Diverse Human Activities Research Articles

Dynamic impact of different human activities on the distribution of organic ultraviolet absorbers in coastal aquatic environments: A case study in Beibu Gulf, South China Sea

The increasing environmental concern surrounding organic ultraviolet absorbers (OUVAs) has prompted heightened attention, particularly their presence in personal care products (organic ultraviolet filters, OUVFs) and industrial products (organic ultraviolet stabilizers, OUVSs). This study investigates the impact of human activities and environmental factors on the occurrence, spatiotemporal distribution, and ecological risk of eight commonly utilized OUVFs and OUVSs in the coastal region of Beibu Gulf, South China Sea. The study area is characterized by multiple functional zones with distinct human activities. Results reveal elevated concentrations of OUVAs during summer compared to winter, attributed to increased residential usage, tourist activities, industrial releases, and intensified ultraviolet (UV) radiation. Interestingly, the proportion of OUVFs increases during summer, while OUVSs decrease. Correlation analysis between OUVAs and sampling sites reveals that tourism and domestic wastewater are the main contributors to OUVF contamination in summer, whereas mariculture and port trade significantly impact OUVS contamination in winter. The ecological risk assessment indicates predominantly low or medium risk levels for most OUVAs in both local seawater and freshwater ecosystems. Nevertheless, OUVFs, with a particular focus on 4-methylbenzylidene camphor (4-MBC), and OUVSs, specifically 2-(2-hydroxy-5-methylphenyl) benzotriazole (UV-P), exhibit a heightened risk compared to alternative substances. These findings provide crucial insights into the development of targeted mitigation strategies for OUVAs, taking into account the varying contamination levels of OUVFs and OUVSs resulting from diverse human activities, aiming to protect the health of aquatic ecosystems in diverse functional zones.

Differences in Anthropogenic Impacts of Typical Mid- to High-Latitude Wetlands in the Heilongjiang Basin

Wetlands represent one of the three principal ecosystems and serve a vital function in the protection of water resources and the regulation of climate. However, wetlands are currently experiencing significant challenges, particularly in the agriculturally productive wetlands of the Heilongjiang River Basin, which have been considerably impacted by human activities. This study focuses on three representative wetlands situated within the Heilongjiang River Basin. This study analyses changes in wetland area and landscape patterns from 2002 to 2022, as well as the impact of agriculture and impervious surface expansion on the wetlands. The findings indicate that agricultural expansion is the primary driver of wetland area loss. The wetland area affected by agriculture demonstrates the most significant change, with the largest observed shift reaching 47.2%. The expansion of impervious surfaces was found to have a significant impact on wetland fragmentation, resulting in a notable decrease in wetland connectivity. This was evidenced by a reduction in the average patch size, which decreased by 14.68 ha over the decade from 2007 to 2017, a period during which impervious surfaces expanded. This paper identifies the distinctions in the influence of diverse human activities on wetland landscape patterns in the Heilongjiang Basin and employs natural samples for control, thereby attenuating the impact of the natural environment. This study offers a novel perspective on the processes of wetland change and the maintenance of wetland health, which is crucial for the realisation of clean water and sanitation (Sustainable Development Goal 6.6).

Interplay of natural and anthropogenic factors in sediment dynamics and trace element distribution in Güllük Gulf, western Türkiye: A comprehensive geochemical and hydrodynamic analysis

