A Narrative Review of Urbanization and Mental Health: An Indian Perspective.

Urbanization is a phenomenon that shows the expansion of urban areas in conjunction with industrial and economic progress. Rapid world urbanization is caused by the swift rise in urban residents as a proportion of the population. Efforts to examine the quality of urban life and urbanization as distinct risk factors for mental illness within specific age groups have been made. However, the issue remains contentious and largely unresolved. Urban mental health issues, such as substance abuse, fear of crime, poverty, and ethnicity, are associated with factors like depression, aggression, fear, sadness, and personality disorders. The entire gamut of the population, particularly adult males and females, is affected by these impacts of urbanization. The size of the population increases the prevalence of the preview study. India is expected to concentrate highly on the whole urban population, but this might inadvertently cause harm to urban residents. This review discusses the impact of urbanization on mental health and well-being. We search via PubMed (Medline), Google Scholar, and databases like WHO. The language of the study is English, and other language articles are excluded. The mental health challenges associated with urbanization impact the entire population, with a notable emphasis on adult males and females. They are raising awareness about various urban programs designed for urban populations. It will function as a coordinator of change in a rapidly modified Indian society to spread awareness about mental illnesses throughout all segments of society.

Rethinking ecological niches and geographic distributions in face of pervasive human influence in the Anthropocene.

Species are distributed in predictable ways in geographic spaces. The three principal factors that determine geographic distributions of species are biotic interactions (B), abiotic conditions (A), and dispersal ability or mobility (M). A species is expected to be present in areas that are accessible to it and that contain suitable sets of abiotic and biotic conditions for it to persist. A species' probability of presence can be quantified as a combination of responses to B, A, and M via ecological niche modeling (ENM; also frequently referred to as species distribution modeling or SDM). This analytical approach has been used broadly in ecology and biogeography, as well as in conservation planning and decision-making, but commonly in the context of 'natural' settings. However, it is increasingly recognized that human impacts, including changes in climate, land cover, and ecosystem function, greatly influence species' geographic ranges. In this light, historical distinctions between natural and anthropogenic factors have become blurred, and a coupled human-natural landscape is recognized as the new norm. Therefore, B, A, and M (BAM) factors need to be reconsidered to understand and quantify species' distributions in a world with a pervasive signature of human impacts. Here, we present a framework, termed human-influenced BAM (Hi-BAM, for distributional ecology that (i) conceptualizes human impacts in the form of six drivers, and (ii) synthesizes previous studies to show how each driver modifies the natural BAM and species' distributions. Given the importance and prevalence of human impacts on species distributions globally, we also discuss implications of this framework for ENM/SDM methods, and explore strategies by which to incorporate increasing human impacts in the methodology. Human impacts are redefining biogeographic patterns; as such, future studies should incorporate signals of human impacts integrally in modeling and forecasting species' distributions.

The association between urbanization and depression in the elderly: A network analysis from the complexity science perspective.

IMPORTANCE: The global increase in urbanization has coincided with a rise in depression prevalence. However, the effect of urbanization on depression remains controversial, especially for the elderly. OBJECTIVE: To clarify how urbanization impacts depression in the elderly from a network perspective. DESIGN, SETTING, AND PARTICIPANTS: This sectional cohort study used data from China Health and Retirement Longitudinal Study (CHARLS). MAIN OUTCOMES AND MEASURES: The occurrence of depressive symptoms in urban and rural elderly residents. Network metrics of depressive symptoms. RESULTS: Of the 13,993 participants, lower incidence of depressive symptoms was observed in urban (26.3 %, 95 % CI, 24.7 %-27.8 %) than in rural (40.4 %, 95 % CI, 39.5 %-41.3 %, P < 0.0001) residents. However, higher incidence of depressive symptoms was observed in urban (26.3 %, 95 % CI, 25.2 %-28.4 %) than in rural (17.5 %, 95 % CI, 16.1 %-18.9 %, P < 0.0001) residents in a subset of 2898 pairs of participants after PSM. No difference in the network structure and metrics between urban and rural residents before (M = 0.071, p = 0.054, S = 0.037, p = 0.80) and after (M = 0.085, p = 0.133, S = 0.086, p = 0.47) PSM was detected. The networks structure revealed that negative affect was strongly connected to somatic symptoms and that the two anhedonic symptoms were also strongly connected. CONCLUSIONS: The current study indicated the homogeneity of the ultimate nature of depression between rural and urban residents from the network perspective, supporting the viewpoint that urbanization might not impose influence on depression. Further researches delving deeper into the complexity of the issue may provide new insights into our understanding of depression in an urban environment among the elderly.

