What Inﬂuences the Cross-Border Air Pollutant Transfer in China–United States Trade: A Comparative Analysis Using the Extended IO-SDA Method

: This paper extends the IO-SDA (input–output and structural decomposition analysis) method to decompose the CBAPT (cross-border air pollutant transfer) into di ﬀ erent e ﬀ ects, and reveals the status of CBAPT and analyzes inﬂuencing factors a ﬀ ecting the CBAPT in China–US trade by comparing China with the US in these factors. This study found that China was a net air pollutant exporter, and this indicates the air pollutants were transferred from the US into China through China–US trade. On the whole, the China energy intensity, China emission coe ﬃ cient, and import scale e ﬀ ects decreased the CBAPT, whereas the export scale and US emission coe ﬃ cient e ﬀ ects increased the CBAPT; the inﬂuences of export structure, US energy intensity, and import structure on CBAPT were uncertain. The sectoral distribution of e ﬀ ects on the CBAPT in China–US trade was unbalanced, which was mainly concentrated in heavy industry and transportation. The China energy intensity, China emission coe ﬃ cient, and import scale e ﬀ ects inhibited sectoral CBAPT, and the export scale e ﬀ ect promoted this sectoral transfer. Other e ﬀ ects on the sectoral transfer were negligible. This paper provides some policy suggestions based on empirical results. the The main are as follows the


Introduction
Pollution transfer is a major issue in the research area of the relationship between trade and environment, and it is mainly concentrated on the cross-border transfer caused by the trade between developed and developing countries. Scholars have put forward the hypothesis of "environmental cost transfer", which means that the international trade may lead to the transfer of environmental pollution from developed to developing countries due to the differences in economic structure, trade structure, and environmental regulation [1]. The US and China are the world's first and second largest economies, respectively. China-US trade has a significant impact not only on China and the US, but also on the world economy. The international trade development between China and the US is of great potential in the long term despite the trade friction in the short term [2]. Thus, China-US trade is the sulfur oxides (SO x ), and non-methane volatile organic compounds (NMVOC) in China-Russian trade, and found that China has become a "pollution heaven" [38], which is consistent with the results of Yu and Chen (2017) [25]. These results indicate that the expansion of export to Russia was the main reason for the increases in EAPs from China's export to Russia, and the progress of emission reduction technology restrained the growth of EAPs.
The current literature presents the following features. First, the existing literature mainly concentrated on embodied carbon issues, while few touched on the EAPs. The current relative studies are only found in the study by Lin and Xu (2019) [38], but in this study the important air pollutant (PM 2.5 ) emissions were not considered in the China-Russian trade. In addition, the China-Russian trade value accounts for only about 2% of China's total, whose influence is less compared with China-US trade. Second, the previous literature focused on embodied emissions in China's exports into the US and imports from the US [28]. However, few studies conducted the analysis in the term of cross-border emission transfer. Third, the IDA and SDA methods were both widely used in the studies on factors influencing embodied emissions; the advantage of the SDA method is that this method can take both direct and indirect effects of various factors into account, and can easily compare the factors affecting cross-border pollutant transfer based on IO table data [39]. However, the current research on bilateral trade using the SDA method mainly focused on embodied carbon, few studies conducted an in-depth analysis of the cross-border transfer of major air pollutants.
For the research gap, this paper extends the SDA method to decompose the CBAPT into different effects, and discusses the influencing factors for CBAPT in China-US trade from 2005 to 2015 by comparing China with the US in these factors. This study can provide the following novelties in the relative research area. First, this paper establishes the relationship between China and the United States in terms of economy, trade, energy consumption, and emissions based on the input-output tables of China and the US, and incorporates the emission coefficients, trade structures, and energy intensities of the two countries into the input-output and structural decomposition analysis (IO-SDA) model, which expands the traditional IO-SDA decomposition model for a single country. This is conducive to analysis of the impact of differences between China and the United States in influencing factors on CBAPT. Second, it is easy to point out the key driving and inhibiting factors and the extent of influences of these factors for CBAPT in China-US trade, through analyzing the differences in emission coefficient, trade structure, and energy intensity between China and the United States, which can provide the basis for the relevant policy formulation.

