Riverine nitrate source and transformation as affected by land use and land cover.

A mixed land use/land cover (LULC) catchment increases the complexity of sources and transformations of nitrate in rivers. Spatial paucity of sampling particularly low-resolution sampling in tributaries can result in a bias for identifying nitrate sources and transformations. In this study, high spatial resolution sampling campaigns covering mainstream and tributaries in combination with hydro-chemical parameters and dual isotopes of nitrate were performed to reveal spatio-temporal variations of nitrate sources and transformations in a river draining a mixed LULC catchment. This study suggested that point sources dominated the nitrate in the summer and winter, while non-point sources dominated the nitrate in the spring and autumn. A positive correlation was observed between proportions from sewage and land use index (LUI). However, negative correlations between soil nitrogen/nitrogen fertilizer and LUI were observed. With an increase of urban areas, the increased contribution from domestic sewage resulted in an increase of NO3- concentrations in rivers. Both urban and agricultural inputs should be considered in nitrate pollution management in a mixed LULC catchment. We concluded that the seasonal variations of nitrate sources were mainly affected by flow velocity conditions and agricultural activities, while spatial variations were mainly affected by LULC. In addition, we found a novel underestimation of dominated sources from Bayesian model because of mixing effect of isotope values from the tributaries to mainstream, however, high spatial resolution sampling can make up for this shortcoming. δ15N and δ18O values of nitrate indicated that nitrate originated from nitrification in soils. The nitrate concentrations and correlation between δ15N and 1/[NO3-] suggested little contribution of nitrate removal by denitrification. Thus, the nitrate reduction in the Yuehe River basin needs to be strengthened. The study provides new implications for estimation of nitrate sources and transformations and basis for nitrate reduction in the river with mixed LULC catchment.

Spatial Coupling Coordination Evaluation of Mixed Land Use and Urban Vitality in Major Cities in China.

Based on the data from 35 major cities in China in 2020, this paper applies the Simpson's diversity index, the entropy value method, and the coupling coordination degree model to comprehensively measure the coupling coordination level of mixed land use and urban vitality in major cities in China and further analyze their spatial distribution characteristics. In addition, this paper analyzes the factors affecting the spatial variation of the coupling coordination level with the help of the geographic probe model. The study finds that: (1) The overall level of coupling coordination between mixed land use and urban vitality is high in 35 major cities in China. There is no disorder between mixed land use and urban vitality. (2) In terms of the spatial distribution of the coupling coordination between mixed land use and urban vitality in 35 cities in China, five cities, namely Beijing, Shenzhen, Shanghai, Guangzhou, and Chengdu, have the highest level of coupling coordination between mixed land use and urban vitality, reaching "good coordination" with a discrete spatial distribution. Central cities such as Hangzhou and Nanjing have the second highest level of coupling coordination and are at the "intermediate coordinate" with a "strip-like distribution" in space. Twenty cities in the north and south have the lowest coupling coordination levels and are in the "primary coordination." Among these twenty cities, seven cities in the south have a higher level of coupling coordination than thirteen cities in the north, with a spatial distribution of a "C" shape. The northern cities have the lowest level of coupling coordination, with a "W"-shaped distribution in space. (3) Population size plays an essential role in guiding the level of coupling coordination between mixed land use and urban vitality in major cities in China, followed by government regulation and economic level. At the same time, transportation conditions and industrial structure have the weakest influence on the level of coupling coordination between mixed land use and urban vitality in major cities in China.

Mixed Land Use Levels in Rural Settlements and Their Influencing Factors: A Case Study of Pingba Village in Chongqing, China.

Mixed land use provides an important means of promoting the intensive and efficient use of land resources and stimulating endogenous development power in rural areas. This paper selected Pingba Village in Chongqing as the research area; the land use status data and the social and economic data on rural settlements in the study area for 2021 were obtained through field visits and interviews. Moreover, the land use types in the rural settlements were subdivided according to the principle of dominant function. Based on these subdivisions, a land mixed-use measurement system for rural settlements was constructed to analyze their levels of mixed land use. Furthermore, the influences of natural environmental, social, economic and other factors on mixed land use were comprehensively explored. The results showed that, (1) the mixed land use of rural settlements in the study area was at a medium level and showed significant spatial variability, and rural settlements in the high, medium and low mixed land use index zones accounted for 12.5%, 35% and 52.5% of the total, respectively. (2) The differences in the natural environment determined the level of mixed land use and the basic pattern of its spatial differentiation. Social and economic factors, such as resident population and average household income, were key impact factors. Rural tourism resources, homestead agglomeration policies and other factors had important impacts on the level of mixed land use. In conclusion, the research suggests that mixed land use is an important way to boost rural revitalization. In the future, village planning could introduce the concept of mixed land use to improve the efficiency of land use, optimize the land use structure according to local conditions and promote the integrated development of rural primary, secondary and tertiary industries. In addition, it is necessary to scientifically and rationally guide rural settlements to agglomerate appropriately to improve the utilization efficiency of land resources and public service resources.

