Mitigation Options Research Articles

Carbon footprints, mitigation effects and economic performance of dairy farm systems in Inner Mongolia

CONTEXTReducing the GHG emissions intensity of milk production has become a key sustainability challenge for the dairy sector. Addressing this challenge requires thorough understanding of the current GHG emission levels of individual farms, the practices influencing GHG emissions, and the economic trade-offs associated with reducing those emissions. OBJECTIVEQuantify the carbon footprint (CF) and economic performance of milk production in Inner Mongolia (the main dairy farming region in China), and understand the main contributing factors to them. The effects of potential mitigation options at dairy farm system level were evaluated. METHODS: Life cycle assessment methodology was used to analyze the CF of 15 dairy farms (with year-round cow housing and crop feeding) selected for different milk production levels, herd structures and diet composition. RESULTS AND CONCLUSIONSThe average CF per kg of fat and protein corrected milk (FPCM; after allocation to milk) was 2.3 kg carbon dioxide equivalents (CO2-eq) (1.5–3.4 kg CO2-eq). Emissions related to feed production, manure management and enteric fermentation were the top three GHG emission sources and contributed an average of 27% (5%–46%), 28% (19%–38%) and 18% (14%–25%), respectively, to total emissions. The average cost of the farm system per ton FPCM was USD 540 per year. Feed costs dominated at 70% of the total costs. The CF of milk was negatively correlated with profit per kg FPCM. Mitigation potential of the CF of dairy production for single mitigation strategies ranged from 2.3% to 20.0% compared with business as usual, and combined mitigation measures could reduce emissions by 48.3%. The most effective mitigation measures should focus on decreasing N-fertilizer use per ha for feed crop production and increasing feed crop yield, adjusting herd structure for milk productivity and using localized feed inputs. All mitigation measures had a positive impact on farm profit, except for the improved manure management (changing the farms using manure composting to a static compost system and changing natural storage to direct land application). Therefore, the combination of crop and dairy production and manure management offer the greatest potential to reduce the GHG emissions from Inner Mongolia dairy farm systems. Economic subsidies and extension of findings to farmers might encourage more rapid adoption of these technologies. SIGNIFICANCEThe insights from our study can provide guidance for defining and prioritizing mitigation strategies for dairy production to reduce GHGs emission in other rapidly developing countries and regions with crop-based housed-cow dairy production.

Environmental problem shifting from climate change mitigation: A mapping review

Abstract Climate change mitigation will trigger major changes in human activity, energy systems, and material use, potentially shifting pressure from climate change to other environmental problems. We provide a comprehensive overview of such “environmental problem shifting” (EPS). While there is considerable research on this issue, studies are scattered across research fields and use a wide range of terms with blurred conceptual boundaries, such as trade-off, side effect, and spillover. We identify 506 relevant studies on EPS of which 311 are empirical, 47 are conceptual–theoretical, and 148 are synthetic studies or reviews of a particular mitigation option. A systematic mapping of the empirical studies reveals 128 distinct shifts from 22 categories of mitigation options to 10 environmental impacts. A comparison with the recent IPCC report indicates that EPS literature does not cover all mitigation options. Moreover, some studies systematically overestimate EPS by not accounting for the environmental benefits of reduced climate change. We propose to conceptually clarify the different ways of estimating EPS by distinguishing between gross, net, and relative shifting. Finally, the ubiquity of EPS calls for policy design which ensures climate change mitigation that minimizes unsustainability across multiple environmental dimensions. To achieve this, policymakers can regulate mitigation options—for example, in their choice of technology or location—and implement complementary environmental policies.

