Effects of urbanization on airport CO₂ emissions: A geographically weighted approach using nighttime light data in China

Highlights

• CO₂ emissions in 2015 from China’s 70 airports are calculated.

• Geographically weighted regression model is used to investigate key influencing factors.

• Night-time light is used to measure urbanization.

• The impacts of urbanization in western region are higher than that in the eastern and the central region.

Abstract

Regional disparities in carbon dioxide (CO₂) emissions from airports at the city level are of increasing importance for low-carbon development of the civil aviation sector. However, CO₂ emissions from airport operations have rarely been estimated and discussed. We investigate the main driving forces of airport CO₂ emissions by using Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR) models, separately, to investigate whether urbanization drives airport CO₂ emissions and to investigate spatial heterogeneity at the city level. Nighttime light (NTL) data from satellite observations are adopted as a proxy for urbanization. We obtained energy consumption data by end-use purpose for 70 airports in China and calculated the CO₂ emissions from on-ground airport operations. The median CO₂ emissions of the 70 sample airports are estimated to be 15.9 million tonnes for 2015. Results from the GWR model indicate that airport CO₂ emissions are affected by five main factors: urbanization, foreign direct investment, the share of tertiary industry in gross domestic output, passenger turnover of civil aviation and passenger turnover of railways. The elasticity of urbanization shows an increasing trend from the east of China to the west. The spatial heterogeneity of the CO₂ emissions of the five airport clusters that are located in five urban agglomerations is discussed. In order to achieve effective reductions of CO₂ emissions from airports, policy-makers should consider the spatial heterogeneity of the major driving factors of carbon emissions in different regions to avoid carbon lock-in.

Introduction

The civil aviation sector accounts for approximately 2–3% of global anthropogenic carbon dioxide (CO₂) emissions (Edwards et al., 2016). The share shows a rapidly increasing trend in the future, due to the increasing volume of aviation traffic and airport expansion. The International Civil Aviation Organization (ICAO) predicts that emissions of global greenhouse gases (GHG) from the civil aviation sector will increase 4 to 6 times by 2050 compared with the 2010 emissions level, due to the increasing number of airlines and the construction of new airports (ICAO, 2014). The Kyoto Protocol delegated to the ICAO the task of developing a GHG emissions target for aviation to mitigate the threat of global climate change. ICAO made an ambitious target: that by 2050 the global annual fuel consumption efficiency will be increased by 2% relative to 2005. After this, the ICAO began to collect GHG emission data from its member countries and reported them to the United Nations Framework Convention on Climate Change (UNFCCC) since 2009. In 2016, the ICAO finalized the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA), which will take effect from 2021. Under the CORSIA, the CO₂ emissions from international civil aviation among the member nations will reach carbon-neutral growth from 2020 onwards.

China’s civil aviation sector has experienced a rapid boom since the 1980s and has become the second largest civil aviation transportation industry globally after the United States since 2005. The total aviation passenger turnover has grown from 6 million in 1980 to 1148 million in 2017 (CAAC, 2016a), which is approximately 192 times. It is predicted that the CO₂ emissions from China’s aviation transport will continue to grow at a rapid pace: according to the IEA, the increasing annual rate of energy demand of China’s aviation industry is 3.4% after 2016 (IEA, 2017), and it is predicted that CO₂ emissions will double by 2030 relative to 2013 (Zhou et al., 2016).

The total number of civil-certificated airports in mainland China reached 231 in 2017. It has been estimated that the on-ground CO₂ emissions from airports accounted for approximately 2% of the total CO₂ emissions of the civil aviation sector in China (CAAC, 2016a). According to the “13th five-year plan of the development of Civil Aviation of China”, the number of public airports in China is expected to reach 260 in 2020 (CAAC, 2016b). As a result, both the energy consumption and the corresponding CO₂ emissions from on-ground airport operation can be expected to continue to grow.

Previous research has focused on the development of an emission inventory from the number of civil passengers and flight departures and arrivals. Fan et al. (2012) calculated the HC, CO, NO_x, CO₂, and SO₂ emissions from domestic flights of civil aviation in China in 2010, among which CO₂ emissions accounted for 38.21 million tons (Mt). Andersen et al. (2010) estimated the CO₂ emissions of exports from China from a consumption perspective and found that CO₂ emissions from air transport of China’s net exported goods in 2008 amounted to approximately 43 Mt. Liu et al. (2019a), 2019b calculated the emission inventory of seven pollutants and CO₂ emissions in 2015, and they found that the total CO₂ emissions for the aviation industry was approximately 60 Mt. However, these previous emission inventories include emissions during the take-offs and landings of civil flights, and on high altitude flights between departure and destination airports. The CO₂ emissions related to on-ground airport operations has rarely been discussed. Energy conservation and CO₂ emission controls from on-ground airport operations are less costly than technology improvements for aircraft and aviation fuels. Understanding the driving forces among different regions for CO₂ emissions from airport operations is critically important for policy formulation analysis of the aviation sector.

