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Impacts of projected urban growth on simulated near-surface temperature in Mexico City Metropolitan Area: Implications for urban vulnerability [1]
['Yosune Miquelajauregui', 'Laboratorio Nacional De Ciencias De La Sostenibilidad', 'Instituto De Ecologia', 'Universidad Nacional Autónoma De México', 'Mexico City', 'Erika Danaé López-Espinoza', 'Instituto De Ciencias De La Atmosfera Y Cambio Climatico', 'Erika Luna Pérez', 'Paola Gómez-Priego', 'Luis A. Bojórquez-Tapia']
Date: 2024-04
Abstract Urbanization impacts the surface temperature fields increasing the vulnerability of urban residents to heat exposure. Identifying vulnerable urban populations to extreme heat exposure is crucial to develop mitigation and adaptation strategies towards sustainability. We used an urban growth model (SLEUTH) to simulate emerging urban areas in Mexico City Metropolitan Area (MCMA) under a hypothetical land-use policy scenario projected to 2060 in which no restrictions were posed to urban growth. SLEUTH outputs were used in the numerical model Weather Research and Forecasting (WRF) to quantify expected changes in near-surface temperature within the MCMA. We calculated and mapped heat exposure as differences in average (Tmean), maximum (Tmax) and minimum (Tmin) temperatures over the diurnal cycle between future and current land cover conditions. Population vulnerability to projected increases in heat exposure was determined using a set of socioeconomic indicators. SLEUTH simulations showed an urban area expansion of nearly 4,790 km2 by 2060. Overall, changes in Tmin were greater than changes observed for Tmax and Tmean. Tmean, Tmax and Tmin increases up to 0.6°C, 1.3°C and 2.6°C, respectively, were recorded for the MCMA with greatest temperature changes observed in the State of Mexico. Results suggested the presence of socioeconomic disparities in the projected spatial exposure of urban-induced heat in MCMA. We argue that our results could be used to inform and guide locally tailored actions aimed at reducing exposure and increasing population´s capacities to cope and adapt to future threats.
Citation: Miquelajauregui Y, López-Espinoza ED, Luna Pérez E, Gómez-Priego P, Bojórquez-Tapia LA, Aquino Martínez LP, et al. (2024) Impacts of projected urban growth on simulated near-surface temperature in Mexico City Metropolitan Area: Implications for urban vulnerability. PLOS Clim 3(4): e0000396.
https://doi.org/10.1371/journal.pclm.0000396 Editor: Jamie Males, PLOS Climate, UNITED KINGDOM Received: June 14, 2023; Accepted: March 1, 2024; Published: April 16, 2024 Copyright: © 2024 Miquelajauregui et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials. Also, raw data were generated at Laboratorio Nacional de Ciencias de la Sostenibilidad and at Instituto de Ciencias de la Atmósfera y Cambio Climático - UNAM. All data available in
https://zenodo.org/records/10119135. Funding: This work was supported by the National Science Foundation under grant CNH Grant (1414052 to LABT) for project 'The Dynamics of Multi-Scalar Adaptation in the Megalopolis: Autonomous Action, Institutional Change and Social- Hydrological Risk (MEGADAPT)', and by the Inter-American Institute for Global Change Research under Grant (CRN3108 to LABT). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.
