Analyzing the relationships between travel mode indicators and the number of passenger transport fatalities at the city level

Objective: A number of efforts have been conducted on travel behavior and transport fatalities at the neighborhood or street level, and they have identified different factors such as roadway characteristics, personal indicators, and design indicators related to transport safety. However, only a limited number of studies have considered the relationship between travel behavior indicators and the number of transport fatalities at the city level. Therefore, this study explores this relationship and how to fill the mentioned gap in current knowledge.

Method: A generalized linear model (GLM) estimates the relationships between different travel mode indicators (e.g., length of motorway per inhabitants, number of motorcycles per inhabitant, percentage of daily trips on foot and by bicycle, percentage of daily trips by public transport) and the number of passenger transport fatalities. Because this city-level model is developed using data sets from different cities all over the world, the impacts of gross domestic product (GDP) are also included in the model.

Conclusions: Overall, the results imply that the percentage of daily trips by public transport, the percentage of daily trips on foot and by bicycle, and the GDP per inhabitant have negative relationships with the number of passenger transport fatalities, whereas motorway length and the number of motorcycles have positive relationships with the number of passenger transport fatalities.     

Capital assets and institutional constraints to implementation of greenhouse gas mitigation options in agriculture

Agriculture is one of the major sources of greenhouse gas (GHG) emission. It accounts for approximately 15% of the total global anthropogenic emissions of GHGs. Emissions could be twice as much if indirect emissions are also taken into the consideration. However, unlike other high emitting sectors such as transport or energy, agriculture is potentially a significant carbon “sink”. It has high technical potential as a carbon sink and if tapped, can substantially enhance global sequestration efforts. The technical potential, however, may not translate into actual GHG reduction because of the capital assets and institutional constraints faced by the smallholder farmers in the developing countries. In this paper we develop a capital assets based framework of physical, financial, social, human and natural barriers to agricultural carbon mitigation initiatives and through analysis of current initiatives, we set out policy based options to reduce each of these barriers. Fundamentally, barrier removal will entail designing agricultural carbon mitigation initiatives in collaboration with farmer communities, through strengthening local institutions, understanding land tenure and natural resource cultures, ensuring legitimacy and equity in payments and fast tracking training and information. We provide a framework that simultaneously aids the dual objectives of alleviating poverty in the poor farming communities of developing countries and lowering global greenhouse gas emissions.     

典型污染场地六六六残留特征分析

在历史上受某六六六(HCH)生产企业污染的场地采集土壤样品,分析和研究土壤中HCH的污染水平和污染分布趋势.结果表明,∑HCH值最大为271.72 mg·kg-1,HCH污染主要集中在表层(深度:0～20 cm)、亚表层(深度:20～40 cm)土壤,表层、亚表层土壤中HCH含量远高于深层(深度:40～150 cm)土壤中HCH含量;β-HCH含量最高,远高于其他3种异构体;通过Kriging法插值,画出表层土壤中∑HCH的等值线图,可清晰地看出HCH的分布趋势.本污染场地表层的硬化阻止了雨水的浸润作用,使HCH向下迁移缓慢,HCH含量随深度增加而降低,HCH污染深度较浅.     

博斯腾湖大湖湖区近20年生态健康状况评价

为支撑博斯腾湖未来保护工作,需认知博斯腾湖近20年的生态健康状况,在对博斯腾湖大湖湖区水质状况调查基础上,适当选取系统评价指标,以1991年水质指标为本底值,运用熵权法建立湖泊生态健康评价模型,计算生态系统健康综合指数,并对博斯腾湖大湖湖区近20年来的健康状况进行评价.结果表明,1997、1998及2005年的水体综合状况略好于其他年份,属较好水平;而1992、1993、2003及2008年的水体综合状况则低于其他年份,属较差水平.     

