Atmospheric emission inventory of multiple pollutants from civil aviation in China: Temporal trend, spatial distribution characteristics and emission features analysis

Science of the Total Environment 648 (2019) 871–879

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Atmospheric emission inventory of multiple pollutants from civil aviation in China: Temporal trend, spatial distribution characteristics and emission features analysis Huanjia Liu a,b, Hezhong Tian a,b,⁎, Yan Hao a,b, Shuhan Liu a,b, Xiangyang Liu a,b, Chuanyong Zhu b,c, Yiming Wu a,b, Wei Liu a,b, Xiaoxuan Bai a,b, Bobo Wu a,b a b c

State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China School of Environmental Science and Engineering, Qilu University of Technology, Jinan 250353, China

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• A dedicated multi-pollutants emission inventory from China's civil aviation is established. • Temporal trend of multi-pollutants emission for historical period 1980–2015 is investigated. • Spatial distribution characteristics by varied airports and airlines are presented. • Multi-pollutants emissions features of LTO and cruise operation modes are analyzed. • Pollution from aviation can't be ignored due to rapid growth in aviation activities.

a r t i c l e

i n f o

Article history: Received 22 May 2018 Received in revised form 24 July 2018 Accepted 29 July 2018 Available online 30 July 2018 Editor: Jianmin Chen Keywords: Civil aviation Multiple air pollutants emission inventory Spatial and temporal distribution LTO and cruise process Scenarios analysis

a b s t r a c t A detailed comprehensive emission inventory of multiple air pollutants from civil aviation in China for the historical period of 1980–2015 is developed by using an approach of combining bottom-up with top-down for the first time. Annual emissions of various pollutants present a rapidly ascending trend along with the increase of economic volume and population, which are estimated at approximately 4.77 kt HC, 59.63 kt CO, 304.77 kt NOx, 59,961 kt CO2, 19.04 kt SO2, 3.32 kt PM2.5, 1.59 kt BC, 1.06 kt OC and 5.44 t heavy metals (HMs), respectively, by the year 2015. We estimate the local emissions in 208 domestic civil airports and allocate the total cruise emissions onto 299 main domestic flight segments with surrogate indexes, such as route distance, cargo and passenger turnover. The results demonstrate that emission intensities in central and eastern China are much higher than those in northeastern and western China, and these regions are characterized with high population density, huge economy volume, as well as transit convenience. Furthermore, we have explored emission characteristics of multiple pollutants under different operation modes in 2015. For PM2.5, SO2/CO2/HMs and NOx, the emissions from cruise process constitute the dominant contributor with a share of 89%, 92% and 81%, of the associated total emissions, respectively, comparing with 76% and 71% of the total CO and HC emissions release from Landing and Takeoff (LTO) process. Consequently, there are notably different emission characteristics from different flight processes due to various combustion status of aviation fuel. In addition, we predict the future trends of multipollutants emissions from China's civil aviation industry through 2050 under three scenarios, and the results

⁎ Corresponding author at: Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China. E-mail address: [email protected] (H. Tian).

https://doi.org/10.1016/j.scitotenv.2018.07.407 0048-9697/© 2018 Elsevier B.V. All rights reserved.

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H. Liu et al. / Science of the Total Environment 648 (2019) 871–879

indicate that the reduction from the improvement of new technology or new national standards would be largely offset by the rise in multi-pollutants emissions from rapidly aviation fuel growth. © 2018 Elsevier B.V. All rights reserved.

1. Introduction Along with the rapid economic development since the implementation of opening and reforms and globalization process, China has become the secondary largest aviation transportation market in the world, followed with the United States since 2005. Total volume of transport turnover (including cargo and passenger turnover) of China's civil aviation industry is reported to be 55.9 billion ton-km in 2015, increased by 201 times over 1980 (CAAC, 2016a). Therein, the passenger turnover volume exceeds 556.6 billion capita-km, increased by 197 times compared with that in 1980 (CAAC, 2016a). The growth rate is far more than that of national GDP and other transportation modes, and the increase in aviation industry is forecasted to continue in the foreseeable future (Chen et al., 2017). Though civil aviation industry brings more convenience for human beings travelling, its growth is related to increased negative effects on environment and human health due to large amounts of aviation fuels combustion. Because it releases various hazardous air pollutants and greenhouse gases including carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), a large volume of hydrocarbons (HC), fine particles containing organic and inorganic components, as well as carbon dioxide (CO2) (Harrison et al., 2015; Lund et al., 2017; Meleo et al., 2016). Previous studies find that emissions from aircraft are related to ozone (O3) depletion in stratosphere and contribute 3.5–4.9% of anthropogenic radiative forcing as aircrafts often operate in upper troposphere and lower stratosphere (Dessens et al., 2014; Lee et al., 2009). Moreover, about 8000 premature mortalities per year around the world are relevant with aircraft activities evaluated by combining with GEOs-chem model (Barrett et al., 2010; Voigt et al., 2012). Furthermore, the International Civil Aviation Organization (ICAO) predicts the total greenhouse gases emissions from aviation industry increase by 400–600% in 2050 compared with that in 2010 (ICAO, 2014). Consequently, risks to local air quality, climate change and human health effects imposed by emissions of multiple atmospheric pollutants from aviation industry capture extensive concerns around the world, especially in China. China, especially North China Plain region, has been frequently suffering from severe haze problems in autumn and winter during the past years (Han et al., 2017; Liu et al., 2017; Ma et al., 2017; Sun et al., 2013; Yang et al., 2016), causing regional joint prevention and control of atmospheric pollution has been a routine control policy and practice for China. More and more pollutants discharge reduction measures are implemented in order to alleviate extent of severe haze. However, most control measures are performed on the major sources such as power plants, iron and steel smelting, cement plants and residential coal burning. Little attention has been paid to atmospheric pollutants emitted from civil aviation, though their regional contributions are evident and cannot be ignored. An integrated aviation emission calculation can be divided into two processes: the LTO (Landing and Take-off) process and high altitude cruise stage. Therein, the emissions from LTO cycle mainly affects airport ground-level atmospheric conditions while cruise process can influence regional air quality and even global climate change. ICAO defines four work modes of the standard airplane LTO cycle: approach, taxiing, take-off, and climb process. The emissions of airports include four operation processed emissions from land surface to the top of atmospheric boundary layer at 915 m (ICAO, 2014). The aviation engine emission database is developed by ICAO according to measurement data under different thrust conditions from aircraft engine manufactures, which can provide pollutants emission factors of HC, CO and NOx, and is used to calculated LTO cycle emissions (Fan et al., 2012; Pejovic et al., 2008; Xia et al., 2008; Xu et al., 2016).

