基于随机森林算法的长江三角洲地区PM2.5浓度模拟研究

PM_(2.5)影响人们的生活,危害城市居民的健康,因而在大范围、连续空间上精准预测PM_(2.5)的浓度对于降低居民暴露在大气污染环境中的风险意义重大。基于空气中PM_(2.5)浓度对气象因子、社会经济因子和下垫面条件因子的响应关系,利用皮尔逊相关分析、PCA分析和随机森林模型RF构建了长江三角洲地区浓度的预测模型。研究发现:(1)PM_(2.5)浓度大小分布与夜间灯光指数NLI、国内生产总值GDP、降雨量PRE、温度TEP、相对湿度RH、植被指数EVI以及土地利用覆被LUCC呈显著相关(P0.05),其中NLI和GDP与PM_(2.5)浓度呈正相关,PRE、TEP、RH与PM_(2.5)浓度呈负相关。(2)主成分数量为4时,方差累积贡献率达到86.7%,PRE、RH、GDP、NLI和EVI是影响长三角地区PM_(2.5)浓度空间变化的最重要的5个因子。(3)PCA-RF模型对于PM_(2.5)浓度的预测具有较好的表现且在长三角中西部的城市预测效果好于东南部沿海城市。相对于逐步回归SR模型,PCA-RF模型验证数据集上的均方根误差RMSE降低12.7%,决定系数R2提高12.1%,平均绝对误差MAE降低8.3%。     

Predicting non-carcinogenic hazard quotients of heavy metals in pepper (Capsicum annum L.) utilizing electromagnetic waves

• There was significant absorption of heavy metals by the pepper in contaminated soils. • The target hazard quotient (THQ) indices followed the order of Pb>Zn>>Cd » Ni. • Relationships exist between contaminated plants and electromagnetic wave. • PCA and random search can select the main spectra and predict THQ for each element. Given the tendency of heavy metals to accumulate in soil and plants, the purpose of this study was to determine the contamination levels of Cd, Ni, Pb, and Zn on peppers (leaves and fruit) grown in contaminated soils in industrial centers. For this purpose, we measured the uptake of the four heavy metals by peppers grown in the heavy metal contaminated soils throughout the four growth stages: two-leaf, growth, flowering, and fruiting, and calculated various vegetation indices to evaluate the heavy metal contamination potentials. Electromagnetic waves were also applied for analyzing the responses of the target plants to various heavy metals. Based on the relevant spectral bands identified by principal component analysis (PCA) and random search methods, a regression method was then employed to determine the most optimal spectral bands for estimating the target hazard quotient (THQ). The THQ was found to be the highest in the plants contaminated by Pb (THQ= 62) and Zn (THQ= 5.07). The results of PCA and random search indicated that the spectra at the bands of b₅₇₀, b₆₅₀, and b₇₆₀ for Pb, b₄₀₀ and b₁₀₃₀ for Ni, b₄₀₀ and b₈₈₀ for Cd, and b₅₆₀, b₉₁₀, and b₁₀₅₀ for Zn were the most optimal spectra for assessing THQ. Therefore, in future studies, instead of examining the amount of heavy metals in plants by chemical analysis in the laboratory, the responses of the plants to the electromagnetic waves in the identified bands can be readily investigated in the field based on the established correlations.     

Measuring direct and indirect treatment effects using safety performance intervention functions

Recent traffic safety research has advocated the use of the Full Bayes (FB) approach to conduct controlled before-after safety evaluations. The FB approach was shown to offer both methodological and data advantages. However, there is still a lack of complete understanding of the role that the model parameters play in the formulation of treatment effectiveness. This paper offers a novel approach to compute components related to direct and indirect treatment effects under a linear intervention model for the Safety Performance Function (SPF). The isolation of a component corresponding to the direct treatment effects enables the analyst to assess the effectiveness of the countermeasures apart from local (site-related) environmental factors. Two case studies are used to demonstrate the approach. The first case study is based on the results published from a previous safety evaluation in Iowa and the second uses a new data set from British Columbia based on the Insurance Corporation of British Columbia Road Improvement Program. The various direct and indirect components have yielded valuable insight into the effects of the model parameters on treatment impacts. Moreover, the calculation of the treatment effectiveness indices have been simplified by providing straightforward equations in terms of model parameters for the computation of their components without resorting to additional algorithms. More importantly, the results can have a significant impact on the economic evaluation of safety programs and countermeasures by allowing the calculation of collision modification factors (CMFs) that vary with time.     

Addressing onsite sampling in recreation site choice models

Independent experts and politicians have criticized statistical analyses of recreation behavior, which rely upon onsite samples due to their potential for biased inference. The use of onsite sampling usually reflects data or budgetary constraints, but can lead to two primary forms of bias in site choice models. First, the strategy entails sampling site choices rather than sampling individuals—a form of bias called endogenous stratification. Under these conditions, sample choices may not reflect the site choices of the true population. Second, exogenous attributes of the individuals sampled onsite may differ from the attributes of individuals in the population—the most common form in recreation demand is avidity bias. We propose addressing these biases by combining two the existing methods: Weighted Exogenous Stratification Maximum Likelihood estimation and propensity score estimation. We use the National Marine Fisheries Service's Marine Recreational Fishing Statistics Survey to illustrate methods of bias reduction, employing both simulated and empirical applications. We find that propensity score based weights can significantly reduce bias in estimation. Our results indicate that failure to account for these biases can overstate anglers' willingness to pay for improvements in fishing catch, but weighted models exhibit higher variance of parameter estimates and willingness to pay.     

