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Technological advances are crucial to the climate benefit of the CRP-corn ethanol system

Current LCIA methods, for example, are not able to properly evaluate potential adverse effects of Bt toxin on populations of non-target species and elevated risk of species invasiveness through genetic modifications . In addition, it should be noted that the trend of decreasing ecotoxicity impact is unlikely to continue for cotton and corn. Due to the dominant use of HR and Bt crops, pests and weeds have evolved to be increasingly resistant . As a result, farmers may need to resort to earlier pest control practices that rely more on conventional pesticides, hence increasing crops’ freshwater ecotoxicity impact. Nevertheless, the dynamics of pest management, and associated ecological impacts, further corroborates the importance of understanding the dynamics of agricultural systems. For many of the impact categories studied, the environmental impacts of US corn and cotton on average are roughly comparable on a per hectare basis, while cotton consumes more water and generates much higher freshwater ecotoxicity impact. However, the average results, mainly reflecting corn produced in the Midwest and cotton produced in the South, are inadequate to capture the likely environmental consequences of corn expansion into cotton, which has taken place in cotton-growing states in the South. The state-level results show that a land use shift from cotton to corn relieves freshwater ecotoxicity but may aggregate many other regional environmental impacts. Due to the limitation of data, a definitive conclusion may not be drawn for other Southern states where the cotton-to-corn land use change has also occurred. But our finding of tradeoffs based on the three states is probably generalizable for these other states considering that cropland there is generally less suitable for corn production than in the Midwest. Taking into account marginal yield and technological advances, the CPT for converting the CRP grassland for corn ethanol production in early 2000s, when the ethanol industry begun to grow, 30 planter pot ranges from 15 years for highly productive grassland with average corn yield to 56 years for infertile grassland with only 50% of average corn yield.

Considering the diminishing climate effect of later GHG emissions within a 100-year time frame, the CPT estimates would increase to 17 to 88 years. Understandably, the shorter the payback time, the less strongly it would be affected by the consideration of emission timing.In the no technological advances scenario, most of the grassland would not produce any climate benefit within a 100-year time frame. Even for the highly productive grassland, it would take up to 46 years before the system could start generate carbon savings. Last, because the technology and productivity of the corn ethanol system changes over time, the timing of land conversion also plays a part in the CPT estimation. If land conversion took place in 2010, the CPT estimates would be 13 to 65 years, as opposed to 17 to 88 years for land conversion occurring in early 2000s. The environmental impacts per hectare crop harvested for most of categories studied were relatively stable in the past decade. This is because these impact categories are dominated by the direct and indirect emissions of nutrient, particularly nitrogen fertilizers, and the amount of nutrient inputs did not change much in the past decade. In contrast, the freshwater ecotoxicity impact per ha corn harvested declined by around 50% from 2001 to 2010 and per ha cotton produced declined by 60% from 2000 to 2007. These downward trends are due in large part to the increasing adoption of genetically modified organisms , which have resulted in reduced use of insecticides and replacement of some conventional herbicides with more benign ones, particularly glyphosate and compounds. Soybean production in the USA has also adopted GMOs widely, and this should have also led to a decline in soybean’s freshwater ecotoxicity as with corn and cotton. But because of the invasion of soybean aphid, a native of Asia, which have resulted in a substantial increase in insecticides use, the freshwater ecotoxicity impact per hectare soybean harvested increased by a factor of 4 from 2002 to 2012. In the meantime, on-farm irrigation water use per ha soybean harvested increased by about 50%.