Researchers established the aircraft emission inventory for Beijing Capital International Airport by improved LTO cycle, including NOx, CO, HC, SO2 and PM2.5 as well as other domestic airports (Chen, 2013; Xia et al., 2008; Xu et al., 2016). Whereas, cruise process is the dominant contributor of pollutants during the whole flight compared with LTO cycle (Wilkerson et al., 2010), thus establishing emission inventory from this process is of great significance for examining the effects of aircraft on atmospheric composition and climate to regional or worldwide air quality. Gardner et al. (1997) developed a three dimensional (latitude, longitude, and altitude) global aviation emissions inventory for NOx with a resolution of 2.8° × 2.8° by 1 km in altitude, demonstrated that 60% of NOx the global was emitted at cruise altitude of 10–12 km and Northern Hemisphere accounted for 93% of global emissions. Although some regional aviation emission inventory has been developed, comprehensive emission inventories of multiple air pollutants from aviation industry for mainland China are not publicly published so far. Thus, developing an integrated emission inventory of China's aviation industry which covers various pollutants (including conventional air pollutants, greenhouse gas and heavy metals) and accounts for airport's LTO cycle and cruise process between airports is quite essential. In this paper, based on refined information on airports' flight schedule, civil aviation aircraft/engine comparison list, revised pollutants emission factors from ICAO database under cruise conditions, we calculate and analyze the spatial distribution characteristics of typical air pollutants (HC, CO, NOx, CO2, SO2, PM2.5 and heavy metals) emitted from civil aviation industry of China including LTO cycle and cruise process for the year 2015. Furthermore, we investigate and present the historical temporal of pollutants emission for aviation industry from 1980 to 2015, and predict the future emission trends until 2050 with scenario analysis. 2. Methodologies and data sources 2.1. Targeted pollutant species, domain and time period In this work, we have made efforts to establish an integrated aircraft emission inventory of multiple pollutants (HC, CO, NOx, CO2, SO2, PM2.5, BC, OC, and heavy metals (including As, Cu, Ni, Se, Cr, Cd, Hg, Pb, Zn)) of 208 civil airports and 299 main domestic flight segments in mainland China for the base year of 2015. Furthermore, we analyze the historical temporal variations of pollutants emissions from 1980 to 2015 and predict the future trends till 2050 under different scenarios. 2.2. Data sources and quality assurance/quality control (1) Flight schedules dataset

The flight schedules are used to calculate the airports' LTO cycle emissions, which are obtained from Civil Aviation Administration of China (CAAC) and main airports' official website. The data needed to collect including airline name, aircraft type, flight number, departure time and place, destination and time, etc. We take great cares to check and compile the collected datasets so as to avoid the omission or double counting flight information during the calculation. (2) Aircraft/engine matching

Boeing and Airbus planes are the main airplane types of China civil airplanes, whereas, many different types of engines, which are

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produced and supplied by different engine manufactures, may equipped to one type of airplane. However, it is difficult to find detail information on engine of each plane and cannot to match with the specific fight. In order to calculate more conveniently, previous researches normally chose one typical engine type for each airplane type (Fan et al., 2012; Ma and Zhou, 2000), whereas in this study, we have made efforts to improve the calculation method for better estimating emission. We have collected all engine types of each type of aircraft of China Civil Aviation, and the detail information come from annual report of airworthiness certification from CAAC (2016b). Take Airbus A319-100 for example, a total of 191 aircraft in operation by the end of the year 2015, 11 planes are equipped with CFM56-5B6/P engine (CFM corporation) with take-off HC emission factor 0.2 g·kg-fuel−1 while 42 aircrafts are equipped with V2527M-A5 engine (International Aero Engines, IAE) with take-off HC emission factor 0.04 g·kg-fuel−1 (ICAO, 2014). Detailed aircraft/engine combination information is summarized in Table S1 in Supplement information (SI). (3) Emission factors of varied pollutant species

