Confronting the Climate Crisis: China’s Leadership and the Imperative for Carbon Pricing in Asia-Pacific
Introduction
The Asia-Pacific region is pivotal in the global effort to combat climate change. According to the latest working paper by the IMF, this region, as a major driver of global economic growth, is also responsible for over half of the world’s greenhouse gas emissions. Notably, China alone accounts for 27% of the global carbon dioxide emissions. Consequently, Asia-Pacific faces dual challenges as it is both highly susceptible to natural disasters and a significant contributor to climate change.
This region’s reliance on carbon-intensive manufacturing results in higher emissions intensity than other areas. Moreover, its substantial dependence on fossil fuels is exacerbated by fossil fuel subsidies, which total an astonishing $1.3 trillion. These subsidies contribute to increased carbon emissions by reducing the costs associated with fossil fuel production and use, thereby hindering the transition to renewable energy sources.
Despite the urgent need for effective climate action, the Asia-Pacific lags in developing mechanisms for climate finance, especially when compared to more advanced economies. This delay offers a vast potential for growth. The financing shortfall in the region is estimated at no less than $800 billion, underscoring a pressing need for a systematic approach to mobilizing both public and private capital.
As the largest emitter and a dominant force in the region, China’s ambitious climate goals, such as peaking carbon emissions before 2030 and achieving carbon neutrality by 2060, require significant systemic reforms. The implementation of carbon pricing in China, including the expansion of existing carbon markets and the inclusion of new sectors, will be crucial. This will help internalize the environmental costs of GHG emissions and demonstrate the transformative potential of well-structured climate finance in addressing climate change.
Section 1: Fossil Fuel Subsidies and Their Environmental Impact
The intersection of economics and the environment is most starkly observed in the context of fossil fuel subsidies, a policy mechanism with profound implications for climate change. These subsidies, often intended to lower the cost of fuel and support economic growth, come at a high environmental cost: they encourage increased consumption of fossil fuels, leading to higher greenhouse gas emissions and accelerating climate change. This market distortion not only hampers the competitiveness of cleaner energy but also locks countries into a carbon-intensive energy infrastructure, making the transition to green energy sources more challenging and expensive.
Fossil Fuel Subsidy Trends in China
In China, the landscape of fossil fuel subsidies reflects a significant environmental and economic dilemma. The steep increase in subsidies for electricity, gas and oil from 2020 onwards, particularly after the COVID-19 pandemic, reveals the tension between economic revival efforts and the transition to sustainable energy.
In examining China’s fossil fuel subsidies by their types, it is evident that subsidies have been a dynamic component of the country’s energy policy. According to the data, subsidies for electricity have shown a pronounced increase. This surge raises important questions about the sources of this electricity. If it stems from renewable resources, it could signal a positive transition to cleaner energy; however, if coal-fired power remains a significant contributor, the increase in subsidies could be counterproductive to emission reduction goals.
The subsidies for oil and gas have also experienced a steady growth. While less polluting than coal, natural gas is still a fossil fuel with considerable greenhouse gas emissions when burned. The subsidies for gas have seen a gradual increase over the years, indicating a potential strategic shift to use gas as a ‘bridge’ fuel in the energy transition. However, this approach has its critics, who argue that investing in gas infrastructure may delay the switch to renewable energy.
Notably, the subsidies for coal have been almost eliminated, reflecting a strategic shift away from the most polluting fossil fuel and a potential alignment with global climate commitments. This could signify a recognition of coal’s outsized impact on emissions and an attempt to mitigate its environmental footprint.
Section 2: Fossil Carbon Emission Trends in China and Asia
The trajectory of fossil carbon emissions in China and across Asia underscores the pressing need to address climate change. Data from the Global Carbon Project paint a stark picture of rising emissions, which, if unchecked, spell dire consequences for global efforts to curb the climate crisis.
Emission Growth in China and Asia
The first graph illustrates the relentless growth in emissions within Asia and China from 2000 to 2020. China’s emissions grew to 3131 million metric tons of CO2 equivalent, not just outpacing other Asian nations but also consistently comprising over half of Asia’s total emissions, which reached 5178 million metric tons in 2020. This accelerating trend in emissions growth is indicative of the region’s rapid industrialization and economic development, which have been largely fueled by fossil fuels.
