In-vitro method and model to estimate methane emissions from liquid manure management on pig and dairy farms in four countries.

Methane (CH4) emissions from manure management on livestock farms are a key source of greenhouse gas emissions in some regions and for some production systems, and the opportunities for mitigation may be significant if emissions can be adequately documented. We investigated a method for estimating CH4 emissions from liquid manure (slurry) that is based on anaerobic incubation of slurry collected from commercial farms. Methane production rates were used to derive a parameter of the Arrhenius temperature response function, lnA', representing the CH4 production potential of the slurry at the time of sampling. Results were used for parameterization of an empirical model to estimate annual emissions with daily time steps, where CH4 emissions from individual sources (barns, outside storage tanks) can be calculated separately. A monitoring program was conducted in four countries, i.e., Denmark, Sweden, Germany and the Netherlands, during a 12-month period where slurry was sampled to represent barn and outside storage on finishing pig and dairy farms. Across the four countries, lnA' was higher in pig slurry compared to cattle slurry (p < 0.01), and higher in slurry from barns compared to outside storage (p < 0.01). In a separate evaluation of the incubation method, in-vitro CH4 production rates were comparable with in-situ emissions. The results indicate that lnA' in barns increases with slurry age, probably due to growth or adaptation of the methanogenic microbial community. Using lnA' values determined experimentally, empirical models with daily time steps were constructed for finishing pig and dairy farms and used for scenario analyses. Annual emissions from pig slurry were predicted to be 2.5 times higher than those from cattle slurry. Changing the frequency of slurry export from the barn on the model pig farm from 40 to 7 d intervals reduced total annual CH4 emissions by 46 %; this effect would be much less on cattle farms with natural ventilation. In a scenario with cattle slurry, the empirical model was compared with the current IPCC methodology. The seasonal dynamics were less pronounced, and annual CH4 emissions were lower than with the current methodology, which calls for further investigations. Country-specific models for individual animal categories and point sources could be a tool for assessing CH4 emissions and mitigation potentials at farm level.

Perspectives on environment and health research in Denmark.

AIMS: We provide an overview of nationwide environmental data available for Denmark and its linkage potentials to individual-level records with the aim of promoting research on the potential impact of the local surrounding environment on human health. BACKGROUND: Researchers in Denmark have unique opportunities for conducting large population-based studies treating the entire Danish population as one big, open and dynamic cohort based on nationally complete population and health registries. So far, most research in this area has utilised individual- and family-level information to study the clustering of disease in families, comorbidities, risk of, and prognosis after, disease onset, and social gradients in disease risk. Linking environmental data in time and space to individuals enables novel possibilities for studying the health effects of the social, built and physical environment. METHODS: We describe the possible linkage between individuals and their local surrounding environment to establish the exposome - that is, the total environmental exposure of an individual over their life course. CONCLUSIONS: The currently available nationwide longitudinal environmental data in Denmark constitutes a valuable and globally rare asset that can help explore the impact of the exposome on human health.

Residential proximity to agriculture and risk of childhood leukemia and central nervous system tumors in the Danish national birth cohort.

BACKGROUND: Living in an agricultural area or on farms has been associated with increased risk of childhood cancer but few studies have evaluated specific agricultural exposures. We prospectively examined residential proximity to crops and animals during pregnancy and risk of childhood leukemia and central nervous system (CNS) tumors in Denmark. METHODS: The Danish National Birth Cohort (DNBC) consists of 91,769 pregnant women (96,841 live-born children) enrolled in 1996-2003. For 61 childhood leukemias and 59 CNS tumors <15 years of age that were diagnosed through 2014 and a ~10% random sample of the live births (N = 9394) with geocoded addresses, we linked pregnancy addresses to crop fields and animal farm locations and estimated the crop area (hectares [ha]) and number of animals (standardized by their nitrogen emissions) by type within 250 meters (m), 500 m, 1000 m, and 2000 m of the home. We also estimated pesticide applications (grams, active ingredient) based on annual sales data for nine herbicides and one fungicide that were estimated to have been applied to >30% of the area of one or more crop. We used Cox proportional hazard models (weighted to the full cohort) to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the association of childhood leukemia and CNS tumors with crop area, animals, and pesticide applications adjusted for gender and maternal age. RESULTS: Sixty-three percent of mothers had crops within 500 m of their homes during pregnancy; winter and spring cereals were the major crop types. Compared to mothers with no crops <500 m, we found increasing risk of childhood leukemia among offspring of mothers with increasing crop area near their home (highest tertile >24 ha HR: 2.0, CI:1.02-3.8), which was stronger after adjustment for animals (within 1000 m) (HR: 2.6, CI:1.02-6.8). We also observed increased risk for grass/clover (highest tertile >1.1 ha HR: 3.1, CI:1.2-7.7), peas (>0 HR: 2.4, CI: 1.02-5.4), and maize (>0 HR: 2.8, CI: 1.1-6.9) in animal-adjusted models. We found no association between number of animals near homes and leukemia risk. Crops, total number of animals, and hogs within 500 m of the home were not associated with CNS tumors but we observed an increased risk with >median cattle compared with no animals in crop-adjusted models (HR = 2.2, CI: 1.02-4.9). In models adjusted for total animals, the highest tertiles of use of three herbicides and one fungicide were associated with elevated risk of leukemia but no associations were statistically significant; there were no associations with CNS tumors. CONCLUSIONS: Risk of childhood leukemia was associated with higher crop area near mothers' homes during pregnancy; CNS tumors were associated with higher cattle density. Quantitative estimates of crop pesticides and other agricultural exposures are needed to clarify possible reasons for these increased risks.

