With China’s rapid economic development and urbanization process, cities are facing great challenges for tackling anthropogenic climate change. In this paper we present features, trajectories and driving forces for energy-related greenhouse gas (GHG) emissions from four Chinese mega-cities (Beijing, Tianjin, Shanghai and Chongqing) during 1995–2009. First, top-down GHG inventories of these four cities, including direct emissions (scope 1) and emissions from imported electricity (scope 2) are presented. Then, the driving forces for the GHG emission changes are uncovered by adopting a time serial LMDI decomposition analysis. Results indicate that annual GHG emission in these four cities exceeds more than 500 million tons and such an amount is still rapidly growing. GHG emissions are mainly generated from energy use in industrial sector and coal-burning thermal power plants. The growth of GHG emissions in four mega-cities during 1995–2009 is mainly due to economic activity effect, partially offset by improvements in carbon intensity. Besides, the proportion of indirect GHG emission from imported energy use (scope 2) keeps growing, implying that big cities are further dependent on energy/material supplies from neighboring regions. Therefore, a comprehensive consideration on various perspectives is needed so that different stakeholders can better understand their responsibilities on reducing total GHG emissions.
Cities with less than one percent of global surface, where half of the global population lives [1], are responsible for more than 60 percent of global energy consumption and three-fourth of world Greenhouse gas emissions [2]. Therefore, cities play a significant role in curbing anthropogenic climate changes. Besides, with high population density, complicated infrastructure and various municipal services, cities are vulnerable for abrupt climate interference and also sensitive to energy conservation and GHG reduction actions [3].
Currently, more than a thousand cities worldwide have pledged to reduce GHG emissions at local scale. Actions such as ‘‘Cities for Climate Protection’’ (CCP) campaign and C40 group are becoming popular [4]. To date, more sophisticated studies on cities’ GHG footprints have been undertaken at different sizes [5], [6], [7], [8]. In order to raise appropriate policies for addressing climate change, GHG emission benchmarks and inventories have been considered as the first step for further analysis [8]. Nevertheless, there are three challenges in the holistic analysis of GHG status at city level.
First, it’s difficult to define a city’s boundary for GHG footprint accounting due to a large amount of cross-boundary GHG emissions caused by urban metabolism [9], [10]. Cross-boundary exchange of goods, services, commuter travel and aviation has posed a “challenge in developing a holistic accounting of GHG emissions associated with human demands for energy and materials in cities” [6]. Direct use of primary energy through industrial activity leads to the direct GHG emissions within territorial boundary, and these emissions are usually defined as scope 1 [11], [12], [13]. Cities consume a large amount of purchased electricity generated by upstream power plant, and the corresponding emissions are defined as scope 2. The consumption of products leads to the emissions from upstream production through supply chain, which is defined as scope 3. Previous studies indicate that emissions among different scopes are significantly different [14], [15]. Various boundary definitions have resulted in uncertainties of cities’ GHG inventories and then become barriers for the comparable study of cities’ GHG emission status at global scale.
Second, appropriate methodologies for the different scopes are still lacking, or having data limitations. To provide a holistic analysis on city’s GHG emission can provide incentives to various stakeholders so that they can raise their emission reduction plans. Thus, a comparative study among scope 1, scope 2 and scope 3 emissions is necessary. However, it is difficult to calculate exact emission for each of scope due to several uncertainties, such as embodied emissions of foods and construction materials. For instance, in order to calculate scope 3 emission, a hybrid IO-LCA (input–output life cycle assessment) methodology should be adopted so as to track the supply chain emissions [16]. But both data collection and model development are challenging missions.