This increase is due probably to the expansion of soybean into marginal land where intensive irrigation is needed. Implications of the above findings have been extensively discussed in individual chapters. Discussed below is the implication of considering marginal yield in the case of direct land use change for studies of indirect land use change and consequential LCA modelling. Some of the points, such as the importance of additional corn and carbon, have been somewhat touched upon in , but the discussion here is more detailed and from a methodological point of view. Early LCA estimates differed with respect to whether corn ethanol offers carbon benefits in displacing gasoline . Notably, the findings of the Cornell Professor David Pimentel were all negative , leading him to strongly oppose the use of corn ethanol . But subsequent LCA studies, with updated data and ethanol coproducts correctly accounted for, seemed to converge on that corn ethanol has a moderately smaller carbon footprint than gasoline, thus contributes to climate goals . However, a core factor was neglected in all these LCA studies, that is, land use change . The reason land use change did not come into play in these LCA studies is that they were basically a portrayal of exiting corn ethanol with corn grown on long-standing cornfield. But with increasing ethanol demand driven by federal policies like the renewable fuel standard aimed partly at mitigating climate change , what mattered was not the carbon footprint of existing corn ethanol but of additional corn ethanol. The key issue then became the supply of additional corn. Yield increase through intensification could produce more corn in the long run, but was hardly enough, and too uncertain, to meet annual ethanol expansion. The pressure was on land resources . Higher corn prices between 2005 and 2008 were driving farmers to bring new cornfield into production by converting natural habitats or to reallocate existing cropland to growing more corn . Either way, however, has dire carbon consequences that run counter to the initial climate goal of the federal policies.

Direct conversion of forest or grassland to grow corn for ethanol production would release a substantial amount of carbon stored in soil and plant biomass, creating a “carbon debt” that may take dozens of years to be repaid by carbon savings from substituting corn ethanol for gasoline . Similarly, reallocation of existing cropland to growing more corn could generate similar nets effects through market mediated mechanisms . For example, if the extra corn came at the expense of reduced soybean production, this could drive up global soybean prices and led farmers across the world to produce more soybeans by converting forest and grassland, resulting in loss of large amounts of carbon as well. In hindsight, that the majority of LCA studies failed to take account of land use change has a lot to do with the methodology they took, namely, attributional LCA . In these studies, corn ethanol’s carbon footprint was quantified in the simple accounting manner. They first estimated carbon emissions at different life-cycle stages based on existing, average corn farming practices and ethanol conversion technologies, and then summed them up and compared the total against the carbon footprint of gasoline. If they found that corn ethanol has a lower carbon footprint,plastic growers pots they would conclude that corn ethanol offers carbon benefits in displacing gasoline. Underneath the conclusion was the implicit assumption that the finding based on existing, average technologies would hold true for any amounts of additional corn ethanol. As argued above, however, the assumption is invalid. Because of land constraints, carbon emissions associated with additional corn ethanol would be much different from that associated with existing corn ethanol based on corn from long-standing cornfield . And it is the additional corn ethanol and associated carbon emissions that ultimately matter from both a policy perspective and in terms of reducing greenhouse gas emissions. In a word, consequential LCA looking into changes and effects is more relevant and better suited for addressing policy questions with potentially large economic and environmental consequences . But it should be noted that which specific methods to use for consequential modelling needs further research . The core to consequential modelling is the consideration of marginal changes, or processes actually to be affected by decisions at hand . In the case of dLUC, marginal changes include land conversion, additional corn production on the converted land, and additional ethanol produced and used. Particularly, the additional corn grown on the converted land sequesters additional carbon from the atmosphere. Without the additional carbon uptake, corn ethanol’s carbon benefits would not be possible as rightly pointed out by Searchinger . In short, it is everything that takes place on the converted land, together with additional ethanol production and use, that should serve as the basis for calculating corn ethanol’s total life-cycle carbon emissions in the case of dLUC .