Soil source, not the degree of urbanization determines soil physicochemical properties and bacterial composition in Ningbo urban green spaces.

Urban green spaces provide multiple ecosystem services and have great influences on human health. However, the compositions and properties of urban soil are not well understood yet. In this study, soil samples were collected from 45 parks in Ningbo to investigate the relationships among soil physicochemical properties, heavy metals and bacterial communities. The results showed that soil dissolved organic matter (DOM) was of high molecular weight, high aromaticity, and low degree of humification. The contents of heavy metals were all below the China's national standard safety limit (GB 3660-2018). The bioavailability of heavy metals highly correlated with soil pH, the content of DOC, the fluorescent component, the degree of humification and the source of DOM. The most abundant genera were Gemmatimonadaceae_uncultured, Xanthobacteraceae_uncultured, and Acidothermus in all samples, which were related to nitrogen cycle and bioavailability of heavy metals. Soil pH, bioavailability of Zn, Cd, Pb, and Ni (CaCl2 extracted) were the main edaphic factors influencing bacterial community composition. It should be noted that there was no significant impact of urbanization on soil physicochemical properties and bacterial composition, but they were determined by the source of soil in urban green spaces. However, with the passage of time, the effect of urbanization on urban green spaces cannot be ignored. Overall, this study provided new insight for understanding the linkage among soil physicochemical properties, heavy metals, and bacterial communities in urban green spaces.

The impact of urbanization and economic growth on carbon dioxide emission in sub-Saharan African countries: a perspective from the spatial-temporal approach.

Sub-Saharan Africa (SSA) is seeing exceptional urbanization and economic expansion rates. Therefore, the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) parameters and the spatial econometric framework are used in this work to examine the influence of economic growth and urbanization on SSA's CO2 emissions. Likewise, to determine the spatial effect and understand how factors influence the spatial dependence of carbon emissions, the study builds a spatial Durbin model (SDM). In line with the findings, the spatial correlation test revealed the spatial correlations across various countries. This indicates that the changes in sub-Saharan African country's CO2 emissions impacted nearby countries and the countries themselves. Additionally, the findings reveal that, in the SSA's countries, urbanization, economic growth, industrial structure, trade, and population, excluding energy intensity, which failed the significant test, all positively influence CO2 outflows, in line with the spatial econometric model's findings. Thus, energy intensity shares an adverse impact on carbon emissions. As an outcome, energy intensity reduces carbon dioxide emissions in nearby nations and the entire region. Thus, the study recommends that policymakers account for the effects of spatial spillover when establishing low-carbon policies, encouraging a low-carbon lifestyle, promoting environmentally friendly technologies, and improving regional collaboration.

Harnessing urban analytics and machine learning for sustainable urban development: A multidimensional framework for modeling environmental impacts of urbanization in Saudi Arabia.

