典型夏季珠江三角洲地区植被的异戊二烯排放

利用中巴卫星影像采用监督分类的方法对影像进行解译,并反演珠江三角洲4种主要的植被类型(PFT).利用自然排放气体和气溶胶模式——MEGAN(Model of Emissions of Gases and Aerosols from Nature),对典型夏季日珠江三角洲地区植被异戊二烯的排放进行了初步研究.结果显示:估算日珠江三角洲植被异戊二烯总的排放量为1.73×106kg(以C计,下同).异戊二烯的排放有明显的日变化特征,最大排放量出现在14:00,为2.39×105kg.广州、江门和惠州的异戊二烯平均排放速率最大,分别为45808·km-2·h-1、4250 g·km-2·h-1和4130 g·km-2h-1;同时江门和惠州也为异戊二烯日排放量的高值区,其日排放总量分别为4.60 ×105kg和4.29 ×105kg,排放贡献率分别为26.6%和24.8%.     

A numerical model for transient-hysteretic flow and solute transport in unsaturated porous media

A two-dimensional flow and transport model was developed for simulating transient water flow and nonreactive solute transport in heterogeneous, unsaturated porous media containing air and water. The model is composed of a unique combination of robust and accurate numerical algorithms for solving the Richards', Darcy flux, and advection-dispersion equations. The mixed form of Richards' equation is solved using a finite-element formulation and a modified Picard iteration scheme. Mass lumping is employed to improve solution convergence and stability behavior. The flow algorithm accounts for hysteresis in the pressure head-water content relationship. Darcy fluxes are approximated with a Galerkin and Petrov-Galerkin finite-element method developed for random heterogeneous porous media. The transport equation is solved using an Eulerian-Lagrangian method. A multi-step, fourth-order Runge-Kutta, reverse particle tracking technique and a quadratic-linear interpolation scheme are shown to be superior for determining the advective concentration. A Galerkin finite-element method is used for approximating the dispersive flux. The unsaturated flow and transport model was applied to a variety of rigorous problems and was found to produce accurate, mass-conserving solutions when compared to analytical solutions and published numerical results.     

Sentiment analysis of the Twitter response to Netflix's Our Planet documentary

The role of nature documentaries in shaping public attitudes and behavior toward conservation and wildlife issues is unclear. We analyzed the emotional content of over 2 million tweets related to Our Planet, a major nature documentary released on Netflix, with dictionary and rule-based automatic sentiment analysis. We also compared the sentiment associated with species mentioned in Our Planet and a set of control species with similar features but not mentioned in the documentary. Tweets were largely negative in sentiment at the time of release of the series. This effect was primarily linked to the highly skewed distributions of retweets and, in particular, to a single negatively valenced and massively retweeted tweet (>150,000 retweets). Species mentioned in Our Planet were associated with more negative sentiment than the control species, and this effect coincided with a short period following the airing of the series. Our results are consistent with a general negativity bias in cultural transmission and document the difficulty of evoking positive sentiment, on social media and elsewhere, in response to environmental problems.     

Arabica-coffee and teobroma-cocoa agro-industrial waste biosorbents,for Pb(II) removal in aqueous solutions

Environmental Science and Pollution Research - Agro-industrial waste biosorbents of arabica–coffee (WCA) and theobroma–cocoa (WCT) have been characterized and tested to remove Pb(II)...     

Waste battery disposal and recycling behavior: a study on the Australian perspective

Environmental Science and Pollution Research - Consumer behavior is a critical consideration for the development of sustainable waste management systems, including waste batteries, which pose a...     

Modelling the globalization-CO2 emission nexus in Australia: evidence from quantile-on-quantile approach

Environmental Science and Pollution Research - Sustainable development policies for achieving net-zero emissions require understanding the factors that influence carbon emissions. Capitalizing on...