Hi need help doing this assignment! i have uploaded 5 files along with the questions, which are to be used for first 2 questions. The articles are to be used for the first question and the chapter is

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Hi need help doing this assignment! i have uploaded 5 files along with the questions, which are to be used for first 2 questions. The articles are to be used for the first question and the chapter is to be used for the second Question. There are total of 4 Questions

Hi need help doing this assignment! i have uploaded 5 files along with the questions, which are to be used for first 2 questions. The articles are to be used for the first question and the chapter is
Projecting a spatial shift of Ontario’s sugar maple habitat in response to climate change: A GIS approach Laura J. BrownSociety, Culture and Environment and Geography, Wilfrid Laurier University Daniel LamhonwahDepartment of Geography, Queen ’s University Brenda L. MurphySociety, Culture and Environment and Geography, Wilfrid Laurier University Canada is the world ’s largest producer of maple syrup. Syrup production depends on weather and climatic conditions of the sugarbush. However, forest ecosystems are highly sensitive to climate change. The effect of rapidly changing precipitation and temperature patterns on tree species is of concern as these long-lived organisms cannot quickly adapt to the new environmental conditions in which they find themselves. As temperatures increase it is expected that there will be a change in species ’ranges poleward. This study uses Multi-Criteria Decision Making (MCDM) and Geographic Information System (GIS) weighted sum analysis to project near future (2050) and distant future (2100) suitability maps of sugar maple (Acer saccharum) habitat in Ontario associated with three different Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) scenarios. Our maps project an overall decrease in the amount of suitable habitat within the current sugar maple range under the scenarios modelled, which intensi fies in the later time period. Furthermore there is a projected shift in central and southern Ontario from a region dominated by suitable habitat to one dominated by unsuitable habitat. Keywords: Sugar maple, Multi-Criteria Decision Making, Geographic Information Systems, climate change, habitat suitability maps La projection d ’un d ecalage spatial de l ’habitat de l ’ erable a sucre en Ontario suite aux changements climatiques : une approche fond ee sur les SIG Le Canada est le plus grand producteur mondial de sirop d ’ erable. La m et eo et les conditions climatiques dans les erabli eres comptent parmi les facteurs qui in fluencent fortement la production de sirop. Cependant, les ecosyst emes forestiers sont s ev erement touch es par les changements climatiques. L ’effet de l ’ evolution rapide des r egimes de pr ecipitations et de temp erature sur les esp eces arborescentes est pr eoccupant, parce que ces organismes d ’une longue dur ee de vie ne peuvent pas s ’adapter rapidement aux nouvelles conditions environnementales locales. On pr edit qu ’avec l ’augmentation des temp eratures, la distribution des esp eces se d eplacera vers le nord. A partir d ’un calcul de la somme pond er ee s ’appuyant sur des outils d ’aide ala d ecision multicrit ere (ADM) et des syst emes d ’information g eographique (SIG), cette etude entrevoit diff erentes perspectives dans un avenir rapproch e (2050) et lointain (2100) en dressant des cartes de l ’indice de qualit edel ’habitat de l ’ erable a sucre (Acer saccharum) en Ontario et en tenant compte des trois sc enarios propos es par le Groupe d ’experts intergouvernemental sur l ’ evolution du climat (GIEC) dans son quatri eme rapport d ’ evaluation (RE4). Ces cartes permettent d ’extrapoler une diminution globale de l ’habitat favorable dans l ’aire actuelle de distribution de l ’ erable a sucre, conform ement aux sc enarios mod elis es, et Correspondence to/Adresse de correspondance: Laura J. Brown, Society, Culture and Environment and Geography, Wilfrid Laurier University, 73 George St Brantford, Ontario, Canada N3T 2Y3. Email/Courriel: [email protected] The Canadian Geographer / Le G eographe canadien 2015, 59(3): 369–381 DOI: 10.1111/cag.12197 © 2015 Canadian Association of Geographers / L’Association canadienne des g eographes qui va en s’intensifiant alafindelap eriode. En outre, on peut etablir des projections selon lesquelles l’habitat favorable qui domine pr esentement le centre et le sud de l’Ontario sera remplac e par un habitat majoritairement d efavorable. Mots cl es : erable a sucre, aide alad ecision multicrit ere, syst emes d’information g eographique, changements climatiques, cartes de l’indice de qualit edel’habitat Introduction “Nothing is more Canadian than maple syrup” stated the Minister of Agriculture Gerry Ritz (Canadian Food Inspection Agency 2012). The trees of Canada’s forests have played a part in the historic development of the nation and the maple tree has been of particular importance both commercially and culturally. Since the 1700s, long before it was instituted on our national flag (February 15, 1965) the maple leaf has been the symbol of Canadian identity (Canadian Heritage 2013). Maple syrup production is part of Canada’s cultural identity and these trees are a dominant species in the forests of the northeastern United States and eastern Canada (Minorsky 2003; Duchesne et al. 2009; Murphy et al. 2012). Canada is the largest maple syrup producer in the world, producing 87 percent of the world’s supply with the remaining 13 percent coming from the United States. The maple syrup industry is an important part of the rural economy and in 2012 was worth an estimated $314.7 million (Statistics Canada 2012). Ontario is the third largest maple-producing province with sales of $11.2 million and production concentrated primarily in the Waterloo-Wellington areas in the southwest, and Lanark County in the east (Figure 1) (Agriculture and Agri-Food Canada 2007). Climate change is affecting forests throughout the world, but the impacts of these changes vary by region. Forest ecosystems are highly sensitive to the rapidly shifting temperature and rainfall regimes associated with climate change because the trees are long lived. When mature trees established them- selves it was under different growing conditions than those created by the present or future climatic conditions and forest species may not be able to adapt quickly enough to these changes (Lindner et al. 2010). Sugar maples (Acer saccharum), upon which the maple syrup industry depends, need to be 40––50 years old before they can be tapped safely, and can live to be 300––400 years of age with an average life span of 150––200 years (Godman et al. 1990).The distribution of plants is controlled by competition and the limiting climatic factors of temperature and precipitation (Perkins 2007). In Ontario, the Canadian Coupled Global Circulation Model (CC-CGCM) projects warmer temperatures, a decrease in precipitation, and increased evapotrans- piration rates resulting in moisture deficits in the summers for most of the province, as a consequence of climate change (Colombo et al. 2007). Climate change has the potential to influence the distribu- tion and composition of Canadian forests, as tree species will migrate when the location of favourable growing conditions change (Parker 1998). Trees are not mobile and“migration”in this context refers to successful reproduction and competitiveness in their new environment (Taggart and Cross 2009). As temperatures increase, it is expected that there will be a shift in plant species’ranges towards the poles and towards higher altitudes based on species’ climatic thresholds (Thomas and Packham 2007) and the availability of other suitable ecosystem conditions (e.g., soil, topography, nutrients). A change of as little as 2°C to 3°C in average temper- atures is enough to change the spatial distribution of trees in Ontario (Stewart 2003). McKenney et al. (2007a) project that sugar maple stands will likely migrate poleward. In his congressional testimony, Perkins (2007) warns that the maple industry of New England in the United States is at risk as a result of climate change due to an expected shift in forest composition causing the loss of the maple- beech-birch forest type within 100þyears. There is also growing concern amongst maple syrup pro- ducers and researchers that climate change will dramatically affect the current stands of sugar maple trees in Ontario (Murphy et al. 2009, 2012). Currently, the maple industry is experiencing significant variations in year to year temperatures, precipitation levels, and production rates; at this point it is unclear if these are normal fluctuations or a shift towards more variation due to climate change (Murphy et