1 Introduction Urbanization is one of the main driving forces of environmental change across multiple scales [1, 2]. The rate of urbanization is increasing rapidly around the world expecting urban land cover to nearly tripling by 2030 [3]. Urbanization increases population density and leads to the replacement of natural land cover with built structures of greater impervious surface areas [4]. Consequently, urbanization can alter the biogeophysical and biogeochemical variables that determine the local and regional climate which impacts can be observed in changes in temperature and precipitation patterns [5–7]. An increase of approximately 0.23°C has been attributed to urban expansion across the continental United States over the past half-century [8]. Similarly, the escalating temperatures attributed to urbanization have been documented in Asian megacities, revealing temperature increases ranging from 0.74°C to 1.6°C, particularly in the densest areas of the city during nighttime [7, 9–11]. This urbanization-driven temperature rise intensifies the vulnerability of urban residents to heat exposure [9, 12]. Additionally, climate change is likely to exacerbate these risks as severe heat waves and droughts become more frequent [13]. Significantly, instances of extreme heat exposure have become more prevalent, affecting half of global urban settlements, and impacting nearly a quarter of the world´s population since the end of the 20th century [14]. Consequently, the identification of high-risk urban populations vulnerable to extreme heat exposure is fundamental for promoting sustainable urban development. Vulnerability may be characterized as the susceptibility of urban populations to harm from exposure to urban heat [15, 16]. Nevertheless, the uneven distribution of vulnerability is evident among diverse populations [17–19]. Disparities in vulnerability are related to the interplay of socioeconomic, demographic, infrastructural and environmental determinants [20, 21]. Hence, this underscores the imperative to craft site-specific mitigation and adaptation strategies targeted at diminishing exposure and amplifying capacities to cope and adapt to future threats [22, 23]. In pursuit of this objective, analytical and modelling tools have become indispensable for capturing, quantifying, and visually representing the spatial distribution of heat exposure within cities [11, 24, 25]. The exploration of urban climate has traditionally centered on the analysis of urban heat patterns often employing numerical models such as MUKLIMO_3 [26], UrbClim [27], and MESO-NH [28]. However, simulations have only encompassed either specific sections of a city for several months or entire cities spanning decades [29–31]. Notably, the Weather Research and Forecasting (WRF) model stands as an exceptionally versatile numerical weather prediction and atmospheric simulation system, extensively utilized across various applications, including urban climate studies [11, 32–34]. In particular, the integration of the WRF model with urban sprawl simulation tools, like SLEUTH [35], confers the capability to generate fine-grained weather forecasts while simultaneously considering urbanization patterns at both local and regional scales [9]. This stands as perhaps the most important consideration for mitigating the vulnerability of urban populations, particularly in cities located in the Global South, such as the Mexico City Metropolitan Area (MCMA). Many of the climate studies based on WRF modeling carried out in the MCMA, have primarily focused on investigating the impact of urbanization on regional meteorology. For instance, [36] studied the sensitivity of temperature forecasts to changes in urban coverage. Similarly, [37], undertook an analysis to ascertain the spatiotemporal variations in near-surface temperature and precipitation resulting from the current urban landscape when compared to pre-settlement conditions. More recently, [38, 39] explored alterations in the diurnal cycles of temperature, precipitation and wind fields associated with urban sprawl. Despite the notable progress of the studies, there remains a gap in urban climate research pertaining to local and long-term exposure to extreme heat, particularly considering the inherent uncertainty of future urban expansion in the MCMA. In this study we integrated WRF with SLEUTH to examine the vulnerability of urban populations to future heat exposure risks induced by urban sprawl in Mexico City Metropolitan Area under a no restrictive urban growth scenario. We coupled SLEUTH outputs with WRF to simulate expected changes in near-surface temperature within the MCMA. We calculated the Gower’s residuals to assess the vulnerability of urban residents to projected heat exposure using socioeconomic indicators derived from the 2020 national census. We argue that the results of this study contribute to identify potential vulnerable areas to heat exposure, which could consequently lead to unequal distribution of vulnerability. Although outside the scope of this study, our results can also be combined with climate change projections to assess synergistic impacts on urban vulnerability to heat exposure. In addition, the resulting insights of this research can contribute to the understanding of the overall quality of life within urban environments the MCMA. The SLEUTH/WRF modelling framework presented here possesses the potential to furnish decision-makers with valuable inputs, guiding the formulation of strategies and initiatives aimed at mitigating vulnerability to extreme heat.