Güllük Gulf, located in the southeastern Aegean Sea, is significantly impacted by diverse human activities, including urban development, tourism, and intensive aquaculture. This study aims to assess the spatial distribution of trace metals in the Gulf's sediments, identify their sources, and evaluate their environmental impacts to inform effective management strategies. It also examines sediment transport patterns, which are crucial in influencing the distribution and concentration of pollutants. Establishing background concentration levels for various elements provides a baseline to assess pollution levels and identify deviations due to anthropogenic impact. Sediment samples were collected from 45 stations and analyzed for grain size, organic carbon, carbonate content, and concentrations of 26 elements. Contamination was assessed using indices such as Enrichment Factor (EF), Geoaccumulation Index (Igeo), Contamination Factor (Cf), Degree of Contamination (Cdeg), Pollution Load Index (PLI), Modified Pollution Index (MPI), and Toxic Risk Index (TRI). Statistical analyses, including Principal Component Analysis (PCA) and Cluster Analysis (CA), were used to identify pollution sources. Results indicated that Güllük Gulf's sediments are predominantly sandy, with significant silt and clay fractions in sheltered bays. Organic carbon content averaged 1.68%, with higher values near urban and aquaculture areas. Trace metal concentrations exhibited notable spatial variability, with elevated levels of Pb, Cu and Zn in specific areas, indicating both natural and anthropogenic sources. PCA identified five significant factors contributing to metal presence, linking them to lithogenic origins, aquaculture activities, and industrial inputs. TRI results showed moderate toxic risk in Asin Bay, primarily due to Ni, As and Cr. The sediment transport model of Güllük Gulf, crucial in understanding regional pollution dynamics, revealed a complex interplay of hydrodynamic forces. The study underscores the significant environmental impact of human activities on sediment quality in Güllük Gulf. Elevated trace metal levels near aquaculture sites emphasize the need for stringent environmental management practices. Effective strategies should include regular monitoring, sustainable aquaculture practices, and stakeholder engagement to mitigate environmental impacts and preserve the Gulf's ecological integrity. This comprehensive approach provides crucial insights for future research and environmental management policies aimed at addressing the complex challenges facing Güllük Gulf.

Comparative analyses of publicness in urban squares within a diversifying metropolis

AbstractEnsuring publicness and accommodating more diverse human activity in urban public spaces is necessary. This research analyses the relationship between human activities, ownership, and physical features encouraging or discouraging use within the city centre of Dublin (Ireland), a diversifying metropolis experiencing dereliction. Four urban squares were assessed through fieldwork, including direct observation and behavioural mapping. Results indicate that publicness and features encouraging or discouraging use are not directly associated with site ownership. Nor was the presence of nature and landscaping determined by ownership, though it generated microclimates that promoted a higher mix of activities. Implications of going beyond formal definitions of ownership for publicness placed under broader sustainability agendas and recommendations for urban design practice are derived.

Adsorption of trace metals onto different plastics during long-term exposure in an estuarine environment: Influence of time, stratified water column, and specific surface area

The pervasive increase of plastics in marine systems and subsequent trace metals (TM) adsorption represents a critical environmental challenge. This long-term study is first to investigate how duration of exposure and stratified water column impact TM adsorption on various plastics in an estuary. We exposed polypropylene (PP), polyethylene (PE), poly(ethylene terephthalate) (PET), and fluorinated ethylene propylene (FEP) to estuarine conditions, categorizing them into three distinct groups to capture diverse human activities: pre-production pellets (Pellets), single-use plastics (SUP) and laboratory plastics (Lab). Plastic and water samples were analyzed before deployment and 1, 4, 7 and 16 months after deployment at three depths in the stratified Krka River estuary (Croatia). We measured TM concentrations, pH and salinity in the water column, and adsorbed TM amounts on plastics. Additionally, we examined plastic sample surfaces by Raman spectroscopy and scanning electron microscopy. TM speciation was modeled from water column data to better explain adsorption processes. Statistical analysis indicates that Zn, Cd, Pb, Ni, and Co adsorption depends on both duration of exposure and stratified water column, while Cu is influenced solely by duration of exposure to estuarine environment. Adsorbed TM amounts varied significantly among the plastic groups (Pellets, SUP and Lab), but not among different polymer types (PP, PE, PET and FEP). A noteworthy observation was the difference in the results of statistical analysis when investigating TM amounts expressed by plastic sample mass and by plastic sample surface area. Results expressed by plastic sample mass showed a difference between SUP group versus Pellets and Lab groups, while results expressed by plastic sample surface area distinguished Pellets group compared to other two groups. Therefore, we suggest presenting TM adsorption results in similar studies both by plastic sample mass and by plastic sample surface area. This approach will improve the understanding of TM adsorption on plastics, and enable more effective comparisons among the scientific literature dealing with plastics of different specific surface areas.

