Impacts of urbanization on energy balance in a central Amazonia city – Nature

Report on Urban Energy Balance in Central Amazonia and its Implications for Sustainable Development Goals

Executive Summary

This report details a pioneering investigation into the radiation and energy balance of Manaus, a major urban center in Central Amazonia. Conducted during the wet and dry seasons of 2022, the study utilized a 30-meter micrometeorological tower to gather the first Eddy Covariance measurements for an urban region in the Amazon. The findings reveal significant alterations in energy partitioning due to urbanization, with direct implications for several Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 3 (Good Health and Well-being). The data underscores how urban surfaces, compared to the native rainforest, increase sensible heat flux, contributing to urban heat island effects and impacting local climate, energy consumption, and human health. This research provides critical data for developing sustainable urban planning strategies and climate resilience policies in tropical regions.

1.0 Introduction: Urbanization, Climate, and Sustainable Development

1.1 The Challenge of Sustainable Urbanization

Urban centers are pivotal to global sustainability. While occupying less than 3% of the Earth’s surface, cities are responsible for approximately 78% of global energy consumption and over 60% of greenhouse gas emissions. This concentration of human activity directly challenges the achievement of the Sustainable Development Goals. The process of urbanization fundamentally alters surface properties, impacting local climate and creating environmental pressures. This study addresses these challenges by examining the urban climate of Manaus, providing data essential for advancing:

• SDG 11 (Sustainable Cities and Communities): By investigating the microclimates of a rapidly growing tropical city, this research supports the development of resilient and sustainable urban environments.
• SDG 13 (Climate Action): Understanding how cities modify energy exchange with the atmosphere is crucial for improving climate models and developing effective climate change mitigation and adaptation strategies.

1.2 Research Objectives in the Amazonian Context

While extensive research has been conducted on the energy balance of the Amazon rainforest, the dynamics of its urban centers remain largely unknown. This study aims to fill that gap by providing the first comprehensive analysis of radiation and energy fluxes in Manaus. The primary objectives were:

1. To quantify the components of the radiation and energy balance in a dense urban area during distinct wet and dry seasons.
2. To assess the role of urban canopy heat storage in the surface energy balance.
3. To provide foundational data for urban climate modeling, contributing to risk management and sustainable urban planning in tropical megacities, thereby supporting the implementation of SDG 11 and SDG 13.

2.0 Methodology: Monitoring Urban Climate for Sustainability

2.1 Study Site and Data Collection

The study was conducted in a high-density residential area of Manaus, Brazil. A 30-meter micrometeorological tower was used to collect data throughout 2022, focusing on the wet (February-April) and dry (August-October) seasons.

• Instrumentation: The tower was equipped with an Eddy Covariance (EC) system, including a 3D sonic anemometer and an infrared gas analyzer, to measure turbulent energy fluxes. Radiation components and soil heat flux were also continuously monitored.
• Site Characteristics: The area within a 500-meter radius of the tower is characterized by 80.5% impermeable surfaces (buildings, concrete, asphalt) and 19.5% permeable surfaces (vegetation, soil). This landscape is typical of urban expansion and is central to the challenges of SDG 11.6 (reducing the environmental impact of cities).

2.2 Data Analysis and Energy Balance Assessment

Turbulent fluxes were calculated using standard EC procedures. A key component of the analysis was the estimation of heat storage in the urban canopy (S), which includes buildings and other structures. The inclusion of this term is critical for accurately assessing the urban energy balance and understanding how cities retain and release heat.

• Urban Heat Storage (S): The Thermal Mass Scheme (TSM) was used to estimate heat storage, accounting for the thermal properties of common construction materials like brick and zinc.
• Energy Balance Closure: The study evaluated the energy balance closure to ensure the quality and completeness of the measurements. The analysis confirmed that incorporating urban canopy heat storage (S) and soil heat flux (G) significantly reduces energy imbalances, providing a more accurate picture of urban energy dynamics.