China’s Share in Global Emissions
The second graph reveals that China’s emissions account for an increasing share of global emissions, surpassing 30% in recent years. This ascent reflects China’s emergence as an industrial powerhouse, the world’s factory, and a growing consumer market. It also points to the significant reliance on fossil fuels, including coal, which has powered much of China’s economic rise.
China’s substantial contribution to global emissions emphasizes its critical role in international climate change mitigation efforts. As the country with the largest share of global emissions, China’s policies, and actions have a considerable impact on global emission trends. The country’s recent moves to eliminate coal subsidies, although a positive development, will need to be matched with further aggressive measures to curb emissions across all sectors, not only to align with its international commitments but also to mitigate the global environmental impact.
Section 3: Carbon Pricing Instruments
The urgent environmental challenge posed by increasing greenhouse gas (GHG) emissions has propelled the implementation of market-based mechanisms to incentivize reduction efforts. Carbon pricing stands as a strategic approach, marrying economic principles with environmental objectives. The primary instruments in carbon pricing are Emissions Trading Systems (ETS) and Carbon Taxes.
Emissions Trading Systems and Carbon Taxes
ETS, or cap-and-trade systems, set a cap on total GHG emissions and allocate or auction off permits to emitters, which represent the right to emit a certain amount. Entities can trade these permits, providing a financial incentive to reduce emissions; those who can reduce emissions at lower costs can sell their excess permits to others. By limiting the number of permits, the ETS ensures that the emission cap is not exceeded, while the trading mechanism discovers the price of carbon. By 2023, there are 37 ETS in operation worldwide, spanning national and subnational jurisdictions. These systems are critical in sectors where direct emission control is challenging.
A carbon tax directly sets a price on carbon by levying a tax on the GHG emissions of fossil fuels. This straightforward approach makes emitting carbon more expensive and clean energy comparatively cheaper, encouraging investments in renewable energy and energy efficiency. By 2023, there are also 37 carbon taxes implemented around the globe.
China’s Pioneering Role
China, recognizing its significant emissions problem, embarked on regional ETS pilots as early as 2013, in major cities and provinces including Beijing, Shanghai, Tianjin, Chongqing, Guangdong, Hubei, and Shenzhen. These pilots were instrumental in testing the waters for a national system.
In 2021, China elevated its commitment by launching a national ETS. The system initially covers large coal- and gas-fired power plants, laying the foundation for expanding to more industries. It represents the largest carbon market in the world, given China’s status as the top emitter of GHG.
The global embrace of carbon pricing instruments is evident in the 2023 statistics, covering 23% of global GHG emissions, equivalent to 11.66 GtCO2e. The donut graph highlights that China’s national ETS accounts for 8.92% coverage, a significant contribution reflecting its substantial emissions profile. Other regions together cover 14.2% of emissions with their carbon pricing instruments.
Carbon pricing instruments are critical tools in the global strategy to mitigate climate change. ETS and carbon taxes both offer pathways to incorporate the cost of emissions into economic decision-making. China’s proactive measures, transitioning from regional pilot programs to a comprehensive national ETS, demonstrate a significant shift towards aligning economic activities with environmental targets. This approach underlines the potential of market-based mechanisms to address the climate crisis by incentivizing emissions reduction while allowing economic flexibility. As the global community continues to strive for a sustainable future, the evolution and effectiveness of these instruments in reducing GHG emissions remain a key focus.
Outlook: Navigating the Climate Challenge in China and Asia-Pacific
The Asia-Pacific region stands at a crossroads between development and environmental sustainability. With rapid economic growth, particularly in China, comes the stark reality of increasing emissions and the resulting environmental impact. Yet, there is a palpable shift towards seeking and implementing solutions to mitigate these challenges.
The map illustrates that within the Asia-Pacific region, only a handful of countries have implemented carbon pricing instruments, with China leading the way with its national ETS. This reflects a proactive approach to climate change mitigation and demonstrates the potential for market-based instruments to incentivize emissions reduction in a way that can be integrated with the economic frameworks of the countries in the region.
However, the map also reveals a vast potential for expansion. Only seven countries in the Asia-Pacific region have adopted carbon pricing strategies, underscoring the opportunity—and the need—for broader adoption of such policies. As the region collectively contributes significantly to global emissions, there is an imperative for more countries to adopt these mechanisms.
