Consumption-based CO2 emissions accounting and scenario simulation in Asia and the Pacific region

This study uses a consumer-based accounting approach to evaluate the CO2 emission factors of 17 countries in Asia and the Pacific region by including all emissions in the supply chain from commodity location to final consumption location in country consumption patterns. In addition, the number of emissions connected with each country’s consumption of products and services in Asia and the Pacific region has received little attention. This study contributes to understanding the effects of countries’ consumption of products and services on carbon emission peaks and formulates efficient carbon mitigation plans for governments and decision-makers. Accelerating economic growth and industrialization have posed significant challenges to global carbon mitigation efforts and climate change responses. The Monte Carlo simulation technique was used to create a dynamic scenario simulation model to investigate possible future peaks in the carbon emissions of countries in Asia and the Pacific region while taking into account factor uncertainties. The results show that total consumption-based CO2 emissions are remarkable in three Asian countries, including China (387,451.95 metric tons Mt CO2), Japan (185,259.60 Mt CO2), and India (100,720.46 Mt CO2). In South Korea, Brunei, and Taiwan, annual consumption emissions are 1.77, 1.62, and 1.49 tons of CO2 per person, respectively. In terms of final consumption, the household sector is the most noteworthy contributor to consumption-based emissions, accounting for 27–56%. The household sector probably peaks at 19.7 Gt CO2 as per the dynamic scenario simulation. For the three other types of final demand, government expenditure will possibly reach a maximum of 44.0 Gt CO2 in the next 30 years, while capital formation will probably reach its highest emission level at 149.5 Gt CO2.


Introduction
The global warming phenomenon that took place many decades ago has begun to affect the earth significantly. This fact is most visible in emerging markets in the Asia and Pacific region. For example, energy and heat producers released approximately 8.1 billion metric tons of CO 2 emissions between 2017 and 2019 in Asia and the Pacific region (Udemba et al. 2021). In addition, fishing in the Asia and Pacific region emitted 10 million metric tons of CO 2 in 2018 (APAC, 2018). The Pacific region emits less than 0.03% of the world's total CO 2 emissions, which is alarming regarding the consequences of climate change. Suppose current world trends in CO 2 emissions continue. In that case, the cost of climate change in the Pacific region is predicted to be between 2.9 and 12.7% of annual gross domestic product (GDP) by approximately 2100 (ADB, 2020). Under lower carbon conditions, this cost could be considerably lower. However, it could also outweigh almost all increases in economic growth from 2100 onward. There is no indication that developing countries are developing carbon-intensive industries in reaction to climate change policy; however, industrial growth in those countries for other purposes indirectly threatens ongoing attempts to control emissions. The regional division of production and consumption confuses the critical issues of who is accountable for pollution.
Asia and the Pacific region are currently undergoing the world's largest-scale urbanization and industrialization process, with higher energy demand and economic expansion. Industrialization is a multifaceted procedure that alters the amounts and patterns of demographic, commercial, and environmental changes (Wiedmann et al. 2015). As a result, carbon emissions will rise dramatically in the near future due to an expansion in heavy industries, increased economic activity in the service sector, and a growing urban household sector. The long-term rise in emissions also leads to increased GDP per capita and unexpected increases in world energy and carbon concentrations (Peng et al. 2021 andPandey et al. 2020). This rise can lead to significant hurdles for energy-saving programs, carbon reduction, and potentially world climate change. Furthermore, this increase might have vast implications for long-term economic growth. For this reason, it is essential to investigate consumption-based emissions and predict CO 2 emission peaks in the contexts of government expenditure, household emissions, capital formation, and changes in inventory sectors.
Among all instances of environmental pollution, CO 2 emissions have been treated as a severe problem for sustainable business in the present. There are two methods for calculating CO 2 emissions: production-based and consumption-based accounting (CBA) (Shigeto et al. 2012;Zhang et al. 2016;and Safi et al. 2021). Production-based CO 2 emissions are generated by national output without regard to where goods are ultimately used or who uses them, including exports (Peters 2008). However, production-based CO 2 emissions cannot calculate the embodied emissions in interregional trade. This method is commonly applied by global climate change policy agreements, such as the Kyoto Protocol and the United Nations Framework Convention on Climate Change (Senbel et al. 2003). Conversely, CBA allocates the entire pollutants produced in supply chains to the final buyers of goods. Furthermore, CBA has been widely used in the multi-regional input-output model (MRIO) (Liang et al. 2017;Meng et al. 2018). Hence, CBE accounts for imports and the emissions embodied in trading; however, it does not include exports. In contrast, production-based emissions consider total exports but do not take into account imports.
Numerous studies have examined consumption-based carbon emissions (CBCE) both worldwide (Davis and Caldeira 2010;Peters et al. 2011;Liddle 2018a;Knight and Schor 2014) and at the national level Mi et al. 2018;Jiborn et al. 2018;Zheng et al. 2020). In addition, some studies have been conducted at the city level (Minx et al. 2013;Mi et al. 2016;Feng et al. 2014). However, no study has been conducted on consumption-based CO 2 emissions (CBE) for Asia and the Pacific region. Due to the perceived threat to carbon emission peak obligations and climate change, researchers have begun to focus on the peak of energy use and carbon emissions (Huo et al. 2020;Xu and Wang 2020;Shi et al. 2019). Most of these studies focus only on calculating CBE, identifying impact factors, and making policy recommendations. The peak of energy usage is also estimated under the production-based method as the amount of CO 2 emissions and mitigation strategies occurring in the context of production activities within national borders. Although numerous relevant studies have examined the critiques of the current system boundaries for computing the countrywide inventory of CO 2 emissions from the standpoint of equality and effectiveness (Chang 2013;Marques et al. 2012;Zhang 2013), the inconsistencies of scenario simulation within the current accounting paradigm have still not been addressed properly. Variable uncertainties when predicting CO 2 emission peaks are missing in all previous studies, which is an essential trajectory in accounting for forthcoming energy habits and carbon emissions of the commercial trade division. To remedy the existing research gap, this study focuses on estimating CBE for Asia and the Pacific region and exploring the possible future peaks of carbon emissions in this region.
This study makes a unique contribution in the following three aspects: (1) An econometric Leontief input-output model was used, which helps researchers evaluate CBE for 17 countries in Asia and the Pacific region. The findings allow us to explore each country's level of emissions by final demand category and to explore total embodied emissions by export and import. (2) An enhanced Monte Carlo simulation technique was utilized to build a dynamic carbon emission simulation model to investigate probable future CO 2 emission peaks while considering variable uncertainty. (3) A total of 17 comprehensive, up-to-date, input-output tables and carbon intensity factors have been used to estimate the total emission levels of each country. Our research implications suggest means for governments and policy-makers to develop reasonable and focused carbon mitigation objectives and strategies. The public, particularly young people and future generations, bears the costs of climate change, which are currently significant and are likely to rise further. As a result, while not adequate, a policy for CO 2 emissions to be accompanied by a price that permits these costs to be absorbed into the economics of energy use is essential. Another implication is that if the temperature is maintained close to the current range and climatic catastrophes are avoided, the earth must swiftly transition to carbon-free resources and energy efficiency, keeping most remaining fossil fuels in the ground. Nevertheless, increasing carbon prices would increase economic efficiency. Our study suggests that future energy efficiency and alternative low-carbon and zero-carbon energy sources should compete on equal terms, with no subsidies. Based on this strategy, the public and business community should be informed that charges will grow. Finally, if we adhere to our current energy consumption strategy, it will be too late to undo our forefathers' mistakes. The future of sustainable cities and communities is unpredictable, and we may fall short of meeting global sustainable development targets. Our findings concerning future emission peaks consider such compensation to be a first estimation. If that objective is not met, the CO 2 target will need to be adjusted, or future global warming will surpass projected estimates.
The framework of our study is as follows: the "Literature review" section describes the theoretical framework, existing studies on CBCE, and carbon emission peak forecasting. The "Method" section outlines the methodology and origins of the dataset. The "Result and analysis" section contains the results and analysis. The "Discussion" section outlines our discussion. The final section contains concluding remarks.

