Climate Vulnerability Assessment and Management Report

Home , Changzhi, Hejin, Heshun County, Jiexiu, Jincheng, Jinzhong

Shanxi Inclusive Agricultural Value Chain Development Project (RRP PRC 48358)

Project number: 48358-001 August 2017

People’s Republic of China: Shanxi Inclusive Agricultural Value Chain Development Project Table of Contents Table of Contents ...... 2 List of Figures ...... 3 List of Tables ...... 4 Abbreviations ...... 5 A. EXECUTIVE SUMMARY ...... 1 B. INTRODUCTION ...... 4 1. Project Background ...... 4 2. Current Climate of Shanxi Province ...... 5 3. Report Objectives and Scope ...... 7 1. Climate Scenarios and Assumptions ...... 8 2. CMIP5 Climate Projection Data ...... 9 3. Projected Changes for Temperature and Precipitation in 2050 ...... 9 4. Extreme Climate Events ...... 14 D. CLIMATE RISKS ASSESSMENT ...... 16 1. Climate Change Impact on Agriculture of Shanxi Province ...... 16 2. Climate Change Impact on Provincial and Regional Water Resources ...... 17 3. Climate Risks to Proposed Subprojects ...... 19 3.1 Climate Risks to Livestock and Poultry Subprojects ...... 19 3.2 Climate Risks to Orchard Subprojects...... 20 3.3 Climate Risks to Mushroom and Vegetable Production Subprojects ...... 21 3.4 Climate Risks to Food Processing Subprojects ...... 21 3.5 Climate Risks to Cold Storages ...... 22 3.6 Climate Risk and Vulnerability Summary ...... 22 E. RECOMMENDED ADAPTATION MITIGATION PRACTICES UNDER THE PROJECT .....23 F. GHG EMISSION ESTIMATES FOR ALL SUBPROJECTS ...... 25 G. ACCOUNTING CLIMATE FINANCE ...... 27 H. REFERENCES ...... 29

List of Figures

Figure 1 Annual mean temperature and precipitation of Shanxi Province ...... 5 Figure 2 Monthly mean precipitation in Datong, Jiexiu, and Yuncheng ...... 6 Figure 3 Annual mean temperature from 1955 to 2010 in Datong, Jiexiu, and Taiyuan...... 6 Figure 4 Annual precipitation from 1955 to 2010 in Datong, Jiexiu, and Yuncheng ...... 7

Figure 5 All forcing agents' atmospheric CO2-equivalent concentrations ...... 8 Figure 6 Projected annual mean temperature for Shanxi Province in 2050 under RCP4.5 and RCP8.5 climate change scenarios ...... 11 Figure 7 Projected annual precipitation for Shanxi Province in 2050 under RCP4.5 and RCP8.5 ...... 12 Figure 8 Projected changes for annual mean temperature and precipitation under RCP4.5 climate change scenario in 2050 for cities of Shanxi Province ...... 13 Figure 9 Projected changes for annual mean temperature and precipitation under RCP8.5 climate change scenario in 2050 for cities of Shanxi Province ...... 13 Figure 10 Current and future (20,500 monthly average precipitation simulated under RCP4.5 and RCP8.5 climate change scenarios for Datong, Linfen, Yuncheng, and Jincheng in Shanxi Province) ...... 14 Figure 11 Possible connections between climate change and heatwaves (adopted from United State Environmental Protection Agency) ...... 15 Figure 12 GEV distribution of the annual maximum daily precipitation of Xining:...... 15 Figure 13 Water consumptions by different sectors of Shanxi Province in 2014 ...... 18

List of Tables

Table 1 CMIP5 global climate models used for analysing future climate change in this study ...... 9 Table 2 Projected changes in annual mean temperature and precipitation by different GCMs in 2050 for Shanxi Province ...... 10 Table 3 The optima, lower and upper temperature threshold of for different types of crop and/or plants ...... 17 Table 4 Livestock and poultry production subprojects ...... 19 Table 5 Orchard subprojects proposed in this project ...... 20 Table 6 Mushroom and vegetable subprojects proposed in this project ...... 21 Table 7 Food processing subprojects proposed in this project ...... 21 Table 8 Summary of structural and non-structural adaptation measures, and project mitigation practices...... 25 Table 9 Estimates of GHG Emission by the livestock subprojects ...... 26 Table 10 Estimates of GHG Emission by the trees and plants subprojects ...... 27 Table 11 Estimates of GHG Emission and Carbon Sequestration by the Project...... 27 Table 12 Climate finance accounting for all subprojects ...... 27

Abbreviations

ADB Asian Development Bank

CVAMR climate vulnerability assessment and management report

GCM general circulation model

GEV general extreme value function

GHG greenhouse gas

IPCC Intergovernmental Panel on Climate Change

PAC project agribusiness company and cooperative

PRC People’s Republic of China

RCP Representative Concentration Pathways (of future GHG)

SPADO Shanxi Poverty Alleviation and Development Office

SPG Shanxi Provincial Government

A. EXECUTIVE SUMMARY 1. Climate change is posing series of challenges to agricultural industries with projected higher temperature and changed precipitation regimes. The agriculture of Shanxi Province is more vulnerable to climate change because of the harsh environment and poverty in many rural areas of the province. 2. The climate of Shanxi Province is characterised as arid continental monsoon climate. The annual mean temperature is ranging from 4.2°C to 14.2°C, increasing from north to south and decreasing from valleys to high mountains. Winters are long, dry, and cold, while summer is warm and humid. Over 60% of precipitation is falling from July to September. Spring is extremely dry and prone to dust storms. Shanxi is one of the sunniest parts of the People’s Republic of China (PRC). Early summer heat waves are common. Double crops are growing in valleys and basins of middle and south of the province whilst only one crop grows in the northern Shanxi Province. In other words, double crops are only growing where is suitable for winter wheat. There are also various fruits growing in various parts of the province such as dates, apple, pear, and so on. 3. This project aims to help Shanxi Province to eradicate extreme poverty and improve livelihood in the poverty-stricken areas of the province. With request from the Shanxi Provincial Government (SPG), this project will promote agriculture-based industry for local specialty agricultural products, as part of its poverty alleviation and rural development program. 4. The project will have two outputs: (i) agricultural value chains strengthened; and (ii) inclusive business mechanism piloted. In summary, the project will support 19 selected subprojects that include livestock and poultry production, orchard and fruit production, mushroom and vegetable production, food processing, and agricultural product markets, together with capacity building for the government in developing agricultural value chains and project management. 5. Climate change risks are assessed for all subprojects based on CMIP5 climate modelling outcomes for 2050 (2041–2060) under the RCP4.5 and RCP8.5 climate change scenarios. It is projected that annual mean temperature will increase for 2.3ºC and 3.0ºC for the four northern cities whilst temperature increases for middle and southern cities are 2.2ºC and 2.9ºC under RCP4.5 and RCP8.5 climate change scenarios, respectively. CMIP5 models are also projected approximately 8%–10% of precipitation increases across the province. However, the seasonal pattern of precipitation is not changing much although winter precipitation is projected to increase more than summer in terms of percentage changes. Furthermore, climate change will also cause increased frequency and intensity of extreme weather events, such as summer rainfall storms, heatwaves, and increased inter-seasonal and inter-annual variability in temperature and precipitation. 6. Higher temperature will cause various risks to the agricultural sector of Shanxi Province. For animal and poultry production, higher temperature will cause heat stresses to animals and poultries. Higher temperature, in combination with increased precipitation and humidity, will also increase infectious diseases as well as their cycles and transmitting patterns. Higher temperature may also cause early flowering for crops and fruit trees. This will make such crops and fruit trees vulnerable to early spring frost due to increased variability in temperature. Higher temperature will also cause increased water demands for crops and trees, which will exacerbate drought stresses to crop and trees during dry season and extended drought periods. Higher temperature will also change the pest and disease patterns to crops and fruit trees. 7. The projected increases in precipitation will increase the overall water resources of Shanxi Province. However, it is not expected that will relief the water deficiency issue due to the existing