al. 2009, 2012). For example, in the spring of 2012 a decline of 54.3 percent in Ontario’s The Canadian Geographer / Le G eographe canadien2015, 59(3): 369–381 370 Laura J. Brown, Daniel Lamhonwah, and Brenda L. Murphy maple production was attributed to a rapid rise in spring temperatures and the resulting short dura- tion of sap flow (Statistics Canada 2012). This warm spring was followed by a summer with record- setting highs and little rain (CBC 2012). In contrast, the very cold, wet spring of 2013 reduced volumes for some producers, especially in northern parts of Ontario. Most producers reported average to high volumes but noted an unusually high production of light and very light syrup and higher levels of“sugar sand”(i.e., nitre: the minerals and nutrients that accumulate as the sap boils). Some producers suggest that the high levels of nitre are related tothe previous summer’s drought and others are worried about the long-term health of the sugar- bush as a result of severe drought (R. Bonenberg, pers. comm. 2013). However, beyond such anecdot- al evidence, there is little substantive research available to help sugarbush managers understand these patterns or develop adequate adaptive plan- ning strategies for the future. To understand the potential future changes facing sugar maple ecosystems and syrup production, and contribute to effective climate change adaptation, the future of Ontario’s sugar maple tree habitat was modelled using a Geographic Information Figure 1 The maple syrup producing regions of Ontario. After: Murphy et al. 2009. The Canadian Geographer / Le G eographe canadien2015, 59(3): 369–381 Climate change and maple habitat 371 System (GIS) weighted sum, site suitability analysis approach. This research is part of a larger ongoing research project on maple syrup, resilience, and climate change. Several other techniques have been used to forecast future habitat suitability due to climate change. There are numerous empirically- based species distribution models (SDMs) which utilize statistical techniques or machine learning approaches to predict habitat niches for both plants and animals (e.g., Austin 2007; Elith and Leathwick 2009; Morin and Thuiller 2009). Climate envelops (e.g., Hamann and Wang 2006; Lawler et al. 2006; McKenney et al. 2009) and niches models (Morin and Thuiller 2009) have been used to predict species distribution based on environmental data. For this study we chose to use a GIS approach because we wanted to generate habitat suitability maps to inform the adaptive strategies of Ontario’s maple syrup producers. The climate projections were generated based on the Intergovernmental Panel on Climate Change Fourth Assessment Report (AR4) (IPCC 2007) ap- proach that utilized several scenarios of potential future concentrations of greenhouse gases. Habitat suitability maps were generated for 2070 and 2100 by combining known optimal growing conditions and environmental stress responses of sugar ma- ples with future climatic conditions. This species grows best in cool, moist climates (Horsley et al. 2002), in deep, slightly acidic to neutral loamy soils (Godman et al. 1990; Nyland 1998; St. Clair et al. 2005; Barkley 2007), and it is stressed by both drought (Bertrand et al. 1994; Burton et al. 1998) and excessive soil moisture (Godman et al. 1990). Steep angled surface slopes often have drier soils due to poor infiltration and higher surface runoff. In- creased air temperatures can result in drier soil moisture levels as evapotranspiration rates in- crease. Precipitation, proximity to water bodies, and proximity to the water table will influence the amount of available soil moisture. Sugar maple seed germination occurs when spring temperatures are about 1°C (Godman et al. 1990) and for natural recruitment of new trees this factor was included. Materials and methods Study area To assess the potential impact of climate change faced by today’s maple syrup industry, the studyarea was geographically bounded by the current extent of the sugar maple range in Ontario. Ontario contains two distinct physiographic regions, and three forest regions. The Canadian Shield region is characterized by thin soils and areas of exposed Precambrian igneous rock. South of the Shield, the St. Lawrence Lowlands are characterized by surficial deposits and features associated with glacial activi- ty. The boreal forest dominates the north, transi- tioning to a mixed forest region in the central part and then into a deciduous region in the southern parts. It is within the mixed forest and deciduous region that the current range of sugar maples is bounded. Input data sets The data sets used in this study to simulate the environmental conditions most suitable for sugar maple trees fall into two categories: dynamic climatic data and static landscape data (Table 1). Since the purpose of this study was to assess the effect of climate change on sugar maple habitat, the model manipulates the climatic variables, while the Table 1 Data sets used in this study and their sources. Data Type Data Set Time Period Source Climate CGCM3.1/T47 time-slice simulations SRES A1B, A2 and B1 Monthly precipitation, minimum and maximum average temperaturesHistoric (1971-2000); Near Future (2041-2070); Far Future (2071-2100)National Forest Service, Natural Resources Canada Landscape Location of Ontario forest stands with 95%þsugar maple contentPresent Ontario Ministry of the Environment Ecozones Soil Landscapes of Canada (SLC) version 3.1.1 data set, Ontario Ministry of Natural Resources Soil; group; drainage; rooting depth Surface slope The Canadian Geographer / Le G eographe canadien2015, 59(3): 369–381 372 Laura J. Brown, Daniel Lamhonwah, and Brenda L. Murphy landscape conditions that most influence sugar maples are held constant. We identified these conditions through our previous work with pro- ducers (Murphy et al. 2009, 2012), the literature and reports (e.g., Godman et al. 1990; Foster and Morrison 1992; Bertrand et al. 1994; Luzadis and Gossett 1996; Burton et al. 1998; Nyland 1998; Horsley et al. 2002; St. Clair et al. 2005; Barkley 2007; USDA Natural Resources Conservation Service 2006; Bonenberg, pers. comm. 2013). The climate data sets include minimum spring and maximum summer temperatures and annual precipitation, while the landscape data sets include surface slope, soil type and acidity, drainage, and rooting depth. An additional data set mapping Ontario’s forest ecozones was also used. There were three time periods of climate data used in this study, the historic period (1971––2000), the near future (2041–– 2070), and far future (2071––2100). The historic period was used to capture the climatic conditions for the habitat of the current range of sugar maples. The two future time periods were chosen in order to project changes to sugar maples within the current and next generation of sap producers. Future climate projections were generated by the Canadian Global Circulation Model (version CGCM3.1/T47) under AR4 scenarios—B1 (low CO 2concentrations), A1B (mid CO 2concentrations), A2 (high CO 2con- centrations). Of the scenarios available at the time of this research, these three scenarios were chosen because they represented the modelled range of low, medium, and high future carbon concentra- tions and likely associated climate impacts. The climate data used were monthly minimum spring and monthly maximum summer temperatures along with monthly precipitation (used to calculate annual precipitation) for the future time periods. Procedures Each of the key climatic and landscape factors were imported as individual layers into ArcMap 9.3 and converted into a raster data set. The model cell size for each layer was 180 km to correspond with the CGCM3.1/T47 climate data sets. Multi-Criteria Decision Making (MCDM) (Hopkins 1977; Carver 1991; Pereira and Duckstein 1993) was used to reclassify and assign numeric values to each of the input landscape and climate factors or criteria, and weighted sum analysis was applied to produce the final habitat suitability maps.The climatic and landscape input data sets had various units of measure and/or were already grouped into classes. Before they could be used in this study the data sets were reassigned into classes with a scaled value between 1 and 5 based on the environmental conditions conducive to optimal habitat for sugar maple growth. In this study a value of 1 represents one end of the scale with conditions most suitable for sugar maple growth, while a value of 5 represents the other end of the scale where conditions are least favourable. For example, the SLC soil drainage data set was originally classified into six classes: well drained, moderately well drained, imperfectly drained, poor- ly drained, rapidly drained, and very poorly drained. Sugar maples grow best in sites with well drained soils (Foster and Morrison 1992; Nyland 1998), so soils originally classified as well drained were reassigned a value of 1, moderately well drained soils were reclassified with a value of 2, imperfectly drained with a value of 3, while a value of 4 was assigned to both the poorly drained and rapidly drained classes and finally, since sugar maple roots are very sensitive to flooding (Godman et al. 1990), very poorly drained soils were reassigned a value of 5 (Table 2). It should be noted that although the range of reclassification values were between 1 and 5, the value of 5 was only assigned to harsh conditions that would severely compromise sugar maples. The heat stress associated with summer temperatures above 30°C, poorly drained soils, and the Hudson Plains Ecozone were all reclassified with a value of 5 (see Table 2 for full disclosure of all reclassification values). The breakpoints between classes for the landscape factors were predeter- mined by their original classifications in the Soil Landscapes of Canada data sets shown in the Class column of Table 2. The climate-based factors were classified into temperature or precipitation ranges first and then assigned a reclass value from 1 to 5. For maximum average summer temperature, 23°C was chosen as the threshold (reclass¼1, optimal) because this is the highest May to August climate average for any location within the study area. Any average temperature higher than this would be considered above the 1971––2001 normal, and negatively affect sugar maple growth due to changes in soil moisture and evapotranspiration rates and at 30°C or higher induce heat stress. The breakpoint of 2° between classes that span 3° was decided upon because a change in average The Canadian Geographer / Le G eographe canadien2015, 59(3): 369–381 Climate change and maple habitat 373 temperature of 2°C to 3°C is enough to change the spatial distribution of tree species in Ontario (Stewart 2003). For minimum spring temperatures, 0°C was chosen as the threshold (reclass¼1, opti- mal) because saplings need above freezing temper- atures to germinate. Any temperatures<0°C were less than optimal, and reclassed 2 through 4. Although a cold spring would decrease the chances for a season’s seedling germination, it would not kill existing stands. Therefore, it was decided a reclass of 5 for any temperature would be too extreme. Sugar maples grow in climates with annual precipi- tation of 500 to 2000 mm; anything above or below this range was given a value of 4. Midrange was reclassed as 1 for optimal. Precipitation values oneither side of the midrange but still falling within the 500mm to 2000mm, were reclassed as 2 for acceptable, but not optimal. The original classifica- tion and reclassification values for all the climate and landscape factors used in this study are shown in Table 2. The weighted sum function was applied to all reclassified layers to generate the model output. Criteria weights for each factor were generated using a decision matrix method called“pairwise ranking comparison”(Saaty 1980; Eastman et al. 1995; Jankowski and Andrienko 2001). This is a method that can be used to establish the priority or ranking of importance between elements. The first step is to make pairwise comparisons between each Table 2 The data set classes and reclassification values for all the climate and landscape habitat factors used in this study Factor group Data Set Class Reclassified value Climate Max. Average Summer Temperature (May to August) 23°C 1 >23°C to 25.9°C 2 26°C to 27.9°C 3 28°C to 29.9°C 4 30°C 5 Min. Average Spring Temperature (March to June) 0°C 1 -1°C to -3.9°C 2 -4°C to -5.9°C 3 -6°C 4 Annual Precipitation (summed monthly data) 1000 mm to 1500 mm 1 500 mm to 1000 mm 2 1500 mm to 2000 mm 2 >2000 mm 4 <500 mm 4 Landscape Drainage Well drained 1 Moderately well drained 2 Imperfectly drained 3 Poorly drained 4 Rapidly drained 4 Very poorly drained 5 Depth to Bedrock 100 cm 1 75 cm to 99.9 cm 2 50 cm to 74.9 cm 3 25 cm to 49.9 cm 4 Soil Acidity Basic, neutral to slightly acidic 1 Slightly acidic 2 Moderately acidic 3 Very acidic 4 Slope 1% to 20% 1 21% to 40% 2 41% to 60% 3 61% to 90% 4 Ecozone Mixed wood plains 1 Boreal shield 1 Hudson Plains 5 The Canadian Geographer / Le G eographe canadien2015, 59(3): 369–381 374 Laura J. Brown, Daniel Lamhonwah, and Brenda L. Murphy contributing factor and build a matrix. A common scale for comparison is the 1––9 scale where an increase in value is associated with an increase in importance (Saaty 1980; Eastman et al. 1995; Jankowski and Andrienko 2001). In this study, the relative importance of pairs of factors were as- sessed and ranked based on their contribution to suitable habitat. To our knowledge there isn’ta publication that ranks the optimum factors of sugar maple habitat, hence the literature providing infor- mation on sugar maple growth previously cited was reviewed to guide these pairwise ranking decisions (see Table 3 for pairwise rankings). For example, we know that sugar maples can grow on both steep and shallow slopes but that they are sensitive to soil moisture. Therefore, soil drainage and maximum summer temperatures (factors both influencing soil moisture) were ranked as“strong importance”(with an associated value of 5) when compared with slope. Each pair of factors was compared and ranked. While assigning ranking to the factors in this study it was decided that“strong importance”was the most any factor could be ranked over any other. Sugar maples can be stressed by high summer temper- atures but can grow on steep to shallow slopes, so summer temperatures were ranked as strong im- portance (5) when compared with slope. The inverse of this relationship must then be true. So, a ranking of 1/5¼0.20 is filled in for the slope/maximum average temperature pair. Overall, maximum aver- age temperatures were ranked highly due to both their influence on soil moisture (an important factor for optimal growing conditions) and heat stress(important for tree health) (Godman et al. 1990; Bertrand et al. 1994; Burton et al. 1998; Horsley et al. 2002). Annual precipitation and drainage were also ranked higher than most other factors as they also contribute to soil moisture. Minimum average spring temperatures were ranked highly due to their influence on seedling germination (Godman et al. 1990). Soil acidity was generally ranked lower than 1 representing“equal importance,”as sugar maples can grow in a wide range of soil types from strongly acidic to slightly alkaline (Godman et al. 1990). Although most of these factors contribute to the Ecozone settings, only factors where sugar maples grow under a wide range of conditions— i.e., slope and soil acidity—were ranked as less important. The final matrix of the pairwise rankings is provided in Table 3. These pairwise rankings were then normalized by dividing each column entry by the column’s sum. The normalized values were used to calculate the final weights assigned to land cover and climate factors: maximum summer and minimum spring temperatures 21.9 percent; soil drainage 15.3 percent; annual precipitation 12.2 percent; rooting depth 10.3 percent; ecozone 9.0 percent; soil acidity 6.1 percent; and slope 3.2 percent. The land cover and climatic layers were then summed to produce output maps where the locations with highest values represent places in Ontario where sugar maple growth will be the most limited or unsuitable. An historical climate data set (1970––2000) was used to test the reclassification and weighting of each of the input factors. A map containing eight Table 3 Pairwise ranking comparison matrix for the sugar maple habitat factors used in this study Max. Avg. Summer TempMin. Avg. Spring TempAnnual Precipitation DrainageRooting Depth EcozoneSoil Acidity Slope Max. Avg. Summer Temp1.00 1.00 2.00 2.00 3.00 3.00 3.00 5.00 Min. Avg. Spring Temp1.00 1.00 2.00 2.00 3.00 3.00 3.00 5.00 Annual Precipitation0.50 0.50 1.00 0.50 2.00 3.00 2.00 5.00 Drainage 0.50 0.50 2.00 1.00 2.00 3.00 2.00 5.00 Rooting Depth 0.33 0.33 1.00 0.50 1.00 3.00 2.00 3.00 Ecozone 0.50 0.33 1.00 0.33 1.00 1.00 2.00 3.00 Soil Acidity 0.33 0.33 0.50 0.50 0.50 0.50 1.00 2.00 Slope 0.20 0.20 0.20 0.20 0.33 0.33 0.50 1.00 SUM 4.37 4.20 9.70 7.03 11.83 16.83 15.50 29.00 The Canadian Geographer / Le G eographe canadien2015, 59(3): 369–381 Climate change and maple habitat 375 locations within south and central Ontario of forest stands with more than 90 percent sugar maples, acquired from the Ontario Ministry of the Environ- ment, was used to ensure that our weighting scheme captured the location of current known maple stands. The values for the cells in the output maps were divided into two classes based on the mean zonal statistics of the output layer at the eight locations of pure sugar maple stands. All output values that fell within the range of values