Literature review
This section synthesizes the whole study in four main subparts. The first subpart focuses on a theoretical framework. The second subpart acknowledges a critical review of CBCE. In a different manner, the third subpart scrupulously evaluates the importance of the peak forecast of carbon emissions. The final subpart illustrates the impact of CBCE and the simulation on industrial practice.

Theoretical framework
CBCE assigns emissions to consumption, specifically accounts for emissions contained in international trade flows, and includes emissions embedded in imports while excluding emissions from services that are produced for export industries (Jiborn et al. 2018). It offers an alternative perspective by focusing on emissions associated with a nation's final demand (i.e., environmental footprint) instead of output. On a global scale, consumption-and productionbased emissions must be equal; the only variation is allocation. However, depending on the type and quantity of foreign commerce in which a country engages, these two measurements might differ significantly. The advantage of this technique is that it eliminates global economic diversion in carbon emissions reporting and ignores carbon leakage as a beneficial influence on carbon control. Moreover, CBCE has a significant effect on the definition of terms and conditions agreed to across national borders.
The input-output (I-O) model depicted in this study is primarily based on earlier models used to evaluate carbon policy initiatives (Metcalf 1999, Fullerton 1996and Senbel et al. 2003. The model includes two key assumptions, which are identical to those of previous models: (1) The model suggests that capital and labor markets are competitive; however, a carbon tax is passed on to the customer in the form of increased energy costs. (2) The second assumption, common to most I-O methods, is that the production process is stable, preventing any influence replacement in reaction to rising (or falling) input values. The I-O diagram depicts monetary interactions between economic sectors (intermediate customers) and individual customers based on observable economic statistics. The method for calculating carbon emissions using a consumption-based model is based on input-output analysis (IOA) of ecological problems (Leontief 1986). The principal methodological instrument used to execute consumption-based GHG inventories in various regions or nations is multi-regional input-output analysis (MRIO), an extension of IAO. The availability of statistical facts will heavily influence the breadth of the MRIO study. Figure 1 shows a stylized representation of the fundamental I-O structure. The fundamental matrix, n × n, is a transactional matrix for each sector (or "flow" matrix). The values indicate intermediary industry inputs to the generation of economic output in this matrix, which depicts the balance of power within industries. The rows reflect the dispersion of industrial output, and the columns show the diversity of industrial input needs (demand) (supply). The model contains a vector at the bottom for value added and a vector along the upper right of the matrix for ultimate consumption, complementing the fundamental industry-by-industry transactions matrix. The critical factor inputs to manufacturing, such as labor and capital resources, are included in the value-added vector. The gross domestic product (GDP) elements that comprise the final demand vectors are consumption, manufacturing, imports, exports, and government expenditure (Davis and Caldeira 2010). Even though the simulation approach may accurately predict the carbon emission index, it ignores the influence of energy efficiency and carbon reduction on policy and socioeconomic concerns. This study used a Monte Carlo simulation technique to predict CBCE likely emission peaks dynamically. To ensure simulation accuracy, each variable has a normal distribution and may be described using the mean value (μ) and standard deviation (σ). This theoretical lens was adopted to establish a link between CBEA and scenario simulation because a given industry's total production can be calculated as either the column total of intermediate goods and value added or the row sum of the intermediate and final productivity of the company (Peters et al. 2011). Furthermore, the total value added, which reflects the entirety of the economy's revenue, must match the total demand, indicating the economy's output.