Methodology
The IO relationship can be expressed as, where A, X, and Y represent the direct consumption coefficient matrix, sectoral total output column vector, and final product column vector, respectively. Assuming that, a ij = x ij /x j, and x ij denotes the value of sector j's input from sector i; then x j , represents sector j's total output. The complete consumption coefficient matrix B is: where (I−A) −1 is the Leontief inverse matrix; I is an identity matrix; the corresponding elements of and ex i represent sector i's output, import, and export, respectively. A m should be deducted in this calculation because the production of imported intermediate products occurs abroad. Thus, Equation (2) can be rewritten as, Sector j's complete energy consumption intensity can be expressed as, where e i is energy consumption of sector I, e i /x i denotes sector i's energy intensity (energy consumption per unit output). Sector j's air pollutant emission coefficient (EI j ) can be written as, where AP j and E j stand for air pollutant emissions and energy consumption of sector j, respectively. Thus, sector j's EAPs in the export (EA j EX ) can be defined as, where EX j is sector j's export value. Assuming that IM j denotes sector j's import value, the EAPs in sector j's import can be expressed as, Thus, the CBAPT from the US into China in China-US trade (EA j NET ) can be written as, Equation (8) can be rewritten as follows, combined with Equations (6) and (7), where CE j China and CE j US respectively represent complete energy consumption intensity in China and the US. EI j China and EI j US respectively represent sector j's air pollutant emission coefficient for China and the US. S EX and S IM respectively denote China's export and import structures in China-US trade. EX and IM are China's total export value into, and total import value from, the US, respectively. Thus, where AP j China and AP j US respectively stand for sector j's air pollutant emissions in China and the US, respectively. E j China and E j US are sector j's energy consumption in China and the US, respectively.
Through the two-polar decomposition method [40], the changes in CBAPT in China-US trade (∆EA NET ) between the 0 period and 1 period can be expressed as, import scale e f f ect (∆IM) Equation (14) can be used to decompose the CBAPT in China-US trade over different periods. The China energy intensity (denoted by ∆I China ), China emission coefficient (denoted by ∆C China ), export structure (denoted by ∆S ex ), export scale (denoted by ∆EX), US energy intensity (denoted by ∆I US ), US emission coefficient (denoted by ∆C US ), import structure (denoted by ∆S im ), and import scale effects (denoted by ∆IM) respectively reflect the impacts of changes in direct and indirect energy consumption per unit output (energy consumption intensity) in China, EAPs per unit energy consumption (EAP emission coefficient) in China's export into the US, China's proportional export into the US for different sectors, China's total export into the US, energy consumption intensity in the US, EAP emission coefficient in China's import from the US, China's proportional import from the US for different sectors, and China's total import from the US, on CBAPT from the US into China.

Data Sources
China's relevant data mainly come from its statistics and official databases. The relevant data of the US come from its statistics and international official databases, so multiple data sources were used in this study. China's and the US IO tables are respectively taken from the "China Statistical Year book" and the website of the World Input-Output Database (WIOD). The data on trade values came from the "China Trade and External Economic Statistical Yearbook". The data on RMB exchange rate to USD in 2005-2015 were from the "China Statistical Yearbook". The data for fossil energy consumed in China and the US were from the "China Statistical Yearbook" and the US Energy Information Administration (EIA), respectively. China's air pollutant emissions (SO 2 , NO x , and PM 2.5 ) were from the "China Statistical Yearbook", the China environment protection database, and emission inventory database from Tsinghua University [41][42][43]. The data for air pollutant emissions in the US were obtained from the United States Environmental Protection Agency (EPA) and the Emission Database for Global Atmospheric Research (EDGAR).
In this paper, the data mentioned above are processed as follows. Considering the consistency with sectoral division, this paper divided the national economy for China and the US into 12 sectors, based on China's 42-sector and America's 56-sector input-output tables, China's and America's 21-sector export and import data, China's 47-sector and America's five-sector energy consumption data, and China's 12-sector and America's 13-sector air pollutant data (Table 1).

