The world population is projected to peak before 2050, with a significant majority residing in highly urbanized areas. As a result, urban areas are expected to undergo further anthropogenic transformations, which will not only influence spatial development (i.e. sealing urban systems) but also affect local climatic conditions. One likely consequence is the increasing incidence of adverse interactions between two phenomena occurring in city centers, which can have a significant impact on human quality of life: urban heat islands (UHI) and urban pollution islands (UPI). Here, we review scientific research relating to the interaction of UHI and UPI. Two basic databases were used: Web of Science and Scopus. The literature review covers publications appearing between 1968 and 2022 (Web of Science: 1,300 related to 'heat island', 18,222 on 'air pollution'; Scopus: 4,393 on 'heat island' and 34,498 on 'air pollution'), in fields such as environmental studies and meteorology studies. A significant number of the published articles were focused on cities located in Asia, Europe, and North America. Our findings show increasing research interest in UHI–UPI interactions, reflecting the risks they pose in the modern world—not only to human health and life, but also to the ecosystem. Effective urban planning emerges as a critical tool for addressing these challenges. Through the careful selection and implementation of targeted mitigation and adaptation strategies, it becomes possible to safeguard and enhance living conditions for urban populations. Such strategic planning is essential for ensuring that cities are not only habitable but also resilient and sustainable in the face of demographic shifts and environmental pressures. 

Assessing the effects of urban heat islands and air pollution on human quality of life

Abstract This study examines the characteristics of the urban heat island (UHI) in Dhaka, the densely populated capital city of Bangladesh under the influence of the South Asian monsoon, and its interaction with heat waves. For this, meteorological data at Dhaka (urban) and Madaripur (rural) stations and reanalysis data for the period of 1995–2019 are used for analysis. Here, the UHI intensity is defined as the urban-rural difference in 2-m temperature, and a heat wave is defined as the phenomenon which persists for two or more consecutive days with the daily maximum 2-m temperature exceeding its 90th percentile. The UHI intensity in Dhaka is in an increasing trend over the past 25 years (0.21 °C per decade). The average UHI intensity in Dhaka is 0.48 °C. The UHI is strongest in winter (0.95 °C) and weakest in the monsoon season (0.23 °C). In all seasons, the UHI is strongest at 2100 LST. The average daily maximum UHI intensity in Dhaka is 2.15 °C. Through the multiple linear regression analysis, the relative importance of previous-day daily maximum UHI intensity (PER), wind speed, relative humidity (RH), and cloud fraction which affect the daily maximum UHI intensity is examined. In the pre-monsoon season, RH is the most important variable followed by PER. In the monsoon season, RH is the predominantly important variable. In the post-monsoon season and winter, PER is the most important variable followed by RH. The occurrence frequency of heat waves in Dhaka shows a statistically significant increasing trend in the monsoon season (5.8 days per decade). It is found that heat waves in Bangladesh are associated with mid-to-upper tropospheric anticyclonic-flow and high-pressure anomalies in the pre-monsoon season and low-to-mid tropospheric anticyclonic-flow and high-pressure anomalies in the monsoon season. Under heat waves, the UHI intensity is synergistically intensified in both daytime and nighttime (nighttime only) in the pre-monsoon (monsoon) season. The decreases in relative humidity and cloud fraction are favorable for the synergistic UHI-heat wave interaction. 

pdf/characteristics-of-the-urban-heat-island-in-dhaka-bangladesh-1uz85k6jfb.pdf

Characteristics of the Urban Heat Island in Dhaka, Bangladesh, and Its Interaction with Heat Waves