Review of consumption-based carbon emissions
Numerous studies on CBCE have been carried out globally due to their necessity for human lives in emerging economies. Peters and Hertwich (2008) calculated carbon emissions in global trading for 87 nations in 2001. The result demonstrated that almost 5.3 Gt of CO 2 is incorporated globally and that Annex B nations are net CO 2 importers. This study focused on a quantitative assessment of how emissions from international commerce impact a country's environmental character and climate change policy. Hertwich and Peters (2009) estimated CO 2 emissions for 73 countries. In 2001, household consumption accounted for 72% of greenhouse gas emissions, including 18% for investment and 20% for food. Household operation and maintenance accounted for 19% of GHG emissions, and transportation accounted for 17% of GHG emissions. Davis and Caldeira (2010) generated a CBCE for 113 nations using an MRIO model. They showed that 23% of worldwide CO 2 emissions, or 6.2 gigatons CO 2 , was exchanged worldwide, predominantly in the form of trades with China and former developing countries. Peters et al. (2011) created a trade-linked worldwide record for CO 2 emissions encompassing 113 nations and 57 major industries and discovered that net emission exchanges passing from emerging to advanced nations via international commerce jumped from 0.4 Gt CO 2 in 1990 to 1.6 Gt CO 2 in 2008. Knight and Schor (2014) investigated the link between economic growth and CO 2 emissions in 29 high-income nations and demonstrated that consumptionbased emissions are more affected by economic growth than geographical emissions. Liddle (2018b) created a CBE database that calculated emissions based on domestic fossil fuel usage plus emissions embodied in imports minus exports. The study tested a panel of 20 Asian countries to examine how vital trade is in national emissions under a territorial consumption-based alternative paradigm. Banerjee (2021) examined the effects of border carbon adjustment (BCA) implementation on exports from developing countries and showed that the lower the BCA and domestic carbon adjustment (DCA) rates are, the more efficient it is to minimize emission intensity and energy usage. Prior studies discovered that trade flows were noteworthy for CBE but not for emissions centered on territory.
CBCE studies have been conducted at the national level. For example, Wood and Dey (2009) calculated Australia's carbon footprint using a consumption-based method. In that study, emissions associated with exports were much more significant than those associated with imports. Australia's overall carbon emissions in 2005 were 522 metric tons (Mt). Wiedmann (2009) and Barrett et al. (2013) estimated the Fig. 1 Framework of the multiregional input-output (MARIO) model for consumption-based carbon emissions and scenario simulation UK's greenhouse gas emissions. They revealed that CBCE quickly rose as the distance between production-based and CBE increased. Feng et al. (2013) investigated the CO 2 emissions incorporated into goods in several Chinese regions. They discovered that products and services utilized outside the province and production accounted for 57% of total emissions. Mi et al. (2018) utilized the MRIO table to show interregional and intersectoral economic flows for each of China's 30 regions in 2012. Zheng et al. (2020) used MRIO to assess regional decarbonization disparities and driving forces from 2012 to 2015. They determined that consumption-based emissions in China peaked in 2013, mainly due to CBE in emerging regions. He et al. (2021) investigated the influence of financial growth and global CBE in Mexico. They suggested that globalization and capital formation increase environmental quality but degrade energy use and economic expansion.

Research on the carbon emission peak forecast
Studies have emphasized the importance of peak energy usage and CO 2 emissions owing to the potential risk to global carbon emission agreements and to climate change and have mostly used the top-down approach (Yuan et al. 2014;Fang et al. 2019;Sun et al. 2019) or the bottom-up model (Zhou et al. 2013;Zhou et al. 2018;McNeil et al. 2016) to predict rising energy use and CO 2 emissions. The top-down approach's key objective is to examine the relationship between carbon and demographic aspects to create future forecasts. The conventional model primarily includes the IPAT model (Zhang and Zhao 2019), the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model (Huo et al. 2020;Xu and Wang 2020), and the computable general equilibrium model (Shi et al. 2019). For example, Zhang and Zhao (2019) utilized the STIRPAT model to assess the impact of carbon emissions in China at the national level and found that R&D investment and energy intensity have a binding effect on sinking carbon emissions in the convenience sector. Xu and Wang (2020) applied the STIRPAT method and scenario analysis to forecast Chinese CO 2 emissions in the construction and household sectors and predicted that energy usage in the construction and household industries will remain high, reaching 1155-1243 Mtce by 2050 and declining to 942-1116 Mtce by 2100. Using the STIRPAT model, Huo et al. (2020) provided a complete framework for urbanization, comprehensively investigated numerous impacts of development on urban building CO 2 emissions in terms of cooperation quantities and structural dimensions, and revealed that urban population and urban building floor size have a deleterious impact on carbon emissions in the construction industry. The carbon tax in the construction sector was investigated using the computable general equilibrium model by Shi et al. (2019), who discovered that a 60 RMB per ton carbon tax is suitable and that the building industry will peak in 2025.
In addition, the bottom-up methodology breaks down the energy usage of a household into several points. This technique combines factors from the bottom up to obtain overall energy usage. It then uses scenario analysis to anticipate carbon emissions . For example, Zhou et al. (2013) used the bottom-up modeling framework to assess the effects of various forecasts with several causes on Chinese commercial household energy demand. They discovered that energy efficiency increases were insufficient to overcome the energy intensity of commercial households. Zhou et al. (2018) also developed the bottom-up paradigm of construction carbon emissions. They discovered that if things continue as they are, Chinese construction energy usage will peak near 2040.

