TOPICS IN MODELLING ADAPTATION DYNAMICS OF CHINESE AGRICULTURE TO OBSERVED CLIMATE CHANGE

Chinese farmers have adopted multiple adaptation measures to mitigate the negative impact of, and to capture the opportunities brought by, the observed climate change in the last several decades. Such adaptations will continue in the coming decades given the foreseeing climate change. Scientifically assessing such dynamism of suitable agricultural adaptation requires unprecedented efforts of the research community to simulate and predict the interactions among crop growth dynamics, the environment and crop management, and cropping systems at and across various scales. This calls for efforts aiming to quantify the interactions of agro-ecological processes across different scales. This dissertation intends to make scientific contributions in this direction. The leading goal of this dissertation is to develop a cross-scale modeling framework that is capable of incorporating the field agricultural advances into the design and evaluation of regional cropping system adaptation strategies. It then applies this framework to identify feasible cropping system adaptation strategies under observed warmer climate and quantify their potential benefits to the grain production and water sustainability in the major cropping regions in north China. Three objectives of this study are: (1) Develop a cross-scale model-coupling framework between the site level DSSAT model and the regional level AEZ model to improve the AEZ performance in capturing the northern expansion of japonica rice under a warmer climate in the Northeast China Plain. (2) Construct a new wheat-maize cropping systems adaptation strategy to meet the double challenge of maintaining the regional grain production level and recovering local groundwater table in the semi-arid North China Plain, where the persistent overexploitation of groundwater has caused severe environmental damages. (3) Establish a dynamic adaptation strategy to identify the desired water sustainable cropping systems across different localities and to meet the challenge of recovery local groundwater table and minimize the output losses of wheat and then total grain production in the Hebei Plain, where the irrigation water shortage has threatened wheat production and thus potentially compromising China’s food security. This dissertation will improve our understanding of the interactions and interlinkage across multi-scale agro-ecosystems in mitigating the environmental risks associated with the irrigation-intensive farming and in adapting to climate change. The cropping systems adaptation strategies proposed by this dissertation provide scientific basis for future agricultural adaptation policy design compatible with local agro-climatic, land and soil conditions across China

Household carbon and energy inequality in Latin American and Caribbean countries

Reducing inequality, eradicating poverty and achieving a carbon-neutral society are recognized as important components of the United Nations’ Sustainable Development Goals. In this study, we focus on carbon and energy inequality between and within ten Latin American and Caribbean (LAC) countries. Detailed carbon and energy footprint were estimated by combining the consumption profiles (2014) in ten LAC countries with environmental extended multi-regional input-output (MRIO) analysis. Our results show significant inequality of regional total and per capita carbon and energy footprint across the studied LAC countries in 2014. The top 10% income category was responsible for 29.1% and 26.3% of the regional total carbon and energy footprint, and their per capita carbon and energy footprint were 12.2 and 7.5 times of the bottom 10% earners in that region. The average carbon footprint of studied LAC countries varied between 0.53 and 2.21 t CO2e/cap (ton of CO2 equivalent, per capita), and the energy footprint ranged from 0.38 to 1.76 t SOE/cap (ton of Standard Oil Equivalent, per capita). The huge difference in total and per capita carbon emissions and energy consumption of different income groups suggests notable differences in climate change responsibility, and supports policies for achieving sustainable consumption in terms of carbon tax, renewable energy subsidy, and decarbonizing the consumption structure in different LAC countries

Impacts of poverty alleviation on national and global carbon emissions

Wealth and income are disproportionately distributed among the global population. This has direct consequences on consumption patterns and consumption-based carbon footprints, resulting in carbon inequality. Due to persistent inequality, millions of people still live in poverty today. On the basis of global expenditure data, we compute country- and expenditure-specific per capita carbon footprints with unprecedented details. We show that they can reach several hundred tons of CO2 per year, while the majority of people living below poverty lines have yearly carbon footprints of less than 1 tCO2. Reaching targets under United Nations Sustainable Development Goal 1, lifting more than one billion people out of poverty, leads to only small relative increases in global carbon emissions of 1.6–2.1% or less. Nevertheless, carbon emissions in low- and lower-middle-income countries in sub-Saharan Africa can more than double as an effect of poverty alleviation. To ensure global progress on poverty alleviation without overshooting climate targets, high-emitting countries need to reduce their emissions substantially

