Alternative carbon dioxide modelling approaches accounting for high residual gases in LandGEM

High Canadian waste disposal rates necessitate landfill gas monitoring and accurate forecasting. CO₂ estimates in LandGEM version 3.02 currently rest on the assumptions that CO₂ is a function of CH₄, where the two gases make up nearly 100% of landfill gas content, leading to overestimated CO₂ collection estimates. A total of 25 cases (five formulas, five approaches) compared annual CO₂ collection at four western Canadian landfills. Despite common use in literature, the 1:1 ratio of CH₄ to CO₂ was not recommended to forecast landfill gas collection in cold climates. The existing modelling approach significantly overestimated CO₂ production in three of four sites, resulting in the highest residual sum of squares. Optimization resulted in the most accurate results for all formulas and approaches, which had the greatest reduction in residual sums of squares (RSS) over the default approach (60.1 to 97.7%). The 1.4 Ratio approach for L _o:L _o-CO2 yielded the second most accurate results for CO₂ flow (mean RSS reduction of 50.2% for all sites and subsection models). The annual k-modified LandGEM calculated k’s via two empirical formulas (based on precipitation) and yielded the lowest accuracy in 12 of 20 approaches. Unlike other studies, strong relationships between optimized annual k’s and precipitation were not observed.

     

Value chain for next-generation biofuels: resilience and sustainability of the product life cycle

Multiple factors including climate change, price uncertainties, and geopolitical instability have prompted many industries to investigate the feasibility of replacing traditional petroleum-based fuels with biofuel alternatives. However, to make this transition successful, these new biofuels must be environmentally sustainable and the necessary support infrastructure must be in place to make the production, distribution, and storage of these biofuels technologically feasible and cost effective. Developing a value chain, spanning from feedstock production to distribution to end users, requires garnering buy-in from multiple stakeholders by demonstrating environmental, economic, and social benefits and incentives. Two critical factors are the environmental benefits achieved from the use of the biofuel technology and the degree of resilience of the value chain to emergent conditions to ensure steady supply to consumers. Moreover, different biofuel pathways have different costs, benefits, and risks which must be compared. In this paper, we describe how environmental sustainability can be modeled using life cycle assessment (LCA) and how the resilience of value chain initiatives can be modeled using a scenario-based decision model. We then describe how sustainability and resilience assessments can be integrated in an iterative, anticipatory LCA framework. These assessments can be used as the basis for a business case for various investments, as well as a means for promoting responsible innovations, with the aviation industry used as a case study.     

Technology and science: innovation at the International Symposium on Sustainable Systems and Technology

While science advances technology, it is also true that technology advances science. Thus, the two bodies of knowledge are increasingly recognized as interdependent. Nonetheless, recent advances in information communication technology (ICT), in particular, may have profound implications for the norms by which science is conducted. For example, treatment of data will increasingly be in terms of probability distributions, rather than as point estimates, because the cost of computation is now so low that more robust approaches to treatment of uncertainty are within the grasp of normal science. Perhaps more importantly, the techniques by which scientists collaborate, communicate, and curate science are undergoing a rare period of rapid change. The papers in this special section exemplify the evolution of the relationship between technology and science in these two important ways: (1) treatment of data uncertainties and (2) participation in novel methods of publication and review. The latter was fostered by the 2016 meeting of the International Symposium on Sustainable Systems and Technologies (ISSST), at which all of the papers in this special section were presented. This editorial summarizes some of the trends in ICT that are the subject of experimentation in ISSST and introduces the idea that scientific societies in the information age are more likely to take the form of a network than they are likely to look like the societies of the last several centuries.     

Simulated climate adaptation in stormwater systems: evaluating the efficiency of adaptation strategies

Adaptations in infrastructure may be necessitated by changes in temperature and precipitation patterns to avoid losses and maintain expected levels of service. A roster of adaptation strategies has emerged in the climate change literature, especially with regard to timing: anticipatory, concurrent, or reactive. Significant progress has been made in studying climate change adaptation decision making that incorporates uncertainty, but less work has examined how strategies interact with existing infrastructure characteristics to influence adaptability. We use a virtual testbed of highway drainage crossings configured with a selection of actual culvert emplacements in Colorado, USA, to examine the effect of adaptation strategy and culvert characteristics on cost efficiency and service level under varying rates of climate change. A meta-model approach with multinomial regression is used to compare the value of better climate change predictions with better knowledge of existing crossing characteristics. We find that, for a distributed system of infrastructural units like culverts, knowing more about existing characteristics can improve the efficacy of adaptation strategies more than better projections of climate change. Transportation departments choosing climate adaptation strategies often lack detailed data on culverts, and gathering that data could improve the efficiency of adaptation despite climate uncertainty.     