The impact of consumption-based emission peaks on industry sectors
Appropriate policies and initiatives for reducing CO 2 emissions are cost-effective in the long run. However, there are significant economic consequences in the short run. Consumption-based accounting aids ultimate or intermediate customers in determining the effects of their purchases on supply chains. According to Steininger et al. (2016), identifying a single actor who can be held causally liable on his or her own is impossible. Both producers and product users release carbon emissions, facilitated by extraction techniques and revenue makers and driven by ultimate consumers. Almost all stakeholders throughout the value chain benefit from value-added production. As a result of this understanding, ideas for blended methods of responsibility sharing have been proposed. Sun et al. (2019) and Qian et al. (2019) used the typical consumption-based emission peak. Tukker et al. (2020) suggested a consumption-based method that is "technologically rectified." According to them, the consumption-based strategy does not encourage exporters to employ environmentally friendly technologies because the embodied effects of their exports are passed on to ultimate consumers in other countries. They suggest that nations that export goods with embodied CO 2 emissions that are less than the global average for that product be rewarded by deducting the disparity. Toptal et al. (2014) suggested that intermediate product users have less independence, as they require these transitional contributions to make additional materials, commodities, or facilities. Increasing inputs will only function properly if system development has been altered and production levels determine input. The consumption-based approach has a significant flaw. It ignores the downstream life cycle consequences of intermediate users who create other materials or product outputs, especially for other intermediate consumers who make other products or service outputs.
In conclusion, past research has provided data and methodologies for predicting future energy demand and carbon emissions based on consumption. However, there are still some significant research gaps: (1) Existing research has predominantly focused on ancient carbon emissions at the global, national, and local levels. No previous studies have emphasized the effects of the numerous consequences of carbon emissions on the future of Asia and the Pacific region.
(2) In terms of the prediction model, prior research relied on steady scenario calculations to forecast future CO 2 emissions trends. However, this analysis fails to account for the uncertainties associated with future variable changes. The possibility of achieving carbon emission peaks is no longer possible. (3) The regional division between Asian and Pacific countries in levels of production and consumption raises the critical issue of who is accountable for pollution. The climate change mitigation responsibility that can be distributed given this uncertainty has remained unclear until now. This situation may make it difficult for policy-makers to implement efficient carbon emissions reduction strategies.
This study proposes a complete input-output model for estimating CBCE to address the drawbacks of existing studies. Then, considering the uncertainty of the parameters, a dynamic simulation model is implemented using the Monte Carlo simulation method to investigate the probable peaks of carbon emissions in households, government expenses, and capital development, as well as variation in inventory sectors.

Data
This study uses the Leontief input-output model to estimate CBCE for 17 countries in Asia and the Pacific region. Data on trade, input-output by sector, and CO 2 emissions based on final demand, exports, and imports are all taken from the OECD 2015 Input-Output table 1 dataset, 2018 edition. The input-output table dataset covers 35 socioeconomic sectors and ten primary industry products. In addition, GDP, population, country area, and energy consumption data are taken from the World Development Indicators 2 database. This study updates regional energy consumption and CO 2 emissions to incorporate all key "commercial" energy sources. Finally, the carbon intensity of each economic sector is calculated using the guidelines referred to by the IPCC territorial emissions accounting method.

Input-output model
The input-output model is one of the most extensively applied methodologies for assessing CBE. This technique has been used in various studies, including studies on environmental challenges (Liddle 2018a).
The I-O calculation is focused on financial flows among industries and countries/regions. As a result, the I-O structure can be expressed as: After calculating x, one can find where (I − A) −1 is the inverse matrix that incorporates explicit industrial inputs to fulfill one unit of ultimate monetary demand and I denotes the identity matrix.
We need the carbon intensity for all sectors of the economy to compute CBE. For example, suppose k i is the carbon intensity of sector i. In that case, the CBCE is computed as: where CO 2 indicates a vector that represents total CO 2 emissions embedded in products and services utilized to meet all areas' ultimate demand and k indicates a vector of CO 2 emissions per unit of economic output in all regions.
To estimate the embodied emissions from imports, we modify Eq. (3) to: where CO 2 im is the total emissions embodied in imports to the regions, ˜k denotes a vector of coefficients for sectoral CO 2 emissions, and y p indicates the final demand vector of region p.

