Threshold and dose response estimation using the “filter model”

The “filter model” has been developed to explain the biologic effects of radiation and chemicals. We have examined nearly 300 sets of dose response data, of which 50 are presented here. Responses (induced by radiation and chemicals) which have been examined include in vitro survival studies on animal and plant tissues, induction of cellular aberrations and time to tumor or death. Similar data from in vivo studies has also been examined. All of the data appear to fit the model R = a lnD + b(lnD)² + c, where R is the response, a and b are parameters fitted by regression to a particular set of data, and c is the response at zero (or lowest) dose. By writing this model in exponential form, it can be seen that the response R results from multistage filtering (by net amounts a and b) of the initial dose, D. The threshold is obtained from this model as the point, $\text{D}\text{?}{}_{\mathrm{T}}$, at which the second derivative becomes zero. This is given by $\text{D}\text{?}{}_{\mathrm{T}}\text{=}\text{exp}\text{(1 ?}\text{a}\text{2b}\text{)}$ when a and b are oppositelt signed.     

Fertility and air pollution: Some empirical findings

This paper attempts to explain regional differences in fertility rates in the standard metropolitan statistical areas of the United States through socioeconomic factors and air pollution. An important feature of this study is that it uses the most recent data pertaining to a homogeneous sample of observations within a country rather than using data for different countries. Statistical results suggest that given other factors, fertility and the level of air pollution have an inverse relationship. This quantitative effect is statistically significant but the absolute impact is rather low. Our results also suggest that an increase in the level of income, relative education of females, temperature, and the availability of physicians would in the long run reduce fertility rates in the urban areas of the United States.     

An appraisal of emissions control requirements in the California South Coast Air Basin

The purpose of this study is to evaluate the effect of reductions of reactive organic gases (ROG) and NO_x emissions on short-term O₃ and NO₂ concentrations and annual average NO₂ concentrations in the California South Coast Air Basin. Short-term air quality predictions were obtained by applying the Systems Applications Airshed Model to summer O₃ and autumn NO₂ episodes. Effects of emission controls on annual NO₂ concentrations were estimated using CDM and a new parcel tracking model NOXTRAK. Results for the summer O₃ episode indicate that ROG emission reduction in an effective means for reducing peak O₃ concentrations. NO_x emission reduction imposed in addition to ROG emission reductions are counterproductive in reducing peak O₃ concentrations. The modeling results also suggest that attainment of the 1-h federal O₃ standard requires ROG emission reductions on the order of 80% from 1987 levels. Results for the autumn NO₂ episode indicate that NO_x emission reductions approximating those recommended in a proposed Air Quality Management Plan (about 22%) will result in only small (about 5%) reductions in the peak NO₂ concentrations. ROG emission reduction may be more effective than NO_x emission reduction in reducing the peak NO₂ concentration. For the episode studied, a reduction of 36% in ROG emissions is estimated to result in a reduction in peak NO₂ concentrations commensurate with that required to attain the 1-h state NO₂ standard. Model calculations also indicate that the federal NO₂ standard may not be meet by 1987 at one or two stations, but may blosely approached.     

Air pollution health effects in the Munich metropolitan area: Preliminary results based on a statistical model

Based on a feasibility study, we have recently proposed a multivariate regression model for the impact of air pollution on the mortality of a long-term exposed population. This article proceeds by providing some experimental results, since this model has been fitted to data on a cross sectional basis for 41 census tracts in the Munich metropolitan area. The results obtained so far could be supportive to more detailed epidemiological studies of air pollution which have been conducted in many industrial countries; unfortunately, only relatively few have been conducted in West Germany.     

Greening flood protection through knowledge processes: lessons from the Markermeer dikes project in the Netherlands

Greening flood protection (GFP) is increasingly recognized as an adaptive and flexible approach to water management that is well suited to addressing uncertain futures associated with climate change. In the last decade, GFP knowledge and policies have developed rapidly, but implementation has been less successful and has run into numerous barriers. In this paper, we address the challenge of realizing green flood protection goals by specifically considering knowledge in the decision-making of a Dutch flood protection project in Lake Markermeer. In this project, an ecological knowledge arrangement and a traditional flood protection knowledge arrangement are compared and their interactions analysed. The analysis provides insight into the specific difficulties of implementing GFP measures and identifies ways to realize GFP goals. The primary challenge is twofold: First, a self-reinforcing cycle of knowledge production and decision-making in the flood protection domain inhibits the introduction of innovative and multifunctional approaches such as GFP; second, the distribution of power is severely unbalanced in terms of ecological enhancement and flood protection, favouring the latter. Implementation of GFP requires structural change and the integration of ecological and flood protection knowledge and policy. Potentially rewarding routes towards this integration are the exploration of shared interests in GFP and the creation of mutual dependency between knowledge arrangements. The case study and the insights it provides show that GFP is far from mainstream practice and that implementation requires serious effort and courage to break with historical practices.     

