松散煤体表面温度与热源温度对应关系的热红外实验研究

煤层自燃火灾的自燃火源位置的精确探测是防灭火的关键,也是一项世界性难题。近年来,应用红外技术探测煤层隐蔽火源位置已成为一个热点,通过红外技术定性和定量研究松散煤体升温过程中红外辐射特征变化及影响因素,掌握松散煤体内部热量传递规律,对于利用红外成像技术探测井下煤层自燃隐蔽火源具有重要的参考价值。本文采用在松散煤体中加线状热源,保持热源位置不变,改变热源温度,当温度场达到稳定时用红外热像仪采集表面照片的方法,研究松散煤体表面温度与热源温度的对应关系。结果表明热源上方为高温区域,近似椭圆状,随着热源温度的升高,高温区域不断扩大,表面温度t与热源温度T、像素坐标χ满足关系式。     

灰色理论及改良方法对我国垃圾产量的预测

为了给城市环境规划提供理论依据,需要对城市生活垃圾产量进行预测,以期揭示其变化规律和发展趋势。本文对三种预测模型进行对比分析研究,并通过灰色关联度分析,选取与垃圾产量最为相关的5个因素,建立了包括多个因素指标的GM(1,1)预测方程的多元线性回归综合模型。该模型考虑了城市生活垃圾产量的主要影响因素,得到的拟合数据比较理想,预测模型和结果也更为合理可信。     

Herbicide Transport in Goodwater Creek Experimental Watershed: II. Long‐Term Research on Acetochlor,Alachlor, Metolachlor,and Metribuzin1

Lerch, R.N., E.J. Sadler, C. Baffaut, N.R. Kitchen, and K.A. Sudduth, 2010. Herbicide Transport in Goodwater Creek Experimental Watershed: II. Long‐Term Research on Acetochlor, Alachlor, Metolachlor, and Metribuzin. Journal of the American Water Resources Association (JAWRA) 1‐15. DOI: 10.1111/j.1752‐1688.2010.00504.x Abstract: Farmers in the Midwestern United States continue to be reliant on soil‐applied herbicides for weed control in crop production, and herbicide contamination of streams remains an environmental problem. The main objective of this study was to analyze trends in concentration and load of acetochlor, alachlor, metolachlor, and metribuzin in Goodwater Creek Experimental Watershed (GCEW) from 1992 to 2006. A secondary objective was to document the effects of best management practices (BMPs) implemented within GCEW on herbicide transport trends. Median relative herbicide loads, as a percent of applied, were 3.7% for metolachlor, 1.3% for metribuzin, 0.36% for acetochlor, and 0.18% for alachlor. The major decrease in alachlor use and increase in acetochlor use caused shifts in flow‐weighted concentrations that were observed over the entire concentration range. The smaller decrease in metolachlor use led to a consistent decreasing time trend only for the upper end of the concentration distribution. Metribuzin also showed moderate decreases in concentration with time since 1998. Annual loads were generally correlated to second quarter discharge. Despite extensive education efforts in the watershed, conservation BMPs within GCEW were mainly implemented to control erosion, and therefore had no discernable impact on reducing herbicide transport. Overall, changes in herbicide use and second quarter discharge had the greatest effect on trends in flow‐weighted concentration and annual load.     

Investigation on the role of traffic volume in accidents on urban highways

Introduction

Roadway safety is a major concern for the general public and public agencies, as roadway crashes claim many lives and cause substantial economic loss each year. In Iran, a large number of vehicles are involved in road accidents each year, which cause many deaths and extensive property damage; such accidents are among the major causes of death and disability in the country. Method: To reduce roadway accidents, the factors that affect the occurrence and severity of accidents should be scrutinized to prevent or reduce their effect. The method that many researchers have adopted to determine the effective parameters surrounding road accidents in recent years is through statistical modeling of accidents. In this article, the role of different kinds of vehicles in traffic flow are investigated separately in terms of the likelihood of crashes on urban highways, and the vehicles are divided into three groups: passenger cars, heavy vehicles, and light non-passenger car vehicles. Poisson and negative binomial (NB) regression models were applied to model the accidents in this research, which were categorized into two groups: no injury (property damage only) accidents and more severe (injury and fatal) accidents. Results: Ultimately, we conclude that light non-passenger car vehicles (i.e., taxis and motorcycles) play the largest role in the occurrence of crashes on urban highways for both types of accidents.     