Effects of herbicides on Odonata communities in a rice agroecosystem

The effects of the five herbicides propanil, quinclorac, molinate/propanil, 2,4-D amine, and bensulfuron on Odonata diversity and abundance at the experimental rice plots was investigated. A total of 13 Odonata morphospecies belonging to two families have been identified. Treated plots exhibited higher species richness (up to 12 species) than the control plot (8 species). Ishnura spp. was the most abundant species in the treated plots with a mean density of 194.2 individuals per m², (ind m^?2) followed by Brachythemis contaminata (152 ind m^?2) and Agriocnemis spp. (124 ind m^?2). In the control plots, Agrocnemis spp. was the dominant species (153 ind m^?2) followed by Ishnura spp. (143 ind m^?2) and Neurothemis fluctuans (59 ind m^?2). In the propanil-treated plot, the highest number of odonate species (10 species) was recorded followed by the plots treated with quinclorax and molinate/propanil (9 species). On the 2,4-D amine or bensulfuron-treated plots as well as the control plot, only eight odonate species were recorded. This study revealed that herbicide application had a positive effect on Odonata diversity. This seems reasonable as Odonata are non-target organisms for herbicides. Furthermore, the decomposed weeds resulting from herbicide application would enrich the water with necessary organic matter.     

Using circuit theory to model connectivity in ecology, evolution, and conservation

Connectivity among populations and habitats is important for a wide range of ecological processes. Understanding, preserving, and restoring connectivity in complex landscapes requires connectivity models and metrics that are reliable, efficient, and process based. We introduce a new class of ecological connectivity models based in electrical circuit theory. Although they have been applied in other disciplines, circuit-theoretic connectivity models are new to ecology. They offer distinct advantages over common analytic connectivity models, including a theoretical basis in random walk theory and an ability to evaluate contributions of multiple dispersal pathways. Resistance, current, and voltage calculated across graphs or raster grids can be related to ecological processes (such as individual movement and gene flow) that occur across large population networks or landscapes. Efficient algorithms can quickly solve networks with millions of nodes, or landscapes with millions of raster cells. Here we review basic circuit theory, discuss relationships between circuit and random walk theories, and describe applications in ecology, evolution, and conservation. We provide examples of how circuit models can be used to predict movement patterns and fates of random walkers in complex landscapes and to identify important habitat patches and movement corridors for conservation planning.     

An analysis between financial development,institutions, and the environment: a global view

Financial development is important for the growth of a country which indirectly affects the environment adversely through industrialization. However, in the presence of strong institutions, this adverse effect can be reduced. The main concern of the present study is to estimate the relation between CO₂ and financial development (FD) in the presence of economic institutions as an interactive term. A sample of 101 countries has been selected for econometric analysis for the period from 1995 to 2017. The cross-section dependence test statistics for dependency, CIPS and CADF for panel unit root test, Westerlund test to ascertain the long-run affiliations, and FMOLS to extract the long-run coefficients have been applied. Dumitrescu and Hurlin test is also employed to know about the causal nature of the panel series. The findings show that financial development has a positive relationship with CO₂. However, after inclusion of economic intuitions, the adverse impact of financial development on the environment is reduced. The study also confirms the presence of environmental Kuznets curve in the context of income and financial development. The findings imply that financial development can help to improve environment quality if it is accompanied with strong institutional framework such as assurance of property rights, government integrity, and liberalization in financial sector.

     

Source apportionment of emissions from light-duty gasoline vehicles and other sources in the United States for ozone and particulate matter

Federal Tier 3 motor vehicle emission and fuel sulfur standards have been promulgated in the United States to help attain air quality standards for ozone and PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm). The authors modeled a standard similar to Tier 3 (a hypothetical nationwide implementation of the California Low Emission Vehicle [LEV] III standards) and prior Tier 2 standards for on-road gasoline-fueled light-duty vehicles (gLDVs) to assess incremental air quality benefits in the United States (U.S.) and the relative contributions of gLDVs and other major source categories to ozone and PM_2.5 in 2030. Strengthening Tier 2 to a Tier 3-like (LEV III) standard reduces the summertime monthly mean of daily maximum 8-hr average (MDA8) ozone in the eastern U.S. by up to 1.5 ppb (or 2%) and the maximum MDA8 ozone by up to 3.4 ppb (or 3%). Reducing gasoline sulfur content from 30 to 10 ppm is responsible for up to 0.3 ppb of the improvement in the monthly mean ozone and up to 0.8 ppb of the improvement in maximum ozone. Across four major urban areas—Atlanta, Detroit, Philadelphia, and St. Louis—gLDV contributions range from 5% to 9% and 3% to 6% of the summertime mean MDA8 ozone under Tier 2 and Tier 3, respectively, and from 7% to 11% and 3% to 7% of the maximum MDA8 ozone under Tier 2 and Tier 3, respectively. Monthly mean 24-hr PM_2.5 decreases by up to 0.5 μg/m³ (or 3%) in the eastern U.S. from Tier 2 to Tier 3, with about 0.1 μg/m³ of the reduction due to the lower gasoline sulfur content. At the four urban areas under the Tier 3 program, gLDV emissions contribute 3.4–5.0% and 1.7–2.4% of the winter and summer mean 24-hr PM_2.5, respectively, and 3.8–4.6% and 1.5–2.0% of the mean 24-hr PM_2.5 on days with elevated PM_2.5 in winter and summer, respectively.

