Urban Air Pollution, Urban Heat Island and Human Health: A Review of the Literature

Evaluating the role of formal urban blue spaces in ecosystem service provision: Insights from New Town, Kolkata

The Urban Blue Space (UBS) refers to managed and unmanaged water spaces crucial for sustainable urban development. This study examines the changes in Ecosystem Service Value (ESV) associated with UBS change in New Town, Kolkata from 1990 to 2020. This study reveals a 254-ha decrease in total blue space and a significant transformation from informal to formal UBS. A 438.43 % increase in built-up areas causes fragmentation of the overall blue spaces, whereas the core area has increased for formal blue spaces providing higher ESV. The total Ecosystem Service Value (ESV) for formal UBS has increased from $478070.44 per year/hectare to $3460197.99 per year/hectare during the study time showing a growing contribution of formal blue space for sustaining ecosystem services. However, the ESV from informal UBS has decreased from $10523635.78 per year/hectare to $9230323.36 per year/hectare. This positive change in ESV obtained from formal UBS and negative change in ESV obtained from informal UBS indicates the importance of formal UBS for maintaining ESV supply for the study area. Hence, the findings highlight the need for policy formulation for the conservation of existing formal blue spaces and the upgradation from informal UBS to formal UBS to maintain sustainable urban development of the study area. This new categorization of UBS and the impact of formal and informal UBS fragmentation on ESV change will open a new avenue for understanding the importance of formal UBS for maintaining ESV in the changing urban scenario of other cities of the world.

Locating the built environment within existing empirical models of climate change and mental health: protocol for a global systematic scoping review

INTRODUCTION

Where a person lives, the characteristics of their housing and neighbourhood environment influence their exposure to climate-related hazards and vulnerability to associated mental health impacts. This suggests that the built environment may be a promising focus for integrated policy responses to climate change and public mental health challenges. However, few empirical studies have focused on the role of the built environment as an important mediator of climate-attributable mental health burden. The proposed scoping review seeks to identify and synthesise existing conceptual models and frameworks linking climate change to mental health via built environment pathways. We aim to provide a preliminary overview of the housing and neighbourhood pathways through which climate change may impact mental health, which will inform future empirical work in this emerging area of research.

METHODS AND ANALYSIS

A systematic scoping review of the global peer-reviewed and grey literature will be conducted in accordance with Arksey and O'Malley's methodological framework and Joanna Briggs Institute recommendations. Included articles must present a conceptual model or framework incorporating relevant built environment pathways through which climate change may impact mental health and well-being. Relevant models and frameworks will be identified through systematic searches (for English-language reports) of Medline, PsycINFO, Embase, Scopus, Web of Science and grey literature databases. Two reviewers will independently screen the article titles, abstracts and full texts, with conflicts resolved by a third reviewer. Data extraction will occur using a predefined template. The presentation of findings will conform to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews, including a narrative synthesis of the role of housing and neighbourhood factors in the relationship between climate change and mental health, as identified from the existing literature. The review will lay essential foundations for future empirical research and place-based policy responses to the mental health consequences of a changing climate.

ETHICS AND DISSEMINATION

The scoping review will be a secondary analysis of published data, for which ethics approval is not required. The results will be disseminated through a peer-reviewed publication and targeted distribution to stakeholders involved in climate change, built environment and health research and policymaking.

STUDY REGISTRATION

Open Science Framework: doi.org/10.17605/OSF.IO/XR74C.

Mental health among U.S. College students: implications of COVID-19 and roles of institutional and individual characteristics

Previous research on college campus environments, student mental health, and COVID-19 has primarily focused on individual-level factors, with limited attention to the broader institutional characteristics. Objective and Methods: Using the national survey data from the American College Health Association, this study examines the influence of both individual-level and institutional-level characteristics on college students' stress, psychological distress, and psychological well-being, before and during COVID-19. Results: (1) COVID-19 significantly impacted students' mental health; (2) institutional-level factors, such as school size, locale, region, and religiously affiliation, were significant predictors of mental health outcomes; and (3) individual-level variables, including gender, age, race/ethnicity, relationship status, moderated the relationship between COVID-19 and mental health. Conclusion: This study suggests the need to consider various institutional contexts in future efforts to understand predictors of mental health conditions and resilience.

The Role of Community Science in Addressing Policy Change: A Critical Review of Air Pollution Literature

BACKGROUND

Community air pollution science serves as a vital tool in public health and urban planning, enabling communities to advocate for policy changes that improve public health outcomes. Despite its potential, there is a noticeable gap in translating research findings into policy actions.

OBJECTIVES

This review aims to assess the focus of studies on community air pollution science published between 1990-2023 and identify the extent to which these studies address the research-to-policy gap.

METHODS

We conducted a comprehensive review of 131 studies that utilize low-cost sensors for monitoring air pollution. The review specifically looked for how these studies contribute to bridging the research-to-policy gap.

RESULTS

Our findings indicate a significant emphasis on evaluating the performance of low-cost sensors, with 90% of the studies centered on this aspect. Only 10% of the studies explicitly aimed at addressing the research-to-policy gap. Among these, 10 studies employed distinct theories of change to tackle this issue effectively.

CONCLUSION

There is a critical need for a paradigm shift in community science research to enhance the impact of scientific findings on policy-making. This shift should include strategies such as equitable sensor distribution, a broader focus on regions in the Global South, and proactive engagement with policymakers from the early stages of research.

