Milind Kandlikar

Prospective Graduate Students / Postdocs

This faculty member is currently not looking for graduate students or Postdoctoral Fellows. Please do not contact the faculty member with any such requests.


Research Interests

Air Quality and Climate Change
Technological Risk
Technology and Development

Relevant Thesis-Based Degree Programs

Affiliations to Research Centres, Institutes & Clusters

Research Options

I am available and interested in collaborations (e.g. clusters, grants).
I am interested in and conduct interdisciplinary research.
I am interested in working with undergraduate students on research projects.

Research Methodology

Mathematical modelling and simulation
Quantitative surveys
Expert Judgment and Elicitation
Statistics and Data Analytics

Great Supervisor Week Mentions

Each year graduate students are encouraged to give kudos to their supervisors through social media and our website as part of #GreatSupervisorWeek. Below are students who mentioned this supervisor since the initiative was started in 2017.


Supervisor appreciation week @UBC! Shoutout to @NRamankutty and @mKandlikar. Extremely proud and blessed to have not one, but TWO super supervisors. Awe-inspiringly smart giants whose shoulders I stand on. @ubcires @ubcSPPGA #GreatSupervisor


Graduate Student Supervision

Doctoral Student Supervision

Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.

Indian agriculture in a changing climate: a statistical analysis (2022)

Predicting crop yield response to climate change is a topic of active research. A popular method involves building statistical models using historical climate and agricultural data, and then applying them on future climate projections for predicting crop yields. Using India as a case study, this dissertation examines these statistical models along two dimensions: the type of climate variables included, and the statistical techniques used. We also employ these models for predicting climate change impact on Indian crop yields till 2100.First, we examine the role of seasonal (e.g. total seasonal precipitation) versus subseasonal (e.g. precipitation over each crop growing stage) climate variables in explaining crop yields. We observe that even though adding extra climate variables does not always improve overall model accuracy, the proportion of yield variability explained by climate (versus non-climatic variables like geography and time) can increase significantly. This underscores the importance of combining physiological and statistical knowledge while choosing climate variables for statistical crop models. Second, we compare the well-known statistical method of OLS linear regression (LR) to a popular machine learning method called boosted regression trees (BRTs). While LR models were simpler to interpret, BRTs could uncover unexpected non-linear relationships and exhibited better yield prediction accuracy. Compared to LR, BRTs sometimes showed lower sensitivity to temperature variation. Higher flexibility of BRTs allowed them to identify obscure interactions between variables that could be missed by LR.We then use different climate variables and statistical techniques for building statistical models to predict climate change impact on India’s future crop yields. We found that nationally-averaged rice, wheat, and pearl millet yields could reduce by up to 3.4, 4.3, and 5.5 percent (respectively) by 2050 under the intermediate emissions scenario. Some parts of India may benefit from climate change, while other regions could face yield losses of up to 20 percent. Depending on the climate variables or statistical technique employed, we observe high variability in yield change predictions. We therefore suggest combining multiple models for estimating climate change impact on crop yields.

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Reimagining conservation landscapes: Adivasi characterizations of the human-dimensions of southern Indian forests (2022)

One of the most damaging consequences of forest management and wildlife conservation policies around the world has been their pivotal role in the long-term dispossession of Indigenous groups from their ancestral lands. Indigenous presence in, knowledge, and understanding of the natural world is perceived as a problem requiring the correction and intervention of the state. These wrongful assumptions are dominant in the treatment of Adivasi (India's Indigenous people) across post-colonial India. This dissertation empirically investigates the relationship of Kattunayakans, a hunter-forager Adivasi community of Southern India and protected area forest landscapes. It critically contrasts the ideology that defines India's forest policy with Adivasi views of human relationships with wildlife, forested land, forest fire, and forest food.From all the above, chapter 2 characterizes Kattunayakan ways of engagement with wildlife as a form of 'deep coexistence' that describes wild animals as: rational beings in conversation with humans; as gods, teachers, and equals; and as relatives with shared origins practicing dharmam (alms). Chapter 3 contributes empirical evidence to the study of Adivasi-forest relationships by articulating socio-cultural meanings and values that Kattunayakans associate with protected area forests. Chapter 4 engages with Adivasi knowledge of forest fire as an agent, co-manager, actor, preserver, groomer, and enabler of socio-ecological functions. It contests the notion of a forest fire as a dangerous phenomenon that should be quickly extinguished and positions fire as a co-habitant being, on par with animal and human residents. Chapter 5 seeks to expand understanding of Adivasi food transitions and ensuing consequences for the socio-ecology of Indigenous peoples. It describes the food as a facilitator of knowledge, memories, identities, aspirations, reciprocities, relationships, and ways of living. It highlights the need to learn about Adivasi foodways beyond nutrition and have policies that bring an Adivasi inclusive take on food transitions. What emerges is an interpretation of the forest that emphasizes coexistence over domination, highlighting the fluid agency of animal and non-animal entities over rigid policy prescriptions and broader notions of forest security as human security. Together these views remain central to Adivasi well-being despite decades of forced dislocation.