The emission factors of HC, CO, NOx of LTO cycle can be obtained from ICAO aircraft engine emission databank, which are voluntarily provided by engine manufactures and measured under the ISA (International Standard Atmosphere) conditions. In addition, the emissions of CO2, SO2, and heavy metals are calculated based on fuel flow, as these pollutants' emissions are dependent on fuel only and not on technology (EEA, 2017). We determine 3150 g·kg−1 and 1 g·kg−1 as the average emission factors of CO2 and SO2 with a combination of previous literatures (Fan et al., 2012; Howitt et al., 2011; Wei and Wang, 2010; Xu et al., 2016) (see Table 1). Because of quite limited measured data about emission factors of heavy metals from China's civil aviation, on accounting of the same engines were equipped between domestic and foreign owned airplanes and no obvious difference of heavy metals content in aviation kerosene standards between China and the EU countries, we adopt the average emission factors of heavy metals (including As, Cu, Ni, Se, Cr, Cd, Hg, Pb, Zn) by referring to EEA air pollutant emission inventory guidebook (EEA, 2017) (see Table 1). 2.3. Calculation methods 2.3.1. Fuel flow The total aircraft fuel consumption can be divided into two parts: the LTO cycle fuel consumption which mainly concentrate around airports, and cruise fuel consumption on high altitude between departure and destination airports. The LTO cycle fuel consumption rates of four stages for different engine type can be obtained from ICAO emission database. Furthermore, by taking a weighted average of different engine types' fuel consumption and pollutants emission factors, we can calculate fuel consumption of each aircraft type. By contrast, the cruise fuel Table 1 Emission factors of CO2, SO2, and heavy metals based on fuel consumption (Unit: g/t-fuel). Pollutant Emission factor

Reference data

SO2a CO2a As*100 Cu Ni Se Cr Cd Hg*10 Pb Zn

[0.8–1.0] (EEA, 2017; Fan et al., 2012; Howitt et al., [3115–3155] 2011; Wei and Wang, 2010; Xu et al., 2016) 0.005 0.023 0.035 0.14 0.01 0.01 0.001 0.055 0.01

a

1 3150 0.005 0.023 0.035 0.14 0.01 0.01 0.001 0.055 0.01

Literature cited

The unit of emission factors for SO2, CO2 is kg/t-fuel.

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consumption of each aircraft type can be calculated by using annual kerosene consumption of the same aircraft type minus the LTO fuel consumption, which is available in official statistical materials (see SI Table S2 in SI) (CAAC, 2016b). 2.3.2. Calculation emissions of CO2, SO2, and heavy metals For estimating the total LTO cycle emissions and cruise process emissions of CO2, SO2, and heavy metals, we adopt fuel-based methodology by referring to EEA aviation emission guidebook (EEA, 2017). The emissions of these species are directly estimated by multiplying kerosene consumption with the assumed average emission factors, as their emissions are dependent on the content in fuel only and little correlate with the performance and technical characteristics of different engine types. 2.3.3. Calculation emissions of PM2.5 and BC, OC The emission rates of PM2.5 are dependent on aircraft type and payload, thus we estimate the emissions of LTO cycle based on aircraft type by referring to EEA aircraft emission guide book (EEA, 2017) (see SI Table S3). The emissions of PM2.5 equal to aircraft movements multiplying emission factors for LTO cycle and then divide by 2. Black carbon (BC) plays an important role in both climate change and health impacts (Bond et al., 2004; Ding et al., 2016; Jacobson, 2017). While organic carbon (OC), mainly from combustion processed, affects radiative forcing through light scattering (Chow et al., 2011). The emissions of BC, OC can be calculated according to the proportion of BC, OC to PM2.5 in LTO cycle and cruise process. Previous studies have done significant amounts of experiments to measure the emissions of BC and OC from different engine type based on test rig or emulation. On the basis of previous research achievements, we use the same average fBC, OC fraction (fBC = 0.48 and fOC = 0.32) for BC, OC emissions calculating (Agrawal et al., 2008; Brem et al., 2015; Durdina et al., 2017; Kinsey et al., 2011; Petzold et al., 2009; Petzold et al., 2003; Rogers et al., 2005; Winther and Nielsen, 2011). 2.3.4. Calculation emissions of China's civil airports Previous research has shown that the aircraft activity is the primary contributor to aircraft pollutants emissions (Xia, 2009) and it is necessary to establish nationwide airport emission inventory. The emissions for standard LTO cycle are considered as aviation emissions inventory for airport (Xu et al., 2016), which is crucial for the air quality in airport and the surrounding areas. In this study, we divided the 208 civil aviation airports in mainland China into four categories, so as for the convenience of calculating aviation emission of each airport on considering the obvious differentiation of passenger and cargo turnover, aircraft moment, etc. The take-off and landing proportion of different aircraft types is considered to be unifying in every group. The similar classifying methodology of developing emission inventory is also used in previous studies (Junker and Liousse, 2008; Pacyna et al., 2006; Salameh et al., 2016; Tian et al., 2014). SI Table S4 list out the detail categorization information of 208 domestic airports for the year 2015. 2.3.5. Revision of reference emission factors of cruise and emission estimation of main airlines The reference emission factors of HC, CO and NOx from aviation provided by ICAO emission databank are measured under ISA condition at sea level. Different ambient conditions (e.g. temperature, pressure) between upper air and sea level can cause enormous discrepancy on emission of jet engine, it is necessary to modify and recalculate emission factors under actual cruise conditions with emission data from ICAO databank. We use REF represent reference emission factors of pollutants from engine under sea level in order to calculate conveniently, then we plot REF against thrust's percentage for each pollutant and each aircraft type on the Cartesian coordinate system (see Fig. S1). Furthermore, we can calculate the emission factor of each pollutant of 70% thrust on sea level according to the fitting equations. Then we use the revised equations to calculate average emission factors under actual cruise