Assessing body condition scores, weight gain dynamics, and fecal egg counts in feedlot and non-feedlot cattle within high throughput abattoirs of the Eastern Cape Province

IntroductionFeedlots have emerged as an ideal mitigation option to pursue sustainable and efficient livestock production. This paper aims to elucidate how the establishment and widespread adoption of feedlots have provided solutions to complex problems of food security, animal welfare, and environmental sustainability.MethodsAn observational cross-sectional study compared fecal egg count per gram (EPG), weight gain, and body condition score (BCS) in feedlot and non-feedlot cattle at high throughput abattoirs. Cattle (n = 120) of different age and sex groups, farms, and breeds were selected from two commercial abattoirs (EA1 and EA2) in the Eastern Cape Province.ResultsAt EA1, non-feedlot cattle exhibited higher EPG values (323.3±28.9) than feedlot cattle (73.3±13.3), indicating a potentially greater susceptibility to internal parasitic infections. The similar weight gains between feedlot (298.1±4.7) and non-feedlot cattle (287.16±7.79) were attributed to the sufficient natural pasture in the communally raised cattle. However, body condition scores were significantly (P< 0.05) better in feedlot than in non-feedlot cattle. Nonetheless, the feedlot farms of origin had a significant effect (P< 0.05) on the EPG and body condition score values in EA1, with no significant effect in EA2.DiscussionMoreover, the negative correlation between EPG and body condition scores highlights that as parasite load increases, there might be a subtle tendency for body condition to decrease. These results underscore the importance of feedlots as an effective management strategy to improve animal health and productivity. Further investigations into the factors driving the differences in non-feedlot cattle are needed for informed decision-making in livestock management and abattoir operations.

Efficient data-driven prediction of household carbon footprint in China with limited features

Household carbon footprints significantly contribute to global carbon emissions, yet the limited features hinder the accurate assessment in regions with inadequate data. In this study, we developed a data-driven model for evaluating household carbon footprint in China based on a nationwide questionnaire survey. Employing explainable machine learning, we identified the most influential features impacting the model outputs, which were utilized to assess household carbon footprints across Chinese provinces and cities from 2006 to 2021. Additionally, we constructed 27 scenarios with varying peak carbon times, technological evolution pathways, and cumulative carbon budgets to analyze climate change mitigation options for policymakers. The results demonstrate that using the XGBoost-TPE method, the model constructed with only five pivotal features achieves a confidence level of 87.4%. From 2006 to 2021, China's provinces exhibited fluctuating growth trends in household carbon footprints, with economically developed and eastern regions demonstrating higher per capita household carbon footprints. Scenario modelling reveals that combining multiple moderate scenarios yields a 26% increase in effectiveness compared to a single scenario. Promoting low-carbon household food, energy, and transport policies earlier or more aggressively can result in an earlier peak in household carbon footprints and a 2.5% greater carbon reduction.

Environmental sustainability of Finnish pork production: life cycle assessment of climate change and water scarcity impacts

PurposeThe degrading impacts of livestock production on the environment are well acknowledged. Although ruminants are much studied due to their large contribution to climate change impact, monogastrics are also known to carry a significant load, and mitigation options need investigation. Here, the climate change impact and water scarcity impact of Finnish pork production was investigated using the life cycle assessment approach.MethodsAs the importance of communicating reliable environmental information has been acknowledged in the EU, methods and guidance for this purpose have been developed. Product Environmental Footprint Category Rules have also been published for several food product categories, although not yet for meat. Here, the life cycle assessment methods were used based on PEFCR guidance and the draft version of red meat PEFCR guidance to achieve a reliable, transparent and comparable assessment.ResultsFinnish pork production resulted in a climate change impact of 3.6 kg CO2 eq. kgCW−1 and a water scarcity impact of 0.69 m3 eq. kgCW−1. The largest contribution to the climate change impact came from feed crop production, with an impact of 43%. Land-use changes were included, and their contribution to the Finnish pork climate change impact was 3%. Similarly, in the water scarcity impact, feed crop production was a major contributor, with 41% from fattening pig feed production. Significant contributions to both categories also came from piglet production, including feed crop production, and to the climate change impact from manure storage.ConclusionsFinnish production was seen to already largely utilise sidestreams and domestic feed ingredients, although, e.g. soybean is still used. Based on the results, in mitigating the environmental impacts of Finnish pork production, attention should especially be paid to the resource-efficient production of domestic feed crops and reduced use of organic soils. As current assessment models are unable to grasp the impacts of regenerative farming techniques, the development of LCA methods is also required. Water scarcity impact was seen to be largely affected by the utilisation of feed crops originating from water-scarce countries. As a mitigation measure, the procurement of these feed crops and ingredients should therefore be directed to water-abundant areas and from production which does not depend on irrigation water or the extensive use of synthetic inputs.

