Farm-level assessment of CO2 and N2O emissions in Lower Saxony and comparison of implementation potentials for mitigation measures in Germany and England

Greenhouse gases (GHG) emissions from agricultural farming practice contribute significantly to European GHG inventories. For example, CO₂ is emitted when grassland is converted to cropland or when peatlands are drained and cultivated. N₂O emissions result from fertilization. Enabling farmers to reduce their GHG emissions requires sufficient information about its pressure–impact relations as well as incentives, such as regulations and funding, that support climate-friendly agricultural management. This paper discusses potentials to improve the supply of information on: farm-specific climate services or impacts, present policy incentives in Germany and England that support climate-friendly farm management and related adaptation requirements. Tools which have been developed for a farm environmental management software (to be added after review because of potential identification) are presented. These tools assess CO₂ emissions from grassland conversion to cropland and peatland cultivation, as well as N₂O emissions from nitrogen fertilization. As input data, the CO₂ tool requires a classification of soil types according to soil organic carbon storage. The input data based on soil profile samples was compared with reference data from the literature. The N₂O tool relies on farm data concerning fertilization. These tools were tested on three farms in order to determine their viability with respect to the availability of required data and the differentiation of results, which determines how well site-specific conservation measures can be identified. Assessing CO₂ retention function of grassland conservation to cropland on the test farms leads to spatially differentiated results (~100 to ~900 potentially mitigated t CO₂ ha^?1). Assessed N₂O emissions varied from 0.41 to 1.1 t CO₂eq. ha^?1 a^?1. The proposed methods support policies that promote a more differentiated funding of climate conservation measures. Conservation measures and areas can be selected so that they will have the greatest mitigation effects. However, even though present policy instruments in Germany and England, such as Cross Compliance and agri-environmental measures, have the potential to reduce agricultural GHG, they do not appear to guide measures effectively or site-specifically. In order to close this gap, agri-environmental measures with the potential to support climate protection should be spatially optimized. Additionally, the wetland restoration measures which are most effective in reducing GHG emissions should be included in funding schemes.     

Perspectives on Disconnects Between Scientific Information and Management Decisions on Post-fire Recovery in Western US

Environmental regulations frequently mandate the use of “best available” science, but ensuring that it is used in decisions around the use and protection of natural resources is often challenging. In the Western US, this relationship between science and management is at the forefront of post-fire land management decisions. Recent fires, post-fire threats (e.g. flooding, erosion), and the role of fire in ecosystem health combine to make post-fire management highly visible and often controversial. This paper uses post-fire management to present a framework for understanding why disconnects between science and management decisions may occur. We argue that attributes of agencies, such as their political or financial incentives, can limit how effectively science is incorporated into decision-making. At the other end of the spectrum, the lack of synthesis or limited data in science can result in disconnects between science-based analysis of post-fire effects and agency policy and decisions. Disconnects also occur because of the interaction between the attributes of agencies and the attributes of science, such as their different spatial and temporal scales of interest. After offering examples of these disconnects in post-fire treatment, the paper concludes with recommendations to reduce disconnects by improving monitoring, increasing synthesis of scientific findings, and directing social-science research toward identifying and deepening understanding of these disconnects.     

When may road fatalities start to decrease?

Introduction

The comparative analysis of macroscopic trends in road safety has been a popular research topic. The objective of this research is to propose a simple and, at the same time, reliable multiple regime model framework for international road safety comparisons, allowing for the identification of slope changes of personal risk curves and respective breakpoints.

Method

The trends of road traffic fatalities in several EU countries have been examined through the temporal evolution of elementary socioeconomic indicators, namely motorized vehicle fleet and population, at the country level.

Results

Piece-wise linear regression models have been fitted, using a methodology that allows the simultaneous estimation of all slopes and breakpoints. The number and location of breakpoints, as well as the slope of the connecting trends, vary among countries, thus indicating different road safety evolution patterns.

Impact on industry

Macroscopic analysis of road accident trends may be proved beneficial for the identification of best examples and the implementation of appropriate programmes and measures, which will lead to important benefits for the society and the economy through the reduction of road fatalities and injuries. Best performing countries and the related programmes and measures adopted may concern several safety improvements at the processes of the road, the vehicle and the insurance industries.

Conclusions

Lessons from the analysis of the past road safety patterns of developed countries provide some insight into the underlying process that relates motorization levels with personal risk and can prove to be beneficial for predicting the road safety evolution of developing countries that may have not yet reached the same breakpoints. Furthermore, the presented framework may serve as a basis to build more elaborate models, including more reliable exposure indicators (such as vehicle-km driven).     

Comprehensive prenatal diagnostics: Exome versus genome sequencing

Objective

This study aimed to assess the diagnostic yield of prenatal genetic testing using trio whole exome sequencing (WES) and trio whole genome sequencing (WGS) in pregnancies with fetal anomalies by comparing the results with conventional chromosomal microarray (CMA) analysis.

Methods

A total of 40 pregnancies with fetal anomalies or increased nuchal translucency (NT ≥ 5 mm) were included between the 12th and 21st week of gestation. Trio WES/WGS and CMA were performed in all cases.

Results

The trio WES/WGS analysis increased the diagnostic yield by 25% in cases with negative CMA results. Furthermore, all six chromosomal aberrations identified by CMA were independently detected by WES/WGS analysis. In total, 16 out of 40 cases obtained a genetic sequence variant, copy number variant, or aneuploidy explaining the phenotype, resulting in an overall WES/WGS diagnostic yield of 40%. WES analysis provided a more reliable identification of mosaic sequence variants than WGS because of its higher sequencing depth.

Conclusions

Prenatal WES/WGS proved to be powerful diagnostic tools for fetal anomalies, surpassing the diagnostic yield of CMA. They have the potential to serve as standalone methods for prenatal diagnosis. The study highlighted the limitations of WGS in accurately detecting mosaic variants, which is particularly relevant when analyzing chorionic villus samples.     

Biofiltration of Cyclic Air Emissions of [H9251]-Pinene at Low and High Frequencies

Abstract

Biofiltration of periodically fluctuating concentrations of an α-pinene-laden waste gas was investigated to treat both high-frequency and low-frequency fluctuations. The effects of periodic concentration fluctuations on biofilter performance were measured. Controlled variables of periodic operation included cycle period and amplitude. The cycle period ranged from 10 min to 6 days, with the inlet α-pinene concentration fluctuating between 0 and 100 parts per million volume. At high-frequency concentration cycling (i.e., on the order of minutes), both cyclic and constant concentration biofilters maintained similar long-term performance with an average removal efficiency of 77% at an averaged loading rate of 29 g α-pinene/m³ bed/hr. A first approximation suggests kinetics that are time-independent, indicating that steady-state data can be used to predict transient behavior at this time scale. Cyclic biofilter operation with a cycle period of 24 hr (with equal on/off time) was achievable for biofilters without a significant loss in performance. At longer time scales, cyclic biofilter performance decreased at the restart of the ON cycle. The recovery time to previous levels of performance increased with increasing cycle period; the recovery time was less than 1 hr for a cycle period of 24 hr and between 6 and 8 hr for a cycle period of 6 days.