RESUMEN

Selecting suitable Megacity Solid Waste Disposal (MSWD) sites is a challenging task in densely populated deltas of developing countries, exacerbated by limited public awareness about waste management. One of the major environmental concerns in Dhaka City, the world's densest megacity, is the presence of dumps close to surface water bodies resources. This study employed the Geographic Information System (GIS)-Analytic Hierarchy Process (AHP) framework to integrate geomorphological (slope and flow accumulation), geological (lithological and lineament), hydrogeological (depth to groundwater table and surface waterbody), socioeconomic (Land use land cover, distance to settlement, road, and airport), and climatological (wind direction) determinants, coupled by land-use and hydro-environmental analyses, to map optimal dumps (MSWDO) sites. The resulting preliminary (MSWDP) map revealed 15 potential landfill areas, covering approximately 5237 hectares (ha). Combining statistical analysis of restricted areas (settlements, water bodies, land use) with AHP-based ratings, the MSWDO map revealed two optimal locations (2285 ha). Additionally, the hydro-environmental analysis confirmed the unsuitability of northern sites due to shallow groundwater (< 5.43 m) and thin clay, leaving 11 options excluded. Sites 12 (Zone A, 2255 ha) and 15 (Zone B, 30 ha), with deeper groundwater tables and thicker clay layers, emerged as optimal choices for minimizing environmental risks and ensuring effective long-term waste disposal. This study successfully integrates remote sensing, geospatial data, and GIS-AHP modeling to facilitate the development of sustainable landfill strategies in similar South Asian delta megacities. Such an approach provides valuable insights for policymakers to implement cost-effective and sustainable waste management plans, potentially minimizing the environmental risks to achieve Sustainable Development Goals (SDGs) 6, 11, 13, and 15.

Asunto(s)

RESUMEN

Due to very high mobility in the environment and penetration ability into living organisms, nanoparticles (NPs) of urban dust pose a potential threat to human health and urban ecosystems. Currently, data on the chemical composition of NPs of urban dust, their fate in the environment, and corresponding risks are rather limited. In the present work, NPs of deposited urban dust have been comprehensively studied for the first time; NPs isolated from 78 samples of dust collected in Moscow, the largest megacity in Europe, being taken as example. The elemental composition, potential sources as well as environmental, ecological, and health risks of NPs of urban dust are assessed. It is found that dust NPs are extremely enriched by Cu, Hg, Zn, Mo, Sb, and Pb, and can serve as their carrier in urban environments. No regularities in the spatial distribution of elements have been found, probably, due to high mobility of dust NPs. High ecological and health risks caused by dust NPs are demonstrated. Source apportionment study has evaluated one natural and two anthropogenic sources of elements in NPs of urban dust; the contribution of natural and anthropogenic sources being comparable. It is also shown that dust NPs may be considered as an important carrier of trace elements in urban aquatic systems. Additionally, the risks associated with NPs and bulk samples of dust have been compared. The observed risks associated with NPs are significantly higher.

Asunto(s)

RESUMEN

According to United Nations projections, future global urban growth will mostly occur in Asian megacities. In this study, a Cellular Automata based Artificial Neural Network (CA-ANN) model is used to simulate the future land use and land cover (LULC) over Delhi megacity (India). Delhi, projected to become the world's most populated city by 2030, is an example of a data poor city in Asia, having millions of climate vulnerable people. The CA-ANN model of Modules for Land Change Simulation (MOLUSCE), an open-source plugin, is first tested to simulate the LULC for 2009. Based on good validation results-structural similarity (SSIM; 0.8288), overall accuracy (79.78 %), kappa index of agreement (KIA; 77.25 %), and minimum validation overall error (0.0379), the same model set-up is used to carry out LULC simulation for 2030. This model is found to be simple, efficient, and computationally less expensive tool, and can be used to model future LULCs with a minimal set of inputs, a constraint often found in data poor cities. Results show continued increase in built-up area from 38.3 % (2014) to 53.8 % (2030), at the expense of cultivable areas, forests, and wastelands. The study incorporates past and future LULC change trajectories to highlight the changing LULC dynamics of the megacity from 1977 to 2030. Rate of urban sprawl, calculated using compound annual growth rate (CAGR) is projected to be 2.51 % for 2014-2030, substantially higher than the estimates for 2006-2014 (0.62 %). Further, the past and future urban growth patterns for Delhi are found to mimic other big Asian cities. The database generated from the present study has wide applicability for scientific research community, governmental bodies, profit and non-profit organizations for topics concerning-future urban climate research, climate risk and adaption policy frameworks, climate finance budgeting, future town planning, etc.