RECOMMENDATIONS

Future research should prioritize closing the research-to-policy gap by incorporating these strategies to ensure that community air pollution science fully realizes its potential in shaping public health policies.

Causal effect of PM2.5 on the urban heat island

The planet is experiencing global warming, with an increasing number of heat waves worldwide. Cities are particularly affected by the high temperatures because of the urban heat island (UHI) effect. This phenomenon is mostly explained by the land cover changes, reduced green spaces, and the concentration of infrastructure in urban settings. However, the reasons for the UHI are complex and involve multiple factors still understudied. Air pollution is one of them. This work investigates the link between particulate matter ≤2.5 μm (PM2.5) and air temperature by convergent cross-mapping (CCM), a statistical method to infer causation in dynamic non-linear systems. A positive correlation between the concentration of fine particulate matter and urban temperature is observed. The causal relationship between PM2.5 and temperature is confirmed in the most urbanized areas of the study site (Quito, Ecuador). The results show that (i) the UHI is present even in the most elevated capital city of the world, and (ii) air quality is an important contributor to the higher temperatures in urban than outlying areas. This study supports the hypothesis of a non-linear threshold effect of pollution concentration on urban temperature.

Effects of Climate Change on Health and Health Systems: A Systematic Review of Preparedness, Resilience, and Challenges

Climate change has a significant impact on the population's health and negatively affects the functioning of healthcare systems. Health systems must be operationally prepared to handle the challenges posed by environmental change. Resilience is required to adapt quickly to critical environmental conditions and reduce carbon emissions. In this systematic review strategies, for health system preparedness and resilience are examined to address the impacts of climate change, and the barriers and challenges faced when implementing them. To identify studies, the Scopus, PubMed and Google Scholar databases were searched three times (from April to October 2024, 21 April, 15 June, and 9 September) for the years 2018 to 2024, using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. Specifically, the search identified 471 articles, of which the specified inclusion and exclusion criteria (secondary studies with inclusion criteria, being in English, etc.) were met by sixteen (16) studies. According to the findings of the studies reviewed, adaptation strategies focus on structural changes, the development of training programs, the development of surveillance systems, and appropriate operational plans. The leader's ability to motivate employees to achieve defined goals, continuous evaluation of goals and interventions, and learning from previous disasters play an important role in their implementation. Similarly, key policies and strategies for mitigation include the adoption of sustainable practices, such as recycling and cultural change. However, lack of resources (human, material, financial) and increased demand for health services make it difficult to implement adaptation and mitigation strategies. The findings of the review are mainly theoretical in nature and are confirmed by other studies. It is suggested that further research on resilience and preparedness of health systems should be pursued, leading to their sustainability and the formulation of appropriate policies.

Fifteen Pathways between Electric Vehicles and Public Health: A Transportation-Health Conceptual Framework

The health impact of electric vehicles (EVs) is complex and multifaceted, encompassing reductions in air pollutants, improvements in road safety, and implications for social equity. However, existing studies often provide fragmented insights, lacking a unified framework to comprehensively assess these public health implications. This paper develops a comprehensive framework to summarize the health outcomes of EVs in urban areas, where the health impacts are more pronounced due to higher levels of traffic congestion and air pollution. Building on previous conceptual work that identified pathways linking general transportation and health, our model illustrates how the characteristics of EVs influence public health through various pathways compared to traditional transportation systems. Additionally, we address socioeconomic factors that introduce variability in EV-related health outcomes, emphasizing the need to consider potential health disparities in policy and intervention development. This comprehensive approach aims to inform holistic policies that account for the complex interplay between transportation, environment, and public health.

Fear in Media Headlines Increases Public Risk Perceptions but Decreases Preventive Behaviors: A Multi-Country Study During the COVID-19 Pandemic

The perception of reality could matter more than reality itself when it comes to disease outbreaks. News media are important sources of information during global disease outbreaks, such as the COVID-19 pandemic. Drawing on theories of fear appeals and the social ecological model, we conducted multilevel modeling analyses to examine how media-level and community-level factors influenced the public's risk perceptions of COVID-19 and frequencies of preventive behaviors in the United States, United Kingdom, Canada, Australia, and India. We combined a large-scale multi-wave cross-country survey (N = 161,374) with a COVID-19 media coverage archive (N = 10,015,187) to test these relationships. We found that fear in media headlines was positively correlated with people's perceptions of risk but negatively correlated with frequencies of preventive behaviors, controlling for individual-, community-, and cultural-level factors. Similar patterns were consistently identified within each individual country. We also show that community factors interacted with the media environment to influence public risk perceptions and behaviors. Our findings highlight a strong mass media influence during the pandemic, and we discuss the implications of our findings for health communication during crisis times.

