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An essential part of urban natural systems, urban green spaces play a crucial role in mitigating the urban heat island effect (UHI). The UHI effect refers to the phenomenon where the temperature within a city is higher than that of the surrounding rural areas. The effects of the spatial composition and configuration of urban green spaces on urban land surface temperature (LST) have recently been documented. However, few studies have examined the effects of the directionality and distribution of green spaces on LST. In this study, we used a landscape index to describe the change in pattern of heat island intensity for the city of Baotou, China. We then used a semi-variable function and nearest neighbor algorithm to analyze the cooling effects of green spaces. We found that: (1) the cooling distance of an urban green space was not only influenced by its size, vegetation cover, and shape, but also showed anisotropy. In general, the larger the area of the urban green space and the higher the value of Normalized Difference Vegetation Index (NDVI; a measure of plant photosynthetic activity), the larger the cooling distance within a certain threshold. Green spaces with more regular shapes displayed higher LST mitigation; however, the cooling distance was directional, and cooling effects depended on the semi-major axis and semi-minor axis of the green space. (2) The distribution of the urban green space within the landscape played a key role in mitigating the UHI effect. Within a certain area, the cooling effect of green spaces that are evenly distributed was greater than that which was associated with either green spaces that were large in area or where greens spaces were aggregated in the landscape. Therefore, within urban areas, where space is limited, urban planning should account for green spaces that are relatively scattered and evenly distributed to maximize cooling effects. The results of this study have key implications for sustainable urban planning and development; to mitigate urban heat island effects it is important to not only increase canopy cover or the size of urban green spaces, but also to optimize their spatial configuration.

PurposeThe environment in high-tech industries is highly dynamic, and after COVID-19, it has become even more unpredictable. Hence, it has become critical for firms to develop strategies to cope with a highly dynamic environment. This paper aims to analyze how the impact of the scientific collaboration networks with URIs (universities and research institutes) on firm innovation performance is contingent on technological and market dynamics.Design/methodology/approachUsing a sample of 174 Chinese firms in the new-energy vehicle industry during 2004–2015, the authors applied a random-effects negative binomial modeling approach to model these relationships.FindingsA broad and strong scientific collaboration network promotes firm innovation network effects are contingent on technological and market dynamics. While technological dynamics strengthen the effect market dynamics weaken it due to the different purposes of collaboration for firms and URIs.Practical implicationsFirms should adjust the structure of scientific collaboration networks with URIs when facing different environments. The government should encourage firms to jointly research with diverse URIs and play an active role in stabilizing market environments.Originality/valueThis study contributes to the academic debate on university-industry scientific collaborations. Applying the temporary competitive advantage (TCA) framework, we provide nuances to the literature that studies the factors that condition the effects of networks. This study also adds to the research on firm scientific collaboration networks by measuring networks based on the coauthorship between firms and URIs.

Exploiting earth-abundant electrocatalysts with comparable high performance and stability to the benchmarking noble metal-based catalysts for oxygen evolution reaction (OER) is of fundamental importance for promising sustainable energy conversion and storage technologies. Herein, we report an in situ grown zinc doped cobalt–iron layered double hydroxide (ZnFeCo LDH) with a unique needle-like nanostructure and partial amorphous phase for highly efficient OER catalysts. Benefitting from the nanoneedle arrays structure, partial amorphous phase, tunable zinc doping, and surface trivalent cobalt ions, partly amorphous Zn doped FeCo LDH 1D nanoneedle arrays (PA-ZnFeCo LDH) exhibited superior electrocatalytic OER activity, with a small Tafel slope of 58.73 mV per decade, an exceptional overpotential of 221, 276, and 294 mV to drive 10, 100, and 300 mA cm–2, respectively, and long-term electrochemical stability of 100 000 s. This work offers insights into the rational design and synthesis of unique 1D non-noble metal hydroxide with partial amorphous phase as highly efficient OER electrocatalysis.

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A modification of the aluminium-lumogallion fluorescence measurement in the presence of the non-ionic surfactant Triton X-100 is presented. The detection limit for dissolved Al is 0.7 nM, with a relative standard deviation of 3.6% at an Al level of 5.0 nM. Compared with previously reported methods in the literature, the method described here is free from matrix effects and can be used for the determination of aluminium in fresh, estuarine and saline waters. The interferences from iron and fluoride were minimized by the addition of o-phenanthroline and Be2+, respectively. The analysis of NIST SRM 1643C and PRC standard 2430101 by the proposed method provides results consistent with the certified values. A successful inter-laboratory calibration exercise also demonstrates the merit of the proposed method for the determination of Al in environmental and marine sciences.

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