Urban heat dynamics in local climate zones (LCZs): A Systematic review

Tropical cyclone (TC) peripheral downdrafts and urbanization can promote extreme heatwave (HW) events in the Greater Bay Area (GBA), a highly urbanized coastal area in China. However, the roles of synoptic patterns and urbanization in the HW events remain unclear, particularly for the joint occurrences of the tropical cyclone and heatwave (TC-HW) extremes. Here, we identify three synoptic patterns closely related to TC-HW events, namely: the northeastern Taiwan TC pattern (P4), the southeastern Taiwan TC pattern (P6), and the eastern Taiwan-Philippine Sea TC pattern (P7), as these patterns could enhance HWs through strong downdrafts, strong solar radiation, and low humidity, thereby favoring the maintenance of TC-HW events. Among the three patterns, P6 is most conducive to the occurrence of TC-HW compound events in the GBA. Moreover, the urban-rural temperature disparities under the TC-HW events are unique than those on the days without TC-HW events, i.e., the daily maximum temperature at rural and suburban stations is higher than that at urban stations. This unique feature is the opposite of the urban heat island and is mainly attributed to the rural subsidence warming induced by the TCs and Foehn effects. These results indicate that the spatial distribution of HW in coastal area is substantially modulated by TCs, which is meaningful to understanding the features and underlying mechanism of compound TC-HW events and adapting to their impacts. 

Tropical cyclone-related heatwave episodes in the Greater Bay Area, China: Synoptic patterns and urban-rural disparities

Abstract Global warming has resulted in higher frequencies of climate extremes, such as drought periods or heat waves. Heat waves are intensified in urban areas due to the urban heat island effect. Studies are inconclusive as to whether the urban heat island effect is intensified during heat waves. Using the city of Hannover, Germany, as a case study, we analysed the intensity of the urban heat island under unprecedented summer heat conditions in the years 2018, 2019 and 2020, which were among the hottest in Germany since weather records began. We compared the intensity of the urban heat island across these years with the non-heat year of 2017. Differences were analysed for various inner-city urban locations and an urban park, while accounting for their distinct land use and land cover characteristics. We identified the urban heat island effect across all years investigated in the study and also found a significant intensified urban heat island effect during the years of unprecedented heat, when night-time temperature minima are considered. The urban heat island was identified on a lower level, however, with maximum daily temperatures when compared to the non-heat year. The lowest intensity of the urban heat island was found for the urban park site, highlighting the need for more city-wide greening strategies, including tree-covered and open green spaces, to provide all residents with the cooling services of green spaces. 

The urban heat island under extreme heat conditions: a case study of Hannover, Germany

Under the background of global warming, interaction between heat waves (HWs) and urban heat island (UHI) has led to trends of increase in the intensity, frequency, and duration of extreme heat events in urban areas, seriously threatening the health of urban populations. Taking Guangzhou (a tropical megacity in China) as an example, this study used automatic weather station data and ERA5 reanalysis data to explore the interaction between HWs and UHI, and to elucidate the effects of wind speed and local climate zones (LCZs) on such interaction. Results revealed obvious HWs–UHI interaction in Guangzhou, whereby HWs induces an amplification effect on UHI intensity (UHII) that was most significant at night. In the main urban area, UHII and HWs both weakened with increasing wind speed, indicating that low wind speeds contribute to increased occurrence of HWs and enhancement of UHII. Differently, in some areas peripheral to the main urban area, the UHII at medium wind speeds was stronger than that at low wind speeds, which reflect the impact of heat advection from the urban center. For different LCZs in the main urban area, the strongest UHII, highest risk of HW occurrence, and most significant HWs–UHI interaction were found in the compact mid-rise buildings and compact low-rise buildings (LCZ2 and LCZ3, respectively), followed by the compact high-rise buildings (LCZ1), which was mainly affected by the shading effect of high-rise buildings. The weakest UHII and lowest risk of HW occurrence were found in open high-rise buildings and open mid-rise buildings (LCZ4 and LCZ5, respectively), which generally have good ventilation conditions. Our findings will help to understand urban warming and its association with UHI and HW events in tropical urban regions, which has implications for rational improvement of the urban thermal environment in other tropical urban regions globally.