Third, due to data availability, boundary and method uncertainties, a comprehensive perspective on urban GHG emission including spatial-temporal features and their underling drivers is missing [8]. Typically, different cities have different features, such as historical development, industrial structure, climate and culture perspectives [17], but little is known on the evolution of urban GHG emission especially with different scope perspectives. In order to raise appropriate mitigation policies, it is also necessary to identify the key factors driving city’s emission. Therefore, it is critical to conduct more comprehensive analysis from both special and temporal perspectives. However, challenges exist. For example, the accounting of emissions from purchased electricity requires the grid emission factor, which is influenced by energy structure for power generation and may vary significantly over time. Scope 3 inventories require detailed information on materials and energy flux, and should be calculated through the use of national and regional input–output (IO) models. But in reality such models always appear late. In addition, with the temporal change of GHG emissions, driving forces also change, therefore, mitigation actions should respond to such changes. Academically, several studies focus on historical change of GHG from different scope and their policy implication at global and national levels [18], [19], but few studies at city level have been conducted.
With regard to China, due to rapid industrialization and urbanization in the last three decades, China has become the largest CO2 emitter in the world, accounting for 25% of global CO2 emission [20] and 20.3% of global primary energy consumption [21]. Due to the fact that Chinese cities contribute three quarters of national GDP and account for 84% of national commercial energy use [5], to undertake quantitative analysis on GHG emissions from Chinese cities is necessary. Practically, China’s regional “low-carbon development” strategy mainly targeted in cities. For example, several cities have already initiated their low-carbon development plans, such as Baoding, Shanghai, Guiyang, Hangzhou, Wuxi, Jilin, Zhuhai, Nanchang and Xiamen [22]. National Reform and Development Commission (NDRC, a ministry leveled agency responsible for national economy planning) initiated national low-carbon demonstration projects in August 2010, in which eight cities were chosen as pilot cities, including Tianjin, Chongqing, Shenzhen, Xiamen, Hangzhou, Guiyang and Baoding. Academically, studies on energy use and GHG emissions in Chinese cities increased quickly, such as Shanghai [23], Shenyang [24], Nanjing [25], Suzhou [10], [26], [27], etc. Both “top-down” and bottom-up” approaches have been applied and most of the GHG emissions were calculated based on the IPCC method for national GHG inventory [28]. For example, Dhakal estimated energy consumption and CO2 emission in 35 cities and analyzed historical changes in Beijing, Tianjin, Shanghai and Chongqing by using a “top-down” approach [5]. Xi et al. [24] and Bi et al. [25] developed a bottom up accounting approach with sectoral detailed GHG emissions. These studies created opportunities for global comparison, but a comparison study among different cities from both spatial and temporal perspectives is still missing, especially between different emission scopes.
Hence, this study fills such a gap by employing a case study approach. Four mega-cities, including Beijing, Tianjin, Shanghai and Chongqing, were chosen due to their prominent positions and data availability. Also, these four cities are key targets for implementing China’s national policy on “energy saving and emission reduction”. The main objective of this paper is to identify the key driving forces on CO2 emissions in Chinese mega-cities through a spatial-temporal analysis so that policy implications can facilitate decision-makers to prepare appropriate policies on responding anthropogenic climate changes. To achieve our research targets, we first elaborate our methodology, including a brief introduction on four cities, data collection, as well as detailed computation process. We then have a deep analysis on research outcomes and raise our proposals for policy development. We finally make our conclusions.
2. Methodology
2.1. Research areas
Beijing, Tianjin, Shanghai and Chongqing are four municipal cities directly accountable to the central government (politically equal to one province) in China. The definition of the total population of these four cities are 70 million, about 1% of world population, and their total GDP counts for 10% of the whole country in 2009 [29]. Beijing is the capital of China which locates in the northern part of the North China Plain. It covers 16, 410 km2 area and has a population of 17.6 million and a gross domestic product (GDP) of 1, 215 billion Yuan (RMB) in 2009 (1 USD equals to 6.83 RMB in 2009). Tianjin is east to Beijing, approximately 160 km from Beijing. It covers an area of 11, 917 km2, with a population of 12.3 million and a GDP of 721 billion Yuan in 2009. Shanghai is an economic center located in Yangtze delta area, with an area of 6340 km2, a population of 19.2 million and a GDP of 1, 505 billion Yuan in 2009. Chongqing is located along the upper reaches of the Yangtze River, straddling the region that connects the central and western parts of China. It covers an area of 82, 400 km2and has a population of 28.6 million and a GDP of 653 billion in 2009. Table 1 lists some basic characteristics of these four cities.
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