Implications: Following U.S. Tier 3 emissions and fuel sulfur standards for gasoline-fueled passenger cars and light trucks, these vehicles are expected to contribute less than 6% of the summertime mean daily maximum 8-hr ozone and less than 7% and 4% of the winter and summer mean 24-hr PM_2.5 in the eastern U.S. in 2030. On days with elevated ozone or PM_2.5 at four major urban areas, these vehicles contribute less than 7% of ozone and less than 5% of PM_2.5, with sources outside North America and U.S. area source emissions constituting some of the main contributors to ozone and PM_2.5, respectively.     

Nitrogen nutrition in cotton and control strategies for greenhouse gas emissions: a review

Cotton (Gossypium hirustum L.) is grown globally as a major source of natural fiber. Nitrogen (N) management is cumbersome in cotton production systems; it has more impacts on yield, maturity, and lint quality of a cotton crop than other primary plant nutrient. Application and production of N fertilizers consume large amounts of energy, and excess application can cause environmental concerns, i.e., nitrate in ground water, and the production of nitrous oxide a highly potent greenhouse gas (GHG) to the atmosphere, which is a global concern. Therefore, improving nitrogen use efficiency (NUE) of cotton plant is critical in this context. Slow-release fertilizers (e.g., polymer-coated urea) have the potential to increase cotton yield and reduce environmental pollution due to more efficient use of nutrients. Limited literature is available on the mitigation of GHG emissions for cotton production. Therefore, this review focuses on the role of N fertilization, in cotton growth and GHG emission management strategies, and will assess, justify, and organize the researchable priorities. Nitrate and ammonium nitrogen are essential nutrients for successful crop production. Ammonia (NH₃) is a central intermediate in plant N metabolism. NH₃ is assimilated in cotton by the mediation of glutamine synthetase, glutamine (z-) oxoglutarate amino-transferase enzyme systems in two steps: the first step requires adenosine triphosphate (ATP) to add NH₃ to glutamate to form glutamine (Gln), and the second step transfers the NH₃ from glutamine (Gln) to α-ketoglutarate to form two glutamates. Once NH₃ has been incorporated into glutamate, it can be transferred to other carbon skeletons by various transaminases to form additional amino acids. The glutamate and glutamine formed can rapidly be used for the synthesis of low-molecular-weight organic N compounds (LMWONCs) such as amides, amino acids, ureides, amines, and peptides that are further synthesized into high-molecular-weight organic N compounds (HMWONCs) such as proteins and nucleic acids.     

Source Apportionment of Carbonaceous Aerosol in New York City by Multiple Linear Regression

A multiple linear regression model was applied to aerosol chemical data from New York City to determine the sources of carbonaceous aerosol. The model used elemental tracers for auto exhaust aerosol (Pb), residual oil combustion (V), resuspended dust (Mn or Fe), and incineration (Cu or Zn). Although relative uncertainties in the source apportionment were greater than 20%, auto exhaust was found to be the main source of organic carbon with lesser contributions from other sources. A substantial fraction of elemental carbon could not be associated with the sources used in the model and was possibly associated with the combustion of diesel and distillate oils. The regression coefficients, which are related to source composition, compared well with actual measured source compositions. Because of the uncertainties it was concluded that source apportionment, especially as it relates to the development of control strategies, should utilize the results of several receptor and source models where possible.