Projecting future carbon emissions from cement production in developing countries

Achieving low-carbon development of the cement industry in the developing countries is fundamental to global emissions abatement, considering the local construction industry’s rapid growth. However, there is currently a lack of systematic and accurate accounting and projection of cement emissions in developing countries, which are characterized with lower basic economic country condition. Here, we provide bottom-up quantifications of emissions from global cement production and reveal a regional shift in the main contributors to global cement CO2 emissions. The study further explores cement emissions over 2020-2050 that correspond to different housing and infrastructure conditions and emissions mitigation options for all developing countries except China. We find that cement emissions in developing countries except China will reach 1.4-3.8 Gt in 2050 (depending on different industrialization trajectories), compared to their annual emissions of 0.7 Gt in 2018. The optimal combination of low-carbon measures could contribute to reducing annual emissions by around 65% in 2050 and cumulative emissions by around 48% over 2020-2050. The efficient technological paths towards a low carbon future of cement industry vary among the countries and infrastructure scenarios. Our results are essential to understanding future emissions patterns of the cement industry in the developing countries and can inform policies in the cement sector that contribute to meeting the climate targets set out in the Paris Agreement.

Inequalities in Air Pollution Exposure and Attributable Mortality in a Low Carbon Future

AbstractUnderstanding the costs and benefits of climate change mitigation and adaptation options is crucial to justify and prioritize future decarbonization pathways to achieve net zero. Here, we quantified the co‐benefits of decarbonization for air quality and public health under scenarios that aim to limit end‐of‐century warming to 2°C and 1.5°C. We estimated the mortality burden attributable to ambient PM2.5 exposure using population attributable fractions of relative risk, incorporating projected changes in population demographics. We found that implementation of decarbonization scenarios could produce substantial global reductions in population exposure to PM2.5 pollution and associated premature mortality, with maximum health benefits achieved in Asia around mid‐century. The stringent 1.5ºC‐compliant decarbonization scenario (SSP1‐1.9) could reduce the PM2.5‐attributable mortality burden by 29% in 2050 relative to a middle‐of‐the‐road scenario (SSP2‐4.5), averting around 2.9 M annual deaths worldwide. While all income groups were found to benefit from improved air quality through a combination of decarbonization and air pollution controls, the smallest health benefits are experienced by the low‐income population. The disparity in PM2.5 exposure across income groups is projected to reduce by 2100, but a 30% disparity between high‐ and low‐income groups persists even in the strongest mitigation scenario. Further, without additional and targeted air quality measures, low‐ and lower‐middle‐income populations (predominantly in Africa and Asia) will continue to experience PM2.5 exposures that are over three times the World Health Organization Air Quality Guideline.

Feasible supply of steel and cement within a carbon budget is likely to fall short of expected global demand

The current decarbonization strategy for the steel and cement industries is inherently dependent on the build-out of infrastructure, including for CO2 transport and storage, renewable electricity, and green hydrogen. However, the deployment of this infrastructure entails considerable uncertainty. Here we explore the global feasible supply of steel and cement within Paris-compliant carbon budgets, explicitly considering uncertainties in the deployment of infrastructure. Our scenario analysis reveals that despite substantial growth in recycling- and hydrogen-based production, the feasible steel supply will only meet 58–65% (interquartile range) of the expected baseline demand in 2050. Cement supply is even more uncertain due to limited mitigation options, meeting only 22–56% (interquartile range) of the expected baseline demand in 2050. These findings pose a two-fold challenge for decarbonizing the steel and cement industries: on the one hand, governments need to expand essential infrastructure rapidly; on the other hand, industries need to prepare for the risk of deployment failures, rather than solely waiting for large-scale infrastructure to emerge. Our feasible supply scenarios provide compelling evidence of the urgency of demand-side actions and establish benchmarks for the required level of resource efficiency.

