Research progress and hot spots of hydrothermal liquefaction for bio-oil production based on bibliometric analysis

Environmental Science and Pollution Research - Hydrothermal liquefaction (HTL) of biomass used HTL reaction under high temperature and pressure to produce bio-oil. This technology is considered as...     

基于多功能协调的湖北省城市建设用地差别化绩效管控

城市建设用地差别化绩效管控是国土空间治理能力现代化的重要体现，也是土地政策精准投放的基础。从新时期城市建设用地的基本价值出发，构建基于经济生产、社会服务、生态保护、政治公平服务保障和科技文化培育五维功能的绩效评价指标体系，采用熵权法绩效评价模型和改进的协调度模型对湖北省城市建设用地五维功能绩效和协调度进行了评价，在此基础上通过“绩效-协调”差异性特征划分了不同类型区，并相应地制定了差别化管控政策。研究表明：湖北省城市建设用地综合绩效差异性表现为“中心城市最高，副中心城市次之，远离中心区域最差”的分布格局，而不同功能维度绩效差异性也较为明显，结合城市建设用地多功能协调程度来看，湖北省16个市域可划分为3类管控区，分别为多功能协调优化区、多功能潜力挖掘区和多功能适度强化区，并可分别从结构优化、功能协调、总量控制、增量供给、存量挖潜等方面对城市建设用地实行差别化管控。该研究可为建设用地双控行动与土地资源优化配置提供方法参考。 关键词： 土地利用；城市建设用地；绩效；多功能协调；差别化管控     

人工园林大面积种植区植被净初级生产力时空变化研究

云南西南地区自然资源丰富，近年来，随着社会经济的快速发展，橡胶、茶园和桉树等人工园林大规模种植主要占用了天然林和耕地，土地利用结构和空间布局发生了很大变化。为了探讨土地利用/覆被变化对植被净初级生产力（NPP）的影响，以人工园林大面积种植区西盟县为研究区，运用综合模型、CASA模型和MODIS产品（BIOME-BGC模型），对西盟县2000年、2005年、2010年和2015年各地类NPP的时间变化和空间分布特征进行分析。结果表明：（1）2000~2015年，CASA模型模拟的西盟县NPP呈先减少后增加的趋势，MODIS模型模拟的NPP值变化趋势与CASA模型一致，综合模型则呈现逐年增加的趋势；（2）西盟县NPP的空间分布形态从西至东均呈“低值-高值-低值-高值-低值”（“M”）变化，与西盟县水热资源的分布特征和土地利用/覆被变化有关，西盟县NPP空间变化主要集中于人工园林种植区；（3）3种模型中，CASA模型和MODIS产品（BIOME-BGC模型）比综合模型更适用于地形气候复杂多样的山区NPP的模拟计算，其中CASA模型空间精度更高。     

基于关联性及趋势性分析的AVHRR NDVI及#br# MODIS NDVI数据产品比较

针对AVHRR NDVI和MODIS NDVI数据集中不同数据产品间的差异和区域适应性问题，利用2003~2013年重叠时间段MODIS Terra/Aqua的NDVI Collection 5(C5)和Collection 6(C6)产品以及AVHRR NDVI中的GIMMS NDVI3g产品，选择汉江流域典型区域进行数据对比分析。通过关联指数IOAs(Index of Association)来评价各数据在季节波动上的一致性；采用Mann Kendall检验分析各数据的长期趋势差异。结果表明，在季节性变化上，同一卫星不同版本产品之间的关联性相对较高。在年际变化上，GIMMS产品相对MODIS 产品，仅能检出部分NDVI变化趋势。在地表覆被异质性相对较高地区，GIMMS产品的长期变化趋势检出率较低。MODIS Terra的NDVI C5产品受传感器退化影响，表现出相对较高的减少趋势。 关键词： GIMMS NDVI；MODIS NDVI；Mann Kendall检验；趋势分析     

环境保护职业教育校企合作的难点与对策

环保职业教育校企合作中存在深度和广度不够、政府主导作用没有充分发挥、环保职业院校努力不够、企业热情不高等问题,这些问题出现的根本原因有环保工作自身的特殊性,环保职业教育与行业发展疏离和高校毕业生就业岗位下沉等。充分发挥政府主导作用和环保行指委平台作用是解决问题、破解难点的关键,政府制定完善的政策法规是重中之重。"政、校、企"三方合作并建立完善的运行机制是我国环保职业教育校企合作有效开展的良策。     