China’s experiences with ETS can serve as a model for neighboring countries. Active regional cooperation and exchange of knowledge are essential for the broader adoption of carbon pricing instruments. The expansion of these instruments, paired with regional collaboration, will be vital in shaping a sustainable and resilient Asia-Pacific.
References and Data Sources
[1] Lim, C. H., et al. (2024, January). Unlocking Climate Finance in Asia-Pacific: Transitioning to a Sustainable Future. International Monetary Fund, Asia and Pacific and Statistics Departments.
[2] World Bank. State and Trends of Carbon Pricing Dashboard.
[3] International Energy Agency (IEA). (2023, October). Fossil Fuel Subsidies Database: Fossil Fuel Consumption Subsidies for Selected Countries, 2010-2022.
[4] World Bank. (2022, October 12). China’s Transition to a Low-Carbon Economy and Climate Resilience Needs Shifts in Resources and Technologies.
[5] Basu, R., & Lim, C. H. (2024, January 29). Explainer: How Asia Can Unlock $800 Billion of Climate Financing.
[6] Global Carbon Project. (2022). Supplemental Data of Global Carbon Budget 2022 (Version 1.0) [Data set]. Global Carbon Project. https://doi.org/10.18160/gcp-2022
Source Code
---title: "Final Report"format: htmleditor: visualcode-fold: falsecode-tools: true---# Confronting the Climate Crisis: China's Leadership and the Imperative for Carbon Pricing in Asia-Pacific## IntroductionThe Asia-Pacific region is pivotal in the global effort to combat climate change. According to the latest working paper by the IMF, this region, as a major driver of global economic growth, is also responsible for over half of the world's greenhouse gas emissions. Notably, China alone accounts for 27% of the global carbon dioxide emissions. Consequently, Asia-Pacific faces dual challenges as it is both highly susceptible to natural disasters and a significant contributor to climate change.This region's reliance on carbon-intensive manufacturing results in higher emissions intensity than other areas. Moreover, its substantial dependence on fossil fuels is exacerbated by fossil fuel subsidies, which total an astonishing $1.3 trillion. These subsidies contribute to increased carbon emissions by reducing the costs associated with fossil fuel production and use, thereby hindering the transition to renewable energy sources.Despite the urgent need for effective climate action, the Asia-Pacific lags in developing mechanisms for climate finance, especially when compared to more advanced economies. This delay offers a vast potential for growth. The financing shortfall in the region is estimated at no less than $800 billion, underscoring a pressing need for a systematic approach to mobilizing both public and private capital. As the largest emitter and a dominant force in the region, China's ambitious climate goals, such as peaking carbon emissions before 2030 and achieving carbon neutrality by 2060, require significant systemic reforms. The implementation of carbon pricing in China, including the expansion of existing carbon markets and the inclusion of new sectors, will be crucial. This will help internalize the environmental costs of GHG emissions and demonstrate the transformative potential of well-structured climate finance in addressing climate change.## Section 1: Fossil Fuel Subsidies and Their Environmental ImpactThe intersection of economics and the environment is most starkly observed in the context of fossil fuel subsidies, a policy mechanism with profound implications for climate change. These subsidies, often intended to lower the cost of fuel and support economic growth, come at a high environmental cost: they encourage increased consumption of fossil fuels, leading to higher greenhouse gas emissions and accelerating climate change. This market distortion not only hampers the competitiveness of cleaner energy but also locks countries into a carbon-intensive energy infrastructure, making the transition to green energy sources more challenging and expensive.