2 water deficiency nature of the province. Further economic development will certainly exacerbate the stressful surface and groundwater resources in the province. Currently, irrigation is the largest water user in Shanxi Province, which is accounting for over 60% of the total provincial consumption in 2014. Wheat is probably the most water demanding crop because the very dry spring in the province. It is assessed that the proposed subprojects are not likely making significant impact on the province’s water resources but may affect other users locally due to the intensity of those enterprises. Therefore, water saving measures are recommended to all subprojects in their project design. 8. Adaptation measures are recommended, together with mitigation practices, to all subprojects. Those are summarised in the following table.

Structural Adaptation Nonstructural Adaptation Subprojects Measures Measures Mitigation Practices Livestock 1). Design heat protection 1). Develop robust disease 1). Using LED lighting for all and poultries and/or prevention measures control measures and farmsa for animal/poultry houses procedures 2). Pig manure biogas 2). Develop more effective generationb animal feeding and 3). Fermentation of chicken management procedures manure for organic fertiliser Fruits and 1). Plant tree/grape species 1). Develop robust 1) Reduce chemical fertiliser grapes that are better adapting the pest/disease control measures uses using organic fertilizer like gradually rising temperature 2). Develop effective irrigation manure etc. and balanced 2). Design and build the schedules fertilizer technology. orchard with effective water 3). Study/explore future 2) biological pest control to saving measures including suitable areas for the reduce pesticide use rain water harvest facilities silverberry plants Mushroom 1). Include insulation in the 1). Develop robust mushroom 1). Design the plastic and plastic greenhouses production schedules to avoid greenhouses with sufficient vegetables 2). Design strengthened damages from heatwaves and energy saving measures, structure for plastic summer storms including insulation of north greenhouses walls, upgraded fans and lighting 3). Design sufficient water and ventilation systemsb and so saving measures on. 4). Design with waste and waste water treatment facilities Food 1). Increase stormwater 1). help the food ingredient 1). Design the food processing processing pipes capacity by 10% to producers, mostly local workshops with sufficient energy account for projected farmers, for maintaining saving measures, including increased precipitation normal raw material supply by insulation of walls, upgraded intensity adapting climate change heating, lighting, ventilation 2). good insulation and systems, and adopting more ventilation to reduce energy efficient equipment potential heat stresses to workers Cold 1). Design with sufficient 1). Develop improved 1). Design with improved storages drainage capacity for the management plans to insulation storage and other related minimise the cold storage time 2) Adopt cooling equipment with facility to avoid damages for food and ingredients high energy efficiencyb from flash floods a Currently, the feasibility study reports (FSRs) costing the whole electrical system as a whole; the required data will be made available as project progress. b Additional data will be provided as project progresses.

9. The total climate finance of this project is accounted for $12.8 million and $5.9 million for adaptation and mitigation respectively to which $7.96 million and $3.91 million are from the Asian Development Bank (ADB) fund. The total greenhouse gas (GHG) emission is accounted for

46,536.77 tons that include total emission of 57,013.21 tons and 10,476.44 tons of offset from tree plantation and other measures.

B. INTRODUCTION 1. Project Background

10. Shanxi Province is located among provinces of Hebei, Henan, Shanxi, and Inner Mongolia. It has been the largest coal producer in the PRC. About 60% of the provincial gross domestic product (GDP) is contributed from the coal industry. However, the coal mining industry in Shanxi Province has been hardly hit by the PRC’s recent economic slowdown and the change in the energy policy promoting renewable energy. As a result, Shanxi became the second slowest PRC province in economic performance in 2015. Given the targeted reduction of overcapacity in the coal industry imposed by the Government of the PRC, Shanxi’s economy is expected to remain an underperformer over the coming years. 11. The economic slowdown poses a challenge to SPG to accomplish the eradication of absolute poverty by 2020 as required by the PRC government. The poverty populations are mostly living in the rural areas of Shanxi Province. Agriculture is still the important means of most rural poverty people. 12. This project is to help Shanxi Province to eradicate extreme poverty and improve livelihood in the poverty-stricken areas of the province. With particular request from SPG, this project is to promote agriculture-based industry for local specialty agricultural products, as part of its poverty alleviation and rural development program. 13. The project will have two outputs: (i) agricultural value chains (AVCs) strengthened; and (ii) inclusive business mechanism piloted. 14. Output 1 will help about 19 project agribusiness companies and cooperative (PACs) finance (i) civil works and equipment (for production bases, processing lines, storage facilities, and logistic facilities), and agricultural materials, (ii) capacity building and advisory services on business strategy and planning, and sustainable cooperation mechanisms with farmers, and (iii) support for certification of food and agricultural product safety; 15. Output 2 will support capacity building for (i) private sector services that are or will be associated with or facilitate the PACs’ AVC strengthening (e.g., financial institutions, agricultural insurance agents, logistic services, e-commerce, wholesale markets, and cooperatives’ professional farming services) and (ii) personnel of managing existing government programs (e.g., small- and medium-sized enterprise support program, rural infrastructure improvement program, and employment promotion program). The project will also facilitate the PACs to establish or strengthen the linkages with private sector services and the government programs. 16. This output will help strengthen the implementation of the Shanxi Provincial Rural Poverty Alleviation and Development Program, 2011–2020 and its follow-up program. The project will (i) train the staff of the Shanxi Poverty Alleviation and Development Office (SPADO) and other relevant agencies on value chain analysis and the IB approach, (ii) help the SPADO design and pilot in advance the impact assessment of the subprojects, and (iii) prepare policy recommendations for a wider application of value chain analysis and the IB approach as part of its poverty alleviation and rural development program to support the PRC’s new rural development policy to promote agriculture-based industry. 17. There are 19 subprojects proposed to this project. Those subprojects include chicken and pig farms, orchards, mushroom production, whole sale markets, and food processing. Among the 19 subprojects, two proposed by Datong City are in the north of Shanxi Province, where the

5 climate is dry and cold. The other 17 subprojects are all located in the middle and south of the province where climate is warmer and wetter than the northern Shanxi Province. 18. This climate risk and vulnerability assessment is conducted to estimate the potential impacts of climate change on each subproject, according to ADB’s guidelines. This assessment reviewed available literature and data sets regarding the historical trend of climate variables, the projected future changes in climate, and an analysis of climate change risk based on available information. 2. Current Climate of Shanxi Province

19. The climate of Shanxi Province is an arid continental monsoon climate. Figure 1 shows the annual mean temperature and precipitation. The annual mean temperature is ranging from 4.2°C to 14.2°C, increasing from north to south and decreasing from valleys to high mountains. Winters are long, dry, and cold, while summer is warm and humid. Spring is extremely dry and prone to dust storms. Shanxi is one of the sunniest parts of the PRC. Early summer heat waves are common. Figure 1: Annual Mean Temperature and Precipitation of Shanxi Province

20. Annual precipitation averages around 350 in the north to 700 millimeters (mm) in the southeast of the province. Figure 2 shows the monthly mean precipitation of Datong, Jiexiu, and Yuncheng which are in the north, middle, and south of Shanxi Province, respectively. A decreasing trend is distinct from south to north. However, their monthly distribution patterns are all identical. July and August are the wettest months followed by June and September.