3.0 Key Findings and Implications for Sustainable Development Goals

3.1 Seasonal Dynamics of Radiation and Energy Fluxes

The study identified significant seasonal differences in the energy balance, driven by changes in solar radiation and precipitation.

• Radiation Fluxes: Incoming shortwave radiation was substantially higher during the dry season due to lower cloud cover. The urban surface albedo was also higher in the dry season (0.18) compared to the wet season (0.15), indicating a change in surface reflectivity.
• Turbulent Fluxes: Sensible heat flux (H), which contributes to air temperature increases, was significantly higher during the dry season (peak of 251 Wm⁻²) compared to the wet season (119 Wm⁻²). In contrast, latent heat flux (LE), related to evaporation, showed low sensitivity to seasonal changes, a unique characteristic compared to non-tropical cities but similar to the surrounding rainforest.

3.2 Urbanization’s Impact on Energy Partitioning

The partitioning of available energy in Manaus differs starkly from the natural Amazonian landscape, highlighting the environmental transformation that challenges SDG 15 (Life on Land).

1. Wet Season: Latent heat flux (evaporation) was a dominant component, accounting for approximately 46% of the available energy, reflecting the high moisture availability.
2. Dry Season: Sensible heat flux dominated, converting 55% of available energy into heating the atmosphere. This shift is a key driver of the Urban Heat Island (UHI) effect.
3. Comparison with Forest: In contrast to the native forest where 70% of energy is used for evapotranspiration (LE), the urban area channels a much larger portion into sensible heat (H). This fundamental shift from a moist, cooling energy pathway to a dry, warming pathway is a direct consequence of replacing vegetation with impermeable surfaces.

3.3 Implications for SDG 11: Sustainable Cities and Communities

The findings directly inform strategies for building more resilient and sustainable cities.

• Urban Heat Island (UHI) Effect: The dominance of sensible heat flux, particularly in the dry season, confirms the mechanisms driving the UHI effect in Manaus. This contributes to thermal discomfort and health risks, undermining Target 11.6 on urban environmental quality.
• Sustainable Urban Design: The significant role of urban canopy heat storage demonstrates that building materials and urban geometry are critical factors in urban temperature. This knowledge can guide policies on green infrastructure, cool materials, and building design to mitigate heat, aligning with Target 11.B (adopting and implementing integrated policies for resilience).

3.4 Implications for SDG 13: Climate Action

This research provides crucial, high-resolution data for enhancing climate resilience.

• Improved Climate Modeling: The unique dataset from an Amazonian city can be used to validate and improve urban climate models, leading to more accurate forecasts of heatwaves and other climate-related hazards.
• Adaptation Strategies: By quantifying the urban impact on local climate, this study provides an evidence base for developing adaptation strategies, such as early warning systems for heat stress and nature-based solutions, contributing to Target 13.1 (strengthening resilience and adaptive capacity).

3.5 Implications for SDG 3 (Good Health) and SDG 7 (Affordable and Clean Energy)

The altered energy balance has cascading effects on public health and energy systems.

• Public Health (SDG 3): Increased urban temperatures and heat stress pose significant risks to vulnerable populations. This data can help public health officials map heat-vulnerable areas and design interventions.
• Energy Consumption (SDG 7): Higher urban temperatures lead to increased demand for air conditioning, straining energy grids and increasing greenhouse gas emissions. Promoting energy-efficient building designs and urban greening can reduce this demand, supporting Target 7.3 on energy efficiency.

4.0 Conclusion: Pathways to a Sustainable Urban Future in the Amazon

This study provides the first-ever measurements of urban energy balance in the Central Amazon, revealing that urbanization profoundly alters the local climate by shifting energy partitioning from evaporative cooling to atmospheric heating. The inclusion of urban canopy heat storage was proven essential for achieving energy balance closure, highlighting the critical role of the built environment.