### Fossil Fuel Subsidy Trends in ChinaIn China, the landscape of fossil fuel subsidies reflects a significant environmental and economic dilemma. The steep increase in subsidies for electricity, gas and oil from 2020 onwards, particularly after the COVID-19 pandemic, reveals the tension between economic revival efforts and the transition to sustainable energy. ```{r}#| echo: false#| message: false#| warning: false# options(repos = c(CRAN = "https://cran.rstudio.com/"))library(readxl)library(dplyr)library(leaflet)library(rnaturalearth)library(rnaturalearthdata)library(ggplot2)library(scales)library(ggthemes)library(tidyverse)library(pkgdown)library(esquisse)library(tidyr)library(readxl)library(RColorBrewer)library(viridis)library(plotly)``````{r}#| echo: falseFossil_fuel_consumption_subsidies_2010_2022 <-read_excel("/Users/sherri/downloads/Fossil fuel consumption subsidies, 2010-2022.xlsx")China <-c("China")China_subsidies_data <- Fossil_fuel_consumption_subsidies_2010_2022 %>%filter(Country %in% China)China_subsidies_data_long <- China_subsidies_data %>%gather(key ="Year", value ="Value", -Country, -Product)China_subsidies_data_long_product <- China_subsidies_data_long[China_subsidies_data_long$Product !="Total", ]ggplot(China_subsidies_data_long_product, aes(x = Year, y = Value, color = Product, group = Product)) +geom_line() +geom_point() +scale_fill_brewer(palette ="Dark2") +theme_minimal(base_size =14) +theme(plot.title =element_text(hjust =0.5, size =16, face ="bold"),plot.subtitle =element_text(hjust =0.5, size =12),legend.title =element_text(size =12),axis.title.x =element_text(size =14, face ="bold"),axis.title.y =element_text(size =14, face ="bold"),axis.text.x =element_text(angle =45, hjust =1),legend.text =element_text(size =10) ) +labs(title ="Fossil Fuel Consumption Subsidies for Energy Products in China", subtitle ="Values represent subsidies in million dollars",x ="Year (2010 - 2022)", y ="Subsidy Value (million dollars)" )```In examining China's fossil fuel subsidies by their types, it is evident that subsidies have been a dynamic component of the country's energy policy. According to the data, subsidies for electricity have shown a pronounced increase. This surge raises important questions about the sources of this electricity. If it stems from renewable resources, it could signal a positive transition to cleaner energy; however, if coal-fired power remains a significant contributor, the increase in subsidies could be counterproductive to emission reduction goals.The subsidies for oil and gas have also experienced a steady growth. While less polluting than coal, natural gas is still a fossil fuel with considerable greenhouse gas emissions when burned. The subsidies for gas have seen a gradual increase over the years, indicating a potential strategic shift to use gas as a 'bridge' fuel in the energy transition. However, this approach has its critics, who argue that investing in gas infrastructure may delay the switch to renewable energy.Notably, the subsidies for coal have been almost eliminated, reflecting a strategic shift away from the most polluting fossil fuel and a potential alignment with global climate commitments. This could signify a recognition of coal's outsized impact on emissions and an attempt to mitigate its environmental footprint.## Section 2: Fossil Carbon Emission Trends in China and AsiaThe trajectory of fossil carbon emissions in China and across Asia underscores the pressing need to address climate change. Data from the Global Carbon Project paint a stark picture of rising emissions, which, if unchecked, spell dire consequences for global efforts to curb the climate crisis.### Emission Growth in China and AsiaThe first graph illustrates the relentless growth in emissions within Asia and China from 2000 to 2020. China's emissions grew to 3131 million metric tons of CO2 equivalent, not just outpacing other Asian nations but also consistently comprising over half of Asia's total emissions, which reached 5178 million metric tons in 2020. This accelerating trend in emissions growth is indicative of the region's rapid industrialization and economic development, which have been largely fueled by fossil fuels.