Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

中国工业碳排放达峰的情景预测与减排潜力评估

实现2030年碳排放达峰不仅是中国为应对全球气候变化向国际社会做出的郑重承诺,也是中国未来经济结构转型与可持续发展的必然选择。基于中国实现2030年碳排放达到峰值的宏观目标为背景,本文以中国碳排放的主要行业工业为研究对象,首先运用拓展的STIRPAT模型对工业及其9个细分行业的碳排放达峰进行了情景预测,然后基于公平和效率的双重视角对工业细分行业的减排潜力进行评估。研究表明:(1)仅有低碳情景和抑制排放情景2可以实现中国碳排放2030年达峰,低碳情景是实现中国工业碳排放达峰的最佳发展模式,达峰时间最早(2030年),峰值最低(140.43亿t)。激进排放情景则是最差的发展模式,达峰时间最晚(2036年),峰值也最高(150.09亿t)。(2)工业内部各细分行业碳排放的最优达峰情景差别较大。建材和纺织制造业能够实现提前达峰,可以在这类行业率先实施达峰管理措施,使其带动其他行业陆续达峰。(3)最具减排潜力的行业是石油制造业,其次是电力行业,这些减排潜力较大的行业应该成为国家节能减排的重点对象。(4)基于工业各细分行业在减排公平性和效率性上的差异将工业9个细分行业分为四类。其中,石油、钢铁制造业和电力行业属于"高效高公平行业";化工、建材制造业属于"低效高公平行业";采掘业属于"高效不公平行业";纺织、轻工和机电制造业属于"低效不公平行业"。中国应针对不同类型的行业制定出相应的减排战略,将减排重点放在各行业最具潜力的方面。最后,文章对实现中国工业碳排放达峰管理提出了几点政策建议。     

Combined Municipal Solid Waste and biomass system optimization for district energy applications

Municipal Solid Waste (MSW) disposal has been a controversial issue in many countries over the past years, due to disagreement among the various stakeholders on the waste management policies and technologies to be adopted. One of the ways of treating/disposing MSW is energy recovery, as waste is considered to contain a considerable amount of bio-waste and therefore can lead to renewable energy production. The overall efficiency can be very high in the cases of co-generation or tri-generation. In this paper a model is presented, aiming to support decision makers in issues relating to Municipal Solid Waste energy recovery. The idea of using more fuel sources, including MSW and agricultural residue biomass that may exist in a rural area, is explored. The model aims at optimizing the system specifications, such as the capacity of the base-load Waste-to-Energy facility, the capacity of the peak-load biomass boiler and the location of the facility. Furthermore, it defines the quantity of each potential fuel source that should be used annually, in order to maximize the financial yield of the investment. The results of an energy tri-generation case study application at a rural area of Greece, using mixed MSW and biomass, indicate positive financial yield of investment. In addition, a sensitivity analysis is performed on the effect of the most important parameters of the model on the optimum solution, pinpointing the parameters of interest rate, investment cost and heating oil price, as those requiring the attention of the decision makers. Finally, the sensitivity analysis is enhanced by a stochastic analysis to determine the effect of the volatility of parameters on the robustness of the model and the solution obtained.     

Composting of waste algae: A review

Although composting has been successfully used at pilot scale to manage waste algae removed from eutrophied water environments and the compost product applied as a fertiliser, clear guidelines are not available for full scale algae composting. The review reports on the application of composting to stabilize waste algae, which to date has mainly been macro-algae, and identifies the peculiarities of algae as a composting feedstock, these being: relatively low carbon to nitrogen (C/N) ratio, which can result in nitrogen loss as NH₃ and even N₂O; high moisture content and low porosity, which together make aeration challenging; potentially high salinity, which can have adverse consequence for composting; and potentially have high metals and toxin content, which can affect application of the product as a fertiliser. To overcome the challenges that these peculiarities impose co-compost materials can be employed.     