Although Fargione et al. rightly considered land conversion and associated carbon loss, they relied on prior LCA studies , which were based on corn from long-standing cornfield, to estimate everything else. In so doing, they failed to recognize that newly converted land is generally not as fertile as cornfield persisting in cultivation and that corn ethanol originating from low-fertility land would provide smaller carbon benefits than corn ethanol originating from long-standing cornfield. Accounting for the actual yield of the converted land , as demonstrated by Yang and Suh , could substantially increase the time it takes for the use of corn ethanol to repay the carbon debt created by the initial land conversion. Exiting iLUC studies calculate corn ethanol’s total carbon emissions in the same way as do previous dLUC studies by adding carbon loss from land conversion to the carbon footprint of corn ethanol. When exposed with the same consequential reasoning, however, the iLUC literature commits the same error as committed in previous dLUC studies. But for iLUC effect it is beyond the actual yield or fertility of the converted land; what and how new crops are produced following land conversion matters. To drive home, let us consider a simple, hypothetical example of iLUC. Suppose, in response to increasing ethanol demand, part of U.S. corn was diverted to ethanol production at the expense of reduced exports to China. Total U.S. corn production and areas thus remained unchanged. This drove up Chinese corn prices and subsequently led Chinese people in rural areas to eat more rice, which drove up rice prices there and led Chinese subsistence farmers to convert reforested land to rice cultivation. What are the carbon consequences of corn ethanol expansion in this example? However, because U.S. corn production did not change or was not affected in this example, it is irrelevant to corn ethanol’s carbon consequences, as is the corn from longstanding cornfield in the case of dLUC. There was no additional carbon uptake from corn growth, nor were there additional carbon emissions from the use of agricultural inputs in corn production. What matters, instead, is the additional rice cultivation in China – which took place to compensate for the U.S. corn diverted to ethanol production – and associated carbon uptake and emissions . Of course, this is an extremely simplified example. Real-world consequences of U.S. corn ethanol expansion could be much more complicated, involving conversion of assorted natural habitats and different croplands brought into production in different countries. In any case, carbon uptake and emissions associated with whatever cropland being brought into production worldwide – including, likely, additional corn – should count towards the carbon consequences of ethanol expansion. Simply adding carbon loss from indirect land conversion across the world to the carbon footprint of U.S. corn ethanol is not meaningful from both theoretical and empirical perspectives. In addition to estimation of carbon loss from indirect land conversion , future studies need also direct efforts to account for what and how crops would be grown following land conversion and associated carbon uptake and emissions. In the chapter on carbon payback time , we assumed a perfect 1:1 displacement ratio between corn ethanol and gasoline on an energy basis, an assumption also used in previous carbon payback time studies .

Climate change also has an impact on seasonal changes and timing of precipitation

San Diego’s landscape has historical and cultural importance, with more than 18 federally recognized tribes which is more Indian reservations than any other county in the United States . The combination of these natural open and agricultural lands, pristine coastal areas, diverse urban neighborhoods, and rich cultural history makes San Diego a vibrant and unique region that supports a variety of human communities and industries.Agricultural rangelands and croplands are an important feature within San Diego’s landscape, constituting 5.11% of the county’s total land with more than 250,000 acres and 5,000 farmers . These working lands are deeply rooted in the county’s landscape, holding historic, economic, environmental, and social significance while providing a multitude of local benefits. Not only are these working lands important to the county for providing the public with local products and counteracting urban growth, they have significant economic value. Ranked 12th largest in the nation, San Diego agriculture has an estimated $2.88 billion annual value to the economy . The region’s agriculture encompasses rangeland, pastureland, and cropland, used for growing annual, perennial, nursery, and field crops . Top crops include nursery products and crops, avocados, citrus, and miscellaneous vegetables . While the relatively moderate Mediterranean climate, in addition to a range of micro-climates, makes San Diego an ideal place to grow agricultural crops and livestock products , there are many challenges associated with farming in the region. San Diego’s current farmers face constraints on water-use efficiency and water availability that limits crop selection and efforts efforts to maximize production while also making a profit. From high irrigation demand,blueberry plant container increasing water costs and land prices, to pervasive pest and plant diseases, San Diego farmers have no choice but to utilize innovative farming techniques and choose smart crop choices .