Monte Carlo simulation technique
The Monte Carlo simulation approach was developed to assess the threat of construction projects. It is now a popular method for dynamic prediction. However, recalculations of variables may be needed until the approach is completed, depending on the nature of uncertainties and the ranges y 11 y 21 y 31 … y 1m y 12 y 22 y 32 … y 2m y 13 y 23 y 33 … y 3m ⋮⋮⋮⋱⋮ y m1 y m2 y m3 y mm (Meinshausen et al. 2009;and Vithayasrichareon and MacGill 2012). Even though the technique may reasonably estimate the carbon emission index, it overlooks the impact of energy efficiency and carbon mitigation on policy and socioeconomic considerations. The Monte Carlo simulation approach is used in this study to estimate CBCE probable emission peaks dynamically. There are three phases involved in using Monte Carlo simulation: (1) Specify the variables' level of uncertainty. Using probability distributions, variables can have varying likelihood of different events occurring. Each variable satisfies the normal distribution and may be characterized using the mean value (μ) and standard deviation (σ) to assure simulation accuracy. The value must be within the probability ranges encompassing the variable's highest and lowest value interval (95%) represented by ± 2σ.
(2) Run 50,000 stochastic simulations based on predetermined probabilities and distributions to precisely determine the probability distribution of each variable. (3) Use probability distribution diagrams to present simulation findings.

Domestic and imported emissions
CBE consists of imported emissions and domestic emissions. For most countries, imported emissions exceeded domestic emissions in 2015 (see Fig. 2). Approximately 60% of consumption-based emissions in nations such as Australia, New Zealand, Malaysia, Singapore, and Thailand are imported from other countries. In terms of overall consumption-based emissions, Hong Kong has the most significant percentage of imported emissions. Hong Kong's imports are approximately nine times higher than its ultimate consumption. Therefore, Hong Kong is reliant on commodities and services produced elsewhere in the world. More than 50% of CBCE arises within in the national area of various countries, including Brunei, China, India, Indonesia, Japan, South Korea, and Russia. For two reasons, approximately 24% of Russia's emissions are imported from neighboring areas. First, Russia imports less than the other countries. Second, Russia's exports have a far greater carbon intensity than its imports.

Emissions in final demand
From the viewpoint of CO 2 emissions in final consumption, final demand includes four categories: capital formation, government expenditure, changes in inventories, and household consumption. In Fig. 3, the highest contributor to consumer-based emissions is household consumption. Vietnam has the largest proportion of emissions attributable to household consumption. Household consumption accounts for a variety of emission percentages, such as 54% (Australia), 49% (India), 60% (Japan), 60% (Russia), 65% (South Korea), 70% (Taiwan), and 75% (Vietnam). Consumptionbased emissions are substantially influenced by urbanization, A u s t r a l i a B r u n e i C a m b o d i a C h i n a I n d i a I n d o n e s i a J a p a n S . K o r e a M a l a y s ia N e w Z e a l a n d P h i l i p p i n e s R u s s i a S i n g a p o r e T a i w a n T h a i l a n d V i e t N a m H o n g k o n g  Figure 4 shows the mean carbon concentration of trade in terms of kg CO 2 per US$ of exports or imports for each country. Carbon intensity is calculated by the quantity of CO 2 emissions per unit energy (ft) divided by the amount of energy consumption per US$ of trade by an individual country. Brunei, Japan, South Korea, and China have the highest total carbon intensity in exports due to the scarcity of carbon-intensive fuels such as coal in these regions and the low volume of energy-intensive exports. On the other hand, New Zealand, the Philippines, and Indonesia require a higher value per unit of energy for their exports. In addition, a more significant percentage of that energy was produced using the low-carbon innovation technique. Central Pacific export markets have a much lower carbon intensity than do Asian economies. Goods imported into Cambodia and Indonesia contain significantly higher CO 2 per US$ than their exports, representing imports of energy-intensive commodities abroad. On the other hand, the carbon intensity of imports to Brunei, Japan, South Korea, China, and India is significantly lower than that of their exports. For example, imports to South Korea, India, and China entail 0.37, 0.27, and 0.24 (MJ) per US$, respectively. Imports have the same carbon intensity as exports in New Zealand, indicating a tighter balance of manufacturing and service sectors in the New Zealand economy. Figure 5 displays the carbon emissions of personified imports and exports, which differ significantly among 17 Asia and Pacific countries. Emissions exemplified in imports in the three Asian nations of Japan, China, and India are significantly higher than in other Pacific nations. For instance, Japan emits 3.16 Gt CO 2 emissions embodied in imports, which is 99 times greater than the same value for Brunei. The sectors of mining support; electricity, gas, and water supply; and construction contribute the most significant emissions embodied in imports. Mining support imports in China emit 52.08 Gt CO 2 , accounting for 2.4% of the total embodied emissions of imports. However, in India, the imports used in mining support produce 35.19 Gt CO 2 , which is the highest embodied import emission in this country. Electricity, gas, and water contribute the highest CO 2 emissions among imports in China (93.83 Gt CO 2 ) and South Korea (25.52 Gt CO 2 ). Furthermore, the construction industry contributes significantly higher carbon emissions in Australia (13.19 Gt CO 2 ), Japan (11.67 Gt CO 2 ), and India (5.51 Gt CO 2 ). Additionally, emissions imported to China far exceed those of any other country and are mainly embodied in agriculture, forestry, and fishing (3.09 Gt); textiles, apparel, and leather (3.58 Gt); coke and refined petroleum (4.92 Gt); manufacture of basic metals (3.82 Gt); fabricated metal products (3.92 Gt); telecommunications (4.51 Gt); and financial and insurance activities (8.25 Gt). Figure 5 indicates that the embodied emissions in most countries' exports are higher than the embodied emissions in their imports. For example, the emissions embodied in China's trades emit 166.14 Gt CO 2 , but those of its imports emit just 2.82 Gt CO 2 . Furthermore, China's manufacturing industry has a lower carbon intensity than that of its exports. One unit of imports emits more CO 2 than a comparable unit of exports. Nevertheless, in New Zealand and the Philippines, the embodied emissions in exports are lower than those in imports. In many areas, consumer duty outweighs producer accountability. For example, the following exports are responsible for China's massive emission imbalance: real estate activities (317.12 Gt CO 2 ); mining support (233.56 Gt); arts and entertainment (166.14 Gt); electricity, gas, and water supply (69.52 Gt); agriculture, forestry, and fishing (26.93 Gt); and financial and insurance activities (358 Gt).