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conditions, and detail calculation process are presented in SI (Fan et al., 2012). For calculating cruise emissions of each airline, we developed the domestic main flight segments databank, including cargo and passenger turnover, route distance, annual flights, airport coordinates and so on. Total transport turnover volume of each airline as allocation coefficient is used to calculate airline separated emissions. 2.3.6. Calculation historical emissions of civil aviation from 1980 to 2015 Chinese domestic civil aviation industry has been grown rapidly during the past over three decades. Between 1980 and 2015, total transport turnover volume increased by 201 times, with passenger turnover and cargo turnover rising by 197 times and 90 times, respectively. To investigate the overall temporal variation characteristics of emissions from civil aviation, we estimated the annual pollutants emissions based on annual fuel consumption. According to EMEP/EEA air pollutant emission inventory guidebook (EEA, 2017), the total emissions of CO2, SO2 and heavy metals are dependent on the fuel only and not on the technology. Here, we calculate these pollutants emissions with constant emission factor due to no limit value in aviation fuel nation standard (GB 65372006 and GB6537-1994). For HC, CO, NOx, PM2.5, BC and OC, their emissions are obviously depended on combustion conditions, technical categories and payload (EEA, 2017). The trends of emission factors can be regard as a uniform model between 1980 and 2015. We adopt the annual improvement of average fuel efficiency of 1.5% for HC, CO, NOx and 1.0% for PM2.5, BC and OC based on the recommend values from EMEP/CORINAIR Emission Inventory Guidebook - 2006 (EEA, 2006).

as those in previous years. The emission factors (including burning condition dependent pollutants, HC, CO, NOx, PM2.5 and fuel dependent pollutants, SO2, heavy metals and so on) refer to those in the base year of 2015. Under the SC scenario and MFTR scenario, we assume that the application of new materials, aero engines technology, new fuel standards, and laws and regulations around the world can gradually improve combustion efficiency. For HC, CO, NOx emissions factors, we make the assumption that the yearly variation of it in the future years will decline according to the EMEP/CORINAIR Emission Inventory Guidebook (EEA, 2006). The annual improvement of average fuel efficiency of 1.5% and 3.0% are adopted for SC scenario and MFTR scenario, respectively. For PM2.5, SO2 and heavy metals emissions trends, the following transformed normal distribution function is used to estimate dynamic emission factor (EF) values of those pollutants over the time period by referring to our pervious study (Hua et al., 2016; Tian et al., 2014; Wang et al., 2016; Zhu et al., 2016):  yp;t ¼ ap e

2

−t2 2s

 þ bp

where y is EF value for pollutant p in the defined year t, b is the best technologically achievable EF value for pollutant p in 2050, a + b is EF value for pollutant p in the present day, and s is the shape parameter for the curve. Here, relevant parameter values used in this model are provided in SI Table S5.

2.4. Key assumptions

3. Results and discussion

In this study, we intend to calculate the emissions of HC, CO, NOx, CO2, SO2, PM2.5, BC, OC, and heavy metals emitted from Chinese civil aviation industry, including LTO cycles and cruise process. In order to simplify the calculation, several key assumptions are made and listed as follows: (1) Civil flights' take-offs and landings follow the standard LTO cycle in order to calculate LTO emissions using ICAO emission databank: Take-off process takes 0.7 min with 100% engine thrust; climb stage takes 2.2 min with 85% engine thrust; approach mode takes 4 min with 30% engine thrust; taxiing and idle takes 26 min with 7% engine thrust. The engine thrust is set as 70% of total thrust for cruise process (Fan et al., 2012; ICAO, 2014; Ma and Zhou, 2000; Wei et al., 2014). (2) All civil aviation flights is proceeding as planned, and the average cruise altitude is supposed as 11 km in this study, because pollutants emissions of aircraft in cruise at about 11 km account for a substantial part of total emissions while the most aircrafts cruise at a height of 9 to 12 km (Daggett et al., 1999; Ma and Zhou, 2000). (3) Assume the airline between two airports is a Great Circle, each airport is considered as one point.