These findings are not merely academic; they are a call to action for evidence-based policy and planning. To advance the Sustainable Development Goals in rapidly urbanizing tropical regions, it is imperative to:

1. Integrate urban climate data into municipal planning to mitigate the UHI effect and enhance climate resilience (SDG 11, SDG 13).
2. Promote green infrastructure and sustainable building materials to reduce heat storage and improve thermal comfort, thereby protecting public health and reducing energy demand (SDG 3, SDG 7, SDG 11).
3. Expand urban micrometeorological monitoring to other cities in the Amazon to build a comprehensive understanding of urbanization’s impact on this critical global ecosystem (SDG 15).

By leveraging this scientific understanding, cities like Manaus can pioneer sustainable development pathways that balance growth with environmental integrity and human well-being.

Analysis of Sustainable Development Goals (SDGs) in the Article

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

• SDG 11: Sustainable Cities and Communities

  The article is fundamentally about understanding the climate dynamics of an urban area, Manaus. It directly addresses the challenges of urbanization, such as the urban heat island effect, altered energy balance, and the environmental impact of a rapidly growing city. The introduction states, “Urban centers play a crucial role in global climate change, as cities increasingly accommodate the world’s population,” and the study aims to provide insights for “urban climate modeling” and “risk management,” which are core to creating sustainable cities.

• SDG 13: Climate Action

  The research investigates how urbanization alters local climate, which is a key aspect of climate change adaptation and mitigation. The introduction highlights that cities “generate over 60% of global greenhouse gas emissions.” By measuring and analyzing the components of radiation and energy balance, the study provides critical data for understanding and modeling the climatic impacts of cities, which is essential for developing strategies to strengthen resilience and adaptive capacity (Target 13.1).

• SDG 15: Life on Land

  The study is set in Manaus, a city within the Amazon, the “largest tropical rainforest region in the world.” The article repeatedly contrasts the urban environment’s energy dynamics with those of the surrounding forest and pasture lands. It discusses how urbanization and land-use change (from forest to urban) drastically alter surface properties like albedo and energy partitioning, thereby highlighting the climatic consequences of deforestation and the loss of terrestrial ecosystems.

• SDG 7: Affordable and Clean Energy

  The article notes that cities “consume 78% of the world’s energy.” The study’s findings on urban heat storage and sensible heat flux are directly related to the urban heat island phenomenon, which increases energy demand for cooling. Understanding these energy dynamics is a prerequisite for designing more energy-efficient cities and mitigating excessive energy consumption.

• SDG 9: Industry, Innovation, and Infrastructure

  This study represents a significant scientific and technological endeavor. It mentions the use of a “30-meter micrometeorological tower” and the “Eddy Covariance (EC) method,” describing the measurements as “the first Eddy Covariance measurements for an urban region of the Amazon.” This enhances scientific research and provides infrastructure for data collection, which supports innovation in urban planning and climate modeling.

• SDG 3: Good Health and Well-being

  The article mentions a significant negative impact of urbanization is “air pollution, which reduces incident solar radiation due to the emission of particles and gases.” It specifically notes that “anthropogenic nitrogen oxide emissions in Manaus intensify the formation of secondary organic aerosols.” Air pollution has direct consequences for human health, connecting the study’s context to SDG 3.

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

1. SDG 11: Sustainable Cities and Communities

   • Target 11.3: By 2030, enhance inclusive and sustainable urbanization and capacity for… sustainable human settlement planning and management. The article’s goal to provide “guiding insights for risk management” and data for “urban climate modeling” directly supports the capacity for better urban planning in a rapidly growing city like Manaus.
   • Target 11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality. The article explicitly identifies air pollution as a negative impact of urbanization in Manaus, mentioning “anthropogenic nitrogen oxide emissions” and “secondary organic aerosols.”
   • Target 11.b: …increase the number of cities… adopting and implementing integrated policies and plans towards… mitigation and adaptation to climate change, disaster risk reduction… The study’s data is presented as crucial for understanding urban climate extremes and developing adaptation strategies for tropical cities.

2. SDG 13: Climate Action

   • Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards. The research on urban heat islands and altered energy balance helps quantify climate-related hazards within cities, which is the first step toward building resilience.
   • Target 13.2: Integrate climate change measures into national policies, strategies and planning. The scientific findings are intended to be incorporated into “urban climate modeling in tropical regions,” which is a tool for integrating climate considerations into urban planning.

