Long short-term memory neural network and improved particle swarm optimization–based modeling and scenario analysis for municipal solid waste generation in Shanghai,China

Accurate estimations of municipal solid waste (MSW) generation are vital to effective MSW management systems. While various single-point estimation approaches have been developed, the non-linearity and multiple site-specific influencing factors associated with MSW management systems make it challenging to forecast MSW generation quantities precisely. To address these concerns, this study developed a two-stage modeling and scenario analysis procedure for MSW generation and taking Shanghai as a test case demonstrated its viability. In the first stage, nine influencing factors were selected, and a hybrid novel forecasting model based on a long short-term memory neural network and an improved particle swarm optimization (IPSO-LSTM) was proposed for the forecasting of the MSW generation quantities, after which actual Shanghai data from 1980 to 2019 were used to test the performance. In the second stage, the future influencing variable values in different scenarios were predicted using an improved grey model, after which the predicted Shanghai MSW generation quantities from 2025 to 2035 were evaluated under various scenarios. It was found that (1) the proposed IPSO-LSTM had higher accuracy than the benchmark models; (2) the MSW generation quantities are expected to respectively increase to 9.971, 9.684, and 9.090 million tons by 2025 and 11.402, 11.285, and 10.240 by 2035 under the low, benchmark, and high scenarios; and (3) the MSW generation differences between the high and medium scenarios were decreasing.

     

Elaboration of a Bio-Colored Material Based on Natural Dye and Polybutylene Succinate: Comparative Study with Colored Polylactic Acid

Journal of Polymers and the Environment - In the context of sustainable development and natural products valorization, new ecological materials enter a logic aimed at removing the causes of...     

Effects of human footprint and biophysical factors on the body-size structure of fished marine species

Marine fisheries in coastal ecosystems in many areas of the world have historically removed large-bodied individuals, potentially impairing ecosystem functioning and the long-term sustainability of fish populations. Reporting on size-based indicators that link to food-web structure can contribute to ecosystem-based management, but the application of these indicators over large (cross-ecosystem) geographical scales has been limited to either fisheries-dependent catch data or diver-based methods restricted to shallow waters (<20 m) that can misrepresent the abundance of large-bodied fished species. We obtained data on the body-size structure of 82 recreationally or commercially targeted marine demersal teleosts from 2904 deployments of baited remote underwater stereo-video (stereo-BRUV). Sampling was at up to 50 m depth and covered approximately 10,000 km of the continental shelf of Australia. Seascape relief, water depth, and human gravity (i.e., a proxy of human impacts) were the strongest predictors of the probability of occurrence of large fishes and the abundance of fishes above the minimum legal size of capture. No-take marine reserves had a positive effect on the abundance of fishes above legal size, although the effect varied across species groups. In contrast, sublegal fishes were best predicted by gradients in sea surface temperature (mean and variance). In areas of low human impact, large fishes were about three times more likely to be encountered and fishes of legal size were approximately five times more abundant. For conspicuous species groups with contrasting habitat, environmental, and biogeographic affinities, abundance of legal-size fishes typically declined as human impact increased. Our large-scale quantitative analyses highlight the combined importance of seascape complexity, regions with low human footprint, and no-take marine reserves in protecting large-bodied fishes across a broad range of species and ecosystem configurations.     

Streamflow Depletion Modeling: Methods for an Adaptable and Conjunctive Water Management Decision Support Tool

Groundwater pumping depletes streamflow, which can have significant ecological impacts depending on the magnitude of depletion relative to environmental flow needs. Streamflow depletion estimates from groundwater pumping have been quantified using both analytical and numerical methods, but are not routinely compared to environmental flow needs or used in practical water management tools. Decision support tools that incorporate groundwater dynamics are becoming increasingly necessary for water managers as groundwater regulations become more important in environmental policy, particularly concerning the preservation of environmental flow needs. We develop and apply methods for a web‐based decision support tool for conjunctive groundwater and surface water management, demonstrated using a case study watershed in British Columbia, Canada. Open‐source data are analyzed with a combination of spatial algorithms and previously developed analytical models, such that the tool can be applied to other regions. Streamflow depletion estimates are calculated in four regions in the largely undeveloped Bulkley Valley, British Columbia. Our transparent methodology has geographic and data input flexibility which is a significant improvement on currently existing water management tool methods.     

Biogeographic distribution patterns of algal community in different urban lakes in China: Insights into the dynamics and co-existence

Urban lake ecosystems are significant for social development, but currently we know little about the geographical distribution of algal community in urban lakes at a large-scale. In this study, we investigated the algal community structure in different areas of urban lakes in China and evaluated the influence of water quality parameters and geographical location on the algal community. The results showed that obvious differences in water quality and algal communities were observed among urban lakes in different geographical areas. Chlorophyta was the dominant phylum, followed by cyanobacteria in all areas. The network analysis indicated that algal community composition in urban lakes of the western and southern area showed more variations than the eastern and northern areas, respectively. Redundancy analysis and structural equation model revealed that nutrients and pH were dominant environmental factors that affected the algal community, and they showed higher influence than that of iron, manganese and COD _Mn concentration. Importantly, algal community and density exhibited longitude and latitude relationship. In general, these results provided an ecological insight into large-scale geographical distributions of algal community in urban lakes, thereby having potential applications for management of the lakes.     

