Suchergebnisse

Along with the globally increasing concern for environmental sustainability, improving urban industrial land use efficiency (UILUE) is critically important for China&rsquo ; s development trajectory. However, the existent studies on UILUE in China are mainly conducted at the provincial level, which significantly undermines their value for tailoring practical policy formulations for lower-level governments. To fill this gap, this paper aims to investigate the spatial and temporal pattern of UILUE in China at the prefectural level, examining the underpinning influential factors for the period 2000&ndash ; 2014. Employing the means of spatial autocorrelation and regression, it is found that UILUE in China has improved significantly over the past decade in general but is also accompanied by significant spatial variations. UILUE is positively related to the agglomeration of industries, labour, capital, and technology, in which technology has fundamental effects upon the other factors. It is suggested to policy makers that government policy interventions should be placed predominantly upon technology regulation, i.e., setting admittance criterion for foreign direct investment (FDI), and industrial investment. For future studies, consistent efforts ought to be exerted to examine UILUE at and even under the prefectural level to achieve better understanding among academics and policy practitioners.

Context
The toxic cane toad (Rhinella marina) has invaded over 50 countries and is a serious conservation issue in Australia. Because the cane toad has taken several decades to colonise northern Australia, due to the large size of the continent and the east–west invasion axis, there is scope for making testable predictions about how toads will invade new areas. The western toad invasion front is far from linear, providing clear evidence for heterogeneity in invasion speed.

Aims
Several ad hoc hypotheses have been offered to explain this heterogeneity, including the evolution of traits that could facilitate dispersal, and spatial heterogeneity in climate patterns. Here an alternative hypothesis is offered, and a prediction generated for the spatiotemporal pattern of invasion into the Kimberley Region – the next frontier for the invading toads in Australia.

Methods
Using observations of spatiotemporal patterns of cane toad colonisation in northern Australia over the last 15 years, a conceptual model is offered, based on the orientation of wet season river flows relative to the invasion axis, as well as toad rafting and floating behaviour during the wet season.

Key results
Our model predicts that toads will invade southern areas before northern areas; an alternative model based on rainfall amounts makes the opposite prediction. The models can now be tested by monitoring the spread of invasion front over the next 5–10 years.

Conclusions
Our conceptual models present a pleuralistic approach to understanding the spatiotemporal invasion dynamics of toads; such an approach and evaluation of the models could prove useful for managing other invasive species.

Implications
Although control of cane toads has largely proved ineffective, knowledge of the spatiotemporal pattern of the toad invasion in the Kimberley could: (1) facilitate potential management tools for slowing the spread of toads; (2) inform stakeholders in the local planning for the invasion; (3) provide researchers with a temporal context for quantifying toad impacts on animal communities; and (4) reveal the mechanism(s) causing the heterogeneity in invasion speed.

Abstract
The slowing of agricultural productivity growth globally over the past two decades has brought a new urgency to detect its drivers and potential solutions. We show that air pollution, particularly surface ozone (O3), is strongly associated with declining agricultural total factor productivity (TFP) in China. We employ machine learning algorithms to generate estimates of high-resolution surface O3 concentrations from 2002 to 2019. Results indicate that China's O3 pollution has intensified over this 18-year period. We coupled these O3 estimates with a statistical model to show that rising O3 pollution during nonwinter seasons has reduced agricultural TFP by 18% over the 2002–2015 period. Agricultural TFP is projected to increase by 60% if surface O3 concentrations were reduced to meet the WHO air quality standards. This productivity gain has the potential to counter expected productivity losses from 2°C warming.