3. SDG 15: Life on Land

   • Target 15.1: …ensure the conservation, restoration and sustainable use of terrestrial… ecosystems and their services, in particular forests… The article provides a quantitative comparison of the energy balance between the urban area of Manaus and the surrounding Amazon rainforest, demonstrating the impact of replacing forest ecosystems with urban infrastructure.
   • Target 15.2: …promote the implementation of sustainable management of all types of forests, halt deforestation… By documenting the significant climatic changes that result from urbanization in a forest region (e.g., increased sensible heat flux, altered albedo), the study implicitly makes a case against deforestation for urban expansion.

4. SDG 7: Affordable and Clean Energy

   • Target 7.3: By 2030, double the global rate of improvement in energy efficiency. The article’s statement that cities “consume 78% of the world’s energy” frames the context. The study of heat storage and sensible heat flux relates directly to the urban heat island effect, a major driver of energy consumption for cooling, and provides a basis for improving urban energy efficiency.

5. SDG 9: Industry, Innovation, and Infrastructure

   • Target 9.5: Enhance scientific research, upgrade the technological capabilities… The entire study is an example of enhancing scientific research. It uses advanced instrumentation (“Eddy Covariance (EC) system”) and is described as a “pioneering investigation” and the “first Eddy Covariance measurements for an urban region of the Amazon.”

6. SDG 3: Good Health and Well-being

   • Target 3.9: By 2030, substantially reduce the number of deaths and illnesses from… air… pollution and contamination. The article’s mention of “air pollution” and “anthropogenic nitrogen oxide emissions” in Manaus directly relates to this target by identifying a key environmental health risk in the city.

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

Yes, the article is rich with quantitative data that can serve as or contribute to official SDG indicators.

1. For SDG 11 (Sustainable Cities and Communities):

   • Indicator for Target 11.3.1 (Ratio of land consumption rate to population growth rate): The article provides data points for this indicator by stating that Manaus’s population grew from “642,000 to approximately 2.2 million inhabitants” since the 1980s, and that the current land use is “predominantly classified as urban (48%)” and “forest fragments (35.5%).”
   • Indicator for Target 11.6.2 (Annual mean levels of fine particulate matter): While not providing a specific PM2.5 value, the article identifies key pollutants by mentioning “anthropogenic nitrogen oxide emissions” and the formation of “secondary organic aerosols,” which are precursors to fine particulate matter.

2. For SDG 13 (Climate Action):

   • Indicators for climate change impact and adaptation (Targets 13.1, 13.2): The core measurements of the study serve as direct indicators of local climate change due to urbanization. These include:
     • Sensible heat flux (H): Measured as significantly higher in the dry season (max of 251 Wm⁻²) compared to the wet season (119 Wm⁻²), indicating increased surface heating.
     • Surface albedo: Measured as 0.15 in the wet season and 0.18 in the dry season, quantifying the change in surface reflectivity compared to the surrounding forest (0.13).
     • Urban canopy heat storage (S): Quantified with maximum values of 102 Wm⁻² (wet) and 127 Wm⁻² (dry), a key factor in the urban heat island effect.
     • Greenhouse gas emissions: The introduction provides a global indicator that “cities… generate over 60% of global greenhouse gas emissions.”

3. For SDG 15 (Life on Land):

   • Indicator for Target 15.1.1 (Forest area as a proportion of total land area): The article provides this data for the study area, stating that the land cover includes “forest fragments (35.5%).” This serves as a direct measure of remaining forest cover within the urban landscape.

4. For SDG 7 (Affordable and Clean Energy):

   • Indicator for Target 7.3.1 (Energy intensity): The article provides a high-level contextual indicator by stating that cities “consume 78% of the world’s energy.” The detailed measurements of heat flux and storage provide a scientific basis for modeling urban energy intensity and efficiency.

4. Summary Table of SDGs, Targets, and Indicators

Source: nature.com