```{r}#| echo: false#| message: false#| warning: falseNational_Fossil_Carbon_Emissions <-read_excel("~/Downloads/National_Fossil_Carbon_Emissions_2022v1.0.xlsx", sheet ="Territorial Emissions Edited")Emission_Data <- National_Fossil_Carbon_Emissions[c("Year","China", "Asia", "World")]Emissions_Data <- Emission_Data %>%mutate(OtherRegions = World - Asia)Emissions_Data <- Emissions_Data %>%mutate(ShareOfChina = (China / World) )``````{r}#| echo: false#| message: false#| warning: falseEmissions_Data_long <-gather(Emissions_Data, key ="Region", value ="Emissions", -Year)emissions_data <- Emissions_Data_long %>%filter(Region %in%c("China", "Asia"))share_of_china_data <- Emissions_Data_long %>%filter(Region =="ShareOfChina") ``````{r}#| echo: false#| message: false#| warning: falsep_growth <-ggplot(emissions_data, aes(x = Year, y = Emissions, fill = Region)) +geom_bar(stat ="identity", position ="dodge", color ="black") +# Add bar bordersscale_fill_manual(values =c("China"="#4F81BD", "Asia"="#B8CCE4")) +# Custom blue tonestheme_minimal() +theme(plot.title =element_text(face ="bold", size =14),axis.title =element_text(size =12),axis.text.x =element_text(angle =45, vjust =0.5), # Angle the x-axis labels if neededlegend.title =element_blank(), # Hide the legend titlelegend.position ="top", # Move legend to the toppanel.grid.minor =element_blank(), # Turn off minor grid linespanel.grid.major.x =element_blank() # Turn off vertical grid lines ) +labs(x ="Year",y ="Emissions (Millions of metric tons of CO2 equivalent)",title ="Emission Growth Trends in China and Asia" ) +geom_text( # Add data labels for the most recent yearaes(label = scales::comma(Emissions)),position =position_dodge(width =0.9),vjust =-0.5,data =subset(emissions_data, Year ==max(Year)),size =3,color ="black" )print(p_growth)```### China's Share in Global EmissionsThe second graph reveals that China's emissions account for an increasing share of global emissions, surpassing 30% in recent years. This ascent reflects China's emergence as an industrial powerhouse, the world’s factory, and a growing consumer market. It also points to the significant reliance on fossil fuels, including coal, which has powered much of China's economic rise.```{r}#| echo: false#| message: false#| warning: falsep_share <-ggplot(share_of_china_data, aes(x = Year, y = Emissions)) +geom_line(color ="#ADD8E6", size =1.5) +geom_point(color ="#ADD8E6", size =2.5)+scale_y_continuous(name ="Share of China (percentage)", labels = scales::percent_format()) +expand_limits(y =0) +theme_minimal(base_size =14) +theme(plot.title =element_text(size =16, face ="bold"),axis.text =element_text(size =12),axis.title =element_text(size =14, face ="bold"),panel.grid.major =element_line(color ="#e5e5e5"), # Add subtle grid linespanel.grid.minor =element_blank(), # Turn off minor grid linespanel.background =element_rect(fill ="white"),axis.ticks =element_blank(), # Remove axis ticksplot.background =element_rect(fill ="white", color =NA), # Remove plot background borderlegend.position ="none"# Remove the legend as there's only one line ) +labs(x ="Year",y ="Share of China (%)",title ="Share of Global Emissions from China" ) print(p_share)```China's substantial contribution to global emissions emphasizes its critical role in international climate change mitigation efforts. As the country with the largest share of global emissions, China's policies, and actions have a considerable impact on global emission trends. The country’s recent moves to eliminate coal subsidies, although a positive development, will need to be matched with further aggressive measures to curb emissions across all sectors, not only to align with its international commitments but also to mitigate the global environmental impact.## Section 3: Carbon Pricing InstrumentsThe urgent environmental challenge posed by increasing greenhouse gas (GHG) emissions has propelled the implementation of market-based mechanisms to incentivize reduction efforts. Carbon pricing stands as a strategic approach, marrying economic principles with environmental objectives. The primary instruments in carbon pricing are Emissions Trading Systems (ETS) and Carbon Taxes.