基于卫星夜间灯光数据的中国分省碳排放时空模拟

中国能源统计数据"横向不可比,纵向不可加"现象依然突出,尤其是分省能源消费统计千差万别,给分省碳排放评估带来了较大困难,如何利用卫星遥感数据科学合理地估算中国分省碳排放是当前亟须研究的问题。本文运用DMSP/OLS全球稳定夜间灯光数据,在通过相互校正、年内融合和年际间校正等系列处理得到中国分省稳定夜间灯光数据的基础上,首先分别构建中国分省稳定夜间灯光亮度DN值与人均碳排放和单位面积碳排放之间的时空地理加权回归模型,两个模型整体效果均较好,拟合优度分别高达96.74%和99.24%;其次运用稳定夜间灯光亮度DN值对分省人均碳排放和单位面积碳排放进行时空模拟;最后运用人口规模和土地面积对分省碳排放进行估算。估算结果显示:(1)整体来看,2000—2013年年均碳排放模拟值与实际值6.3349×109t较为接近,两个模型的相对误差均在0.5%以内。(2)分年度来看,所有年份的相对误差均在5%以内,2006年分省加总碳排放模拟值与实际碳排放6.2036×109t最为接近,绝对误差和相对误差均较小,两个模型模拟值的相对误差均为0.04%。(3)分省域来看,2000—2013年年均碳排放模拟值与实际碳排放均非常接近,除海南和宁夏外,其余28个省区市的相对误差均在1%以内。(4)分年度分省域来看,以2013年为例,40%省份的相对误差在2%以内,70%省份的相对误差在5%以内。从整体、分年度、分省域、分年度分省域的估算结果来看,基于稳定夜间灯光数据的中国分省碳排放时空模拟效果良好。因此,运用卫星夜间灯光数据可以较为准确地对中国分省碳排放进行估算和预测,为卫星遥感影像数据服务分省碳排放监测和评估提供一种补充性参考。     

Carbon dioxide emissions from cities in China based on high resolution emission gridded data

Based on the China high resolution emission gridded data (1 km spatial resolution), this article is aimed to create a Chinese city carbon dioxide (CO₂) emission data set using consolidated data sources as well as normalized and standardized data processing methods. Standard methods were used to calculate city CO₂ emissions, including scope 1 and scope 2. Cities with higher CO₂ emissions are mostly in north, northeast, and eastern coastal areas. Cities with lower CO₂ emissions are in the western region. Cites with higher CO₂ emissions are clustered in the Jing-Jin-Ji Region (such as Beijing, Tianjin, and Tangshan), and the Yangtze River Delta region (such as Shanghai and Suzhou). The city per capita CO₂ emission is larger in the north than the south. There are obvious aggregations of cities with high per capita CO₂ emission in the north. Four cities among the top 10 per capita emissions (Erdos, Wuhai, Shizuishan, and Yinchuan) cluster in the main coal production areas of northern China. This indicates the significant impact of coal resources endowment on city industry and CO₂ emissions. The majority (77%) of cities have annual CO₂ emissions below 50 million tons. The mean annual emission, among all cities, is 37 million tons. Emissions from service-based cities, which include the smallest number of cities, are the highest. Industrial cities are the largest category and the emission distribution from these cities is close to the normal distribution. Emissions and degree of dispersion, in the other cities (excluding industrial cities and service-based cities), are in the lowest level. Per capita CO₂ emissions in these cities are generally below 20 t/person (89%) with a mean value of 11 t/person. The distribution interval of per capita CO₂ emission within industrial cities is the largest among the three city categories. This indicates greater differences among per capita CO₂ emissions of industrial cities. The distribution interval of per capita CO₂ emission of other cities is the lowest, indicating smaller differences of per capita CO₂ emissions among this city category. Three policy suggestions are proposed: first, city CO₂ emission inventory data in China should be increased, especially for prefecture level cities. Second, city responsibility for emission reduction, and partitioning the national goal should be established, using a bottom-up approach based on specific CO₂ emission levels and potential for emission reductions in each city. Third, comparative and benchmarking research on city CO₂ emissions should be conducted, and a Top Runner system of city CO₂ emission reduction should be established.     

Does Including Soil Moisture Observations Improve Operational Streamflow Forecasts in Snow‐Dominated Watersheds?

Changing climate and growing water demand are increasing the need for robust streamflow forecasts. Historically, operational streamflow forecasts made by the Natural Resources Conservation Service have relied on precipitation and snow water equivalent observations from Snow Telemetry (SNOTEL) sites. We investigate whether also including SNOTEL soil moisture observations improve April‐July streamflow volume forecast accuracy at 0, 1, 2, and 3‐month lead times at 12 watersheds in Utah and California. We found statistically significant improvement in 0 and 3‐month lead time accuracy in 8 of 12 watersheds and 10 of 12 watersheds for 1 and 2‐month lead times. Surprisingly, these improvements were insensitive to soil moisture metrics derived from soil physical properties. Forecasts were made with volumetric water content (VWC) averaged from October 1 to the forecast date. By including VWC at the 0‐month lead time the forecasts explained 7.3% more variability and increased the streamflow volume accuracy by 8.4% on average compared to standard forecasts that already explained an average 77% of the variability. At 1 to 3‐month lead times, the inclusion of soil moisture explained 12.3‐26.3% more variability than the standard forecast on average. Our findings indicate including soil moisture observations increased statistical streamflow forecast accuracy and thus, could potentially improve water supply reliability in regions affected by changing snowpacks.     