Due to historic development patterns in San Diego, agriculture is often embedded within urban areas, with more small farms than any other county in the nation. Because of the average size of farms, the agricultural sector is spatially scattered throughout the unincorporated county, which can be difficult for identifying and monitoring existing agricultural land and practices. Nonetheless, San Diego’s agricultural production remains more valuable than many other urbanized areas of California, including San Francisco, Orange County, and Los Angeles combined . San Diego’s agricultural landscape is composed of diverse lands, with varying terrain, vegetation, and agricultural use. These lands provide valuable and beneficial services for the region’s food supply and ecosystems, including creation of wildlife, habitat, food for people and pollinators, and water filtration .At a latitude of approximately 32 degrees North, San Diego is situated in the heart of the subtropical climate zone. The region encompasses a unique landscape, positioned between the coastal zone of the Pacific Ocean to the west and the foothills, interior mountains, valleys, and deserts to the east. Like most areas in California, the region is known for its Mediterranean climate in which it experiences hot, dry summers, and mild winters . San Diego’s climate is characterized seasonally by latitudinal climate influences that cause this subtropical dryness in the summer and midlatitude storm-tracks in a concentrated wet season from October through April . Additionally, coastal low clouds and fog are a defining characteristic of San Diego’s climate. CLCF typically persist throughout early summer months, helping moderate heating, buffer dryness and solar insolation, while also providing cooling and water for the region’s coastal ecosystems . The combination of complex topography, coastal effects, and wide altitudinal ranges coupled with subtropical and midlatitude influences results in a range of diverse micro-climates throughout the region . In addition to impacting temperatures and humidity on the coast and further inland, the combination of these factors produce variability in monthly precipitation during the winter months . With annual precipitation totals varying from as little as 50% to greater than 200% of long-term averages, California experiences the largest yearly variations in precipitation compared to any other region in the U.S .

In particular, the year-to-year variability in southern California is higher than anywhere else in the U.S . The average annual precipitation for San Diego is 10.34 inches , however, historical averages reaching as low as 3.3 inches in 2002 and as high as 22.60 inches in 2005 highlight the region’s large inter-annual variability. Variability in precipitation is primarily tied to the number of extreme precipitation events, known as Atmospheric Rivers . ARs contribute to 68% of extreme-rainfall accumulations in southern California . Figure 4 illustrates the correlation between the number of these top 5% of rainy days and precipitation variability. Given that the occurrence of a few AR events each year dictate floods, droughts , and water availability , understanding these extreme events are important for regional weather forecasting, infrastructure planning, and resource management. The San Diego County Water Authority has served as the wholesale supplier for San Diego since its creation in 1944, working to secure reliable water supply for the region. SDCWA’s water supply sources have changed throughout San Diego’s unique historical periods. Despite these changes, SDCWA has consistently relied on imported water in some capacity . Currently, San Diego County imports around 80% of its water supply, using both local and imported sources . In the past, San Diego relied heavily on a single supplier of water, the Metropolitan Water District of Southern California , which includes water from Northern California and the Colorado Basin. Since the enactment of the Colorado River Compact in 1922, allowing for the diversion of water from the river to surrounding states, Colorado has been a major supplier for San Diego . In 1991, the MWD constituted 95% of San Diego’s water supply . In the last two decades, after an extensive drought that caused MWD to reduce water delivery to San Diego, SDCWA has developed several strategies and long-term plans to diversify the region’s water supply portfolio. These strategies aim to improve the region’s water infrastructure, promote water-use efficiency, and ultimately secure reliability of supply . In 2017, supply from MWD had significantly declined to 40%, allowing for inclusion of other sources. Agreements made with the Imperial Irrigation District, and the Coachella and All-American canals, which source water from the Colorado Basin, contributes another 40% of imported water to San Diego’s current supply portfolio. Local sources contribute the remainder of supply, including groundwater, recycled water, and desalination . Agriculture is one of the many sectors that is greatly dependent on these water resources. With water pricing escalating since the early 1990’s, water costs have been the primary water concern for San Diego farmers .

