Key Findings

1. Top-performing cities, primarily in Europe, excel across all categories, particularly in climate emissions and air quality. Lower-performing cities, often in Asia and South America, face challenges with climate change, PM_2.5 pollution and urban heat indicators.

To assess the environmental performance of cities, we evaluate five categories composed of ten total indicators: 3 for air quality (gray), 2 for public transit (orange), 2 for urban heat (yellow), one for climate change (purple) and 2 for urban ecosystem (green). 

Top-performing cities (Figure 1)  consistently perform better in tree cover per capita, proximity to public transit, and fine particulate matter pollution (PM_2.5) concentration, while there is more variation in their urban heat, tree cover loss, and nitrogen dioxide (NO₂) concentration. Of the 25 top-performing cities, 18 are located in Europe and Central Asia, five in East Asia and the Pacific, and two in South America. 

The bottom 25 cities display greater variation across all categories and indicators. Most are also located in East Asia & Pacific - including 15 cities from China - followed by 2 cities in Sub-Saharan Africa, 2 in Europe and Central Asia, and 2 Latin American cities. However, it’s important to note that while Chinese cities are heavily represented as some of the lowest performers, this is partly due to the fact that they comprise 16 percent of UESI Global South cities and 8% of the total. As data coverage for Global South cities expands, we may see different outcomes. Across the board, low-scoring cities are struggling with PM_2.5 exposure, greenhouse gas emissions, and urban heat, while performance varies widely for tree cover and public transit. 

For example, Santiago (CHL) and Istanbul (TUR) have very low UHI scores, indicating an immediate need to improve urban heat exposure management. Among the lowest performers, Chinese cities such as Beijing, Wuhan, Suzhou, and Hangzhou have failed to provide their inhabitants with safe and clean air, despite making improvements over recent years.

2. Despite Sustainable Development Goal 11’s (SDG-11) charge for cities to be both sustainable and inclusive, cities are not sharing environmental benefits and burdens equally. 

While many cities perform well or above average on the UESI indicators, more than half of cities (166 out of 275) are failing to achieve these environmental results in an equitable way, disproportionately burdening less affluent citizens with poor air quality, exposure to urban heat, and lack of access to tree cover and public transport. As illustrated in Figure 2, the greatest number of cities are located in Quadrant 1 (101 or 37 percent), which indicates that environmental performance and equity are not necessarily concurrent, since these cities have better than average environmental performance but are still disproportionately burdening their less affluent citizens. Quadrant 3, where 65 (~23%) cities are located, shows an even worse scenario where poorer citizens disproportionately face more severe environmental outcomes in cities with already low environmental performance. 

While improving environmental performance is desirable, it does not necessarily provide a more equitable environment, highlighting the need for cities and local governments to actively address issues of distributional equity as part of their environmental and development interventions. This condition is global, as we see that many cities in North America, Europe & Central Asia and East Asia & the Pacific are burdening their poorer residents. 

3.  Wealth doesn’t always equate to strong environmental performance: some African cities outperform their GDP expectations, while emerging cities with larger populations rank low. Europe and North America’s wealthier cities continue to lead with high environmental performance.

For the first time, we do not observe a clear or obvious positive relationship between wealth and environmental performance. As Figure 3 illustrates, a cluster of African cities, including Dodoma and Shiyana in Tanzania and Freetown in Sierra Leone score above the average UESI score of 66. If wealth predicted environmental performance, we’d expect to see these cities perform below 40, where we see Chinese cities Jincheng, Tianjin, Chongqing and Urumqi, along with Monterey in Mexico. Instead, the strong performance of these African cities indicates the capacity for developing cities to perform as well as European and North American cities, shaded in red and blue respectively.

Interestingly, 56 cities, including major global cities like Singapore, Paris, Sydney and Los Angeles boast high levels of GDP per capita but lag in environmental performance. One of the primary reasons for their lower performance is due to our new Greenhouse Gas Emissions Index, which provides a comprehensive view of a city’s climate trajectory.  It penalizes cities with high emission per capita, high consumption based emissions, and negative emission trends over the past decade -- factors commonly associated with developed cities. In addition, some cities show particularly low scores on certain components of the UESI, primarily Air Pollution, Urban Heat and Urban Ecosystems, which lowers their overall performance score. 