found at the pure maple stand locations were classified as suitable habitat and the rest were classified unsuitable. Sensitivity analysis was used to identify which factors proved most sensitive to change when all the weighted factors were combined. Sensitivity analy- sis involves altering the input value of a factor, running the revised model, and assessing the resultant change in output. A significant change in output values signifies that the model is sensitive to the tested factor. To test the sensitivity of our model the weights of the input factors were held constant but the landscape and climate input values were changed by increasing and decreasing them by 5percent, 10 percent, and 20 percent. For this analysis we used the historic climate data set and compared the output from this model run with those produced using increases or decreases in a factor’s input value. The graphed outcomes of the sensitivity analysis are shown in Figure 2. The bars in this figure show the difference as a percentage in the amount of suitable habitat associated with the factor’s input change. For example, when maximum summer temperature input was decreased by 5 percent there was no difference in the amount of suitable habitat, therefore the resultant change shown in Figure 2 is 0 percent. Slope and precipita- tion were found to be the least sensitive factors and soil drainage and maximum summer temperatures were the most sensitive. Overall, there is less than a 10 percent change in suitable habitat with but one exception when the change is up to 15 percent, indicating that the amount of modelled suitable habitat is not very sensitive to changes in one specific input variable. Therefore, when the model’s output projects a significant change in suitable sugar maple habitat, this result would not be driven primarily by the bias of a single sensitive input Figure 2 Results of the sensitivity analysis testing the effect of changing the input of the weighted suitability factors on the amount of suitable habitat. The Canadian Geographer / Le G eographe canadien2015, 59(3): 369–381 376 Laura J. Brown, Daniel Lamhonwah, and Brenda L. Murphy factor but instead must be the result of combined input values. Results Initially, the GIS habitat suitability model was tested by using an historic climate data set and the environmental factors. The output suitability map generated (Figures 3a and 4a) shows that the suitable habitat regions correspond well with loca- tion of the eight known stands with more than 90 percent in sugar maples. This map demonstrates that 84 percent of the cells within the current sugar maple range are suitable habitat. The unsuitable habitat areas (16 percent of the cells) in this map can be attributed to a combination of landscape or climate factors such as poorly drained soils, acidic soils, and/or high summer temperatures. The modelwas then run to project the future habitat within this range for the near future (2041––2070 climate data) and the distant future (2071––2100 climate data), under three Fourth Assessment Report (AR4) scenarios. Overall, for all three scenarios the decrease in the amount of future suitable habitat intensifies in the later time periods. There is also a shift in eastern and southern Ontario from a region dominated by suitable habitat towards a region of unsuitable habitat; however there is little change in the northwestern section of the current range. Even under the low increased levels of CO 2emissions forecast by the B1 scenario, there is a loss of suitable habitat from 84 percent of the modelled cells to 78 percent in the near future and 73 percent in the distant future. However, we have surpassed the CO 2 emissions projected under this scenario and will focus the rest of our analysis on the remaining two Figure 3 Results of the habitat suitability analysis showing the amount of suitable habitat with the current sugar maple range: a) generated with 1970––2000 climate data set, b) near future projection generated with A1B 2041––2070 data set, c) distant future projection generated with A1B 2071––2100. The Canadian Geographer / Le G eographe canadien2015, 59(3): 369–381 Climate change and maple habitat 377 scenarios. Of the three climate projections mod- elled, A1B represented a moderate CO 2emission atmosphere of 16GtC by 2050 with a fall to 13 GtC by 2100 due to a balanced use of fossil fuel and non- fossil fuel energy sources. Under this scenario the area of suitable habitat falls to 65 percent of the current range in the near future and 49 percent in the distant future (Figure 3). In the near future (Figure 3b) this study projects that sugar maple habitat within the maple producer regions (Figure 1) of South Western and Eastern, the southern parts of both Waterloo Wellington and the Lanark District, along with the areas around Espanola and Sudbury in the Algonquin producing region, could be at risk. By 2100, this analysis projects that sugar maple habitat in much of southern and eastern Ontario’s maple-producing regions could be at risk, with the further expansion of unsuitable habitat into most of the Waterloo Wellington and the Simcoe regions inthe west and much of the Haliburton Kawartha, the Quinte, and the Ottawa Valley regions in the east (Figure 3c). Primarily, the likely areas of suitable habitat will be the southern part of the Algonquin region, much of Algoma, as well as a few scattered pockets along Lake Ontario’s shoreline, along the St. Lawrence River and the north-western fragment of the current sugar maple range. The A2 scenario represented a high increase in CO 2 emissions and projected a CO 2 emission atmosphere similar to A1B at 2050, but increasing to a high emission atmosphere of 33 GtC by 2100 (IPCC 2009). Hence, in the near future projection there is little difference between the A1B and A2 modelled suitable habitat (Figure 4b). Under this scenario 63 percent of the cells within the current range represent suitable habitat and the same maple-producing regions are at risk of habitat loss. However, the modelled projection for the Figure 4 Results of the habitat suitability analysis showing the amount of suitable habitat with the current sugar maple range: a) generated with 1970––2000 climate data set, b) near future projection generated with A2 2041––2070 data set, c) distant future projection generated with A2 2071––2100. The Canadian Geographer / Le G eographe canadien2015, 59(3): 369–381 378 Laura J. Brown, Daniel Lamhonwah, and Brenda L. Murphy distant future shows a drop in suitable habitat to 38 percent of the current range (Figure 4c). Again there are a few scattered pockets of suitable habitat along the shoreline of Lake Ontario, in the northwestern section and in the Algoma region, but much of central Ontario including the Algonquin region has shifted to unsuitable habitat. The remaining areas of suitable habitat are concentrated in the northern parts of the sugar maple range. Discussion In this study a model was developed based on MCDM coupled with weighted sum analysis to determine changes in maple habitat suitability due to projected changes in precipitation and tempera- ture associated with climate change in Ontario. The ranking and weighting schemes inherent in this type of analysis were based on a synthesis of a collection of materials on sugar maple habitat and growth from previous studies and publications; however, there is still some subjectivity in the reclassification values and weights. Despite this subjectivity, the model performs appropriately as it captures the current sugar maple range and the areas with known maple stands very well, using the historic climate data set. In addition, sensitivity analysis shows that the model is not biased towards one single factor and that the significant decrease in suitable habitat projected by this model must be the result of the combined input values. The modelled results are in line with the expected trend of a future northward migration of maple habitat predicted by McKenney et al. (2007a) and Perkins (2007). This study has focussed on the current range of sugar maple, however climate change may expand this range farther north into what is now the boreal forest. Current research projects undertaken by our group are exploring this possibility. The mapped results are generalized to a regional level due to the scale of the model’s cell being rather coarse, at 180km. Microclimates and local variations in soil characteristics and land cover are not included but instead climate and landscape attrib- utes are treated as homogenous within each modelled cell. Therefore, the results of this study can only project maple habitat suitability at the regional level as opposed to the local level. To capture localized impacts, finer-grained models will be required. In addition, GIS analysis can besupplemented by archival and oral histories