Integrating irrational behavior into flood risk models to test the outcomes of policy interventions.

Householders are increasingly responsible for managing residual flood risk at property level. Yet, consumers are observed to adopt irrational behaviors under scenarios of risk, often making suboptimal decisions. Therefore, the question is raised, if householders are required to manage flood risk at household level, how can this be made fair and efficient? Policy instruments often incorporate "fairness" by subsidizing the costs of mitigation options, assuming a linear relationship between available finances and the uptake of risk mitigation measures. To integrate behavior into the assessment of policy instruments, this article develops a method to compare the uptake of flood mitigation between agents following models of Expected Monetary Value (EMV) and Prospect Theory (PT). An agent-based model is created, offering the option to apply either EMV or PT frameworks. EMV represents a rational gamble, determining whether an agent "should" invest in insurance or property-level protection. On the other hand, the PT option incorporates behavioral aspects to examine how agents are likely to respond to investment decisions in flood risk environments. The models are applied to Flood Re, a policy aimed at ensuring affordable insurance access for all individuals in flood risk areas. The results demonstrate that PT models exhibit greater similarity to observed behavior compared to models based on EMV. These findings emphasize the importance of accommodating "irrational" behaviors within the design of policy instruments, promoting fairness and efficiency. Overall, this research provides insights into the integration of behavior in policy assessments and highlights the benefits of considering PT frameworks alongside traditional rational models. By understanding and accounting for human behavior in decision-making processes, policymakers can design more effective and equitable policy instruments for managing flood risk.

Understanding How Reservoir Operations Influence Methane Emissions: A Conceptual Model

Because methane is a potent greenhouse gas (GHG), understanding controls on methane emissions from reservoirs is an important goal. Yet, reservoirs are complex ecosystems, and mechanisms by which reservoir operations influence methane emissions are poorly understood. In part, this is because emissions occur in ‘hot spots’ and ‘hot moments’. In this study, we address three research questions, ‘What are the causal pathways through which reservoir operations and resulting water level fluctuations (WLF) influence methane emissions?’; ‘How do influences from WLF differ for seasonal drawdown and diurnal hydropeaking operations?’; and ‘How does understanding causal pathways inform practical options for mitigation?’. A graphical conceptual model is presented that links WLF in reservoirs to methane emissions via four causal pathways: (1) water-column mixing (2) drying–rewetting cycles, (3) sediment delivery and redistribution, and (4) littoral vegetation. We review what is known about linkages for WLF at seasonal and diurnal resolutions generate research questions, and hypothesize strategies for moderating methane emissions by interrupting each causal pathway. Those related to flow management involve basin-scale management of tributary flows, seasonal timing of hydropeaking (pathway #1), timing and rates of drawdown (pathway #2). In addition, we describe how sediment (pathway #3) and vegetation management (pathway #4) could interrupt linkages between WLF and emissions. We demonstrate the strength of conceptual modeling as a tool for generating plausible hypotheses and suggesting mitigation strategies. Future research is needed to develop simpler models at appropriate timescales that can be validated and used to manage flow releases from reservoirs.

Unwitting Participants at Our Expense: A/B Testing and Digital Exploitation

Firms use A/B testing, a methodology to compare two or more versions of ideas to see which one performs better, to decide on features of their digital products and services. Although A/B testing brings benefits, some A/B testing can lead to digital exploitation (i.e., appropriating resources from users to increase firms’ performance). We explicate why A/B testing can lead to digital exploitation, suggest mitigation options by establishing Institutional Review Boards, explicitly seeking users’ consent, and implementing incentive schemes, and conclude with research directions on this topic.