By 29 May 2020, the coronavirus disease (COVID-19) caused by SARS-CoV-2 had spread to 188 countries, infecting more than 5.9 million people, and causing 361,249 deaths. Governments issued travel restrictions, gatherings of institutions were cancelled, and citizens were ordered to socially distance themselves in an effort to limit the spread of the virus. Fear of being infected by the virus and panic over job losses and missed education opportunities have increased people's stress levels. Psychological studies using traditional surveys are time-consuming and contain cognitive and sampling biases, and therefore cannot be used to build large datasets for a real-time depression analysis. In this article, we propose a CorExQ9 algorithm that integrates a Correlation Explanation (CorEx) learning algorithm and clinical Patient Health Questionnaire (PHQ) lexicon to detect COVID-19 related stress symptoms at a spatiotemporal scale in the United States. The proposed algorithm overcomes the common limitations of traditional topic detection models and minimizes the ambiguity that is caused by human interventions in social media data mining. The results show a strong correlation between stress symptoms and the number of increased COVID-19 cases for major U.S. cities such as Chicago, San Francisco, Seattle, New York, and Miami. The results also show that people's risk perception is sensitive to the release of COVID-19 related public news and media messages. Between January and March, fear of infection and unpredictability of the virus caused widespread panic and people began stockpiling supplies, but later in April, concerns shifted as financial worries in western and eastern coastal areas of the U.S. left people uncertain of the long-term effects of COVID-19 on their lives.

Urban expansion is not only reflected in the increase in horizontal urban area, but also in the increase in vertical urban height, that is, the city's vertical expansion. Exploring the spatiotemporal evolution of urban vertical expansion and its influencing factors is critical for furthering urban expansion research. This paper characterized the degree of urban vertical expansion using the floor area ratio (FAR) of newly added residential land in Jiangsu Province, China, from 2009 to 2018, and discussed the spatiotemporal characteristics, regional differences and influencing factors of urban vertical expansion. The results indicate the following: (1) The degree of urban vertical expansion in Jiangsu Province exhibited an inverted "U" shape that increased and then decreased. Spatially, it presented a pattern of high in the west and low in the east areas, while high in the north and low in the south areas. (2) There were significant α-convergence, β-convergence and club convergence phenomena in Jiangsu Province's urban vertical expansion. The convergence speed was fast in the north and south areas but slow in the middle. (3) Real estate development investment and slope had a significant positive impact on urban vertical expansion, while urban per capita disposable income and economic structure had a non-linear impact on urban vertical expansion intensity. Finally, this paper highlighted the importance of further investigation into urban expansion from multiple dimensions. The government should strengthen its control over the various land plot ratios to ensure the city's orderly expansion and healthy development.

Abstract. Climate change in the Mediterranean region is manifesting itself as an increase in average air temperature and a change in the rainfall regime: the value of cumulative annual rainfall generally appears to be constant, but the intensity of annual rainfall maxima, between 1 and 24 h, is increasing, especially in the period between late summer and early autumn. The associated ground effects in urban areas consist of flash floods and pluvial floods, often in very small areas, depending on the physical-geographical layout of the region. In the context of global warming, it is therefore important to have an adequate monitoring network for rain events that are highly concentrated in space and time. This research analyses the meteo-hydrological features of the 27 and 28 August 2023 event that occurred in the city of Genoa, Italy, just 4 d after the record maximum air temperature was recorded: between 19:00 and 02:00 UTC almost 400 mm of rainfall was recorded in the eastern sector of the historic centre of Genoa, with significant ground effects such as flooding episodes and the overflowing of pressurised culverts. Rainfall observations and estimates were made using both official or "authoritative" networks (rain gauges and meteorological radar) and rain gauge networks inspired by citizen science principles. The combined analysis of observations from authoritative and citizen science networks reveals, for the event analysed, a spatial variability of the precipitation field at an hourly and a sub-hourly timescale that cannot be captured by the current spatial density of the authoritative measurement stations (which have one of the highest densities in Italy). Monthly total rainfall and short-duration annual maximum time series recorded by the authoritative rain gauge network of the Genoa area are then analysed. The results show significant variation even at distances of less than 2 km in the average rainfall depth accumulated over sub-hourly duration. Extreme weather monitoring activity is confirmed as one of the most important aspects in terms of flood prevention and protection in urban areas. The integration between authoritative and citizen science networks can prove to be a valid contribution to the monitoring of extreme events.