoriamento Remoto
11.
Environ Monit Assess ; 192(6): 368, 2020 May 15.
Artigo em Inglês | MEDLINE | ID: mdl-32415400

RESUMO

Located in the eastern lap of the Karakoram Range, the Siachen Glacier is the second longest glacier in the non-polar areas of the world. High altitude, extreme climate and frequent military conflicts on this glacier create antagonistic surroundings for conventional field studies. Although recent advancements in geodetic technique have helped in the estimation of Siachen mass budget (MB), these geodetic estimates have been observed only for short time periods ranging 6 to 10 years. Hence, current study presents a comprehensive assessment of the Siachen long-term MB (32 years) based on temperature index (TI) model. Annual surface MB variability was modelled between 1986 and 2018 by forcing daily air temperature and precipitation from multiple ground stations distributed well across accumulation/ablation zone of the glacier. Mean annual temperature lapse rate (LR) was found midway between dry adiabatic and moist adiabatic LRs. Precipitation gradient (PG) was observed remarkably different below and above 4800 m.a.s.l. glacier altitude. Furthermore, snowmelt factor (SMF) was also estimated using snow thickness and positive degree days (PDDs) information over the glacier surface. Model results showed a nearly balanced condition (- 0.02 ± 0.05 m.w.e./year) during 1986-2006 followed by an accelerated rate of mass loss during 2007-2018 (- 0.11 ± 0.05 m.w.e./year), thus making the overall condition of Siachen MB negative during the period 1986-2018 (- 0.05 ± 0.05 m.w.e./year). Comparison of modelled MB was made with few geodetic studies conducted for the Siachen Glacier at different time scales (mainly after year 2000). Further, the sensitivity of the modelled glacier-wide MB was - 0.24 m.w.e./year for a temperature rise by 1 °C, while the sensitivity towards 10% increase in precipitation was estimated to be + 0.16 m.w.e./year. A relationship of the annual MB with accumulation area ratio (AAR) and equilibrium line altitude (ELA) was also established for Siachen glacier.


Assuntos
Monitoramento Ambiental , Camada de Gelo , Modelos Teóricos , Altitude , Clima , Neve
12.
Sci Total Environ ; 735: 139560, 2020 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-32464409

RESUMO

Due to the close relationship between the incidence of infectious diseases by epidemics and environmental conditions, this research explores the temperature, evaporation, precipitation and regional climate effects on the local transmission of coronavirus SARS-CoV-2 inside 31 states and capital of Mexico since February 29 (national onset) to March 31, 2020. Statistical analysis was conducted to explore the association between the daily local COVID-19 confirmed positive cases (LCPC) and both climate characteristics and the daily weather reported by the regional meteorological stations. In this work, the local transmission ratio (LTR) was calculated with the regional LCPC divided by the number of the effective contagion days since regional onset in each state. The results showed a negative association between temperature (mean, max and min) and climate classification with both LCPC and LTR variables. The precipitation associated positively with LCPC and LTR. The associations between the climate classification with LCPC and LTR are statistically significant. The tropical climate (mean temperature around 25.95 °C and mean precipitation around 8.74 mm) delayed the regional onset. However, the regional onset in dry climates emerged earlier as consequence of the lower temperatures and higher precipitations (20.57 °C and 20.87 mm respectively) than the observed in the tropical climate. The fastest regional onsets were observed in tempered climates in states where the lowest temperatures and lowest precipitations were registered (19.65 °C and 8.48 mm respectively). Meteorological factors influenced the trend on the regional outbreaks in Mexican's states likely by the host predisposition and susceptibility during the cold winter season. In Mexico, the climate characteristics played a crucial role on the local infection during the phase 1 being the tempered regions (as Michoacán, Jalisco, Puebla, etc.) more vulnerable than the dry (as Chihuahua, Durango or Zacatecas, etc.) or tropical areas (as Colima, Campeche, Morelos etc.).