Opportunities for mitigating net system greenhouse gas emissions in Southeast Asian rice production: A systematic review

Southeast Asia (SEA) is a key producer and exporter of rice, accounting for around 28% of rice produced globally. To effectively mitigate greenhouse gas (GHG) emissions in SEA rice systems, field methane (CH4) and nitrous oxide (N2O) emissions have been intensively studied. However, an integrated assessment of system-level GHG emissions which includes other carbon (C) balance components, such as soil organic carbon (SOC) or energy use, that can positively or negatively influence the net capacity for climate change mitigation is lacking. We conducted a systematic review of published research in SEA rice systems to synthesize findings across four main components of net system emissions: (1) field GHG emissions, (2) energy inputs, (3) residue utilization beyond the field, and (4) SOC change. The objectives were to highlight effective mitigation opportunities and explore cross-component effects to identify tradeoffs and key knowledge gaps. Field GHG emissions were the largest contributor to net system emissions in agreement with existing scientific consensus, with results showing that practices such as floodwater drainage and residue removal are sound options for CH4 mitigation. On the other hand, increasing SOC potentially provides a large GHG mitigation opportunity, with long-term continuous rice cropping and practices such as residue incorporation and biochar application promoting SOC increase. A reduction in energy inputs was mainly achieved by optimizing agrochemical use, especially N fertilizers. For residue utilization beyond the field, GHG emission mitigation mainly came from preventing open field burning through residue removal. Removed residue can subsequently be used for producing energy that offsets GHG emissions associated with conventional fuel sources (e.g. fossil fuel-based electricity generation) or substituting material used in other production systems. Integrating all four components of net system emissions into one analysis underscores the following two main takeaways. First, the components of field GHG emissions and SOC change are the biggest opportunities for reducing net system emissions and need to be considered for effective climate change mitigation. Second, the reduction of C inputs through residue removal and increased soil aeration through multiple drainage will lower CH4 emissions but may also potentially decrease SOC stocks over time. Hence, we argue that future research needs to consider cross-component effects to optimize net system emissions, specifically the “stacking” of best management practices for mitigation related to field GHG emissions or SOC change in long-term experiments.

Does rice paddy management increase soil organic carbon in the warm temperate and tropical regions?

Enhancing soil organic carbon (SOC) storage in agricultural fields is an effective option for climate change mitigation and food security. In temperate regions, rice farming under paddy is known to increase SOC stock due mainly to the reduced decomposition caused by prolonged submerged conditions compared to the cropping practices under non-flooded conditions. It remains unclear, however, if and to what extent rice paddy management increases SOC storage in warmer climate regions where decomposition is much faster. We thus examined the factors controlling the SOC stock and the net change in SOC normalized to the duration under paddy (ΔSOC) at paddy fields in warm temperate (21 sites) and tropical climatic regions (11 sites) from peer-reviewed literature which was concentrated to Asia. Using collected data (e.g., SOC content, bulk density, mean annual temperature (MAT), precipitation, management duration, soil management, crop rotation), we evaluated predictor variables that account for ΔSOC variability (i.e., mean decrease accuracy) by random forest regression. The mean paddy duration for all data (n = 170) was 22 years. Average SOC stock and ΔSOC at 0–20 cm depth were 38 ± 1.45SE Mg C ha−1 and 0.34 ± 0.04SE Mg C ha−1 yr−1, respectively, indicating that continuous paddy management had a positive effect on SOC storage in both climatic regions. SOC stock was two-fold higher and ΔSOC was four-fold higher in the warm temperate region compared to the tropical region (p < 0.05). The best predictor variables for ΔSOC were MAT followed by soil management and then paddy duration. While organic amendment including both straw and manure increased ΔSOC in both warm temperate and tropical paddies, we did not detect a positive effect of chemical fertilizer application alone or crop rotation type (e.g., rice-upland vs rice-rice). Despite high variability, ΔSOC in the warm temperate region significantly declined over time from 0.82 ± 0.10 Mg C ha−1 yr−1 (< 20 yrs) to 0.22 ± 0.06 Mg C ha−1 yr−1. While SOC stock was 50% lower, the tropical paddies showed no clear decline in ΔSOC up to 41 years (0.04–0.21 Mg C ha−1 yr−1). These results suggest that SOC accretion might have reached equilibrium after 20 years of paddy practice in the warm temperate region and, if so, ΔSOC is likely to diminish to zero in the near future. In tropical paddy fields, on the other hand, slow SOC build-up may continue for a longer term although the ΔSOC value itself is not high. While the current study showed the efficacy of paddy management on SOC build-up under the warmer climate regions, further study on the rate and qualitative changes is necessary to evaluate the trade-offs between soil fertility improvement (e.g., soil N build-up) and methane emission.