4 Discussion In this work, we simulated future urban growth in Mexico City Metropolitan Area projected to 2060 under a no restrictive scenario (U2060 experiment) using the cellular automata model SLEUTH. We integrated SLEUTH outputs to WRF to evaluate heat exposure measured as Tmean, Tmax and Tmin changes linked to future urban conditions. Socioeconomic vulnerability was assessed for selected administrative units according to a set of population, health, economic and infrastructure indicators. The Gower’s residuals provided insights into the relative vulnerability levels of different administrative units based on selected indicators of population, health, economy, and infrastructure. Hence, our results contribute to the overall understanding of the physical connections between temperature increases and the expansion of impervious surfaces in urban spaces and provides information about the spatial distribution of heat exposure in MCMA. This characterization allowed us to prioritize the administrative units greater exposed projected heat risks within the MCMA. According to SLEUTH simulations, urban growth in the MCMA is expected to cover an area of 6,811 km2 by 2060 under our no restrictive scenario. This represents a percentage change of 337% (~4,790 km2) compared to current conditions. According to simulations, the greatest urban expansion would occur in the northern and southern portions of the State of Mexico and Hidalgo, respectively. In Mexico City, most of the projected urban expansion would take place in the southern municipalities of Tláhuac and Xochimilco. Our results agree with historical urban growth patterns in the MCMA. According to [73], the MCMA experienced an accelerated urban and industrial expansion during the last decade of the 20th century, with substantial increases in population, infrastructure, and transportation. From 1995 to 2010, urban expansion took place predominantly in Ecatepec, Cuautitlán Izcalli, Ixtapaluca and Zumpango located in the north of the State of Mexico as well as in Tizayuca in Hidalgo, reaching the highest growth rates by 2015 (S2 Fig). During that period, new informal urban areas were also developed in the southern portion of Mexico City, where much of the conservation land (CL) is located. The CL covers nearly 50% of the total area of Mexico City and represents a space of high ecological value protected under federal laws and regulations [74]. As urban borders expand to meet population growth demands, the replacement of natural land surfaces by impervious surfaces and the loss of green spaces increase the regional heat storage capacity [4, 73]. Our WRF simulations indicate significant contributions of land use and land cover changes associated to new urban developments to increases in Tmean up to 1.3°C in many parts of the MCMA by 2060, particularly in the north of the State of Mexico and the south of Hidalgo. These regions are characterized by a rather flat topography compared to the more complex orography encompassing the western and eastern portions of the MCMA [75]. Disparities in topography can significantly contribute to the simulated increases in near-surface temperature extending well beyond the MCMA limits (Fig 3). Urban-induced temperature increases have been largely reported in the scholarly literature. For instance, [36] documented mean temperature differences between 1990 and 2009 urban landscapes from 0.5 to 1°C. Additionally, [37, 76] carried out numerical simulations of thermal variations due to past land use changes in MCMA with temperature increases of up to 4°C. In our study, the most relevant urban-related impact was observed for nightime temperatures (Tmin) with an increase up to 2.6°C reflecting the nocturnal nature of heat release. This work adds to the growing number of regional WRF modelling studies examining the relative contribution of different land cover types on simulated temperature changes (e.g., the replacement of water bodies by urban cover) [4, 7, 76]. Greatest Tmin changes were associated with losses of agricultural land and water bodies as shown in Fig 4. In this line of thinking, [37, 58, 76] established a direct physical link between the observed historical warming and the drastic reduction of the lacustrine system that once covered much of the total surface area of the Basin of Mexico. Our results show that vulnerability to projected heat exposure is unequally distributed within MCMA. In Ecatepec and Cuenca de México Hidalguense, the major socioeconomic vulnerability sources were defined by population, economic and health conditions, whereas in Tláhuac and Texcoco by infrastructure conditions (Fig 1A, Table 2). According to current projections, the State of Mexico and Hidalgo are anticipated to undergo a population growth of 12% and 8%, respectively by 2050 accompanied by significant increases in social deprivation ([77]; S2 Fig). Notably, the State of Mexico is expected to become the densely populated state at the national level by 2050. Population growth for Mexico City is projected to decrease, unlike the State of Mexico and Hidalgo, most likely due to lower birth rates and increased mobility to other states [77]. Our findings emphasize the multidimensional nature of vulnerability as stated by [15]. This matches with some environmental studies conducted in urban centers worldwide (i.e., [14, 78]) which argue that socially and economically disadvantage people are disproportionally affected by extreme heat exposure. Our findings also stress the importance of developing joint solutions so that extreme heat mitigation policies and social vulnerability reduction and adaptation policies (i.e., human, social, financial, physical, and technical) can reinforce each other. Future vulnerability assessments for sustainable urban planning need also to explore