Regional emissions
In Fig. 6, row 1, this study illustrates the top 10 levels of CBCE for countries in Asia and the Pacific region. Four Asian countries have the highest overall consumption-based emissions: China (387,451.95 Mt CO 2 ), Japan (185,259.60 Mt CO 2 ), India (100,720.46 Mt CO 2 ), and South Korea (90,223.37 Mt CO 2 ). China and India ranked as the top two countries with the highest CO 2 emissions, 59,604.16 and 57,499.86 kg per $GDP, respectively. In Fig. 6, row 1 shows that in South Korea, Brunei, and Taiwan, annual consumption-based emissions are 1.77, 1.62, and 1.49 tons of CO 2 per person, respectively. Consumption-based emissions per capita in China are extremely low, at 0.28 tons of CO 2 per person. However, overall consumption-based emissions in this country are very high. A significant difference between per capita and consumption-based emissions has been illustrated based on total carbon emissions and per capita consumption. Therefore, methods for computing emissions substantially impact the determination of who is responsible for climate change mitigation. Therefore, consumptionbased carbon accounting methodologies must be thoroughly evaluated (Caney 2009). Figure 6 indicates the total emissions embodied in imports. Emerging economies are more likely to import CO 2 emissions. As the most developed nations in Asia and the Pacific region, China and Japan have the highest emissions embodied in imports. In contrast, few emissions are embodied in imports in Brunei and Cambodia, which are two less advanced countries. This fact indicates that manufacturingbased nations develop into consumption-based nations as these nations progress socioeconomically. Overall import emissions are most significant in, e.g., China (243,863.34 Mt CO 2 ), Japan (116,816.47 Mt CO 2 ), India (86,680.84 Mt CO 2 ), and South Korea (66,022.48 Mt CO 2 ). India is the highest CO 2 emitter in terms of CO 2 imported per $GDP. Hong Kong and Singapore ranked first and second for per capita imported emissions, with 2.94 and 2.89 tons per capita, respectively. The conclusions of this study support Feng et al. (2013) and Mi et al. (2018), who calculated countrylevel CBE. In terms of exports (Fig. 6, row 4, left), emissions embodied in exports are most significant in Taiwan and Korea, which is a primary reason for the high productionbased CO 2 emissions of these countries. Korea and Japan ranked first and second for per capita exported emissions, with 85.5 and 24.35 tons per person, respectively.

Emission peak simulation
We use 50,000 Monte Carlo simulations to show the likely CO 2 emission peaks in four final demand categories (Fig. 7). This study uses 95% confidence intervals to choose probable simulation results that follow a normal distribution to reduce the effects of extreme values. The mean value of expected carbon emissions changes in inventory is 0.43 Gt, with a standard deviation of 0.86 Gt (Fig. 7). The most likely peak range is between − 1.0 and 1.2 Gt CO 2 . Therefore, compared to 2015, inventory carbon emissions will grow by 35-70% during the next 30 years. As a result, there will be continued pressure on inventory changes to decrease energy use and carbon emissions. Figure 7a-c show the probable emission peak of prospective CO 2 emissions in the household sector, government expenditure, and capital formation. The household sector is expected to peak at 19.7 Gt CO 2 . The estimated emission peaks are probably between − 2.6 and 25.7 Gt CO 2 (Fig. 7a). In contrast, the maximum emission peak ranges for government expenditure will be between − 16.0 and 20.0 Gt CO 2 (Fig. 7b). However, the highest probable emission peak is 8.0 Gt CO 2 . Future CO 2 emissions from capital formation will be similar to those from the  (Fig. 7d). Therefore, the household sector and capital formation will continue to be key contributors to the carbon emission peaks of Asia and the Pacific region in the near future.
To summarize the Monte Carlo simulation findings, we find that dynamic scenario simulation of the CO 2 emission  6 Top 10 countries/regions by consumption emissions, net imports, and net exports peak is achievable. Therefore, overall household consumption will exceed a peak of 131.64 Gt CO 2 very soon. For the three other types of final demand, government expenditure will possibly reach a maximum of 44.0 Gt CO 2 in the next 30 years, while capital formation will probably hit its highest emissions at 149.5 Gt CO 2 during these specific times. Additionally, inventory change is likely to achieve its highest emissions at 3.6 Gt CO 2 . Thus, based on these initial findings, the household and capital formation sectors will be the primary contributors to the emission peaks. Despite the fact that several studies have demonstrated the use of consumerbased accounting methods in investigating the causes of carbon emission increases (Brizga et al. 2014;Wiedmann et al. 2015), few countries have incorporated consumption-based indices into their policy programs (Yu et al. 2010;Barrett et al. 2013).