Figure 2: Monthly Mean Precipitation in Datong, Jiexiu, and Yuncheng

Figure 3: Annual Mean Temperature from 1955 to 2010 in Datong, Jiexiu, and Taiyuan

21. Like many areas of the PRC, distinct climate change trends have also been identified for Shanxi Province. Zhao et al (2006) reported that the annual temperature is rising 0.15°C/decade and precipitation is decreasing 17.3 mm/decade on average of 30 stations across Shanxi Province between 1957 and 2003. Annual mean temperature analysis results (Figure 3) are consistent with Zhao et al (2006). Those stations are in the north, middle, and south of Shanxi province, which is representing the different types of climate of the province. However, the conclusion of Zhao et al (2006) regarding decrease in precipitation may be arguable based on

7 the annual precipitation time series of the same three stations (Figure 4). Based on our analysis of those time series, there is a decreasing trend in precipitation but not statistically significant. Precipitation increases in 2004-2010 may have changed the simple statistical results of Zhao et al (2006). Figure 4: Annual Precipitation from 1955 to 2010 in Datong, Jiexiu, and Yuncheng

3. Report Objectives and Scope

22. This project is aimed at strengthening agricultural production, processing, storage, and marketing of selected agricultural products through developing rural enterprises, infrastructure, financial services and capacity building to relevant government agencies for inclusive rural development. Climate change is likely to affect most subproject with rising temperature and changing precipitation regimes, hence the available water resources to agricultural production and food processing. This study is to assess the potential climate risks and vulnerability of proposed subprojects and develop appropriate proofing and adaptation measures that will be included in the project design. 23. In the following sections, the methodology and climate change scenarios are reported in Section C, followed by Section D that report climate risks to proposed subprojects and proofing/adaptation measures. Section D will report the mitigation measures that are included in this project. Section F will calculate the climate finance of this project including investment for both adaptation and mitigation.

C. CLIMATE CHANGE SCENARIOS AND DATA 1. Climate Scenarios and Assumptions

24. Future climate projections of the Intergovernmental Panel on Climate Change (IPCC) CMIP5 global climate models (GCMs) are used for constructing climate change scenarios for this study. These scenarios will be constructed in Shanxi provincial scale and city scale, to consistent with the required analyses. 25. The CMIP5 climate projections have been simulated under four different scenarios defined by the representative concentration pathways (RCPs): RCP2.6, RCP4.5, RCP60, and RCP8.5. Those scenarios are defined by the RCPs to represent the GHG concentration (not emission) that supersedes the Special Report on Emissions Scenarios (SRES) used in the IPCC AR4 Assessment. Figure 5 illustrate the forcing agents' atmospheric CO2-equivalent concentrations defined by all four scenarios.

Figure 5: All Forcing Agents' Atmospheric CO2-equivalent Concentrations (in parts-per-million-by-volume [ppmv]) according to four RCPs)

26. The projected changes of those four scenarios are illustrated in Figure 5. Among the four scenarios, RCP2.6 is considered the lowest scenario that corresponds to the agreed outcomes of the Paris Agreement (no more than 2.0°C over pre-industrial). RCP4.5 and RCP6.0 are the medium and high scenarios but their differences are evident only in the late stage of this century. There is little difference in 2050 time slice adopted in this study. RCP8.5 is the extreme case that projects the most significant changes. Therefore, we use the RCP4.5 and RCP8.5 in conducting this study. 27. It is emphasized that climate projections are subject to considerable uncertainty. One important aspect is to comprehend such an uncertainty in decision making and policy planning process. Within this context, any climate change scenario constructed on single GHG emission rate and/or individual GCM outputs is generally considered inappropriate for assessment

9 purposes because it cannot provide information of the uncertainty and it associated projection range. 28. To reflect the uncertainties in future climate change projection, different GHG RCPs was required to reflect different trajectories of future social-economic development. The uncertainty also comes from our limited understanding to the climate systems, hence possible errors in GCM simulation of the real world. Comprehensive scientific experiments, with a large number of GCMs, have been conducted to check the climate sensitivity resulted from such uncertainty. The climate sensitivity results were generally also adopted in assessment. Thus, a combination of different RCPs and climate sensitivities could be used to characterise the future climate change scenario as well as associated uncertainty range. 2. CMIP5 Climate Projection Data

29. The IPCC CMIP5 climate projection and baseline data are obtained from www.worldclim.org website. The projection data is downscaled GCM data from CMIP5 (IPPC Fifth Assessment) with different resolution that are available for all AR5 GCMs. Table 1: CMIP5 Global Climate Models Used for Analysing Future Climate Change in This Study GCM Code RCP4.5 RCP8.5 ACCESS1-0 (#) AC tn, tx, pr tn, tx, pr BCC-CSM1-1 BC tn, tx, pr tn, tx, pr CCSM4 CC tn, tx, pr tn, tx, pr CESM1-CAM5-1-FV2 CE tn, tx, pr CNRM-CM5 (#) CN tn, tx, pr tn, tx, pr GFDL-CM3 GF tn, tx, pr tn, tx, pr GFDL-ESM2G GD tn, tx, pr GISS-E2-R GS tn, tx, pr tn, tx, pr HadGEM2-AO HD tn, tx, pr tn, tx, pr HadGEM2-CC HG tn, tx, pr tn, tx, pr HadGEM2-ES HE tn, tx, pr tn, tx, pr INMCM4 IN tn, tx, pr tn, tx, pr IPSL-CM5A-LR IP tn, tx, pr tn, tx, pr MIROC-ESM-CHEM (#) MI tn, tx, pr tn, tx, pr MIROC-ESM (#) MR tn, tx, pr tn, tx, pr MIROC5 (#) MC tn, tx, pr tn, tx, pr MPI-ESM-LR MP tn, tx, pr tn, tx, pr MRI-CGCM3 MG tn, tx, pr tn, tx, pr NorESM1-M NO tn, tx, pr tn, tx, pr

30. The baseline data is for the period of 1961–1990 that are developed based on observation data. For the future projections, there are two time slices are available, including 2050 and 2070, which are averages of 2040–2060 and 2060–2080 respectively. The 2050 changes used in this study are derived by comparing 2050 projections with 1960–1990 baseline data. As shown in Table 1, a total of 19 and 17 GCMs are used for analysing projected climate changes for Shanxi Province under RCP4.5 and RCP8.5 scenarios respectively. Daily climate projection data are also obtained to refer the severity and frequency of those extreme climate events. However, previous analysis suggests that those daily time series are often no better than the change ratios derived from the average of downscaled climate projections. 3. Projected Changes for Temperature and Precipitation in 2050

31. The future climate changes are derived by analysing CMIP5 GCMs for Shanxi Province with focus on project cities. As reported in Table 1, a total of 19 and 17 GCMs are used in analysing the 2505 changes under RCP4.5 and RCP8.5 scenarios respectively. As reported in

Chapter 3, different GCMs simulated different climate for Shanxi Province due to their initialization and simulation setting.