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Access to modern energy, air pollution and greenhouse gas mitigation: Inter-linking three major energy challenges facing India today (2019)

The majority of the Indian population relies on traditional fuels such as biomass, and an estimated million people die prematurely in India due to poor air quality, both indoor and outdoor, annually. A major CO₂-emitter, India has also committed to a low carbon development pathway. In this thesis, I study the problem of indoor and outdoor air pollution exposure in India, and its links to energy equity and climate mitigation.First, I use national-scale household survey data to quantify changes in cooking habits and health. I show that electrification and complete transition to Liquefied Petroleum Gas (LPG) provide significant health and time-saving benefits, particularly for women, but using LPG together with biomass provides negligible benefits. Second, I use national-scale household energy use data to show that indoor exposures to fine particulate matter (PM2.5) in rural and low-income urban households exceed those in higher income urban households by an order of magnitude. Using a diffusion model for future energy use I show that comprehensive access to modern fuels for all is needed to drastically reduce indoor PM2.5 exposures, and it would add minimally to current levels of GHG emissions, if non-Kyoto pollutants from traditional fuels are considered. Third, I construct a multi-box atmospheric transport model for PM2.5 to analyze the spatial and seasonal variation of ambient air pollution. I then use a national air pollution inventory to calculate source contribution to ambient PM2.5 exposure. Residential biomass use dominates mortality burdens from ambient air pollution in India. I show that the informal sector (sources beyond the direct ambit of regulation including traditional household fuels) is responsible for 73% of deaths attributable to ambient air pollution and 33% of nation-wide GHG (including non-Kyoto) emissions. Coal use in formal industry is the second leading contributor to mortality and is responsible for half of national GHG emissions. The significant contribution of informal sources to ambient air pollution and GHG emissions leads to the conclusion that a focus on formal sources (e.g. power and transport) alone is inadequate - the role of informal sources needs to be addressed to meet air quality and climate goals.

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Regulating the last mile: paratransit in Delhi (2018)

Paratransit plays a vital role in cities in the Global South, including India. Paratransit modes - those which lack a fixed route and timetable - perform trips impractical or impossible on mass transit and, in Delhi, increasingly provide feeder services to the city’s metro rail and Bus Rapid Transit (BRT) systems.Despite their critical role in the urban transit ecosystem in Indian cities, paratransit operators have a poor reputation amongst the middle-classes and the English-language media for overcharging passengers and flouting regulations. In response, the current policy approach to paratransit regulation is marked by judicial and technical interventions. These are seldom empirically driven, and often represent a relative neglect of the paratransit sector. This study aims to correct this neglect by providing a detailed empirical account of paratransit operations and the regulatory environment in Delhi. It makes the case that paratransit is a vital last mile mode, and that evidence based regulation of paratransit modes is critical to improving public transport in Indian cities.This study does this by analyzing existing paratransit regulation and demonstrating that the current approach involves a heavy burden of compliance that inflates costs for operators. It then presents an empirical analysis of the economics of operating an auto-rickshaw using a survey of drivers (n=301). It finds that overcharging may be explained by the structure of operators’ costs and revenues. A survey of passengers (n=689) provides data for a series of statistical models, which suggests that the incidence and magnitude of overcharging are explained by the economics of auto-rickshaw trip making and associated with such variables as trip distance and the location of the destination.It then seeks to explain the rise of battery-rickshaws as a mode paratransit in the city and the lessons provided by their sudden proliferation. A fieldwork survey of drivers (n=302) provides data on their role and operating economics. A passenger survey (n=540) finds battery-rickshaws are largely replacing cycle-rickshaws. This case study sheds light on the environment in which urban transportation policy decisions are made. The study concludes by presenting some policy recommendations for paratransit in Delhi.