Sector Code Sector
Sector 1 Agriculture, forestry, animal husbandry, and fishery Sector 2 Metal manufacture Sector 3 Non-metallic mineral products Sector 4 Coke and refined petroleum Sector 5 Chemical industry Sector 6 Mining and quarrying Sector 7 Food manufacture Sector 8 Textile manufacture Sector 9 Paper manufacture Sector 10 Other industries Sector 11 Commerce Sector 12 Transportation The data on currency variables were adjusted based on the year 2005, and the price indices for different sectors in China and the US were respectively calculated based on the producer price indices (price indices of 2005 = 100), which came from the corresponding period in the "China Statistical Yearbook" and the "United States Statistical Yearbook".

The Status of CBAPT in China-US Trade
The trends of changes in SO 2 and NO x embodied in China's export into the US showed an "inverted V" shape (   In recent studies, some scholars found that the trade surplus was a driving factor for the increment of embodied energy consumption in China-EU trade [44]. Comparison with the change trends of trade value in China-US trade indicates a huge trade surplus for China from 2005 to 2015. The net export value presented an upward trend apart from a slight decline due to the financial crisis in 2009 ( Figure 2). However, the CBAPT from the US into China showed a declining trend over the study period. This indicates that the trade surplus played a small role in the CBAPT in China-US trade. Although they had a declining trend, China's EAPs per unit export value into the US were still much higher than the US EAPs per unit export value into China from 2005 to 2015 ( Figure 3). This was because of the large share of coal and other high-pollution energy consumption in China's production. The proportion of coal consumption covered 65.97%-72.72% during 2005-2015, which was much greater compared with the US (17.86%-24.73%). Moreover, there were differences in the energy consumption structure and energy efficiency between the two countries.  In recent studies, some scholars found that the trade surplus was a driving factor for the increment of embodied energy consumption in China-EU trade [44]. Comparison with the change trends of trade value in China-US trade indicates a huge trade surplus for China from 2005 to 2015. The net export value presented an upward trend apart from a slight decline due to the financial crisis in 2009 ( Figure 2). However, the CBAPT from the US into China showed a declining trend over the study period. This indicates that the trade surplus played a small role in the CBAPT in China-US trade. Although they had a declining trend, China's EAPs per unit export value into the US were still much higher than the US EAPs per unit export value into China from 2005 to 2015 ( Figure 3). This was because of the large share of coal and other high-pollution energy consumption in China's production. The proportion of coal consumption covered 65.97%-72.72% during 2005-2015, which was much greater compared with the US (17.86%-24.73%). Moreover, there were differences in the energy consumption structure and energy efficiency between the two countries. In recent studies, some scholars found that the trade surplus was a driving factor for the increment of embodied energy consumption in China-EU trade [44]. Comparison with the change trends of trade value in China-US trade indicates a huge trade surplus for China from 2005 to 2015. The net export value presented an upward trend apart from a slight decline due to the financial crisis in 2009 ( Figure 2). However, the CBAPT from the US into China showed a declining trend over the study period. This indicates that the trade surplus played a small role in the CBAPT in China-US trade. Although they had a declining trend, China's EAPs per unit export value into the US were still much higher than the US EAPs per unit export value into China from 2005 to 2015 ( Figure 3). This was because of the large share of coal and other high-pollution energy consumption in China's production. The proportion of coal consumption covered 65.97%-72.72% during 2005-2015, which was much greater compared with the US (17.86%-24.73%). Moreover, there were differences in the energy consumption structure and energy efficiency between the two countries.  Comparison with EAP emission coefficients in various sectors shows that the US emitted less EAPs per unit energy consumption than China on the whole (Table 2). From a sectoral perspective, embodied pollutant emission coefficients in China's Sectors 1, 5, 6, and 9 from 2005 to 2015 were sometimes lower than these coefficients in the same sectors for the US. The US has realized the mechanization of agriculture and other primary productions, and has been developing towards modernization, specialization, and technology. However, the large-scale application of machinery brought more energy consumption and higher pollutant emission coefficients for these sectors.  2014) suggested that a large amount of coal consumption was closely related to higher pollutant emission coefficients [45]. China's export were mainly concentrated in Sectors 2, 8, and 10, and most of these sectors had higher emission coefficients when compared with the US. In addition, China's import from the US were concentrated in Sectors 1, 5, and 11, and the emission coefficients in these sectors were lower when compared with the US.   Comparison with EAP emission coefficients in various sectors shows that the US emitted less EAPs per unit energy consumption than China on the whole (Table 2). From a sectoral perspective, embodied pollutant emission coefficients in China's Sectors 1, 5, 6, and 9 from 2005 to 2015 were sometimes lower than these coefficients in the same sectors for the US. The US has realized the mechanization of agriculture and other primary productions, and has been developing towards modernization, specialization, and technology. However, the large-scale application of machinery brought more energy consumption and higher pollutant emission coefficients for these sectors.  2014) suggested that a large amount of coal consumption was closely related to higher pollutant emission coefficients [45]. China's export were mainly concentrated in Sectors 2, 8, and 10, and most of these sectors had higher emission coefficients when compared with the US. In addition, China's import from the US were concentrated in Sectors 1, 5, and 11, and the emission coefficients in these sectors were lower when compared with the US.

