Impact of variation in climatic factors on crop yield

Project by Prabhat Barnwal:

This study examines the effects of temperature and precipitation on mean and

variance of seasonal rice yield in Andhra Pradesh, India. Two distinct approaches are employed: stochastic production function and quantile regression. The findings suggest adverse impact of temperature rise on mean rice yield as well as its variability. Furthermore, quantile regression reveals that rice yield’s sensitivity to climate change differs significantly across the quantiles of yield distribution. International University of Japan Working paper.

Journeys toward Sustainable Development: Policy Entrepreneurs and the Rise of the Green State in Chile and Peru

Project by Jose Carlos Orihuela (completed thesis):

Journeys inquire why and how mineral-rich Chile and Peru joined in the international trend of good green governance. Behind formal governance convergence hides effective institutional divergence: a relatively strong and autonomous green state in Chile and a relatively weak and captured green state in Peru. The “green state” comprises ministries of the environment, transsectoral regulatory agencies, national standards of environmental quality, systems of protected areas, and citizen participation schemes. Inquiring on the agency of policy-entrepreneurs , the dissertation shows how legacy, opportunity, and agency shape institutional change. The thesis uses a political economy approach, building on analytic frameworks and methods from institutional schools in the social sciences.

The effects of convective clouds on transport of pollutants using a numerically simulated flow field

Project by Nicole Ngo:

In the planetary boundary layer (PBL) (loosely defined as the layer < 1 km above the surface), pollutants travel smaller distances and have shorter residence times relative to those in the upper troposphere.  As a result, understanding the processes by which pollutants can be transported to the upper troposphere is critical. One way this can occur is by deep convective cloud systems. In this study, we observe how deep convection influences the distribution of an insoluble or less soluble chemical species, like carbon monoxide (CO), O3, and NOx, within the troposphere. This is done by using a Lagrangian approach that traces particles along a simulated time-evolving, three-dimensional wind field associated with a deep convection system.

Air pollution in urban areas in Sub-Saharan Africa

Project by Nicole Ngo:

There are few large urban areas in Sub-Saharan Africa (SSA), but the cities in SSA are rapidly expanding.  As such, there is increasing concern over urban planning and coping with a growing urban population, including mitigating environmental health problems.  Of particular concern is air pollution.  There have been few studies examining urban air pollution in SSA (to my knowledge, < 5 studies), but a 2-week study in the summer of 2009 in Nairobi found that particulate matter (PM) emitted from vehicles was more than 10 times that of World Health Organization standards.  This project will continue the efforts to monitor urban air pollution in Nairobi, not only for its health impacts but also its influence on climate change.

Measurements of black carbon from vehicles in New York City

Project by Nicole Ngo:

There is concern over the public health issues concerning black carbon (BC), a species of particulate matter.  One major source of BC in urban areas is vehicles that use diesel, such as trucks or buses.  To examine population exposure, studies have used data from monitors that  measure background pollution, since they are cheaper than having individuals carry around monitors.  Though, there’s evidence that BC decays quickly from sources, such as roadways.  As a result, monitors may not properly capture population exposure.  To better understand if monitors are capturing some trend from the road or pure noise, I use the Clean Fuel Bus Program in NYC to see if variations in types of buses (e.g., diesel buses, hybrid buses, CNG buses) along bus routes by monitors are captured by the monitors.

Purchase Feedback

Project by James Rising:

This project is part research and part social entrepreneurship.  The goal is to construct a software system that can evaluate the unintended consequences of individual purchases, and match them to charities that ameliorate those specific effects.  Using this framework, consumers could get detailed information about the effects of their purchases and have an easy way to respond to that information, just by copying their credit card statements or entering their receipts on a website, or (in collaboration with a store’s customer-tracking system) getting the information immediately when buying their items.

An Open Model of Climate Change Behaviors

Project by James Rising:

The behaviors that produce climate change are overdetermined and systemic, but that fact suggests that there exist “leverage points” within society where small policy changes will have big effects on these behaviors.  The goal of this project is to generate a new style of system dynamical model of society, at a sufficiently high level of granularity to identify those policies and institutions.  Some complimentary goals include the incorporation of fractal networks into system dynamics, producing an online interface for researchers to contribute and run simulations, and develop a numerical framework to analyze the coherence and local-significance of the model elements.

Flooding in Pakistan

Project by James Rising (with Prof. John Mutter):

This research has two complementary directions: studying the projected evolution of flood variability in the Himalayan floodplain with respect to glacier melt. What portion of the current flooding along Himalayan rivers is attributable to glacier melt, and how will that change as the glaciers retreat?  Second, I’m focusing on the economic consequences of floods for Pakistan, using an inter-sectoral model of their economy.  When floods hit agriculture, for example, how does that trickle down to other sectors, and what sectors are most likely to be unaffected?

Distributive Impacts of Dams and Governmental Responses in County-level in China

Project by Xiaojia Bao:

This paper initially built a theoretical model for governments’ fiscal response with respect to the distributive impacts of dams along a river basin. The model claimed that upstream counties should get compensated, while downstream counties should compensate or transfer out, if the local governments were functioning efficiently. Then the paper verified the distributive impacts of dams on different areas along a river basin using empirical data in county level in China from 2000 to 2008. Empirical analysis indicated that dam construction and finished dams mainly had distributive impacts on agricultural economic outcome variables, such as primary industry valued added per capita and grain production.  Local counties would suffer from agricultural loss due to the disruption from dam construction work and land loss for reservoir construction, but those areas were compensated correspondingly, which can be seen from the reduced deficit percentage. Upstream counties suffered from deteriorated economic outcome indicators both in agricultural and non-agricultural industries with GDP per capita decreased by 1540 RMB and net income per capita in rural households decreased by 147 RMB, while they got compensated to some extend through the revenue increase (close to 87 RMB per capita). Downstream counties benefited from dam construction on agricultural production, mainly in grain production and meat production, corresponding to a decrease in the expenditure (43 RMB per capita) and increase in revenue (122 RMB per capita).

Rural Household Residential Water Use Behavior in Northern China

Project by Xiaojia Bao:

This paper modeled household water use in a water-scarce rural village in Northern China using household level data. Several household characteristics were identified to impact water use significantly. Household size shows a scale-economy effect, with a coefficient close to 0.25. Gender structure and characteristics of household head don’t show a significant effect. In addition, households adjust their water use as a response to weather variability.  The increase of average monthly precipitation by 1mm corresponds to 0.1-0.2% decrease in per capita water use . And the increase of average monthly temperature by 1 degree corresponds to 2-5% increase in per capita water use. The response of households’ water use to weather is state-dependent. Generally, smaller and younger households increase water use more as a response to temperature increase, but decrease water use less as a response to precipitation increase.