Chlorinated solvents in a petrochemical wastewater treatment plant: an assessment of their removal using self-organising maps

The self-organising map approach was used to assess the efficiency of chlorinated solvent removal from petrochemical wastewater in a refinery wastewater treatment plant. Chlorinated solvents and inorganic anions (11 variables) were determined in 72 wastewater samples, collected from three different purification streams. The classification of variables identified technical solvents, brine from oil desalting and runoff sulphates as pollution sources in the refinery, affecting the quality of wastewater treatment plant influent. The classification of samples revealed the formation of five clusters: the first three clusters contained samples collected from the drainage water, process water and oiled rainwater treatment streams. The fourth cluster consisted mainly of samples collected after biological treatment, and the fifth one of samples collected after an unusual event. SOM analysis showed that the biological treatment step significantly reduced concentrations of chlorinated solvents in wastewater.     

Effects of Urban Spatial Structure,Sociodemographics, and Climate on Residential Water Consumption in Hillsboro,Oregon1

House-Peters, Lily, Bethany Pratt, and Heejun Chang, 2010. Effects of Urban Spatial Structure, Sociodemographics, and Climate on Residential Water Consumption in Hillsboro, Oregon. Journal of the American Water Resources Association (JAWRA) 46(3):461-472. DOI: 10.1111/j.1752-1688.2009.00415.x Abstract: In the Portland metropolitan area, suburban growth in cities such as Hillsboro is projected to increase as people seek affordable housing near a burgeoning metropolis. The most significant determinants for increases in water demand are population growth, climate change, and the type of urban development that occurs. This study analyzes the spatial patterns of single family residential (SFR) water consumption in Hillsboro, Oregon, at the census block scale. The following research questions are addressed: (1) What are the significant determinants of SFR water consumption in Hillsboro, Oregon? (2) Is SFR water demand sensitive to drought conditions and interannual climate variation? (3) To what magnitude do particular census blocks react to drought conditions and interannual climate variation? Using ordinary least squares multiple regression and spatial regression methods, we found that base use, representing indoor water use, is dependent on household size and that seasonal use, representing external water use is dependent on both education level and the size of the property’s outdoor space. Spatial analysis techniques determined that although the water demand of the study area as a whole is not sensitive to drought conditions, certain individual census blocks do respond with a higher magnitude of water use. The most climate-sensitive census blocks tend to contain newer and larger homes, and have higher property values and more affluent and well-educated residents.     

中国环境效率评价及其影响因素实证研究

环境效率是实际污染排放和潜在污染排放的一种度量。本文运用包含污染排放的环境DEA模型,测算了1998-2007年中国省际环境效率,检验了其收敛情况。结果显示,全国环境效率总体水平较低,省际、区域间差距较大,表明现阶段实行地区间减排合作、推动环保技术在区域间扩散的现实必要性;分别从20032、005年开始,省际、区域环境效率差距逐渐缩小,存在一定的收敛趋势;同时,本文采用Tobit模型分析了影响环境效率因素,研究发现人均GDP对提高环境效率具有积极影响,而工业比重上升、财政分权度的提高以及贸易自由化对环境效率具有显著的负面影响。最后,基于实证研究的结果,就减少地区污染排放、提高我国环境效率给出了相关政策建议。     

上海霾气候数据序列重建及其时空特征

利用上海11个气象站点1960～2008年日均相对湿度、能见度以及天气现象资料,重建了上海近50a霾气候数据序列,并从时间和空间两个方面分析了上海霾日数的气候特征和变化规律。结果表明,上海霾气候数据序列重建值与报表记录值之间变化形态存在着较好的一致性,重建值较记录值偏高。1960～2008年,上海霾日数以9.7d/10a的线性趋势显著增加,2002年以后霾日数总体上呈减少趋势。上海多年平均霾日数以冬季最多而夏季最少。近50a,上海霾日数呈现出西南部最多-市区较多-东北和东南部最少的空间分布,霾日数的空间变化趋势则表现为西南部增加较多而东部增加较少。1981～2008年,上海霾日数在西部和南部都增加,东部则减少。     

Substituting missing data in compositional analysis

Multivariate analysis of environmental data sets requires the absence of missing values or their substitution by small values. However, if the data is transformed logarithmically prior to the analysis, this solution cannot be applied because the logarithm of a small value might become an outlier. Several methods for substituting the missing values can be found in the literature although none of them guarantees that no distortion of the structure of the data set is produced. We propose a method for the assessment of these distortions which can be used for deciding whether to retain or not the samples or variables containing missing values and for the investigation of the performance of different substitution techniques. The method analyzes the structure of the distances among samples using Mantel tests. We present an application of the method to PCDD/F data measured in samples of terrestrial moss as part of a biomonitoring study.     

Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning

Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ∼87.0%, ∼71.4%, ∼87.5%, and 100% for the four groups; Control (non-amended system), low dose (amended at 10 μg U L⁻¹), medium dose (amended at 100 μg U L⁻¹), and high dose (500 μg U L⁻¹). The SVM model achieved an overall cross-validated classification accuracy of ∼87% in contrast to ∼59% for the best linear classifier.     

An Empirical Study on the Environmental Kuznets Curve for China’s Carbon Emissions:Based on Provincial Panel Data

Based on the Environmental Kuznets Curve theory,the authors choose provincial panel data of China in 1990 2007 and adopt panel unit root and co-integration testing method to study whether there is Environmental Kuznets Curve for China’s carbon emissions.The research results show that:carbon emissions per capita of the eastern region and the central region of China fit into Environmental Kuznets Curve,but that of the western region does not.On this basis,the authors carry out scenario analysis on the occurrence time of the inflection point of carbon emissions per capita of different regions,and describe a specific time path.