Using culturomics and social media data to characterize wildlife consumption

Wildlife provides food, medicine, clothing, and other necessities for humans, but overexploitation can disrupt the sustainability of wildlife resources and severely threaten global biodiversity. Understanding the characteristics of consumer behavior is helpful for wildlife managers and policy makers, but the traditional survey methods are laborious and time-consuming. In contrast, culturomics may more efficiently identify the features of wildlife consumption. As a case study of the culturomics approach, we examined tiger bone wine consumption in China based on social media and Baidu search engine data. Tiger bone wine is one of the most purchased tiger products; its consumption is closely related to tiger poaching, which greatly threatens wild tiger survival. We searched a popular social media website for the term “tiger bone wine” and focused on posts that were originally created from 1 January 2012 to 31 December 2018. We filtered and classified posts related to the purchase, sale, or consumption of tiger bone wine and extracted information on providers, consumption motivations, year of production, and place of origin of the tiger bone wines based on the texts and photos of these posts. We found 756 posts related to tiger bone wine consumption, 113 of which mentioned providers of tiger bone wine, including friends (53%), elder relatives (37%), peer relatives (7%), and others (3%). Out of the 756 posts, 266 indicated the motivations of tiger bone wine consumption. Tiger bone wines were consumed as a tonic (34%), medicine (23%), game product (30%), and a symbol of wealth (28%). Some posts indicated ≥2 consumption motivations. These findings were consistent with the search queries from Baidu index. Such information could help develop targeted strategies for tiger conservation. The culturomics approach illustrated by our study is a rapid and cost-efficient way to characterize wildlife consumption.     

2005-2019年我国重特大安全生产事故特征分析

为探究我国重特大安全生产事故特征,选取2005-2019年国内852起重特大事故作为研究对象,基于Python编程语言针对重特大事故发生的年份、季度、月份、工作日与非工作日、地域特征进行分析.结果表明:2005-2019年,国内重特大安全生产事故起数和死亡人数均在不断下降;第四季度发生重特大事故最多,而第三季度平均每起事故造成的死亡人数最多;重特大事故数量和死亡人数随月份显示出反复波动的趋势,均呈现3个"^",形;工作日期间发生的重特大事故数量最多,非工作日平均事故率最大;国庆节是重特大事故发生最多的节假日;贵州、湖南、山西、云南、河南等省份"十四五"期间需要重点加强安全和应急管理.     

The accounting method and application of CO2 emissions responsibility by the electricity sector at the provincial level in China

When accounting the CO₂ emissions responsibility of the electricity sector at the provincial level in China,it is of great significance to consider the scope of both producers’ and the consumers’ responsibility,since this will promote fairness in defining emission responsibility and enhance cooperation in emission reduction among provinces.This paper proposes a new method for calculating carbon emissions from the power sector at the provincial level based on the shared responsibility principle and taking into account interregional power exchange.This method can not only be used to account the emission responsibility shared by both the electricity production side and the consumption side,but it is also applicable for calculating the corresponding emission responsibility undertaken by those provinces with net electricity outflow and inflow.This method has been used to account for the carbon emissions responsibilities of the power sector at the provincial level in China since 2011.The empirical results indicate that compared with the production-based accounting method,the carbon emissions of major power-generation provinces in China calculated by the shared responsibility accounting method are reduced by at least 10%,but those of other power-consumption provinces are increased by 20% or more.Secondly,based on the principle of shared responsibility accounting,Inner Mongolia has the highest carbon emissions from the power sector while Hainan has the lowest.Thirdly,four provinces,including Inner Mongolia,Shanxi,Hubei and Anhui,have the highest carbon emissions from net electricity outflow- 14 million t in 2011,accounting for 74.42% of total carbon emissions from net electricity outflow in China.Six provinces,including Hebei,Beijing,Guangdong,Liaoning,Shandong,and Jiangsu,have the highest carbon emissions from net electricity inflow- 11 million t in 2011,accounting for 71.44% of total carbon emissions from net electricity inflow in China.Lastly,this paper has estimated the emission factors of electricity consumption at the provincial level,which can avoid repeated calculations when accounting the emission responsibility of power consumption terminals（e.g.construction,automobile manufacturing and other industries）.In addition,these emission factors can also be used to account the emission responsibilities of provincial power grids.     

我国探矿权资产化、证券化的模式及设想

探矿权资产化、证券化是我国改革探矿业投融资体制，解决探矿业资金瓶颈问题的关键。本文从制度建设、机构投资者的发展状况等方面分析了我国初步推行探矿权资产化、证券化的有利条件．指出了探矿权资产化、证券化的三种模式。并以基金模式和股权模式为例提出了实施探矿权资产化、证券化的步骤设想。     

Estimating sampling frequency in pollen exposure assessment over time

A time series model was fitted to the pollen concentration data collected in the Greater Cincinnati area for the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). A traditional time series analysis and temporal variogram approach were applied to the regularly spaced databases (collected in 2003) and irregularly spaced ones (collected in 2002), respectively. The aim was to evaluate the effect of the sampling frequency on the sampling precision in terms of inverse of standard error of the overall level of mean value across time. The presence of high autocorrelation in the data was confirmed and indicated some degree of temporal redundancy in the pollen concentration data. Therefore, it was suggested that sampling frequency could be reduced from once a day to once every several days without a major loss of sampling precision of the overall mean over time. Considering the trade-offs between sampling frequency and the possibility of sampling bias increasing with larger sampling interval, we recommend that the sampling interval should take values from 3 to 5 days for the pollen monitoring program, if the goal is to track the long-term average.