Testing the importance of accurate meteorological input fields and parameterizations in atmospheric transport modelling using dream - validation against ETEX-1

A tracer model, the DREAM, which is based on a combination of a near-range Lagrangian model and a long-range Eulerian model, has been developed. The meteorological meso-scale model, MM5V1, is implemented as a meteorological driver for the tracer model. The model system is used for studying transport and dispersion of air pollutants caused by a single but strong source as, e.g. an accidental release from a nuclear power plant. The model system including the coupling of the Lagrangian model with the Eulerian model are described. Various simple and comprehensive parameterizations of the mixing height, the vertical dispersion, and different meterological input data have been implemented in the combined tracer model, and the model results have been validated against measurements from the ETEX-1 release. Several different statistical parameters have been used to estimate the differences between the parameterizations and meterological input data in order to find the best performing solution.     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.     

Polarographic investigations on the complexation of cadmium and zinc by thiol peptides

Complex formation of Cd²⁺ and Zn²⁺ with thiol derivatives has been investigated by differential pulse polarography. The binding of Cd²⁺ and Zn²⁺ with cysteine (CySH), glutathione (GSH) and the model peptide N‐acetyl‐cysteine‐methylamide (ASH) reveals different stoichiometry. Thus, Cd²⁺ forms 1:1 and 1:2 complexes with CySH while 1:2 and 1:4 complexes have been observed with GSH and ASH, respectively. Overall formation constants of Cd²⁺ with CySH (Iogβ ₂ 15.3) and with GSH (Iogβ5₂ 14.4) have been estimated using competitive complexation with nitrilotriacetic acid (NTA). Investigation of competition between Zn²⁺ and Cd²⁺ for the thiol complexation has underlined the role played by the amino group in CySH for the stabilization of Zn complexes in contrary to Cd complexes.     

Does the stock market value the inclusion in a sustainability stock index? An event study analysis for German firms

This paper empirically analyzes the effect of the inclusion of German corporations in the Dow Jones STOXX Sustainability Index (DJSI STOXX) and the Dow Jones Sustainability World Index (DJSI World) on stock performance. In order to receive robust estimation results, we apply an (short-term) event study approach that is based on both a modern asset pricing model, namely the three-factor model according to Fama and French [24], and additionally a t-GARCH(1,1) model. Our empirical results suggest that stock markets may penalize the inclusion of a firm in sustainability stock indexes. This finding is mainly driven by a strongly negative effect of the inclusion in the DJSI World. In contrast, we do not find significant average cumulative abnormal returns for the inclusion in the DJSI STOXX. This suggests that the inclusion in a more visible sustainability stock index may have larger negative impacts.     

The influence of collection facility attributes on household collection rates of electronic waste: The case of televisions and computer monitors

In the US, household electronic waste collected for recycling is primarily by voluntary drop-off at designated collection facilities. This study examines the influence of specific collection facility attributes (recycling fees charged, number of days open, and driving distance) on the household collection rate of e-waste in the US state of Maine. Data were collected for household computer monitor and television collection for 92 municipal waste transfer facilities representing 30% of the state's population for one year. Results suggest that recycling fees are negatively correlated with the number of televisions and computer monitors collected; furthermore, the more frequently facilities were open, the more televisions and computer monitors were collected per capita. The distance from the facility had no correlation, which prompted an analysis of whether the existence of a curbside collection system in the municipality was influential. Results show a negative correlation between computer monitor and television collection and a municipality having recycling (but not e-waste) curbside collection. Based on the results of this study, policymakers may be able to increase the collection rate of household e-waste by eliminating or lowering recycling fees, expanding collection days and hours to increase convenience, and/or considering curbside collection of e-waste.     

Occurrence of PCBs in raw and finished drinking water at seven public water systems along the Hudson River

Polychlorinated biphenyls (PCBs) were measured in raw and finished drinking water at seven Public Water Systems (PWSs) along the Hudson River as part of a baseline monitoring program prior to the extensive sediment dredging of the Upper Hudson River. Water samples were either analyzed using an Aroclor method (based on USEPA Method 508) or a congener method (Modified Green Bay Mass Balance Method). Using the congener-based method, raw water concentrations ranged from <9.3 to 164.3 ng/L and finished water concentrations ranged from <9.3 to 186.6 ng/L. Using the Aroclor method, finished water concentrations ranged from <5.0 to 200.9 ng/L. Most finished water samples above 73.0 ng/L were from a PWS with wells drilled near the river. Excluding the well data, total PCB concentrations in raw water at systems in the Upper River were similar to concentrations at systems in the Lower River, though the congener patterns differed. Paired comparison of total PCB concentrations using the two analytical methods showed good agreement, although raw water showed a different relationship than finished water.     

Analyzing the cost effectiveness of Santiago, Chile's policy of using urban forests to improve air quality

Santiago, Chile has the distinction of having among the worst urban air pollution problems in Latin America. As part of an atmospheric pollution reduction plan, the Santiago Regional Metropolitan government defined an environmental policy goal of using urban forests to remove particulate matter less than 10 microm (PM(10)) in the Gran Santiago area. We used cost effectiveness, or the process of establishing costs and selecting least cost alternatives for obtaining a defined policy goal of PM(10) removal, to analyze this policy goal. For this study, we quantified PM(10) removal by Santiago's urban forests based on socioeconomic strata and using field and real-time pollution and climate data via a dry deposition urban forest effects model. Municipal urban forest management costs were estimated using management cost surveys and Chilean Ministry of Planning and Cooperation documents. Results indicate that managing municipal urban forests (trees, shrubs, and grass whose management is under the jurisdiction of Santiago's 36 municipalities) to remove PM(10) was a cost-effective policy for abating PM(10) based on criteria set by the World Bank. In addition, we compared the cost effectiveness of managing municipal urban forests and street trees to other control policies (e.g. alternative fuels) to abate PM(10) in Santiago and determined that municipal urban forest management efficiency was similar to these other air quality improvement measures.     

Are EMS environmentally effective? The link between environmental management systems and environmental performance in European companies

Based on the analysis of a large dataset on the environmental performance of European companies in five industrial sectors, this paper examines the question of whether the presence of an environmental management system (EMS) has a positive impact on the eco-efficiency of companies. It begins with a review of evidence about the link between EMS and environmental performance in business organisations, finding that, despite much research, there is still little quantitative evidence. The second part of the paper uses three independent statistical methods (simple correlations, Jaggi-Freedman indices and a ‘trend differences’ approach) to assess whether companies and production sites with EMS perform better than those without and whether performance improves after an EMS has been introduced. The paper shows that there is currently no evidence that EMS have a consistent and significant positive impact on environmental performance. Policy action based on the simple assumption that companies with an EMS perform better than those without therefore seems inappropriate.