Oxygen demand for the stabilization of the organic fraction of municipal solid waste in passively aerated bioreactors

Conventional aerobic waste treatment technologies require the use of aeration devices that actively transport air through the stabilized waste mass, which greatly increases operating costs. In addition, improperly operated active aeration systems, may have the adverse effect of cooling the stabilized biomass. Because active aeration can be a limiting factor for the stabilization process, passive aeration can be equally effective and less expensive. Unfortunately, there are few reports documenting the use of passive aeration systems in municipal waste stabilization. There have been doubts raised as to whether a passive aeration system provides enough oxygen to the organic matter mineralization processes. In this paper, the effectiveness of aeration during aerobic stabilization of four different organic fractions of municipal waste in a reactor with an integrated passive ventilation system and leachate recirculation was analyzed. For the study, four fractions separated by a rotary screen were chosen. Despite the high temperatures in the reactor, the air flow rate was below 0.016 m³/h. Using Darcy’s equation, theoretical values of the air flow rate were estimated, depending on the intensity of microbial metabolism and the amount of oxygen required for the oxidation of organic compounds. Calculations showed that the volume of supplied air exceeded the microorganisms demand for oxidation and endogenous activity by 1.7–2.88-fold.     

Recycling of high purity selenium from CIGS solar cell waste materials

Copper indium gallium diselenide (CIGS) is a promising material in thin film solar cell production. To make CIGS solar cells more competitive, both economically and environmentally, in comparison to other energy sources, methods for recycling are needed. In addition to the generally high price of the material, significant amounts of the metals are lost in the manufacturing process. The feasibility of recycling selenium from CIGS through oxidation at elevated temperatures was therefore examined. During oxidation gaseous selenium dioxide was formed and could be separated from the other elements, which remained in solid state. Upon cooling, the selenium dioxide sublimes and can be collected as crystals. After oxidation for 1 h at 800 °C all of the selenium was separated from the CIGS material. Two different reduction methods for reduction of the selenium dioxide to selenium were tested. In the first reduction method an organic molecule was used as the reducing agent in a Riley reaction. In the second reduction method sulphur dioxide gas was used. Both methods resulted in high purity selenium. This proves that the studied selenium separation method could be the first step in a recycling process aimed at the complete separation and recovery of high purity elements from CIGS.     

Prediction of future disposal of end-of-life refrigerators containing CFC-11

The objective of this study was to predict the number of refrigerators containing CFC-11 blown isolation foam and the amount of CFC-11 banked in these refrigerators. By using a Weibull-based survival function, the number of CFC-11 containing and still-functioning refrigerators was estimated to be approximately 1.6 million in 2013 in Turkey. In order to determine the amount of CFC-11 in the isolation foam of these refrigerators, polyurethane (PU) foam samples were taken from a refrigerator manufactured in 1993 and the quantity of CFC-11 was analyzed by a GC-MS. It was determined that 113–195 mg CFC-11/g PU remains in the PU foam depending on the location such as door, sides, top and bottom. Knowing that a mid-sized refrigerator contains 4 kg PU on average, the total amount of PU foam to be disposed of is 6344 tons when the CFC-11 containing refrigerators in Turkey become obsolete in the near future. Furthermore, 717–1237 tons of CFC-11 are expected to be banked in the PU foam of these refrigerators which will exert an equivalent amount of ozone depleting potential (ODP). In addition, the global warming potential will vary between 3.4 and 5.9 million tons of CO₂.     

Valorisation of used cooking oil sludge by codigestion with swine manure

The addition of lipid wastes to the digestion of swine manure was studied as a means of increasing biogas production. Lipid waste was obtained from a biodiesel plant where used cooking oil is the feedstock. Digestion of this co-substrate was proposed as a way of valorising residual streams from the process of biodiesel production and to integrate the digestion process into the biorefinery concept.Batch digestion tests were performed at different co-digesting proportions obtaining as a result an increase in biogas production with the increase in the amount of co-substrate added to the mixture. Semi-continuous digestion was studied at a 7% (w/w) mass fraction of total solids. Co-digestion was successful at a hydraulic retention time (HRT) of 50 d but a decrease to 30 d resulted in a decrease in specific gas production and accumulation of volatile and long chain fatty acids. The CH₄ yield obtained was 326 ± 46 l/kg VS_feed at an HRT of 50 d, while this value was reduced to 274 ± 43 l/kg VS_feed when evaluated at an HRT of 30 d. However these values were higher than the one obtained under batch conditions (266 ± 40 l/kg VS_feed), thus indicating the need of acclimation to the co-substrate. Despite of operating at low organic loading rate (OLR), measurements from respirometry assays of digestate samples (at an HRT of 50 d) suggested that the effluent could not be directly applied to the soil as fertiliser and might have a negative effect over soil or crops.     