/pdf/the-interactions-between-urban-heat-island-and-heat-waves-1o5szq3z.pdf

The interactions between urban heat island and heat waves amplify urban warming in Guangzhou, China: Roles of urban ventilation and local climate zones

S evere spring to early summer drought over Southwest China (SWC) in 2019 caught the public by surprise with its extreme intensity and damage (Ding and Gao 2020; Lu et al. 2021; Wang et al. 2021). Having still not fully recovered from this event, SWC then encountered one of its worst droughts on record in spring to early summer 2020 (the March–June mean ranks 13th and June ranks first in dryness since records began in 1961). Compared to the 2019 drought, the 2020 drought was episodic, developed rapidly from March to April due to the exceptionally high temperature and low precipitation, was slightly alleviated by sporadic precipitation during late April and May, and strengthened again to the lowest precipitation and highest temperature on record in June. This severe 2020 drought, especially in June, has raised questions about anthropogenic drought influences because of its large-scale damage to the local ecology, agriculture, and economy. Usually a humid region, SWC has suffered more frequent and severe droughts in recent decades (Li et al. 2019; Yan et al. 2017; Ding and Gao 2020). According to previous research on SWC droughts, persistent abnormal sea surface temperature (SST) over the tropical Pacific and Indian Oceans (Ju and Chen 2003; Liu et al. Fu Luo, Shanshan Wang, Yongli He, Yanxin Wang, and Hao Wang

Anthropogenic Warming Has Increased the 2020 Extreme Hot and Dry Conditions over Southwest China

Most western Northwest China (WNWC) has experienced notable wetting in recent decades. Despite the widespread attention of scientific community, the causes of such climate shift are still not well‐understood. In this study, we find that the dominant mode of Indian Ocean sea surface temperature variability — Indian Ocean Basin mode (IOBM) plays a crucial role in the precipitation over WNWC. Nonetheless, such a close lagged relationship is unstable, and varies with Pacific Decadal Oscillation (PDO). When the PDO is in its warm phase, there is no robust lagged relationship between April‐June WNWC precipitation variations and January‐March IOBM. When the PDO is in its cold phase, the warm phase of the IOBM inspires a wavetrain across the Eurasian continent in the next April‐June, with an uncommon low pressure around Lake Baikal, thereby enhancing the westerlies and thus more moisture into the WNWC region. This enables the IOBM‐based statistical rainfall prediction scheme to estimate the precipitation in the WNWC region with some confidence. This remarkable contrast in the influence of IOBM between the two phases of the PDO highlights exciting new avenues for improving climate predictions over the WNWC.

Enhanced Impacts of Indian Ocean Sea Surface Temperature on the Dry/Wet Variations Over Northwest China

In June‐July 2020, the Middle and Lower Yangtze River Region (MLYR) encountered the most severe precipitation event over the past 60 years. The Indian Ocean Dipole (IOD) in the previous autumn of the unusual precipitation event was the main contributing factor. Nonetheless, not every strong IOD event could bring anomalously high precipitation in the MLYR. This study showed significantly enhanced influence of IOD on East Asia climate since 2000. The IOD's effect on MLYR summer precipitation has strengthened significantly with the correlation coefficient up to 0.55 during 2000–2020. The northward movement of East Asia–Pacific pattern associated with IOD since 2000 (as compared with before) was primarily responsible for the enhanced effect. Since 2000, the MLYR has been controlled by a deep baroclinic instability system with anomalous low pressure in the lower troposphere and anomalous high pressure (completely different from before). Furthermore, the western Pacific subtropical high shifted northward and westerly jets were significantly enhanced with eastward expansion. All of these patterns contributed to the water vapor convergence and precipitation generation in the MLYR, which was not the case in the past. The record‐breaking IOD in 2019 autumn and the enhanced IOD's climatic effect in 2000–2020 contribute to the extreme Meiyu in 2020 jointly. The significant change in the influence of IOD and the enhanced climate effect of IOD highlight exciting new avenues for improving climate predictions in the MLYR.

Strengthened Impacts of Indian Ocean Dipole on the Yangtze Precipitation Contribute to the Extreme Rainfall of 2020 Meiyu Season

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The interactions between urban heat island and heat waves amplify urban warming in Guangzhou, China: Roles of urban ventilation and local climate zones

Anthropogenic Warming Has Increased the 2020 Extreme Hot and Dry Conditions over Southwest China

Enhanced Impacts of Indian Ocean Sea Surface Temperature on the Dry/Wet Variations Over Northwest China

Strengthened Impacts of Indian Ocean Dipole on the Yangtze Precipitation Contribute to the Extreme Rainfall of 2020 Meiyu Season