High-resolution urban temperature simulation method considering various spatiotemporal boundary impacts

Climate change has heightened the frequency and intensity of extreme heat events in cities, greatly impacting human health, the environment, and socio-economic activities, particularly in densely populated areas. Canopy temperature (T2m) is a key indicator of whether urban area extreme heat is occurring, with significant implications for public health, energy consumption, and pollution levels. However, the diverse urban topography, functional layout, and human activities contribute to significant variations in the distribution of T2m. While computational fluid dynamics (CFD) models offer high-resolution T2m simulations, complexities in urban spatial and temporal dynamics make accurately defining boundary conditions challenging, potentially leading to large simulation errors. This study addressed the challenge of determining precise boundary conditions for urban CFD simulations by employing the Weather Research and Forecasting model to integrate meteorological reanalysis data. Different meteorological reanalysis datasets used to simulate T2m were compared, including Final Operational Global Analysis, Global Forecast System, and European Centre for Medium-Range Weather Forecasts Reanalysis v5. When combined with the reanalysis data, the minimum mean relative error of simulated T2m was 4%, which is a threefold improvement in accuracy compared to traditional meteorological boundary conditions. This study provides technical support for refined zoning of urban extreme heat risk and urban management in the context of climate change.

Robust and tunable hydrogels strengthened by dynamic amphiphilic ionic domains

Hydrogels have gained increasing attentions in wearable electronics, but endure notch-sensitive and poor mechanical behavior in real-world applications. Herein, a robust and tunable hydrogel network was constructed by involving a polymerizable amphiphilic ionic liquid in polymer chains through a facile and novel strategy without additional chemical crosslinkers. The ingeniously designed dynamic amphiphilic ionic domains that are tuned by the structural domain and functional domain are crucial for reinforcing the structural integrity and allowing the polymer chains to accomplish reversible unfolding and ordered migration. The robust and functional microstructures effectively prevent crack propagation, enhancing the fracture strain (1200–2390%), tensile stress (380–1560 kPa), toughness (5–15 MJ m−3), and conductivity (0.13–0.2 mS cm−1). The obtained hydrogel acts as an excellent mechanoresponsive sensor to perceive various external stimuli to sensitively detect diverse human activities including large body motions and subtle muscle movements via electrical signals. Additionally, this strategy shows good applicable potential for preparing high-performance hydrogels based on monomers containing active double bonds, overcoming the disadvantages of poor mechanical properties of traditional free radical polymerization gels. It is anticipated that the design of dynamic amphiphilic ionic domains will provide guidance for regulating the polymer network of hydrogels and show great application potentials in real-life scenarios.

Spatiotemporal Simulation of Soil Pb Accumulation Process in Urban-Rural Areas: A Case Study of a Large City in Central China

The high intensity of diverse human activities in urban-rural areas leads to complex soil Pb accumulation processes and high spatiotemporal heterogeneity, making it difficult to reveal the spatiotemporal characteristics of soil Pb accumulation in these areas. This study used a typical urban-rural area in a large city in Central China as the study area, constructed a soil Pb accumulation model, and established a spatiotemporal simulation method for soil Pb accumulation processes combining this model and land use classification and simulation results. Using this method, we simulated the soil Pb content in the study area from 2013 to 2040 and elucidated the future spatiotemporal variation characteristics of soil Pb content. The results showed that the average soil Pb content in the study area in 2013 was approximately 1.77 times the background value of the Pb content in the surface soil of the province where the city is located, indicating significant soil Pb pollution. The soil Pb content was predicted to continue increasing from 2013 to 2040, with relatively low increases (0.53-2.25 mg·kg-1) in the western, northern, and southern parts of the study area, accounting for 25.46 % of the total area, and relatively high increases (3.98-5.70 mg·kg-1) in the eastern part, accounting for 17.14 % of the total area. The increase in the area of forest land and the decrease in the area of water bodies and grassland in the eastern part of the study area led to a substantial rise in soil Pb content in this region; in addition, the spatial distribution of soil Pb content was highly correlated with the distribution of important factories and transportation facilities. This study overcomes the limitations of previous research that treated land use as unchanging and to a certain extent reflects the impact of regional land use changes on the heavy metal accumulation process. It provides a method for simulating the soil Pb accumulation process in urban-rural areas and a basis for controlling soil Pb pollution in the city's urban-rural areas.