### Emissions Trading Systems and Carbon TaxesETS, or cap-and-trade systems, set a cap on total GHG emissions and allocate or auction off permits to emitters, which represent the right to emit a certain amount. Entities can trade these permits, providing a financial incentive to reduce emissions; those who can reduce emissions at lower costs can sell their excess permits to others. By limiting the number of permits, the ETS ensures that the emission cap is not exceeded, while the trading mechanism discovers the price of carbon. By 2023, there are 37 ETS in operation worldwide, spanning national and subnational jurisdictions. These systems are critical in sectors where direct emission control is challenging.A carbon tax directly sets a price on carbon by levying a tax on the GHG emissions of fossil fuels. This straightforward approach makes emitting carbon more expensive and clean energy comparatively cheaper, encouraging investments in renewable energy and energy efficiency. By 2023, there are also 37 carbon taxes implemented around the globe.```{r}#| echo: falseCarbon_Emissions_Instrument <-read_excel("~/Downloads/Carbon_Emissions_Instrument.xlsx", sheet ="Compliance_Emissions_Edited")Beijing_ets_data <- Carbon_Emissions_Instrument %>%filter(`Name of the initiative`=="Beijing pilot ETS") %>%select(`2000`:`2023`)Beijing_ets_data <- Beijing_ets_data %>%mutate(Instrument ="Beijing pilot ETS") %>%select(Instrument, everything())Tianjin_ets_data <- Carbon_Emissions_Instrument %>%filter(`Name of the initiative`=="Tianjin pilot ETS") %>%select(`2000`:`2023`)Tianjin_ets_data <- Tianjin_ets_data %>%mutate(Instrument ="Tianjin pilot ETS") %>%select(Instrument, everything())Shanghai_ets_data <- Carbon_Emissions_Instrument %>%filter(`Name of the initiative`=="Shanghai pilot ETS") %>%select(`2000`:`2023`)Shanghai_ets_data <- Shanghai_ets_data %>%mutate(Instrument ="Shanghai pilot ETS") %>%select(Instrument, everything())Hubei_ets_data <- Carbon_Emissions_Instrument %>%filter(`Name of the initiative`=="Hubei pilot ETS") %>%select(`2000`:`2023`)Hubei_ets_data <- Hubei_ets_data %>%mutate(Instrument ="Hubei pilot ETS") %>%select(Instrument, everything())Chongqing_ets_data <- Carbon_Emissions_Instrument %>%filter(`Name of the initiative`=="Chongqing pilot ETS") %>%select(`2000`:`2023`)Chongqing_ets_data <- Chongqing_ets_data %>%mutate(Instrument ="Chongqing pilot ETS") %>%select(Instrument, everything())Fujian_ets_data <- Carbon_Emissions_Instrument %>%filter(`Name of the initiative`=="Fujian pilot ETS") %>%select(`2000`:`2023`)Fujian_ets_data <- Fujian_ets_data %>%mutate(Instrument ="Fujian pilot ETS") %>%select(Instrument, everything())Shenzhen_ets_data <- Carbon_Emissions_Instrument %>%filter(`Name of the initiative`=="Shenzhen pilot ETS") %>%select(`2000`:`2023`)Shenzhen_ets_data <- Shenzhen_ets_data %>%mutate(Instrument ="Shenzhen pilot ETS") %>%select(Instrument, everything())Guangdong_ets_data <- Carbon_Emissions_Instrument %>%filter(`Name of the initiative`=="Guangdong pilot ETS") %>%select(`2000`:`2023`)Guangdong_ets_data <- Guangdong_ets_data %>%mutate(Instrument ="Guangdong pilot ETS") %>%select(Instrument, everything())china_ets_data <- Carbon_Emissions_Instrument %>%filter(`Name of the initiative`=="China national ETS") %>%select(`2000`:`2023`)china_ets_data <- china_ets_data %>%mutate(Instrument ="China National ETS") %>%select(Instrument, everything())world_ets_data <- Carbon_Emissions_Instrument %>%filter(`Name of the initiative`=="Total") %>%select(`2000`:`2023`)world_ets_data <- world_ets_data %>%mutate(Instrument ="World Total") %>%select(Instrument, everything())instrument_data <-bind_rows(china_ets_data,Beijing_ets_data,Tianjin_ets_data,Shanghai_ets_data,Hubei_ets_data,Chongqing_ets_data,Fujian_ets_data,Shenzhen_ets_data,Guangdong_ets_data, world_ets_data)regional_ets_data <- instrument_data %>%filter(Instrument %in%c("Beijing pilot ETS", "Tianjin pilot ETS", "Shanghai pilot ETS","Hubei pilot ETS", "Chongqing pilot ETS", "Fujian pilot ETS","Shenzhen pilot ETS", "Guangdong pilot ETS"))regional_ets_total <- regional_ets_data %>%select(-Instrument) %>%summarise(across(everything(), ~sum(.x, na.rm =TRUE)))regional_ets_total <- regional_ets_total %>%mutate(Instrument ="Regional ETS") %>%select(Instrument, everything())China_world_data <-bind_rows(Beijing_ets_data,Tianjin_ets_data,Shanghai_ets_data,Hubei_ets_data,Chongqing_ets_data,Fujian_ets_data,Shenzhen_ets_data,Guangdong_ets_data,regional_ets_total,china_ets_data, world_ets_data)China_world_data <- China_world_data %>%mutate(across(everything(), ~ifelse(is.na(.x), 0, .x)))years_to_remove <-as.character(2000:2012) China_world_data <- China_world_data %>%select(-all_of(years_to_remove))regional_ets_total <- regional_ets_total %>%select(-all_of(years_to_remove))```### China's Pioneering RoleChina, recognizing its significant emissions problem, embarked on regional ETS pilots as early as 2013, in major cities and provinces including Beijing, Shanghai, Tianjin, Chongqing, Guangdong, Hubei, and Shenzhen. These pilots were instrumental in testing the waters for a national system.In 2021, China elevated its commitment by launching a national ETS. The system initially covers large coal- and gas-fired power plants, laying the foundation for expanding to more industries. It represents the largest carbon market in the world, given China's status as the top emitter of GHG.The global embrace of carbon pricing instruments is evident in the 2023 statistics, covering 23% of global GHG emissions, equivalent to 11.66 GtCO2e. The donut graph highlights that China's national ETS accounts for 8.92% coverage, a significant contribution reflecting its substantial emissions profile. Other regions together cover 14.2% of emissions with their carbon pricing instruments.Carbon pricing instruments are critical tools in the global strategy to mitigate climate change. ETS and carbon taxes both offer pathways to incorporate the cost of emissions into economic decision-making. China’s proactive measures, transitioning from regional pilot programs to a comprehensive national ETS, demonstrate a significant shift towards aligning economic activities with environmental targets. This approach underlines the potential of market-based mechanisms to address the climate crisis by incentivizing emissions reduction while allowing economic flexibility. As the global community continues to strive for a sustainable future, the evolution and effectiveness of these instruments in reducing GHG emissions remain a key focus.```{r}#| echo: falseChina_ETS <-filter(China_world_data, Instrument =="China National ETS")Regional_ETS <-filter(China_world_data, Instrument =="Regional ETS")World_Total <-filter(China_world_data, Instrument =="World Total")China_ETS_long <-pivot_longer(China_ETS, cols =`2013`:`2023`, names_to ="Year", values_to ="Emissions")Regional_ETS_long <-pivot_longer(Regional_ETS, cols =`2013`:`2023`, names_to ="Year", values_to ="Emissions")World_Total_long <-pivot_longer(World_Total, cols =`2013`:`2023`, names_to ="Year", values_to ="Emissions")proportion_data <-left_join(China_ETS_long, Regional_ETS_long, by ="Year", suffix =c("_China", "_Regional")) %>%left_join(World_Total_long, by ="Year") proportion_data_long <-pivot_longer( proportion_data,cols =c("Instrument_China", "Instrument_Regional", "Instrument"),names_to ="ETS_Type",values_to ="Proportion")proportion_data_long <- proportion_data_long %>%mutate(Year =as.numeric(Year))``````{r}#| echo: falselibrary(plotly)Instrument_2023 <- proportion_data_long %>%filter(Year ==2023)Instrument_2023 <- Instrument_2023[3, ]Instrument_2023 <- Instrument_2023[, 1:4]Instrument_2023_long <-pivot_longer(Instrument_2023, cols =-Year, names_to ="ETS_Type", values_to ="Proportion")emissions_value <- Instrument_2023_long[Instrument_2023_long$ETS_Type =="Emissions", "Proportion"]# Calculate the Uncovered Emissionsuncovered_emissions <-1- emissions_value# Create a new rownew_row <-data.frame(Year =2023, ETS_Type ="Uncovered Emissions", Proportion = uncovered_emissions)# Append the new row to the original data frameInstrument_2023_long <-rbind(Instrument_2023_long, new_row)emissions_total <- Instrument_2023_long[Instrument_2023_long$ETS_Type =="Emissions", "Proportion"]emissions_china <- Instrument_2023_long[Instrument_2023_long$ETS_Type =="Emissions_China", "Proportion"]# Calculate Emissions_Covered_Otheremissions_covered_other <- emissions_total - emissions_china# Create a new rownew <-data.frame(Year =2023, ETS_Type ="Emissions_Covered_Other", Proportion = emissions_covered_other)# Append the new row to the original data frameInstrument_2023_long <-rbind(Instrument_2023_long, new)Instrument_2023_long <- Instrument_2023_long[c(1, 4, 5),] fig <-plot_ly(Instrument_2023_long, labels =c("Emissions Covered by China National ETS", "Uncovered Emissions","Emissions Covered by Other