Assessing the Polarising Impacts of Low-Traffic Neighbourhoods: A Community Perspective from Birmingham, UK

Globally, the transport sector is a major contributor to air pollution. Currently, in the UK, vehicle emissions contribute significant amounts of nitrogen oxide (NOx) and particulate matter (PM) pollution in urban areas. Low-emission-zone policies have been used as an intervention to tackle air pollution, and in this context, the UK launched the Low-Traffic Neighbourhood scheme. This study investigates the impacts of the Low-Traffic Neighbourhood in Kings Heath, Birmingham, UK, to evaluate its impact in reducing air pollution and local community perspectives about the scheme and perceived impacts on health and well-being. This study employs a mixed-method approach comprising an air-quality-monitoring assessment and a survey questionnaire involving 210 residents. The findings reveal an increase in active travel and a reduction in air pollution levels in the years after the implementation of the scheme, although the area is still non-compliant with the 2021 WHO air quality guidelines. Nonetheless, the scheme has a polarising effect and created a division within the local community about the overall scheme acceptance and spatial distribution of the scheme's benefits. This study underscores the importance of comprehensive baseline data, long-term community engagement, and integration with broader urban planning initiatives to enhance the success of future Low-Neighbourhood Traffic schemes.

The heat-mortality association in Jordan: Effect modification by greenness, population density and urbanization level

BACKGROUND

The Middle East is one of the most vulnerable regions to the impacts of climate change, yet evidence of the heat-related mortality remains limited in this area. Our present study investigated the heat-mortality association in Jordan and the potential modifying effect of greenness, population density and urbanization level on the association.

METHODS

For each of the 42 included districts, daily meteorological and mortality data from 2000 to 2020 were obtained for the warmest months (May to September). First, a distributed lag non-linear model was applied to estimate the district level heat-mortality association, then the district specific estimates were pooled using multivariate meta-regression models to obtain an overall estimate. Last, the modifying effect of district level greenness, population density and urbanization level was examined through subgroup analysis.

RESULTS

When compared to the minimum mortality temperature (MMT, percentile 0th, 22.20 °C), the 99th temperature percentile exhibited a relative risk (RR) of 1.34 (95 % CI 1.23, 1.45). Districts with low greenness had a higher heat-mortality risk (RR 1.39, 95 % CI 1.22, 1.58) when compared to the high greenness (RR 1.28, 95 % CI 1.13, 1.45). While heat-mortality risk did not significantly differ between population density subgroups, highly urbanized districts had a greater heat-mortality risk (RR 1.41, 95 % CI 1.23, 1.62) as compared to ones with low levels of urbanization (RR 1.32, 95 % CI 1.13, 1.55). Districts with high urbanization level had the highest heat-mortality risk if they were further categorized as having low greenness (RR 1.63, 95 % CI 1.30, 2.04).

CONCLUSION

Exposure to heat was associated with increased mortality risk in Jordan. This risk was higher in districts with low greenness and high urbanization level. As climate change-related heat mortality will be on the rise, early warning systems in highly vulnerable communities in Jordan are required and greening initiatives should be pursued.

Introducing PLEMS: the application of a low-cost, portable monitoring system in environmental walks

The application of innovative systems using low-cost microcontrollers in human biometeorology studies is a promising alternative to conventional monitoring devices, which are usually cost-intensive and provide measurements at specific points, as in stationary meteorological stations. A Portable Low-cost Environmental Monitoring System (PLEMS) aimed at the pedestrian scale is introduced. The backpack-type equipment consists of a microcontroller with attached sensors that assess environmental conditions in a broad sense, integrating measurements of air quality, lighting and noise levels alongside variables typically measured at meteorological stations. The application of the system took place in altogether 12 environmental walks carried out with questionnaire-surveys with concurrent environmental monitoring with the PLEMS in Curitiba, Brazil, a subtropical location characterized by a Cfb climate type. Results allowed us to test the equipment and method of data gathering within a limited period (approximately 50 min) and for a short walking circuit of 800 m. The equipment was successfully able to capture even slightest differences in environmental conditions among points of interest, whereas subjective responses (n= 3843 responses to a total of 11 questions) showed consistency with measured data. From a multi-domain perspective, relevant insights could be obtained for the measured variables.

Evaluation of thermal effects on urban road spatial structure: A case study of Xuzhou, China

Urban heat islands (UHI) are important environmental issue in cities where urban spatial structure has been proven to play an important role in alleviating UHI effects. The relationship between land surface temperature and urban spatial structures has been explored, providing strong support for their cooling effects. Urban roads are the skeleton of urban spatial structures, with obvious spatial structure characteristics; however, research on the relationship between roads and the thermal environment has been mostly focused at the micro and meso level, lacking exploration at the macro spatial structure scale. Xuzhou-a typical average-sized city in China-was selected as the research object and the road system as the carrier. The thermal environmental effects of road elements such as their structural attributes, geometric attributes and unique construction attributes were quantitatively analyzed using geographically weighted regression analysis. The results revealed that 1) the contribution of roads in the study area to the UHI effect is relatively stable; therefore, this area should become an important cooling space to decompose UHI patch connectivity and thus decrease the UHI effect. 2) the self-organizing structural characteristics of urban roads affect their thermal environments where in the straightness of the road structure and road thermal environment showed a clear overall negative correlation And 3) the length and width of the road segments had negative and positive effects on the thermal environment, respectively. The green coverage of the roads has a global negative effect on the thermal environment, but shows obvious spatial non-stationarity. Therefore, green measures must be implemented in different regions. The results here provide a quantitative basis for urban road system planning and urban form management and control that incorporates thermal environment improvements, as well as a reference for the study of urban thermal environments under different spatial forms and planning control systems in other countries and regions.