how heat risk exposure is negotiated in decision-making processes under contexts of uncertainty. These analyses could shed light into the complexity of interactions of coupled human-environmental systems and how multiple risks cascade spatially and temporally [79]. This paper provides spatially explicit information on differentiated urban-related projected heat exposures that can be incorporated in future research aiming at examining uncertainties associated with socio-demographic projections, governance and institutional elements (i.e. accountability, transparency, conflict resolution, participation, and inclusion), which can also drive socioeconomic vulnerability. We encountered a few challenges during the implementation of SLEUTH. Firstly, due to the complex nature of urban growth patterns within the MCMA, the calibration of SLEUTH with historical data was challenging. Secondly, within the MCMA, administrative units are subject to local, state, or federal conservation regulations crafted to safeguard priority conservation areas from urban growth. Nonetheless, the effectiveness of these regulations varies significantly throughout the MCMA due to deficiencies in governance and lax enforcement of land tenure and land regularization [80]. As a result, SLEUTH was not employed as a predicting model but was utilized primarily as an exploratory tool, facilitating the examination of the most extreme scenario—where urban sprawl encountered no constraints—Thirdly, the spatial resolution of our analysis proved challenging, particularly for the percentage slope allowed. Some areas of the MCMA have shown urban growth in slopes of 30% or more, measured at a scale not available for all input data layers. Thus, working at a 1 ha resolution might diminish SLEUTH capacity to capture the actual growth on some of the high-risk urban populations. Finally, in recent years some areas of the MCMA are growing vertically rather than through urban sprawl and the effects on extreme heat exposure cannot be measured with the two models applied. Improvements to our methodology can be disaggregated into the two models used. Initially, the recent availability of openly accessible imagery sources, such as Sentinel and the new digital elevation models at a 1: 20,000 scale could have offered the potential to enhance the data resolution. However, this could have limited SLEUTH forecasting capacity by reducing the time frame of historical data. For WRF, improvements to our methodology include tuning the numerical weather prediction (NWP) based on the WRF model for the Valley of Mexico to capture model sensitivities to variations in how land surface processes associated to different land cover types are represented and parametrized (i.e., [36]). Additionally, important sources of variation in urban temperatures including anthropogenic heat release, urban density and design could be also included in future studies. We acknowledge that urban growth combined with climate change can lead to higher projected increases in near-surface temperature [4]. Analyzing synergistic impacts of multiple drivers of heat risk exposure is therefore critical to achieve sustainable urban systems, however, it was out of the scope of this paper.
5 Conclusions Risk informed decision-making for sustainable urban planning requires the consideration of scenarios of exposure and vulnerability. In this work, we coupled WRF with SLEUTH to ascertain the vulnerability of urban populations to future heat exposure in Mexico City Metropolitan Area under a no restrictive urban growth scenario. According to SLEUTH simulations, greatest urban expansion occurred in the northwest part of the State of Mexico and the southern portion of Hidalgo. WRF simulations showed that overall, losses of natural surfaces increased near-surface temperature (Tmean, Tmax, and Tmin). Tmin was a better indicator of thermal changes compared to Tmax, Tmean. Urban-induced heat exposure together with socioeconomic attributes including population, health, economic status, and infrastructure are drivers of population vulnerability. In the case of Ecatepec and Cuenca de Mexico Hidalguense, socioeconomic vulnerability was mostly associated with population density, unemployed population, and population with limited access to health care, whereas Tláhuac vulnerability was associated with limited access to infrastructure services such as drinking water and electricity. The results of this study can serve as reference information for decision-makers to ensure that urban expansion in the MCMA is sustainable through the implementation of urban policy measures that regulate the development of new urban settlements. This study emphasizes the role of urban planners in designing projects considering a wider extension beyond the MCMA to take preventive measures to reduce the environmental impacts and the consequences of warming. Moreover, close collaboration between academia and the government through long-term, well-financed research is required to better inform guidelines to mitigate heat exposure risks and reduced associated vulnerabilities.
Acknowledgments We acknowledge the support of Dr. Hallie Eakin of the School of Sustainability, Arizona State University (ASU) during the development of this project. We would also like to thank Fidel Serrano-Candela, Rodrigo García Herrera, and Edith P. Villa Mendoza from the Laboratorio Nacional de Ciencias de la Sostenibilidad for their key participation in generating the urban projections, and to Octavio Gómez Ramos from the Instituto de Geofísica for his technical assistance with the WRF model. The authors gratefully acknowledge the computing time granted by LANCAD and CONACYT on the supercomputer Miztli at DGTIC UNAM (Project: LANCAD-UNAM-DGTIC-393).
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