Combining chemical analysis and toxicological methods to access the ecological risk of complex contamination in Daye Lake

As one of the nine primary non-ferrous metal smelting bases in China, Daye Lake basin was polluted due to diverse human activities. But so far the pollution status and related ecological risks of this region have not been detailly investigated. In current study, pollutants including heavy metals, polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides (OCPs) in eight sediment samples from Daye Lake were quantified. 18S rRNA gene sequencing was employed to profile the nematode community structure within these sediments. Model organism Caenorhabditis elegans (C. elegans) were further applied for a comprehensive ecological risk assessment of Daye Lake. Notably, Cadmium (Cd) was identified as a key driver of ecological risk, reaching an index of 1287.35. At sample point S4, OCPs particularly p,p′-DDT, displayed an extreme ecological risk with a value of 23.19. Cephalobidae and Mononchida showed strong sensitivity to pollutant levels, reinforcing their suitability as robust bioindicators. The composite pollutants in sampled sediments caused oxidative stress in C. elegans, with gene Vit-2 and Mtl-1 as sensitive biomarkers. By employing the multiple analysis methods, our data can offer valuable contributions to environmental monitoring and health risk assessment for composite polluted areas.

Mechanically robust, stretchable and environmentally adaptable organohydrogels with cross-linked fibrous structure for sensory artificial skins

Hydrogels are promising materials for fabricating sensory artificial skins (SASs), but their mechanical properties and environment adaptability are often limited, leading to restricted performances of SASs. In this work, mechanically robust, stretchable and environment adaptable organohydrogels with cross-linked fibrous structure are designed and constructed. The organohydrogels are prepared by introducing doped polyaniline (PANI) into cross-linked fibrous mats of poly(acrylic acid) (PAA) and poly(vinyl alcohol) (PVA). Cross-linked PAA-PVA mat works as skeleton to account for the mechanical robustness while PANI serves as the conductive component to achieve mechanosensing functionality. Due to the unique structure, the resultant organohydrogels, being denoted as PAA-PVA/PANI organohydrogels, exhibit high tensile strength (5.06 MPa), stretchability, fatigue resistance and excellent environment adaptability (anti-freezing, anti-drying and swelling resistance). SASs of such organohydrogels have achieved a gauge factor of 1.81, a sensing range of 0–70 %, a response time of 0.28 s and a reversible sensing in more than 2,000 cycles. In addition, SASs are further attempted in monitoring diverse human motions and physiological activities, such as joint bending, muscle motion and pulse. Overall, this work has provided promising soft materials for future SASs that work properly under complicated environmental conditions.

Holocene utopias and dystopias: Views of the Holocene in the Anthropocene and their impact on defining the Anthropocene

In delineating the Anthropocene, the Holocene is being redefined as the formative epoch of human development leading to the Anthropocene. This has led to a diversity of views of the Holocene and Holocene humanity in the Anthropocene, the extremes of which may be described as “Holocene utopianism” and “Holocene dystopianism.” The former views the Holocene as a solution to the predicament of the Anthropocene, as an idealized past of human activities and stable climate that must be aspired to. The latter perceives the Holocene and Holocene humanity as the root cause of the ills of the Anthropocene that must be avoided in the future. These views reflect a gross simplification of human activities and the environment of the Holocene. Human activity in the Holocene is characterized by diverse human behaviors that can be perceived as both destructive and sustaining to the earth’s ecological systems, and in many cases, emerged as a response to fluctuations in the Holocene climate. The Holocene does not provide an escape from the Anthropocene, as a solution or as a cautionary tale. Nonetheless, future human endeavors must necessarily draw from the diversity of human activities and systems of organization observed in the Holocene, but do so carefully.