and local knowledges to understand the current and future impacts of climate change in specific geo- graphic locations. The model projects that the top maple syrup production regions in Ontario could be at risk. Perkins (2007) expected that by 2100 climatic conditions in New England would be such that maples would be displaced. This study projects that for the second largest producing region, and parts of the largest producing region, this shift may come even sooner as Lanark County appears to be affected as early as 2070. By 2100 the habitat for sugar maples may be unsuitable for much of Waterloo-Wellington, the largest maple-producing region in Ontario, as well as most of southern and central areas of the province. As favourable climatic conditions change to ones where maple trees may be stressed and eventually displaced, maple sap harvesters face the risk of decreased sap yield and eventually loss of viable maple syrup production. Conclusions In this study a GIS based model was developed to project the impact of climate change on the current range of sugar maple habitat in Ontario to address the concerns of maple producers and researchers. We modelled three SRES (AR4) scenarios and our model projects a decline in future suitable habitat within the current range of sugar maples, a trend that intensifies in the later modelled time period. Both the major maple-producing regions of south- western and eastern Ontario are projected to become unfavourable for maple stands while cen- tral Ontario appears to maintain suitable habitat. The results of this modelling are projections not predictions; this means that future sugar maple habitat could be quite different given mitigation and adaptation strategies and other factors. Key factors could include atmospheric carbon loadings higher or lower than the models projections, and climatic impacts not captured by the current models. Maple syrup producers have demonstrated continued capacity to innovate and adapt to changing bio- physical conditions (Morin 2014). For instance, line- based collection systems are better able to capture irregular and intense sap flows and reverse osmosis technology has vastly improved the ability to handle variable flow conditions. Future adaptations could The Canadian Geographer / Le G eographe canadien2015, 59(3): 369–381 Climate change and maple habitat 379 include the introduction of sugar maple ecotypes better suited to drought conditions and manage- ment practices that enhance forest health and support vigorous species regeneration. The results of this study provide a basis upon which those involved in the maple industry can begin working on adaptation and mitigation strategies. This work has focused on the effect of climate change on sugar maple habitat; however, it is important to recognize that sap flow, and therefore syrup production, are also weather and climate dependent. Current work by our research group is extending the geographic scale beyond the current sugar maple range to include the potential poleward migration of the species and focusing on the effects of climate change on sap flow as well as potential mitigation and adaptation strategies for syrup production. Acknowledgements The Social Sciences and Humanities Research Council of Canada provided the funding for this research. We thank C. Watson for providing the locations of stands with 90 percent sugar maple coverage and D. McKenney at Natural Resources Canada for providing the climate data sets and useful discussions regarding the effect of climate change on trees. We also thank the many members of the Ontario Maple Syrup Producers Association for their continued support of our research. References Agriculture and Agri-Food Canada. 2007. Canadian maple products situation and trends 2006-2007. Site no longer active; last accessed 5 December 2014. http://www4.agr.gc. ca/AAFC-AAC/display-afficher.do? id=1193169758779〈=eng#altformat Austin, M. 2007. Species distribution models and ecological theory: A critical assessment and some possible new ap- proaches.Ecological Modelling200 (1––2): 1––19. Barkley, Y. C. 2007. Sugar maple. http://www.uidaho.edu/ /media/Files/Extension/Forestry/Forest%20Products/ Alternative%20Products/Sugar%20maple.ashx Bertrand, A., G. Robitaille, P. Nadeau, and R. Boutin. 1994. 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Duckstein. 1993. A multiple criteria decision- making approach to GIS-based land suitability evaluation. International Journal of Geographical Information Systems7 (5): 407––424. Perkins, T. D. 2007. Congressional testimony to the house of select committee on energy independence and global warm- ing. Site no longer active; last accessed June 18, 2013 http:// globalwarming.markey.house.gov/tools/assets/files/0101. pdf Saaty, T. 1980.The analytical hierarchy process: planning, priority setting, resource allocation. New York: McGraw-Hill. St. Clair, S. B., J. E. Carlson, and L. P. Lynch. 2005. Evidence for oxidative stress in sugar maple stands growing on acidic, nutrient imbalanced forest soils.Oecologia145 (2): 258–– 269. Statistics Canada. 2012. Production and value of honey and maple products, 2012. http://www.statcan.gc.ca/daily-quoti- dien/121214/dq121214c-eng.htm Stewart, R. B. 2003. Climate change: Implications for forest ecosystems and forest management in Eastern Ontario. Presentation at East Central Winter Woodlot Conference, Lindsay, Ontario, 20 Febru- ary 2003. http://www.ontariowoodlot.com/pdf_older/CLIMATE% 20CHANGE%20-%20IMPLICATIONS%20FOR%20FOREST%20 ECOSYSTEMS.pdf Taggart, R. E., and A. T. Cross. 2009. Global greenhouse to icehouse and back again: The origin and future of the boreal forest biome.Global and Planetary Change65 (3––4): 151–– 121. Thomas, P. A., and J. R. Packham. 2007.Ecology of woodlands and forests: Descriptions, dynamics and diversity. New York: Cam- bridge University Press. USDA (United States Department of Agriculture) Natural Re- sources Conservation Service. 2006. Plant guide: Sugar maple. http://plants.usda.gov/plantguide/pdf/pg_acsa3.pdf The Canadian Geographer / Le G eographe canadien2015, 59(3): 369–381 Climate change and maple habitat 381
Hi need help doing this assignment! i have uploaded 5 files along with the questions, which are to be used for first 2 questions. The articles are to be used for the first question and the chapter is
A case study of Akbarpur Sugar mill Rakesh B. Gautam*, Sunanda, Som Datta, Sumit Kumar Vishwakarma, Shubham Ojha, Sukhvendra Singh, Suneel Kumar, Uttam Singh a nd Shailesh Mishra Department of Processing and Food Engineering, NDUAT, Kumarganj, Faizabad *Email: [email protected] Abstract India has emerged as one of the largest production of sugarcane and sugar in the world with highest number of sugar factories. In other countries sugar is a by-product, but in India sugar is the main product produced by sugar mills. India is producing large quantity of sugar because of our own needs, but now a day’s only sugar production is not produc tion is not profitable for sugar mills. Sugar industry needs to increase their capacity in by pro ducts like alcohol, ethanol co-generation etc. In India, Uttar Pradesh and Maharashtra are one of the major sugars producing State in the country. Major sugar producing states are Uttar Pradesh (36% ), Maharashtra (24%), Karnataka (11%), Tamilnadu (11%), Gujrat (4%), Andhra Pradesh (5%), Bihar (3%), Uttrakhand (2%), Haryana (2%), and Punjab (2%). Total sugar production is 100000 q uintal and recovery rate is 11%. Total cost of operation is 9677 lakh rupees. Total profit is 5677 lakh rupees. Current price of sugarcane is 325 rupees per quintal. Keywords: Sugar, Sugarcane juice, Expeller, Crystals of sugar and evaporators. Paper cited: Gautam, R.B., Sunanda: Datta, S., Vishwakarma, S.K. , Ojha, S., Singh, S., Kumar, S., Singh, U. and Mishra, S. (2017). A case study of Akbarpur Sugar mill. South Asian Journal of Food Technology and Environment, 3(1): . Introduction India has emerged as one of the largest production of sugarcane and sugar in the world with highest number of sugar factories. In India, Uttar Pradesh and Maharashtra are one of the major sugars producing State in the country and in Maharashtra; Kolhapur District in particular, became a potential sugarcane belt area. Sugarcane occupies an important place in the economy of the district it is the most important cash crop of the District. Sugarcane in as agri-energy crop and India is the homeland of these crops. India is one of the largest producer and consumer of sugar in the world. Sugar industry is the second major agro based industry of our country next only to cotton industry, which can generate prosperity in rural area through increasing employment and income. These generated income and employment have multiplier effect and helps in over all development of the country. Indian sugar industry