Changes in global food consumption increase GHG emissions despite efficiency gains along global supply chains

Greenhouse gas (GHG) emissions related to food consumption complement production-based or territorial accounts by capturing carbon leaked through trade. Here we evaluate global consumption-based food emissions between 2000 and 2019 and underlying drivers using a physical trade flow approach and structural decomposition analysis. In 2019, emissions throughout global food supply chains reached 30 ±9% of anthropogenic GHG emissions, largely triggered by beef and dairy consumption in rapidly developing countries—while per capita emissions in developed countries with a high percentage of animal-based food declined. Emissions outsourced through international food trade dominated by beef and oil crops increased by ~1 Gt CO2 equivalent, mainly driven by increased imports by developing countries. Population growth and per capita demand increase were key drivers to the global emissions increase (+30% and +19%, respectively) while decreasing emissions intensity from land-use activities was the major factor to offset emissions growth (−39%). Climate change mitigation may depend on incentivizing consumer and producer choices to reduce emissions-intensive food products.</p

Implementation of carbon pricing in an aging world calls for targeted protection schemes

Understanding the impact of climate fiscal policies on vulnerable groups is a prerequisite for equitable climate mitigation. However, there has been a lack of attention to the impacts of such policies on the elderly, especially the low-income elderly, in existing climate policy literature. Here, we quantify and compare the distributional impacts of carbon pricing on different age-income groups in the United States, the United Kingdom, and Japan and then on different age groups in other 28 developed countries. We find that the elderly are more vulnerable to carbon pricing than younger groups in the same income group. In particular, the low-income elderly and elderly in less wealthy countries face greater challenges because carbon pricing lead to both higher rate of increase in living cost among low-income elderly and greater income inequality within the same age group. In addition, the low-income elderly would benefit less than the younger groups within the same income group in the commonly proposed carbon revenues recycling schemes. The high vulnerability of the low-income elderly to carbon pricing calls for targeted social protection along with climate mitigation polices toward an aging world

Nonconvex optimization for optimum retrieval of the transmission matrix of a multimode fiber

Transmission matrix (TM) allows light control through complex media such as multimode fibers (MMFs), gaining great attention in areas like biophotonics over the past decade. The measurement of a complex-valued TM is highly desired as it supports full modulation of the light field, yet demanding as the holographic setup is usually entailed. Efforts have been taken to retrieve a TM directly from intensity measurements with several representative phase retrieval algorithms, which still see limitations like slow or suboptimum recovery, especially under noisy environment. Here, a modified non-convex optimization approach is proposed. Through numerical evaluations, it shows that the nonconvex method offers an optimum efficiency of focusing with less running time or sampling rate. The comparative test under different signal-to-noise levels further indicates its improved robustness for TM retrieval. Experimentally, the optimum retrieval of the TM of a MMF is collectively validated by multiple groups of single-spot and multi-spot focusing demonstrations. Focus scanning on the working plane of the MMF is also conducted where our method achieves 93.6% efficiency of the gold standard holography method when the sampling rate is 8. Based on the recovered TM, image transmission through the MMF with high fidelity can be realized via another phase retrieval. Thanks to parallel operation and GPU acceleration, the nonconvex approach can retrieve an 8685$\times$1024 TM (sampling rate=8) with 42.3 s on a regular computer. In brief, the proposed method provides optimum efficiency and fast implementation for TM retrieval, which will facilitate wide applications in deep-tissue optical imaging, manipulation and treatment