Relationship between foliar polycyclic aromatic hydrocarbons (PAHs) concentrations and plant traits: Intracanopy variability for a broadleaf species in an urban environment

The emission of potentially harmful compounds, including polycyclic aromatic hydrocarbons (PAHs), and the resulting air pollution is a serious problem in modern cities. It is therefore important to develop mitigation strategies, such as "smart" planting of trees that act as sinks for PAHs. However, the intra-individual (within-tree) variability in leaf PAH concentrations remains unknown. In this paper, we studied 15 ornamental apple trees (Malus × moerlandsii 'Profusion') growing on a main street in a medium-sized city in Galicia (NW Spain). We determined the PAH concentrations at 12 canopy positions in each tree (2 orientations and 2 distances from the trunk at 3 heights), measured various ecological traits (specific leaf area [SLA], δ13C, stomatal density, fatty acid contents and leaf hairiness) and analyzed the variability in traits within the canopy in relation to PAH concentrations. We observed high intra-individual variability in the PAH concentrations and the leaf traits. Statistical analyses revealed that leaf height was the main source of variability both in the PAH concentrations and in the traits, mainly due to the leaf morphology, particularly to the SLA. Therefore, the ideal vegetation to remove PAHs would be high leaf biomass trees, not too tall and with a high proportion of shade leaves.

Air quality in a revitalized special economic zone at the center of an urban monocentric agglomeration

In this study, we have examined the air quality within a revitalized, post-industrial urban area in Łódź, Poland. The use of Dron technology with mobile measurement equipment allowed for accurate assessment of air quality (particulate matter and gaseous pollutants) and factors influencing air quality (wind speed and direction) on a local scale in an area of 0.18 km2 and altitudes from 2 to 50 m. The results show that the revitalization carried out in the Lodz special economic zone area contributed to eliminate internal air pollution emitters through the use of ecological and effective heat sources. The exceedances permissible concentration values were local, and concerned mainly the higher measurement zones of the troposphere (more than 30 m above ground level). In the case of gaseous pollutants, higher wind speeds were associated with a decrease in the concentration of SO2 and an increase in H2S concentration. In both cases, the wind contributed to the occurrence of local areas of accumulation of these gaseous pollutants in the spaces between buildings or wooded areas.

Particulate and gaseous air pollutants exceed WHO guideline values and have the potential to damage human health in Faisalabad, Metropolitan, Pakistan

First-ever measurements of particulate matter (PM2.5, PM10, and TSP) along with gaseous pollutants (CO, NO2, and SO2) were performed from June 2019 to April 2020 in Faisalabad, Metropolitan, Pakistan, to assess their seasonal variations; Summer 2019, Autumn 2019, Winter 2019-2020, and Spring 2020. Pollutant measurements were carried out at 30 locations with a 3-km grid distance from the Sitara Chemical Industry in District Faisalabad to Bhianwala, Sargodha Road, Tehsil Lalian, District Chiniot. ArcGIS 10.8 was used to interpolate pollutant concentrations using the inverse distance weightage method. PM2.5, PM10, and TSP concentrations were highest in summer, and lowest in autumn or winter. CO, NO2, and SO2 concentrations were highest in summer or spring and lowest in winter. Seasonal average NO2 and SO2 concentrations exceeded WHO annual air quality guide values. For all 4 seasons, some sites had better air quality than others. Even in these cleaner sites air quality index (AQI) was unhealthy for sensitive groups and the less good sites showed Very critical AQI (> 500). Dust-bound carbon and sulfur contents were higher in spring (64 mg g-1) and summer (1.17 mg g-1) and lower in autumn (55 mg g-1) and winter (1.08 mg g-1). Venous blood analysis of 20 individuals showed cadmium and lead concentrations higher than WHO permissible limits. Those individuals exposed to direct roadside pollution for longer periods because of their occupation tended to show higher Pb and Cd blood concentrations. It is concluded that air quality along the roadside is extremely poor and potentially damaging to the health of exposed workers.

How urban growth dynamics impact the air quality? A case of eight Indian metropolitan cities

Air pollution is a matter of great significance that confronts the sustainable progress of urban areas. Against India's swift urbanization, several urban areas exhibit the coexistence of escalating populace and expansion in developed regions alongside extensive spatial heterogeneity. The interaction mechanism between the growth of urban areas and the expansion of cities holds immense importance for the remediation of air pollution. Henceforth, the present investigation utilizes geographically weighted regression (GWR) to examine the influence of urban expansion and population growth on air quality. The examination will use a decade of data on the variation in PM2.5 levels from 2010 to 2020 in eight Indian metropolitan cities. The study's findings demonstrate a spatial heterogeneity between urban growth dynamics and air pollution levels. Urban growth and the expansion of cities demonstrate notable positive impacts on air quality, although the growth of infilling within expanding urban areas can significantly affect air quality. Given the unique trajectories of urban development in developing countries, this research provides many suggestions for urban administrators to foster sustainable urban growth.