Table 2: Projected Changes in Annual Mean Temperature and Precipitation by Different GCMs in 2050 for Shanxi Province RCP4.5 RCP8.5 GCM Tmean (°C) Precip. (%) Tmean (°C) Precip. (%) ACCESS1-0 (#) 2.6 9.74% 3.2 11.69% BCC-CSM1-1 2.2 12.24% 3.0 8.68% CCSM4 1.9 6.55% 2.5 13.44% CESM1-CAM5-1-FV2 4.8 10.89% CNRM-CM5 (#) 1.7 18.00% 2.3 9.44% GFDL-CM3 1.4 10.30% GFDL-ESM2G 3.2 12.25% 4.0 1.46% GISS-E2-R 2.0 9.62% 2.3 6.13% HadGEM2-AO 2.6 23.14% 3.0 19.46% HadGEM2-CC 2.5 11.55% 3.4 12.09% HadGEM2-ES 2.5 10.18% 3.0 12.76% INMCM4 1.0 4.92% 1.5 2.77% IPSL-CM5A-LR 2.8 9.54% 3.9 7.64% MIROC-ESM-CHEM (#) 2.2 19.33% 2.7 20.85% MIROC-ESM (#) 1.6 16.14% 2.1 14.86% MIROC5 (#) 2.5 4.35% 3.9 8.05% MPI-ESM-LR 2.5 -3.22% 2.9 1.47% MRI-CGCM3 2.6 8.03% 3.7 16.10% NorESM1-M 2.3 0.53% 2.8 11.56%

32. As shown in Table 2, the projected annual mean temperature changes are ranging from +1°C to + 4.8°C and from +1.5°C to + 4.0°C in Shanxi Province under RCP4.5 and RCP8.5 climate change scenarios respectively based on different GCMS. Similarly, annual precipitation is also projected to change from -3.22% to +23.14% and from +1.46% to +20.85% under climate change scenarios of RCP4.5 and RCP8.5 respectively based on different GCMs. Whilst variations are large among different GCMs, they have consistently projected that both temperature and precipitation will increase in 2050 in Shanxi Province. 33. From Table 2, it is recognized that there are very large discrepancies in GCM simulation results when we apply them in a specific location or region because they are global models. In other words, they may be consistent each other globally but greatly varied in a specific location or region.

Figure 6: Projected Annual Mean Temperature for Shanxi Province in 2050 under RCP4.5 and RCP8.5 Climate Change Scenarios

34. In this study, the median change value of those GCMs projections is used for climate change scenarios of RCP4.5 and RCP8.5. The assessment will be based on those values for project component. The average of GCMs is normally not used for impact studies because average of GCM projections is easily affected by GCMs with extremely low or high projections. Median of all GCM projections reflects projections of majority of GCM simulation results. 35. Figure 6 and Figure 7 show the projected annual mean temperature and precipitation for Shanxi Province in 2050 under RCP4.5 and RCp8.5, respectively. Compared to the current annual temperature and precipitation shown in Figure 1, Shanxi Province is getting warmer and wetter in 2050 under either RCP4.5 or RCP8.5 climate change scenarios. 36. Under the low climate change scenario (RCP4.5), there is a clear trend that temperature increases are lower in southern cities and higher in northern cities. As shown in Figure 8, the temperature will increase for 2.3 – 2.4°C for those northern cities of Datong, Suozhou, Xinzhou, and Luliang whilst increases for all other cities are all below 2.3°C. Increases are clearly lower for three southern cities of Yuncheng, Jincheng and Changzhi than all other cities. Temperature projected under the high climate change scenarios (RCP8.5) is significantly higher than the low scenario (Figure 9). Increases for northern cities are all at approximately 3.0 whilst other cities are also projected to increase above 2.9°C except the three southern cities of Changzhi, Jincheng and Yuncheng.

Figure 7: Projected Annual Precipitation for Shanxi Province in 2050 under RCP4.5 and RCP8.5

37. Precipitation is also projected to increase under both climate change scenarios. Increases projected under the low scenario (RCP4.5) are slightly higher than the high scenario. In term of percentage, it is projected higher increases for northern cities that are at approximately 10% increases under both scenarios. However, absolute increases in term of mm are higher in those middle and southern cities as their current precipitation is much higher than those of northern cities. 38. Comparing Figure 8 with Figure 9, it is not difficult to find that the high climate change scenario (RCP8.5) has projected higher temperature increases than the low climate change scenario (RCP4.5) but less precipitation increases than the low scenario. This suggests that future precipitation changes may not be in the same direction with temperature. 39. Compared with annual total precipitation, it is also very important for changes in precipitation distribution over months and seasons. Historically, over 60% of the annual precipitation of Shanxi is falling in June, July, and August. Spring is normally very dry. Changes in the monthly precipitation pattern will affect the cropping system and agriculture profoundly. Figure 10 shows that the projected annual precipitation increases are not changing the current monthly distribution patterns of Shanxi Province. There is a fairly even monthly increase in precipitation across the 12 months as simulated under RCP4.5 and RCP8.5, respectively. This is likely to benefit the agriculture and water resources of Shanxi Province.

Figure 8: Projected Changes for Annual Mean Temperature and Precipitation under RCP4.5 Climate Change Scenario in 2050 for Cities of Shanxi Province

Figure 9: Projected Changes for Annual Mean Temperature and Precipitation under RCP8.5 Climate Change Scenario in 2050 for Cities of Shanxi Province

Figure 10: Current and Future (20,500 Monthly Average Precipitation Simulated under RCP4.5 and RCP8.5 Climate Change Scenarios for Datong, Linfen, Yuncheng, and Jincheng in Shanxi Province)

4. Extreme Climate Events

40. One of the important aspects of climate change is increased frequency and severity of extreme events, such as heatwaves and severe storms and resultant flash floods. The most likely causes behind an extreme weather event can be complicated. These events are formed mostly by combinations of multiple factors and natural variability. In general, extreme weather is typically rare. For example, there are only 6 days with maximum temperature reached or higher than 38°C in Taiyuan over the 60 years from 1951 to 2010. However, as shown in Figure 11, climate change is increasing the odds of more extreme weather events taking place. Figure 11 is also applicable to extreme rainfalls. In a skewed distribution, such as that of precipitation, a change in the mean of the distribution generally affects its variability or spread, and thus an increase in mean precipitation would also imply an increase in heavy precipitation extremes, and vice-versa (IPCC, 2013). However, it is often difficult to identify a definite change ratio for extreme precipitation events and/or heat waves. 41. In this study, the change ratio of extreme precipitation events is determined in combination of average changes of summer precipitation but also referred to downscaled daily GCMs. A generalized extreme value (GEV) distribution function is applied to selected stations in describing its annual maximum daily rainfall in calculating the recurrences of different extreme precipitation events.

Figure 11: Possible Connections between Climate Change and Heatwaves (adopted from United State Environmental Protection Agency)

Figure 12: General Extreme Value Distribution of the Annual Maximum Daily Precipitation of Xininga

a Baseline and it changes under future climate scenarios, where black dots are projected maximum daily rainfall events; black line is the projected trends; the blue and red lines are the lower and upper uncertainty boundaries, respectively.