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Explaining climate-sensitive decision-making: on the relationship between cognitive logic and climate-adaptive behaviour (2017)

The harmonization of climate-adaptive behaviour with pre-existing decision-making processes is central to the way climate change adaptation is described in the literature. Yet such behaviour is largely understudied, making it difficult to predict whether and how individuals can integrate (i.e., ‘mainstream’) climate change with risk management processes for weather and other ‘normal’ stressors. In this dissertation, I examine the decision-making processes of South Africa’s commercial grain farmers, as a uniquely informative case, through five complementary studies of two original datasets. I seek to better understand the relationship between risk perceptions and climate-adaptive behaviour in this group, who are known to be sensitive to weather risks and who are adopting climate-resilient farming practices (i.e., Conservation Agriculture (CA)), but who are nonetheless perceived by local experts to be insensitive to climate change risks. In doing so, I distinguish between weather-sensitive decision-making, in which farmers perceive and react to weather risks in conjunction with other ‘normal’ risks, and climate-sensitive decision-making, in which they also perceive and react to the anticipated effects of climate change. Using mental models interviews in the Western Cape province (N = 90), I first reconceptualise farmers’ risk-based decision-making processes, drawing on theories of risk perception and framing from cognitive psychology and behavioural economics to interpret the empirical evidence. Second, I explain the variation in farmers’ adoption of climate-resilient CA practices based on the different cognitive frames (expressed as linguistic frames) that they use to perceive, interpret and respond to weather risks. Third, I use these results to guide the quantitative analysis of a national survey (N = 441), with which I assess the utility of the CA concept in promoting, monitoring and evaluating sustainable and climate-resilient farming practices, as envisioned by the Climate-Smart Agriculture and Sustainable Intensification frameworks. Fourth, I use the interview data to evaluate whether and how farmers integrate climate change and weather risks in farm-level decision-making. Fifth, I build on these findings by using the survey data to quantitatively test whether farmers perceive weather and climate change as equivalent risks.

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Air pollution in New Delhi, India: spatial and temporal patterns of ambient concentrations and human exposure (2016)

Urban air pollution is a major health and environmental concern worldwide, and the levels are extremely high in New Delhi, India. This research is focused on the spatial and temporal variability of air pollutant concentrations and its implications for population exposure in New Delhi. Since traffic is considered a significant source of air pollutants in urban environments, robust and multiple linear regression models were used to understand the impact of local traffic flow on ambient concentrations of PM₂.₅, CO, NO and NO₂ at a busy intersection. To elicit the spatiotemporal variability of PM₂.₅ and its constituents (black carbon and ultrafine particles), land use regression (LUR) models were developed. Separate morning and afternoon models were developed using 136 hours (39 sites), 112 hours (26 sites) and 147 hours (39 sites) of PM₂.₅, BC and UFPN data, respectively. Finally, to understand how spatiotemporal variations in PM₂.₅ concentrations impact population exposure, a probabilistic simulation framework was developed to integrate the PM₂.₅ LUR models with time-activity data obtained from a field survey. Regression models explained about 50–80% variability in hourly pollutant concentrations and localized traffic flow explained up to 19% of variability on that scale. Auto-rickshaw and truck flow had a higher influence on NO₂ and PM₂.₅ concentrations, respectively. Independent variables in the LUR models included population density, distance from major roads, and major and minor road lengths in buffers of different radii; measurements from a fixed continuous monitoring site were also used as independent variables in the PM₂.₅ and BC models. The temporal term explained most of the variability (63–77%) in PM₂.₅ and BC models compared to spatial variables (4–16%). Exposure simulations indicate that the estimated annual average PM₂.₅ exposure (109 µg m-³) was high compared to North American or European cities. PM₂.₅ exposures were highest during the winter months (~200 µg m-³) compared to the summer months (~50 µg m-³). Ignoring mobility (i.e. exposure during transport or at work/school locations), as is generally assumed in epidemiologic studies of long-term exposure, underestimated PM₂.₅ population exposure by about 11%.

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Integrative Approaches to Environmental Life Cycle Assessment of Consumer Electronics and Connected Media (2014)

The environmental impacts of information and communication technologies and consumer electronicsare challenging to evaluate. Organizations and individuals wishing to reduce the impacts attributable to their usage of these products and systems rely on a limited technical knowledge base that struggles to stay current. Using a life cycle assessment approach which expresses environmental impacts quantitatively in terms of greenhouse gas emissions and primary energy demand, this dissertation significantly expands our understanding of the impacts of desktop computers, electronics products in general, and connected media services accessed in the home, in order to support environmentally-conscious decision-making and policy regarding these products and systems. The first of three studies, a meta-analysis of prior life cycle assessments of desktop PCs, resolves an important ambiguity in this literature and demonstrates that greenhouse gas emissions due to operational energy consumption usually exceed those due to device manufacturing. The second study calculates embodied greenhouse gas emissions of eleven electronics products through a teardown analysis, and finds a linear relationship between mass and embodied emissions, thus demonstrating that lightweight, compact products offer environmental benefits relative to larger products. A comparison to studies of older products also reveals that newer products are more materially efficient, largely due to reduction in integrated circuit content per product. Finally, the third study calculates aggregate US consumer greenhouse gas emissions due to broadcast television, video on demand, online video, other online uses, and offline uses when consumed using televisions, personal computers, tablets, and smartphones, including emissions due to devices in the home, networks, and datacenters. The study concludes that emissions due to video end-uses account for 75% of total consumer ICT emissions. About 71% of consumer ICT emissions arise due to devices in the home, especially TVs and desktop PCs, with the remainder due to networks and datacenters. Mobile platforms using Wi-Fi connections are the least impactful mode of consuming connected media content. Collectively, the dissertation argues for a more integrated approach towards impact estimation, in order to surmount issues regarding variation of modeling assumptions across existing studies, longevity of published work, and coverage of emerging products and services.