Evaluating the impact of landscape configuration, patterns and composition on land surface temperature: an urban heat island study in the Megacity Lahore, Pakistan

The urban heat island (UHI) phenomenon is negatively impacted by rapid urbanization, which significantly affects people's everyday lives, socioeconomic activities, and the urban thermal environment. This study focuses on the impact of composition, configuration, and landscape patterns on land surface temperature (LST) in Lahore, Pakistan. The study uses Landsat 5-TM and Landsat 8-OLI/TIRS data acquired over the years 2000, 2010 and 2020 to derive detailed information on land use, normalized difference vegetation index, LST, urban cooling islands (UCI), green cooling islands (GCI) and landscape metrics at the class and landscape level such as percentage of the landscape (PLAND), patch density (PD), class area (CA), largest patch index (LPI), number of patches (NP), aggregation index (AI), Landscape Shape Index (LSI), patch richness (PR), and mean patch shape index (SHAPE_MN). The study's results show that from the years 2000 to 2020, the built-up area increased by 17.57%, whereas vacant land, vegetation, and water bodies declined by 03.79%, 13.32% and 0.4% respectively. Furthermore, landscape metrics at the class level (PLAND, LSI, LPI, PD, AI, and NP) show that the landscape of Lahore is becoming increasingly heterogeneous and fragmented over time. The mean LST in the study area exhibited an increasing trend i.e. 18.87°C in 2000, 20.93°C in 2010, and 22.54°C in 2020. The significant contribution of green spaces is vital for reducing the effects of UHI and is highlighted by the fact that the mean LST of impervious surfaces is, on average, roughly 3°C higher than that of urban green spaces. The findings also demonstrate that there is a strong correlation between mean LST and both the amount of green space (which is negative) and impermeable surface (which is positive). The increasing trend of fragmentation and shape complexity highlighted a positive correlation with LST, while all area-related matrices including PLAND, CA and LPI displayed a negative correlation with LST. The mean LST was significantly correlated with the size, complexity of the shape, and aggregation of the patches of impervious surface and green space, although aggregation demonstrated the most constant and robust correlation. The results indicate that to create healthier and more comfortable environments in cities, the configuration and composition of urban impermeable surfaces and green spaces should be important considerations during the landscape planning and urban design processes.

Built Environment, Natural Environment, and Mental Health

Mental health disorders have become a global problem, garnering considerable attention. However, the root causes of deteriorating mental health remain poorly understood, with existing literature predominantly concentrating on socioeconomic conditions and psychological factors. This study uses multi-linear and geographically weighted regressions (GWR) to examine the associations between built and natural environmental attributes and the prevalence of depression in US counties. The findings reveal that job sprawl and land mixed use are highly correlated with a lower risk of depression. Additionally, the presence of green spaces, especially in urban area, is associated with improved mental health. Conversely, higher concentrations of air pollutants, such as PM2.5 and CO, along with increased precipitation, are linked to elevated depression rates. When considering spatial correlation through GWR, the impact of population density and social capital on mental health displays substantial spatial heterogeneity. Further analysis, focused on two high depression risk clustering regions (northwestern and southeastern counties), reveals nuanced determinants. In northwestern counties, depression rates are more influenced by factors like precipitation and socioeconomic conditions, including unemployment and income segregation. In southeastern counties, population demographic characteristics, particularly racial composition, are associated with high depression prevalence, followed by built environment factors. Interestingly, job growth and crime rates only emerge as significant factors in the context of high depression risks in southeastern counties. This study underscores the robust linkages and spatial variations between built and natural environments and mental health, emphasizing the need for effective depression treatment to incorporate these multifaceted factors.

A Comprehensive Look at the Development of Asthma in Children

Asthma, a prevalent chronic respiratory condition affecting millions of children globally, presents a significant health challenge. This review critically examines the developmental pathways of asthma in children, focusing on genetic, environmental, and early-life determinants. Specifically, we explore the impact of prenatal and postnatal factors such as maternal smoking, nutrition, respiratory infections, and allergen exposure on asthma development. Our analysis highlights the intricate interplay of these influences and their contribution to childhood asthma. Moreover, we emphasize targeted strategies and interventions to mitigate its burden, including genetic counseling for at-risk families, environmental modifications to reduce triggers, and early-life immunomodulation. By delving into these preventive measures and interventions, our review aims to provide actionable insights for healthcare professionals in developing tailored strategies to address the complexities of childhood asthma. In summary, this article offers a detailed examination of asthma development in children, aiming to enhance understanding and inform efforts to reduce its burden through targeted interventions.

How hydrological components of urban blue space influence the thermal milieu?

Present study examines the possible improvement of thermal discomfort mitigation. Unlike prior researches, which focused primarily on cooling effects of urban blue space, this study, instead of physical presence of blue space considers its hydrological components. The aim of the study is to better understand the role hydrological components like water consistency depth etc. In temperature regulation. The work uses field surveys and modeling to demonstrate how these hydrological factors influence the cooling effect of blue space, providing insights on urban thermal management. To fulfill the purpose, spatial association of hydrological components blue space with its thermal environment and cooling effects was assessed. The control of hydrological components on the surrounding air temperature was examined by conducting case studies. RESULTS: reveals greater hydro-duration, deeper water, and higher Water Presence Frequency (WPF) produce greater cooling effects. The study demonstrates a favorable correlation between hydrological richness and temperature reduction. The study also analyzes how land use and wetland size affect temperature, emphasizing the significance of hydrological conservation and restoration for successful temperature mitigation. Due to their hydrology, larger wetlands are able to moderate temperature to some extent, whereas smaller, fragmented wetlands being hydrologically poor are not so influential in this regard. With these results, the present study reaches beyond to the general understanding regarding the cooling effects of the urban blue spaces. While the previous studies primarily focused on estimating the cooling effect of urban blue space, the current one shows its synchronization with the hydrological characteristics. Novelty also entrusts here, through the modeling and field survey current study demonstrates deeper and consistent water coverage in the urban blue space for maximum period of a year pronounces the cooling effect. In addition, in this cooling effect, the role of land use which is a strong determinant of many aspects of the urban environment is also highlighted. Since all these findings define specific hydrological feature, the study has several practical implications. Mare restoration of urban blue space is not enough to mitigate the thermal discomfort. In order to optimize the cooling effect, the conservation of the hydrological richness is essential. The hydrological richness of the smaller wetlands and the edge of the larger wetlands is to be improved. The connection of these wetlands with the adjacent mighty may strengthen the hydrology. The vegetation was found to promote the cooling effect whereas shorter building helped in spreading the cooling effect. Such finding drives to incorporate the blue space with the green infrastructure along with restricting the building height atleast at the edge of the blue space.