RESUMEN

BACKGROUND: Against the backdrop of the global public health crisis, the COVID-19 pandemic has exposed significant disparities in the supply and demand of risk information related to public health crises, posing severe challenges to risk governance in megacities. Shanghai, China, introduced community WeChat groups for community communication, effectively facilitating the dissemination and response of grassroots information and providing a new path for interactive governance in the community. METHODS: This study collected 1006 questionnaires from residents of 350 communities in Shanghai through an online survey between June 10 and July 10, 2022. Multiple linear regression analysis was conducted to examine the impact of different participants (including the community, core residents, and the combined community and core residents) on community risk communication, perceived communication quality, and dissemination themes related to COVID-19 on community communication satisfaction. Additionally, in-depth interviews were conducted with 20 core residents from different types of communities, focusing on the specific methods of risk communication through community WeChat groups and their ability to disseminate information, respond to, and solve problems. RESULTS: Perceived information coverage and perceived response efficiency are significantly positively correlated with communication satisfaction. Notably, the speed of community information response has the greatest impact on communication satisfaction. Regarding COVID-19-related information dissemination themes, "community outbreaks, supplies, nucleic acids, outbreak prevention measures, and scientific content" all have a significant impact on communication effectiveness, with "nucleic acid testing information" having the greatest impact. Although the statistical data indicate that the participation of core residents in risk communication does not significantly affect communication satisfaction, it seems to be related to the size of the community, and the interview results further validate this conclusion. CONCLUSION: In the future, grassroots communities should consider the affordances of social media, recognize the significant correlation between risk communication and grassroots trust, and formulate more detailed and targeted risk communication strategies. In particular, incorporating core residents into "semiformal" grassroots organizations can improve community service quality, thereby enhancing community resilience in the face of public health emergencies.

Asunto(s)

RESUMEN

Although cycling has numerous health benefits, the increased breathing volume and lack of protection from exposure to the environment while cycling poses health risks that cannot be disregarded. Previous studies evaluating the exposure of cyclists to air pollution have typically focused on assessing exposure to a single pollutant or exposure concentrations on specific urban routes, and have not performed a comprehensive assessment considering the distribution of cyclists. The present study used bicycle-sharing big data to conduct a more comprehensive and refined real-time population weighted exposure risk assessment of pileless bike sharing riders in Beijing. We quantified the spatial distribution of high exposure areas at different times and found that the exposure risk during the evening peak period was significantly higher than that during the morning peak and early morning periods, particularly in the city center and its environs. By establishing stepwise regression models, we identified the significant impact of various urban points of interest (POIs) on exposure risk, with sports venues, public toilets, educational institutions, scenic spots, and financial entities particularly influential at different time periods. Medical institutions and shopping venues have a significant negative impact on the exposure levels of PM2.5 and NO2 among cyclists in most cases. These findings emphasize the need for targeted pollution control strategies. The aim of this study is to mitigate the impact of air pollution on cyclists and create a healthier cycling environment. The research results can provide new ideas for urban health planning and support scientific decision-making for sustainable urban development.

Asunto(s)