Sustainable urban development is crucial for managing natural resources and mitigating environmental impacts induced by rapid urbanization. This study demonstrates an integrated framework using machine learning-based urban analytics techniques to evaluate spatiotemporal urban expansion in Saudi Arabia (1987-2022) and quantify impacts on leading land, water, and air-related environmental parameters (EPs). Remote sensing and statistical techniques were applied to estimate vegetation health, built-up area, impervious surface, water bodies, soil characteristics, thermal comfort, air pollutants (PM2.5, CH4, CO, NO2, SO2), and nighttime light EPs. Regression assessment and Principal Component Analysis (PCA) were applied to assess the relationships between urban expansion and EPs. The findings highlight the substantial growth of urban areas (0.067%-0.14%), a decline in soil moisture (16%-14%), water bodies (60%-22%), a nationwide increase of PM2.5 (44 µg/m3 to 73 µg/m3) and night light intensity (0.166-9.670) concentrations resulting in significant impacts on land, water, and air quality parameters. PCA showed vegetation cover, soil moisture, thermal comfort, PM2.5, and NO2 are highly impacted by urban expansion compared to other EPs. The results highlight the need for effective and sustainable interventions to mitigate environmental impacts using green innovations and urban development by applying mixed-use development, green space preservation, green building technologies, and implementing renewable energy approaches. The framework recommended for environmental management in this study provides a robust foundation for evidence-based policies and adaptive management practices that balance economic progress and environmental sustainability. It will also help policymakers and urban planners in making informed decisions and promoting resilient urban growth.

Research on the coordinated development between land urbanization and population urbanization in Shaanxi Province, China.

The coordinated development of land urbanization and population urbanization is crucial for the advancement of new urbanization. The study applied the entropy weight method and coupling coordination degree model, taking Shaanxi-a province in China characterized by a moderate pace of economic development and volume, along with distinct geographic and demographic features within its region-as the subject. It assessed the coordination conditions of these two types of urbanization from both macro and micro scales during the years 2010-2022. Utilizing the Analytic Network Process (ANP), the study ranked and analyzed the causes of issues stemming from uneven development, thus connecting a crucial link from theoretical analysis to decision-making implementation. The results showed that: (1) The province's land urbanization index was between 0.075 and 0.203, whereas the population urbanization index ranged from 0.221 to 0.408, with the development of the former significantly lagging behind the latter. (2) The coupling degree between land and population urbanization ranged from 0.835 to 0.854, with a coordination degree between 0.148 and 0.306. This indicated that a close connection had been formed between the two, yet a benign coupling relationship had not been established, displaying a spatial distribution characterized by "high in the middle, low in the north and south". (3) The limitation on further urban expansion was identified as the primary issue to be addressed (with a weight of 0.324), followed by insufficient infrastructure (with a weight of 0.261). The extent of ecological environmental damage was comparatively lower (with a weight of 0.225), and the degree of social injustice was the lowest (with a weight of 0.191). Therefore, to alleviate the problems associated with the imbalanced development between land urbanization and population urbanization, measures such as optimizing land spatial layout, enhancing urban ecological service functions, and strengthening the central cities' radiating effect should be implemented.

Combining the role of urbanization and renewable energy in sustainable development: testing the EKC hypothesis for Africa.

The pressing necessity to curb greenhouse gas emissions due to climate change has sparked significant scientific interest in comprehending the factors behind CO2 emissions, particularly concerning environmental sustainability challenges. Nonetheless, there exists a notable gap in our understanding of how the process of urbanization interacts with the utilization of renewable energy to impact CO2 emissions. This research endeavor seeks to evaluate the complex interplay among urbanization, renewable energy, and CO2 emissions across 46 African nations spanning from 1990 to 2019. To accomplish this objective, a variety of econometric methodologies are employed, including Driscoll-Kraay standard errors, IV-GMM, and method of moments quantile regression (MMQR) panel estimations to address issues like cross-sectional dependencies, endogeneity, heterogeneity, and panel Granger causality examination. The empirical results suggest that urbanization leads to an increase in CO2 emissions, whereas the consumption of renewable energy plays a role in enhancing environmental quality by reducing CO2 emissions. A significant outcome of the study is the revelation that a combination of urbanization and renewable energy leads to a decrease in carbon emissions. Moreover, the Environmental Kuznets Curve (EKC) hypothesis is validated. Lastly, through the Dumitrescu-Hurlin panel causality test, it is uncovered that urbanization and renewable energy consumption exhibit a bidirectional relationship with CO2 emissions. To reduce dependence on fossil fuels and curb CO2 emissions, policymakers should promote renewable energy usage in urban areas.