Contrary to expectation: The surface urban heat island intensity is increasing in population shrinking region while decreasing in population growing region-A comparative analysis from China

Exploring the complex relationship between population change and surface urban heat island (SUHI) effect has important practical significance for the ecological transformation development of shrinking cities in the context of the prevalence of urban shrinkage and the global climate change. This paper compares the population change and SUHI effect between population shrinking region (Northeast Region, NR) and population growing region (Yangtze River Delta, YRD) in China, and explores their differences in driving mechanisms, using GIS spatial analysis and Geodetector model. Our results indicated that there are significant differences in population changes and SUHI intensity between these two regions. About 72.22% of the cities in the NR were shrinking, while their SUHI intensities increased by an average of 1.69°C. On the contrary, the urban population in the YRD shows a linear growth trend, while their SUHI intensities decreased by 0.11°C on average. The results of bivariate Moran's I index also indicated that the spatial correlation between the urban population changes and the SUHI intensity changes are not significant in the above regions. Furthermore, there are significant differences in the primary drivers of SUHI variations between these two regions. In the NR, underlying surface changes, including the changes of green coverage and built-up areas, are the most important driving factors. However, atmospheric environment changes, such as carbon dioxide emission and sulfur dioxide emission, are the key drivers in the YRD. Northam's theory of three-stage urbanization and environmental Kuznets curve hypothesis are powerful to explain these differences.

A Study on Environmental Impact of Slow Moving Electric Vehicles Using Microsimulation on Lucknow Urban Road With an On-Ramp

Background

The adoption of electric vehicles for mobility is seen as a major step towards the conservation of the environment. In India, slow-moving Electric 3-Wheelers (E3Ws) have been adopted for last-mile connectivity. The present study investigated the impact of slow-moving electric 3-wheelers on the environment in terms of emissions and traffic performance in mixed conditions.

Methods

Field traffic data from a section of road in the city of Lucknow was collected and used for the calibration of the traffic model. A total of 6 scenarios were tested using traffic modelling in the open-source microsimulation software SUMO. Krauss model was used to model mixed traffic and HBEFA 4 was used to calculate the emissions of fuel-driven vehicles. In each scenario, the volume of fuel-driven vehicles was kept constant and the volume of E3Ws was varied. For the last 2 scenarios, E3Ws were replaced with modified Electric 3-wheelers (ME3Ws) and Electric Buses.

Results

Initial findings showed that the average emission decreased as the number of slowly moving electric vehicles increased, but the average flow and harmonic mean speed decreased by 49.8% and 28.8%, respectively, despite keeping the original composition of fuel-driven vehicles the same in every scenario. Further analysis of scenarios revealed a strong correlation (R 2 = 0 . 88 ) between the reduction in the number of vehicles and the reduction in emissions like Carbon Dioxide (CO 2 ), which is responsible for global warming. Scenarios in which faster electric vehicles and electric buses replace slow-moving E3Ws also demonstrate emission reduction without noticeably affecting traffic performance parameters.

Conclusion

The study shows that the environmental benefits of E3Ws in a limited section of Lucknow road are offset by their low-speed capability. Hypothetical scenarios wherein Modified E3Ws and Electric Buses were introduced reported benefits both in terms of emissions and traffic performance.

The economics of nature's healing touch: A systematic review and conceptual framework of green space, pharmaceutical prescriptions, and healthcare expenditure associations

Green spaces play a crucial role in promoting sustainable and healthy lives. Recent evidence shows that green space also may reduce the need for healthcare, prescription medications, and associated costs. This systematic review provides the first comprehensive assessment of the available literature examining green space exposure and its associations with healthcare prescriptions and expenditures. We applied Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to search MEDLINE, Scopus, and Web of Science for observational studies published in English through May 6, 2023. A quality assessment of the included studies was conducted using the Office of Health Assessment and Translation (OHAT) tool, and the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) assessment was used to evaluate the overall quality of evidence. Our search retrieved 26 studies that met the inclusion criteria and were included in our review. Among these, 20 studies (77 % of the total) showed beneficial associations of green space exposure with healthcare prescriptions or expenditures. However, most studies had risks of bias, and the overall strength of evidence for both outcomes was limited. Based on our findings and related bodies of literature, we present a conceptual framework to explain the possible associations and complex mechanisms underlying green space and healthcare outcomes. The framework differs from existing green space and health models by including upstream factors related to healthcare access (i.e., rurality and socioeconomic status), which may flip the direction of associations. Additional research with lower risks of bias is necessary to validate this framework and better understand the potential for green space to reduce healthcare prescriptions and expenditures.