Assuntos
Clima , Infecções por Coronavirus/transmissão , Pneumonia Viral/transmissão , Estações do Ano , Temperatura , Betacoronavirus , Humanos , México/epidemiologia , Pandemias
13.
Sci Total Environ ; 729: 138997, 2020 Aug 10.
Artigo em Inglês | MEDLINE | ID: mdl-32353724

RESUMO

In this study, we aimed at analyzing the associations between transmission of and deaths caused by SARS-CoV-2 and meteorological variables, such as average temperature, minimum temperature, maximum temperature, and precipitation. Two outcome measures were considered, with the first aiming to study SARS-CoV-2 infections and the second aiming to study COVID-19 mortality. Daily data as well as data on SARS-CoV-2 infections and COVID-19 mortality obtained between December 1, 2019 and March 28, 2020 were collected from weather stations around the world. The country's population density and time of exposure to the disease were used as control variables. Finally, a month dummy variable was added. Daily data by country were analyzed using the panel data model. An increase in the average daily temperature by one degree Fahrenheit reduced the number of cases by approximately 6.4 cases/day. There was a negative correlation between the average temperature per country and the number of cases of SARS-CoV-2 infections. This association remained strong even with the incorporation of additional variables and controls (maximum temperature, average temperature, minimum temperature, and precipitation) and fixed country effects. There was a positive correlation between precipitation and SARS-CoV-2 transmission. Countries with higher rainfall measurements showed an increase in disease transmission. For each average inch/day, there was an increase of 56.01 cases/day. COVID-19 mortality showed no significant association with temperature.


Assuntos
Betacoronavirus , Infecções por Coronavirus , Pandemias , Pneumonia Viral , Clima , Humanos
14.
Artigo em Inglês | MEDLINE | ID: mdl-32429517

RESUMO

This paper investigates whether the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) pandemic could have been favored by specific weather conditions and other factors. It is found that the 2020 winter weather in the region of Wuhan (Hubei, Central China)-where the virus first broke out in December and spread widely from January to February 2020-was strikingly similar to that of the Northern Italian provinces of Milan, Brescia and Bergamo, where the pandemic broke out from February to March. The statistical analysis was extended to cover the United States of America, which overtook Italy and China as the country with the highest number of confirmed COronaVIrus Disease 19 (COVID-19) cases, and then to the entire world. The found correlation patterns suggest that the COVID-19 lethality significantly worsens (4 times on average) under weather temperatures between 4 ∘ C and 12 ∘ C and relative humidity between 60% and 80%. Possible co-factors such as median population age and air pollution were also investigated suggesting an important influence of the former but not of the latter, at least, on a synoptic scale. Based on these results, specific isotherm world maps were generated to locate, month by month, the world regions that share similar temperature ranges. From February to March, the 4-12 ∘ C isotherm zone extended mostly from Central China toward Iran, Turkey, West-Mediterranean Europe (Italy, Spain and France) up to the United State of America, optimally coinciding with the geographic regions most affected by the pandemic from February to March. It is predicted that in the spring, as the weather gets warm, the pandemic will likely worsen in northern regions (United Kingdom, Germany, East Europe, Russia and North America) while the situation will likely improve in the southern regions (Italy and Spain). However, in autumn, the pandemic could come back and affect the same regions again. The Tropical Zone and the entire Southern Hemisphere, but in restricted colder southern regions, could avoid a strong pandemic because of the sufficiently warm weather during the entire year and because of the lower median age of their population. Google-Earth-Pro interactive-maps covering the entire world are provided as supplementary files.


Assuntos
Clima , Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Estações do Ano , Fatores Etários , Betacoronavirus , Infecções por Coronavirus/mortalidade , Humanos , Pandemias , Pneumonia Viral/mortalidade
15.
Artigo em Inglês | MEDLINE | ID: mdl-32466199