基于汶川地震的地震人员伤亡预测模型研究

地震发生以后及时掌握人员伤亡情况对灾后救援具有重要作用,因此,建立地震人员伤亡预测模型是极为重要的。以2008年汶川地震人员伤亡数据及房屋破坏面积数据为基础,运用线性回归分析方法模拟出地震人员伤亡预测模型。该函数模型是以建筑物的易损性为自变量,分别以死亡人数、受伤人数为因变量构建的。同时对回归模型进行误差分析,并参考前人模型可知房屋内人口密度和地震发生时间2个因素对模型有很大影响,进而对回归系数进行调整。最后利用文中模型和其他几种预测模型分别对汶川地震和玉树地震进行验证,并与地震实际伤亡结果进行比较,证明研究的模型的准确性和适用性。     

基于机器学习方法的小麦镉富集因子预测

应用机器学习方法解析区域土壤-小麦系统镉(Cd)富集特征有助于风险决策的准确性和科学性.基于区域调查,构建了Freundlich-type转移方程、随机森林(RF)模型和神经网络(BPNN)模型对小麦Cd富集因子(BCF-Cd)进行预测,验证不同模型的预测精度并评估其不确定性.结果表明,RF(R²=0.583)和BPNN(R²=0.490)模型预测性能均优于Freundlich转移方程(R²=0.410).重复训练结果显示RF和BPNN平均绝对误差(MAE)和均方根误差(RMSE)较为接近,但RF(R²为0.527～0.601)较BPNN(R²为0.432～0.661)模型精度和稳定性更高.特征变量重要性分析显示多重因素的共同作用导致小麦BCF-Cd的异质性,其中土壤磷(P)和锌(Zn)是影响小麦BCF-Cd变化的关键变量.参数优化可进一步提高模型精度、稳定性和泛化能力.     

冬季采暖期气象条件对PM2.5等空气质量要素的影响——以咸阳市为例

以汾渭平原典型城市——咸阳为研究区域,利用地面空气质量监测数据和欧洲中期天气预报中心（ECMWF）发布的第五代全球气候再分析资料数据集（ERA5）,分析了咸阳市2018—2020年3 a采暖期污染物浓度变化特征和不同污染程度下的气象条件,采用统计学方法分析各项污染物浓度与气象因素间的相关性,使用多元线性回归模型评价各气象因素对PM_2.5浓度的影响程度,使用二元Logistic回归分析气象因素对PM_2.5超标风险的影响。咸阳市采暖期首要污染物以细颗粒物（PM_2.5）和可吸入颗粒物（PM₁₀）为主,采暖期超标最多的污染物为PM_2.5,超标天数逐年递减;PM₁₀的日变化呈“双峰双谷”型,PM_2.5的谷值出现在17∶00且夜晚浓度较高。颗粒物浓度与相对湿度呈正相关,与风速、边界层高度、温度、气压呈负相关。多元线性回归预测模型显示PM_2.5浓度预测值与实测值变化趋势保持一致,预测值的波动频率比实测值大,预测准确率为51.54%;二元Logistic回归模型显示：除相对湿度外,其他气象因素对PM_2.5超标情况都是保护因素,边界层高度每增高1 m,日均浓度超标风险降低0.7%;相对湿度每升高1%,日均浓度超标风险升高5.3%;温度每升高1℃,日均浓度超标风险降低19.8%;气压每升高1 hPa,日均浓度超标风险降低9.7%。以上研究结果揭示了咸阳市采暖期主要气象因素对空气污染的影响程度,为我国北方城市今后的空气污染治理提供科学依据,为相关政策制定提供理论参考。     

