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1.
Sci Total Environ ; 884: 163791, 2023 Aug 01.
Artículo en Inglés | MEDLINE | ID: mdl-37142033

RESUMEN

Global climate change and revegetation programs have significantly changed the ecological quality (EQ) in the Chinese mainland after 1999. Monitoring and assessing the changes in the regional EQ and analyzing their drivers are crucial for ensuring ecological restoration and rehabilitation. However, it is challenging to carry out a long-term and large-scale quantitative assessment of the EQ of a region based on traditional field investigations and experiment methods alone; notably, in previous studies, the effects of carbon and water cycles and human activities on the variations in EQ have not been studied comprehensively. Therefore, in addition to remote sensing data and principal component analysis, we used the remote sensing-based ecological index (RSEI), to assess the EQ changes in the Chinese mainland during 2000-2021. Additionally, we also analyzed the impacts of carbon and water cycles and anthropological activities on the changes in the RSEI. The main conclusions of this study were: since the beginning of the 21st century, we observed a fluctuating upward trend in the EQ changes in the Chinese mainland and eight climatic regions. From 2000 to 2021, in terms of the EQ, North China (NN) portrayed the highest increase rate (2.02 × 10-3 year-1, P < 0.05). There was a breaking point in 2011, the EQ in the region experienced a change, from a downward trend to an upward one. Northwest China, Northeast China, and NN portrayed an overall significant increasing trend in the RSEI, whereas the southwest part of the Southwest Yungui Plateau (YG) and a part of the plain region of the Changjiang (Yangtze) River (CJ) river region portrayed a significant decreasing trend in the EQ. Overall, the carbon and water cycles and human activities played a pivotal role in determining the spatial patterns and trends of the EQ in the Chinese mainland. In particular, the self-calibrating Palmer Drought Severity Index, actual evapotranspiration (AET), gross primary productivity (GPP), and soil water content (Soil_w) were identified as the key drivers of the RSEI. In the central and western Qinghai-Tibetan Plateau (QZ) and the northwest region of NW, the changes in RSEI were dominated by AET; however, in central NN, southeastern QZ, northern YG, and central NE, the changes were driven by GPP, and in the southeast region of NW, south region of NE, northern region of NN, middle YG region, and a part of the middle CJ region, the changes were driven by Soil_w. The population-density-related change in the RSEI was positive in the northern regions (NN and NW) but negative in the southern regions (SE), whereas the RSEI change related to ecosystem services was positive in the NE, NW, QZ, and YG regions. These results are beneficial for the adaptive management and protection of the environment and the realization of green and sustainable developmental strategies in the Chinese mainland.


Asunto(s)
Ecosistema , Ambiente , Humanos , Carbono , China , Tecnología de Sensores Remotos , Suelo , Ciclo Hidrológico , Ciclo del Carbono , Efectos Antropogénicos
2.
Sci Total Environ ; 856(Pt 2): 159075, 2023 Jan 15.
Artículo en Inglés | MEDLINE | ID: mdl-36174685

RESUMEN

Recently, drought events have occurred frequently and have profoundly altered the carbon sequestration in terrestrial ecosystems. How drought affects carbon sequestration is an important issue which may assist in understanding and confronting the challenges of extreme climate change. Nevertheless, drought-induced carbon-cycle effects remain scarce from the perspective of drought indices. In this study, we quantified the impacts of potential evapotranspiration (PET), standardized precipitation evapotranspiration index (SPEI), downward short-wave radiation flux (SWDown), and soil water (Soil_w) on net ecosystem productivity (NEP). We showed that the spatiotemporal heterogeneity of drought was extremely significant, and the hot spots of aridification were mainly distributed in the southwestern Yungui Plateau (YG) and Northwest China (NW). Moreover, the "pan evaporation paradox" appeared across the Chinese mainland before the 1990s and subsequently disappeared. Similarly, in contrast to the moderate NEP fluctuation between 1981 and 1999, since the beginning of the 21st century, NEP has increased significantly across Chinese mainland, YG, the plains region of Changjiang (CJ), and Southeast China (SE). Meanwhile, there are obvious directional, temporal, and spatial differences in the effects of the drought indices on NEP. Specifically, a higher SPEI value results in a more obvious promoting effect on NEP in SE, North China (NN), and northeastern YG. An increase in SWDown can promote an increase in NEP, especially in the northeastern YG and central SE. The increase in Soil_w in parts of the Qinghai-Tibetan Plateau, Xinjiang Region (XJ), southeastern NW, NN, and Northeast China with poor water conditions can promote carbon sinks. The inhibition effect is particularly obvious in some areas of CJ, where water resources are abundant. The fluctuation in PET has a relatively low influence on NEP. This study provides a comprehensive assessment of drought change and its impact on carbon sequestration and may help in formulating appropriate policies for carbon management and ecological security.