Agricultural practices drive biological loads, seasonal patterns and potential pathogens in the aerobiome of a mixed-land-use dryland.

Air carries a diverse load of particulate microscopic biological matter in suspension, either aerosolized or aggregated with dust particles, the aerobiome, which is dispersed by winds from sources to sinks. The aerobiome is known to contain microbes, including pathogens, as well as debris or small-sized propagules from plants and animals, but its variability and composition has not been studied comprehensibly. To gain a dynamic insight into the aerobiome existing over a mixed-use dryland setting, we conducted a biologically comprehensive, year-long survey of its composition and dynamics for particles less than 10 µm in diameter based on quantitative analyses of DNA content coupled to genomic sequencing. Airborne biological loads were more dependent on seasonal events than on meteorological conditions and only weakly correlated with dust loads. Core aerobiome species could be understood as a mixture of high elevation (e.g. Microbacteriaceae, Micrococcaceae, Deinococci), and local plant and soil sources (e.g. Sphingomonas, Streptomyces, Acinetobacter). Despite the mixed used of the land surrounding the sampling site, taxa that contributed to high load events were largely traceable to proximal agricultural practices like cotton and livestock farming. This included not only the predominance of specific crop plant signals over those of native vegetation, but also that of their pathogens (bacterial, viral and eukaryotic). Faecal bacterial loads were also seasonally important, possibly sourced in intensive animal husbandry or manure fertilization activity, and this microbial load was enriched in tetracycline resistance genes. The presence of the native opportunistic pathogen, Coccidioides spp., by contrast, was detected only with highly sensitive techniques, and only rarely. We conclude that agricultural activity exerts a much stronger influence that the native vegetation as a mass loss factor to the land system and as an input to dryland aerobiomes, including in the dispersal of plant, animal and human pathogens and their genetic resistance characteristics.

A novel methodology for Groundwater Flooding Susceptibility assessment through Machine Learning techniques in a mixed-land use aquifer.

Many areas around the world are affected by Groundwater Level rising (GWLr). One of the most severe consequences of this phenomenon is Groundwater Flooding (GF), with serious impacts for the human and natural environment. In Europe, GF has recently received specific attention with Directive 2007/60/EC, which requires Member States to map GF hazard and propose measures for risk mitigation. In this paper a methodology has been developed for Groundwater Flooding Susceptibility (GFS) assessment, using for the first time Spatial Distribution Models. These Machine Learning techniques connect occurrence data to predisposing factors (PFs) to estimate their distributions. The implemented methodology employs aquifer type, depth of piezometric level, thickness and hydraulic conductivity of unsaturated zone, drainage density and land-use as PFs, and a GF observations inventory as occurrences. The algorithms adopted to perform the analysis are Generalized Boosting Model, Artificial Neural Network and Maximum Entropy. Ensemble Models are carried out to reduce the uncertainty associated with each algorithm and increase its reliability. GFS is mapped by choosing the ensemble model with the best predictivity performance and dividing occurrence probability values into five classes, from very low to very high susceptibility, using Natural Breaks classification. The methodology has been tested and statistically validated in an area of 14,3 km2 located in the Metropolitan City of Naples (Italy), affected by GWLr since 1990 and GF in buildings and agricultural soils since 2007. The results of modeling show that about 93% of the inventoried points fall in the high and very high GFS classes, and piezometric level depth, thickness of unsaturated zone and drainage density are the most influencing PFs, in accordance with field observations and the triggering mechanism of GF. The outcomes provide a first step in the assessment of GF hazard and a decision support tool to local authorities for GF risk management.

Quantifying spatial heterogeneity of vulnerability to short-term PM2.5 exposure with data fusion framework.