For example, while Paris has an average score on the PM_2.5 indicator, it scores poorly in the Urban Ecosystem category, with districts losing a median of 9.6% of their tree cover since 2000 and only providing a median of 5.13 m² per person in each district. Singapore performs especially poorly in the GHG Index and Urban Ecosystem categories, and, when combined with average performances in other areas, lowers its overall score to place among the bottom 25 performers. These results suggest that the relationship between economic development and environmental performance is far from linear and instead influenced by factors such as urban planning, policy frameworks and each city’s individual economic and contextual circumstances.

4.  In nearly half of cities, environmental benefits and hazards are unevenly distributed, amplifying already stark income inequalities.

In nearly half of the cities (166 out of 275) analyzed, environmental benefits and hazards are unevenly distributed, deepening the already stark divides caused by income inequality (left-hand quadrants in Figure 4). Within these cities, negative environmental outcomes (e.g., air pollution and urban heat) are disproportionately affecting less affluent populations, which also have less access to amenities (e.g., tree cover) that would ameliorate them. On the other hand, 102 cities (right-hand quadrants in Figure 4) allocate their environmental outcomes so the more affluent populations are exposed to higher negative environmental conditions or have less access to positive ones. 

Additionally, 43 cities that allocate environmental burdens to their less affluent populations also exhibit higher than the average income inequality. This disparity compounds existing inequality, placing an even greater strain on lower-income communities (lower left-hand quadrant). While cities worldwide fall into this category, North American cities in particular are located here, where around 30 cities disproportionately expose less-affluent residents to environmental hazards. 

The lower left-hand quadrant of Figure 4 highlights the most extreme cases where both environmental and income inequalities converge, but it’s important to note that the upper left-hand quadrant, which includes 123 cities (~45%), also represents scenarios where the environmental burdens disproportionately fall on the less affluent, even if income inequality is less pronounced. This quadrant features cities from across the globe, including Melbourne (AUS), Vancouver (CAN), Ulsan (KOR), Paris (FRA), and Betim (BRA)l. On the other hand, cities in the right-hand quadrants represent cases where wealthier populations disproportionately bear the environmental burdens. 

Finally, it is important to note that these results are sensitive to the availability of income data (see Methods). Due to the use of globally-available GDP-proxy data for income, the calculations of both the Gini Index and the Concentration Index for cities lacking self-reported district-level income data show less within-city variability than income, which leads to a possible underestimation of real inequality for those cities (see further details in the Methods).

5. Progress on environmental performance and equity has stagnated between 2019 and 2024, revealing a concerning lack of momentum in cities' efforts to tackle growing environmental challenges and social disparities.

Analyzing the 2019 and 2024 UESI results reveals that overall environmental performance has barely shifted over the past five years. Despite some individual cities showing improvement—like Las Vegas (USA), Asunción (PRY), and Bangkok (THA)—the majority of cities have failed to make significant gains. In fact, some cities, such as Melbourne (AUS) and Bamako (MLI), have seen their environmental performance decline, indicating a broader lack of progress in addressing critical environmental challenges. 

Similarly, despite some variation in the distribution of overall results, UESI cities have not made significant strides in improving the equity of their environmental outcomes. Manaus (BRA) and Albuquerque (USA) are examples of only a few cities that have seen some improvements in equity, whereas some have become less equitable, like Delhi (IND) or Hangzhou (CHN).

The lack of an overall positive trend for both performance and equity metrics in UESI cities indicates that progress stalled between 2019 and 2024. These findings highlight the need for cities to intensify their efforts to provide healthier and safer environmental conditions for their citizens while taking actions to promote equity and justice.

6. Air pollution remains one of the most dangerous environmental threats to human health in cities.

Air pollution, the second leading risk factor for death after high blood pressure, is responsible for over 8 million deaths globally. Yet, almost all of the population living in UESI cities are exposed to unsafe PM_2.5 levels (higher than WHO 2021 PM_2.5 guideline: 5 μg/m³ ), compared to 99 percent globally.  91 percent of the population in UESI cities are exposed to at least a moderate level of PM2.5 (10 µg/m³ - WHO 2005 guideline). PM_2.5 exposure levels have been particularly high in Global South regions over the past two decades, where economic development is more closely associated with high-pollution industries such as coal-fired power plants, manufacturing, mining, and oil and gas extraction. 