Analysis of Daily Peaking and Run‐of‐River Operations with Flow Variability Metrics,Considering Subdaily to Seasonal Time Scales

Environmental flows are an important consideration in licensing hydropower projects as operational flow releases can result in adverse conditions for downstream ecological communities. Flow variability assessments have typically focused on pre‐ and post‐dam conditions using metrics based on daily averaged flow values. This study used subdaily and daily flow data to assess environmental flow response to changes in hydropower operations from daily peaking to run‐of‐river. An analysis tool was developed to quantify flow variability metrics and was applied to four hydropower projects. Significant differences were observed between operations at the 99% confidence level in the median flow values using hourly averaged flow datasets. Median daily rise and fall rates decreased on average 34.5 and 27.9%, respectively, whereas median hourly rise and fall rates decreased on average 50.1 and 50.6%, respectively. Differences in operational flow regimes were more pronounced in the hourly averaged flow datasets and less pronounced or nonexistent in the daily averaged flow datasets. These outcomes have implications for the development of ecology‐flow relationships that quantify effects of flow on processes such as fish stranding and displacement, along with habitat stability. Results indicate that flow variability statistics should be quantified using subdaily datasets to accurately represent the nature of hydropower operations, especially for daily peaking facilities.     

狼毒对西藏高原高寒草甸退化的指示作用

局部草甸退化是西藏高原面临的主要生态问题,狼毒在高寒退化草甸中的入侵、扩散也日益严重,已经成为退化草甸中主要的毒杂草之一.为了解狼毒对高寒草甸退化程度的指示作用,在西藏当雄县草原站选择3处不同退化程度的高寒草甸群落,调查植物群落组成,并测定各群落表层土壤的理化指标.结果显示:随着狼毒分布增加,草甸呈逐步退化的态势,一方面,草甸群落的优势物种组成从以牧草为主转变为以毒杂草为主,狼毒盖度、地上生物量及重要值逐渐增加,而禾本科、莎草科等优良牧草的盖度、地上生物量以及重要值逐渐降低;另一方面,草甸表层土壤表现出贫瘠化的趋势,土壤有机质、全氮含量、土壤含水量均显著降低,无机氮(硝态氮、氨态氮)也呈降低的趋势,而pH值、土壤容重则呈增加趋势.狼毒盖度及地上生物量与牧草地上生物量、土壤全氮、有机碳及土壤含水量呈显著的负相关(P0.05),而与土壤容重和pH值呈极显著正相关(P0.01).因此,较易测定的狼毒盖度及地上生物量能较好地指示当雄草原化草甸的退化程度,可作为判定草甸退化程度的指标.     

Antibacterial and antimutagenic activitiy of extracts and essential oil from (Tunisian) Pistacia lentiscus

Aqueous and flavonoid-enriched extract as well as essential oil (EO) obtained from leaves of Pistacia lentiscus were assessed for antibacterial and antimutagenic activities. Antibacterial activity of different extracts and EO were evaluated against six bacterial strains. A marked inhibitory effect was observed against Salmonella typhimurium, whereas lower activity was observed against Staphylococcus aureus, Pseudomonas aeruginosa, and Salmonella enteritidis. EO showed significant inhibitory effects against Salmonella typhimurium, Salmonella enteritidis and Staphylococcus aureus. The antimutagenic activity of the different extracts against Aflatoxin B₁ (AFB₁) and sodium azide was demonstrated with the Salmonella typhymurium assay. The number of revertants per plate decreased significantly when the plant extracts were added to the assay system using Salmonella typhimurium TA100, TA98 and TA1535.     

乙炔燃爆特性的研究

为减少乙炔火灾爆炸事故的发生,采用20 L爆炸罐为试验仪器,对常温、初始压力0.1 MPa条件下,不同体积配比乙炔-空气混合气的燃爆特性及氮气对乙炔分解爆炸的影响进行了试验研究,并结合碰撞理论和燃烧反应方程对试验结果进行了理论分析。结果表明:乙炔-空气混合气体随乙炔体积分数增大,最大爆炸压力逐渐升高;在乙炔体积分数为10%~55%范围内,乙炔与空气混合气的最大爆炸压力恒定在1.7 MPa,乙炔体积分数为10%时取得最大爆炸指数(78.14MPa.m/s);乙炔体积分数为55%~100%范围内,混合气体爆炸与初始压力有关,并且初始压力随乙炔体积分数增大而升高;纯乙炔分解爆炸的初始压力为0.18 MPa。氮气对乙炔分解爆炸有一定的抑制作用,并随氮气体积分数增加,抑制作用逐渐增大。