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From cradle-to-grave at the nanoscale: Expert risk perceptions, decision-analysis, and life cycle regulation for emerging nanotechnologies (2013)

Engineered nanomaterials (ENMs) promise great benefits for society, yet our knowledge of potential risks and best practices for regulation are still in their infancy. High uncertainty and novel ENM properties complicate the management of risk, rendering existing regulatory frameworks inadequate. This thesis investigates the challenges that nanotechnologies pose for risk regulation, and aims to inform the development of policies and practices to address these challenges. In chapter 2, US federal environmental, health and safety (EHS) regulations are analyzed using a life cycle framework, to evaluate their adequacy as applied to ENMs. This analysis reveals that life cycle risk management of nanomaterials under existing regulations is plagued with difficulty, and populated by myriad gaps through which ENM may escape federal oversight altogether. Chapters 3 and 4 examine expert opinions on risks, and perceptions of regulatory agency preparedness to manage risks, using a web-based survey (N=404) of US and Canadian nanotechnology experts. Risk and preparedness perceptions were found to differ significantly across groups of experts. Nano-scientists and engineers were more than twice as likely as nano-regulators to believe that benefits from nanotechnology would greatly exceed risk. Yet, those working in regulatory agencies were far more likely to regard government agencies as unprepared than were experts outside government. These differences were explained by expert views of the novelty of benefits and risks, attitudes toward other classes of risk, preferred approaches to regulation, experts’ degree of economic conservatism, and trust in regulatory agencies.Recognizing the myriad challenges for risk regulation, chapter 5 explores the use of decision-analytic models to cope with uncertainty. Drawing on baseline data monitoring efforts of the US EPA and California DTSC, this chapter argues for the use of novel decision-analytic tools and approaches (such as risk ranking, multi-criteria decision analysis, and “control banding”) in lieu of formal risk assessment to meet regulators’ goals in particular decision contexts.Considered together, this thesis concludes that oversight can be improved through pending regulatory reforms, the utilization of expert opinion to inform decision-making, and the development of improved decision-analytic tools that enable the assessment and management of risks under high uncertainty.

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Engineered debates and emergent biosafety: the social controversy and regulatory challenged confronting GE crops in India (2012)

This dissertation investigates the social controversy and regulatory challenges presented by genetically engineered (GE) crops in India. Current research insufficiently addresses risk controversies in the developing world, nor provides adequate consideration of GE biosafety as an important socio-political concept as well as a technical one. The study addresses these gaps by mapping the GE controversy in India, its insertion into health and safety decision-making, and the ways in which divergent stakeholders have established positions in these risk debates. Secondly, it assesses the challenges facing the biosafety regulatory regime in India, particularly as a country undergoing a "risk transition," whereby a growing middle class and marginal farmers are pitted against one another in surprising ways.The data for this study are drawn from three main sources using a case study methodology. Firstly, interviews with: farmers, civil society groups, and regulators. Secondly, an analysis of key policy and legal documents that serve as the foundation of India's regulatory regime. And finally, an analysis of the literature and materials that help make up the "public debate" including NGO publications, website postings, films, and newspaper articles covering aspects of the controversy from key Indian English language sources. Rooted in the social studies of risk, the dissertation also draws from literatures on comparative policy analysis, narrative theory in social science, political ecology, and science and technology studies. India is undergoing a "risk transition", and the country's response to GE agriculture can be expected to differ from what has been more thoroughly mapped in other parts of the world. Moreover, biosafety is the central organizing principle of agricultural biotechnology regulation in India, and its ongoing negotiated quality has spurred both regulatory innovation and larger governance challenges.India has a diverse, largely agrarian population and this study finds that developing new ways to understand how the GE regulatory regime is changed by public debate is crucial, as are meaningful ways to solicit and incorporate public participation in a complex democracy. Strategies to address public perspectives must extend beyond organized civil society groups to include other citizens, especially marginal producers with much at stake in the GE debates.