3.1. Spatial distribution characteristics of atmospheric emissions from civil airports in 2015

2.5. Scenario projections on emissions for 2020–2050 To evaluate the potential effects and emission characteristics of aviation industry in the future, it is of great necessity to conduct scenario projections for exploring possible future emission trends. For nonOECD countries, available national perspectives on growth rates of aviation fuel consumption up to the year 2040 are directly adopted from EIA (U.S. Energy Information Administration) research report. In this study, we adopt the reference situation up to the year 2040 in international energy outlook 2017 (EIA, 2017) and furthermore project to the target year 2050 by using trend extrapolation with Microsoft Excel tool. Based on projections of aviation fuel consumption in international energy outlook (EIA, 2017), three scenarios are defined: Business As Usual (BAU), Strengthen Control (SC) and the Maximum Feasible Technological Reduction (MFTR) scenarios, respectively. The BAU scenario assumes that combustion efficiency of aero engines, national standard of aviation fuel and aviation emission regulations are treated the same

The multi-pollutants atmospheric emissions from 208 domestic civil airports in 2015 are summarized in SI Table S6. In this study, the peak value of multi-pollutant emissions among the 208 civil airports appeared in the Beijing Capital International Airport, at which the emissions of HC, CO, NOx, CO2, SO2, PM2.5, BC, OC and heavy metals are estimated at about 338.1 t, 4143.9 t, 6416.7 t, 1312.8 kt, 416.8 t, 33.1 t, 15.9 t, 10.6 t and 119.1 kg, respectively. The detailed emissions separated by different airports please see SI Table S6. Furthermore, the soft ArcGIS version 10.2 is used to demonstrate spatial distribution characteristics of multi-pollutant emissions from civil airports for 2015 (The data set of administration district is provided by Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences (RESDC) (http://www.resdc.cn)). Fig. 1 and SI Fig. S2 display the 36 km × 36 km gridded spatial resolution of multi-pollutant emissions in Chinese mainland for the year 2015. Emissions of these pollutants are very unevenly distributed from one airport to another, with the annual heavy metals emissions ranging from 0.9 g to 119.1 kg, for instance, due to close correlation between emissions and economic development, traffic inconvenience in Chinese mainland. The grid cells with high emission intensities of pollutants are mainly concentrated in Beijing, Shanghai, Chongqing municipalities and Guangdong, Sichuan, Yunnan provinces. Take NOx emissions for example, the emissions from the top nine busiest airports (Beijing Capital, Shanghai Pudong, Guangzhou Baiyun, Chengdu Shuangliu, Shenzhen Baoan, Shanghai Hongqiao, Kunming Changshui, Xi'an Xianyang and Chongqing Jiangbei Airport) account for about 50% of the national total NOx emissions. Xinjiang, which is a core area of the Silk Road economic belt, also shows the high emissions of atmospheric pollutants from civil aviation industry mainly because of its remote distance with eastern and central China and thus highly time-consuming and inconveniences for transit with other transportation systems. Therefore, the levels of economic development and convenience of transportation system, which are quite different from other industry emissions, have resulted in the special spatial distribution characteristics from China's civil aviation industry.

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Fig. 1. Gridded PM2.5 and NOx emission from 208 civil airports in China for the year 2015 (36 km × 36 km resolution, unit: tons per year per grid cell).

Up till now, the comprehensive and dedicated research works on multipollutant emissions of civil airports in China are still quite limited. Therefore, only several pollutants emissions calculated from typical airports are compared with previous studies (Chen, 2013; Fan et al., 2010; Huang et al., 2014; Xia et al., 2008; Xu et al., 2016). As shown in Table 2, pollutants emissions from BJA (Beijing Capital International Airport) are higher than estimated emissions from PDA (Pudong International Airport of Shanghai), BYA (Baiyun International Airport of Guangzhou), SLA (Shuangliu International Airport of Shanghai), and BAA (Bao'an International Airport of Shenzhen). Emissions of multi-pollutants represent a remarkable upward trend except PM2.5. The most important factor causing the discrepancy is the difference of emission factor of PM2.5 from LTO cycle. In this paper, according to EEA air pollutant emission inventory guidebook (EEA, 2017), we determine the emission factor of PM2.5 for LTO cycle according to different aircraft types (e.g. 0.1 kg/LTO for A310, 0.25 kg/LTO for A380), which are much lower than that used by the previous study (constant value 0.53 kg/LTO) (MEPPRC, 2015; Xu et al., 2016). Consequently, we calculate that the PM2.5 emissions from BJA are about 33.1 tons for the year 2015, obviously much lower than 150.4 tons reported in previous study (Xu et al., 2016). Overall, PM2.5 emission estimation in this study may be somewhat less than other studies due to adopting different emission factors, while our results of other pollutants emissions agree well with previous estimations. 3.2. Spatial distribution characteristics of multi-pollutants emissions of different airlines in 2015 In this study, cruise emissions of multi-pollutants for about 299 main domestic airlines are estimated based on several critical influence factors like annual flights, route distance, cargo and passenger turnover, etc. (CAAC, 2016b). Fig. 2 illustrates the spatial distribution characteristics of 299 domestic main airlines emissions for the year 2015. One of the most