Market-pull, technology-push, and regulatory stringency determinants: All in need in firms' decisions for large-scale demonstration of direct air capture technologies

Carbon dioxide removal approaches such as direct air carbon capture and storage (DACCS) technologies have come to the fore as essential mitigation options to limit the increase in global warming to 1.5 °C. Previous studies have touched upon the technical, economic, environmental, and social and political feasibilities of DACCS technologies. These studies have commonly found that these technologies are not yet suitable for widespread deployment. However, large-scale demonstration projects have recently been successful, and facility construction for deployment is ongoing. There is a lack of studies exploring firm-level behaviors in DACCS technologies. What behavioral determinants are responsible for firms undertaking large-scale demonstrations and deployment with innovative but uncertain DACCS technologies? Using an analytical framework that included market pull, technology push, and regulatory stringency determinants, a case study of the firm, Carbon Engineering, was conducted. The results reveal that the most important determinants are regulatory factors that are vital for mobilizing financial resources.

307 Hothog: a Smartphone Application to Support Environmental Management Decisions for Non-Pregnant and Gestating Sows

Abstract Several management practices and technologies have been developed to mitigate thermal stress in swine. However, recommended temperature thresholds for implementing thermal stress mitigation are variable and may not accurately reflect the thermal requirements of non-pregnant and gestating sows with modern genetics. Therefore, a tool to support environmental management decisions for non-pregnant and gestating sows was created. The decision support tool is based on several published works by our group that characterized responses of non-pregnant, mid-gestation, and late-gestation sows across a wide temperature range. Cool, comfortable, and warm ranges were identified based upon behavioral thermal preferendum, and physiological responses were used to determine mild, moderate, and severe heat stress thresholds. The inflection points of respiration rate and body temperature as a function of dry bulb temperature were used to establish heat stress thresholds by gestation stage. Non-pregnant, mid-gestation, and late-gestation sow mild heat stress thresholds differed (P &amp;lt; 0.05) and occurred at 25.5, 25.1, and 24.0 °C, respectively. Body temperature inflection points indicative of moderate heat stress differed by gestation stage (P &amp;lt; 0.05) and occurred at 28.1, 27.8, and 25.5 °C, respectively. Severe heat stress inflection points were lower (P &amp;lt; 0.05) for late-gestation sows (30.8 °C) but were similar for non-pregnant and mid-gestation sows (32.9 °C). Dewpoint influenced heat stress response for mid- and late-gestation sows (P &amp;lt; 0.05) but did not have an effect on non-pregnant sows (P &amp;gt; 0.05). Heat stress threshold data were integrated with behavioral thermal preferendum data. For non-pregnant and mid-gestation sows, similar (P &amp;gt; 0.05) cool (&amp;lt; 13.2°C) and comfortable (13.2 to 16.4°C) temperature ranges were observed. However, late-gestation sows had lower (P &amp;lt; 0.05) cool (&amp;lt; 12.6°C) and comfortable (12.6 to 15.6°C) temperature ranges relative to non-pregnant and mid-gestation sows. The dry bulb temperature (TDB) that non-pregnant, mid-gestation, and late-gestation sows found to be warm was estimated as TDB preference range &amp;lt; TDB &amp;lt; mild heat stress. The decision support tool was integrated into a smartphone application called HotHog. This smartphone application provides hourly and daily predictions of thermal comfort and stress in non-pregnant, mid-gestation, and late-gestation sows. Users can set geographical locations, either manually or by current location, for thermal index predictions. Additionally, hourly and daily precipitation, and temperature predictions are displayed for the selected location. Management observations and mitigation options, as well as expected physiological and behavioral changes, are provided for each thermal index category to help users identify stressed pigs and assist with management decisions. HotHog will support swine producers in making more informed decisions related to in-barn environmental management to reduce the negative effects of thermal stress on sows and their gestating offspring. Furthermore, the tool may be helpful for teaching thermal management to livestock technicians and students.