RESUMEN

Greater Cairo, the largest megacity of the Middle East North Africa (MENA) region, is currently suffering from major aerosol pollution, posing a significant threat to public health. However, the main sources of pollution remain insufficiently characterized due to limited atmospheric observations. To bridge this knowledge gap, we conducted a continuous 2-month field study during the winter of 2019-2020 at an urban background site, documenting for the first time the chemical and physical properties of submicron (PM1) aerosols. Crustal material from both desert dust and road traffic dust resuspension contributed as much as 24 % of the total PM1 mass (rising to 66 % during desert dust events), a figure not commonly observed in urban environments. Our observations showed significant decreases in black carbon concentrations and ammonium sulfate compared to data from 15 years ago, indicating an important reduction in both local and regional emissions as a result of effective mitigation measures. The diurnal variability of carbonaceous aerosols was attributed to emissions emanating from local traffic at rush hours and nighttime open biomass burning. Surprisingly, semi-volatile ammonium chloride (NH4Cl) originating from local open biomass and waste burning was found to be the main chemical species in PM1 over Cairo. Its nighttime formation contributed to aerosol water uptake during morning hours, thereby playing a major role in the build-up of urban haze. While our results confirm the persistence of a significant dust reservoir over Cairo, they also unveil an additional source of highly hygroscopic (semi-volatile) inorganic salts, leading to a unique type of urban haze. This haze, with dominant contributors present in both submicron (primarily as NH4Cl) and supermicron (largely as dust) modes, underscores the potential implications of heterogeneous chemical transformation of air pollutants in urban environments.

Asunto(s)

RESUMEN

Ozone pollution is profoundly modulated by meteorological features such as temperature, air pressure, wind, and humidity. While many studies have developed empirical models to elucidate the effects of meteorology on ozone variability, they predominantly focus on local weather conditions, overlooking the influences from high-altitude and broader regional meteorological patterns. Here, we employ convolutional neural networks (CNNs), a technique typically applied to image recognition, to investigate the influence of three-dimensional spatial variations in meteorological fields on the daily, seasonal, and interannual dynamics of ozone in Shenzhen, a major coastal urban center in China. Our optimized CNNs model, covering a 13° × 13° spatial domain, effectively explains over 70% of daily ozone variability, outperforming alternative empirical approaches by 7 to 62%. Model interpretations reveal the crucial roles of 2-m temperature and humidity as primary drivers, contributing 16% and 15% to daily ozone fluctuations, respectively. Regional wind fields account for up to 40% of ozone changes during the episodes. CNNs successfully replicate observed ozone temporal patterns, attributing -5-6 µg·m-3 of interannual ozone variability to weather anomalies. Our interpretable CNNs framework enables quantitative attribution of historical ozone fluctuations to nonlinear meteorological effects across spatiotemporal scales, offering vital process-based insights for managing megacity air quality amidst changing climate regimes.

Asunto(s)

RESUMEN

Introduction: During the global COVID-19 pandemic, densely populated megacities engaged in active international exchanges have faced the most severe impacts from both the disease and the associated infodemic. This study examines the factors influencing public participation behavior on government microblogs in these megacities during the pandemic. It guides megacities in disseminating epidemic information, promoting knowledge on epidemic prevention, managing public opinion, and addressing related matters. Methods: Utilizing the elaboration likelihood model's central and peripheral routes, drawing on an empirical analysis of 6,677 epidemic-related microblogs from seven Chinese megacities, this study analyses the influence mechanisms influencing public participation behavior and reveals the regulatory role of confirmed case numbers. Meanwhile,a qualitative comparative analysis examines and discusses diferent confgurations of ixn fuential factors. Results: The study reveals that microblog content richness demonstrates a U-shaped impact on public participation behavior. Conversely, content interaction, content length, and the number of fans positively impact participation, while update frequency has a negative impact. Additionally, the number of new confrmed cases positively regulates the impact of microblog content and publisher characteristics on public participation behavior. Public participation behavior also varies based on publishing time and content semantic features. This study further revealed the different confgurations of influential factors by QCA method. Conclusion: This study reveals the impact mechanism of the microblog content and publisher characteristics on public participation behavior. It also demonstrates the regulatory role of newly confrmed cases in the way content and publishers' characteristics influence public participation behavior. This study is of great significance for the operation of government microblogs, the release of emergency information, and the promotion of public participation.

Asunto(s)

RESUMEN

Urban greenness serves as a key indicator of sustainable urban development, with smart city construction emerging as a primary strategy for its enhancement. However, there is little empirical evidence considering multi-dimension between urban greenness and smart city construction on the city level. This study focuses on the impact on urban greenness of smart city construction in megacities, using the difference-in-differences regression model to evaluate the impact based on urban development conditions in various aspects from 2010 to 2021 in 10 megacities in China. The results of panel data of different indicator samples show unique conclusions. First, smart city pilot policy in megacities has significant impact on urban greenness, primarily due to demographic and economic developments. Second, the impact is different between the megacity and national level, and different factors of urban greenness have different effects on smart city construction. Third, the effects are time-lagged and lasted for years, and regional heterogeneity divided by building climate zones is existed, where the effect is more obvious in city agglomeration. These findings of smart city construction reveal the unique influences on megacity greenness, and can be generalized to cities with similar characteristics accordingly.