Regions"), values =~Proportion, type ='pie', hole =0.6, textinfo ='label+percent',insidetextorientation ='radial', marker =list(colors =c('#b2dfee', '#89c4e2','#aec6cf'))) %>%# Change these colors to your preferred pastel blueslayout(title ='Global GHG Emissions Covered',annotations =list(list(text ='2023',x =0.5,y =0.5,font =list(size =20),showarrow =FALSE ) )) %>%layout(showlegend =TRUE)fig```## Outlook: Navigating the Climate Challenge in China and Asia-PacificThe Asia-Pacific region stands at a crossroads between development and environmental sustainability. With rapid economic growth, particularly in China, comes the stark reality of increasing emissions and the resulting environmental impact. Yet, there is a palpable shift towards seeking and implementing solutions to mitigate these challenges.The map illustrates that within the Asia-Pacific region, only a handful of countries have implemented carbon pricing instruments, with China leading the way with its national ETS. This reflects a proactive approach to climate change mitigation and demonstrates the potential for market-based instruments to incentivize emissions reduction in a way that can be integrated with the economic frameworks of the countries in the region.However, the map also reveals a vast potential for expansion. Only seven countries in the Asia-Pacific region have adopted carbon pricing strategies, underscoring the opportunity—and the need—for broader adoption of such policies. As the region collectively contributes significantly to global emissions, there is an imperative for more countries to adopt these mechanisms.China's experiences with ETS can serve as a model for neighboring countries. Active regional cooperation and exchange of knowledge are essential for the broader adoption of carbon pricing instruments. The expansion of these instruments, paired with regional collaboration, will be vital in shaping a sustainable and resilient Asia-Pacific. ```{r}#| echo: falsecarbon_instrument_data <-read_excel("~/Downloads/Carbon_Emissions_Instrument.xlsx", sheet ="Compliance_Price")east_asia_pacific_countries <- carbon_instrument_data %>%filter(Region =="East Asia & Pacific") %>%select("Jurisdiction Covered", "Instrument Type") %>%distinct()selected_jurisdictions <-c("Australia", "China", "Indonesia", "Japan", "Korea, Rep.", "New Zealand", "Singapore")east_asia_pacific_selected_countries <- east_asia_pacific_countries %>%filter(`Jurisdiction Covered`%in% selected_jurisdictions)east_asia_pacific_selected_countries <- east_asia_pacific_selected_countries %>%mutate(`Jurisdiction Covered`=ifelse(`Jurisdiction Covered`=="Korea, Rep.", "South Korea", `Jurisdiction Covered`))world <-ne_countries(scale ="medium", returnclass ="sf")countries_map_data <- world %>%filter(name %in% east_asia_pacific_selected_countries$`Jurisdiction Covered`)leaflet(data = countries_map_data) %>%addProviderTiles(providers$CartoDB.Positron) %>%addPolygons(fillColor =~colorFactor(palette ="blues", domain = countries_map_data$geounit)(geounit),weight =1, opacity =1,color ="white", dashArray ="3", fillOpacity =0.7,highlightOptions =highlightOptions(weight =2,color ="#A2D2FF",dashArray ="",fillOpacity =0.7,bringToFront =TRUE)) %>%addLegend("bottomright", pal =colorFactor(palette ="blues", domain = countries_map_data$geounit),values =~geounit, title ="Country",opacity =0.7)%>%setView(lng =100, lat =0, zoom =2.5)```## References and Data Sources[1] Lim, C. H., et al. (2024, January). Unlocking Climate Finance in Asia-Pacific: Transitioning to a Sustainable Future. International Monetary Fund, Asia and Pacific and Statistics Departments.[2] World Bank. State and Trends of Carbon Pricing Dashboard.[3] International Energy Agency (IEA). (2023, October). Fossil Fuel Subsidies Database: Fossil Fuel Consumption Subsidies for Selected Countries, 2010-2022.[4] World Bank. (2022, October 12). China’s Transition to a Low-Carbon Economy and Climate Resilience Needs Shifts in Resources and Technologies.[5] Basu, R., & Lim, C. H. (2024, January 29). Explainer: How Asia Can Unlock $800 Billion of Climate Financing.[6] Global Carbon Project. (2022). Supplemental Data of Global Carbon Budget 2022 (Version 1.0) [Data set]. Global Carbon Project. https://doi.org/10.18160/gcp-2022