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Strategies to reduce transportation emissions in India: Identifying air-quality and climate co-benefits for the developing world (2011)

Emissions from on-road transportation sources are a complex mixture of gaseous and particulate pollutants. Particulate matter (PM) emissions are especially important because – although short lived in the atmosphere – they are strongly associated with cardiovascular and respiratory disease and are strong climate forcing agents. The overall objective of this research was to quantify the effectiveness of emission control policies for in-use vehicles in India. I have focused on understanding the impacts of large-scale adoption of compressed natural gas (CNG) as an alternative to diesel and gasoline in New Delhi, India. In Chapter 2, I quantified the climate impacts of switching to CNG for public transportation vehicles (taxis and buses). The study showed that converting buses from diesel to CNG significantly reduced climate-warming diesel particulate matter (PM), but the increase in CH₄ emissions from all vehicle types offset much of this benefit. Chapters 3-5 focused on auto-rickshaws (three-wheeled taxis), which are an important mode of passenger transport in many developing countries. In Chapter 3, a survey of 350 drivers quantified activity patterns, fuel consumption and CO₂ emissions for auto-rickshaws, and a model was developed to better understand the determinants of visible smoke emissions. Chapter 4 describes a laboratory (chassis dynamometer) study that measured emissions from 31 auto-rickshaws, and establishes fuel-based emission factors for gaseous and fine PM pollutants from 2-stroke and 4-stroke spark-ignited engines fueled with CNG and gasoline. Finally, Chapter 5 examines a range of emission-reduction policies for auto-rickshaws, including phasing out 2-stroke engines, switching to CNG fuel, scrapping older vehicles and four different types of inspection and maintenance (I/M) programs. Together, these studies demonstrate that certain fuel/engine combinations, such as CNG-fueled 4-stroke engines, are more robust low-emitters than others, and can be an effective alternative to diesel engines (in buses) or 2-stroke engines (in auto-rickshaws). Although this research has examined emissions-reduction policy in New Delhi, the findings are applicable to in-use vehicles in many other jurisdictions in the developing world.

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Master's Student Supervision

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

Electric vehicle lithium-ion battery recycling in China : scale and policy challenges (2023)

China is the world’s largest producer and consumer of Electric Vehicles (EVs). This study assesses: (i) the number of future passenger and commercial electric vehicles (EVs), and consequent retired lithium-ion battery (LIB) amounts in China and (ii) current Chinese policies regarding retired battery reuse and recycling. The first part of this work used the Bass Diffusion Model (BDM) framework to predict the China’s future EV sales trends and uses those numbers to calculate retired battery amounts. We use 4 scenarios to assess future EV sales based on (i) solely historical trends for internal combustion vehicles (ICEVs); (ii) a rapid sales scenario for EVs; (iii) a scenario based on government goals for EVs and (iv) a slow uptake scenario. The scenario based on historical trends for ICEVs predicts the most rapid growth rate and is expected to reach market saturation (95% adoption) within the next decade and provides the best fit for the EV and ICEV data. Thus, this work predicts a far more rapid uptake of EVs in China than previous work and government predictions. The results show that the cumulated retired battery amounts across scenarios range between 120 million tonnes to 263 million tonnes by 2060, with the higher end of this range being the most plausible. This sets up an immediate challenge for the Chinese battery recycling regulatory system. The second section combines a review of existing Chinese state and regional policies regarding the reuse and recycling of retired EV batteries, along with a combination of surveys and 16 interviews on current and future policy expectations. We find that current policy directives are mostly issued on a national level and intended to serve primarily as guidelines for the industry. Experts see the recycling industry as informal and fragmented and are deeply concerned about lack of monitoring and an absence of emission standards in the reuse and recycle sector. As retired battery amounts are expected to grow fast, experts recommended introducing the deposit scheme, extended producer responsibility (EPR), closed-loop tracking system, and qualification of recycling facilities to solve the current policy deficiencies and industrial problems.

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Remote detection of the impact of mines on local landscapes : lessons for the low-carbon energy transition (2023)

The low-carbon energy transition is an essential feature of avoiding climate crisis, but it raises additional concerns due to the mineral extraction required to initiate such a large-scale technological shift. Among the many anticipated impacts, changes in land cover represent a significant threat which have flow-on implications including for Indigenous rights-holders. Land cover impacts were assessed through Geographic Information Science (GIS) and remote sensing methodologies. Previously, studies which have assessed mining impacts through GIS and remote sensing methods have been limited to the scale of one mine, limited to measuring impacts at one point in time, and/or limited in the reliability of how they predict the extent of future mining impacts. A novel methodology was developed which allowed for the assessment of land cover impacts for 77 mines in British Columbia using the satellite-derived Normalized Difference Vegetation Index (NDVI) as a metric for environmental degradation. Ten buffers were drawn around each mine in 1-kilometer intervals and the mean NDVI within each buffer was calculated from 1984-2022 using Landsat Best-Available-Pixel composites. T-tests and Kruskal-Wallis significance tests were run testing the relationship between NDVI and three parameters: distance from the mine, mine size, and primary commodity. The majority of parameters had no statistically significant impact on NDVI. However, significance was found in the case of copper mines and mine sizes between 24,000 and 140,000 tonnes up to a maximum distance of 4 km. BAP composites were inspected for five case studies to identify features which could impact the results of the NDVI analysis. The case studies revealed that non-mining disturbance such as harvest or forest fires and cloud cover can influence NDVI and be falsely attributed to mining through this methodology. The results of this study have indicated that the land cover impacts of mining may be limited to the extent of the mine from an areal perspective. Studies which aim to predict the future impacts of mining should exercise caution when choosing standard buffer distances that are much greater than 4km to estimate the potential area of influence of a mine.