The development of a method to determine the burden of climate change on different health outcomes at a local scale: a case study in Osaka Prefecture,Japan

Climate change impacts human health in a variety of ways. Variables including the climate-related risk factor, the health outcome and location all determine the nature and extent of the impact. The existence of different pathways and endpoints presents a problem for quantifying and comparing impacts. Disability-adjusted life year (DALY) provides a common scale, whereby the impact of climate change on both acute and chronic health outcomes can be compared. This study presents a methodology to calculate the impact of climate change on human health at a local scale, using cardiovascular disease (CVD) and meteorological disaster-related injuries (DRIs) in Osaka Prefecture, Japan, as applied case studies. An additional very fine scale assessment of CVD conducted at the neighbourhood level to demonstrate the importance of conducting risk assessments at a local level. The comparative results calculated the impact of climate change in 2050 to be 16.866 DALY/100,000 population for CVD and 0.645 DALY/100,000 for meteorological DRIs. The actual impact of climate change by 2050 on CVD is judged to be higher, although the relative risk was projected to be lower (1.006, compared to 1.263 for meteorological DRIs). The fine scale assessment revealed the variations in the projected impact of climate change on CVD for all administrative zones in Osaka Prefecture. The range of impacts varied from 0 to 114.29 DALY/100,000. The results demonstrate the applicability of using DALY to quantify the impact of climate change on different health outcomes, using a transferable methodology, and provide information that enables evidence-based prioritisation of climate change adaptation strategies at a local scale.     

Optimizing angles of rooftop photovoltaics,ratios of solar to vegetated roof systems,and economic benefits,in Portland,Oregon, USA

This study analyzed insolation data to account for multiple scattering in calculating optimal tilt angles for stationary and seasonally moving photovoltaics on three different roof types in the US Pacific Northwest: vegetated roofs, white roofs, and dark roofs. Using these results, we modeled the energy savings for vegetated roofs and roofs covered in varying numbers of photovoltaic panels. We then calculated the net present value, internal rate of return, and other economic measures for all possible combinations of covering rooftops in mixes of photovoltaic arrays and vegetation, accounting for installation costs, proposed carbon taxes, stormwater management discounts, and other relevant factors. Our results quantify how, in the US Pacific Northwest and similar locations, photovoltaics produce higher returns on investment than do vegetated roofs for new buildings, while vegetated roofs produce better returns on investment than do photovoltaics for older buildings. This is important because in many areas, some buildings have photovoltaics when a vegetated roof would have been more cost and energy efficient, while other buildings have vegetated roofs when photovoltaics would have been more cost and energy efficient. Potential applications include modifying incentive programs and other policies to account properly for building age, use, and other relevant factors to ensure building owners make the most energy-efficient decisions between photovoltaic versus vegetated roof installation. Our research also demonstrates how positive returns on investment can be realized in the US Pacific Northwest and similar regions through vegetated roofs and photovoltaics provided they are each installed optimally.     

Trends and applications of multi-criteria decision analysis in environmental sciences: literature review

Approximately 3000 papers concerning multi-criteria decision analysis (MCDA) in the environmental field were identified through a series of queries in the Web of Science database and classified by MCDA method and environmental application using text mining in R. Stemming and stop word removal techniques were used to remove irrelevant text from the literature. Trends in MCDA methods (AHP/ANP, TOPSIS, outranking, MAUT/MAVT) associated with specific environmental applications (water, air, energy, natural resources, and waste management) or interventions/tools applications (stakeholders, strategies, sustainability, and GIS) were identified. The results show a linear growth in the share of MCDA papers in environmental science across all application areas. Furthermore, the results show that AHP/ANP and MAUT/MAVT are the most frequently mentioned MCDA methods in the literature. For environmental applications, the results showed that natural resource and waste management keywords were, respectively, the most and least commonly discussed applications within the MCDA papers. For intervention/tool applications, we found that keywords associated with ‘strategy’ and ‘GIS’ applications are, respectively, the most and least commonly discussed keywords within the MCDA papers. The authors found that MCDA method keywords were evenly distributed across the environmental and intervention/tool applications, indicating a lack of preference in the environmental field for use of specific MCDA methods. This paper demonstrates that text mining is an applicable tool to assess specific textual trends and patterns when analyzing larger bodies of MCDA literature.     