Figure 6 shows smogstripes -  annual population-weighted PM_2.5 exposure compared to the 2005 WHO guideline for all UESI cities, seven regions, and selected cities. From the 267 UESI cities we evaluated, global air quality is generally improving. However, many cities in the Middle East & North Africa and South Asia continue to experience higher PM_2.5 levels, such as Tehran (IRN) and Bangalore (IND). Cities in East Asia & the Pacific, Latin America & the Caribbean, and Sub-Saharan Africa have managed to control air pollution, showing either a steady trend or a peak in PM_2.5 levels from a decade ago but a decrease in recent years, with examples including Seoul (KOR), Beijing (CHN), Mexico City (MEX), and Kinshasa (COD). On the positive side, cities in Europe & Central Asia and North America are making strides to improve air quality. For instance, after years of high PM_2.5 exposure for residents, London (GBR), New York City (USA), and Montreal (CAN) have successfully reduced PM_2.5 levels below 10 µg/m³ in 2020, 2008, and 2022, respectively.

7. Across the world, as urban temperatures have increased across regions, cities are still burdening the poor.

The urban heat island effect – the temperature difference between an urban area and the surrounding rural area – is exacerbated in cities with lower tree cover or more built environment. Adding vegetation to neighborhoods can help offset urban heat, providing shade and evaporative cooling. The construction of built-up structures makes urban heat more intense by storing and trapping heat, and replacing vegetation that could otherwise help keep urban areas cool. 

From 2019 to 2024, the median daytime surface Urban Heat Island (UHI) intensity has risen across all regions, increasing from 1.37°C to 1.51°C overall, with notable growth in the Latin America and Caribbean region. This upward trend is also evident across most climate zones, except in Arid regions, with the most pronounced increases observed in Tropical areas. Exposure to urban heat, however, is not evenly distributed across all neighborhoods. 156 out of 275 cities across multiple continents are disproportionately burdening their lower-income citizens with higher levels of UHI exposure regardless of their performance in this indicator including cities like Shenzhen (CHN), Delhi (IND), Madrid (ESP), Santiago (CHL), San Francisco (USA) among others highlighted in red in Figure 8. Inequality in urban heat distribution has also remained unchanged, since the number of cities that were disproportionately exposing the poor in 2019 (104 cities) is the same as in 2023.

While cities across multiple countries and continents are burdening poorer populations with higher UHI, this challenge continues to be prevalent in the US and Australia. since over 80% of the cities evaluated in those countries are burdening their less affluent citizens with higher UHI exposure.

8. Across multiple regions, about half of the cities have climate targets that are as ambitious as their country’s climate targets, however, there are still relevant cities particularly in the global north which are lacking concrete climate mitigation strategies.

The UESI’s new Climate Policy indicator provides a complete assessment of the available climate mitigation policies cities have pledged to reduce their GHG emissions. Following the recommendations of the Integrity Matters for Cities, States, and Regions, a guideline for net-zero target setting, the indicator evaluates climate mitigation documents on 4 key aspects: Ambition, Target Setting, Comprehensiveness and Transparency. Top-performing cities are primarily located in North America and Europe & Central Asia including Copenhagen (DNK), Denver (USA), Stockholm (SWE), and San Francisco (USA), while lowest-performing cities are present in all regions, although more frequently from the Global South. An example of cities pledging net-zero without a specific plan can be seen in cities like Vienna (AUT) and  Santo Domingo (DOM), which are part of collective initiatives but have failed to establish climate actions with concrete and comprehensive targets.

The national context for urban climate action is crucial for ensuring policy coherence and taking advantage of national strategies, including financial resources, to effectively implement urban climate strategies. Figure 8 shows the alignment between city climate mitigation targets and timeframes and national mitigation strategies, such as  Nationally Determined Contributions (NDC). Overall we see that 116 out of 216 cities (53% of the evaluated cities) distributed across all regions have a climate strategy that is just as ambitious as their corresponding national strategy, meaning that the city has the same mitigation target as the national government and aims to achieve it within the same timeframe, suggesting an existing linkage between local and national levels. Conversely, 33 cities (15%) in the US and Europe have less ambitious climate strategies compared to their national counterparts, which could hinder positive reinforcement between local and national efforts. Finally, we have a group of 67 cities that have no climate action plan or have no quantifiable mitigation targets located across multiple regions including Naples (ITA), Moscow (RUS), Tianjin (CHN) and Omaha (USA).

One possible reason some cities lack a comprehensive climate strategy could be the governance structure in certain countries. For instance, cities in highly centralized or unitary states, such as those in China and many parts of the Global South, may not have the capacity to develop independent plans and instead rely heavily on national strategies. However, cities in the Global North, particularly in the US and Europe, as well as capital cities in Latin America and the Caribbean, should prioritize developing their own climate strategies given their importance to both their countries and regions. 