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Making carbon price as an effective signal (2021)

Carbon pricing is a rapidly spreading policy to mitigate GHG emissions. However, the current carbon price is not high enough to make an effective price signal. This study assesses the carbon tax policies in Sweden, British Columbia, and France as examples of high carbon tax rates. This work expands the scope of the carbon price impact incorporating explicit and implicit sources, focusing on a carbon tax and a fuel tax. The carbon prices are calculated by fuel types and weighted by their share in the Total Primary Energy Supply (TPES). A quantitative analysis shows that implicit fuel taxes mainly drive the carbon price signals, and the carbon pricing is skewed towards vehicle fuels, such as gasoline and diesel. The research considers the emission coverage of the carbon tax, an increasing price trajectory, and revenue management. The policy designs are all diverse in the three cases. Lessons are drawn from their experiences regarding allowing exemptions, expanding emission coverage by the carbon tax, setting an increasing price trajectory, and effectively managing revenue. In the beginning, it seems easier to allow exemptions to the sensitive industries and then to expand the emission coverage after allowing enough time for those industries to adjust. Increasing price trajectory is an essential quality for a sustainable carbon tax. In addition, revenue neutrality is not a must-have condition for successful carbon taxation. However, it is an undoubtedly effective strategy to persuade the public, framing the carbon tax as a tax shift, not as a tax increase.These findings point out the skewed carbon price signals even in jurisdictions with high carbon taxes. It suggests that more efforts need to be made to expand the carbon price signal, especially for the non-vehicle fuels and sectors. It can be suggested that policy makers who are considering implementing a new carbon tax or revising the current carbon tax policy need to consider the carbon price from implicit sources, such as fuel taxes, to have a comprehensive picture. Moreover, jurisdiction-specific contexts need to be carefully considered to make the tax policy a sustainable measure to combat climate change.

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Agricultural waste burning in northern India - economic analysis and farmers' perspectives (2020)

Rice farmers in Northern India burn the rice “stubble” left in the fields after a harvest in order to clear land for the next sowing season. During several weeks in the burning season residents of the Indo-Gangetic Plain are exposed to levels of fine particulate matter that are ~100x greater than the annual WHO standard. Despite a ban on Agricultural Waste Burning (AWB), 9.96 million metric tons of rice residue was burnt in Punjab in 2018. Several ‘active management’ alternatives to AWB that include in-situ and ex-situ rice residue management are available to rice farmers. However, financial, logistical and institutional challenges make their adoption and impact inadequate.This work focuses on the alternatives to AWB in the Punjab, particularly on (i) farmers’ perspectives on available active management practices and challenges in adopting them (ii) the cost of residue management and how it influences practice (iii) role of government incentives. We expand on existing cost analyses of residue management processes by conducting semi-structured interviews with farmers and key experts to better understand how operational factors and cascading impacts may affect the profitability of different alternatives. These considerations include: timing of government subsidies, fixed bonus incentives, timely availability of required machinery, and pest implications. Our results show that given timely government incentives of a fixed bonus and subsidy on machinery, the cost of rice residue management through active residue management practices are comparable with residue burn. However, due to a short time window between cropping cycles, and wariness among farmers on the timely arrival of government subsidy, status quo of residue burn is more convenient and cost-effective for farmers in Punjab. Farmers also highlight concerns of groundwater depletion in Punjab that residue management does not address, and highlight the need for crop diversification to address both issues of air quality and depleting groundwater. These findings point to the importance of addressing AWB as more than simply a problem of residue management, but instead as part of a landscape of issues, including rice production in Punjab for national food security, mechanization, depleting groundwater, and short time duration for rice harvest.