Life goes on: Spatial heterogeneity promotes biodiversity in an urbanized coastal marine ecosystem.

Both human populations and marine biodiversity are concentrated along coastlines, with growing conservation interest in how these ecosystems can survive intense anthropogenic impacts. Tropical urban centres provide valuable research opportunities because these megacities are often adjacent to mega-diverse coral reef systems. The Pearl River Delta is a prime exemplar, as it encompasses one of the most densely populated and impacted regions in the world and is located just northwest of the Coral Triangle. However, the spatial and taxonomic complexity of this biodiversity, most of which is small, cryptic in habitat and poorly known, make comparative analyses challenging. We deployed standardized settlement structures at seven sites differing in the intensity of human impacts and used COI metabarcoding to characterize benthic biodiversity, with a focus on metazoans. We found a total of 7184 OTUs, with an average of 665 OTUs per sampling unit; these numbers exceed those observed in many previous studies using comparable methods, despite the location of our study in an urbanized environment. Beta diversity was also high, with 52% of the OTUs found at just one site. As expected, we found that the sites close to point sources of pollution had substantially lower diversity (44% less) relative to sites bathed in less polluted oceanic waters. However, the polluted sites contributed substantially to the total animal diversity of the region, with 25% of all OTUs occurring only within polluted sites. Further analysis of Arthropoda, Annelida and Mollusca showed that phylogenetic clustering within a site was common, suggesting that environmental filtering reduced biodiversity to a subset of lineages present within the region, a pattern that was most pronounced in polluted sites and for the Arthropoda. The water quality gradients surrounding the PRD highlight the unique role of in situ studies for understanding the impacts of complex urbanization pressures on biodiversity.

Research on the coordinated development of provincial urbanization and carbon emission efficiency of construction industry in China.

BACKGROUND: Energy conservation and emission reduction policies restrict the economic and social development of all countries in the world, and the impact on China, which has low urbanization, is more serious. In the process of promoting urbanization, the pressure of carbon emission reduction in the construction industry has increased, and the high emissions of the construction industry have made the low-carbon development of cities face severe challenges. China is at a critical stage of urbanization development, and there is become a general consensus on how to improve the carbon emission efficiency of the construction industry. The interaction between urbanization and the carbon emission efficiency of the construction industry is a long-term and complex process. As one of the industries contributing to China's urbanization process and carbon emissions, it is of great practical significance to explore the coordination relationship between urbanization and the carbon emission efficiency of the construction industry (CEECI) to realize the goal of "double carbon", promoting urbanization construction and solving the problem of "green development". Taking 30 provinces in China as the research target area, the double weighted summation method and the undesirable output superefficiency window-EBM-DEA model are used to measure the provincial urbanization level and CEECI, respectively. Then, the coupling coordination degree model of the relative development index is introduced, and the spatial autocorrelation model and the spatial and temporal differentiation characteristics of the coordination level of urbanization and the CEECI are analysed. RESULTS: From 2010 to 2021, China's urbanization level increased steadily, but the growth rate gradually decreased. There were significant differences in urbanization levels among provinces. The eastern provinces have a higher level of urbanization but lack an impetus in the later period, while the western provinces have a lower level of urbanization but a faster growth rate. The low-carbon development trend of China's construction industry is good, and the overall development of the CEECI shows an "N" type, and the inflection points appear in 2013 and 2018. The interprovincial urbanization level is significantly different from that of the CEECI, and the development form of the central and western provinces is better than that of the eastern provinces. The coordination level of urbanization and the CEECI in China is transitioning from the running-in stage to the coordination stage, and the coupling coordination degree between systems is on the rise, while the relative development degree is on the decline. The spatial distribution pattern is in a dynamic state of change, and the overall distribution pattern is "high in the east and low in the central and western regions". The differences among provinces were significantly decreased, with 63.33% of provinces at the high running-in level. The provinces that entered the coordination stage were mainly located in the eastern region, and only Beijing was in the coordination stage by the end of the study. In addition, 90% of the provinces exhibited lagging efficiency, and only Jiangxi, Guangxi and Chongqing, which had low coordination levels maintained synchronous development of the two systems. The coordination level between provincial urbanization and the CEECI showed a positive spatial distribution, the global Moran index showed a "V" shape trend, and the spatial dependence of the coordination level between the two systems gradually weakened. In the local spatial distribution, there are two types of convergence: high and low. CONCLUSIONS: The coordination degree of urbanization and the CEECI analysed in this study is an extension of the research on the relationship between the two. By integrating the two into a unified framework, the method of combining quantitative and qualitative analysis is used to further explore the coordination relationship between the two, which not only enhances the scientificity and accuracy of the research but also extends the breadth and depth of relevant theoretical research. At the same time, according to the coordination type between urbanization and the CEECI, China should propose corresponding targeted coordination and optimization paths from the perspective of urbanization and low-carbon development of the construction industry to achieve high-quality development of China's economy and society.