is an important and big share in agriculture processing industry. It has very strong impact on our rural development and provides successful rural economy. In our country nearly 50 million farmers provide employment. The Indian sugar mills currently has 527 operational sugar mills out of that 234 are in cooperative sector. Total sugar production in India 243 lakh tones out of 108.55 lakh tones in co-operative sector in the year 2010-11 also total sugar production in the year2011-12 was 262 lakh tones and also sugar production in the year 2012-13 are 250lakh tones, estimated production in the year 2013-14 were 237 lakh tones (Table 1). The sugarcane is grown in 21 various states of India. Mainly sugarcane mills are operating in large sugarcane growing areas like Maharashtra, Gujarat, Tamilnadu, Karnataka and Utter Pradesh (Fig. 1). In Maharashtra alone is producing 30% of national sugar on put and maximum number of sugar mills are also in Maharashtra compared to other states in India. In the year of 2011-12 sugar factory South Asian J. Food Technol. Environ., 3(1):492-501 (2017) ISSN 2394-5168(Print), 2454- 6445(online) www.sweft.in South Asian J. Food Technol. Environ., 3(1): 492-50 1 (2017) [492] crushing season, 118-co-operative and 51- private sugar factories have crushed the sugarcane and the total sugar production of 90th Lakh tones and in the year 2012-13 sugar produced 70.44lakh tones in Maharashtra State. The experience of some of the progressive co-operative sugar factories, particularly those located in the State of Maharashtra in setting up and running the industries based on the by-products of the sugar industries have proved the multifarious advantages of such industries. The main by- products of the sugar industry are bagasse and molasses. By setting up industries to the first in state, it has been proved that waste materials can also be converted into wealth by adopting suitable technologies. In the second way, such industries create more employment opportunities in the rural parts of the country. Where the sugar factories are usually located such industries improve the economic status of thousand of sugarcane growers and the overall financial viability of the sugar factories there by making the working of the sugar factories much more successful. With the gradual decline in prices of sugar in India and increase in cost of production of sugar, the working of many sugar factories is not comfortable. Therefore this is the right time to launch some by-product industry, to make the sugar industry financially viable. The dynamic leadership given by some progressive co- operative sugar factories in this direction has encouraged many more co-operative sugar factories to set up such by-product industries. In other countries sugar is a by- product, but in India sugar is the main product produced by sugar mills. India is producing large quantity of sugar because of our own needs, but now a day’s only sugar production is not production is not profitable for sugar mills. Sugar industry needs to increase their capacity in by products like alcohol, ethanol co-generation etc. This could be possible only through fuller and better utilization of the by- products and alternative produce, so that the higher value products are manufactured from them and sugar industry derives maximum benefit from the sugar crop. The ultimate prosperity of the Indian sugar industry depends upon diversification into numerous avenues based on the by-products of the sugar industry. Table 1: Sugar production in India Year Sugar production (mt) 2009-10 2923 2010-11 3424 2011 -12 3538 2012-13 3544 2013-14 3456 2014-15 3668 2015-16 3369 Materials and Methods Sugar mill specification (Fig. 2) Feed Section (Delivery, Unloading, weighing & Handling of Cane): Raw material (sugar cane) is imported and weighed on weight balance. Then it is introduced onto the feeding table by elevating the trawler through jack. Feed table: There are four Feed tables in the industry. The purpose of feed table is to transfer the sugar cane on the cane carrier. Conveyer belts and impellers are mounted on Rakesh B. Gautam et al., South Asian J. Food Technol. Environ., 3(1): 492-50 1 (2017) [493] the feed table. They help in transportation of cane from feed point to cane carrier. Cane Carrier: The Cane Carrier is a moving apron. Cane carrier is a type of conveyer belt which carries cane from feed table and transport it towards leveller, cutters, leveller, magnetic separator, shredder, mills, boilers, and finally to bagasse storage point. It consists majorly of two portion stated as following: • The horizontal portion: It is used for horizontal transportation of cane. • The inclined portion: It conveys cane horizontally as well as vertically simultaneously. Cane carrier is driven through electric motor. As this is essentially a constant-speed machine, and the carrier speed must be frequently varied, the drive is affected by a variable speed coupler. Leveller: Leveller is a set of knives which evens out the layer of cane, so that other size reduction operations can easily be performed. The leveller blades, which are coated with specific material which are inert to cane juice, mounted on the shaft which rotates at a specific rpm. The shaft is driven through electric motor. After passing through the leveller the cane would be at such a level that can easily be handled in cutters without jamming it. There are two levellers in the sugar industry one is used before cutters and other one is used after cutters. Cutters: Cutters are used to cut the cane into small pieces. Three cutters are installed over the feed carrier. Two of the cutters are motor driven and third one is driven through steam turbine. The knives are mounted on the shaft spindle. Different number of knives is used to make the cutting more effective. Magnetic Separator: Magnetic separator is used to remove the iron particles or pieces which become the part of cutter cane or other iron particles which are already present. The commonest objects are: pieces of knife blades, sling hooks, broken pieces of slings, monkey wrenches, horse shoes, bolts and nuts. If iron pieces are not removed then they jam the mills and pressure feeder, and so it is required to remove them before cane feeding to mills. Mills are very expensive due to the mill rollers. Shredder: The objective of shredder is to complete the preparation and disintegration of the cane, so as to facilitate the extraction of juice by the mills. Shredder is a type of hammer mill which is used to disintegrate the cane. It is driven by steam turbine imported from Germany. It receives the cane from the leveller, which is placed after the third cutter and sends it to the milling house. The cane is hammered by the hammers mounted on the rod, which is inserted into the disk holes. These hammers are mounted alternatively. These hammers disintegrate the cane against a curved metal plate. After shredding this cane is passed to the milling section by shredded cane elevator. Turbines: It is a device which is used to convert the pressure energy of the superheated steam into mechanical work. It is basically a type of prime mover. In the feed section two turbines are used. One is used to drive cutter-3 and other one is used to drive shredder. The turbine specifications are stated below. • Turbine for Cutter-3 Turbine for Shredder • Power 650 kW Power 1800 kW • Inlet Steam Temperature 330°C • Inlet Steam Pressure 22 kgf/cm 2 • Outlet Steam Pressure 1.15 kgf/cm 2 Mills: Mill is a machine which is used to extract the juice from shredded cane. It consists of two major parts: (a) Pressure Feeder: Pressure feeder consists of three rolls stacked together to form a shape of triangle and its lower roller is driven through steam turbine. Objective of pressure feeder is to feed the shredded cane at high pressure to the mill inlet in order to facilitate the cane milling operation for proper juice extraction and in order to avoid shredded cane back coming effect. A case study of Akbarpur Sugar mill South Asian J. Food Technol. Environ., 3(1): 492-50 1 (2017) [494] (b) Mill: Mill itself also consists of three rolls for juice extraction. The rolls of a mill are stacked together to form a triangle shape and its upper roller is driven through steam turbine. Objective of a mill is to extract the juice from shredded cane. In reality pressure feeder and mill both are integrated to each other in order to form a six roll stack for easier cane handling. There are five mills are used in series, each mill have a pressure feeder associated with it. About 80% juice is extracted in mill-1. Feed to each pressure feeder is introduced by inclined cane carrier. So every mill’s pressure feeder has an inclined cane carrier associated with it and it proceeds to mill. Trace Plate: Trash plate is a plate with teethes on both