CEO education and corporate environmental footprint

We analyze the effect of CEO education on environmental decision-making. Using a unique sample of Danish firms from 1996 to 2012, we find that CEO education significantly improves firms' energy efficiency. We seek to derive causality using health shocks: the hospitalization of highly educated CEOs induces a drop in energy efficiency, whereas the hospitalization of less educated CEOs does not have any significant effect. Exploring the mechanisms at play, we show that our results are largely driven by advanced education in business degrees. Moreover, we show that CEO education is associated with greater environmental awareness: highly educated CEOs exhibit greater concerns for climate change, as measured by a survey of social preferences, and drive more environmentally efficient cars. Taken together, our findings suggest that education shapes managerial styles giving rise to greater sustainability in corporate actions.     

Learning and climate feedbacks: Optimal climate insurance and fat tails

We study the effect of potentially severe climate change on optimal climate change policy, accounting for learning and uncertainty in the climate system. In particular, we test how fat upper tailed uncertainty over the temperature change from a doubling of greenhouse gases (the climate sensitivity), affects economic growth and emissions policy. In addition, we examine whether and how fast uncertainties could be diminished through Bayesian learning. Our results indicate that while overall learning is slow, the mass of the fat tail diminishes quickly, since observations near the mean provide evidence against fat tails. We denote as “tail learning” the case where the planner rejects high values of the climate sensitivity with high confidence, even though significant uncertainty remains. Fat tailed uncertainty without learning reduces current emissions by 38% relative to certainty, indicating significant climate insurance, or paying to limit emissions today to reduce the risk of very high temperature changes, is optimal. However, learning reduces climate insurance by about 50%. The optimal abatement policy is strongly influenced by the current state of knowledge, even though greenhouse gas (GHG) emissions are difficult to reverse. Once the mass of the fat tail diminishes, the remaining uncertainty is largely irrelevant for optimal emissions policy.     

Climate change and soil salinity: The case of coastal Bangladesh

This paper estimates location-specific soil salinity in coastal Bangladesh for 2050. The analysis was conducted in two stages: First, changes in soil salinity for the period 2001–2009 were assessed using information recorded at 41 soil monitoring stations by the Soil Research Development Institute. Using these data, a spatial econometric model was estimated linking soil salinity with the salinity of nearby rivers, land elevation, temperature, and rainfall. Second, future soil salinity for 69 coastal sub-districts was projected from climate-induced changes in river salinity and projections of rainfall and temperature based on time trends for 20 Bangladesh Meteorological Department weather stations in the coastal region. The findings indicate that climate change poses a major soil salinization risk in coastal Bangladesh. Across 41 monitoring stations, the annual median projected change in soil salinity is 39 % by 2050. Above the median, 25 % of all stations have projected changes of 51 % or higher.     

A new synergetic paradigm in environmental numerical modeling: Hybrid models combining deterministic and machine learning components

A new type of environmental numerical models, hybrid environmental numerical models (HEMs) based on combining deterministic modeling and machine learning components, is introduced and formulated. Conceptual and practical possibilities of developing HEM, as an optimal synergetic combination of the traditional deterministic/first principles modeling (like that used for solving PDEs on the sphere representing model dynamics of global climate models) and machine learning components (like accurate and fast neural network emulations of model physics or chemistry processes), are discussed. Examples of developed HEMs (hybrid climate models and a hybrid wind–wave ocean model) illustrate the feasibility and efficiency of the new approach for modeling extremely complex multidimensional systems.     

Ancillary benefits of reduced air pollution in the US from moderate greenhouse gas mitigation policies in the electricity sector

Actions to slow atmospheric accumulation of greenhouse gases also would reduce conventional air pollutants yielding “ancillary” benefits that tend to accrue locally and in the near-term. Using a detailed electricity model linked to an integrated assessment framework to value changes in human health, we find a tax of $25 per metric ton of carbon emissions would yield NO_x-related health benefits of about $8 per metric ton of carbon reduced in the year 2010 (1997 dollars). Additional savings of $4–$7 accrue from reduced investment in NO_x and SO₂ abatement in order to comply with emission caps. Total ancillary benefits of a $25 carbon tax are $12–$14, which appear to justify the costs of a $25 tax, although marginal benefits are less than marginal costs. At a tax of $75, greater total benefits are achieved but the value per ton of carbon reductions remains roughly constant at about $12.     