Simulation and Forecasting Study on the Influential Factors of PM2.5 Related to Energy Consumption in the Beijing–Tianjin–Hebei Region

It is still necessary to regularly investigate the breakdown of socio-economic elements as a starting point for analyzing the effects of diverse human production activities on PM2.5 intensity from industrial and regional viewpoints. In this paper, the emission factor model was adopted to measure PM2.5 emissions in the Beijing–Tianjin–Hebei (BTH) region at the regional and industrial levels. The logarithmic mean Divisia index (LMDI) decomposition model was employed to analyze the factors affecting PM2.5 emissions related to energy consumption in the BTH region at the regional and sectoral levels. Building on this foundation, a system dynamics (SD) model was established to make a prediction regarding PM2.5 pollution in the BTH region in 2025. This study found that secondary industry was a major source of PM2.5 emissions in the BTH region. Coal remained the main form of energy consumption in the BTH region. Secondly, the effect size of the factors affecting PM2.5 intensity ranked in the order of energy intensity, energy structure, and industrial structure. Thirdly, in 2025, PM2.5 emissions in the BTH region will decline appreciably, but there is still a certain gap in terms of meeting the targets of “the 14th Five-Year Plan” between the three provinces and cities. These results indicate that the BTH region should achieve the effective management of PM2.5 pollution at the source through the following initiatives: it is necessary to carry out the continuous adjustment of energy structures to gradually increase the proportion of clean energy; we must steadily promote the decline in energy intensity reduction, and gradually strengthen scientific and technological innovation; and we must continue to promote the optimization of the industrial structure and increase the proportion of tertiary industry every year.

MFCANN: A feature diversification framework based on local and global attention for human activity recognition

Human activity recognition (HAR) is a crucial detection technique extensively employed in various contexts demanding accurate identification of human actions. Currently, mainstream HAR approaches frequently rely on sequential data generated by wearable sensors, with a primary focus on extracting feature representations that align with various human activities. Nevertheless, complex and diverse human activities encompass various kinds of features and substantial variations in the features emphasized across different activities, making it challenging for current artificial intelligence methods to achieve accurate recognition. To address this challenge, this paper introduces a network framework called the Multi-Feature Combining Attention Neural Network (MFCANN). This framework incorporates diverse feature extraction, along with both local and global feature attention mechanisms. It is composed of stacked Multi-Feature Combining Attention Blocks (MFCAB) designed by us. In contrast to traditional convolutional methods, MFCAB parallelly stacks various convolutional components, enabling the extraction of a broader range of features from human activity data. Additionally, we propose the Intra-Module Attention Block (Intra-MAB) and the Inter-Module Attention Block (Inter-MAB), which simultaneously focus on local fine-grained features within module feature maps and global distinguishing features across module feature maps. This aims to achieve more targeted feature learning, reinforcing the network’s ability to distinguish between different human activities. Abundant experimental results demonstrate that the proposed MFCANN in this paper outperforms current mainstream deep learning algorithms in HAR tasks, achieving recognition accuracies of 0.9813, 0.9324, and 0.9930 on the UCI-HAR, USC-HAD, and RealWorld datasets respectively. We release our code at https://github.com/RangerHeart/MFCANN.

Biological effects of perfluoroalkyl substances on running water ecosystems: A case study in Beiluo River, China

Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are emerging contaminants that pose a threat to the biodiversity of the Beiluo River, a polluted watercourse on the Loess Plateau impacted by diverse human activities. However, the occurrence, spatial distribution, and substitution characteristics of PFASs in this region remain unclear. This study aimed to unravel PFAS distribution patterns and their impact on the aquatic ecosystems of the Beiluo River Basin. The total PFAS concentration in the area ranged from 16.64–35.70 ng/L, with predominantly perfluorocarboxylic acids (PFCAs) and perfluorosulfonic acids (PFSAs), collectively contributing 94%. The Mantel test revealed threats to aquatic communities from both legacy long-chain (perfluorooctanoic acid and sodium perfluorooctane sulfonic acid) and emerging (6:2 fluorotelomer sulfonic acid, 2-Perfluorohexyl ethanoic acid, and hexafluoropropylene oxide dimer acid (Gen-X)) PFSAs. The canonical correspondence analysis ordination indicated that trace quantities of emerging PFASs, specifically 2-Perfluorohexyl ethanoic acid and hexafluoropropylene oxide dimer acid (Gen-X), significantly influenced geographical variations in aquatic communities. In conclusion, this study underscores the importance of comprehensively exploring the ecological implications and potential risks associated with PFASs in the Beiluo River Basin.