Optimizing regional cropping systems with a dynamic adaptation strategy for water sustainable agriculture in the Hebei Plain

Unsustainable overexploitation of groundwater for agricultural irrigation has led to rapid groundwater depletion and severe environmental damage in the semi-arid Hebei Plain of China. Field experiments have recommended annual winter fallowing (i.e., forgoing winter wheat production) as the most effective way to replenish groundwater. However, adopting the recommendation across the Hebei Plain would lead to a significant reduction in total wheat production. This research aims to find the most favorable water-sustainable cropping systems for different localities in the Hebei Plain, which at the regional aggregation level maintains the uppermost overall levels of wheat and grain production respectively. Our simulations indicate that in the Hebei Plain, an optimal allocation of a wheat-early maize relay intercropping system and an early maize-winter fallow cropping system across the Hebei Plain could lead to significant water savings while minimizing grain production losses to around 11%. Compared to the prevailing wheat and summer maize cropping system, to prevent a drop in the water table, 39% of the current wheat cropping land would need to be fallowed in winter, reducing irrigation water use by 2639×106m^3. Replacing the prevailing wheat and summer maize cropping system with our optimized allocation system could lead to a 36% increase in total maize production and 39% decrease in total wheat production, resulting in total agricultural irrigation water savings of 2322×106m^3 and a total grain production reduction by 11%. The findings indicate the potential benefits of our cropping system adaptation method to meet the challenge of recovering local groundwater level with the least possible reduction of wheat and total grain production in the Hebei Plain

Implementation of carbon pricing in an aging world calls for targeted protection schemes

Understanding the impact of climate fiscal policies on vulnerable groups is a prerequisite for equitable climate mitigation. However, there has been a lack of attention to the impacts of such policies on the elderly, especially the low-income elderly, in existing climate policy literature. Here, we quantify and compare the distributional impacts of carbon pricing on different age–income groups in the United States, the United Kingdom, and Japan and then on different age groups in other 28 developed countries. We find that the elderly are more vulnerable to carbon pricing than younger groups in the same income group. In particular, the low-income elderly and elderly in less wealthy countries face greater challenges because carbon pricing lead to both higher rate of increase in living cost among low-income elderly and greater income inequality within the same age group. In addition, the low-income elderly would benefit less than the younger groups within the same income group in the commonly proposed carbon revenues recycling schemes. The high vulnerability of the low-income elderly to carbon pricing calls for targeted social protection along with climate mitigation polices toward an aging world

Agro-ecological suitability assessment of Chinese Medicinal Yam under future climate change

Chinese Medicinal Yam (CMY) has been prescribed as medicinal food for thousand years in China by Traditional Chinese Medicine (TCM) practitioners. Its medical benefits include nourishing the stomach and spleen to improve digestion, replenishing lung and kidney, etc., according to the TCM literature. As living standard rises and public health awareness improves in recent years, the potential medicinal benefits of CMY have attracted increasing attention in China. It has been found that the observed climate change in last several decades, together with the change in economic structure, has driven significant shift in the pattern of the traditional CMY planting areas. To identify suitable planting area for CMY in the near future is critical for ensuring the quality and supply quantity of CMY, guiding the layout of CMY industry, and safeguarding the sustainable development of CMY resources for public health. In this study, we first collect 30-year records of CMY varieties and their corresponding phenology and agro-meteorological observations. We then consolidate these data and use them to enrich and update the eco-physiological parameters of CMY in the agro-ecological zone (AEZ) model. The updated CMY varieties and AEZ model are validated using the historical planting area and production under observed climate conditions. After the successful validation, we use the updated AEZ model to simulate the potential yield of CMY and identify the suitable planting regions under future climate projections in China. This study shows that regions with high ecological similarity to the genuine and core producing areas of CMY mainly distribute in eastern Henan, southeastern Hebei, and western Shandong. The climate suitability of these areas will be improved due to global warming in the next 50 years, and therefore, they will continue to be the most suitable CMY planting regions