Effects of glyphosate and foliar amendments on activity of microorganisms in the soybean rhizosphere

A field study was conducted to determine the effects of glyphosate on microbial activity in the rhizosphere of glyphosate-resistant (GR) soybean and to evaluate interactions with foliar amendments. Glyphosate at 0.84 kg ae ha^{? 1} was applied GR soybean at the V4–V5 development stages. Check treatments included a conventional herbicide tank mix (2003 study only) and no herbicides (hand-weeded). Ten days after herbicide application, a commercially available biostimulant and a urea solution (21.0% N) were applied to soybean foliage at 33.5 mL ha^{? 1} and 9.2 kg ha^{? 1}, respectively. Soil and plant samples were taken 0, 5, 10, 15, 20 and 25 days after herbicide application then assayed for enzyme and respiration activities. Soil respiration and enzyme activity increased with glyphosate and foliar amendment applications during the 2002 growing season; however, similar increases were not observed in 2003. Contrasting cumulative rainfall between 2002 and 2003 likely accounted for differences in soil microbial activities. Increases in soil microbial activity in 2002 suggest that adequate soil water and glyphosate application acted together to increase microbial activity. Our study suggests that general soil microbial properties including those involving C and N transformations are not sensitive enough to detect effects of glyphosate on rhizosphere microbial activity. Measurements of soil-plant-microbe relationships including specific microbial groups (i.e., root-associated Fusarium spp.) are likely better indicators of impacts of glyphosate on soil microbial ecology.     

Gas-phase and semivolatile organic emissions from a modern nonroad diesel engine equipped with advanced aftertreatment

ABSTRACT

U.S. Tier 4 Final and Euro Stage IV and V regulations for nonroad compression-ignition engines have led to the development of exhaust aftertreatment technologies optimized for nonroad engines and duty cycles. In this study, several aftertreatment configurations consisting of state-of-the-art diesel oxidation catalysts (DOCs), diesel particulate filters (DPFs), copper (Cu) zeolite– and vanadium-based selective catalytic reduction (SCR) catalysts, and ammonia oxidation (AMOX) catalysts are evaluated using both nonroad transient (NRTC) and steady (8-mode NRSC) cycles in order to understand both component- and system-level effects of diesel aftertreatment on gas-phase, semivolatile, and particle-phase and particle-bound unregulated organic emissions. Organic emissions reported in this work include total hydrocarbon (THC), n-alkanes, branched alkanes, saturated cycloalkanes, aromatics, aldehydes, ketones, hopanes, steranes, and soluble organic fraction (SOF). Brake-specific emissions are reported for four configurations, including engine-out, DOC+CuZ-SCR+AMOX, V-SCR+AMOX, and DOC+DPF+CuZ-SCR+AMOX, and conversion of engine-out emissions is reported for the three aftertreatment configurations. Mechanisms responsible for the reduction of organic species are discussed in detail. This summary of emissions from a current nonroad diesel engine equipped with advanced aftertreatment can be used to more accurately model the impact of anthropogenic emissions on the atmosphere with tools such as the U.S. Environmental Protection Agency’s Motor Vehicle Emissions Simulator (MOVES2014a) model.

Implications: Anthropogenic emissions are a source of significant human health and environmental risk. This study, focused on the treatment of exhaust emissions from a modern nonroad diesel engine with a variety of aftertreatment configurations, examines the impact that human industrial activity can have on air pollution. In particular, we focus on the remediation of gas-phase and semivolatile organic emissions by emission reduction technologies. This detailed summary of emissions from a current nonroad diesel engine equipped with advanced aftertreatment can be used to more accurately model the impact of anthropogenic emissions on the atmosphere with tools such as the U.S. Environmental Protection Agency’s MOVES2014a model.