42. Figure 12 shows the GEV distribution of the projected annual maximum daily precipitation of Taiyuan in 2050 under the RCP4.5 scenario, together with lower and upper uncertainty limits. The current 50 year return annual maximum daily precipitation at Taiyuan is 118.00 mm. Under the RCP4.5 climate change scenarios, the precipitation event of such intensity is likely becoming 128.97mm with lower and upper uncertainty limits of103.36 mm and 160.49 mm, respectively. This suggests that there is chances for 50 years return precipitation events in 2050 may be similar to the current 100 years return precipitation in Taiyuan. 43. Therefore, current design for some project components based on current standard may be subject to expose to climate risks in the coming years. Therefore, it is important to assess those designs against future climate change projections. Modifications to design may be required for some project components if the assessment finds that they are vulnerable to climate change. D. CLIMATE RISKS ASSESSMENT 44. There are 19 subprojects proposed in this project. Those subprojects are all agriculture related enterprises, which include pig farms, chicken farms, lamb production, mushrooms, orchards, vegetables, food processing, storage and whole sales. Those enterprises are all closely related to the agriculture of Shanxi Province. Therefore, in assessing climate risks to those subprojects, it is also important to discuss climate risks to agriculture of Shanxi Province. 1. Climate Change Impact on Agriculture of Shanxi Province

45. Climate change affects agriculture in a number of ways, such as through changes in average temperature and rainfalls, extreme events (heat waves and storms), pests and diseases, and so on. Another important factor is changes in regional water resources caused by precipitation changes in both average and seasonal distribution as well as increased inter-annual and seasonal variability. 46. The topography of Shanxi Province is dominated by mountains and hills, which makes approximately 80% of the total provincial areas. The cultivated areas is making only about 25% of the total land areas of the province, including plain areas of valleys/basins and small proportion of the hilly areas. Double crops are mainly located in where winter wheat growing areas in valleys/basins of middle and south of Shanxi Province. Areas in the north of Taiyuan are mainly single cropping zone due to the harsh winter and short growing seasons. 47. First of all, the projected temperature change is likely push the winter wheat growing boundary further north in the future. This will expand the double cropping areas of Shanxi Province. The cropping patterns in the middle and south of the province may also be affected. For example, the harvest of winter wheat may be gradually shifting to earlier dates. This will make more growing time for the second crop in the region. However, the two-crop patterns are not likely to change as the current cropping patterns are suitable for a wide range of climate patterns in northern PRC. The higher temperature in the winter season may also favourable to vegetable productions that are mostly growing in the plastic greenhouses during the winter season. This is particularly favourable for areas in the north of the province where is normally difficult to grow vegetables. 48. However, rising temperature may also have adverse impact on agriculture in the middle and south of the province. Different plant species/varieties are responding to temperature differently. As summarised by Nix (1981), and Zuo (1996), crops and their temperature responses may be categorised as microtherm (mainly conifers and cool temperate climatic plants), mesotherm (including all the major temperate crop species like wheat, barley, oats), megatherm C3 (soybean, peanut, rice, etc.), and megatherm C4 (maize, sorghum and sugarcane). The optima, lower and upper temperature for those crop/plant types are shown in Table 3. There is an

17 optimal temperature for plant/crop to growth. The growth rates are slowing down as temperature increase or decrease from the optimum temperature. 49. Therefore, warmer conditions projected for Shanxi Province may affect the productivity and grain quality of the current crop varieties. Agricultural scientists, crop breeders may need to develop new crop lines/varieties that are perform better in warmer conditions. 50. In general, the projected rising precipitation is favourable for crop production in a dry region like Shanxi Province. However, continuous wet conditions in wheat grain filling stage may affect both the wheat productivity and grain quality, which is likely in middle May to early June. Furthermore, increased temperature and precipitation in spring will also cause increases insects and disease for crops across the province. Table 3: The Optima, Lower, and Upper Temperature Threshold of Four Different Types of Crop and/or Plants Optima Lower Threshold Higher Threshold microtherm 10-12°C 0°C 25°C mesotherm 19°C 3°C 35°C megatherm C3 28°C 8°C 40°C megathermC4 32°C 10°C 45°C

51. Livestock production is an important component of agriculture. Frequent and extended heatwaves will cause stresses to animals and poultries, which will affect the productivity of farms. Increased wet conditions may also have adverse effects on animal production. Similar to crops and fruit trees, higher temperature and precipitation may cause changes in the extent and cycles of pests and diseases. New diseases/pests may also grow from changed climate environment. 52. Finally, agriculture production is heavily relying on regional water resources. Irrigation uses more than half of the total water consumption in Shanxi Province. Further agricultural development and higher temperature will certainly cause higher water demands from the agricultural sector. Due to its importance, water resource issue is discussed separately in the following section. 2. Climate Change Impact on Provincial and Regional Water Resources

53. Water is one of the most sensitive resources to climate change. In general, changed precipitation will significantly affect regional water resources. Higher temperature will increase evaporation and reduce river flow and recharge to groundwater. Furthermore, changes in seasonal precipitation patterns will also affect the overall water resources. 54. As reported earlier, both temperature and precipitation are projected to increase for Shanxi Province in 2050. However there is not obvious changes in the monthly/seasonal precipitation patterns. This is likely to benefit the overall available water resources although the projected higher temperature will increase the evaporation. 55. In general, increased precipitation will lead to increased water flow in rivers and hence more available water resources. Similarly, increased precipitation will also lead to more recharges to groundwater. Those increases are varied significantly with local conditions. In Australia, the stream flow may increase 1.5%–2.5% if rainfall increases 1% (Chiew et al, 2002). This is complicated by rising temperature in assessing climate change impact on water resources. This is because higher temperature will cause significant increases of evaporation, especially for the cold regions. Based on the modelling results carried out in Qinghai and Heilongjiang (work for other ADB projects—unpublished), it is estimated that the regional water resources will increase for approximately 10%–12% on average.

56. However, this does not mean less drought events in Shanxi Province in the future. Whilst long term mean precipitation may increase, it is more likely that Shanxi Province will have more frequent and extended drought events in the future due to increased inter-annual climate variability caused by climate change. 57. Shanxi Province is a water scarcity province. The total annual water resources are assessed as 14.2 billion cubic meters (m3) based on data from 1956 to 1979 (Xue, 2004). This includes both surface and groundwater resources. The assessed maximum extractable water volume is 6 billion m3. However, it is estimated that annual water demands are approximately ranging from 7 to 8 billion m3 (Duan et al, 2005). 58. Currently, PRC implements the strictest water resource management policy that provincial government allocates total extractable water volumes to each city, and the city will do the same to its counties. According to the provincial year book of 2014, the total available and extracted water resources in 2014 were 11.126 and 7.137 billion m3 in Shanxi Province, respectively. As shown in Figure 13, irrigation is the largest water user in Shanxi province, which is consuming 64% of the total extracted water resources in 2014. The other large water users are the industrial uses, and urban households, which used 19.9% and 12.8% of the total extracted water resources. Water consumed by other users were made only a small proportion of the overall water uses. Those include rural household, forestry, fisheries, livestock, and ecological uses.

Figure 13: Water Consumptions by Different Sectors of Shanxi Province in 2014

59. Due to the dry spring, wheat is the largest single crop requiring large volume of irrigation water. Therefore, the largest risk to the overall water resources in Shanxi Province is likely the expansion of winter wheat crop, which may become possible due to climate change caused higher temperature in the middle/north of the province. Therefore, the provincial authority should take the water resource issue seriously and restrict the wheat growing area now and the future.

