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Spatial autocorrelation and driving factors of carbon emission density of crop production in China
Mitigating carbon emissions from crop production is essential for addressing global warming. At a macro-level, existing studies have often relied on...
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Spatiotemporal evolution of water ecological footprint based on the emergy-spatial autocorrelation method
To quantify and analyze the human demand for water resources and the available supply of water resource systems, this study combined emergy analysis...
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Spatiotemporal Characterization of LST and Analysis of Its Spatial Dependence: A Spatial Autocorrelation Approach
The temperature of the land surface is an important indicator of climate as it shows the connection between land and the atmosphere. The relationship...
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Spatial autocorrelation analysis of the environmental efficiency of coal-fired power plants in China
AbstractAlthough many studies have analyzed the environmental efficiency of coal-fired power plants in China with the aim of reducing CO 2 emissions,...
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Characterizing spatial dependence of boron, arsenic, and other trace elements for Permian groundwater in Northern Anhui plain coal mining area, China, using spatial autocorrelation index and geostatistics
Anthropogenic and geological factors play an essential role in the variability of groundwater quality, resulting in a weak spatial dependence of...
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Global autocorrelation test based on the Monte Carlo method and impacts of eliminating nonstationary components on the global autocorrelation test
Autocorrelation and non-stationarity are always concerned in analysis of meteorological and hydrological time series. Current commonly used methods,...
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Street dust-bound metal(loid)s in industrial areas of Iran: Moran's spatial autocorrelation distribution, eco-toxicological risk assessment, uncertainty and sensitivity analysis
AbstractThis study investigated the contamination, spatial distribution, and eco-toxicological risks of metal(loid)s in street dust samples collected...
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Analysis of changes in air pollution quality and impact of COVID-19 on environmental health in Iran: application of interpolation models and spatial autocorrelation
In the global COVID-19 epidemic, humans are faced with a new challenge. The concept of quarantine as a preventive measure has changed human...
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Combining spatial autocorrelation with artificial intelligence models to estimate spatial distribution and risks of heavy metal pollution in agricultural soils
Information on spatial distribution and potential sources of heavy metals in agricultural lands is very important for human health and food safety....
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Random forest and spatial cross-validation performance in predicting species abundance distributions
Random forests (RF) have been widely used to predict spatial variables. Several studies have shown that spatial cross-validation (CV) methods...
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Influence of short- and long-term persistence on identification of rainfall temporal trends using different versions of the Mann-Kendall test in Mizoram, Northeast India
Investigating the temporal dynamics of rainfall in a changing climate, especially in rainfed agriculture regions, is crucial for analyzing...
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Spatial and temporal differences in the response of water conservation and soil conservation to ecosystem fragmentation: evidence from Qilian Mountain National Park of China
Using spatial autocorrelation methods, we explored the spatial and temporal differences in the response of soil conservation (SC) and water...
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Exploring Lagged Effects in Time Series
In this chapter, we will introduce lagged effects to build on the previous work in modeling time series data. Time-lagged effects occur when an event...
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Characteristics of rural domestic sewage discharge and their driving mechanisms: evidence from the Northern Region, China
The traits of rural domestic sewage emission are unclear, negatively affecting rural domestic sewage treatment and sewage management. This study used...
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Spatial–temporal variations and influencing factors of air quality in China’s major cities during COVID-19 lockdown
To control the spread of COVID-19, the Chinese government announced a “lockdown” policy, and the citizens’ activities were restricted. This study...
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Impacts of hydrometeorological factors on discharge simulation in the North West Himalayas: a SUFI-2 algorithm-driven investigation using the SWAT model
The Soil and Water Assessment Tool (SWAT) is a computational hydrological model extensively utilised for develo** sustainable strategies and viable...
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Potential and health impact assessment of air pollutant emission reduction: a case study of China
Air pollution has become the world’s largest human health and environmental risk factor. This study used the greenhouse gas and air pollution...
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Spatiotemporal dynamics and influencing factors of carbon productivity in counties of Shandong Province, China
In the context of the increasing global greenhouse effect, the Chinese government has proposed a “dual carbon” target. As a major carbon-emitting...
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Dynamic evolutionary characteristics and influence mechanisms of carbon emission intensity in counties of the Yangtze River Delta, China
Clarifying the intrinsic mechanism of county carbon emission intensity (CEI) is essential for guiding the realization of a low-carbon economy as well...
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Exploring the association of PM2.5 with lung cancer incidence under different climate zones and socioeconomic conditions from 2006 to 2016 in China
Air pollution generated by urbanization and industrialization poses a significant negative impact on public health. Particularly, fine particulate...