Research priorities for managing the impacts and dependencies of business upon food,energy, water and the environment

Delivering access to sufficient food, energy and water resources to ensure human wellbeing is a major concern for governments worldwide. However, it is crucial to account for the ‘nexus’ of interactions between these natural resources and the consequent implications for human wellbeing. The private sector has a critical role in driving positive change towards more sustainable nexus management and could reap considerable benefits from collaboration with researchers to devise solutions to some of the foremost sustainability challenges of today. Yet opportunities are missed because the private sector is rarely involved in the formulation of deliverable research priorities. We convened senior research scientists and influential business leaders to collaboratively identify the top forty questions that, if answered, would best help companies understand and manage their food-energy-water-environment nexus dependencies and impacts. Codification of the top order nexus themes highlighted research priorities around development of pragmatic yet credible tools that allow businesses to incorporate nexus interactions into their decision-making; demonstration of the business case for more sustainable nexus management; identification of the most effective levers for behaviour change; and understanding incentives or circumstances that allow individuals and businesses to take a leadership stance. Greater investment in the complex but productive relations between the private sector and research community will create deeper and more meaningful collaboration and cooperation.     

Visualizing dynamic capabilities as adaptive capacity for municipal water governance

This study seeks to expand empirical research on how municipalities have adapted and innovated (or not) their water systems as a result of climate change. We analyze characteristics of water governance at the municipal scale in Oklahoma, USA. ArcMap 10.3 was used to build a qualitative geographic information system (GIS) based on fieldwork, including interviews and site-observations, to compare dynamic capabilities that lead to innovation in 38 cities in the state. The GIS enables visualization of our digitalized research to understand the interconnections between drivers of innovativeness—the combination of dynamic capabilities and innovation rates—and state of water resource infrastructure in place specific and regional planning contexts. In particular, the GIS takes into consideration income level, the influence of state-level water policy (Water for 2060 Act), water manager certification levels, population, dynamic capabilities, and perceptions of risk and vulnerability to water system change. Digitizing this information provides a diverging perspective on the historical lack of innovation in the public sector, as different socio-cultural, socio-economic, and socio-political contexts occur throughout Oklahoma, a state notorious for its oil centered economy and its climate change deniers. The findings suggest that innovativeness is directly related to dynamic capabilities and indirectly related to population size, income level, and the educational backgrounds of water decision-makers. The visualizations also show that some cities have surplus capacity for adaptation, while others were able to more efficiently turn capacity into water management innovations. Seeing representations of water governance success and failure in communities affords the opportunity to educate citizens and decision-makers to adapt water infrastructures to the effects of climate change, showcasing the utility of digitalization in a quest for sustainable solutions.     

Social-ecological system resonance: a theoretical framework for brokering sustainable solutions

Sustainability science is a solution-oriented discipline. Yet, there are few theory-rich discussions about how this orientation structures the efforts of sustainability science. We argue that Niklas Luhmann’s social system theory, which explains how societies communicate problems, conceptualize solutions, and identify pathways towards implementation of solutions, is valuable in explaining the general structure of sustainability science. From Luhmann, we focus on two key concepts. First, his notion of resonance offers us a way to account for how sustainability science has attended and responded to environmental risks. As a product of resonance, we reveal solution-oriented research as the strategic coordination of capacities, resources, and information. Second, Luhmann’s interests in self-organizing processes explain how sustainability science can simultaneously advance multiple innovations. The value logic that supports this multiplicity of self-organizing activities as a recognition that human and natural systems are complex coupled and mutually influencing. To give form to this theoretical framework, we offer case evidence of renewable energy policy formation in Texas. Although the state’s wealth is rooted in a fossil-fuel heritage, Texas generates more electricity from wind than any US state. It is politically antagonistic towards climate-change policy, yet the state’s reception of wind energy technology illustrates how social and environmental systems can be strategically aligned to generate solutions that address diverse needs simultaneously. This case demonstrates that isolating climate change—as politicians do as a separate and discrete problem—is incapable of achieving sustainable solutions, and resonance offers researchers a framework for conceptualizing, designing, and communicating meaningfully integrated actions.