Asunto(s)

RESUMEN

Urban green space is a direct way to improve the carbon sink capacity of urban ecosystems. The carbon storage assessment of megacity green spaces is of great significance to the service function of urban ecosystems and the management of urban carbon zoning in the future. Based on multi-period remote sensing image data, this paper used the CASA model and the InVEST model to analyze the spatio-temporal variation and driving mechanism of carbon storage in Shenzhen green space and discussed the applicability of the two models to the estimation of carbon storage in urban green space. The research results showed that, from 2008 to 2022, in addition to the rapid expansion of construction land, the area of green space and other land types in Shenzhen showed a significant decrease trend. The estimation results of the carbon storage model showed that the carbon storage of green space shows a significant trend of reduction from 2008 to 2022, and the reduction amounts are 0.8 × 106 t (CASA model) and 0.64 × 106 t (InVEST model), respectively. The evaluation results of the model show that, in megacities, the spatial applicability of InVEST model is lower than that of CASA model, and the CASA model is more accurate in estimating the carbon storage of urban green space. The research results can provide a scientific basis for the assessment of the carbon sink capacity of megacity ecosystems with the goal of "dual carbon".

RESUMEN

Several epidemiological studies have demonstrated that particulate matter (PM) in air pollution can be involved in the genesis or aggravation of different cardiovascular, respiratory, perinatal, and cancer diseases. This study assessed the in vitro effects of PM10 on the secretion of cytokines by a human monocytic cell line (THP-1). We compared the chemotactic, pro-inflammatory, and anti-inflammatory cytokines induced by PM10 collected for two years during three different seasons in five different Mexico City locations. MIP-1α, IP-10, MCP-1, TNF-α, and VEGF were the main secretion products after stimulation with 80 µg/mL of PM10 for 24 h. The THP-1 cells showed a differential response to PM10 obtained in the different sites of Mexico City. The PM10 from the north and the central city areas induced a higher pro-inflammatory cytokine response than those from the south. Seasonal pro-inflammatory cytokine secretion always exceeded anti-inflammatory secretion. The rainy-season-derived particles caused the lowest pro-inflammatory effects. We concluded that toxicological assessment of airborne particles provides evidence supporting their potential role in the chronic exacerbation of local or systemic inflammatory responses that may worsen the evolution of some chronic diseases.

RESUMEN

Exposure to elevated particulate matter (PM) concentrations in ambient air has become a major health concern over urban areas worldwide. Reactive oxygen species (ROS) generation due to ambient PM (termed as their oxidative potential, OP) is shown to play a major role in PM-induced health effects. In the present study, the OP of the ambient PM2.5 samples, collected during summer 2019 from New Delhi, were measured using the dithiothreitol (DTT) assay. Average volume-normalized OP (OPV) was 2.9 ± 1.1 nmol DTT min-1 m-3, and mass-normalized OP (OPm) was 61 ± 29 pmol DTT min-1 µg-1. The regression statistics of OPv vs chemical species show the maximum slope of OPV with the elemental carbon (EC, r2 = 0.72) followed by water-soluble organic carbon (WSOC, r2 = 0.72), and organic carbon (OC, r2 = 0.64). A strong positive correlation between OPm and secondary inorganic aerosols (SIA, such as NH4+ and NO3- mass fractions) was also observed, indicating that the sources emitting NO2 and NH3, precursors of NO3- and NH4+, also emit DTT-active species. Interestingly, the slope value of OPv vs OC for aged aerosols (OM/OC > 1.7, f44 > 0.12 and f43 < 0.04) was 1.7 times higher than relatively fresh organic aerosols (OA, OM/OC < 1.7, f44 < 0.12, f43 > 0.04). An increase in OPv and OPoc with f44 indicates the formation of more DTT active species with the ageing of OA. A linear increase in OPoc with increasing Nitrogen/Carbon (N/C) ratio suggests that nitrogenous OA have higher OP.