常州市臭氧污染传输路径和潜在源区

利用NCEP全球再分析资料和HYSPLIT4模式,计算了2013—2015年常州市臭氧(O_3)超标日的气流后向轨迹。结合聚类分析方法和常州市PM2.5、PM10、SO2、NO2、O_3数据,分析了O_3超标日不同类型气团来源对各污染物浓度的影响,并利用引入权重因子后的潜在污染源贡献函数分析了影响常州市O_3超标的潜在污染源区分布特征。结果表明:常州市O_3超标期间易受到东南和西南方向气流影响,其中从东海和黄海途经浙江东北部、上海、江苏南部等地的东南气流占比达50%以上。自内陆途经黄山-湖州-宜兴到常州的气流对应的O_3平均质量浓度最高,为116μg/m3。自山东经枣庄-宿迁-淮安-泰州-苏州-无锡到常州的气流对应的O_3平均质量浓度最低,为78μg/m3,但该气流对应的SO2和NO2平均值为各聚类中的最高。影响常州市O_3的潜在污染源区主要在常州周边200 km以内的区域,且集中在从南京至上海的长江下游沿线区域和杭州湾区域;其中太湖湖区为重点污染源源区之一。O_3超标日影响常州NO2的潜在污染源区主要集中在江苏南部、浙江东北部和上海3个区域,太湖周边的常州、无锡、苏州和湖州等几个临近城市为潜在的重点污染源区。与影响常州O_3的WPSCF高值区相比,影响NO2的高值区分布范围更大、距离更远。影响常州O_3的潜在污染源区分布,与长江三角洲地区人为源大气污染物的高排放区域较为一致,说明长江三角洲地区的O_3污染与本区域的人为源大气污染物排放有着极为密切的关联。     

Field effectiveness evaluation of advanced driver assistance systems

Abstract

Objective: Advanced driver assistance systems (ADAS) are a class of vehicle technologies designed to increase safety by providing drivers with timely warnings and autonomously intervening to avoid hazardous situations. Though laboratory testing suggests that ADAS technologies will greatly impact crash involvement rates, real-world evidence that characterizes their effectiveness is still limited. This study evaluates and quantifies the association of ADAS technologies with the likelihood of a moderate or severe crash for new-model BMWs in the United States.

Methods: Vehicle ADAS option information for the cohort of model year 2014 and later BMW passenger vehicles sold after January 1, 2014 (n?=?1,063,503), was coded using VIN-identified options data. ADAS technologies of interest include frontal collision warning with autonomous emergency braking, lane departure warning, and blind spot detection. BMW Automated Crash Notification system data (from January 2014 to November 2017) were merged with vehicle data by VIN to identify crashed vehicles (n?=?15,507), including date, crash severity (delta V), and area of impact. Using Cox proportional hazards regression modeling, the study calculates the adjusted hazard ratio for crashing among BMW passenger vehicles with versus without ADAS technologies. The adjusted percentage reduction in moderate and severe crashes associated with ADAS is interpreted as one minus the hazard ratio.

Results: Vehicles equipped with both autonomous emergency braking and lane departure warning were 23% less likely to crash than those not equipped (hazard ratio [HR]?=?0.77; 95% confidence interval [CI], 0.73–0.81), controlling for model year, vehicle size and body type. Autonomous emergency braking and lane departure warning generally occur together, making it difficult to tease apart their individual effects. Blind spot detection was associated with a 14% reduction in crashes after controlling for the presence of autonomous emergency braking and lane departure warning (HR =0.86; 95% CI, 0.744–0.99). Differences were observed by vehicle type and crash type. The combined effect of autonomous emergency braking and lane departure warning was greater in newer model vehicles: Equipped vehicles were 13% less likely to crash (HR =0.87; 95% CI, 0.79–0.95) among 2014 model year vehicles versus 34% less likely to crash (HR =0.66; 95% CI, 0.57–0.77) among 2017 model year vehicles.

Conclusion: This robust cohort study contributes to the growing evidence on the effectiveness of ADAS technologies.