60. The subprojects of this project are mainly proposed for livestock and poultry, food/vegetable storage, mushroom production, and food processing. Those are not likely consuming significant volume of water resources in overall and cause risks to provincial and/or regional water resources. However, they may cause issues at local scale due to production intensity of those enterprises. Whilst their water consumption is not significant in regional scale, they may affect water uses of their neighbours and/or local catchment/aquifer. This issue should be addressed by the environmental and social safe guarding process. 3. Climate Risks to Proposed Subprojects

61. A total of 19 subprojects are proposed in this project, which are in various cities across Shanxi Province. Those subprojects may be considered as five categories of enterprises according to their product types, including (i) livestock and poultry; (ii) orchards; (iii) mushroom and vegetables; (iv) food processing; and (v) market and storage. Climate change will have direct impact on those enterprises with higher temperature, changed precipitation regimes, and more frequent and severer extreme weather events. Furthermore, they will also indirectly affected by changes in local crop, vegetables and fruit production caused by climate change. 3.1 Climate Risks to Livestock and Poultry Subprojects

62. Climate change impact on livestock and poultry production include changes in feedstuff supply, animal growth and productivity, diseases, and other possible changes such as reproduction and biodiversity (Rojas-Downing, M.M., et al, 2017). In this project, seven livestock and poultry production subprojects are proposed, including egg, chicken, pig, beef cattle and meat lamb production (Table 4). Those subprojects are likely affected mainly by changes in temperature and precipitation. 63. Temperature is the most critical climate factor that affects livestock and poultry production, which will affect the productivity and health of animals and birds. High temperature and heat waves will cause heat stress to animals and birds that will reduce growth rates of beef cattle, chickens, pigs, and lambs, as well as the reproduction efficiency of hens and consequently egg production. 64. A combination of higher temperature and increased precipitation could translate into the increased spread of existing vector-borne diseases and macro-parasites, accompanied by the emergence and circulation of new diseases. Climate change may also generate new disease transmission models for livestock and poultry in Shanxi Province. Therefore, disease prevention and control will be a big issue for those intensive livestock and poultry farms. 65. Other climate change impacts to livestock farms are changes to the quantity and quality feedstuff and/or fodder caused by changed temperature and precipitation regimes. Changes in the availability of locally grain production will affect the cost of feedstuff, and hence the economic viability of those intensive chicken and pig farms. Those cattle and lamb production farms are almost certain to be affected by the increased inter-annual and/or season variability that will cause changes in the productivity of local fodder crops and grazing grasses. Table 4: Livestock and Poultry Production Subprojects City County Project Name Shanxi Jinlong Group Jinghua Livestock and Poultry Products Development Co., Ltd. - One Yuncheng Jishan million commercial hen farm development project Liulin Fuzhongyuan Agricultural Development Co., Ltd. - Pig farm expansion and new Luliang Liulin variety introduction project Lifen Fenxi Fenxi Hongchang Breeding Co., Ltd. - two million meat chicken farm development project

City County Project Name Fushan Guhuan Husbandry Scientific and Technology Co., Ltd. - Pig fattening and piglets Fushan farm development project Lifen Linfen Zhongde Farming Technology Development Co., Ltd. - Pig fattening and piglets Yaodu farm development project Heshun County Luhe Ecological Agriculture and Livestock Development Co., Ltd. - Beef JInzhong Heshun Cattle introduction and farm expansion project

3.2 Climate Risks to Orchard Subprojects

66. Orchards are generally susceptible to the impacts of climate change. For example, higher temperature in early spring will result early or premature flowering that is vulnerable to spring frost. Hot and dry summer will increase the water demands of fruit trees water availability is likely reduced by increased inter-seasonal and/or annual precipitation variability caused by climate change. Furthermore, orchards are potentially facing new threat from pests and diseases caused by climate change. 67. There are three different types of orchard subproject proposed in this project (Table 5). Those include subprojects of vineyard, pear orchard, and silverberry plantation. The three subprojects are very different from each other; hence very different responses to climate change. 68. Climate is very important to grape and wine production which makes a major impact on wine style and flavour. This distinguishes wine from other agriculture products. In general, grapes are more sensitive to temperature changes than most other crops. The projected temperature changes of 2.3ºC–3.0ºC in Datong will significantly change the quality of grapes and possibly flavours of the wine. The grape productivity and quality will also be affected by increased severity and frequency of heat stress during the growing season and increase in unusual weather events such as frost, hail and summer storms. 69. The silverberry (Elaeagnus sp.) is a protected plant species in PRC that grows at shady slopes of hills with elevation of 800–1,500 meters in counties of Xiangning, Hejin, and Yicheng of Shanxi Province, and Huxian county of Shaanxi Province. The areas are generally dry and hot with a growing period of 150–190 days. The precipitation of those areas is ranging from 450 mm to 550 mm that are mostly falls from July to September. The silverberry plants are cold and dry resistant but do not grow well under persistent wet conditions. It is not a widely-grown plant species.

Table 5: Orchard Subprojects Proposed in This Project City County Project Name Shanxi Phoenix Wine Industry Co., Ltd. - One thousand mu vineyard and wine production Datong Datong line project Shanxi Qierkang Elaeagnus Biological Products Co. Ltd. - Construction of 15,000 mu Base Lifen Xiangning of Silverberry (Elaeagnus sp.) Plantation

70. Climate change will certainly pose risks to the silverberry plantation project by altering the thermal and moisture environment of silverberry growing areas with increased temperature and precipitation. This may cause the silverberry growing areas expanding further north, and/or shrinking in some areas because of getting too wet. This may not affect the proposed subproject much as climate change is a gradual process. However, attention should be raised to relevant research agencies for biodiversity and conservation purposes.

3.3 Climate Risks to Mushroom and Vegetable Production Subprojects

71. There are four mushroom and vegetable subprojects proposed in this project (Table 6). In Shanxi Province, a common feature of mushroom and vegetable production is that they are all relying on controlled or semi-controlled environment, such as mushroom seedling production workshop and plastic green houses. Table 6: Mushroom and Vegetable Subprojects Proposed in This Project City County Project Name Yuncheng Yanhu Shanxi Kaisheng Fertilizers Group Co., Ltd. – mushroom production project Shanxi Juxin Weiye Agricultural and Sci & Tech Development Co., Ltd. – vegetable Jinzhong Taigu nursery and processing Guangling Kitano Edible Fungus Industrial Development Co., Ltd. – mushroom Datong Guangling seedling package production Quwo Lvheng Agricultural Development Co., Ltd. – Mushroom production, storage and Linfen Quwo processing project

72. High temperature and heatwaves are one of the major climate risks to mushroom production. Mushroom grows within a temperature range of 5°C–32°C with optimum growth temperature is 20°C–25°C, depending on types of mushrooms. The mushroom growth speed will be significantly reduced when temperature is below 15°C although mushrooms can survive temperature close to 0°C. However, it will damage mushrooms if temperature is persistently above 30°C. For fully controlled production environment, such as the mushroom seedling production, high temperature and heatwaves will cause increased cost for maintaining suitable temperature for production activities. Therefore, those mushroom production enterprises will certainly be vulnerable to the projected temperature increases caused by climate change. 73. Another climate risk is the increased severity and frequency of summer storms that cause damages to the plastic films and/or the whole structure of the plastic greenhouses used for mushroom/vegetable production. Historically, a large proportion of the precipitation is fall in a form of summer rain storms in Shanxi Province during the summer season. Climate change will further strengthen this phenomenon and poses more risks to plastic greenhouses dependent mushroom and vegetable production activities. In addition to damages to plastic greenhouses, summer storms may also result in flash floods that can cause damages to mushroom and vegetable production. 74. Climate change may also cause water shortage to mushroom and vegetable production although the overall regional water resource is not projected to reduce based on the projected precipitation changes for Shanxi Province. Both mushroom and vegetable are highly intensive production activities that require a large volume of water for small areas of lands. This can cause issues with other water users in the same aquifer and/or catchment, especially during the extended dry season. 3.4 Climate Risks to Food Processing Subprojects