RESUMEN

Antibiotic resistance genes (ARGs) constitute emerging pollutants and pose serious risks to public health. Anthropogenic activities are recognized as the main driver of ARG dissemination in coastal regions. However, the distribution and dissemination of ARGs in Shenzhen Bay Basin, a typical megacity water environment, have been poorly investigated. Here, we comprehensively profiled ARGs in Shenzhen Bay Basin using metagenomic approaches, and estimated their associated health risks. ARG profiles varied greatly among different sampling locations with total abundance ranging from 2.79 × 10-2 (Shenzhen Bay sediment) to 1.04 (hospital sewage) copies per 16S rRNA gene copy, and 45.4% of them were located on plasmid-like sequences. Sewage treatment plants effluent and the corresponding tributary rivers were identified as the main sources of ARG contamination in Shenzhen Bay. Mobilizable plasmids and complete integrons carrying various ARGs probably participated in the dissemination of ARGs in Shenzhen Bay Basin. Additionally, 19 subtypes were assigned as high-risk ARGs (Rank I), and numerous ARGs were identified in potential human-associated pathogens, such as Burkholderiaceae, Rhodocyclaceae, Vibrionaceae, Pseudomonadaceae, and Aeromonadaceae. Overall, Shenzhen Bay represented a higher level of ARG risk than the ocean environment based on quantitative risk assessment. This study deepened our understanding of the ARGs and the associated risks in the megacity water environment.

Asunto(s)

RESUMEN

BACKGROUND: Increased attention has been paid to humid-heat extremes as they are projected to increase in both frequency and intensity. However, it remains unclear how compound extremes of heat and humidity affects morbidity when the climate is projected to continue warming in the future, in particular for a megacity with a large population. METHODS: We chose the Wet-Bulb Globe Temperature (WBGT) index as the metric to characterize the humid-heat exposure. The historical associations between daily outpatient visits and daily mean WBGT was established using a Distributed Lag Non-linear Model (DLNM) during the warm season (June to September) from 2013 to 2015 in Shanghai, a prominent megacity of China. Future morbidity burden related to the combined effect of high temperature and humidity were projected under four greenhouse gases (GHGs) emission scenarios (SSP126, SSP245, SSP370 and SSP585). RESULTS: The humid-heat weather was significantly associated with a higher risk of outpatient visits in Shanghai than the high-temperature conditions. Relative to the baseline period (2010-2019), the morbidity burden due to humid-heat weather was projected to increase 4.4 % (95 % confidence interval (CI): 1.1 %-10.1 %) even under the strict emission control scenario (SSP126) by 2100. Under the high-GHGs emission scenario (SSP585), this burden was projected to be 25.4 % (95 % CI: 15.8 %-38.4 %), which is 10.1 % (95 % CI: 6.5 %-15.8 %) more than that due to high-temperature weather. Our results also indicate that humid-hot nights could cause large morbidity risks under high-GHGs emission scenarios particularly in heat-sensible diseases such as the respiratory and cardiovascular disease by the end of this century. CONCLUSIONS: Humid heat exposures significantly increased the all-cause morbidity risk in the megacity Shanghai, especially in humid-hot nights. Our findings suggest that the combined effect of elevated temperature and humidity is projected to have more substantial impact on health compared to high temperature alone in a warming climate.

Asunto(s)

