Measuring global monetary damages from particulate matter and carbon dioxide emissions to track sustainable growth – Communications Earth & Environment

Abstract

An integrated framework that tracks global stocks and flows of natural capital is essential to assess sustainable economic growth. This study develops a comprehensive set of monetary damages from particulate matter air pollution and greenhouse gas emissions across 165 countries from 1998 to 2018. The findings indicate that pollution intensity increased after a decade of decline, driven by larger economic production shares and higher pollution intensity in China and India. Adjusting for pollution damage yields higher growth estimates before the Great Recession and attenuates growth afterward. Modeling monetary damages instead of physical measures affects sustainable development inferences. Particulate emissions’ monetary damages peak earlier in the development path than carbon dioxide emissions. In 2018, most countries were below the income level where damages peak, suggesting rising future damages as nations develop.

Introduction

Global Economic Transition

The global economy is transitioning, with energy systems moving away from fossil fuels, reshaped consumer behavior due to COVID-19, and disrupted trade networks due to geopolitics and war. These factors affect energy sources, consumption, and greenhouse gas emissions, emphasizing sustainability in economic growth.

National Income and Product Accounts (NIPAs)

Policymakers rely on NIPAs, including GDP, to track economic progress. However, NIPAs are incomplete as they do not capture the value of natural resources or pollution costs. Efforts to expand NIPAs include the System of Environmental Economic Accounting, adopted by 90 countries. Monetization of environmental quality facilitates tracking sustainable development by integrating environmental costs into NIPAs, aggregating values across resources, and capturing changes in societal willingness-to-pay for environmental improvements.

Sustainable Growth Definition

Sustainable growth requires non-negative capital formation, including both man-made and natural capital. As natural resources are consumed and the environment is used for residuals, the value of additional output must exceed the loss of natural capital.

Study Focus

This study tracks monetary damages from PM_2.5 and CO₂ across 165 countries from 1998 to 2018. Gross External Damage (GED) estimates are integrated into NIPAs to calculate environmentally-adjusted value added (EVA), capturing external pollution costs not included in conventional GDP estimates.

Results

Global Trends

From 1998 to 2008, EVA outpaced GDP growth, indicating a less pollution-intensive global economy. Post-Great Recession, GDP growth exceeded EVA, indicating increased pollution intensity. Developing economies’ rising output shares contributed significantly to this trend.

Income Group Analysis

1. High-Income Countries: Pollution intensity fell from 10% to 7% of GDP from 1998 to 2018.
2. Upper-Middle-Income Countries: Pollution intensity surged from 7% to 10%, driven by China’s rapid economic growth.
3. Lower-Middle-Income Countries: Pollution intensity increased gradually from 7% to 8%, with significant contributions from India.
4. Low-Income Countries: Stable pollution intensity at around 4% of GDP.

Environmental Kuznets Curve (EKC)

The EKC analysis shows that monetary damages peak at higher income levels than physical measures. For PM_2.5, damages peak at $45,000 per capita income, while CO₂ damages peak at nearly $80,000. This suggests that high-income countries have reached peak pollution damage, while developing nations are likely to see rising damages.

Sensitivity Analysis

Drivers of PM_2.5 Damages

The analysis shows that rising real income is the dominant driver of pollution damage in China and India. In developed countries, improving air quality partially offsets rising VSL due to income growth.

Parametric Sensitivity Analysis

• VSL Assumptions: Lower VSL results in lower pollution intensity estimates across all income groups.
• SCC Estimates: Higher SCC leads to higher pollution intensity estimates.

Conclusion

This study advocates for augmented NIPAs to track sustainable economic growth by integrating monetary damages from CO₂ and PM_2.5. Key findings include the global shift in pollution intensity post-Great Recession, the role of economic development in driving pollution damages, and the importance of monetizing environmental costs for accurate sustainable development assessments.

Data Availability

The data used in this study are publicly available at https://doi.org/10.5281/zenodo.7903337.

Code Availability

The code for producing all results and figures is available on Github at https://github.com/ani-mohan/Measuring-monetary-damages-air-emissions.

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Analysis of the Article in Relation to Sustainable Development Goals (SDGs)

1. Which SDGs are addressed or connected to the issues highlighted in the article?

1. SDG 3: Good Health and Well-being
2. SDG 7: Affordable and Clean Energy
3. SDG 8: Decent Work and Economic Growth
4. SDG 9: Industry, Innovation, and Infrastructure
5. SDG 11: Sustainable Cities and Communities
6. SDG 12: Responsible Consumption and Production
7. SDG 13: Climate Action

2. What specific targets under those SDGs can be identified based on the article’s content?

1. SDG 3: Good Health and Well-being
   • Target 3.9: Substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water, and soil pollution and contamination.
2. SDG 7: Affordable and Clean Energy
   • Target 7.2: Increase substantially the share of renewable energy in the global energy mix.
3. SDG 8: Decent Work and Economic Growth
   • Target 8.4: Improve progressively, through 2030, global resource efficiency in consumption and production and endeavor to decouple economic growth from environmental degradation.
4. SDG 9: Industry, Innovation, and Infrastructure
   • Target 9.4: Upgrade infrastructure and retrofit industries to make them sustainable, with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies.
5. SDG 11: Sustainable Cities and Communities
   • Target 11.6: Reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management.
6. SDG 12: Responsible Consumption and Production
   • Target 12.4: By 2020, achieve the environmentally sound management of chemicals and all wastes throughout their life cycle.
7. SDG 13: Climate Action
   • Target 13.2: Integrate climate change measures into national policies, strategies, and planning.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

1. SDG 3: Good Health and Well-being
   • Indicator 3.9.1: Mortality rate attributed to household and ambient air pollution.
2. SDG 7: Affordable and Clean Energy
   • Indicator 7.2.1: Renewable energy share in the total final energy consumption.
3. SDG 8: Decent Work and Economic Growth
   • Indicator 8.4.1: Material footprint, material footprint per capita, and material footprint per GDP.
4. SDG 9: Industry, Innovation, and Infrastructure
   • Indicator 9.4.1: CO2 emission per unit of value added.
5. SDG 11: Sustainable Cities and Communities
   • Indicator 11.6.2: Annual mean levels of fine particulate matter (e.g., PM2.5) in cities (population weighted).
6. SDG 12: Responsible Consumption and Production
   • Indicator 12.4.2: Hazardous waste generated per capita and proportion of hazardous waste treated, by type of treatment.
7. SDG 13: Climate Action
   • Indicator 13.2.2: Total greenhouse gas emissions per year.

4. Findings from Analyzing the Article