دانلود مقاله ISI انگلیسی شماره 145870
ترجمه فارسی عنوان مقاله

تجزیه و تحلیل فضایی روابط زیست محیطی متابولیسم کربن شهری بر اساس یک مدل شبکه 18 گره

عنوان انگلیسی
Spatial analysis of the ecological relationships of urban carbon metabolism based on an 18 nodes network model
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
145870 2018 34 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Cleaner Production, Volume 170, 1 January 2018, Pages 61-69

ترجمه کلمات کلیدی
متابولیسم کربن شهری، قانون اساسی، تجزیه و تحلیل شبکه محیط زیست، تجزیه و تحلیل فضایی، 18 شبکه گره
کلمات کلیدی انگلیسی
Urban carbon metabolism; Relationship constitution; Ecological network analysis; Spatial analysis; 18 nodes network;
پیش نمایش مقاله
پیش نمایش مقاله  تجزیه و تحلیل فضایی روابط زیست محیطی متابولیسم کربن شهری بر اساس یک مدل شبکه 18 گره

چکیده انگلیسی

The study of carbon metabolism from the perspective of a network has received much attention in ecological simulation. The present study focused on the previous analysis of natural metabolism, and we generated a spatial network model with 18 nodes consisting of natural and technical metabolic components. We combined flow and utility analysis using the ecological network method to quantitatively analyze the structure of the ecological relationships and summarize the key metabolic functions among different relationships of Beijing. The positive or negative effect of these relationships on the system was also explored. Furthermore, we used the GIS method to map the different relationships and examine their flux to characterize the spatial variations of Beijing. We concluded that transportation and industrial land, cultivated and urban land were the main components that contributed to exploitation and control relationships, resulting in excessive carbon emissions during urban sprawl. Natural metabolic components and cultivated land were the foundation of mutualism relationships that increase carbon sequestration. Beijing needs more space to develop mutualism relationships while cutting down on the carbon emission brought by the competition relationships. The results will guide the optimization of the spatial structure in urban areas, and the well-constructed framework could be applied to future urban planning.