A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.     

Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.     

创新价值链视角下企业创新效率差异及影响因素分析——基于江苏省国家高新区企业的验证

中国经济新常态背景下,高新区企业创新增效提质是增强高新区创新能力的内生动力.从创新价值链视角出发,将企业创新过程分为技术开发阶段和经济转化阶段,运用两阶段DEA模型分别对2016年江苏省12个国家高新区、11个技术领域以及各高新区内不同技术类型企业的整体和分阶段创新效率进行测度,并构建Tobit回归模型探究每个阶段企业创新效率的影响因素.研究表明:(1)江苏省国家高新区整体创新效率有较大提升空间,其中技术开发效率表现优于经济转化效率.(2)高创新效率的技术领域集中在电子与信息、新材料等,生物医药、环境保护和光机电一体化等技术领域整体创新效率处于较低水平.(3)以各阶段创新效率均值为分界,划分创新资源利用的四种模式,大部分高新区企业处于高开发-低转化和低开发-高转化型模式,存在技术创新与经济转化联系不够紧密的现象.(4)资本投入水平、劳动力的“质”和“量”、政府支持力度对企业创新效率的影响存在明显的阶段差异性.最后,根据研究结果,从强化知识交流网络、集聚多元化人才、调整资源投入产出评估方式及采取扬优补短式效率提升路径四个方面给出提升高新区企业创新效率的政策建议.     

Changes in the Distribution of Broadleaf Tree Species in the Central Part of the Southern Urals since the 1970s

Russian Journal of Ecology - Changes in the distribution of broadleaf tree species—Tilia cordata Mill., Quercus robur L., Acer platanoides L., and Ulmus glabra Huds.—in the central part...     

Materials,fuels, upgrading,economy, and life cycle assessment of the pyrolysis of algal and lignocellulosic biomass: a review

Climate change issues are calling for advanced methods to produce materials and fuels in a carbon–neutral and circular way. For instance, biomass pyrolysis has been intensely investigated during the last years. Here we review the pyrolysis of algal and lignocellulosic biomass with focus on pyrolysis products and mechanisms, oil upgrading, combining pyrolysis and anaerobic digestion, economy, and life cycle assessment. Products include oil, gas, and biochar. Upgrading techniques comprise hot vapor filtration, solvent addition, emulsification, esterification and transesterification, hydrotreatment, steam reforming, and the use of supercritical fluids. We examined the economic viability in terms of profitability, internal rate of return, return on investment, carbon removal service, product pricing, and net present value. We also reviewed 20 recent studies of life cycle assessment. We found that the pyrolysis method highly influenced product yield, ranging from 9.07 to 40.59% for oil, from 10.1 to 41.25% for biochar, and from 11.93 to 28.16% for syngas. Feedstock type, pyrolytic temperature, heating rate, and reaction retention time were the main factors controlling the distribution of pyrolysis products. Pyrolysis mechanisms include bond breaking, cracking, polymerization and re-polymerization, and fragmentation. Biochar from residual forestry could sequester 2.74 tons of carbon dioxide equivalent per ton biochar when applied to the soil and has thus the potential to remove 0.2–2.75 gigatons of atmospheric carbon dioxide annually. The generation of biochar and bio-oil from the pyrolysis process is estimated to be economically feasible.

     

Water,sanitation, hygiene and waste disposal practices as COVID-19 response strategy: insights from Bangladesh

Environment, Development and Sustainability - The COVID-19 pandemic has caused a global emergence, and the absence of a proven vaccine or medicine has led to the implementation of measures to...     

Institutional quality,financial development and sustainable economic growth among lower income countries

This article postulates strong endogenous relationships in lower income countries between institutional quality, financial development and sustained economic growth. These associations were investigated using the vector-error correction model (VECM) and Granger causality method for a sample of 79 countries from 2005 to 2022. The findings show that (1) these variables reinforce each other in the short run. (2) In the long run, both institutional quality and financial development can fuel economic growth. (3) The positive effect of institutional quality on economic growth is greater than that of financial development. Policy implications of these findings are that careful attention should be paid to co-development policies to enhance the institutional quality and the financial system in these economies. Policies should also consider economic growth strategies to enable sustainable economic growth rates.     

Between Active Seekers and Non-Users: Segments of Science-related Media Usage in Switzerland and Germany

ABSTRACT

Citizens’ attitudes toward science are related to their use of science-related information from various sources. Evidence is scarce regarding citizens’ individual media repertoires for staying informed about science as segmentation studies so far have primarily focused on scientific attitudes. In this paper, we explore audience segments regarding their science-related information behavior and whether such segments are comparable or vary between two countries with similar information environments. Based on two surveys in Switzerland and Germany, we identify national audience segments that differ in their science-related information repertoires, and analyze their sociodemographic characteristics and science-related attitudes. In both countries, we find very comparable information user segments ranging from those who inform themselves frequently about science (“Active Seekers”/“Science Consumers”) to those who hardly get in contact with any information about science and research (“Non-Users”). Those segments which get in contact with information about science frequently show generally more positive attitudes.     

常州市春节期间污染物相关性分析

分析了常州市2017年春节前后各污染物浓度的关联性和差异性。结果表明,除O_3外,春节期间各污染物均值均低于春节前后,春节前后随着污染源的变化,污染物之间的相关性表现出较为明显的差异。SO_2与PM_(2.5)、PM_(10)、CO和NO_2的相关性均较春节前后有显著下降;爆竹集中燃放时间段,CO与综合指数、PM_(2.5)和PM_(10)之间的相关系数0.96;而在烟花爆竹燃放相对较少的初三和初四,该相关系数0.6。工业减产停产和机动车使用减少对空气质量改善有较大贡献,而在不利气象条件下,烟花爆竹可导致空气质量在短时间内恶化。