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The construction of new towns is one of the main measures to evacuate urban populations and promote regional coordination and urban–rural integration in China. Mining the spatio-temporal pattern of new town hot spots based on multivariate data and analyzing the influencing factors of new town construction hot spots can provide a strategic basis for new town construction, but few researchers have extracted and analyzed the influencing factors of new town internal hot spots and their classification. In order to define the key points of Wuhan's new town construction and promote the construction of new cities in an orderly and efficient manner, this paper first constructs a space-time cube based on the luminous remote sensing data from 2010 to 2019, extracts hot spots and emerging hot spots in Wuhan New City, selects 14 influencing factor indicators such as population density, and uses bivariate Moran's index to analyze the influencing factors of hot spots, indicating that the number of bus stops and vegetation coverage rate are the most significant. Secondly, the disorderly multivariate logistic regression model is used to analyze the influencing factors of emerging hot spots. The results show that population density, vegetation coverage, road density, distance to water bodies, and distance to train stations are the most significant factors. Finally, based on the analysis results, some relevant suggestions for the construction of Wuhan New City are proposed, providing theoretical support for the planning and policy guidance of new cities, and offering reference for the construction of new towns in other cities, promoting the construction of high-quality cities. [ABSTRACT FROM AUTHOR]

Elevated atmospheric reactive nitrogen (Nr) emissions and the subsequent nitrogen (N) deposition have negatively impacted the global environment, particularly in China. In order to assess the long-term trends in atmospheric N deposition in the south of China, Taojiang County in Hunan Province was selected as a representative rural area for study. We analyzed interannual variation in atmospheric Nr, including gaseous ammonia (NH3), nitrogen dioxide (NO2), nitrate acid (HNO3) vapor, particulate ammonium (NH4+), and nitrate (NO3−) in air and NH4+-N and NO3−-N in precipitation from 2011 to 2020. The 10-year average atmospheric wet-plus-dry N deposition was 41.9 kg N ha−1 yr−1, which decreased by approximately 24% after 2012, indicating that NH3 and NOx emissions were effectively reduced by emission controls introduced in 2013. Wet deposition accounted for approximately 74% of the total N deposition and was significantly influenced by annual precipitation amount. Reduced N (NH3, pNH4+, and NH4+ in rainwater) was the dominant form, comprising approximately 58% of the total N deposition, while oxidized N (pNO3−, NO2, HNO3, and NO3− in rainwater) accounted for 42% of the total N deposition. Atmospheric HNO3, NO2, and NH3 concentrations and deposition declined by 30–80% over the decade, while particulate NH4+ and NO3− concentrations and deposition remained at relatively stable levels, which suggests that ongoing research and policy should focus on rural particulate pollution. Future strategies must concentrate on the integrated control of NH3 and NOx emissions to mitigate air pollution and protect human health, particularly in rural areas because current abatement efforts are primarily directed toward urban areas and the industrial sector, whereas non-point source NH3 pollution, influenced mainly by agricultural activities, dominates in rural regions. [ABSTRACT FROM AUTHOR]

A modified parallel model for estimating the thermal conductivity of unsaturated sand was proposed in this study. The heat conduction in the solid phase of sand depends mainly on the form of contacts between solid particles, while water bridges at the particle contacts increase the contact areas and remarkably enlarge the transfer paths of heat conduction in sandy soils. However, the thermal conductivity of the solid particle itself (λs) cannot describe the influence of the form of contacts and water bridges on heat conduction through the solid phase. In this study, the equivalent thermal conductivity of the solid particle (λes) was presented which reflected the influence of the form of contacts and water bridges between particles under dry conditions or a low degree of saturation, respectively. The relationship between λes and degree of saturation was described by hyperbolic expression. The modified model was calibrated using measured values of the thermal conductivity from published datasets, including those for 41 types of sand from 15 studies. Numerical analyses of the temperature field of the energy pile were performed and validated against laboratory measurements. The results illustrated that the modified model was more applicable than the original model for predictions of sand thermal conductivity. [ABSTRACT FROM AUTHOR]