印度城市地区温室气体排放的地理分布:初步评估

P. Marcotullio, Jochen Albrecht, Andrea Sarzynski
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引用次数: 13

摘要

本文研究了印度城市地区温室气体(GHG)排放的模式,印度是一个快速增长和城市化的国家。它使用一个新的数据集——全球大气研究排放数据(EDGAR)来估计城市在国家温室气体排放中所占的份额。它通过城市形态(城市人口规模、面积大小、密度和增长率)、经济(GDP和人均GDP)、地理(排放位置:距离城市20公里、40公里和80公里)和生物物理(生态系统和气候:冷却度)特征呈现了排放变化的地理图景。因变量包括2000年来自14个来源活动(农业土壤、农业废物、航空、能源、化石燃料燃烧、固体逸出物、工业、牲畜、航海、非公路运输、石油和天然气生产、住宅、公路运输和废物)的二氧化碳(CO2)、甲烷(CH4)、氧化亚氮(N2O)和六氟化六烷(SF6)的排放,这些活动分配在0.1°全球网格上。我们研究了721个超过5万居民的城市地区(占印度城市总人口的92%),提出了研究结果,并将我们的结果与城市层面的碳足迹分析进行了比较。结果表明,印度城市地区的温室气体排放量低于文献中提出的水平,并且排放水平的差异因城市形态、经济、地理和生物物理变量而异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The geography of greenhouse gas emissions from within urban areas of India: a preliminary assessment
This paper examines the patterns of greenhouse gas (GHG) emissions from urban areas in India–a rapidly growing and urbanizing nation. It uses a new dataset, Emission Data for Global Atmospheric Research (EDGAR), to estimate the urban share of national GHG emissions. It presents a geographic picture of emission variation by urban form (urban population size, area size, density, and growth rate), and economic (GDP and GDP per capita), geographic (location of emissions released: 20, 40, and 80 km from urban areas), and biophysical (ecosystem and climate: cooling degree days) characteristics. Dependent variables include emissions of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and hexafl uoride (SF6) from 14 source activities (agricultural soils, agricultural wastes, aviation, energy, fossil-fuel fi res, fugitive escapes from solids, industry, livestock, navigation, non-road transport, oil and gas production, residential, road transport, and waste) for the year 2000 that are allocated on a 0.1° global grid. We examine 721 urban areas with more than 50,000 residents (accounting for 92% of the total Indian urban population), present fi ndings, and compare our results with urban-level carbon footprint analyses. The results demonstrate that GHG emissions from urban areas in India are lower than that presented in the literature, and that differences in emissions levels vary with urban form, economic, geographic, and biophysical variables.
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