significant features of the spatial distribution of domestic airlines cruise emissions is that the airline density is much higher in eastern and central China than that in northeastern and western China, and these regions are characterized by high population density, huge economy volume, as well as aviation transit convenience. Take HC emissions for example, the several most heavily airlines are routes that link between several megacities, like Beijing and Shanghai, Shanghai and Shenzhen, Chengdu and Beijing, Guangzhou and Shanghai, Guangzhou and Beijing, Beijing and Shenzhen. HC emissions of these six airlines for the year 2015 are 40.1 t, 27.1 t, 35.0 t, 24.7 t, 41.0 t and 39.4 t, of which emission intensities are 33.5 kg·km−1, 22.6 kg·km−1, 29.2 kg·km−1, 20.6 kg·km−1, 34.2 kg·km−1, 32.9 kg·km−1, respectively. The flight segments emissions from these six routes almost account for about 15.2% of the total airline emissions. Therein, the flight segment emissions for that from Chengdu to Beijing are higher than that from Shanghai to Shenzhen, though several factors such as annual flights, passenger and cargo transportation volume are higher from latter route than the former, which is mainly ascribed to the longer route distances and more cruise fuel consumption. Moreover, several airlines that move toward northwest also play a prominent role for pollutants emissions (HC, CO, NOx, CO2, SO2, PM2.5, BC, OC and heavy metals), especially the airlines between Urumqi and other mega-cities such as Beijing, Shanghai, mainly due to both the farther distance and travelling inconvenience with other transportation systems. The same situation happens on the airlines that move toward Chengdu airports. In addition, along with the rapid development of international tourism island establishment, the tourism in Hainan province is flourishing, resulting in higher pollutant emissions intensity of airline routes to Sanya and Haikou cities in the Hainan Island. In general, the airline emissions and emission intensities per kilometer demonstrate real spatial distribution features of those multi-pollutants from civil aviation industry.

Table 2 Comparison of HC, CO, NOx, SO2, PM2.5 emissions from civil airports in China (Unit: tons). Airport

Year

HC

CO

NOx

SO2

PM2.5

BJA

2015-This study 2013-Method 1 2013-Method 2 2011 2007 2015-This study 2006 2015-This study 2012 2015-This study 2011 2015-This study 2011

338.1 295.3 289.1 256.8

4143.9 3189.9 3118.1 2431.8 2542 3153.7 954.2 2876.4 1477 2061.7 1070.17 2144.7 1032.7

6416.7 7042.1 5701.6 3915.9 3735.5 4883.4 1536.4 4454.1 2936.8 3192.5 1723.1 3321 1662.7

416.8 429.4 363.5 287.4 – 317.2 112.8 289.3 188.2 207.4 126.5 215.7 122

30.6 150.4 150.4 – – 23.3 – – – 15.2 – 15.9 –

PDA BYA SLA BAA

257.3 100.8 234.7 166.6 168.2 113.2 175 109.1

Literature cited (Xu et al., 2016) (Xu et al., 2016) (Chen, 2013) (Fan et al., 2010) (Xia et al., 2008) (Huang et al., 2014) (Chen, 2013) (Chen, 2013)

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Fig. 2. 299 Domestic main flight segments and HC emissions of main airlines for the year 2015 (unit: kilograms per kilometer per year).

3.3. Emission characteristics of different flight processes in flying circulation The annual multiple pollutants emission characteristics of different operation modes for the year 2015 are summarized in Fig. 3. Emissions of multiple pollutants show great discrepancy among different operation modes (see Fig. 3a). For PM2.5, SO2/CO2/HMs and NOx, emission from cruise process constitutes the dominant contributor with a share of 89%, 92% and 81%, of the associated total emissions, respectively. It should be noted that PM2.5 emissions from LTO cycle are calculated here on an aircraft-type basis by using emission value referring from EEA guidebook, therefore PM2.5 emissions from LTO cycle as a whole, which are different from other pollutants, account for 11% of the total emissions. Furthermore, cruise process contribute 24% and 29% of the total CO and HC emissions, implying that the airports and surrounding areas are the most affected regions by those emissions from civil aviation industry, which are byproducts of incomplete fuel combustion. By contrast, the emissions characteristics of SO2, CO2 and HMs are grouped together mainly due to their emissions calculation are positively proportion with fuel consumption and component concentrations in fuel. Overall, the emissions for each pollutant are closely related to combustion states and flight duration. For pollutants emissions characteristics of different stages in LTO cycle, Fig. 3b illustrates the separate contribution to total emissions from taxiing and idle process, approach process, climb process and take-off process. Therein, four different operation modes (taxiing and idle, approach, climb and take-off) contribute about 14%, 14%, 48% and 24% of total NOx emission of LTO cycle for the year 2015, respectively. Climb mode is the dominant contributor of NOx emissions for the LTO cycle, followed by take-off process. The results are well consistent

with the previous studies, showing that NOx emissions of LTO cycle are mainly released from climb process (Stettler et al., 2011; Winther et al., 2015; Xu et al., 2016). As can be seen from SI Fig. S1, there is a linear relationship between NOx emission factor and engine thrust setting, resulting in highly contribution to the total NOx emissions of LTO cycle while climb mode was setting 85% engine thrust and took 20 min. It can be concluded that NOx emissions from civil aviation industry are associated with thrust setting of engine and flight duration. For SO2, CO2 and HMs, emissions contributions of those pollutants are proportional to fuel consumption of different operation modes. It is noteworthy that the contributions to HC and CO emission of LTO cycle from climb, take-off and approach modes are far less than taxiing and idle process, which is quite different from other pollutants. It is because emissions of HC and CO from jet engine are mainly caused by incomplete combustion of aviation fuel (Herndon et al., 2006) and 26 min as well as 7% engine thrust are demanded for this process while 100% engine thrust for take-off mode, 30% engine thrust for approach process (Fan et al., 2012; ICAO, 2014). Consequently, there are notably different emission characteristics from different flight processes due to various combustion status of aviation fuel. 3.4. Historical trends of air pollutants emissions From 1980 to 2015, the volumes of passenger turnover and cargo turnover in mainland China have increased from 2.8 billion person kilometers and 0.074 billion ton kilometers to 556.6 billion person kilometers and 6.7 billion ton kilometers, respectively (CAAC, 2016b). Meanwhile, the related atmospheric pollutants emissions from Chinese domestic civil aviation industry have increased dramatically

Fig. 3. Emission contribution rates of different operation modes for the year 2015 (a: contribution to emissions from the whole process; b: contribution to emissions from different processes of LTO cycle).