Water quality monitoring of welang river basin

The Welang watershed, located in Malang Regency and Pasuruan Regency, has diverse human activities that can affect watershed hydrology, one of which is related to water quality. The purpose of this research is to determine the current water quality of the Welang watershed. This research was conducted in March 2023 - June 2023, which was conducted using random purposive samples with parameters of sunlight intensity, humidity, air temperature, water temperature, pH, TDS, brightness, chlorine, bromine, lead, nitrate, nitrite, fluoride, iodine, cyanuric acid, carbonate root, and total alkalinity. From this study, it was obtained that the upstream part of the Welang River on the Arjuno side and Bromo side contained Chlorine (Cl), Bromine (Br), Iron (Fe), Lead (Pb), Nitrate (NO3-), Nitrite (NO2-), Fluoride (F-), and Carbonate Root (CO3 2–). Meanwhile, the middle part of the Welang River dominantly has the same content, but no Iron (Fe) was found but instead Cyanuric Acid C3N3(OH)3. Meanwhile, the downstream part of the Welang River contained Chlorine (Cl), Copper (Cu), Lead (Pb), and Fluoride (F-).

Metal-sulfide/polysulfide functionalized layered double hydroxides - recent progress in the removal of heavy metal ions and oxoanionic species from aqueous solutions.

Water constitutes an indispensable resource for global life but remains susceptible to pollution from diverse human activities. To mitigate this issue, researchers are committed to purifying water using a variety of materials to remove harmful chemicals, such as heavy metals. Layered double hydroxides (LDHs), with their intriguing, layered structure and chemical behavior, have attained substantial attention for their effectiveness in removing heavy metal cations and various inorganic oxoanions from water. To enhance the efficiency, considerable endeavors have focused on functionalizing LDHs with different chemical species. Intercalation with metal sulfides has proven to be particularly effective, facilitating heavy metal absorption through multiple mechanisms, including ion-exchange, reductive precipitation, and surface sorption. This review concentrates on the synthesis and performance of polysulfide (Sx, x = 2-5), Mo-S, and Sn-S anion intercalated LDHs for heavy metal cations and inorganic oxoanion sorption, along with their mechanisms. Furthermore, the discussion includes prospects for expanding the chemistry of metal sulfide intercalated LDHs, with existing challenges and future outlooks.

Deep learning-based human activity recognition using CNN, ConvLSTM, and LRCN

Human activity recognition (HAR) plays a crucial role in assisting the elderly and individuals with vascular dementia by providing support and monitoring for their daily activities. This paper presents a deep learning (DL)-based approach to HAR, leveraging convolutional neural network (CNN), convolutional long short-term memory (ConvLSTM), and long-term recurrent convolutional network (LRCN) architectures. These models are designed to extract spatial features and capture temporal dependencies in video data, enhancing the accuracy of activity classification. We conducted experiments on the UCF50 and HMDB51 video datasets, encompassing diverse human activities. Our evaluation demonstrates that the ConvLSTM model achieves an accuracy of 82% on UCF50 and 68% on HMDB51, while the LRCN model gives accuracies of 93.44% and 71.55%, respectively. Finally, the CNN model outperforms with an accuracy rate of 99.58% for the UCF50 and 92.70% for the HMDB51 datasets. These significant improvements showcase the effectiveness of integrating convolutional and recurrent neural networks for HAR tasks. Our research contributes to advancing HAR systems with potential applications in healthcare, assisted living, and surveillance. By accurately recognizing human activities, our models can assist in remote patient monitoring, fall detection, and public safety initiatives. These findings underscore the importance of DL in enhancing the quality of life and safety for individuals in various contexts.

Estimation of gridded anthropogenic heat flux at the optimal scale by integrating SDGSAT-1 nighttime lights and geospatial data