Influencing Factors for CBAPT in China-US Trade
Equation (14) was used to decompose the CBAPT from the US into China in China-US trade (∆EA NET ) over different periods. Table 3 shows that the effects on the changes in the CBAPT and their contributions over different periods. On the whole, the China energy intensity, China emission coefficients, and import scale effects inhibited the CBAPT from the US into China, among which the China emission coefficient effect was a key factor. The US emission coefficient and export scale effects greatly promoted the CBAPT from the US into China. The export structure, US energy intensity and import structure effects, contributed positively or negatively to the CBAPT.    [46]. In the 12th FYP (2011-2015), the requirement for decreasing energy intensity by 16% was put forward. During the 13th FYP (2016-2020), the target was clearly declared that the energy intensity would be reduced by 15% by 2020 compared with 2015 s level. China has made a great progress in decreasing energy intensity. Figure 4 indicates that China's energy intensity went down from 2005 to 2015. According to China statistics, China's energy intensity declined by 4.5% in 2014, and this was the largest degree of decline since 2008. However, China's economic growth rate was on a declining trend from 2012 to 2015, and the emission reduction was neglected in some places for maintaining steady economic growth. Additionally, the decreases in energy prices, such as coal and crude oil, led to the decline in enthusiasm of energy conservation and emission reduction for enterprises, and the long-term development of energy saving transformation also limited the promotion space for enterprises in the future [47]. Thus, the energy intensity in China went down during the study period, but this degree of decline decreased. The inhibitory impact of China's energy intensity effect on CBAPT decreased as well. The energy intensity for the US was stable, which increased steadily from 2005 to 2010, and then decreased from 2010 to 2015. The US Obama administration proposed to "bring manufacturing back" in 2009 to create more jobs and develop the US economy because of the financial crisis in 2008. The "bring manufacturing back" proposal inevitably intensified energy consumption, so the energy consumption per unit output for the US increased during 2008-2010. Barkhordari and Fattahi (2017) suggested the decline in energy intensity was induced by energy price reduction and technological changes [48]. At the end of 2013, the US announced the withdrawal of quantitative easing policy. The USD exacerbated the decline in energy price, so the energy intensity showed a downward trend during this period. As one of the highest energy efficiency countries, the US will not greatly change the energy intensity through the adjustment of energy use proportion or progress of cleaner production technology. Therefore, the US energy intensity had a relatively small effect on the CBAPT, which was consistent with Xu et al. of 2013, the US announced the withdrawal of quantitative easing policy. The USD exacerbated the decline in energy price, so the energy intensity showed a downward trend during this period. As one of the highest energy efficiency countries, the US will not greatly change the energy intensity through the adjustment of energy use proportion or progress of cleaner production technology. Therefore, the US energy intensity had a relatively small effect on the CBAPT, which was consistent with Xu et al.