sides and it is used among mill rollers. It fulfils two basic functions: • It provides a tight fitting between rollers which improves the crushing and so juice recovery is improved. • Its teeth clarify the space between roller disks to some extant which prevent mill choking. Clarifier (Sedimentation): The main purpose of the clarifier is to clarify the juice by removing impurities in the form of mud. Hot juice enters into the clarifier by four paths that combines in the feed launder. Then after the filling of the feed launder it falls inside the channel to deplection plate. The purpose of the deplection plate is to minimize the splashing effect which causes mud disturbance. Splashing causes to break the mud cake at the bottom of the clarifier due to this mud disturbance it may come in the juice again and so clarification will not give clarified juice, so we have to prevent splashing by deplection plate. Impurities are converted into mud by the addition of a suitable polyelectrolyte. This polyelectrolyte having high molecular weight attaches impurities with it and form strong bond with them which causes the formation of mud. This mud having high density starts to fall under the action of gravity to the bottom of the clarifier which is known as sedimentation, and this is the basic concept which governs this type of clarification. The polyelectrolyte in the form of solution is supplied to four juice supply distribution drums, where it is mixed in a certain proportion with hot juice feed which goes into feed launder. This polyelectrolyte solution in water is made prior to clarification in a vessel by simple mixing effect. The level of juice raises in the clarification tank and reaches to the inside and outside launders. Juice enters into these two launders and then with the help of their separate outlet pipes combine into a compartment of the outlet supply drums. It attains a level in the compartment and then enters into the second compartment of the outlet supply drum from which it is supplied to the DSM screens. There are three DSM screens used in the industry with 0.35mm screen size. The juice is then sent to juice pre heater where its temperature is increased to 110°C ~ 115°C. The mud is removed from the bottom of the clarifier tank with the help of the scraper and is sent to the Mud mixer. There are two clarifiers used in the sugar mill. In first clarifier the deplection plate has conical upper surface. The height and diameter of first clarifier are 6m and 9.15m respectively. Second clarifier is of SRI type. In the second clarifier the upper surface of deplection plate is flat. And in the second clarifier mud scraper also translate itself for better mud removal. The length and diameter of second clarifier are 3m and 8m respectively. Only one clarifier operates in the season during production. The temperature inside the clarification tank is kept to 105°C. Evaporators: Evaporator is equipment that is used to concentrate the solution by evaporating the solvent (water).There are two types of evaporators are used in the industry as follows: • Falling film evaporator (FFE) • Multiple Effect Evaporator (MEE) Multiple Effect Evaporators : It is also a type of shell and tube heat exchanger. In this evaporator vapours or steam which is used for Rakesh B. Gautam et al., South Asian J. Food Technol. Environ., 3(1): 492-50 1 (2017) [495] first effect as a heating media will condense and the vapours produced by evaporation of solution will be used in next effect as heating media, while the same solution is evaporated in multiple effects. This Process repeats in the remaining effects. Such types of ten effects are installed in the industry while five of them works for the produced capacity. There is a gap between the half bundles of tubes which is known as central well. The width of the central well is ¼ times of the diameter of the evaporator. Juice enters from the bottom of calandria and after heat exchange it comes back from central well. Water present in the juice is evaporated and collected from the top and is further utilized as heating media to the next evaporator. Concentrated juice is collected from the bottom and it is sent to the next body. Juice discharges as concentrated juice termed as syrup is collected from last body (evaporator). Juice enters the FFE from juice pre heater at 110°C ~ 115°C, and after passing through FFE it enters into MEE which increase the Brix and converts juice to syrup. There are two FFE’s are installed in the industry, one of them is in working condition. There are ten evaporators other than FFE’s. These evaporators are used in multi effect. No of effects required depends upon the required heat transfer area. In usual production, five effects are used in order to get the required evaporation. At the entrance of 1 st effect brix is 15, while at the outlet of 5 theffect brix is 65. Crystallizers: There are two main types of crystallizers: • Horizontal crystallizer • Vertical crystallizer Horizontal Crystallizer: The crystallizer, horizontal in shape with open top side is called horizontal crystallizer. The crystallization process consists of two major events, nucleation and crystal growth. Nucleation is the step where the solute molecules dispersed in the solvent start to gather into clusters that become stable under the current operating conditions. The crystal growth is the subsequent growth of the nuclei that succeed in achieving the critical cluster size. Nucleation and growth continue to occur simultaneously while the super saturation exists. Super saturation is the driving force of the crystallization hence the rate of nucleation and growth is driven by the existing super saturation in the solution. Vertical Crystallizer: Vertical crystallizer is used in cane sugar industry for efficient sugar crystallization from low-purity crystal suspensions. Sugar Grader: Sugar grader is used to separate the different sizes sugar crystals for market and industrial operation demands. Particle Size of Sugar grain 4, 8, 12, 16, 20 mesh is produced as per market requirement. Dryer: Drier is used to dry the final product sugar crystals with the help of steam. Hopper: Hopper is used to supply the final sugar to packaging section. Packaging: After hopper sugar is packed into 50 kg bags. Manual packaging is used and it is closed by sewing machine. In 8 hr shift 3500 bags are produced. Table 1: Basic information about sugar producti on in akbarpur sugar mill Particulars Data Sugarcane price payable (Rs/quintal) 325 Recovery Rate 11 % Sugarcane price per kg of sugar produced (Rs/kg) 2 6.40 Conversion cost from Sugarcane to raw sugar (Rs/kg) 3.50 Total cost of raw sugar production (Rs/kg) 29.90 Conversion cost from raw to white sugar (In Rs/kg) 2.5 Total cost of production for white sugar (Rs/kg) 3 2.40 Domestic ex -mill sugar price (Rs/kg) 26.10 -26.60 A case study of Akbarpur Sugar mill South Asian J. Food Technol. Env iron., 3(1): 492 -501 (2017) [496] Fig.2: Flow chart of sugar mill process Results and Discussions Processing of sugar The sugar process divided in the following steps. The basic information and production data of sugar production of Akbarpur sugar mill given in Table 1 & 2. Entry or transportation of the sugar: Sugar is obtained from the cane at mills located near centers of production. The cane first goes through a washer, then is cut into small pieces by revolving knives. After this step the small pieces are shredded. The shredder is a large powerful hammer mill that shreds the cane into a fibrous material. The cells in the cane stalk containing the sugar juice are ruptured but no juice is extracted at this stage. After this preparation, the juice from the sugar cane can be extracted. Milling train: The shredded cane is fed through a series of crushing mills to extract the sugar rich juice, which is then pumped away for further processing. The remaining fibre is called bagasse. The crushers consist of two large grooved rollers mounted horizontally, and then one above of the others. On the upper roller heavy hydraulic pressure is maintained. Clarification: The limed juice enters a gravitational settling tank: a clarifier. The juice travels through the clarifier at a very low superficial velocity so that the solids settle out and clear juice exits. The mud from the clarifier still contains valuable sugar so it is filtered on rotary vacuum filters where the Rakesh B. Gautam et al., South Asian J. Food Technol. Environ., 3(1): 492-50 1 (2017) [497] residual juice is extracted and the mud can be washed before discharge, producing sweet water. The juice and the sweet water are returned to process. Evaporation: The clarified juice is concentrated to syrup by boiling off excess water in a series of connected vessels. Under automatically controlled conditions in the evaporator station, each subsequent vessel operates