Diverse human activities in megaregions have generated excellent anthropogenic heat (AH), which disrupts the urban energy balance and affects the urban climate. However, few studies have investigated the spatial scale effect (SSE) of estimating the multi-source AH flux (QF). Hence, this study proposes a method, i.e., a nighttime light index (NTLI)-based top-down inventory model, to investigate the optimal spatial scale (So) for estimating multi-source gridded QF at the county level and mapping gridded products for the central region of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) megaregion in 2018. The method combines the multi-scale (10–500 m) enhanced NTLI with a top-down inventory model. We generated the enhanced NTLI by integrating the Sustainable Development Science Satellite 1 (SDGSAT-1) nighttime lights (NTL), points of interest, and road network data. Then we analyzed the SSE of QF estimation to determine the So and evaluated the accuracy and characteristics of multi-source QF at the So. The results showed that (1) the So of estimation for six heat components varied between 10 m and 450 m, which related to the difference in energy source and spatial pattern; (2) considering the estimation accuracy, numerical characteristics, and spatial detail of critical urban features, the So of QF was 300 m; (3) the proposed method reduced the estimation error of QF more effectively than the NTL-based inventory model. The root mean square error (RMSE) decreased by 2.45–21.20 %, and the goodness of fit (R2) increased by 2.17–13.66 % among six heat components; and (4) our multi-source QF product at 300 m outperformed previous QF products in spatial heterogeneity and numerical accuracy. This study first explored the SSE of QF estimation and captured the spatial and numerical information of multi-source QF at the So, which could provide valuable knowledge for urban micro-climate.

Progress in agricultural waste derived biochar as adsorbents for wastewater treatment

The wastewater generated from diverse human activities needs to be treated, restore, and reused. Researchers have moved from the deployment of synthetic absorbents to manufacturing adsorbents from waste biomass for the elimination of contaminants from wastewater. The deployment of biochar constructed from agricultural waste has elicited significant devotion due to its ready availability, accessibility, low cost, ease of preparation, and environmental sustainability. This review presents developments in the utilization of biochar obtained from agricultural waste for the remediation of domestic wastewater, industrial wastewater, agricultural wastewater, and stormwater. Discussions on the classification, composition, and characteristics of agricultural waste, techniques for biochar production, and characteristics of wastewater as well as the outcomes of the deployment of biochar in the decontamination of wastewater were highlighted. The study concludes that, notwithstanding the identified environmental, social, economic, and infrastructural challenges, biochar constructed from agricultural waste is an effective, efficient, easy to use, and eco-friendly adsorbent for the decontamination of wastewater. Agricultural waste-derived biochar removes contaminants from wastewater and safeguards aquatic ecosystem and contributes to availability of safe water. Future research directions on innovative and more effective avenues for the application of biochar developed from agricultural waste for wastewater treatment are suggested. The outcome of this review will stimulate renewed interests in using readily available and eco-friendly materials in wastewater remediation.

Interpreting floodplain heterogeneity: Using field data to understand unsupervised floodplain classifications

The dynamic environment of natural river floodplains creates spatial heterogeneity that influences floodplain functions. Diverse human activities have homogenized natural floodplains and reduced their functions across many river networks in the temperate latitudes. Consequently, quantification of floodplain heterogeneity is needed to understand patterns of spatial heterogeneity on diverse floodplains and to inform floodplain restoration. We use a novel approach of spatially connecting field and remotely sensed data in order to interpret the output of, and build upon, a previous unsupervised classification workflow. We apply the method to three rivers in the US Pacific Northwest and the Altamaha River in the southeastern US and compare our results to a previous study. We find that field classifications, relative topography, and NDVI are useful for interpreting results from the unsupervised classification workflow. The interpretations are visually interesting, but we propose that it is the heterogeneity within the groups that is vital to floodplain functioning. Natural floodplains in the Pacific Northwest and coastal Southeast have moderate to high evenness, moderate to high intermixing, and moderate aggregation; and aggregation and evenness similar to rivers in Colorado and Oklahoma, USA, but lower intermixing. We attribute lower intermixing at the Altamaha River to slower rates of lateral channel migration, and lower intermixing at the Hoh River to the different hydrologic and sediment regimes and less stable braided planform. The results show that the larger rivers in this study (Altamaha, Hoh, and Sol Duc Rivers) have spatial heterogeneity similar to beaver-modified and shortgrass prairie rivers in Colorado, whereas the more inland and smaller river (Lookout Creek) has spatial heterogeneity similar to the tallgrass prairie site (Sand Creek). From the results of an ad hoc sensitivity analysis, we suggest using the highest spatial resolution topographic data available, using aerial imagery/mosaics from the same sensor, and removing largest patch index from the suite of comparable indices. The metrics reveal similarities and differences between rivers in the United States, and indicate that discernable trends may arise from a meta study comparing heterogeneity from more rivers across the country.