Flood Inundation mapping and mitigation options in data-scarce region of Beledwayne town in the Wabi Shebele River Basin of Somalia

Somalia has experienced extreme flash floods in recent years across the arid regions causing tremendous loss of lives and properties. However, the flood magnitude, depth, and frequency of occurrence are not yet quantified. This is mainly due to scarce datasets in the area. . In this study, integration of observed and Climate Hazards Infrared Precipitation (CHIRP) satellite rainfall products and remote sensing raster data were used to improve hydrological model simulation outputs. The Hydrologic Engineering Center namely HEC-HMS and HEC-RAS models were used to simulate the rainfall-runoff processes and flood inundation, respectively. The land use, soil, slope and Digital Elevation map (DEM) were used to set-up the models and generate outputs. The HEC-HMS model calibration results depict that the model is able to reproduce the observed streamflow The simulated flows generated by the model predicted good agreement with the observed flow with values of 0.79, 0.74, 0.78, and 0.78 evaluated through the Nash and Sutcliffe Efficiency (NSE), Runoff Volume Error (RVE), coefficient of determination (R2), and percentage error of peak flow (PEPF), respectively. The HEC-RAS model result indicates that the maximum flood depth and velocity were obtained at the floodplain area. The peak flood at 50, 100, and 200-year return period using General Extreme Value (GEV) distribution revealed 384m3s-1, 409m3s-1, and 434m3s-1, respectively. The 100-year peak flood discharge in a specific part of the river revealed a flood depth of 7.53m. The provision of Levees as mitigation measures revealed reduction of the flood extent by 35% and suggested as possible flood protection measures for the study area.

Game-Theoretic Capacity Expansion Analysis Under Carbon Emission Constraints

In this paper, we develop a long-term capacity expansion analysis model that considers strategic bidding behavior by dominant generation companies together with new entry decisions, including renewables, to meet a long-term carbon reduction constraint. We deploy a centralized quadratic programming formulation of the Nash-Cournot game to analyze day-ahead electricity market prices. In our model, strategic producers simultaneously make investment and production decisions, deploying an open-loop Cournot game. We have implemented the model for Ukraine's day-ahead electricity market, which has been highly prone to market power issues. The case study results show significant inefficiencies in peak prices and explore scenarios of alternative mitigation options and their efficacies. Finally, the case study is extended to also explore implications of a low carbon future through emission-constrained runs, evaluation of the performance-based emission policy, and sensitivity on different portfolios of new renewable investors.

