Spatial and Seasonal Response of Municipal Water Use to Weather across the Contiguous U.S.

Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R² ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

A critical overview of driver recording tools

Introduction: Technological advancements during recent decades have led to the development of a wide array of tools and methods in order to record driving behavior and measure various aspects of driving performance. The aim of the present study is to present and comparatively assess the various driver recording tools that researchers have at their disposal. Method: In order to achieve this aim, a multitude of published studies from the international literature have been examined based on the driver recording methodologies that have been implemented. An examination of more traditional survey methods (questionnaires, police reports, and direct observer methods) is initially conducted, followed by investigating issues pertinent to the use of driving simulators. Afterwards, an extensive section is provided for naturalistic driving data tools, including the utilization of on-board diagnostics (OBD) and in-vehicle data recorders (IVDRs). Lastly, in-depth incident analysis and the exploitation of smartphone data are discussed. Results: A critical synthesis of the results is conducted, providing the advantages and disadvantages of utilizing each tool and including additional knowledge regarding ease of experimental implementation, data handling issues, impacts on subsequent analyses, as well as the respective cost parameters. Conclusions: New technologies provide undeniably powerful tools that allow for seamless data handling, storage, and analysis, such as smartphones and in-vehicle data recorders. However, this sometimes comes at considerable costs (which may or may not pay off at a later stage), while legacy driver recording methods still have their own niches to fill in research. Practical Applications: The present research supports researchers when designing driver behavior monitoring studies. The present work enables better scheduling and pacing of research activities, but can also provide insights for the distribution of research funds.     

探究环境监测数据在环境执法中的应用

伴随经济发展的迅速,人们对环境越来越重视,国家也制定了相应的环境执法与保护措施,保障环境质量。在环境执法的过程中,必须严格依照环境监测的数据,从而保障信息的准确性,使环境执法策略的开展能够顺应时代发展,符合目前发展的现状。因此,环境执法中环境监测数据占据重要的位置。基于此,本文分析了环境执法中环境监测数据的应用,笔者根据自身经验提出相应的建议。     

基于大数据技术构建生态环境信息化体系及其重点应用研究

本文首先分析了生态环境信息化体系的主要构成要素,其后基于大数据技术的生态环境信息化体系重点领域应用进行了深入研究。     

基于超效率DEA模型的三峡库区生态效率评价及空间演化格局分析

本文基于2010—2017年的统计数据,首先采用超效率DEA模型对三峡库区26个区县的生态效率进行测算,然后运用空间自相关分析方法对三峡库区生态效率的演化格局进行了实证分析,探索三峡库区生态效率的时空动态演变特征。研究表明:2010—2017年三峡库区生态效率平均水平处于0.5601～1.1920,整体呈现波动性变化趋势,生态效率在一定程度上有所改善,但是整体水平仍然较低;从区域层面看,各个区县间生态效率水平不平衡,空间分布上呈现"西高东低"的非均衡性特征。局部空间自相关分析表明,三峡库区2010—2017年集聚性呈逐渐减弱态势,空间异质性逐渐增加,整体的生态效率差异变大。最后依据实证研究分析结果,本文对如何提升三峡库区生态效率提出了相应的政策建议。     

中国服务业碳生产率的空间收敛性研究

在经济服务化与低碳化的双重背景下,研究中国服务业碳生产率的演变轨迹,区域差异及空间收敛特征,对于推动中国服务业高质量发展具有重要的意义。采用2004—2016年中国30个省(区、市)的面板数据,对服务业碳生产率进行测度,并对其演变轨迹与区域差异进行分析,在此基础上,系统考察中国服务业碳生产率的空间收敛性。研究表明:①中国服务业碳生产率在整体上呈逐年增长态势,且呈现从东到西逐次递减的格局。②中国服务业碳生产率存在正向空间自相关关系,并且空间自相关程度表现出波动上升趋势。③全国与西部服务业碳生产率均不存在σ收敛,即服务业碳生产率的地区差异并未随着时间的推移而缩小;东、中部服务业碳生产率则在整体上呈现σ收敛特征。全国以及东、中、西部服务业碳生产率均存在绝对β收敛和条件β收敛,即服务业碳生产率落后地区对发达地区存在"追赶效应",各地区服务业碳生产率最终向自身的稳态水平趋同;空间效应加快了全国与东部服务业碳生产率的β收敛速度。④人均服务业增加值增长速度、部门结构以及能源消费结构对服务业碳生产率具有显著的负向效应,人力资本则对服务业碳生产率产生了显著的正向影响。据此,本文的政策启示如下:①重视服务业碳排放问题,构建服务业低碳绩效评估体系。②探索建立定期会商制度,加强服务业低碳技术的跨区域交流合作。③完善基础设施,促进要素空间互动和优化重组。④调整服务业能源结构与部门结构,推进人力资本积累和服务业稳增长。     