Tree species classification improves the estimation of BVOCs from urban greenspace

Accurate estimation of biogenic volatile organic compounds (BVOCs) emissions from urban plants is important as BVOCs affect the formation of secondary pollutants and human health. However, uncertainties exist for the estimation of BVOCs emissions from urban greenspace due to the lack of tree species classification with high spatial resolution. Here, we generated a tree species classification dataset with 10 m resolution to estimate tree species-level BVOCs emissions and quantify their impact on air quality in Shenzhen in southern China. The results showed that for the entire city, the BVOCs emissions based on traditional plant functional types (PFTs) dataset were substantially underestimated compared with the tree species classification data (6.37 kt versus 8.23 kt, with 22.60 % difference). The underestimation is particularly prominent in urban built-up areas, where our estimation was 1.65 kt, nearly twice of that based on PFTs data (0.86 kt). BVOCs estimation in built-up areas contributed approximately 20.07 % to the total. These BVOCs contributed substantially to the increase of ambient O3, but had limited impacts to ambient fine particulate matter (PM2.5). Our results underscore the importance of high spatial resolution tree species-level classification in more accurate estimation of BVOCs, especially in highly developed urban areas. The enhanced understanding of the patterns of BVOCs emissions by urban trees and the impact on secondary pollutants can better support fine-scale tree planning and management for livable environments in urban areas.

Association of residential land cover and wheezing among children and adolescents: A cross-sectional study in five provinces of China

The association between residential land cover (RLC) and wheezing remains poorly understood. This study aimed to investigate the association between RLC and wheezing in childhood and adolescence. A cross-sectional survey was conducted among children and adolescents in five provinces of China. Land cover data were obtained from the Cross-Resolution Land-Cover mapping framework based on noisy label learning, classifying land cover into five categories: cropland, forest, grass/shrubland, wetland, and impervious. Generalized linear mixed models were employed to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the risk of wheezing. Mediation analysis was employed to investigate whether ambient particulate matter (PM2.5) acts as a mediator in the association between RLC and wheezing. A total of 12,875 participants were included in the study, comprising 318 patients and 12,557 controls. Cropland500m was significantly associated with decreased odds of wheezing (OR: 0.929, 95% CI: 0.879-0.982), while impervious surfaces500m significantly was associated with increased odds of wheezing (OR: 1.056, 95% CI: 1.019-1.096) in all participants. In the stratified analysis, significant differences were found in the main outcomes between the adolescence group (age ≥10 years) and the childhood group (age <10 years) (Pinteraction < 0.05), while no significant differences were observed between the southern and northern regions, or between male and female respondents. Mediation analysis revealed that PM2.5 partially mediated the association between cropland500m and impervious surfaces500m with wheezing. RLC plays a significant role in wheezing during childhood and adolescence, with cropland offering protection and impervious surfaces posing a heightened risk.

Field temperature performances of in-use permeable sidewalks and asphalt vehicle roads and the potential impacts on apparent temperature and land surface temperature

Permeable pavements help reduce surface temperatures and have been widely implemented in urban areas. This study utilized an in-use permeable pavement sidewalk in front of a mass rapid transit station in the Taipei city center of Taiwan to determine the actual pavement surface temperature performance. A neighboring asphalt road and impervious pavement were also monitored. With a full year of continuous monitoring, the results showed that the temperature of permeable pavement was 3.7 °C lower than that of impervious pavement and 4.5 °C lower than that of asphalt pavement in the hot season. The frequent rainfall in spring resulted in the smallest temperature differences between the different pavement types. The cooling effects of permeable pavement differed at the different air temperatures. At air temperatures lower than 15 °C, the differences among pavement surface temperatures were noticeable. However, when the air temperature was higher than 35 °C, the surface temperature of permeable pavement was not different from that of impervious pavement and was greater than 55 °C. Field observations were carried out to determine the effects on the apparent temperature and the future surface temperature of climate change scenarios. The results showed that permeable pavement could reduce the average apparent temperature to near the air temperature, and asphalt pavement could increase the apparent temperature by 1.2 °C, assuming that the pavement temperature completely affects the air temperature. With the good prediction ability of the machine learning approach and 15 environmental factors, the preliminary prediction showed the projected surface temperature change in Taipei city in 2033. In the worst-case scenario, the average impervious pavement temperature is as high as 39.12 °C, whereas the average permeable pavement temperature is 32.50 °C.

Synthesis of TiO2-SiO2-Ag/Fiberglass with Antibacterial Properties and Its Application for Air Cleaning

The TiO₂-SiO₂-Ag/fiberglass with antibacterial properties under UV light irradiation was synthesized. The effects of compositions of TiO₂-SiO₂-Ag/fiberglass, optical, and textural characteristics on the antibacterial activity were studied. The TiO₂-SiO₂-Ag film was coated on the surface of fiberglass carrier filaments. The temperature effect on the formation of the TiO₂-SiO₂-Ag film was established by thermal analysis, and the temperature treatment mode was selected as 300 °C for 30 min, 400 °C for 30 min, 500 °C for 30 min, and 600 °C for 30 min. The influence of silicon oxide and silver additives on the antibacterial properties of TiO₂-SiO₂-Ag films was established. Increasing the treatment temperature of the materials up to 600 °C increased the thermal stability of the titanium dioxide anatase phase, while the values of optical characteristics decreased: the film thickness decreased to 23.92 ± 1.24 nm, the refractive index decreased to 2.154 ± 0.002, the energy of the band gap width decreased to 2.8 ± 0.5, and the light absorption shifted to the visible-light regime, which is important for photocatalytic reactions. The results showed that the use of TiO₂-SiO₂-Ag/fiberglass allows significant decrease in the value of CFU microbial cells to 125 CFU m^-3.