Asunto(s)
Secuestro de Carbono , Sequías , Ecosistema , Cambio Climático , Suelo , Carbono/análisis , Agua , China
3.
J Environ Manage ; 271: 110895, 2020 Oct 01.
Artículo en Inglés | MEDLINE | ID: mdl-32778257

RESUMEN

Effective strategies, policies and measures for carbon emission reduction need to be developed and implemented according to good understanding of both local conditions and spatial differentiation mechanism of energy consumption associated with human activities at high resolution. In the study, we first collected statistical yearbooks, high resolution remotely sensed imageries, and 3895 usable questionnaires for the urban areas of Kaifeng; then measured the carbon emissions from household energy consumption, using the accounting method provided in the IPCC GHG Inventory Guidelines; and finally applied both exploratory and explanatory statistical methods to characterize the spatial pattern of carbon emissions at high resolution, identify key influencing factors, and gain better understanding of the spatial differentiation mechanism of urban residential carbon emissions. Our study reached the following conclusions: (1) Central heating facilities with controllable flow are important for carbon emissions reduction, but its spatial distribution shows unfairness; (2) Spatial clusters of high carbon emission areas were primarily located in the outer suburbs of the city, validated to some extent the hypothesis that urban sprawl has a driving effect on the increasing urban residential carbon emissions; (3) Factors like size of residential area, family structure, life style, personal preference and behavior rather than household income have significant impacts on household carbon emissions, implying that effective control of residential areas, promotion of family life and low-carbon lifestyle, and effective guidance of proper behaviors and preferences will play a crucial role in reducing urban residential carbon emissions; and (4) Most of the identified influencing factors exhibit clear and specific spatial patterns and gradients of impact, implying that measures for urban residential carbon emission reduction should be adapted to location conditions. The study has generated a set of concrete evidences and improved understandings of the spatially differentiated mechanisms upon which the formation and deployment of any effective strategies, policies and measures for reducing urban residential carbon emissions should be based.


Asunto(s)
Dióxido de Carbono/análisis , Carbono/análisis , China , Ciudades , Calefacción , Humanos
4.
Artículo en Inglés | MEDLINE | ID: mdl-30897773

RESUMEN

A set of exposure⁻response coefficients between fine particulate matter (PM2.5) pollution and different health endpoints were determined through the meta-analysis method based on 2254 studies collected from the Web of Science database. With data including remotely-sensed PM2.5 concentration, demographic data, health data, and survey data, a Poisson regression model was used to assess the health losses and their economic value caused by PM2.5 pollution in cities of atmospheric pollution transmission channel in the Beijing⁻Tianjin⁻Hebei region, China. The results showed the following: (1) Significant exposure⁻response relationships existed between PM2.5 pollution and a set of health endpoints, including all-cause death, death from circulatory disease, death from respiratory disease, death from lung cancer, hospitalization for circulatory disease, hospitalization for respiratory disease, and outpatient emergency treatment. Each increase of 10 µg/m³ in PM2.5 concentration led to an increase of 5.69% (95% CI (confidence interval): 4.12%, 7.85%), 6.88% (95% CI: 4.94%, 9.58%), 4.71% (95% CI: 2.93%, 7.57%), 9.53% (95% CI: 6.84%, 13.28%), 5.33% (95% CI: 3.90%, 7.27%), 5.50% (95% CI: 4.09%, 7.38%), and 6.35% (95% CI: 4.71%, 8.56%) for above-mentioned health endpoints, respectively. (2) PM2.5 pollution posed a serious threat to residents' health. In 2016, the number of deaths, hospitalizations, and outpatient emergency visits induced by PM2.5 pollution in cities of atmospheric pollution transmission channel in the Beijing⁻Tianjin⁻Hebei region reached 309,643, 1,867,240, and 47,655,405, respectively, accounting for 28.36%, 27.02% and 30.13% of the total number of deaths, hospitalizations, and outpatient emergency visits, respectively. (3) The economic value of health losses due to PM2.5 pollution in the study area was approximately $28.1 billion, accounting for 1.52% of the gross domestic product. The economic value of health losses was higher in Beijing, Tianjin, Shijiazhuang, Zhengzhou, Handan, Baoding, and Cangzhou, but lower in Taiyuan, Yangquan, Changzhi, Jincheng, and Hebi.


Asunto(s)
Contaminación del Aire/efectos adversos , Costo de Enfermedad , Exposición a Riesgos Ambientales/efectos adversos , Estado de Salud , Material Particulado/efectos adversos , Contaminación del Aire/análisis , Beijing/epidemiología , China/epidemiología , Ciudades/epidemiología , Exposición a Riesgos Ambientales/análisis , Monitoreo del Ambiente , Gastos en Salud , Humanos , Mortalidad/tendencias , Material Particulado/análisis
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