under decreasing pressure with the last one being under almost a total vacuum. After this step the syrup is ready to go to the high-vacuum boiling pans. Crystallization: Concentration of the syrup from the evaporator is continued in vacuum pans. Very small seed crystals are introduced to the concentrating syrup and these begin to grow in size. When the crystals reach the required size, the mixture of crystals and syrup is discharged from the pan. Separation: The sugar crystals are separated from the syrup in centrifugal machines that have an action similar to a spin- dryer. After leaving the centrifugals, the moist raw sugar is tumble dried in a stream of air and transferred to bulk storage bins. The separated syrup is reboiled and further sugar is crystallized. After three boiling no further sugar can be economically removed. The residual sugar is called molasses. Sugar refining: The purpose of the refinery is to remove impurities from sugar crystals. The refinery accepts raw sugar as its feed material. The sugar is dissolved (melted) and the colour is removed by various clarification processes. The final refining steps include melting the brown or raw sugar, decolouring by passing through carbon filters, recrystallizing in vacuum boiling pans, and drying by centrifuging. Affination: The Affination process comprises a U-mixer, hot magma mingler, centrifugal and sugar melter. In the U-mixer raw sugar is stirred with a measured amount of water before transfer to the mingler for heating and slurrying. Carbonation: Dissolved sugar from the melter is reacted under carefully controlled conditions of ph and temperature, with milk of lime (CaO) and Carbon Dioxide (CO2) to form a calcium carbonate (CaCO3) precipitate. Filtration: Carbonated liquor (solution) is pumped through a series of leaf filters which retain the calcium precipitate in the filter and discharge a clear but coloured sugar solution. Ion exchange: The clear but tan coloured sugar solution is pumped through a series of columns containing an ion exchange resin which absorbs the remaining colour to produce a clear and colour less solution known as fine liquor. Evaporation: Water is evaporated from the fine liquor in specially designed equipment to concentrate the sugar solution into a stream known as thick liquor. Vacuum pan & Crystallizer: Thick liquor is transferred to boiling vessels known as pans where under controlled vacuum the liquor is boiled at low temperature to further concentrate the solution. As water evaporates and the liquor concentrates, sugar crystals begin to form, their growth being controlled by careful adjustment of the boiling conditions. Centrifugal: Massecuite from the crystallizers is processed through centrifugals where the spinning action separates the sugar crystals from the remaining liquid solution (molasses). Sugar handling & Packaging: The wet crystals are discharged through a rotating drum into which hot air is continuously blown to remove moisture and dry the crystals. At the exit of the dryer the crystals are cooled and passed through a sieve to grade the crystal size. Any dust formed during this process is removed by vacuum and the sugar then conveyed to the packing area for final packing into 50kgs bags. Cost analysis of Sugar Production in Akbarpur Sugar mill Cost analysis of sugar production of Akbarpur Sugar mill is discussed in Table 4. A case study of Akbarpur Sugar mill South Asian J. Food Technol. Environ., 3(1): 492-50 1 (2017) [498] Table 2: Performance data of akbarpur chini mill Particulars 2013-2014 2014-2015 2015-2016 Crushing Capacity (M.T.) 7500 7500 7500 Cane Crushed (Lakh M.T.) 7.06 6.34 7.14 Sugar Produced (Lakh / Qtl ) 6.99 6.10 7.85 Sugar Recovery ( % ) 9.76 9.60 11.0 Molasses Produced (M.T.) 32017 29853 32165 Table 4: Cost analysis of Akbarpur Sugar mill S. No. Description Rs. (Lakhs) A. Civil Work 1. Land Development, grading & Levelling 100.00 2. TG Building 225.00 3. Plant Buildings for the Fermentation Control Rooms Electrical rooms, WTP Alcohol Issue area 200.00 4. Foundation for the complete distillery & power plan t & Tanks 550.00 5. Raw Water Tank 70.00 6. Conveyor Foundations 90.00 7. Road and Drain Work – Land & Site 80.00 8. Pipe Rack Support & Cable Rack 68.40 9. Concrete Chimney 80.00 10. Total for Civil works 1463.40 B. Mechanical Work 1. Complete distillery plant (fermentation distillation, evaporation) including Interconnecting piping, structural suppor ts etc. 3000.00 2. 20 TPH spent wash incineration steam generator incl uding fabric filter, fans pumps, valves and specialities, piping PRDS and other Auxiliaries. 1450.00 3. 1 x 2.2 MW back pressure turbo generator unit, incl uding all auxiliaries, piping, governor turbovisory, controls and Instrumentation and electrical as per scope. 350.00 4. Bagasse handing system with all its accessories. 150.00 5. Ash handling system for the boiler consisting of su bmerged scrapper conveyers, for wet ash and dense phase handing syst em for fly ash. 120.00 6. Induced draft cooling tower (RCC work included in c ivil scope). 60.00 7. Centrifugal Pumps with base frames and electric mot or drives for the cogeneration power plant. 60.00 8. Steam, Water piping and valves & supports from the power plant. Tanks for Molasses, DM & Process water. 325.00 9. Reverse Osmosis based water Treatment Plant. 220.00 10. Day receiver and Bulk Storage Tanks for the product s. 400.00 11. Power House EOT Crane 30.00 12. Air Conditioning system & Ventilation system for th e TG building, MCC room & control rooms in process plant & cogen. Plant. 80.00 13. Air Compressors for both Process and cogeneration p lant. 65.00 14. Fire Protection Systems for the process and cogeneration plant. 180.00 15. Laboratory 28.00 16. Weigh Bridge 25.00 17. Condensate & Spent lees treatment and Polishing 275.00 Total for mechanical works 6818.00 Rakesh B. Gautam et al., South Asian J. Food Technol. Environ., 3(1): 492-501 (2017) [499] C. Instrumentation works 1. Distributed Control system & Miss Instrumentation other than those covered by other packages and UPS. 225.00 2. Balance of Plant Instrumentation. 125.00 Total for instrumentation works 350.00 D. Electrical works 1. Generator and all generator accessories including r elay metering and control panels, AVR, Synchronising panel, NGR & LAV T and Switchboards. Included in turbine 2. Plant Electrical Package including Transformers, ca bles, LT Panels, VFD Panels, contract package etc. 500.00 3. DG Set Package. 110.00 4. Total electrical works 610.00 E. Miscellaneous fixed assets 1. Furnitures for Office, WTP building office including computers, EPABX etc. 15.00 2. Furnitures for process control rooms and office. 10 .00 3. Plant Vehicles 15.00 4. Office Air Conditioning & Ventilation Equipment, Lighting, etc. 5.00 Total for miscellaneous fixed assets 45.00 TOTAL WORKS COST (A+B+C+D+E) 9286.00 F. Calculation of interest during construction Construction Period (Months) 16 Rate Of Interest for Term Loan 12.50 % Rate of Interest for SDF Loan 6.50% Rate of Interest for Bridge Loan ** 13.00 % Debt Equity Ratio (SDF Loan is also considered as Equity) 1 Total interest during construction 390.91 Total cost of operation = 9286 + 390.91 = 9676.91 lakh or ~ 9677.00 lakh Total sugar production = 100000 Quintal = 10000000 kg Price of sugar per kg = 40 Rs Total profit = Total cost of machine – Total produc tion × Price of sugar = 967700000 –10000000×40 = Rs. 567700000/- or = 5677 lakh Conclusions • The group member expressed satisfaction of the opportunity to visit the chini mill. • Filled reality on operation and functional mill of huge capacity was first kind for all the group members. • Fairly a good idea received in the collection, milling and marketing of sugar. • Contact points for business were understood. • Gross expenditure required for running a mill was visualized. • Roll of middle man in sugar trading was not to be important to expand the sugar business was understood. • Besides, field with production of sugar at the time of visit was encouraging. • The purpose of this visit is well achieved. The case study of Akbarpur sugari mill at Mijhaura, Ambedkarnagar was done on the A case study of Akbarpur Sugar mill South Asian J. Food Technol. Env iron., 3(1): 492 -501 (2017) [500] basis of data collection. On the basis of study following conclusion has been drawn. • The cost of operation is the Rs. 9677.00 lakh. • The total sugar production at Akbarpur Chini mill plant during 2016 is 100000 Quintal. • Total profit 5677.00 lakh. • Recovery from 1 quintal is 11%. • The technologies simple that person can be trained in only two weeks to operate the chini mill. Rakesh B. Gautam et al., South Asian J. Food Technol. Environ., 3(1): 492-50 1 (2017) [501] Received : April 2017 Revised : June, 2017 Published : June, 2017

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