The current estimations of the burden of disease (BD) of PM2.5 exposure is still potentially biased by two factors: ignorance of heterogeneous vulnerabilities at diverse urbanization levels and reliance on the risk estimates from existing literature, usually from different locations. Our objectives are (1) to build up a data fusion framework to estimate the burden of PM2.5 exposure while evaluating local risks simultaneously and (2) to quantify their spatial heterogeneity, relationship to land-use characteristics, and derived uncertainties when calculating the disease burdens. The feature of this study is applying six local databases to extract PM2.5 exposure risk and the BD information, including the risks of death, cardiovascular disease (CVD), and respiratory disease (RD), and their spatial heterogeneities through our data fusion framework. We applied the developed framework to Tainan City in Taiwan as a use case estimated the risks by using 2006-2016 emergency department visit data, air quality monitoring data, and land-use characteristics and further estimated the BD caused by daily PM2.5 exposure in 2013. Our results found that the risks of CVD and RD in highly urbanized areas and death in rural areas could reach 1.20-1.57 times higher than average. Furthermore, we performed a sensitivity analysis to assess the uncertainty of BD estimations from utilizing different data sources, and the results showed that the uncertainty of the BD estimations could be contributed by different PM2.5 exposure data (20-32%) and risk values (0-86%), especially for highly urbanized areas. In conclusion, our approach for estimating BD based on local databases has the potential to be generalized to the developing and overpopulated countries and to support local air quality and health management plans.

Mixed land use and neighborhood crime.

The concentration of certain land uses has been linked to crime rates; yet, it remains to be seen whether mixed land use, defined as heterogeneity among several land uses, independently affects neighborhood crime. The goal of the current study, therefore, is to build upon the extant literature by examining how mixed land use influences crime, net of specific land uses and sociodemographic characteristics. Using data on Los Angeles block groups, a Herfindahl index was constructed of eight specific land uses to capture mixed land use, and a series of negative binomial regression models were estimated to assess the main and moderating effects of mixed land use on neighborhood crime. Although mixed land use was found to exert a deleterious influence on two crime types, concentrated disadvantage moderated the effect of mixed land use on all crime types. The implications of these findings for criminology, urban studies, and policy are discussed.

Linking ecological health to co-occurring organic and inorganic chemical stressors in a groundwater-fed stream system.

Freshwaters are among the most endangered ecosystems worldwide, due predominantly to excessive anthropogenic practices compromising the future provisioning of ecosystem services. Despite increased awareness of the role of multiple stressors in accounting for ecological degradation in mixed land-use stream systems, risk assessment approaches applicable in field settings are still required. This study provides a first indication for ecological consequences of the interaction of organic and inorganic chemical stressors, not typically evaluated together, which may provide a missing link enabling the reconnection of chemical and ecological findings. Specifically, impaired ecological conditions - represented by lower abundance of meiobenthic individuals - were observed in the hyporheic zone where a contaminant groundwater plume discharged to the stream. These zones were characterized by high xenobiotic organic concentrations, and strongly reduced groundwater (e.g. elevated dissolved iron and arsenic) linked to the dissolution of iron hydroxides (iron reduction) caused by the degradation of xenobiotic compounds in the plume. Further research is still needed to separate whether impact is driven by a combined effect of organic and inorganic stressors impacting the ecological communities, or whether the conditions - when present simultaneously - are responsible for enabling a specific chemical stressor's availability (e.g. trace metals), and thus toxicity, along the study stream. Regardless, these findings suggest that benthic meioinvertebrates are promising indicators for supporting biological assessments of stream systems to sufficiently represent impacts resulting from the co-occurrence of stressors in different stream compartments. Importantly, identification of the governing circumstances is crucial for revealing key patterns and impact drivers that may be needed in correctly prioritizing stressor impacts in these systems. This study further highlights the importance of stream-aquifer interfaces for investigating chemical stressor effects in multiple stressor systems. This will require holistic approaches for linking contaminant hydrogeology and eco(toxico)logy in order to positively influence the sustainable management of water resources globally.

Assessing the chemical contamination dynamics in a mixed land use stream system.