RESUMO

Nowadays, an infectious disease outbreak is considered one of the most destructive effects in the sustainable development process. The outbreak of new coronavirus (COVID-19) as an infectious disease showed that it has undesirable social, environmental, and economic impacts, and leads to serious challenges and threats. Additionally, investigating the prioritization parameters is of vital importance to reducing the negative impacts of this global crisis. Hence, the main aim of this study is to prioritize and analyze the role of certain environmental parameters. For this purpose, four cities in Italy were selected as a case study and some notable climate parameters-such as daily average temperature, relative humidity, wind speed-and an urban parameter, population density, were considered as input data set, with confirmed cases of COVID-19 being the output dataset. In this paper, two artificial intelligence techniques, including an artificial neural network (ANN) based on particle swarm optimization (PSO) algorithm and differential evolution (DE) algorithm, were used for prioritizing climate and urban parameters. The analysis is based on the feature selection process and then the obtained results from the proposed models compared to select the best one. Finally, the difference in cost function was about 0.0001 between the performances of the two models, hence, the two methods were not different in cost function, however, ANN-PSO was found to be better, because it reached to the desired precision level in lesser iterations than ANN-DE. In addition, the priority of two variables, urban parameter, and relative humidity, were the highest to predict the confirmed cases of COVID-19.


Assuntos
Inteligência Artificial , Betacoronavirus , Clima , Infecções por Coronavirus , Pandemias , Pneumonia Viral , Algoritmos , Cidades , Infecções por Coronavirus/diagnóstico , Humanos , Itália , Redes Neurais de Computação , Pneumonia Viral/diagnóstico , Temperatura , Vento
16.
CMAJ ; 192(21): E566-E573, 2020 05 25.
Artigo em Inglês | MEDLINE | ID: mdl-32385067

RESUMO

BACKGROUND: It is unclear whether seasonal changes, school closures or other public health interventions will result in a slowdown of the current coronavirus disease 2019 (COVID-19) pandemic. We aimed to determine whether epidemic growth is globally associated with climate or public health interventions intended to reduce transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We performed a prospective cohort study of all 144 geopolitical areas worldwide (375 609 cases) with at least 10 COVID-19 cases and local transmission by Mar. 20, 2020, excluding China, South Korea, Iran and Italy. Using weighted random-effects regression, we determined the association between epidemic growth (expressed as ratios of rate ratios [RRR] comparing cumulative counts of COVID-19 cases on Mar. 27, 2020, with cumulative counts on Mar. 20, 2020) and latitude, temperature, humidity, school closures, restrictions of mass gatherings, and measures of social distancing during an exposure period 14 days previously (Mar. 7 to 13, 2020). RESULTS: In univariate analyses, there were no associations of epidemic growth with latitude and temperature, but weak negative associations with relative humidity (RRR per 10% 0.91, 95% confidence interval [CI] 0.85-0.96) and absolute humidity (RRR per 5 g/m3 0.92, 95% CI 0.85-0.99). Strong associations were found for restrictions of mass gatherings (RRR 0.65, 95% CI 0.53-0.79), school closures (RRR 0.63, 95% CI 0.52-0.78) and measures of social distancing (RRR 0.62, 95% CI 0.45-0.85). In a multivariable model, there was a strong association with the number of implemented public health interventions (p for trend = 0.001), whereas the association with absolute humidity was no longer significant. INTERPRETATION: Epidemic growth of COVID-19 was not associated with latitude and temperature, but may be associated weakly with relative or absolute humidity. Conversely, public health interventions were strongly associated with reduced epidemic growth.


Assuntos
Clima , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/prevenção & controle , Pandemias/prevenção & controle , Pneumonia Viral/epidemiologia , Pneumonia Viral/prevenção & controle , Saúde Pública/métodos , Estudos de Coortes , Saúde Global , Humanos , Estudos Prospectivos
17.
Chemosphere ; 254: 126846, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32361542