RESUMEN

Naturally occurring radioactive materials (NORMs: 232Th, 226Ra, 40K) can reach our respiratory system by breathing of road dust which can cause severe health risks. Targeting the pioneering consideration of health risks from the NORMs in road dust, this work reveals the radioactivity abundances of NORMs in road dust from a megacity (Dhaka) of a developing country (Bangladesh). Bulk chemical compositions of U, Th, and K obtained from neutron activation analysis were converted to the equivalent radioactivities. Radioactivity concentrations of 226Ra, 232Th, and 40K in road dust ranged from 60-106, 110-159, and 488-709 Bq kg-1 with an average of 84.4 ± 13.1, 126 ± 11, and 549 ± 48 Bq kg-1, respectively. Estimated 226Ra, 232Th, and 40K radioactivities were, respectively, 1.7-3.0-, 3.7-5.3-, and 1.2-1.8-folds greater than the affiliated world average values. Mechanistic pathway of NORMs' enrichment and fractionation relative to the major origin (pedosphere) were evaluated concerning the water logging, relative solubility-controlled leaching and translocation, climatic conditions, and aerodynamic fractionations (dry and wet atmospheric depositions). Computation of customary radiological risk indices invokes health risks. Noticing the ingress of NOMR-holding dust into the human respiratory system along with the associated ionizing radiations, the computed radiological indices represent only the least probable health hazards. Nevertheless, in real situations, α-particles from the radioactive decay products of 232Th and 238U can create acute radiation damages of respiratory system. Policymakers should emphasize on limiting the dust particle evolution, and public awareness is required to alleviate the health risks.

Asunto(s)

RESUMEN

Background Bus drivers are a high-risk group for work-related musculoskeletal disorders (WMSDs). There are a large number of bus drivers in mega-cities. High volumes of passenger traffic and complexity of road conditions may elevate their risk of WMSDs, but there are few studies related to this group. Objective To investigate the prevalence of WMSDs among bus drivers in a mega-city and to analyze potential influencing factors. Methods Based on cross-sectional study design and self-administered questionnaire, the prevalence of WMSDs in past 12 months were estimated by stratified cluster sampling among bus drivers in a mega-city. Pearson χ2 and logistic regression models were used to analyze the influencing factors for the body regions with a high prevalence. Results The overall prevalence of WMSDs in past 12 months among bus drivers in a mega-city was 49.5% (551/1113). The prevalence of WMSDs by body regions ranged from 4.0% to 38.5%, and led by neck pain (38.5%), lower back pain (25.5%), and shoulder pain (20.8%). The results of logistic regression showed that the risk factors for neck pain were age (>50 years), smoking, tiredness after work (moderate, severe), long sitting (frequently), awkward postures (sometimes, often, frequently), overtime(occasionally, often), workplace temperature (uncomfortable), and noise (severe) (OR=2.014、1.577、2.793、3.025、2.708、2.032、3.406、2.746、1.442、2.998、1.456、3.506；P<0.05); the lower back pain risk factors were current work experience (6-10 years, 11-15 years, and 16-20 years), smoking, tiredness after work (moderate, severe), and awkward postures(sometimes, often, frequently)(OR=1.777、2.130、2.400、1.503、2.951、3.364、1.836、4.569、2.786，P<0.05); and the shoulder pain risk factors were age (46-50 years, and >50 years), smoking, tiredness after work (moderate, severe), vehicle type (hybrid power, diesel oil), awkward postures (often, frequently), overtime (often), and workplace temperature (uncomfortable) (OR=1.737、2.357、1.553、2.259、2.489、1.659、3.295、2.777、3.320、2.266、1.426，P<0.05). Identified protective factors for neck and lower back pain were off-duty physical activity (1-2 times per week, and ≥3 times per week) (OR=0.553、0.470、0.586、0.485，P<0.05). Conclusion Nearly half of the bus drivers in the mega-city report symptoms of WMSDs, mainly in the neck, lower back, and shoulders. The prevalence is related to individual and occupational factors, and prevention and intervention measures should be actively taken.

RESUMEN

A total of 84 PM2.5 (fine particulate matter) aerosol samples were collected between October 2020 and August 2021 within an urban site in Hangzhou, an East China megacity. Chemical species, such as organic carbon (OC), elemental carbon (EC), as well as char, soot, and n-alkanes, were analyzed to determine their pollution characteristics and source contributions. The mean yearly concentrations of OC, EC, char, soot, and total n-alkanes (∑n-alkane) were 8.76 ± 3.61 µg/m3, 1.44 ± 0.76 µg/m3, 1.21 ± 0.69 µg/m3, 0.3 ± 0.1 µg/m3, and 24.2 ± 10.6 ng/m3. The OC, EC, and ∑n-alkanes were found in the highest levels during winter and lowest during summer. There were strong correlations between OC and EC in both winter and spring, suggesting similar potential sources for these carbonaceous components in both seasons. There were poor correlations among the target pollutants due to summertime secondary organic carbon formation. Potential source contribution functions analysis showed that local pollution levels in winter and autumn were likely influenced by long-range transportation from the Plain of North China. Source index and positive matrix factorization models provided insights into the complex sources of n-alkanes in Hangzhou. Their major contributors were identified as terrestrial plant releases (32.7%), traffic emissions (28.8%), coal combustion (27.3%), and microbial activity (11.2%). Thus, controlling vehicular emissions and coal burning could be key measures to alleviate n-alkane concentrations in the atmosphere of Hangzhou, as well as other Chinese urban centers.