9. Cities’ consumption-based emissions can be between 5 to 10 times their territorial emissions, highlighting the significant role urban areas play as both major contributors to emissions and key opportunities for climate change mitigation.

The UESI’s GHG Emission Index provides a comprehensive view of a city’s territorial emissions performance including their historic, near-past and current emissions trajectory, the intensity of their most recent emission per capita and per km2, and their carbon footprint per capita. Top-performing cities in this indicator are located in both developed and developing regions such as Genova (ITA), Rennes (FRA) and Kinshasa (COD), while low performers include Detroit (USA), Ulsan (KOR), and Singapore (SGP). Overall, we find that cities with better performance have higher proportion of territorial emissions associated with the energy and building sectors, while lower performance is associated with the high relative presence of industrial activity within the city boundaries, as well as higher consumption-based emissions.

Examining city carbon footprints in relation to their territorial emissions highlights the significance of emissions tied to urban centers, especially considering the imports of food, energy, and other goods produced outside these areas. Figure 9 shows the ratio of Carbon Footprint to Territorial Emissions, where we can observe that most cities in all regions are responsible for generating more emissions beyond their immediate t territorial emissions. For instance, cities in developed countries can have a carbon footprint of over ten times their territorial emissions, while other cities range between 2 and 5 times their territorial emissions. Lastly, a small group of cities, mainly in developing countries—particularly in Africa—have territorial emissions that are equal to or greater than their consumption-based carbon footprints.  Several factors influence these ratios, but a key one is the relocation of high-emitting sectors—such as industries, waste and wastewater treatment facilities, and energy plants—outside many developed cities. This exportation increases their consumption-based emissions as these activities still serve the cities' needs. In contrast, in some developing regions, these facilities are often located within city boundaries, contributing to higher territorial emissions. 

These results highlight the importance of consumption-based emissions when assessing the real contributions of urban areas to the global amount of emissions. A comprehensive assessment of these emissions enables cities to better grasp the full scale of their emissions, evaluate the potential effectiveness of their mitigation efforts, and understand their overall impact on climate action.

10. Tree Cover - UESI cities lost a total of 4,023.6 square kilometers of urban tree cover from 2000 to 2023  – an area more than 5.7 times the size of New York City. 

The cities that have experienced the greatest loss in urban tree cover from 2000 to 2023 (using a 2000 baseline) include Vientiane, Laos, mainly in nearby humid forest due to urban and agricultural expansion; Coimbra, Portugal, which experienced a substantial loss of forests due to plantations in the outskirts of the urbanized areas; Perth, Australia due to increased urban areas in previously undeveloped land and loss in the nearby forested area; Porto, Portugal which lost some of its already small forested areas particularly to the east of the city and Fortaleza, Brazil, which saw urban expansion throughout the city and loss of forest to the south. Figure 10 shows the cities with the highest proportions of tree loss during this period. 

Vegetated space tends to be removed to make space for new developments and city infrastructure, especially in developing countries where cities are still increasing their footprint and building infrastructure as their populations increase. 

11. Public Transit - More than a quarter of UESI cities (71 cities) on average lack access to public transit within walking distance.

Walking distance is defined as 1.2 kilometers or 0.75 miles, the distance an average city resident is willing to walk to a public transportation stop. Cities like Paris (FRA), Barcelona (ESP), Buenos Aires (ARG), and Tokyo (JPN) have public transportation stations that require a walking distance of less than 300 meters, while cities such as Wenzhou (CHN), Harare (ZWE), and Houston (USA) require residents to walk an average distance of at least 5 kilometers (just over 3 miles) to reach a public transit station. 

Overall, we see an improvement in performance on this indicator. Almost half, or 123 of the 275 UESI cities with sufficient data have on average a public transit station access within 1.2 kilometers or less for all their neighborhoods, which includes 34 cities that achieved this target for all their neighborhoods in 2019 as well as 33 cities that have reduced their distance below 1.2 km in 2023. In most other cities, access to public transit can vary dramatically across different parts of the city, but we see an improvement from 2019 with a reduction of the median distance to public transit from 530 meters to 334 meters in all neighborhoods. As we discuss in the Transportation profile , there are some limitations that should be considered when interpreting these results, particularly with respect to the source of transportation data used (OpenStreetMap) and the variable size of the neighborhoods.