RESUMO

The Water Sediment Regulation Scheme (WSRS) is a unique engineering measure that has been regularly performed to reduce reservoir sedimentation and increase the flood capacity of the Yellow River in China since 2002. As a side effect, the WSRS greatly increases the monthly input flux of nutrients to the Bohai Sea (BHS) in summer, potentially exacerbating eutrophication levels therein and subsequently affecting the growth of phytoplankton. However, its influence on the Chlorophyll-a (Chl-a) dynamics over the BHS is still poorly understood. In this study, two approaches were adopted to investigate it: 1) long-term in-situ observations and satellite-derived data of surface Chl-a were used to study its seasonal variations before and since 2002, and 2) one 1D physical-biological coupled model was developed to evaluate the impact of WSRS on seasonal Chl-a. The results showed that the surface Chl-a exhibited two peaks in spring and autumn until 2002, but has exhibited only one peak in spring-summer since 2002. Satellite-derived Chl-a concentrations in spring-summer since 2002 have increased by 56% compared to those until 2002. The simulated results showed that the change in Yellow River discharge induced by the WSRS has resulted in the appearance of high concentrations of Chl-a in summer over the Central Bohai Sea since 2002. The WSRS increased the ratio of added Chl-a owing to the riverine nutrients to total Chl-a by 19% compared to that until 2002. Overall, WSRS greatly affects the seasonal cycling of Chl-a in the Bohai Sea, and the side effect needs to be considered.


Assuntos
Clorofila A/análise , Monitoramento Ambiental , China , Clorofila/análogos & derivados , Clorofila/análise , Clima , Conservação dos Recursos Hídricos , Eutrofização , Fitoplâncton , Rios , Estações do Ano , Água , Poluição da Água/prevenção & controle
18.
Infez Med ; 28(2): 166-173, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32275258

RESUMO

The world has been thrown into pandemonium due to the recent Coronavirus Disease-19 (COVID-19) pandemic. Early available clinical data have indicated that geriatric persons cum those with comorbidity such as cardiovascular, metabolic and immunological disorders suffered severe form of COVID-19. All countries and territories of the world are currently exploring available strategies to control the pandemic with the hope to significantly minimize its morbidity and mortality rate. This present study critically reviewed available and latest research progress on the genetics and ecology of SARS-CoV-2, as well as the influence of climatic factors on the spread of COVID-19, and thus, discussed how these concepts could be harnessed for COVID-19 control and further scientific advancements in resolving the pandemic.


Assuntos
Betacoronavirus/patogenicidade , Infecções por Coronavirus/epidemiologia , Pandemias/prevenção & controle , Pneumonia Viral/epidemiologia , Betacoronavirus/genética , Betacoronavirus/imunologia , Clima , Infecções por Coronavirus/fisiopatologia , Infecções por Coronavirus/prevenção & controle , Infecções por Coronavirus/transmissão , Ecossistema , Microbiologia Ambiental , Humanos , Peptidil Dipeptidase A/metabolismo , Pneumonia Viral/fisiopatologia , Pneumonia Viral/prevenção & controle , Pneumonia Viral/transmissão , Receptor Tipo 2 de Angiotensina/metabolismo
19.
J Environ Manage ; 262: 110345, 2020 May 15.
Artigo em Inglês | MEDLINE | ID: mdl-32250820

RESUMO

With the introduction of its energy concept in 2010, the German government set ambitious targets for the country's energy and climate policy. According to this concept, greenhouse gas (GHG) emissions will have to be reduced by 80% by 2050, as compared to 1990 levels, and renewables will have to supply 80% of all electricity needs by the same year. Additionally, Germany has decided to phase out its nuclear energy by 2022. This study investigates the possible components to achieve these targets. The analysis is based on an hourly simulation model EnergyPlan. Three scenarios are developed to investigate the potential development of the German energy supply system until 2050. The results indicate renewable shares of 92% and 81% for scenarios B and A, respectively, by 2050 compared to 69% in the reference scenario. The proposed renewable energy system is even found to involve lower costs than today's energy system (i.e. total annual cost for scenario B is € 260 bn compared to € 293 bn in the reference scenario). The results show that a massive decarbonization of the German energy system until 2050 seems technically and economically feasible, if smart grid costs are disregarded and if this sustainable energy transformation is accompanied by political and genuine public willingness to actually achieve the set goals and take the necessary steps.


Assuntos
Carbono , Energia Renovável , Clima , Eletricidade , Alemanha
20.
Nature ; 580(7804): 456, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-32317800

Assuntos
Clima , Efeito Estufa
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA