面对税收政策差异如何进行跨地区施工纳税管理与策划

建筑企业为了寻求企业发展,都在不断地进行跨地区作业,各地税收政策直接影响了施工企业的纳税成本。为此,建筑企业应加强内部税务管理、进行税收策划、降低纳税成本、规避税务风险、增强企业竞争能力。本文主要是以企业价值最大化为目标,根据施工企业的特点,利用施工地点税收征管差异,合理、合法避税,以达到降低企业税务风险目的。     

我国轻型汽油车污染物排放劣化系数分析

对我国轻型汽油车Ⅴ型试验结果进行了统计和分析,得出了2001年后我国轻型汽油车型式核准各污染物成分实测劣化系数的综合水平。     

论我国房价收入比的不合理性及解决思路

房价过高是造成房价收入比不合理的主要原因，过高过滥的税费是房价过高的主要根源。通过剖析我国的房产税费现状，参照国外经验，提出了若干降低房价收入比的思路。     

Driving cycles that reproduce driving patterns,energy consumptions and tailpipe emissions

This study presents the Energy Based Micro-trip (EBMT) method, which is a new method to construct driving cycles that represent local driving patterns and reproduce the real energy consumption and tailpipe emissions from vehicles in a given region. It uses data of specific energy consumption, speed, and percentage of idling time as criteria of acceptable representativeness. To study the performance of the EBMT, we used a database of speed, fuel consumption, and tailpipe emissions (CO₂, CO, and NO_x), which was obtained monitoring at 1 Hz, the operation of 15 heavy-duty vehicles when they operated within different traffic conditions, during eight months. The speed vs. time data contained in this database defined the local driving pattern, which was described by 19 characteristic parameters (CPs). Using this database, we ran the EBMT and described the resulting driving cycle by 19 characteristics parameters (CPs*). The relative differences between CPs and CPs* quantified how close the obtained driving cycle represented the driving pattern. To observe tendencies of our results, we repeated the process 1000 times and reported the average relative difference (ARD) and the interquartile range (IQR) of those differences for each CP.. We repeated the process for the case of a traditional Micro-trip method and compared to previous results. The driving cycles constructed by the EBMT method showed the lowest values of ARDs and IQRs, meaning that it produces driving cycles with the highest representativeness of the driving patterns, and the best reproduction of energy consumption, and tailpipe emissions.     

Does a carbon tax affect the feasibility of Arctic shipping?

The Arctic route has huge potential for shipping between Europe and Northeast Asia with significant savings in transit time and distance. However, GHG emissions from shipping would harm the environment of Arctic area. Potential Market Based Measures of GHG emission reduction (such as carbon tax) are under consideration but they may affect the economic viability of Northern Sea Route (NSR) for containerships. This paper investigates the economic viability of NSR against Suez Canal Route (SCR) under 2 proposed carbon tax schemes (fixed vs. progressive). Three different fuel oil types (Heavy Fuel Oil, Light Fuel Oil, Liquified Natural Gas) are used as main bunker fuel for the calculation of economic feasibility. Our result reveals that when there is no carbon tax on NSR nor SCR, or both routes are under a carbon tax scheme, no matter fixed or progressive, NSR is more economically viable, regardless of fuel type choice. When only NSR is under a carbon tax scheme, the viability depends on specific carbon tax scheme and fuel choice, but for the majority of containership sizes, NSR has lower unit cost. The result also suggests that for a given route, a progressive scheme in preferable than a fixed one and LNG would be an appealing fuel with lower unit cost.     

Atmospheric dispersion modeling near a roadway under calm meteorological conditions

Atmospheric pollutant dispersion near sources is typically simulated by Gaussian models because of their efficient compromise between reasonable accuracy and manageable computational time. However, the standard Gaussian dispersion formula applies downwind of a source under advective conditions with a well-defined wind direction and cannot calculate air pollutant concentrations under calm conditions with fluctuating wind direction and/or upwind of the emission source. Attempts have been made to address atmospheric dispersion under such conditions. This work evaluates the performance of standard and modified Gaussian plume models using measurements of NO₂, PM₁₀, PM_2.5, five inorganic ions and seven metals conducted near a freeway in Grenoble, France, during 11–27 September 2011. The formulation for calm conditions significantly improves model performance. However, it appears that atmospheric dispersion due to vehicle-induced turbulence is still underestimated. Furthermore, model performance is poor for particulate species unless road dust resuspension by traffic is explicitly taken into account.     