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accompanied by a huge increase in GDP or per capita GDP. Fig. 4 demonstrated the temporal trend of emissions from domestic civil aviation industry over China in a calendar year from 1980 to 2015 (detail emissions see SI Tables S7 and S8). The top value of annual total emissions of pollutants appeared in the year 2015, of which HC, CO, NOx, CO2, SO2, PM2.5, BC, OC and heavy metals are estimated at about 4.77 kt, 59.63 kt, 304.77 kt, 59,961 kt, 19.04 kt, 3.32 kt, 1.59 kt, 1.06 kt and 5.44 t, respectively, while the minimum emissions occurred in start point of 1980 (see SI Tables S7 and S8). We estimate that heavy metals emissions have increased from 73 kg in 1980 to the peak value at about 5440 kg in 2015. Take Pb emission for example, we calculate Pb emission in 2012 is about 747 kg, which is closely consistent with pervious study (Tian et al., 2015). Moreover, we found that there is a high correlation between the major pollutants emissions of aviation industry with the national GDP or GDP per capita from 1980 to 2015. Take PM2.5 emissions as an example, the coefficient of correlation between them is over 98%. This suggests that emissions from Chinese domestic civil aviation industry are closely linked to the growth in economy of China and the increasing demand for rapid and convenient travelling. Compared with previous studies (Xue et al., 2016a; Xue et al., 2016b; Zhu et al., 2016), our results demonstrate that atmospheric emissions of CO, NOx from China's civil aviation cannot be neglected, especially for the surrounding areas of large-scale airports in mega-cities like Beijing, Shanghai and Guangzhou. Due to quite limited studies on emission estimations of various pollutants on aviation industry, we chose the estimated emission of CO, NOx, CO2, and SO2 to compare with previous studies (Fan et al., 2012; Xu et al., 2016). Fan et al. established emission inventories from civil aviation for China in the single year of 2010, CO, NOx, CO2, SO2 emissions are estimated at 39.7 kt, 154.1 kt, 38,210 kt and 9.7 kt (Fan et al., 2012), which are comparable with our results of 39.27 kt, 200.7 kt, 36,659 kt and 11.6 kt in this study for the same year 2010. With regard to SO2 emission, different emission factors are thought to be the main causes of this discrepancy. Ma and Zhou (2000) developed a three-dimensional (1° longitude × 1° latitude × 1 km altitude) inventory of aviation NOx emissions over China from 30 March 1997 to 20 March 1999, they estimated the NOx emissions were 1.22 × 105 kg·day−1 and equivalent to 44.5 kt·yr−1, which is closely agreement with our results of 52.1 kt for the whole year 1997 in this study. Therefore, we can conclude that this comprehensive emission inventory which is dedicated to China's civil aviation industry is comparable and reasonable compared with previous studies. 3.5. Scenario analysis for future emission trends of 2020–2050 Based on the assumptions elaborated under the three scenarios (BAU, SC, MFTR scenarios), future emission trends of multi-pollutants from China's domestic aviation industry are analyzed and projected, as shown in Fig. 5 and SI Table S9. In the Business as usual scenario, typical pollutants are projected to increase nearly 2 times between 2015 and 2050 under the assumption that there is no obvious development on

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new technology/material of aero engine and the aviation fuel continue to increase rapidly. Heavy metals emissions from aviation industry are expected to gradually increase year by year due to no relevant values limit in national aero fuel standard under this scenario. Under SC scenario, we calculate that those air pollutants emissions (HC, SO2, PM2.5 and HMs) present a slowly increase trend compared with their emissions in the base year 2015. One possible reason is that the degradation of emission factors due to new technology development can't offset the influence caused by increasing consumption of aero fuel accompanied with human activities and China's economy continues to increase. Notwithstanding, there is a benefit of reducing about 11%–20% heavy metals emissions compared with BAU scenario and that demonstrate a slowly increase trend of air pollutants emission under the SC scenario. Under the MFTR scenario, we estimate that HC emission will increase from 4.46 kt in 2020 to the peak value at about 4.95 kt in 2040 and then decline slowly in the following future 10 years. Hydrocarbon emissions from domestic aviation are estimated about 4.47 kt in 2050 with 0.3 kt of emission reduction compared with the base year of 2015. A higher reduction of 40%–66% of MFTR scenario for HC, SO2, PM2.5 and HMs emissions for the 2050 can be obtained. Furthermore, emissions of SO2, PM2.5 and heavy metals in 2050 are slightly higher than those in the base year of 2015. In conclusion, the emission reduction from the improvement of new technology or new national standard between 2015 and 2050 would be largely offset by the rise in multi-pollutants emissions from aero fuel growth rapidly. 3.6. Uncertainly analysis This comprehensive emission inventory of multiple pollutants is compiled by using the approach of combining bottom-up with topdown based on detailed data of domestic aviation industry in Chinese mainland. There are two aspects of uncertainties affecting the accuracy of our estimate, uncertainties from activity level and uncertainties from emission factors. For activity level, the discrepancies between collected flight planning schedules and actual flight schedules on accounting of particular extreme weather, emergency landing, and traffic control etc., can affect flight duration and fuel consumption. However, the LTO cycle numbers of official statistics are less affected by those influence factors. In addition, simplifying assumption about the engine thrust setting and modes duration defined by ICAO may deviates from actual situation of every flight. For instance, the average daily height of actual atmospheric boundary layer change with temperature fluctuates in a range from 500 to 2000 m by statistical analysis of lidar data and reaching highest level at 14 o'clock (Davies et al., 2007), comparing with the widely adopted constant value of 3000 ft (equal to 914 m) as LTO cycle upper limit of height. Xu et al. (2016) developed the Beijing Capital International Airports emission inventory, which fully considering the fact that atmospheric boundary height changes with temperature using AMDAR (Aircraft Meteorological Data Relay) data. In general, airports emissions are relatively reliable because the majority