As drought conditions increasingly threaten the region’s imported water sources, farmers have shifted their focus towards water availability as well . While SDCWA has worked to ensure reliable and diversified water sources over the last few decades, new water sources have proven to be expensive . In the last 12 years, the price of water has tripled, while the revenue from farm products are generally consistent, creating challenges for farmers across the region. Water alone constitutes the largest monthly expense for many farmers . Thus, farmers are eager to adopt strategies that maximize water-use efficiency, minimize use and overall costs, and increase financial returns. For farmers who choose to participate in SDCWA’s special agricultural water pricing, water charges are priced at discounted rates. Nonetheless, costs per acre foot remain high, and much of the sector, specifically nursery, flower, fruit, and livestock farmers, do not participate . Not all of San Diego receives the imported water supplied by MWD and geographically,30 plant pot the majority of the unincorporated area is reliant on groundwater-dependent districts or private wells that are managed separately from SDCWA . Thus, these areas are completely reliant on groundwater resources and are impacted by its availability. The agricultural sector also relies on groundwater resources, and is considered one of the “large quantity” groundwater users . These groundwater resources are often limited due to unfavorable geology, resulting in aquifers with limited groundwater in storage volume and/or groundwater recharge. Several areas throughout the county that are groundwater-dependent, specifically the unincorporated county, face groundwater hydrology issues. Given that agricultural users are not regulated or metered for water quantity, these large quantity users can create localized groundwater problems throughout the groundwater dependent areas . It is clear that water resources, availability, and supply are major focuses for the county, especially the agricultural sector. With the need to limit water use to allow for profits, water concerns continue to be a driving force for the conservation efforts of San Diego’s farming community. It is projected that over the next several decades, California will continue to experience several changes associated with climate change, including sea level rise, precipitation patterns, and temperatures. Amid historic coastline and mountains, San Diego region encompasses many diverse climate zones. In turn, the region will likely experience a myriad of changes with dynamic, complex, and compounded effects. As a result, the county will face several challenges that could ultimately threaten the natural and human landscapes that it supports. While the region’s diverse ecological systems, industries and communities have adapted to San Diego’s variable and seasonal climate, climate change could exacerbate these conditions and ultimately threaten the survival of these valuable systems . As one of the most “climate-challenged” regions in North America, it is critical that the county understand these regional variations in climate impacts and vulnerability .

In the region, climate change will significantly increase yearly average temperature over the next several decades, with projections ranging from 5-10° Fahrenheit depending on the Representative Concentration Pathway greenhouse gas concentration and region . San Diego and neighboring areas will face varying changes in the average hottest day per year, daily maximum temperature and daily minimum temperature because of the region’s diverse topography and distinct micro-climates. Under RCP 8.5, representing a high concentration scenario, the average hottest day per year will increase from the historic range of 90-100° F to 100-110° F in coastal zones, and from 105-115° F to 110-125° F in desert regions . Temperature extremes are projected to increase, with climate warming increasing duration, frequency, and intensity of heat waves compared to historic climate . The probability of heat waves varies regionally, with some locations expected to have a greater probability of increase in the number of extremes, and in either daytime or nighttime heat waves. Extreme temperature events and increasing Tmax will further intensify the impacts of drought . Although it is projected that there will be fewer total wet days and a decrease in the number of ARs globally, these wet events will likely increase in width and length by 25%, in addition to intensity . With a Mediterranean climate that is uniquely balanced between both mid-latitude storms and expanding subtropical zones, projections for California’s precipitation regime show more uncertainty and variability compared to most other Mediterranean climates around the world. While models consistently project future drying over Mediteranean climates globally, projections for California diverge from these trends, becoming wetter in winter aggregate and experiencing increases in mean precipitation . As a result, the region will likely experience wetter winters yet longer, dryer warm seasons, contributing to increased year-to-year variability. With intensified extreme precipitation events, climate models indicate that the variable character of Southern California’s precipitation will continue to increase .It is projected that precipitation will increase during the region’s concentrated wet winter season, while decreasing in both autumn and spring . Warmer temperatures are causing winter precipitation to fall in the form of rain rather than snow, meaning that the snow pack that acts as a natural reservoir for the state’s water supply will be diminished . As less precipitation is stored in these snow pack reservoirs, compounded with warming temperatures, the state is experiencing earlier springtime snow melt . These projected changes in snow pack, precipitation and springtime snow melt will continue to challenge many regions of California, defining the state’s current and future water resources . Although local snow pack is not significant, loss of snow pack in the state overall will negatively impact the imported water supplies that San Diego relies upon.Coastal low clouds and fog that migrate along the West Coast fluctuate on annual and decadal scales, as a response to a combination of naturally occurring climate and weather patterns .