75. There are five food processing subprojects proposed in this project (Table 7). Those enterprises are all producing food with locally featured agricultural material in Shanxi Province, such as dates, sophora flower-bud, millet, and wall nut. Table 7: Food Processing Subprojects Proposed in This Project City County Project Name Yuncheng Yuanqu Shanxi Shanlihong Food Co., Ltd. - Wall nut storage and processing project Yuncheng Ruicheng Shanxi Tianzhirun Date Processing Co., Ltd.- Date drink development project Xinjiang Hefeng Grain Planting Technology Cooperatives - sophora flower-bud Yuncheng Xinjiang processing project

City County Project Name Shanxi Qinzhouhuang Millet Group Co., Ltd. - Nutritious millet powder production and Changzhi Qinxian packaging Luliang Shilou Shilou Shude Jujube Industry Co., Ltd. - Date and local featured agro-product processing

76. There are two direct climate risks to those food processing enterprises. One is severe summer rainfall storms may cause localised floods if there is not sufficient drainage capacity designed for the enterprise. The other is increases in temperature and precipitation that may accelerate the degradation of the quality of food material after harvest, hence increasing the post- harvest handling cost to food processing enterprises. Indirect climate risks are climate change caused changes in quality and quantity of food material for the enterprises. For example, the increased precipitation variability may cause large fluctuations in yields of the featured food materials. Unseasonal high temperature may also cause early mature of crops and/or fruits with poor quality. Those will then affect the profitability of food processing enterprises. 3.5 Climate Risks to Cold Storages

77. There are a number of cold storages proposed in this project, including enterprises for vegetable whole sale market, mushroom and vegetable production, and food processing. Those proposed cold storages are aimed to keep the freshness of vegetables or other food ingredients for a longer period. 78. Climate risks to those cold storages are mainly the faster deteriorating rates of food ingredients, fruits, and vegetables due to increases in temperature, precipitation and humidity. As reported earlier, both temperature and precipitation are projected to increase in Shanxi Province. The freshness and quality of food ingredients, fruits and vegetables may deteriorate faster during the post-harvest handling process. The effectiveness of the cold storage will be compromised if other post-harvest handling process is not effectively managed. The higher temperature will also result in higher cost for those cold storage facilities due to energy consumption. 3.6 Climate Risk and Vulnerability Summary

79. In summary, climate change poses risks to all five categories of subprojects proposed in this project. climate risks to those industrial livestock and poultry production subprojects include (1) higher temperature may cause slow growth of livestock due to reduce food intake, increased sweating and body temperature; (2) more frequent and new infectious diseases may affect animal growth and production; (3) changed fodder and crop growth condition may cause potential local feed shortage; and (4) Increased temperature and heatwaves may cause stress to livestock and affect animal growth and health. 80. Climate risks to orchard subprojects include (1) increases in early spring temperature may cause premature flowering of fruit trees, which is vulnerable to spring frost; changed temperature and rainfalls will change the quality and flavours of grapes as well wines; (2) higher temperature and changed rainfall patterns and variability may cause increased crop water needs and decreased water availability; (3) changed temperature may cause increased pest and disease activities; and (4) changed climate environment may cause silverberry distribution areas or environmental viability of the unique protected plant species. 81. Climate change risks to mushroom and vegetables include (1) high temperature and heatwaves may cause slow growth and damages to mushrooms; (2) high temperature will cause increased cost for maintaining suitable production environment for those mushroom seedling plastic greenhouses; (3) high temperature may also cause higher water demands for mushroom

23 production; (4) summer storms may cause damages to the plastic films and/or the structure of plastic greenhouses. 82. The direct climate risks to the food processing subprojects include (1) increased running cost and water demands due to higher temperature and heatwaves; (2) increased frequency and severity of extreme climate events may cause damages to facilities and equipment of many subprojects, such as mushroom planting, food processing, livestock enterprises and so on; (3) increased temperature and precipitation may cause faster deteriorating rates for food processing ingredients and hence the quality of the products; and (4) indirect climate risks such as changes in quality and quantity of food processing ingredients caused by climate change, will affect the industry more severely because most of those subprojects are relying on locally feature food products. 83. There are a number of cold storages proposed for post-harvest handling from various subprojects. The main climate risks are that the effectiveness of those cold storages may be affected by faster deteriorating rates caused by climate change. Higher temperature will also cause higher running costs for those cold storages. E. RECOMMENDED ADAPTATION MITIGATION PRACTICES UNDER THE PROJECT 84. Adaptation measures are developed for proposed subprojects corresponding to climate risks assessed in Section D. Those include structural and non-structural adaptation measures. The structural adaptation measures will be included and constructed to the proposed infrastructure to proof/reduce potential risks posed by climate change. For example, measures designed for keeping animal/poultry houses cooler are structural adaptation measures for heatwave risks to livestock/poultry production. Nonstructural measures are operational and/or management measures to prevent/reduce climate risks. For example, developing more effective irrigation schedules to reduce drought risks caused by climate change. Both structural and nonstructural adaptation measures are applicable to all the five categories of subprojects. 85. For livestock and poultry production subprojects, an important adaptation measure is to modify infrastructure design to protect livestock and poultries from heat stress caused by high temperature and heatwaves. One of the most important adaptation measures is to develop robust disease control measures and procedures for future climate conditions. There are standard general disease control procedures for the livestock and poultry industries in PRC. Further development of such procedure is to prevent and/or control climate change caused infectious, waterborne, and other potential diseases caused by changed thermal and moisture environment. Secondly, heat/protection/prevention measures are developed for the design of those animal/poultry houses to reduce the heat-stress of animal and poultries during heatwaves. Those include various types of fans and cooling cells, which are much cheaper than air-conditioning but effective in the peak high temperature season. Finally, it is also recommended that those livestock/poultry production enterprises to develop more effective animal feeding and management procedures to reduce risks posed by climate change, which may range from the farm’s day to day feeding, water saving measures, hygiene management to the planning of feedstuff sources and mix and so on. 86. Adaptation for orchards subprojects include measures for adapting to the rising temperature and climate changed caused precipitation variability and water shortage. For the pear and grape plantations, it is recommended to plant more suitable tree/grape species that are better adapting the gradually rising temperature, which is normally a fruit tree species with longer growing periods during the year. The other important aspect is irrigation. Because of climate change, fruit trees may require mode water to maintain normal growth and productivity. Therefore,