Fig. 4. Historical trend of air pollutants emissions from domestic aviation industry of China, 1980–2015.

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Fig. 5. Scenario projections of air pollutants from domestic aviation industry, 2020–2050.

of the activity level, including airplane type, flight numbers, aircraft/engine combination information, are collected from related statistical materials and online websites. However, compared to conventional pollutants, we have less confidence about the estimated HMs emissions due to the lack of field measurement data and there are no limit values of these metals in related aviation fuel standards whether overseas or China interiorly. The uncertainties in emissions of HC, CO and NOx are relatively low, because those emission estimations are based on actual flight movement data, which considering flight type, engine type and different LTO processes. Uncertainties lie in emission factors of adopted bottom-up calculation approach in this study are thought to approximately 5–10% (EEA, 2017). PM2.5 has moderate uncertainties ranked behind HC, CO and NOx, whose calculation methodology is based on aircraft types. SO2 and CO2 emissions have relatively higher uncertainties than PM because of the simple calculation approach, which is only based on volume of fuel consumption data, simplified the complexity of actual process to some extent. The uncertainty may lie between 20 and 30% for LTO factors according to EEA guidebook. 4. Conclusions We have estimated emissions of multiple pollutants for the 208 civil airports as well as emissions of 299 main domestic flight segments from civil aviation industry in Chinese mainland for the year 2015. Further, we investigated historical emissions during the period of 1980–2015 and forecasted future trends from aviation industry until 2050 under three scenarios. An approach of combining bottom-up with top-down was established to compile the comprehensive emission inventory based on detailed statistical data about flight information, aircraft/engine matching information and adopting multiple types of emission factors recommended by ICAO such as aircraft-type based, engine-type based and fuel-based. From 1980 to 2015, the total atmospheric emissions (including airports emissions and cruise emissions) of HC, CO, NOx, CO2, SO2, PM2.5, BC, OC and heavy metals from domestic civil aviation industry have increased dramatically accompanied by a huge increase in GDP and aviation fuel consumption. The spatial distribution results show that air pollutant emissions from domestic civil airports are very unevenly from one place to another. Among the 208 domestic civil airports, Beijing Capital International Airport ranks as the largest contributor, accounting for about 10% of total airports emissions for the year 2015. Furthermore, we have developed emission databank of main domestic flight segments for Chinese mainland in 2015. One of the most significant features of the spatial distribution of domestic airlines is that the airline density is much higher in central and eastern China than that in northeastern and western China, and these regions are characterized by high population density, huge economy volume, as well as transit convenience. Moreover, our results show that the emissions from cruise process constitute the dominant contributor for PM2.5, SO2/CO2/HMs

and NOx while LTO cycle process represents the mainly contributor for HC and CO emissions, implying that airports and the surrounding areas are the most affected regions by HC and CO pollutants. Under the BAU scenario, typical pollutants emitted from civil aviation industry would increase nearly 2 times in 2050 compared with that in 2015. In general, the emission reduction from the improvement of new technology or new national standard between 2015 and 2050 would be largely offset by the rise in multi-pollutants emissions from aero fuel growth rapidly. The overall uncertainties in our high resolution inventory are thought to be acceptable with the data availability. Nevertheless, to achieve more accurate estimations from aviation industry, more detailed investigations and field tests for all kinds of aircraft engines are still greatly needed in the future. In conclusion, the high resolution emission inventories of multiple pollutants can help to better understand the current air pollution situations of civil aviation and develop more niche targeting pollution control measures and policies. Indeed, to mitigate the related atmospheric pollution and health risks caused by civil aviation, it is of great importance to tighten the fuel standards, develop renewable energy, as well as improve the combustion technology.

Acknowledgment This work was funded by the Trail Special Program of Research on the Cause and Control Technology of Air Pollution under the National Key Research and Development Plan of China (2016YFC0201501), the National Natural Science Foundation of China (21777008 and 21377012), and the National Key Scientific and Technological Project on Formation Mechanism and Control of Heavily Air Pollution (DQGG0209). Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2018.07.407.

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