Emission Coefficient Effect
The China emission coefficient had a great inhibitory effect on CBAPT from the US into China. This effect respectively reduced the volumes of SO 2 , NO x , and PM 2. Comparing China's air pollutant emission coefficients with the US (Figure 6), the emission coefficients in China are significantly higher. This indicates that the emission efficiency for the US was higher than China on the whole. China's emission coefficients presented a decreasing trend, reflecting the promotion of China's emission efficiency. The SO2 and NOx emission coefficients in the US decreased, but the PM2.5 emission coefficient increased slightly. Further analysis shows that the change trend of emission coefficient effect in China was consistent with the change trend of SO2, NOx, and PM2.5 emission coefficients from 2005 to 2015 (Figure 7). This indicates the effect of emission coefficient on CBAPT mainly depended on the change of China's emission efficiency. However, the US had low proportional coal consumption ( Figure 5). The coal consumption in the US presented a declining trend on the whole, and the oil and gas consumption accounted for a great proportion; the "low carbonization" characteristic for the US economy is obvious. The US has formed a service-dominated economic mode since the mid-1990s, and the proportion of industry declined. The proportion of manufacturing industry for the US was less than 11% by 2015, whereas the US imported industrial products from China accounted for 96.32% of its total, which resulted in the CBAPT into China.
Comparing China's air pollutant emission coefficients with the US (Figure 6), the emission coefficients in China are significantly higher. This indicates that the emission efficiency for the US was higher than China on the whole. China's emission coefficients presented a decreasing trend, reflecting the promotion of China's emission efficiency. The SO 2 and NO x emission coefficients in the US decreased, but the PM 2.5 emission coefficient increased slightly. Further analysis shows that the change trend of emission coefficient effect in China was consistent with the change trend of SO 2 , NO x , and PM 2.5 emission coefficients from 2005 to 2015 (Figure 7). This indicates the effect of emission coefficient on CBAPT mainly depended on the change of China's emission efficiency. coefficients in China are significantly higher. This indicates that the emission efficiency for the US was higher than China on the whole. China's emission coefficients presented a decreasing trend, reflecting the promotion of China's emission efficiency. The SO2 and NOx emission coefficients in the US decreased, but the PM2.5 emission coefficient increased slightly. Further analysis shows that the change trend of emission coefficient effect in China was consistent with the change trend of SO2, NOx, and PM2.5 emission coefficients from 2005 to 2015 (Figure 7). This indicates the effect of emission coefficient on CBAPT mainly depended on the change of China's emission efficiency.  From a sectoral perspective (Table 4), Sectors 3, 10, and 12, were with the high emission coefficients in China from 2005 to 2015, followed by Sectors 1,9,and 10. This indicates that the emission efficiency for these sectors was relatively low. These sectors account for a considerable proportion of export into the US (Table 5). For example, the export shares for Sector 10 reached 65.09% (2005)-67.73% (2012) from 2005 to 2015. Meanwhile, China's total SO2, NOx, and PM2.5 emissions in the exports into the US were all more than 300 kt. In addition, Sector 10 also had the highest emission coefficient among all sectors in the US, and its export share into China was more than 45%. This means that the US also emitted a large amount of air pollutants from its exports into China. The emissions in the US were far less than the emissions in China because of the cleaner production technology and more advanced end-treatment level. This resulted in a large amount of CBAPT from the US into China.

Trade Structure Effect
The export structure effect increased the volumes of SO2 and NOx transferred into China by 3.0 and 32.6 kt, respectively, from 2005 to 2015, whereas the export structure effect decreased the volume of PM2. From a sectoral perspective (Table 4), Sectors 3, 10, and 12, were with the high emission coefficients in China from 2005 to 2015, followed by Sectors 1, 9, and 10. This indicates that the emission efficiency for these sectors was relatively low. These sectors account for a considerable proportion of export into the US (Table 5). For example, the export shares for Sector 10 reached 65.09% (2005)-67.73% (2012) from 2005 to 2015. Meanwhile, China's total SO 2 , NO x , and PM 2.5 emissions in the exports into the US were all more than 300 kt. In addition, Sector 10 also had the highest emission coefficient among all sectors in the US, and its export share into China was more than 45%. This means that the US also emitted a large amount of air pollutants from its exports into China. The emissions in the US were far less than the emissions in China because of the cleaner production technology and more advanced end-treatment level. This resulted in a large amount of CBAPT from the US into China.