Agricultural policies exacerbate honeybee pollination service supply-demand mismatches across Europe.

Declines in insect pollinators across Europe have raised concerns about the supply of pollination services to agriculture. Simultaneously, EU agricultural and biofuel policies have encouraged substantial growth in the cultivated area of insect pollinated crops across the continent. Using data from 41 European countries, this study demonstrates that the recommended number of honeybees required to provide crop pollination across Europe has risen 4.9 times as fast as honeybee stocks between 2005 and 2010. Consequently, honeybee stocks were insufficient to supply >90% of demands in 22 countries studied. These findings raise concerns about the capacity of many countries to cope with major losses of wild pollinators and highlight numerous critical gaps in current understanding of pollination service supplies and demands, pointing to a pressing need for further research into this issue.

Conscious worst case definition for risk assessment, part II: a methodological case study for pesticide risk assessment.

This paper illustrates, by a case study, how to apply the conceptual Worst-Case Definition (WCD) model, developed in the methodological paper in the current journal, by Sørensen et al. (2010-this issue). The case is about eco-toxicological risk assessment of pesticides under Danish conditions. Cumulative aspects are included on a conceptual basis as elements of the worst-case conditions. This defines factors that govern the risk assessment, including location in time and space of risk "hotspots". Two pillars of concern drive the conceptual modelling: (1) What to protect (denoted Protected Units (PUs)) and (2) the reason for increased risk level (denoted Causes of Risks (CRs)). Both PUs and CRs are analysed using hierarchical procedures that facilitate a complete listing of concrete factors governing increased risk for adverse effect due to agricultural usage of pesticide. The factors governing pesticide risk are combined in a context that combines the protection of relevant groupings of organisms with the factors for increased risk level for each of these. Identification of the most important relations between defined types of PUs and CRs is illustrated using expert knowledge. Existing databases are used to form spatial distributed risk indicators as estimators for a selection of important relations between PUs and CRs. This paper illustrates how the WCD model can break down the complex issue of uncertainty into fractions that are more open for evaluations. Finally, it shows application of risk indicators in a multi-criterion analysis using respectively self organizing mapping and partial order technique in a comparative analysis that highlights critical aspects of uncertainty, due to the ambiguity between single risk indicator rankings.

Footprints on ammonia concentrations from environmental regulations.

Releases of ammonia (NH3) to the atmosphere contribute significantly to the deposition of nitrogen to both terrestrial and aquatic ecosystems. This is the background for the national NH3 emission ceilings in Europe. However, in some countries the national legislation aims not only to meet these ceilings but also to reduce the atmospheric nitrogen deposition to local ecosystems. Such measures to reduce the load of nitrogen to local ecosystems were introduced in Denmark in 1994. In this paper we demonstrate that this regulation is reflected in the NH3 concentrations in Denmark. The Danish legislation forces farmers to applying manure to the fields during the crop-growing season. We have analyzed the seasonal variation in local NH3 concentrations over the time period of 1989-2003. During this period the seasonal variation has changed from having moderate spring and autumn concentration peaks to having a single and much more pronounced spring peak. In the analysis we apply an NH3 emission model to demonstrate that these changes in the seasonal variation are a result of the changes in the Danish legislation. The analysis demonstrates the strength of using a high-resolution emission model in the analysis of routine monitoring data.