Associations between heat waves and chronic kidney disease in China: The modifying role of land cover.

The increasing frequency of heat waves under the global urbanization and climate change background poses elevating risks of chronic kidney disease (CKD). Nevertheless, there has been no evidence on associations between long-term exposures to heat waves and CKD as well as the modifying effects of land cover patterns. Based on a national representative population-based survey on CKD covering 47,086 adults and high spatial resolution datasets on temperature and land cover data, we found that annual days of exposure to heat waves were associated with increased odds of CKD prevalence. For one day/year increases in HW_975_4d (above 97.5 % of annual maximum temperature and lasting for at least 4 consecutive days), the odds ratio (OR) of CKD was 1.14 (95 %CI: 1.12, 1.15). Meanwhile, stronger associations were observed in regions with lower urbanicity [rural: 1.14 (95 %CI: 1.12, 1.16) vs urban: 1.07 (95 %CI: 1.03, 1.11), Pinteraction < 0.001], lower water body coverage [lower: 1.14 (95 %CI: 1.12, 1.16) vs higher: 1.02 (95 %CI: 0.98, 1.05), Pinteraction < 0.001], and lower impervious area coverage [lower: 1.16 (95 %CI: 1.14, 1.18) vs higher: 1.06 (95 %CI: 1.03, 1.10), Pinteraction = 0.008]. In addition, this study found disparities in modifying effects of water bodies and impervious areas in rural and urban settings. In rural regions, the associations between heat waves and CKD prevalence showed a consistent decreasing trend with increases in both proportions of water bodies and impervious areas (Pinteraction < 0.05). Nevertheless, in urban regions, we observed significant effect modification by water bodies, but not by impervious areas. Our study indicates the need for targeted land planning as part of adapting to the kidney impacts of heat waves, with a focus on urbanization in rural regions, as well as water body construction and utilization in both rural and urban regions.

Spatial-temporal differentiation and influencing factors of carbon emission trajectory in Chinese cities - A case study of 247 prefecture-level cities.

Cities, where human energy activities and greenhouse gas emissions are concentrated, contribute significantly to alleviating the impacts of global climate change. Utilizing the China Carbon Emissions Accounting Database (CEADs) to provide carbon dioxide emission inventories for urban areas in China at the prefecture level, this study closely examines the historical evolution trajectories of carbon emissions across 247 urban units from 2005 to 2019. The logarithmic cubic function model was employed to simulate these trajectories, evaluating urban emission peaks and classifying the different carbon emission trajectories. Further, the Geographical and Temporal Weighted Regression model was employed to explore spatiotemporal traits and essential variables that impact the variations in carbon emissions among four identified trajectory types. Our results showed that Chinese urban carbon emission trajectories can be classified into four categories: a) peaking emissions, b) fluctuating growth, c) continuous growth, and d) passive decline. Specifically, 43 cities, primarily in North China, proactively attained their emission peak post-2010, driven by the reduction in secondary industry and energy intensity. 90 cities, largely industrial hubs in the southeast coast and inland, reached an emission plateau around 2015, exhibiting fluctuating growth due to dependencies on secondary industries. 101 cities, predominantly located in western and central regions, demonstrated a clear upward trend in carbon emissions, propelled by rapid urbanization and heavy industry-oriented economic development. Lastly, 13 cities, typically in the northeastern and southwestern regions, experienced a passive decline in carbon emissions, attributable to resource depletion or economic downturns. It is evident that China's city-level carbon peaking has demonstrated some effectiveness, yet considerable progress is still required.