Trade Structure Effect
The export structure effect increased the volumes of SO 2 and NO x transferred into China by 3.0 and 32.6 kt, respectively, from 2005 to 2015, whereas the export structure effect decreased the volume of PM 2.   The import scale effect significantly reduced the SO 2 , NO x , and PM 2.5 transferred into China, whose contribution was negative during each period. From 2005 to 2015, this inhibitory effect on SO 2 transfer decreased and then increased, and gradually increased the NO x and PM 2.5 transfer. The US is China's largest export market and the third largest import source [49]. From 2005 to 2015, the export into the US increased from 169.52 to 379.70 billion USD, with an increase by 123.99%. During the period of 2005-2007, China's economy developed rapidly. As one of the "troikas" driving the economic growth, China's export rose by 60.12%, of which the exports into the US increased by 34.76%. The foreign demand decreased due to the financial crisis in 2008, and the growth rate of China's exports into the US declined slightly, dropping by 65.77% from 2005-2007 to 2007-2010. Over this period, the export scale effect changed from promoting to inhibitory. Over the next few years, the exports continued to increase, rising by 48.54% in 2015 compared with 2010, and the growth rate increased from 17.93% to 25.96% (Figure 9). Accordingly, the export scale effect on the CBAPT increased as well. The import from the US increased by 2.25 times from 2005 to 2015, and the import growth rate decreased and then increased, so the inhibition of import scale effect on the SO 2 transfer into China decreased and then increased. The exports into the US were two to three times greater than its imports from 2005 to 2015. The huge trade surplus also led to the CBAPT from the US into China to a certain extent. It can be predicted that the export scale into the US may be reduced due to the China-US trade frictions, and this may weaken the promoting trade scale effect on the CBPT in the future.
increased as well. The import from the US increased by 2.25 times from 2005 to 2015, and the import growth rate decreased and then increased, so the inhibition of import scale effect on the SO2 transfer into China decreased and then increased. The exports into the US were two to three times greater than its imports from 2005 to 2015. The huge trade surplus also led to the CBAPT from the US into China to a certain extent. It can be predicted that the export scale into the US may be reduced due to the China-US trade frictions, and this may weaken the promoting trade scale effect on the CBPT in the future.

Conclusions and Policy Suggestions
The original idea of this work is that the status of emission cross-border transfers and their driving factors can be revealed through the international trade links between different countries. In this regard, the US and China's IO tables and air pollutant emission dataset are used in this empirical study. The proposed framework can be applied to other aggregate indicators and extended to multicountry analysis. This paper extends the SDA method to decompose the CBAPT into the energy intensity effect, emission coefficient effect, trade structure effect, and trade scale effect from the twonational perspectives, and discusses the influencing factors for CBAPT in China-US trade through comparison of China with the US. The main conclusions are as follows through the results above.
(1) China was a net air pollutant exporter, and the CBAPT from the US into China existed in China-US trade. (2) On the whole, the China energy intensity, China emission coefficient, and import scale had great inhibitory effects on the CBAPT from the US into China, while the increases in CBAPT were induced by the export scale and US emission coefficient effects; the influences of export structure, US energy intensity, and import structure were uncertain on the CBAPT. (3) The sectoral distribution of effects on the CBAPT from the US into China in China-US trade was unbalanced, which was mainly concentrated in the heavy industry and transportation, such as Sectors 3, 5, 10, and

Conclusions and Policy Suggestions
The original idea of this work is that the status of emission cross-border transfers and their driving factors can be revealed through the international trade links between different countries. In this regard, the US and China's IO tables and air pollutant emission dataset are used in this empirical study. The proposed framework can be applied to other aggregate indicators and extended to multi-country analysis. This paper extends the SDA method to decompose the CBAPT into the energy intensity effect, emission coefficient effect, trade structure effect, and trade scale effect from the two-national perspectives, and discusses the influencing factors for CBAPT in China-US trade through comparison of China with the US. The main conclusions are as follows through the results above.