Discussion
Climate change issues are now considered a particular focus for sustainable global development. To create an environmentally friendly industrialization process, it is critical to comprehend the energy consumption patterns of every country and their impact on the environment. While scientists continue to establish a relationship between CO 2 emissions from energy consumption and the atmospheric effects caused by these emissions, economic experts have been looking into the most cost-effective ways to reduce CO 2 emissions and to avoid or mitigate the effects of substantial global warming. For this purpose, the CBEA model in this study provides a framework for estimating comprehensive commodity price impacts in reaction to carbon policies. CBEA is not just important at the national and international policy levels; it has also been suggested that this measure is essential for cities that frequently offshore their emissions to the countryside Wiedmann 2009;Chen et al. 2016;Fry et al. 2018;Mi et al. 2016). Our domestic and import emission results in Fig. 2 show that Hong Kong and Vietnam have the highest percentage of imported emissions, which is approximately nine times their final consumption. For embodied emissions in the final demand category in Fig. 3, China emitted the highest percentages of CO 2 in the household, government, and capital formation sectors. Consumption-based emissions are significantly impacted by urbanization, significant economic expansion, and government regulations. Another argument might be that a significant increase in infrastructure investment is linked to CO 2 emissions effectiveness (Bilgili et al. 2021). Nevertheless, Fig. 5 shows that the embodied emissions in most Asian and Pacific countries' exports are higher than the embodied emissions in their imports. The sectors of mining support; electricity, gas, and water supply; and construction contribute the most significant emissions embodied in imports. On the other hand, real estate activities (317.12 Gt CO 2 ); mining support (233.56 Gt); arts and entertainment (166.14 Gt); electricity, gas, and water supply (69.52 Gt); agriculture, forestry, and fishing (26.93 Gt); and financial and insurance activities (358 Gt) sectors contribute the highest percentages of CO 2 emissions embodied in exports. Our results differ in terms of their indications from those of Ding et al. (2021). Those authors established that developing or rising economies emphasize essential goods, whereas industrialized countries create high-end items. Xu and Wang (2020) and Peng et al. (2021) observed that emissions associated with imported items are frequently shifted (exported) from developed countries to developing countries for local consumption. However, when identical items are compared across established and developing nations, the intensity of CO 2 emissions varies as a result of differences in production technology.
With the increase in high energy consumption and absurd industrialization practices, our results document the longterm adverse effect of carbon emissions. Several studies have examined the environmental effects of government spending, energy demand, and industrial development. Figure 6 indicates that four Asian countries have the highest overall consumption-based emissions, including China (387,451.95 Mt CO 2 ), Japan (185,259.60 Mt CO 2 ), India (100,720.46 Mt CO 2 ), and South Korea (90,223.37 Mt CO 2 ). Energy consumption, which has a significant environmental impact, is directly tied to GDP (Abbasi et al. 2021). For nations with low-income dissimilarity, Baležentis et al. (2020) pointed out many patterns of association between inequality and carbon footprint per capita: As disparity rises, CBE footprint per capita rises, but further expansion in the carbon footprint is inhibited. The rise in CBE footprint per capita resulting from increasing disparity is documented at exceptionally high levels of income dissimilarity. The principal sources of worldwide disparities in emissions per capita are these carbon transfers across nations. Typically, countries with lower production-based CO 2 emissions have low consumptionbased CO 2 emissions and vice versa (Wen and Wang 2020).
These findings reveal considerable differences in carbon emission flows among Asia and Pacific region countries. This fact indicates that CO 2 emissions have been rising in recent years. If the current trend continues, Asia and the Pacific region will become the world's foremost carbon importers. Similarly, the current findings suggest that swift economic expansion in Asian and Pacific nations poses a danger to environmental attributes due to a steady increase in nonrenewable energy use. These results are consistent with previous studies conducted for global economies (Davis and Caldeira 2010), developed countries (Knight and Schor 2014), Asian economies (Qingquan et al., 2020), OECD (Ahmed et al. 2020), BRICS (Danish et al. 2019), and emerging economies (Sapkota and Bastola 2017). To cope with the harmful environmental impact, Asian and Pacific countries have adopted various eco-innovation solutions.
To understand the trajectory of energy consumption in Asian and Pacific nations with rising living standards and environmental consciousness, we may need to look at the trend of energy consumption in Asian and Pacific countries more closely. These factors will have a significant impact on the emission peak and peak period of prospective consumption-based carbon emissions. According to the dynamic scenario simulation, the Monte Carlo simulation findings suggest that the household sector is most likely to achieve a high peak at 19.7 Gt CO2. The highest probable emission peak in the household sector range will be between − 2.6 and 25.7 Gt CO2 (Fig. 7a). For three other types of final demand, government expenditure's possible emission peak ranges from − 16.0 to 20.0 Gt CO 2 . The highest emission peak is 8.0 Gt (Fig. 7b). Future CO 2 emissions in the capital formation sector resemble those in the household sector. Capital formation most likely contributes an emission peak range between − 25.4 Gt and 44.5 Gt, with an average value of 17.85 Gt CO 2 . Thus, the household and capital formation sectors account for the majority of the emission peak. As a result, the findings of this study concerning the more ecologically significant consequences of the household and capital formation sectors are consistent with past findings. According to some researchers, Asia has a good chance of reaching its peak before 2035, provided certain actions are taken, such as aggressively changing economic processes and speeding up the transition from the growth model Hassani 2016). However, various researchers have arrived at different conclusions regarding the peak period of emissions. Some experts believe Asia's CO 2 emissions will peak in 2025 (Chen 2017), while others believe it will happen between 2030 and 2035 (Mi et al. 2017) or perhaps after 2030 (Huo et al. 2020). The possible reasons for these variations include disparate sources of data, various forecasting methodologies, and different underlying assumptions. To the best of our knowledge, this study is the first to evaluate the applicability of simulation of CBE in the presence of a set of regional carbon adjustment estimates in a consumptionbased system boundary framework.

