Data for assessment of sediment, soil, and water quality at Ashfield flats reserve, Western Australia.

Sediment and water samples were collected using transects and grids within sampling strata, in 2019, 2020, and 2021 from a riparian reserve adjoining the Swan River estuary in Western Australia. Different sampling designs were used each year, with transects and/or grids designed to assess changes in sediment and water quality across assumed environmental gradients such as salinity or distance from possible contaminant sources. Sediments were from 0-10cm; pH and electrical conductivity were measured on suspensions, 32 elements measured by ICP-OES on HNO3/HCl digests, and microplastics counted microscopically after Fenton digestion and density separation. Surface water was from wetland ponds and stormwater drains, with pH, EC measured in-situ. Filtered acidified water subsamples used to measure nitrate + nitrite and dissolved phosphate spectrophotometrically and 26 elements using ICP-OES. Reported data include metadata and are for 231 sediment/soil samples and 172 water samples, including sampling strata categories and UTM and Longitude-Latitude coordinates. Elemental concentrations have been censored based on blank subtraction and calculated lower detection limits, with censored data presented with missing value codes.

Paradoxical impact of sprawling intra-Urban Heat Islets: Reducing mean surface temperatures while enhancing local extremes.

Extreme heat is one of the deadliest health hazards that is projected to increase in intensity and persistence in the near future. Here, we tackle the problem of spatially heterogeneous heat distribution within urban areas. We develop a novel multi-scale metric of identifying emerging heat clusters at various percentile-based thermal thresholds and refer to them collectively as intra-Urban Heat Islets. Using remotely sensed Land Surface Temperatures, we first quantify the spatial organization of heat islets in cities at various degrees of sprawl and densification. We then condense the size, spacing, and intensity information about heterogeneous clusters into probability distributions that can be described using single scaling exponents (denoted by ß, [Formula: see text], and λ, respectively). This allows for a seamless comparison of the heat islet characteristics across cities at varying spatial scales and improves on the traditional Surface Urban Heat Island (SUHI) Intensity as a bulk metric. Analysis of Heat Islet Size distributions demonstrates the emergence of two classes where the dense cities follow a Pareto distribution, and the sprawling cities show an exponential tempering of Pareto tail. This indicates a significantly reduced probability of encountering large heat islets for sprawling cities. In contrast, analysis of Heat Islet Intensity distributions indicates that while a sprawling configuration is favorable for reducing the mean SUHI Intensity of a city, for the same mean, it also results in higher local thermal extremes. This poses a paradox for urban designers in adopting expansion or densification as a growth trajectory to mitigate the UHI.

Emergent self-similarity and scaling properties of fractal intra-urban heat islets for diverse global cities.

Urban areas experience elevated temperatures due to the urban heat island (UHI) effect. However, temperatures within cities vary considerably and their spatial heterogeneity is not well characterized. Here, we use land surface temperature (LST) of 78 global cities to show that the surface UHI (SUHI) is fractal. We use percentile-based thermal thresholds to identify heat clusters emerging within SUHI and refer to them collectively as intra-urban heat islets. The islets display properties analogous to that of a percolating system as we vary the thermal thresholds. At percolation threshold, the size distribution of these islets in all cities follows a power law, with a scaling exponent (ß) of 1.88 (±0.23,95%CI) and an aggregated perimeter fractal dimension (D) of 1.33 (±0.064,95%CI). This commonality indicates that despite the diversity in urban form and function across the world, the urban temperature patterns are different realizations with the same aggregated statistical properties. Furthermore, we observe the convergence of these scaling exponents as the city sizes increase. Therefore, while the effect of diverse urban morphologies is evident in smaller cities, in the mean, the larger cities are alike. Lastly, we calculate the mean islet intensities, i.e., the difference between mean islet temperature and thermal threshold, and show that it follows an exponential distribution, with rate parameter λ, for all cities. λ varied widely across the cities and can be used to quantify the spatial heterogeneity within SUHIs. In conclusion, we present a basis for a unified characterization of urban heat from the spatial scales of an urban block to a megalopolis.