海洋碳汇渔业绿色发展空间外溢效应评价研究

海洋碳汇渔业绿色发展空间关联性及其外溢效应对于海水养殖业的有效协调和区域海洋环境的有效保护具有重要意义,科学估算沿海各省(自治区)海水养殖渔业碳汇量并探讨其空间相关性特征是制定差异化渔业碳汇发展政策的重要基础。根据2006—2016年中国大陆沿海9个省(自治区)的碳汇渔业资源清查数据,在检验和比较省域空间渔业碳汇总量相关性特征的基础上,运用空间计量模型分析了渔业碳汇的外溢效应及其影响因素。结果表明:①中国海水养殖渔业碳汇量整体上呈现上升趋势,但各省渔业碳汇量也存在明显差异。②研究期内的Moran's I指数整体呈现为"V"型的波动变化特征,渔业碳汇在省域空间分布上的差异性并不是随机的,而是具备显著的空间相关性。③海水养殖渔业碳汇存在明显的空间外溢效应,通过随机效应的杜宾模型分解后得出渔业产值、劳动力投入的直接效应为正,而渔业受灾面积和科研项目经费投入的直接效应为负;从间接效应来看,渔业产值在各省域间存在竞争与依存关系,海水养殖业劳动力投入和渔业技术推广的项目经费投入在各省域间存在互补关系。因此,中国沿海各省份在发挥海洋水产养殖业生态功能时,应当考虑省域区位因素,合理制定兼具差异化和协调性的海洋碳汇渔业发展政策。     

Spatial Patterns and Rankings of Contaminant Concentrations in Herring Gull Eggs from 15 Sites in the Great Lakes and Connecting Channels, 1998–2002

Mean values of eight contaminants in Herring Gull (Larus argentatus) eggs were calculated for 15 Great Lakes sites for the 5 year period 1998–2002. The sites were ranked according to the concentrations of each of seven compounds relative to fish flesh criteria for the protection of piscivorous wildlife, and a single overall rank of contamination was calculated for each site. Based on this weighted ranking scheme, we found that sum PCBs, dioxin and DDE contributed the most (60.2, 30.5% and 8.5%, respectively) to the overall rankings. The weighted ranking scheme showed that eggs from Channel-Shelter Island (Saginaw Bay, Lake Huron), Strachan Island (St. Lawrence River) and Gull Island (northern Lake Michigan) ranked as the three most contaminated sites, while Agawa Rocks (eastern Lake Superior), Chantry Island (southern Lake Huron) and Port Colborne (eastern Lake Erie) ranked as the three least contaminated sites. Two of the three most contaminated sites are Areas of Concern; none of the three least contaminated sites are Areas of Concern.     

Spatial Characterization and Prioritization of Heavy Metal Contaminated Soil-Water Resources in Peri-Urban Areas of National Capital Territory (NCT), Delhi

Due to rapid industrialization and urbanization during last two decades, contamination of soils by heavy metals is on an increase globally. Lands under peri-urban agriculture are the worst affected. In NCT, Delhi about 14.4% of land area is chemically degraded. In order to take care of this problem, recently the Supreme Court of India ordered to shift various non-confirming (about 39,000 units) industries to regions outside NCT, Delhi. However in spite of this, there have been several reports and parliamentary debates on the phyto-toxicity and extensive accumulation of heavy metals in the region. Literature review revealed that the basis of these debates is a few studies on some point locations in/around Delhi. It was further observed that information on the distribution and extent of heavy metal pollution problem in the region was completely missing. The present study was thus basically aimed at assessing the spatial distribution/extent and type of heavy metal pollution in the study area, for enabling future designing of appropriate site-specific management measures by the decision makers.For this, detailed spatial information on bio-available heavy metal concentrations in the soils and surface/sub-surface waters of NCT (Delhi) was generated through actual soil/water surveys, standard laboratory methods and GIS techniques. The study showed that concentration of all micronutrients (viz. Zn: 0.05–0.18 ppm; Cu: in traces; Fe: 0–0.5 ppm; and Mn: 0–1.2 ppm) and most heavy metals (viz. Ni: 0–0.7 ppm; Pb: 0–0.15 ppm and Cd: in traces) in the surface/sub-surface irrigation waters were well within permissible limits. However Cr concentrations in irrigation waters of Alipur and Shahdara blocks were far above their maximum permissible limit of 1 ppm. It was further observed that Ni and Cr concentrations in the drinking waters of almost entire test area were far above maximum permissible levels of 0.02 and 0.01 ppm, respectively. Bio-available concentrations of several heavy metals (viz. Pb: 0.1–2 ppm; Cd: traces; Ni: 0.05–2 ppm and Cr: 0–0.4 ppm) in the study area soils were also observed to be well within the maximum permissible limits. However there were point Cu contaminations (5–10 ppm) in the sewage-sludge amended soils of vegetable growing areas near south Shahdara block. This was attributed to increased Cu availability due to oxidized acidic conditions generated by over-irrigation of agricultural lands. Available Mn concentrations in Kanjhawala, western Najafgarh and Alipur soils were also observed to be above maximum permissible limit of 10 ppm. This was observed to be mainly due to the geology (i.e. presence of Mn rich sedimentary rocks) and prevalence of reduced acidic conditions, due to paddy cultivation, in these areas. It was further observed that there is acute zinc (Zn) deficiency (< 0.6 ppm) in paddy growing soils of north Kanjhawala, Alipur and some parts of Najafgarh and Shahdara blocks due to extensive leaching of available Zn fractions to lower soil horizons. Similar available Zn deficiencies in high pH (8.5) soils of areas around Bamnoli village in E-Najafgarh block were also observed.