A spatially explicit model of landscape pesticide exposure to bees: Development, exploration, and evaluation

Pesticides represent one of the greatest threats to bees and other beneficial insects in agricultural landscapes. Potential exposure is generated through compound- and crop-specific patterns of pesticide use over space and time and unique degradation behavior among compounds. Realized exposure develops through bees foraging from their nests across the spatiotemporal mosaic of floral resources and associated pesticides throughout the landscape. Despite the recognized importance of a landscape-wide approach to assessing exposure, we lack a sufficiently-evaluated predictive framework to inform mitigation decisions and environmental risk assessment for bees. We address this gap by developing a bee pesticide exposure model that incorporates spatiotemporal pesticide use patterns, estimated rates of pesticide degradation, floral resource dynamics across habitats, and bee foraging movements. We parameterized the model with pesticide use data from a public database containing crop-field- and date-specific records of uses throughout our study region over an entire year. We evaluate the model performance in predicting bee pesticide exposure using a dataset of pesticide residues in pollens gathered by bumble bees (Bombus vosnesenskii) returning to colonies across 14 spatially independent landscapes in Northern California. We applied alternative model formulations of pesticide accumulation and degradation, floral resource seasonality, and bee foraging behavior to evaluate different levels of detail for predicting observed pesticide exposure. Our best model explained 73 % of observed variation in pesticide exposure of bumble bee colonies, with generally positive correlations for the dominant compounds. Timing and location of pesticide use were integral, but more detailed parameterizations of pesticide degradation, floral resources, and bee foraging improved the predictions little if at all. Our results suggest that this approach to predict bees' pesticide exposure has value in extending from the local field scale to the landscape in environmental risk assessment and for exploring mitigation options to support bees in agricultural landscapes.

Solar photovoltaic systems for the Short Sea Shipping’s compliance with decarbonization regulations in the European Union

Carbon Intensity Indicator (CII) regulation came into force In January 2023 as one of the main International Maritime Organization’s measures to reduce Greenhouse Gas (GHG). Short Sea Shipping (SSS) demand significant electricity supply by reaching up to 30% of total on-board power. This paper addresses SSS-fleet compliance with CII regulation, Market and Goal-Based Measures imposed by the European Union (EU) through solar photovoltaic systems (PV) for on-board electricity production. The paper analyses the techno-economic feasibility of this solution from the shipowners’ standpoint in the medium-term. To meet this aim, a SSS Car-carrier between Canary Islands and Iberian Peninsula is assessed by simulating PV performance, vessel’s technical implications, and economic consequences of GHG mitigation in the context of the EU. The results reveal that PV reduces fuel consumption for electricity generation by 15.5% by reducing the total CO2 emissions by 3.38%. Although this improvement is not substantial enough to change the CII score of the vessel, the Internal Rate of Return of the PV investment achieved 55% for 10 years with three years as payback period. This fact along with the robustness of the results achieved suggest PV system is a promising mitigation option for SSS vessels.

Effects of flight crew role assignment on aviation accidents and incidents: Evidence of a systemic safety issue

To investigate whether a reported association between flight crew role assignment and accident/incident frequency has persisted subsequent to reforms introduced to address it, we analyze global civil aviation data on 841 accidents and safety critical incidents for the period 2000–2020 resulting in 5318 fatalities. We find that significantly more such events occur, and significantly more fatalities result, when the Captain (Pilot-in-Command) rather than the Co-pilot (Second-in-Command) is acting on the controls as “Pilot Flying” rather than acting as “Pilot Monitoring” – prima facie evidence that the regular combination of command and control (Pilot-in-Command as Pilot Flying) presents a significant systemic safety risk. The yearly proportion of events with the Pilot-in-Command as Pilot Flying significantly increased over 2000–2020. Moreover most (72.2%) events occurred in the absence of any emergency, in technically airworthy aircraft and most (87.9%) were also judgmentally assessed as preventable by the flight crew. Our findings are consistent with accounts of the crew assignment effect that invoke role-dependent status hierarchy effects interfering with effective monitoring and with cognitive overload debilitating the Pilot-in-Command when assigned as the Pilot Flying. We interpret these findings as evidence that measures specifically introduced to implement effective flight crew teamwork, such as Crew Resource Management training, fail to prevent ineffective flight crew teamwork. We consider the implications of our findings for the aviation industry and present options for mitigation and issues for further research.