(1) China was a net air pollutant exporter, and the CBAPT from the US into China existed in China-US trade. (2) On the whole, the China energy intensity, China emission coefficient, and import scale had great inhibitory effects on the CBAPT from the US into China, while the increases in CBAPT were induced by the export scale and US emission coefficient effects; the influences of export structure, US energy intensity, and import structure were uncertain on the CBAPT. (3) The sectoral distribution of effects on the CBAPT from the US into China in China-US trade was unbalanced, which was mainly concentrated in the heavy industry and transportation, such as Sectors 3, 5, 10, and 12; the China energy intensity, China emission coefficient, and import scale effects inhibited sectoral CBAPT; the export scale effect promoted this sectoral transfer, and other effects on the sectoral transfer were negligible.
Future studies will use the extended SDA method to analyze whether China-US trade promotes or reduces the total amount of air pollutant emissions for the two countries, and explore the impact of China-US trade frictions on the CBAPT considering the current China-US trade situation. The following policy suggestions are put forward based on these conclusions.
We looked at adjusting trade division and accelerating industrial transformation. Most of China's exports into the US are resource-, capital-and labor-intensive, while its imports from the US are mainly technology-intensive. Accelerating the transformation and upgrading China's industrial structure is an effective measure to improve social productivity and reduce air pollutant emissions. The volumes of SO 2 , NO x , and PM 2.5 transferred from the US into China showed a downward trend from 2005 to 2015, indicating that China's international division in China-US trade had been improved. Thus, in order to change China's trade status as a net air pollutant exporter, it is necessary to improve China's international division position; transform and upgrade traditional dominant industries (such as textiles, machinery, optics, and other manufacturing industries); cultivate and develop new industries (such as information, electronics, new materials and bioengineering), rebrand the new competitive advantages of traditional industries; and improve international comprehensive competitiveness. In addition, the industrial structure should be adjusted to accelerate the development of industry towards innovation driven, intelligent manufacturing, and low carbon.
In terms of optimizing the trade structure and restricting the high-emission sectoral export, the expansion of China's exports into the US is an important reason for promoting the CBAPT into China, but the export restrictions will inevitably hinder economic development. Thus, China should optimize its trade structure by increasing the added value of export products, improving export quality and enriching the types of export products, so as to reduce the promotion of export scale effect on the CBAPT into China. The export from high-emission sectors, such as Sectors 2, 3, and 10, greatly promoted the CBAPT into China, while the import from these sectors were conducive to reducing air pollutant emissions. Therefore, China should reduce domestic air pollutant emissions through some trade measures, such as reducing the export of high-emission sectors and reducing the import tariffs on high-emission products. Moreover, China should optimize the resource allocation in heavy industries, guide the social resources to flow into the low-pollution industries, and vigorously support the development of modern industries, such as the internet, microelectronics, new energy, and ecotourism.
We also considered the adoption of scientific and technological innovations to reduce China's emission coefficient and improve its energy efficiency. The China energy intensity and China's emission coefficient effects greatly inhibited the CBAPT from the US into China. Thus, China should attach full importance to this advantage, and further improve China's emission efficiency and energy efficiency. First, China can learn from the experience of developed countries in energy conservation and emission reduction, draw on their successful policies and guidelines, refer to their emission regulations, and use high standards to limit production emissions. For example, at the beginning of the 21st century, the US issued more than 10 policies and regulations to promote energy conservation and emission reduction, and adopted strict legislation to restrain the high consumption and pollution behavior of the government and enterprises. Now, Japan strongly supports and encourages energy-saving and emission-reduction activities. Through financial allocation, the Japanese government vigorously supports research institutions in developing energy-saving technologies, and subsidizes energy-saving products. Secondly, more attention should be paid to production details and emission links, to encourage the transformation and innovation of production equipment, phase out the backward production mode, and strengthen the emission supervision. Detailed air pollutant treatment standards should be established for each type of emissions to ensure that all production processes should meet these standards. Third, governments should encourage the development and application of clean energy and replace high-pollution energy with clean energy. It is necessary to establish a new energy-saving and emission-reduction innovation system with the government as a leading force, enterprises as driving forces, and research institutions as supporting forces, and then form a virtuous development cycle.