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Life cycle assessment of electric and combustion vehicles in India (2020)

This study assesses the life cycle greenhouse gas emissions of electric and conventional vehicles in the context of India, a country which still relies on a coal-fired power grid. It assesses the emissions of electric and conventional vehicles under three different scenarios for the development of the electricity grid between now and 2030. These three scenarios are the Current Trends Scenario (CTS), which is a business-as-usual scenario, the Current Policies Scenario (CPS), under which extant renewable energy policies are fully implemented, and a High Renewable Energy Scenario (HRES), under which additional renewable energy is added to the grid. In the HRES, this work incorporates the benefits of utilizing the battery for grid energy storage after the life of the vehicle is over, because high penetrations of renewable energy will also require grid-level energy storage.This study finds that, even with a carbon-intensive power grid, electrification of vehicles confers a reduction in greenhouse gas emissions. In a business-as-usual CTS scenario for the power grid’s evolution, an average electric vehicle (EV) has life cycle GHG emissions 23% below the equivalent combustion vehicle’s (ICEVs) in 2030. This benefit greatly increases in a HRES scenario when the batteries are utilized for energy storage after the life in a battery. In this case, an average EV has life cycle GHG emissions 60% below equivalent combustion vehicles.In addition, this study conducted uncertainty analysis to assess the impact of uncertainty in the fleet averages for various input variables. It used a Monte Carlo analysis to assess the life cycle GHG emissions of conventional and combustion vehicles under a range of values for seven to eight key variables (depending on the scenario). It found that under the HRES, all simulation runs resulted in lower emissions with the EV, and in the CPS, almost all simulation runs resulted in lower emissions with the EV. In the CTS, 95% of simulation runs indicated that EVs have lower life cycle emissions.

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Electricity Use Analysis of Existing and Planned University Buildings and Opportunities for Life Cycle Costing (2017)

Increasing environmental awareness has initiated a change in building design and efficiency in order to reduce the large amount of energy associated with this industry. Life cycle cost (LCC) analysis is a decision-making tool to evaluate the economic long-term benefits of different design options compared to the building’s basic design. LCC analysis can motivate decision-makers to reallocate building budgets towards higher initial capital costs if the long-term operational savings balance higher upfront expenses. However, LCC needs well-calibrated predictive modeling for such savings to be realized. ‘Bottom up’ Energy modeling software has been used to evaluate savings associated with different building designs. Although these models require a large amount of building specific information, their predictions are often far off from the actual energy use. An alternative proposed in this thesis is to use ‘top down’ models that predict energy consumption using aggregate building characteristics such as size, age, type and occupancy. We have developed a ‘top-down’ model for electricity use in buildings based on daily electricity consumption data of 48 research buildings at the University of British Columbia (UBC). The model is a set of linear regressions analyzed with MATLAB. Our model requires only a few simple, aggregate inputs in order to make electricity use predictions. These compare favorably to the more complex LEED energy tested models for ten UBC research buildings. Thus, the ‘top down’ models are an additional, useful tool for energy planning and design. The effort to collect data for such models is also small compared to the ‘bottom-up’ alternative.

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Carbon Management In Airports (2016)

Airports are multi-stakeholder organizations that can be as complex to manage as small cities. Carbon emissions have begun to occupy an important place in airport environmental management plans. Proposed solutions to reduce carbon emissions from airports’ landside and airside operations are diverse and contain different courses of action for emission sources located both on the ground and in the air. However, due to the complexity of airport governance, the implementation of carbon management policy faces technical, financial, and organizational challenges. Buildings, ground fleets, and ground support equipment (GSE) used at airports tend to be owned by different parties, including airlines, airports, and third-party sub-contractors, and the lack of coordination among those parties can be a challenge to developing emission-reduction goals. Emission-reduction goals in airports require collaborative environmental management, including emission monitoring, and designated personnel who can supervise the progress of the policy’s implementation. The study conducted for this thesis examined the following topics: · The ways airports report and monitor carbon emissions· Airports’ perceived environmental management priorities · Constraints on carbon management in airports· Currently incorporated elements of collaborative carbon management in airports. The study involved two parts. The first part is a review of current GHG emission reports published by airports, and the second part is an internet-based survey that was sent to airports. The analysis conducted for part 1 (reported in chapter 2) reveals the need for new harmonized GHG reporting standards for airports that better reflect the technological interdependence between airplanes and airports. The findings of part 2 (reported in chapter 3), based on the responses received from airports (n=31), reveal a growing willingness to allocate more resources to reduce carbon emissions in airports, in addition to constraints on carbon management. The constraints are in the form of lack of government regulation that requires airport authorities to engage tenants in the carbon management process, lack of access to tenants’ emission data, and high costs of implementing technological solutions currently available for carbon reduction. The results highlight the importance of developing strategies to address carbon emissions in inter-organizational levels.

