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A Tool for Air Pollution Scenarios (TAPS v1.0) to enable global, long-term, and flexible study of climate and air quality policies

Authors' Summary: Understanding policy effects on human-caused air pollutant emissions is key for assessing related health impacts. We develop a flexible scenario tool that combines updated emissions data sets, long-term economic modeling, and comprehensive technology pathways to clarify the impacts of climate and air quality policies. Results show the importance of both policy levers in the future to prevent long-term emission increases from offsetting near-term air quality improvements from existing policies.

Abstract: Air pollution is a major sustainability challenge – and future anthropogenic precursor and greenhouse gas (GHG) emissions will greatly affect human well-being. While mitigating climate change can reduce air pollution both directly and indirectly, distinct policy levers can affect these two interconnected sustainability issues across a wide range of scenarios.

We help to assess such issues by presenting a public Tool for Air Pollution Scenarios (TAPS) that can flexibly assess pollutant emissions from a variety of climate and air quality actions, through the tool’s coupling with socioeconomic modeling of climate change mitigation. In this study, we develop and implement TAPS with three components: recent global and fuel-specific anthropogenic emissions inventories, scenarios of emitting activities to 2100 from the MIT Economic Projection and Policy Analysis (EPPA) model, and emissions intensity trends based on recent scenario data from the Greenhouse Gas–Air Pollution Interactions and Synergies (GAINS) model.

An initial application shows that in scenarios with less climate and pollution policy ambition, near-term air quality improvements from existing policies are eclipsed by long-term emissions increases – particularly from industrial processes that combine sharp production growth with less stringent pollution controls in developing regions. Additional climate actions would substantially reduce air pollutant emissions related to fossil fuel (such as sulfur and nitrogen oxides), while further pollution controls would lead to larger reductions for ammonia and organic carbon (OC).

Future applications of TAPS could explore diverse regional and global policies that affect these emissions, using pollutant emissions results to drive global atmospheric chemical transport models to study the scenarios’ health impacts.

Assessing Compounding Risks Across Multiple Systems and Sectors: A Socio-Environmental Systems Risk-Triage Approach

Abstract: Physical and societal risks across the natural, managed, and built environments are becoming increasingly complex, multi-faceted, and compounding. Such risks stem from socio-economic and environmental stresses that co-evolve and force tipping points and instabilities. Robust decision-making necessitates extensive analyses and model assessments for insights toward solutions.  However, these exercises are consumptive in terms of computational and investigative resources. In practical terms, such exercises cannot be performed extensively – but selectively in terms of priority and scale. Therefore, an efficient analysis platform is needed through which the variety of multi-systems/sector observational and simulated data can be readily incorporated, combined, diagnosed, visualized, and in doing so, identifies “hotspots” of salient compounding threats. In view of this, we have constructed a “triage-based” visualization and data-sharing platform – the Socio-Environmental Systems Risk Triage (SESRT) – that brings together data across socio-environmental systems, economics, demographics, health, biodiversity, and infrastructure. Through the SESRT website, users can display risk indices that result from weighted combinations of risk metrics they can select. Currently, these risk metrics include land-, water-, and energy systems, biodiversity, as well as demographics, environmental equity, and transportation networks. We highlight the utility of the SESRT platform through several demonstrative analyses over the United States from the national to county level. The SESRT is an open-science tool and available to the community-at-large.  We will continue to develop it with an open, accessible, and interactive approach, including academics, researchers, industry, and the general public.

 

Photo credit: Flickr Creative Commons, James Marvin Phelps

Decarbonizing the global shipping industry: Evaluating pathways for alternative fuels

Abstract: Achieving net-zero emissions across all sectors, including the shipping industry, which relies heavily on fossil fuels and traditional internal combustion engines for propulsion, is critical to mitigating climate change and limiting global temperature rise. This thesis evaluates decarbonizing pathways for the global shipping industry through alternative fuels.

The decarbonization pathways for shipping are constructed by considering significant system decisions, including powertrains, fuel types, and feedstock. Each pathway is assessed based on cost and multi-attribute utility using system-level metrics relevant to shipping. For alternative fuels, fuel cost models have been developed to estimate the levelized cost of production based on varying electricity prices, natural gas prices, and capital and operating expenditure assumptions. With the fuel cost model results, the total cost of ownership models of bulk carrier vessels has been developed to calculate and compare the lifetime cost for operating vessels for various alternative fuel pathways. The cost models provide insights into the cost markup of alternative fuel pathways relative to the conventional fuels of maritime ships. The MIT’s Economic Projection and Policy Analysis (EPPA) model has been enhanced to represent a low-emission shipping option to assess the economic impact and make projections on the market share of the alternative fuel pathway through 2050. Required investment to enable low-emission shipping to enter the market has been estimated using the EPPA model.

Combining findings from the multiattribute utility, including lifecycle emissions of alternative fuels and economic modeling results, near-term, medium-term, and long-term pathways for low-emission shipping have been proposed.

Incorporating dynamic crop growth processes and management practices into a terrestrial biosphere model for simulating crop production in the United States: Toward a unified modeling framework

Abstract: Agricultural decision-making by different interest groups (e.g., farmers, development agents and policymakers) usually takes place on different scales (e.g., plot, landscape and country). Currently, tools to assist decision-making
are either dedicated to small-scale management guidance or large-scale assessment, which ignore the cross-scale linkages and interactions and thus may not provide robust and consistent guidance and assessment. 

Here, we developed an advanced agricultural modeling framework by integrating the strengths of conventional crop models in representing crop growth processes and management practices into a terrestrial biosphere model
(TBM), the Dynamic Land Ecosystem Model (DLEM), to meet the cross-scale application needs (e.g., adaptation and mitigation). Specifically, dynamic crop growth processes, including crop-specific phenological development,
carbon allocation, yield formation, biological nitrogen fixation processes, and management practices such as tillage, cover cropping and genetic improvements, were explicitly represented in DLEM.

The new model was evaluated against site-scale observations, and the results showed that the model performed generally well, with an average normalized root mean square error of 19.91% for leaf area index and 17.46% for aboveground biomass
at the seasonal scale and 14.42% for annual yield. Then the model was applied to simulate corn, soybean, and winter wheat productions in the conterminous United States from 1960 to 2018. The spatial patterns of simulated crop productions were consistent with ground survey data. Our model also captured both the long-term trends and interannual variations of the total national productions of the three crops.

This study demonstrates the significance of fusing conventional crop modeling techniques into TBMs to establish a unified modeling framework, which holds the potential to address climate impacts, adaptation and mitigation across varied spatiotemporal scales.

Highlights:

• A unified agricultural modeling framework is implemented in DLEM v4.0. 

• Simulated results agree well with site-scale LAI, biomass and yield measurements.

• Regional simulations can well reproduce spatial-temporal patterns of crop production.
 
• DLEM v4.0 can be used to support agricultural climate adaptation and mitigation.

A recent study in the journal Nature found that in order to avert the worst impacts of climate change, most of the world’s known fossil fuel reserves must remain untapped. According to the study, 90% of coal and nearly 60% of oil and natural gas must be kept in the ground in order to maintain a 50% chance that global warming will not exceed 1.5 degrees Celsius above pre-industrial levels.

Stranded assets could exact steep costs on fossil energy producers and investors

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