Does emission control area policy reduce sulfur dioxides concentration in Shanghai?

As an important measure to abate ship-source air emissions, the establishment of Emission Control Area (ECA) has been adopted not only at international level, but also at national and regional level. However, there exists a research gap of employing econometric models to enrich the ECA policy evaluation research by testing the effectiveness of an ECA policy based on the empirical data. This paper focuses on the effectiveness of the ECA policy in shanghai port by adopting regression discontinuity (RD) approach. The RD design is considered as a wonderful substitution for the randomized control trial, which usually serves as a conventional and effective tool to address endogeneity. The causal effect of the ECA policy on the SO₂ concentration reduction can be detected by the RD approach. According to the estimated results, there is a discontinuity around the ECA policy cutoff point, and it is indicated that the SO₂ concentration in Shanghai decreased by at least 0.229 μg/m³ daily on average due to the implementation of the ECA policy. The positive role that the ECA policy plays in reducing SO₂ concentration in Shanghai is well demonstrated. This paper also puts forward an agenda for the future studies in the domain of the ECA policy evaluation.     

Measuring transport related CO2 emissions induced by online and brick-and-mortar retailing

We develop a method for empirically measuring the difference in transport related carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their transport CO₂ footprints by 84% when buying standard consumer electronics products.     

Second-order models and traffic data from mobile sensors

Mobile sensing enabled by GPS or smart phones has become an increasingly important source of traffic data. For sufficient coverage of the traffic stream, it is important to maintain a reasonable penetration rate of probe vehicles. From the standpoint of capturing higher-order traffic quantities such as acceleration/deceleration, emission and fuel consumption rates, it is desirable to examine the impact on the estimation accuracy of sampling frequency on vehicle position. Of the two issues raised above, the latter is rarely studied in the literature. This paper addresses the impact of both sampling frequency and penetration rate on mobile sensing of highway traffic. To capture inhomogeneous driving conditions and deviation of traffic from the equilibrium state, we employ the second-order phase transition model (PTM). Several data fusion schemes that incorporate vehicle trajectory data into the PTM are proposed. And, a case study of the NGSIM dataset is presented which shows the estimation results of various Eulerian and Lagrangian traffic quantities. The findings show that while first-order traffic quantities can be accurately estimated even with a low sampling frequency, higher-order traffic quantities, such as acceleration, deviation, and emission rate, tend to be misinterpreted due to insufficiently sampled vehicle locations. We also show that a correction factor approach has the potential to reduce the sensing error arising from low sampling frequency and penetration rate, making the estimation of higher-order quantities more robust against insufficient data coverage of the highway traffic.     

Modeling the impacts of alternative emission trading schemes on international shipping

Various market-based measures have been proposed to reduce CO₂ emissions from international shipping. One promising mechanism under consideration is the Emission Trading Scheme (ETS). This study analyzes and benchmarks the economic implications of two alternative ETS mechanisms, namely, an open ETS compared to a Maritime only ETS (METS). The analytical solutions and model calibration results allow us to quantify the impacts of alternative ETS schemes on the container shipping sector and the dry bulk shipping sector. It is found that an ETS, whether open or maritime only, will decrease shipping speed, carrier outputs and fuel consumption for both the container and dry bulk sectors, even in the presence of a “wind-fall” profit to shipping companies. Under an open ETS, the dry bulk sector will suffer from a higher proportional reduction in output than the container sector, and will thus sell more emission permits or purchase fewer permits. Under an METS, container carriers will buy emission permits from the dry bulk side. In addition, under an METS the degree of competition within one sector will have spill-over effects on the other sector. Specifically, when the sector that sells (buys) permits is more collusive (competitive), the equilibrium permit price will rise. This study provides a framework for identifying the moderating effects of market structure and competition between firms on emission reduction schemes, and emphasizes the importance of understanding the differential impacts of ETS schemes on individual sectors within an industry when considering alternative policies.