Concluding remarks
Asian and Pacific countries are experiencing an extensive period of industrialization, which is precisely leading to high energy demand and carbon emissions. Collaborations between consumption and production areas are essential for climate change mitigation. An increasing number of academics and policy-makers accept CBE accounting for climate change policies. This study estimates consumption-based carbon emissions for 17 major Asian and Pacific countries. Additionally, dynamic scenario simulation was executed to examine future carbon emission peaks in the household, government expenditure, capital development, and change in inventory sectors. Our empirical findings show that Australia, New Zealand, Malaysia, Singapore, and Thailand imported more than 65% of CBCE from other countries in 2015. In terms of overall CBCE, Hong Kong produces the most significant percentage of import emissions. Household consumption is the most significant source contributing to maximum consumer-based emissions among 17 countries. As Asian and Pacific countries continue to urbanize, more people will shift from rural to urban lifestyles, resulting in higher CO 2 emissions from household consumption. Capital formation seems to be the second-highest source of emissions. Rapid urbanization, extensive economic expansion, and government strategies contribute significantly high capital-intensive funding to consumer-based emissions.
Emissions embodied in imports for four Asian countries, China, India, Japan, and South Korea, are significantly higher than those of other Pacific countries. For instance, Japan has 3.16 Gt CO 2 of emissions embodied in imports, which is 99 times higher than that of Brunei. Most countries' export emissions exceed their import emissions. However, export-embodied emissions in New Zealand and the Philippines are lower than import-embodied emissions. Total consumption-based emissions are most remarkable for three Asian countries: China (387,451.95 Mt CO 2 ), Japan (185,259.60 Mt), and India (100,720.46 Mt). The Monte Carlo simulation result shows that the household sector will likely achieve a peak at 19.7 Gt CO 2 . The highest probable emission peak range for the household sector will be between − 2.6 and 25.7 Gt CO 2 (Fig. 7a). Future CO 2 emissions in the capital formation sector will resemble those in the household sector. Capital formation most likely contributes to an emission peak range between − 25.4 Gt and 44.5 Gt, with an average value of 17.85 Gt CO 2 . Thus, the household and capital formation sectors will account for the majority of emission peak. This information is an important finding since previous literature has not addressed consumption-based CO 2 emissions and emission peaks for Asia and the Pacific region using the input-output and simulation method. Furthermore, this paper finds statistical evidence that the household and capital formation sectors are responsible for most of the emission peaks and increased environmental pollution in Asia and the Pacific region. The negative impact of CO 2 emissions in production-based economies is more significant than their negative impact in consumptionbased economies. Therefore, our study offers new insights into the role of consumption-based CO 2 emissions on environmental degradation.
The following suggestions are made. The industrial arrangement and the exposure of these industries to competition in international markets must be adjusted to sever the connection between CO 2 emissions and industrial production. The low-carbon development of primary industry must be promoted. Carbon pricing policies can be implemented by a tax to give a direct financial incentive to reduce emissions (Toptal et al. 2014). For example, existing markets can seamlessly include the cost of cutting emissions into the prices of all goods and services. Moreover, carbon taxes or trading give the industry a persistent price signal to cut emissions where doing so is most cost-effective. A vital component of climate mitigation policy is investing in breakthrough clean energy and emission reduction technologies Mishra et al. 2021). The federal government might enhance financing for this effort. Finally, to regulate energy intensity, more rigorous energy efficiency requirements and energy consumption goal systems should be implemented to combat climate change and develop new technologies. More sustainable and greener energy sources should be created to reduce carbon emissions.
This study has some limitations. First, the number of balanced observations used in the simulation procedure is reduced due to specific missing observations in the data of 17 Asian nations. Second, this study's capacity to establish the exact pricing dynamics involved in changing the energy needs of different sectors is limited due to its static and generally aggregated analytical methodology. Third, there are limited numbers of applications for consumptionbased emissions for peak time evaluation. To the best of our knowledge, this framework does not address the testing analyses for emission peak time. Furthermore, very little research was conducted on consumption-based emission scenarios. The simulation approach suggested in this study may be used to tackle these issues quickly using real-world energy data. This approach provides a theoretical foundation for future research concerning water, land, and biodiversity. As a new pattern of industrialization is the only method of reducing carbon emissions, future research should focus on important routes, alter consumption structures, and perform scientific and technological innovations to reduce carbon emissions.