Previous research focused on investigations of the driving factors of CO₂ emissions for aircraft transportation. A set of measures had been discussed to reduce the in-flight CO₂ emissions from civil aviation, including reducing time-dependent costs (Edwards et al., 2016), converting from aviation oil to biofuels (Chiaramonti et al., 2014; Staples et al., 2018), etc. Liu et al. (2019a,2019b) found a high correlation between the major pollutants and the national GDP during the period 1980 to 2015. Regarding the relationship between pollutants and economic growth, Grossman and Krueger (1991) proposed an inverted U-shaped curve, commonly known as the Environmental Kuznets curve. It hypothesizes that when the economy reaches a certain stage, for example, high-level growth, pollutants start to decrease. However, at the present time China is facing a booming civil aviation industry, implying that it is projected that emissions will continue to increase as the economy grows. In addition, the emission intensity of the civil aviation industry in central and eastern China is much higher than in northeastern and western China, which may be due to the larger traffic volume and transit convenience. However, the relationship between city-level CO₂ emissions of on-ground airports and city development has not been investigated in previous research. Civil aviation is part of China's transport sector, which has been classified as a tertiary industry in the national accounts. Jiao (2005) found that the shares of tertiary industry, labor and total passenger volume are the main influential factors of airport turnover in China. Das et al. (2016) found that airport design and air traffic control have positive impacts on fuel consumption reduction. Passenger turnover has a higher impact on CO₂ emissions in the less-developed provinces (Xu and Lin, 2018). The demand patterns of passengers are strongly affected by economic and demographic factors, and these may directly induce higher airport CO₂ emissions. Bruderer Enzler (2017) found that higher income is positively correlated with increased air travel.

Among all the potential influential factors of aviation CO₂ emissions, taking into account the increasing emphasis on city development and economic growth in recent years, urbanization has been determined to be a key driving factor (Li et al., 2019a,2019b). China reached an urbanization rate of 56.1% in 2015 (Xu and Hu, 2016), and urbanization is closely associated with socio-economic activities (Ma et al., 2012; Zhang et al., 2017). These indicators, among which are economic urbanization, space urbanization and population urbanization, have been shown to be indicative of the urbanization level in China (Wu et al., 2018). Xu and Lin (2018) found that the influences of urbanization on CO₂ emissions from the transportation sector in the mid- to upper-development level provinces are higher than in other provinces. Thus, urban development also plays a significant role in aviation CO₂ emissions.

Space-based observations can provide explicit and reliable information on the process of urban development. Previous research found that nighttime light (NTL) data reflect the general intensity of human activities (Letu et al., 2015; Li et al., 2019a,2019b); and these data have been adopted as a proxy to estimate population (Sutton et al., 2001), urban built-up area (Liu et al., 2012; Meng et al., 2014), energy consumption (Letu et al., 2010), in-use steel stock of buildings and civil engineering infrastructures (Hattori et al., 2014; Liang et al., 2017) and CO₂ emissions (Cui et al., 2019b; Letu et al., 2014). Global urbanization characteristics have been mapped and analyzed by using NTL and optical remote sensing data (Goldblatt et al., 2018; Kasimu et al., 2009). Zhang and Seto (2011) discovered the potential of analyzing urbanization dynamics at regional and global scales by using multi-temporal Defense Meteorological Satellite Program (DMSP) Operational Line-Scan System (OLS) NTL data. Ma et al. (2012) found that the spatial-temporal relationship between urban NTL and urbanization variables were highly correlated in China, thus proving that the NTL data are reliable for characterizing the urbanization level at different regional scales.

Three current research gaps can be summarized. First, before this estimation, the on-ground airport CO₂ emissions have not yet been estimated due to data availability, and existing research on the driving forces of on-ground airport emissions is very limited. Second, researchers have employed NTL data to investigate the relationship between urbanization level and air quality, for example PM_2.5 concentrations (Du et al., 2018) and NO₂ (Cui et al., 2019a). But NTL data have not been applied to analyze the influences of city development on airport CO₂ emissions. Third, most of the existing research is based on an Ordinary Least Square (OLS) method, which assumes that there is no spatial heterogeneity across regions. Empirical results based on average data cannot emphasize the spatial differences among regions. Previous research has failed to explain the regional issues of CO₂ emissions in these empirical studies, although it is important to face the fact that different regions have different situations: the western and eastern cities of China are at very different development levels. The spatial distributions of airport CO₂ emissions, their regional differences and the effects of urbanization on airport CO₂ emissions have not been investigated yet.

To represent the spatial differences across regions, the Geographically Weighted Regression (GWR) model makes use of geographical features to explore spatial data (Stewart Fotheringham et al., 1996). The GWR model had been widely adopted to investigate the driving factors affecting CO₂ emissions for the agricultural sector (Sheng et al., 2017; Xu and Lin, 2017), the manufacturing sector (Xu et al., 2017), all industrial sectors (Li et al., 2018), and overall provincial CO₂ emissions (Ru et al., 2018). In this work, we compare the results of OLS and GWR models, and investigate the influences of urbanization and other factors on airport CO₂ emissions in China.

The results of this work will help decision makers in the fields of regional and urban planning and airport development authorities to increase their insight into the management and extension of the current aviation infrastructure (airports, depots, transport-interchange, and other accessary support facilities), and also the planning and construction of new ones. We also provide estimates of the CO₂ emissions of airports as a contribution to the design of carbon reduction strategies in the civil aviation sector and in support of negotiations within the International Civil Aviation Organization (ICAO) under the auspices of the UNFCCC.