Application of a Random Forest algorithm to predict spatial distribution of the potential yield of Ruditapes philippinarum in the Venice lagoon, Italy

We present a modelling framework that combines machine learning techniques and Geographic Information Systems to support the management of an important aquaculture species, Manila clam (Ruditapes philippinarum). We use the Venice lagoon (Italy), the first site in Europe for the production of R. philippinarum, to illustrate the potential of this modelling approach. To investigate the relationship between the yield of R. philippinarum and a set of environmental factors, we used a Random Forest (RF) algorithm. The RF model was tuned with a large data set (n = 1698) and validated by an independent data set (n = 841). Overall, the model provided good predictions of site-specific yields and the analysis of marginal effect of predictors showed substantial agreement among the modelled responses and available ecological knowledge for R. philippinarum. The most influent environmental factors for yield estimation were percentage of sand in the sediment, salinity, and water depth. Our results agree with findings from other North Adriatic lagoons. The application of the fitted RF model to continuous maps of all the environmental variables allowed estimates of the potential yield for the whole basin. Such a spatial representation enabled site-specific estimates of yield in different farming areas within the lagoon. We present a possible management application of our model by estimating the potential yield under the current farming distribution and comparing it to a proposed re-organization of the farming areas. Our analysis suggests a reduction of total yield is likely to result from the proposed re-organization.     

基于随机森林的开封市重型柴油车NOx排放总量估算模型

近年来,在相关法律文件的推动下,监控平台技术得到发展与应用,有助于准确、实时获取海量实车行驶和排放数据,为建立机动车排放清单提供了重要数据基础.基于此背景,本文依托河南开封重型柴油车远程监控平台排放大数据,考虑了中观尺度上的活动因子分布特征及活动因子的影响权重,利用随机森林回归模型对重型柴油车污染物排放量预测方法进行研究.结果表明：①开封市重型柴油车行驶工况呈Ω型分布,而且随着发动机排量的增大,工况范围有逐渐缩小的趋势,且重型柴油车有20%的时间行驶在怠速区域和至少40%的时间行驶在中低转速区域.②在样本车中,在活动因子影响程度占比排序方面,有超过80%的柴油车将车速排在首位,其次分别是SCR床温、废气流量、发动机转速、燃料流量.③NO_x排放总量估算模型计算的6种典型排量下的重型柴油车NO_x排放总量与实际排放总量相比,误差不超过25%,能够满足实际需求.     

Measuring eddy covariance fluxes of ozone with a slow-response analyser

Ozone (O₃) fluxes above a temperate mountain grassland were measured by means of the eddy covariance (EC) method using a slow-response O₃ analyser. The resultant flux loss was corrected for by a series of transfer functions which model the various sources of high- and, in particular, low-pass filtering. The resulting correction factors varied on average between 1.7 and 3.5 during night and daytime, respectively. A cospectral analysis confirmed the accuracy of this approach. O₃ fluxes were characterised by a comparatively large random uncertainty, which during daytime typically amounted to 60%. EC O₃ fluxes were compared against O₃ flux measurements made concurrently with the flux-gradient (FG) method. The two methods generally agreed well, except for a period between sunrise and early afternoon, when the FG method was suspected of being affected by the presence of photochemical sources/sinks. O₃ flux magnitudes and deposition velocities determined with the EC method compared nicely with the available literature from grassland studies. We conclude that our understanding of the causes and consequences of various sources of flux loss (associated with any EC system) has sufficiently matured so that also less-than-ideal instrumentation may be used in EC flux applications, albeit at the cost of relatively large empirical corrections.     

Dissecting the tragedy: A spatial model of behavior in the commons

Much of the discussion of the tragedy of the commons focuses on aggregate impacts, often in data-poor developing country settings. Few non-experimental empirical studies shed light on contextual circumstances driving the extent of rent dissipation and overexploitation. We utilize a high-resolution data set to estimate a behavioral model of fishermen's spatial choices. A unique policy setting allows us to measure the degree to which individual fishermen's choices appear aimed at mitigating the tragedy of the commons in a small numbers setting. We find evidence of partial mitigation in excess of what we would expect under pure self-interest but short of what would occur under group-maximizing behavior. We also examine how contextual factors in the fishery shape the degree of cooperation within the fishing season and find evidence that competition for the common pool resource distorts fishermen's implicit cost of distance—creating a form of “common property inertia”.     

Optimal management of strategic reserves of nonrenewable natural resources

This paper studies the stockpiling issue for an oil importing country that is likely to suffer embargoes, the occurrence and duration of which are uncertain. I show the existence of a decreasing reserves path that the country wants to attain in order to hedge against these disruptions. Allowing the importing country to invest in R&D in order to free itself from the embargo threat, I determine the optimal effort that should be engaged in research. The incentive to develop a backstop is shown to increase with the depletion of the reserves.     

The Relative Efficiency of Ranked Set Sampling in Ordinary Least Squares Regression

Ranked set sampling was developed for situations where measurement cost is expensive compared with unit acquisition. This paper presents results of simulations and theory examining the impact of balanced ranked set sampling on the relative efficiencies of the slope and intercept estimators of an ordinary least squares regression. Perfect ranking of either the independent or the dependent variable is assumed throughout. In contradistinction to most of the published ranked set sampling work, it is demonstrated that balanced ranked set sampling offers at most little improvement in the relative efficiencies of the slope estimator at any sample size.