Attribution of Carbon Dioxide Fluxes to Crop Types in a Heterogeneous Agricultural Landscape of Argentina

The increasing proportion of agricultural lands worldwide makes it necessary to intensify the research concerning the carbon exchange at agricultural sites. In order to determine the Net Ecosystem Exchange (NEE) in an agricultural landscape in the province of Buenos Aires, Argentina, we carried out eddy covariance measurements with a flux tower, which was placed between two agricultural fields. Therefore, the measured CO₂ flux represents the accumulated flux from both areas, i.e., from different crop types. We here present an analysis method which attributes the flux to the two crop types. For this analysis, we applied the Hsieh footprint model to identify the contributing source area to the flux measurement. We then applied a multiple regression analysis to calculate the NEE in the growing season 2011/2012 for each field separately. The pronounced differences in the time courses of the CO₂ fluxes in the two fields can be explained by the different sowing times and different growth stages of both cultivations. The time courses furthermore show that the CO₂ uptake of the plants was strongly affected by the drought which lasted from December 2011 to January 2012. For the growth cycle of maize (216 days), the NEE was ?240 g C m^?2 and for the growth cycle of soybean (154 days) ?231 g C m^?2. In order to obtain the NEE of a complete agricultural cycle (from harvest to harvest), we also considered the NEE of autumn and winter 2011. Uncertainties of the spatially partitioned NEE are quantified and discussed.     

“Science is Everywhere,but No One Knows It”: Assessing the Cultural Distance to Science of Rural South African Publics

ABSTRACT

In science communication, a prerequisite for reaching different parts of a society is to find out how these publics experience and interpret science. Since rural South African publics are perceived to exhibit a large cultural distance to science, the present exploratory study aimed to know in more detail how rural South Africans perceive and understand science in their local and social contexts. Theoretical notions on cultural distance and the methodological approach of segmentation studies were considered. Semi-structured interviews with rural South Africans were carried out in four towns (n?=?52) that differ with respect to having a large scientific installation in their vicinity, or not. Sensitively comparing local and social contexts helped identifying three different publics who differed regarding their perceptions of science; however, the large scientific installations only made a difference in perceptions for those publics who were generally less exposed to and less knowledgeable about science.     

Towards quantifying the glacial runoff signal in the freshwater input to Tyrolerfjord–Young Sound,NE Greenland

Terrestrial freshwater runoff strongly influences physical and biogeochemical processes at the fjord scale and can have global impacts when considered at the Greenland scale. We investigate the performance of the HIRHAM5 regional climate model over the catchments delivering freshwater to Tyrolerfjord and Young Sound by comparing to the unique Greenland Ecological Monitoring database of in situ observations from this region. Based on these findings, we estimate and discuss the fraction of runoff originating from glacierized and non-glacierized land delivered at the daily scale between 1996 and 2008. We find that glaciers contributed on average 50–80% of annual terrestrial runoff when considering different sections of Tyrolerfjord–Young Sound, but snowpack depletion on land and consequently runoff happens about one month earlier in the model than observed in the field. The temporal shift in the model is a likely explanation why summer surface salinity in the inner fjord did not correlate to modelled runoff.     

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.     

Hydroponic root mats for wastewater treatment—a review

Hydroponic root mats (HRMs) are ecotechnological wastewater treatment systems where aquatic vegetation forms buoyant filters by their dense interwoven roots and rhizomes, sometimes supported by rafts or other floating materials. A preferential hydraulic flow is created in the water zone between the plant root mat and the bottom of the treatment system. When the mat touches the bottom of the water body, such systems can also function as HRM filter; i.e. the hydraulic flow passes directly through the root zone. HRMs have been used for the treatment of various types of polluted water, including domestic wastewater; agricultural effluents; and polluted river, lake, stormwater and groundwater and even acid mine drainage. This article provides an overview on the concept of applying floating HRM and non-floating HRM filters for wastewater treatment. Exemplary performance data are presented, and the advantages and disadvantages of this technology are discussed in comparison to those of ponds, free-floating plant and soil-based constructed wetlands. Finally, suggestions are provided on the preferred scope of application of HRMs.     

Long-term change in drivers of forest cover expansion: an analysis for Switzerland (1850-2000)

Regional Environmental Change - The spatial distribution of forests in Europe represents the legacy of centuries of human land use decisions. Due to the limited availability of historical data,...     

Modeling and data assessment of longitudinal salinity in a low-gradient estuarine river

Continuous data of vertical-profile salinity were analyzed for four stations located successively upriver in a macrotidal estuary, the lower St. Johns River (Northeast Florida, USA). The data analysis confirmed well-mixed salinity conditions in the river with at most 1.3 ppt of vertical variability at Dames Point (river km 20), where the main variations of salinity are along the longitudinal axis of the river. Given the well-mixed salinity conditions and dominant horizontal structure of salinity variations in the river, we present and apply a barotropic, two-dimensional modeling approach for hydrodynamic-salinity transport simulation in the lower St. Johns River. When properly forced by offshore surge, high-resolution wind fields and freshwater river inflows, the model replicated the salinity measurements remarkably well, including the separation into tidal and sub-tidal components. The data and model results show that, at times, offshore winds and surge can be more influential on longitudinal salinity variations than local winds over the river. We demonstrate the importance of using proper boundary conditions to force the model relative to the minimal sensitivity of the model to parameter adjustment of horizontal mixing and uncertainty-based perturbation of wind and inflow forcings.     

The data not collected on community forestry

Conservation and development practitioners increasingly promote community forestry as a way to conserve ecosystem services, consolidate resource rights, and reduce poverty. However, outcomes of community forestry have been mixed; many initiatives failed to achieve intended objectives. There is a rich literature on institutional arrangements of community forestry, but there has been little effort to examine the role of socioeconomic, market, and biophysical factors in shaping both land‐cover change dynamics and individual and collective livelihood outcomes. We systematically reviewed the peer‐reviewed literature on community forestry to examine and quantify existing knowledge gaps in the community‐forestry literature relative to these factors. In examining 697 cases of community forest management (CFM), extracted from 267 peer‐reviewed publications, we found 3 key trends that limit understanding of community forestry. First, we found substantial data gaps linking population dynamics, market forces, and biophysical characteristics to both environmental and livelihood outcomes. Second, most studies focused on environmental outcomes, and the majority of studies that assessed socioeconomic outcomes relied on qualitative data, making comparisons across cases difficult. Finally, there was a heavy bias toward studies on South Asian forests, indicating that the literature on community forestry may not be representative of decentralization policies and CFM globally.     

Environmental impact of exhaust emissions by Arctic shipping

Since 2005, a dramatic decline of the Arctic sea-ice extent is observed which results in an increase of shipping activities. Even though this provides commercial and social development opportunities, the resulting environmental impacts need to be investigated and monitored. In order to understand the impact of shipping in arctic areas, the method described in this paper determines the travel time, fuel consumption and resulting exhaust emissions of ships navigating in arctic waters. The investigated case studies are considering ship particulars as well as environmental conditions with special focus on ice scenarios. Travel time, fuel consumption and exhaust gas emission were investigated for three different vessels, using different passages of the Northern Sea Route (NSR) in different seasons of years 1960, 2000 and 2040. The presented results show the sensitivity of vessel performance and amount of exhaust emissions to optimize arctic traffic with respect to efficiency, safety and environmental impact.     

A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.