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Is Free Trade Free of Environmental Cost? (2016)

The impact of international trade on the environment has been the field of focus since the 1970’s. There have been a number of empirical studies exploring the environmental consequence of free trade but the results are mixed and only a few environmental indicators have been used in place of the total environmental impact. In this study, I used combined environmental cost data which converted environmental impact indicators into US$ terms (the data is taken from World Bank database). Also, by taking advantage of panel data (observations from 60 countries over 25 years) and (two-way) fixed effects model, I attempted to reduce the threat of endogeneity problem. Most importantly, environmental impact which is filtered through the trade induced changes of economic activity was analyzed in parallel with unfiltered through effects. And the results revealed that trade openness reduces national level environmental cost rather than increasing it. Meanwhile, income related technique effect was found to be underperforming and when the full sample was split into four income groups, the income-environment relationship appeared to be closer to N-shape as opposed to the inverted U-shaped environmental kutznets curve hypothesis.

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Characterization of Ultrafine Particulate Matter from Traditional and Improved Biomass Cookstoves (2012)

Billions of people worldwide use biomass fires or cookstoves on a daily basis, with significant resultantcontributions to emissions of global carbonaceous aerosols. The use of biomass as a fuel has an impact on localecosystems, contributes to CO2 levels in the atmosphere, and black carbon (BC) and organic carbon (OC) affect theearth’s radiative balance. Widespread initiatives, including carbon funding programs, propose to replace traditional“three-stone” open fires with “improved” cookstoves designed to reduce fuel usage. While numerous studiesinvestigate cookstove efficiency and publish emissions factors for gaseous pollutants and overall particulate matter(PM), there is a lack of focus on the size and nature of ultrafine particulate (UFP) emissions. This paper comparesultrafine emissions during steady combustion from a traditional three-stone fire and two improved stoves: a Rocketstove (“Chulika”) and a Gasifier stove (“Oorja”).An AVL emissions bench measured gaseous products. PM instrumentation included a TSI SMPS, TSI APS, TSIDustTrak DRX, Magee Scientific Aethalometer, and 47mm PTFE and quartz filters; a thermophoretic samplingdevice was employed to gather material for PM imaging using transmission electron microscopy (TEM).The improved cookstoves demonstrated high combustion efficiency compared to the three-stone fire and are likelyto reduce biomass consumption. Additionally, emitted PM mass was reduced by a significant amount. PMemissions from improved stoves had a higher proportion of BC compared with total PM, though there was relativelylittle variation in overall BC levels. The reduction in highly scattering OC that would accompany a large-scale shifttowards usage of improved stoves could affect the earth’s radiative balance, but this merits investigation withconsideration to other particle characteristics. Primary particles emitted from the improved stoves were smaller thanthose from the three-stone fire and appeared slightly less likely to coagulate into chain agglomerates. The observedshift towards greater quantities of smaller nanometer-sized particles could pose health concerns and is a point forfurther consideration by health scientists and reinforces the need for adequate ventilation for all cookstoves,independent of type.

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Climate science, equity and development: the role of international institutions in capacity building for climate change (2012)

Climate change is a serious global problem that will have a disproportionate impact on developing countries. The ability of these countries to cope depends, at least in part, on the strength of their human capital and institutional capacity related to climate science. This thesis begins by examining the extent to which developing country scientists are participating in global climate science, and then evaluates international efforts to build the capacity of developing country scientists to address the climate change problem. A quantitative analysis of authorship data of the United Nations Intergovernmental Panel on Climate Change (IPCC) assessment reports (1990, 1995, 2001 and 2007) reveals that developing country scientists and institutions remain grossly under-represented – even after normalizing for a number of factors. The IPCC has recently acknowledged this ongoing problem, while the international community has resolved through the United Nations Framework Convention on Climate Change (UNFCCC) process to prioritize capacity building in developing countries. Extensive open source research and interviews with key informants at leading international organizations were used for qualitative purposes to identify, analyze, and evaluate such capacity building efforts. While several impressive initiatives were identified at the regional level, most capacity building activity was isolated and likely to be of limited effectiveness in advancing concerted global action to mitigate and adapt to climate change. The overall conclusion is that the existing international approach to building scientific capacity in the developing world to address climate change is inadequate. Several significant obstacles to achieving sustainable, long- term scientific capacity to address climate change in developing countries are explored, including: institutional barriers, financial issues, the “brain drain” phenomenon, data access and quality, technology and research resource limitations, complexities with downscaling/up-scaling of climate modeling, the interdisciplinary nature of climate change, navigating the science-policy interface, and issues related to operating across culture, language, and gender. Finally, this thesis concludes that the largely ad hoc approach to individual capacity building activities should give way to a more comprehensive, integrated, strategic approach to more effectively build scientific capacity in the developing world to meet the climate change challenge.

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