Shifting forward: Urban ecology in perspective.

The world has become urban; cities increasingly shape our worldviews, relation to other species, and the large-scale, long-term decisions we make. Cities are nature, but they need to align better with other ecosystems to avoid accelerating climate change and loss of biodiversity. We need a science to guide urban development across the diverse realities of global cities. This need can be met, in part, by shifts in urban ecology and its linkages to related sciences. This perspective is a "synthesis of syntheses", consolidating ideas from the other articles in the Special Section. It re-examines the role of urban ecology, and explores its integration with other disciplines that study cities. We conclude by summarizing the next steps in the ongoing shift in urban ecology, which is fast becoming an integral part of urban studies.

Sex-specific associations of environmental exposures with prevalent diabetes and obesity - results from the KORA Fit study.

BACKGROUND: Promising evidence suggests a link between environmental factors, particularly air pollution, and diabetes and obesity. However, it is still unclear whether men and women are equally susceptible to environmental exposures. OBJECTIVES: We aimed to assess sex-specific long-term effects of environmental exposures on metabolic diseases. METHODS: We analyzed cross-sectional data from 3,034 participants (53.7% female, aged 53-74 years) from the KORA Fit study (2018/19), a German population-based cohort. Environmental exposures, including annual averages of air pollutants [nitrogen oxides (NO2, NOx), ozone, particulate matter of different diameters (PM10, PMcoarse, PM2.5), PM2.5abs, particle number concentration], air temperature and surrounding greenness, were assessed at participants' residences. We evaluated sex-specific associations of environmental exposures with prevalent diabetes, obesity, body-mass-index (BMI) and waist circumference using logistic or linear regression models with an interaction term for sex, adjusted for age, lifestyle factors and education. Further effect modification, in particular by urbanization, was assessed in sex-stratified analyses. RESULTS: Higher annual averages of air pollution, air temperature and greenness at residence were associated with diabetes prevalence in men (NO2: Odds Ratio (OR) per interquartile range increase in exposure: 1.49 [95% confidence interval (CI): 1.13, 1.95], air temperature: OR: 1.48 [95%-CI: 1.15, 1.90]; greenness: OR: 0.78 [95%-CI: 0.59, 1.01]) but not in women. Conversely, higher levels of air pollution, temperature and lack of greenness were associated with lower obesity prevalence and BMI in women. After including an interaction term for urbanization, only higher greenness was associated with higher BMI in rural women, whereas higher air pollution was associated with higher BMI in urban men. Discussion We observed sex-specific associations of environmental exposures with metabolic diseases. An additional interaction between environmental exposures and urbanization on obesity suggests a higher susceptibility to air pollution among urban men, and higher susceptibility to greenness among rural women, which needs corroboration in future studies.

Managing urban agglomeration processes in Russia in the context of agglomerative and socio-economic development.

Studies on urban agglomeration typically focus on the management of urban agglomerations as special types of spatial organization. The problem of finding an adequate management model which accounts for the level of spatial connectivity and socio-economic development of a given territory remains in the background. This article identifies urban agglomeration management models in Russia which account for the agglomerative and socio-economic development of a given territory. A methodology for assessing urban agglomeration processes is presented which, unlike existing methodologies, includes an assessment of agglomeration maturity and an assessment of the socio-economic development of urban agglomerations. This methodology is based on conceptual platforms within spatial development theory; new economic geography; and agglomeration theory and cluster development. The methodology was tested on the data of Chelyabinsk Region agglomerations. The study determined that the Chelyabinsk and Gorniy Ural agglomerations are socio-economically developed and highly agglomerated, while the Magnitogorsk agglomeration shows high socio-economic development and low agglomeration. The conurbations are underdeveloped in both areas. The paper gives several recommendations on methods for choosing urban agglomeration management models. The developed methodology can be used to assess agglomerations across Russia and to choose the most adequate management model for a territory depending on its agglomerative and socio-economic development.