煤矿井下气候参数和劳动强度对矿工生理参数影响的研究

对机械化采煤工作面的采煤机司机和支柱工的劳动心率和能量代谢进行了现场实测。就气候参数和劳动强度对作业人员的生理参数影响进行了模拟实验,取得一些实验研究成果。对改善劳动条件和作业环境,提高生产效率,保护井下矿工的身心健康与安全,提供了科学依据。     

1994年江淮伏旱及其影响研究

利用江谁地区18个站点1951～1995年6～8月降水量资料,用Z指数建立了历年夏季旱涝序列,着重对1994年江淮伏旱及其对农业、水资源的影响进行了分析评述,获得了一些有意义的结论。     

Prospects for a multi-stakeholder dialogue on climate engineering

ABSTRACT

Lessons from the literature on multi-stakeholder dialogue (MSD) that are relevant to the debate on climate engineering (CE) are examined. MSDs have been used to prod slow-to-develop intergovernmental regulatory processes on a range of transnational and global controversies. A CEMSD might push forward anticipatory governance of CE by promoting social learning, sharpening and legitimizing governance norms, and starting to arrange the political space for governance by states. However, significant challenges and risks are also identified, including questions about the ripeness of the issue for stakeholder dialogue; difficult trade-offs in the design of dialogues, particularly around issues of participation and knowledge-power; and inherent tensions in the various purposes a CEMSD might serve. Given these challenges, steps forward that would better prepare a space for legitimate and effective dialogue are recommended.     

Simulated dynamics of carbon stocks driven by changes in land use, management and climate in a tropical moist ecosystem of Ghana

Sub-Saharan Africa is large and diverse with regions of food insecurity and high vulnerability to climate change. This project quantifies carbon stocks and fluxes in the humid forest zone of Ghana, as a part of an assessment in West Africa. The General Ensemble biogeochemical Modeling System (GEMS) was used to simulate the responses of natural and managed systems to projected scenarios of changes in climate, land use and cover, and nitrogen fertilization in the Assin district of Ghana. Model inputs included historical land use and cover data, historical climate records and projected climate changes, and national management inventories. Our results show that deforestation for crop production led to a loss of soil organic carbon (SOC) by 33% from 1900 to 2000. The results also show that the trend of carbon emissions from cropland in the 20th century will continue through the 21st century and will be increased under the projected warming and drying scenarios. Nitrogen (N) fertilization in agricultural systems could offset SOC loss by 6% with 30 kg N ha⁻¹ year⁻¹ and by 11% with 60 kg N ha⁻¹ year⁻¹. To increase N fertilizer input would be one of the vital adaptive measures to ensure food security and maintain agricultural sustainability through the 21st century.     

Does weather shape rodents? Climate related changes in morphology of two heteromyid species

Geographical variation in morphometric characters in heteromyid rodents has often correlated with climate gradients. Here, we used the long-term database of rodents trapped in the Sevilleta National Wildlife Refuge in New Mexico, USA to test whether significant annual changes in external morphometric characters are observed in a region with large variations in temperature and precipitation. We looked at the relationships between multiple temperature and precipitation variables and a number of morphological traits (body mass, body, tail, hind leg, and ear length) for two heteromyid rodents, Dipodomys merriami and Perognathus flavescens. Because these rodents can live multiple years in the wild, the climate variables for the year of the capture and the previous 2 years were included in the analyses. Using multiple linear regressions, we found that all of our morphometric traits, with the exception of tail length in D. merriami, had a significant relationship with one or more of the climate variables used. Our results demonstrate that effects of climate change on morphological traits occur over short periods, even in noninsular mammal populations. It is unclear, though, whether these changes are the result of morphological plasticity or natural selection.