Unpacking the inter- and intra-urban differences of the association between health and exposure to heat and air quality in Australia using global and local machine learning models

Environmental stressors including high temperature and air pollution cause health problems. However, understanding how the combined exposure to heat and air pollution affects both physical and mental health remains insufficient due to the complexity of such effects mingling with human society, urban and natural environments. Our study roots in the Social Ecological Theory and employs a tri-environmental conceptual framework (i.e., across social, built and natural environment) to examine how the combined exposure to heat and air pollution affect self-reported physical and mental health via, for the first time, the fine-grained nationwide investigation in Australia and highlight how such effects vary across inter- and intra-urban areas. We conducted an ecological study to explore the importance of heat and air quality to physical and mental health by considering 48 tri-environmental confounders through the global and local random forest regression models, as advanced machine learning methods with the advantage of revealing the spatial heterogeneity of variables. Our key findings are threefold. First, the social and built environmental factors are important to physical and mental health in both urban and rural areas, and even more important than exposure to heat and air pollution. Second, the relationship between temperature and air quality and health follows a V-shape, reflecting people's different adaptation and tolerance to temperature and air quality. Third, the important roles that heat and air pollution play in physical and mental health are most obvious in the inner-city and near inner-city areas of the major capital cities, as well as in the industrial zones in peri-urban regions and in Darwin city with a low-latitude. We draw several policy implications to minimise the inter- and intra-urban differences in healthcare access and service distribution to populations with different sensitivity to heat and air quality across urban and rural areas. Our conceptual framework can also be applied to examine the relationship between other environmental problems and health outcomes in the era of a warming climate.

How can green credit decrease social health costs? The mediating effect of the environment

Green credit plays an important role in environmental protection and residents' health. This paper discusses the impact path of green credit on social health costs with the help of a quantile regression. The implementation of a green credit policy can decrease social health costs in China, and green credit works best in the economically developed Eastern region. As the quantile increases, so gradually does the absolute value of the green credit coefficient. This result proves that for provinces with rich per capita financial health expenditures, green credit plays a greater role in decreasing social costs, a conclusion also supported by our robustness test. In addition, we find that environmental pollution plays a mediating role in the path of green credit affecting health, and this finding is verified in the green credit and health general equilibrium model. Based on these findings, the government should encourage the active innovation of green credit products, and the banking industry should develop personalized green credit products for specific pollutant types or industries while decreasing government pressure.

Statistically Validated Urban Heat Island Risk Indicators for UHI Susceptibility Assessment

This research proposes a collection of urban heat island (UHI) risk indicators under four UHI risk components: hazard, exposure, sensitivity, and adaptive capacity. There are 46 UHI risk indicators linked to three pillars of sustainability: social equity, economic viability, and environmental protection. In this study, the UHI risk indicators were first validated by experts to determine their relevancy and subsequently applied to randomly sampled dwellers of Thailand's capital Bangkok. The UHI indicators were further validated with confirmatory factor analysis to determine the factor loadings (0-1) and reliability. Under the hazard component, the percentage of days when the daily minimum temperature is less than the 10th percentile exhibited the highest indicator-level factor loading (0.915). Vehicular traffic was the UHI exposure indicator with the highest factor loading (0.923), and the proportion of green space to build environment was the UHI sensitivity indicator with the highest factor loading (0.910). For the UHI adaptive capacity component, the highest factor loading (0.910) belonged to government policy and action. To effectively mitigate UHI impacts, greater emphasis should be placed on the indicators with highest factor loadings. Essentially, this research is the first to use statistical structural equation modeling to validate UHI indicators.

Investigating the association between air pollutants' concentration and meteorological parameters in a rapidly growing urban center of West Bengal, India: a statistical modeling-based approach

The ambient air quality in a city is heavily influenced by meteorological conditions. The city of Siliguri, known as the "Gateway of Northeast India", is a major hotspot of air pollution in the Indian state of West Bengal. Yet almost no research has been done on the possible impacts of meteorological factors on criterion air pollutants in this rapidly growing urban area. From March 2018 to September 2022, the present study aimed to determine the correlations between meteorological factors, including daily mean temperature (℃), relative humidity (%), rainfall (mm), wind speed (m/s) with the concentration of criterion air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, CO, O₃, and NH₃). For this research, the trend of all air pollutants over time was also investigated. The Spearman correlation approach was used to correlate the concentration of air pollutants with the effect of meteorological variables on these pollutants. Comparing the multiple linear regression (MLR) and non-linear regression (MLNR) models permitted to examine the potential influence of meteorological factors on concentrations of air pollutants. According to the trend analysis, the concentration of NH3 in the air of Siliguri is rising, while the concentration of other pollutants is declining. Most pollutants showed a negative correlation with meteorological variables; however, the seasons impacted on how they responded. The comparative regression research results showed that although the linear and non-linear models performed well in predicting particulate matter concentrations, they performed poorly in predicting gaseous contaminants. When considering seasonal fluctuations and meteorological parameters, the results of this research will definitely help to increase the accuracy of air pollution forecasting near future.