Dynamic Assessment of Urban Carrying Capacity Load Number Using the Enhanced UCCLN Model

Marissa Liponhay (), Alyssa Valerio, Glydel Fornan, Christian Alis and Christopher Monterola
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Marissa Liponhay: Analytics Computing and Complex Systems Laboratory (ACCeSs@AIM), Asian Institute of Management, 123 Paseo de Roxas, Makati City 1229, Philippines
Alyssa Valerio: Analytics Computing and Complex Systems Laboratory (ACCeSs@AIM), Asian Institute of Management, 123 Paseo de Roxas, Makati City 1229, Philippines
Glydel Fornan: Analytics Computing and Complex Systems Laboratory (ACCeSs@AIM), Asian Institute of Management, 123 Paseo de Roxas, Makati City 1229, Philippines
Christian Alis: Analytics Computing and Complex Systems Laboratory (ACCeSs@AIM), Asian Institute of Management, 123 Paseo de Roxas, Makati City 1229, Philippines
Christopher Monterola: Analytics Computing and Complex Systems Laboratory (ACCeSs@AIM), Asian Institute of Management, 123 Paseo de Roxas, Makati City 1229, Philippines

Sustainability, 2023, vol. 16, issue 1, 1-19

Abstract: The sustainability of cities often changes as rapid urban developments and population growth affect the carrying capacity. Understanding the dynamics of carrying capacity becomes crucial for tourist-oriented cities. This study focused on Baguio City, the “Summer Capital of the Philippines”, attracting large crowds on holidays and actively promoting various events on other days, thus having temporal context variations classified as regular days, days with events, and holidays. Using the enhanced urban carrying capacity load number (EUCCLN) model, the changes in the load number (LN) are calculated for different temporal contexts based on spatial indicators grouped into air, traffic, economy and waste. The city experiences the worst pressures on air quality during holidays, with 99.23% of the districts at very high to critical levels, followed by regular days and days with events. However, the total LN during holidays is balanced by favorable economic conditions with only 9.23% of the districts at the critical level. EUCCLN effectively pinpoints areas that are at critical states at any given time, advocating targeted government monitoring. We demonstrate that nighttime light, for places with no available economic data, can be used as a proxy to highlight areas requiring improved urban vibrancy. This work suggests that monitoring urban pressures using EUCCLN can easily be extended to real time with nowcasting indicator data.

Keywords: enhanced urban carrying capacity load number (EUCCLN) model; urban ecosystems; urban sustainability; urban carrying capacity; Baguio City (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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