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31.
为了实现碳排放达峰目标和碳中和愿景,明确应对气候变化的法律地位、工作目标和法律要求,规定部门职责及温室气体排放权的法律属性与交易机制,分解工作目标并开展评价考核,彰显国家应对气候的法治决心,亟须制定综合性基础法律——应对气候变化法。该法的制定已具备充足的研究起草基础和下位法支撑,建议尽快纳入全国人大常委会立法计划,并启动《环境保护法》等相关法律的修改。本文建议,将低碳发展和碳排放达峰、碳中和等纳入立法目的,设立总则、规划与标准、气候变化减缓、气候变化适应、管理和监督、国际合作、法律责任、附则八章,合理设立规范重点。健全统一监管与部门分工负责的体制和基金筹集、市场交易、社会共治等机制,全面构建国内应对气候变化管理制度体系,部署国际协商与合作措施,设置地方政府工作目标责任,对违法行为规定罚则。 相似文献
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人类活动作用于土地资源,使LUCC(土地利用/土地覆被变化)在全球环境变化过程中起主导作用,随着国际LUCC研究计划的进展,各国依据本国的实际情况开展研究。对西安市以往五年(2000-2004年)的土地利用基础数据开展调查统计分析,建立灰色系统动态GM(1,1)模型,预测2005—2010年西安市土地利用结构变化状况,尝试计算西安市土地生态系统服务价值损失(简称生态损失),用一种直观经济指标-货币来反映这种生态损失。预测2010年西安市生态损失为331、84×10^6元。 相似文献
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通过在二类标准适用区进行不同高度的噪声监测试验,利用获得的监测数据进行统计分析,找出不同高度噪声Leq小时值的统计特征,从而确定二类功能区噪声垂直变化规律。 相似文献
35.
Bushra Khali Ayesha Khali Sidra Muslim Ammara Habi Kishwar Khan Debora Souza Alvim Sehrish Shakoor Sonia Mustaf Sana Zaheer Momel Zoon Azmat Hayat Khan Sana Ilyas Bin Chen 《环境科学学报(英文版)》2021,33(1):28-39
This study finds out seasonal and monthly variations in Aerosol Optical Depth (AOD) over eastern and western routes of China Pakistan Economic Corridor (CPEC) and the relationship between AOD and meteorological parameters (i.e., temperature, rainfall and wind speed). The Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) data was used from the terra satellite for the period of 2000-2016. This study aims to overtake the conventional view of the purpose of using the satellite datasets. This study takes on to the concept that validated satellite data sets rather should be used for the analysis instead of just validation specifically for our study region. Hence, after comparing MODIS AOD with MISR AOD, only MISR AOD dataset is used for further analysis. The results show a decreasing trend of AOD in summer season, a positive relationship between temperature and AOD during winter and spring seasons whereas a positive relationship between wind speed and AOD in winter and spring seasons over eastern and western routes. Periodic analysis of MODIS AOD and MISR AOD depicts May-Aug as the peak period of aerosol concentration over central Pakistan. The inter-annual analysis shows the aerosol trend remained higher during summer season however rainfall shows the washout effect. Eastern route has higher standard deviation and larger values for aerosol prevalence as compared to western route. The trajectory analysis using the HYSPLIT model suggests the bias of air mass trajectory caused deviation in the aerosol trend in the year 2014. 相似文献
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Maria Lumbierres Prabhat Raj Dahal Moreno Di Marco Stuart H. M. Butchart Paul F. Donald Carlo Rondinini 《Conservation biology》2022,36(3):e13851
Area of habitat (AOH) is defined as the “habitat available to a species, that is, habitat within its range” and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups. 相似文献
37.
Cho ST Tsai SH Ravindran A Selvam A Yang SS 《Environmental geochemistry and health》2008,30(3):255-272
To investigate the seasonal variations of microbial ecology in grassland of Tatachia forest, soil properties, microbial populations,
microbial biomass, and 16S rDNA clone library analysis were determined. The soil had temperatures 6.6–18.4°C, pH 3.6–5.1,
total organic carbon 1.11–10.68%, total nitrogen 0.18–0.78%, and C/N ratios 3.46–20.55. Each gram of dry soil contained bacteria,
actinomycetes, fungi, cellulolytic, phosphate-solubilizing microbes, and nitrogen-fixing microbes 4.54 × 104 to 3.79 × 107, 3.43 × 102 to 2.17 × 105, 5.74 × 103 to 3.76 × 106, 1.97 × 103 to 1.34 × 106, 8.49 × 102 to 5.59 × 105, and 3.86 × 102 to 3.75 × 105 CFU, respectively. Each gram of soil contained 117–2,482 μg of microbial biomass carbon, 23–216 μg of microbial biomass nitrogen
and 9–29 μg of DNA. The microbial populations, microbial biomass, and DNA decreased stepwise with the depth of soil, and they
had low values in winter seasons. The microbial populations, microbial biomass carbon, microbial biomass nitrogen, and DNA
at the BW2 horizon were 8.42–17.84, 19.26–64.40, 16.84–61.11, and 31.03–46.26% of those at the O horizon, respectively. When
analyzing 16S rDNA library, members of Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes,
candidate division TM1, candidate division TM7, Gammatimonadetes, and Verrucomicrobia were identified. Members of Proteobacteria
(44.4%) and Acidobacteria (33.3%) dominated the clone libraries. Within the phylum Proteobacteria, α-, β-, and γ-Proteobacteria
were most numerous, followed by δ-Proteobacteria. 相似文献
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广州市大气可吸入颗粒物(PM10)中多环芳烃的季节变化 总被引:24,自引:1,他引:24
采集广州五山、荔湾(2002-06-12~2003-06-31)2个采样点共112个PM10样品进行了GC/MS分析,结果表明2采样点全年多环芳烃浓度范围为8.11~106.26 ng·m-3,呈现出夏季低冬季高的特征.PAHs化合物的相对分布也呈明显的季节变化,5~6环PAHs的比重夏季比冬季高,而3~4环PAHs的比重冬季比夏季高.冬季PAHs可分为2种模式,不同模式之间PAHs的浓度和分布特征有明显的差异.统计结果表明,广州市多环芳烃浓度变化主要受气象条件的影响,风速(当温度<20℃时)和温度(当温度>20℃时)是影响多环芳烃浓度最主要的因素.此外,本研究还表明,汽车尾气排放是广州市大气颗粒物多环芳烃污染最主要的污染来源. 相似文献