基于MGWR的土壤pH值空间建模及其影响因素分析

以安徽、河南、江苏和山东省为研究区,利用599个土壤样点数据,从地形、气候和生物等方面选取与土壤pH相关的9个环境因子,采用多尺度地理加权回归（MGWR）、混合地理加权回归（Mixed GWR）、地理加权回归（GWR）和多元线性回归（MLR）这4种模型对研究区土壤pH空间分布进行建模,并结合MGWR与分位数回归揭示环境因子对土壤pH作用的空间差异性.结果表明：①研究区土壤pH在不同空间距离上呈不同程度的显著全局和局部空间自相关性,聚集特征明显.② 4种模型中MGWR模型最优,MGWR、Mixed GWR、GWR和MLR的建模集R_adj²为0.64、0.62、0.59和0.48.MGWR的残差独立分布性最强,其空间自相关性最弱,全局Moran''s I仅为0.07.③ 3种GWR预测结果显示,研究区土壤pH值空间分布总体由北至南逐渐降低,河南北部最高,安徽南部最低.④ MGWR回归结果表明年均降雨量（MAP）、多尺度谷底平坦度（MRVBF）和海拔对土壤pH的影响较强,且存在较强的空间异质性.在江苏北部和山东大部分地区,MAP对土壤pH的影响较强;在江苏北部和山东西部,MRVBF对土壤pH的正向作用较强;在江苏北部和中部,海拔对土壤pH的负向作用最强.⑤ MAP对不同分位数水平上的土壤pH均呈显著负作用,作用强度随分位数水平增加呈减弱趋势;MRVBF对低分位数水平（θ为0.1~0.4）上的土壤pH呈显著负作用,对高分位数水平（θ为0.5~0.9）的土壤pH作用不显著.研究结果可为利用MGWR开展大区域土壤属性影响因素分析及预测制图提供参考.     

Development of machine learning multi-city model for municipal solid waste generation prediction

● A database of municipal solid waste (MSW) generation in China was established. ● An accurate MSW generation prediction model (WGMod) was constructed. ● Key factors affecting MSW generation were identified. ● MSW trends generation in Beijing and Shenzhen in the near future are projected. Integrated management of municipal solid waste (MSW) is a major environmental challenge encountered by many countries. To support waste treatment/management and national macroeconomic policy development, it is essential to develop a prediction model. With this motivation, a database of MSW generation and feature variables covering 130 cities across China is constructed. Based on the database, advanced machine learning (gradient boost regression tree) algorithm is adopted to build the waste generation prediction model, i.e., WGMod. In the model development process, the main influencing factors on MSW generation are identified by weight analysis. The selected key influencing factors are annual precipitation, population density and annual mean temperature with the weights of 13%, 11% and 10%, respectively. The WGMod shows good performance with R² = 0.939. Model prediction on MSW generation in Beijing and Shenzhen indicates that waste generation in Beijing would increase gradually in the next 3–5 years, while that in Shenzhen would grow rapidly in the next 3 years. The difference between the two is predominately driven by the different trends of population growth.     

佛山臭氧浓度预报方程的建立与应用

臭氧作为大气中的二次污染物,其形成和变化复杂,臭氧预报更是当下空气污染治理的难题之一.通过分析2014~2017年佛山地区近地面O₃浓度与高低层气象要素的关系,建立了佛山O₃浓度预报方程,并进行了检验和应用.结果表明,佛山近地面O₃的变化与高低层气象要素关系密切,气温和日照时数等气象要素与O₃浓度呈显著正相关,相对湿度、总（低）云量和风速等与其呈负相关;高浓度O₃污染发生的气象条件为小风速、晴间少云、低相对湿度、较长的日照时间和较高的温度,高浓度O₃潜势指数（HOPI）和风向指数（WDI）的定义可以较好地衡量O₃污染气象条件的好坏;综合考虑HOPI和不同高度WDI等13种气象要素,采用多指标叠套和多元逐步回归建立了佛山地区臭氧浓度预报方程;利用2018年资料检验发现,模拟值与实测值二者的相关系数R可达0.82,预报方程具有良好的拟合效果和可预报性.