Urban river recovery: a systematic review on the effectiveness of water clean-up programs.

Urban rivers are affected at different levels by the intensification of human activities, representing a serious threat to the maintenance of terrestrial life and sustainable urban development. Consequently, great efforts have been dedicated to the ecological restoration of urban rivers around the world, as a solution to recovering the environmental functionality of these environments. In this sense, the present work aimed to investigate the effectiveness of interventions carried out aimed at the recovery of urban rivers, through a systematic review of the literature between 2010 and 2022, using the search term "rivers recovery." The results showed that there have been notable advances in the implementation of river recovery programs in urban areas around the world between the years analyzed. The ecosystems studied were affected, for the most part, by the increase in the supply of nutrients from domestic and industrial effluents, in addition to having highly urbanized surroundings and with several changes in land use patterns. The preparation of this literature review made it possible to demonstrate that the effectiveness of river recovery is extremely complex, since river recovery projects are developed for different reasons, as well as being carried out in different ways according to the intended objective.

Revisiting the relationships between energy consumption, economic development and urban size: A global perspective using remote sensing data.

Existing methods of measuring energy consumption require complex statistics and computing. A real-time and globally applicable approach for comparing energy consumption across different cities is still lacking. Additionally, the nonlinear relationships and varying thresholds of energy consumption in relation to economic activities and urbanization remain unconfirmed. This study aims to fill these gaps by utilizing Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data in 2015 and a top-down approach based on a multiple regression model to examine energy consumption in global cities employing a redefined urban boundary. It also explores the accurate relationship between energy consumption, population density (as a proxy of urbanization), and per capita gross domestic product (GDP) across different regions and urban sizes using generalized additive models and regression models. High-resolution gridded population and GDP datasets covering the entire planet are utilized for this purpose. The study also estimates the development potentiality. The study yields followings outcomes: Firstly, the top 30 cities with the highest per capita energy consumption account for over 0.66% of the total per capita energy consumption of all cities. Secondly, in East Asia (EA) and Southeast Asia (SEA), the per capita energy consumption decreases when per capita GDP reaches $40,000 and $75,000, respectively, while it remains stable in cities located in Western Europe (WE) and North America (NA) as per capita GDP increases. Thirdly, the per capita energy consumption declines with increasing urban population density until reaching 10,000 person/km2, 22,000 person/km2, and 4000 person/km2 in EA, SEA, and NA, respectively. Fourthly, in Central Asia (CA), megacities can save over 100 Mbtu/population when per capita GDP increases by $1000 compared to big cities. This pioneering study provides a comparable investigation of energy consumption at the global city level, exploring its relationship with urbanization and economy by employing a unified calculation standard. It will facilitate long-term energy-saving policies and urban planning strategies.

Anopheles gambiae larvae's ability to grow and emerge in water containing lethal concentrations of clothianidin, acetamiprid, or imidacloprid is consistent with cross-resistance to neonicotinoids.