Traditionally, the monitoring of streams for chemical and ecological status has been limited to surface water concentrations, where the dominant focus has been on general water quality and the risk for eutrophication. Mixed land use stream systems, comprising urban areas and agricultural production, are challenging to assess with multiple chemical stressors impacting stream corridors. New approaches are urgently needed for identifying relevant sources, pathways and potential impacts for implementation of suitable source management and remedial measures. We developed a method for risk assessing chemical stressors in these systems and applied the approach to a 16-km groundwater-fed stream corridor (Grindsted, Denmark). Three methods were combined: (i) in-stream contaminant mass discharge for source quantification, (ii) Toxic Units and (iii) environmental standards. An evaluation of the chemical quality of all three stream compartments - stream water, hyporheic zone, streambed sediment - made it possible to link chemical stressors to their respective sources and obtain new knowledge about source composition and origin. Moreover, toxic unit estimation and comparison to environmental standards revealed the stream water quality was substantially impaired by both geogenic and diffuse anthropogenic sources of metals along the entire corridor, while the streambed was less impacted. Quantification of the contaminant mass discharge originating from a former pharmaceutical factory revealed that several 100 kgs of chlorinated ethenes and pharmaceutical compounds discharge into the stream every year. The strongly reduced redox conditions in the plume result in high concentrations of dissolved iron and additionally release arsenic, generating the complex contaminant mixture found in the narrow discharge zone. The fingerprint of the plume was observed in the stream several km downgradient, while nutrients, inorganics and pesticides played a minor role for the stream health. The results emphasize that future investigations should include multiple compounds and stream compartments, and highlight the need for holistic approaches when risk assessing these dynamic systems.

A comparison of the spatial distribution of vadose zone water in forested and agricultural floodplains a century after harvest.

To improve quantitative understanding of the long-term impact of historic forest removal on floodplain vadose zone water regime, a study was implemented in fall 2010, in the Hinkson Creek Watershed, Missouri, USA. Automated, continuously logging capacitance-frequency probes were installed in a grid-like formation (n=6) and at depths of 15, 30, 50, 75, and 100 cm within a historic agricultural field (Ag) and a remnant bottomland hardwood forest (BHF). Data were logged at thirty minute intervals for the duration of the 2011, 2012, and 2013 hydrologic years. Results showed volumetric water content (VWC) to be significantly different between sites (p<0.01) during the study, with site averages of 33.1 and 32.8% at the Ag and BHF sites, respectively. Semi-variogram analyses indicate the presence of strong (<25%) horizontal and vertical spatial correlation of VWC at the Ag site, and a relatively short-range (25 cm) vertical spatial correlation at the BHF, but only indicate horizontal VWC spatial correlation in the top 30 cm of the BHF profile. Likely mechanisms contributing to patterns of observed differences are contrasting rates and depths of plant water use, and the presence of preferential flow paths in the below ground BHF. Results suggest historic forest removal and cultivation of the Ag site lead to an effective homogenization of the upper soil profile, and facilitated the development of strong VWC spatial dependency. Conversely, higher hydraulic conductivity of the more heterogeneous BHF subsurface likely results in a wetting of the deeper profile (75 cm) during climatically wet periods, and thus a more effective processing of hydrologic inputs. Collective results highlight the greater extent and degree to which forest vegetation impacts subsurface hydrology, relative to grassland/agricultural systems, and point to the value of reestablishing floodplain forests for fresh water routing, water quality, and flood mitigation in mixed-land-use watersheds.

Quantifying suspended sediment flux in a mixed-land-use urbanizing watershed using a nested-scale study design.

Suspended sediment (SS) remains the most pervasive water quality problem globally and yet, despite progress, SS process understanding remains relatively poor in watersheds with mixed-land-use practices. The main objective of the current work was to investigate relationships between suspended sediment and land use types at multiple spatial scales (n=5) using four years of suspended sediment data collected in a representative urbanized mixed-land-use (forest, agriculture, urban) watershed. Water samples were analyzed for SS using a nested-scale experimental watershed study design (n=836 samples×5 gauging sites). Kruskal-Wallis and Dunn's post-hoc multiple comparison tests were used to test for significant differences (CI=95%, p<0.05) in SS levels between gauging sites. Climate extremes (high precipitation/drought) were observed during the study period. Annual maximum SS concentrations exceeded 2387.6 mg/L. Median SS concentrations decreased by 60% from the agricultural headwaters to the rural/urban interface, and increased by 98% as urban land use increased. Multiple linear regression analysis results showed significant relationships between SS, annual total precipitation (positive correlate), forested land use (negative correlate), agricultural land use (negative correlate), and urban land use (negative correlate). Estimated annual SS yields ranged from 16.1 to 313.0 t km(-2) year(-1) mainly due to differences in annual total precipitation. Results highlight the need for additional studies, and point to the need for improved best management practices designed to reduce anthropogenic SS loading in mixed-land-use watersheds.