Asunto(s)

RESUMEN

Heavy metal pollution in roadside soil may harm humans, animals, plants, and local ecosystems. This study aimed to explore the sources and potential ecological risks of heavy metals in soils of roadside trees under different land uses, using soil samples collected from 136 roads across 16 administrative districts in Shanghai. The contents, pollution characteristics, potential ecological risks, and sources of seven heavy metals were analyzed, including Cr, Ni, Cd, Pb, As, Cu, and Zn. Results showed that (1) land use patterns affected the heavy metal contents, with industrial and construction areas showing higher contents while agricultural and forestry areas lower; (2) the ranking of heavy metal pollution levels was Cd > As > Pb > Cu > Ni > Cr > Zn. Cd exhibited the highest potential ecological risk, falling within the moderate to considerable potential ecological risk interval; (3) the sources of Cu, Zn, Cr, Ni, Cd, and Pb were associated with traffic emissions, whereas As had independent other sources and Pb in industrial and construction areas was also influenced by industrial emissions. These results provide valuable references on the control of heavy metal pollutants and the management of land uses in megacities.

Asunto(s)

RESUMEN

Complex urbanisation dynamics, on the one hand, create a high demand for animal products, and on the other hand put enormous pressure on arable land with negative consequences for animal feed production. To explore the impact of accelerated urbanisation on dairy cattle health in urban farming systems, 151 farmers from different parts of the Greater Bengaluru metropolitan area in India were individually interviewed on aspects addressing cattle management and cattle health. In addition, 97 samples of forages from the shores of 10 different lakes, and vegetable leftovers used in cattle feeding were collected for nutritional analysis. Along with the use of cultivated forages, crop residues, and concentrate feed, 47% and 77% of the farmers occasionally or frequently used lake fodder and food leftovers, respectively. Nutritionally, lake fodder corresponded to high-quality pasture vegetation, but 43% of the samples contained toxic heavy metals such as arsenic, cadmium, chromium, and lead above official critical threshold levels. Therefore, lake fodder may affect cows' health if consumed regularly; however, heavy metal concentrations varied between lakes (P < 0.05), but not between fodder types (P > 0.05). Although 60% of the interviewed farmers believed that their cows were in good health, logit model applications revealed that insufficient drinking water supply and the use of lake fodder negatively impacted cattle health (P < 0.05). While it remains unknown if regular feeding of lake fodder results in heavy metal accumulation in animal products, farmers and farm advisors must address this and other urbanization-related challenges to protect cattle health.

Asunto(s)

RESUMEN

Cities have become significant sources of greenhouse gas emissions. Effective land management may be the solution to carbon neutrality targets for megacities with limited land resources. This paper takes Shanghai as a case study to investigate the regional land use dynamics and its impact on carbon emissions following the implementation of land conservation and intensive use policy. During 2010-2020, the land use pattern in Shanghai changed from the previous urban land expansion to a combination of industrial land reduction and woodland expansion. Meanwhile, the area proportion of land-use mixture grids increased from 90.50% to 92.28% with the spatial pattern of mixed types also changing. Furthermore, the notable land-use mixture does not necessarily lead to carbon emission reduction, but it can reduce carbon emission hotspots in industrial agglomerations by promoting the mixed use of industrial land and other land use types. However, megacities cannot achieve carbon balance through land use management alone. Due to the increasing carbon emission density of hybrid industrial land, the joint implementation of a land conservation and intensive use strategy with industrial and energy structure adjustments may be an effective way forward.

Asunto(s)