BACKGROUND: For decades, various agrochemicals have been successfully repurposed for mosquito control. However, preexisting resistance caused in larval and adult populations by unintentional pesticide exposure or other cross-resistance mechanisms poses a challenge to the efficacy of this strategy. A better understanding of larval adaptation to the lethal and sublethal effects of residual pesticides in aquatic habitats would provide vital information for assessing the efficacy of repurposed agrochemicals against mosquitoes. METHODS: We reared field-collected mosquito larvae in water containing a concentration of agrochemical causing 100% mortality in susceptible mosquitoes after 24 h (lethal concentration). Using this experimental setup, we tested the effect of lethal concentrations of a pyrrole (chlorfenapyr, 0.10 mg/l), a pyrethroid (deltamethrin, 1.5 mg/l), and three neonicotinoids including imidacloprid (0.075 mg/l), acetamiprid (0.15 mg/l), and clothianidin (0.035 mg/l) on mortality rates, growth, and survival in third-instar larvae of the two sibling species Anopheles gambiae and Anopheles coluzzii collected from Yaoundé, Cameroon. RESULTS: We found that An. gambiae and An. coluzzii larvae were susceptible to chlorfenapyr and were killed within 24 h by a nominal concentration of 0.10 mg/l. Consistent with strong resistance, deltamethrin induced low mortality in both species. Lethal concentrations of acetamiprid, imidacloprid, and clothianidin strongly inhibited survival, growth, and emergence in An. coluzzii larvae. By contrast, depending on the active ingredient and the population tested, 5-60% of immature stages of An. gambiae were able to grow and emerge in water containing a lethal concentration of neonicotinoids, suggesting cross-resistance to this class of insecticides. CONCLUSIONS: These findings corroborate susceptibility profiles observed in adults and suggest that unintentional pesticide exposure or other cross-resistance processes could contribute to the development of resistance to neonicotinoids in some Anopheles populations.

Environmental occurrence and assessment of organic pollutants in surface sediments of South Peninsular Malaysia.

Organic pollution continues to be an important worldwide obstacle for tackling health and environmental concerns that require ongoing and prompt response. To identify the LAB content levels as molecular indicators for sewage pollution, surface sediments had obtained from the South region of Malaysia. The origins of the LABs were identified using gas chromatography-mass spectrometry (GC-MS). ANOVA and a Pearson correlation coefficient at p < 0.05 were used in the statistical analyses of the differences between the research locations. Internal to external (I/E) ratio, homologs C13/C12, and long to short (L/S) chains are used to identify the effectiveness of wastewater treatments. According to statistical analysis, the range of LAB level at the stations was 67.4 to 188.7 ng g-1dw. A significant difference was observed between LAB homologs (p < 0.05), with a higher level of C13 in most of the stations. The computed LAB ratio (I/E), which varied from 1.6 to 2.7, revealed the released wastewater from primary and secondary sources. LAB degradation varied between 33 and 49% in the areas that were evaluated. The treatment system of wastewater requires to be further improved, and using LAB markers to track anthropogenic contamination is imperative.

A comprehensive research on open surface drinking water resources in Istanbul using remote sensing technologies.

Istanbul is a megacity with a population of 15.5 million and is one of the fastest-growing cities in Europe. Due to the rapidly increasing population and urbanization, Istanbul's daily water needs are constantly increasing. In this study, eight drinking water basins that supply water to Istanbul were comprehensively examined using remote sensing observations and techniques. Water surface area changes were determined monthly, and their relationships with meteorological parameters and climate change were investigated. Monthly water surface areas of natural lakes and dams were determined with the Normalized Difference Water Index (NDWI) applied to Sentinel-2 satellite images. Sentinel-1 Synthetic Aperture Radar (SAR) images were used in months when optical images were unavailable. The study was carried out using 3705 optical and 1167 SAR images on the Google Earth Engine (GEE) platform. Additionally, to determine which areas of water resources are shrinking, water frequency maps of the major drinking water resources were produced. Land use/land cover (LULC) changes that occurred over time were determined, and the effects of the increase in urbanization, especially on drinking water surface areas, were investigated. ESRI LULC data was used to determine LULC changes in watersheds, and the increase in urbanization areas from 2017 to 2022 ranged from 1 to 91.43%. While the basin with the least change was in Istranca, the highest increase in the artificial surface was determined to be in the Büyükçekmece basin with 1833.03 ha (2.89%). While there was a 1-12.35% decrease in the surface areas of seven water resources from 2016 to 2022, an increase of 2.65-93% was observed in three water resources (Büyükçekmece, Sazlidere, and Elmali), each in different categories depending on their size. In the overall analysis, total WSA decreased by 62.33 ha from 2016 to 2022, a percentage change of 0.70%. Besides the areal change analysis, the algae contents of the drinking water resources over the years were examined for the major water basins using the Normalized Difference Chlorophyll Index (NDCI) and revealed their relationship with meteorological factors and urbanization.