24 it is recommended to develop more robust irrigation schedules and water saving measures for those fruit tree plantations to use water more efficiently and adapting to potential water shortages caused by changed temperature and precipitation regimes. It is also recommended that orchard enterprises to develop robust pest/disease control measures to deal with potential changed pest and disease frequency and cycles caused by climate change. Finally, it is also recommended that relevant agencies at provincial and/or city level to study/explore future suitable areas for the silverberry plants as climate change may make change the environment that the plant has been adapted to for thousands of years. This is not only for an adaptation measure for the plantation enterprise, but more importantly a biodiversity conservation measure for the state protected plant species. 87. Those mushroom and vegetable production subprojects are all using plastic greenhouses that is fully or semi-controlled growing environment. It is recommended the design of those plastic greenhouses to include heat insulation measures to prevent crop damages caused by unseasonal heatwaves and high temperature. It is also recommended to strengthen the structure of those plastic greenhouses to resist summer storms that often damage the plastic films and the greenhouse structure. Similar to fruit production, efficient water use and water saving is also a necessary adaptation measure. It is recommended that the design and construction of those infrastructure to include sufficient water saving measures to reduce water consumption in the production process. 88. For food processing subprojects, it is recommended that stormwater pipes for workshop and/or production areas are designed with an extra 10% of drainage capacity to avoid floods caused by increased intensity and frequency of summer rainfall/storms. It is also recommended the workshop design to include good insulation/ventilation to reduce potential heat stresses to workers during the hot season. Other nonstructural measure recommended to these enterprises is to help the food ingredient producers, mostly local farmers, for maintaining normal raw material supply by adapting climate change. 89. Adaptation measures for cold storages are mainly designed with improved insulation to reduce the impact of high temperature. In the other hand, it is also recommended that relevant enterprises develop better plans to minimise the cold storage time for their products in order to preserve the product quality and reduce the storage costs. 90. Mitigation measures are required to be designed into all subprojects where is appropriate. For all subprojects, energy saving measures are recommended for project design. Those include using LED lighting systems, improved insulation to reduce energy consumption, and using efficient energy equipment in cold storage, food processing, and mushroom and vegetable productions. Waste processing measures are also recommended for those enterprises to reduce GHG emission. For those pig farm expansion subprojects, existing biogas facility is used in the design for pig farms in processing pig manure for reducing the environmental pollution and GHG emission from pig manure. The biogas produced from the pig farm will be supplied to neighbouring farmers as fuel for their household uses. Chicken farms are designed with fermentation equipment to produce organic fertilizer that will also reduce the chicken manure GHG emission by replacing chemical fertilizer application. Furthermore, the three fruit plantations will also reduce the GHG emission. 91. Fruit trees planted in this project have dual benefits. First, the silverberry plantation expands the growing areas for a protected plant species although there are economic purposes. The rain water harvesting measures are also an adaptation measure. To plant pear fruit trees, terraces are going to be built for better water and soil conservation, which is also an adaptation

25 measure. All fruit trees and grape crops proposed in this project will convert and store carbon dioxide, which are mitigating GHG emission. 92. Table 8 summarizes the recommended structural and non-structural adaptation measures as well as mitigation practices for different categories of proposed subprojects. Structural adaptation measures have been recommended to the design institute (DI) to include into the final project design. Non-structural adaptation measures are recommended to be included into the capacity building program for building resilience to these enterprises in the implementation stage. Table 8: Summary of Structural and Nonstructural Adaptation Measures, and Project Mitigation Practices Structural Adaptation Nonstructural Adaptation Subprojects Measures Measures Mitigation Practices Livestock 1). Design storm, flash 1). Develop robust disease 1). Using LED lighting for all and poultries floods, and heat protection control measures and farms and/or prevention measures procedures 2). Pig manure biogas for animal/poultry houses 2). Develop more effective generation animal feeding and 3). Fermentation of chicken management procedures manure for organic fertiliser Fruits and 1). Plant tree/grape species 1). Develop robust 1) Reduce chemical fertiliser grapes that are better adapting the pest/disease control measures uses using organic fertilizer like gradually rising temperature 2). Develop effective irrigation manure etc. and balanced 2). Design and build the schedules fertilizer technology. orchard with effective water 3). Study/explore future 2) biological pest control to saving measures including suitable areas for the reduce pesticide use rain water harvest facilities silverberry plants Mushroom 1). Include insulation in the 1). Develop robust mushroom 1). Design the plastic and plastic greenhouses production schedules to avoid greenhouses with sufficient vegetables 2). Design strengthened damages from heatwaves and energy saving measures, structure for plastic summer storms including insulation of north greenhouses walls, upgraded fans and 3). Design sufficient water lighting and ventilation systems saving measures and so on. 4). Design with waste and waste water treatment facilities Food 1). Design an extra 10% of 1). Help the food ingredient 1). Design food processing processing drainage capacity for producers, mostly local workshops with sufficient workshop and/or factory farmers, for maintaining energy saving measures, 2). good insulation and normal raw material supply by including insulation of walls, ventilation to reduce adapting climate change upgraded heating, lighting, potential heat stresses to ventilation systems, and workers adopting more energy efficient equipment Cold 1). Design with sufficient 1). Develop improved 1). Design with improved storages drainage capacity for the management plans to insulation storage and other related minimise the cold storage time 2) Adopt cooling equipment with facility to avoid damages for food and ingredients high energy efficiency from flash floods

F. GHG EMISSION ESTIMATES FOR ALL SUBPROJECTS 93. The GHG emissions will be generated during operation from the use of energy, including coal, fuel oil, natural gas, diesel, electricity, and from management offices and operational equipment and vehicles at each subproject. In addition to CO2 emission from the burning of fossil fuels, other non-CO2 GHG, such as methane (CH4) and nitrous oxide (N2O), are also contributing to global warming. In this project, such non-CO2 gases are mainly from livestock subprojects. Those non-CO2 greenhouse gases are calculated as CO2 equivalent. The total GHG emissions

26 will also be partly offset by carbon sequestration from those fruit tree planting subprojects, which will use some traditional energy but will also absorb CO2 during tree/plant growth and store carbon above surface and in soils. The GHG emission is calculated using data provided by the feasibility study report (FSR) documents for all 19 subprojects. 94. The annual GHG emissions (Table 11) from consuming coal, natural gas, petrol, diesel, and electricity in this project are estimated as 4,226.70, 3,629.83, 35.80, 1,127.33, and 37,229.76 ton CO2e by multiplying their conversion factor, respectively. Those are estimated - based on the IPCC guidelines (IPCC, 2006). 95. In addition to GHG emission from consuming fossil fuels, these livestock subprojects are also releasing non-CO2 greenhouse gas, such as CH4 and N2O, which is also an important GHG contributing to global warming. The estimated non-CO2 GHG emission from livestock subprojects are shown in Table 9. The total annual non-CO2 GHG emission is estimated to 10,763.79 ton CO2e for this project, in which contributions from swine, cattle, and chicken are estimated as 6,482.0, 3,528.38, and 753.39 ton CO2e, respectively. The global warming potentials used for CH4 and N2O are 28 and 265, respectively. The estimation is done based on guidelines of provincial greenhouse gas inventories (GPGGI, 2011). Table 9: Estimates of GHG Emission by the Livestock Subprojectsa Enteric Manure Manure fermentation management management methane methane N2O Methane emission emission emission emissio N2O GHG Annual factors factors (kg factors (kg n (ton emission emission average (kg CH4 CH4 head-1 N2O head-1 CH4 yr - (ton N2O (ton CO2e population head-1 yr -1) yr -1) yr -1) 1) yr-1) yr-1) Swine 36,939.7 1.0 3.12 0.227 152.19 8.38 6,482.02 (head) Cattles 1,993.2 52.9 2.82 0.794 111.06 1.58 3,528.38 (head) Chickens 353,712.3 ---- 0.01 0.007 3.53 2.47 753.39 (head) Total 10,763.79 a The methane emission factors from Enteric fermentation and mature management and N2O emission factor from mature management are referred to Tables 3.14,3.18 and 3.20 in GPGGI (2011).

96. The major mitigation action in the project implementation is revegetation. This will contribute to GHG reduction by carbon sequestration from planting fruit trees and plants. The areas of the revegetation include 871.96 hectares (ha) or 13,079.45 mu for Elaeagnus mollis diels at Xiangning County in Linfen, and 2.68 ha (26,857 square meters [m2] for factory tree planting). Next, we will give a rough estimate of carbon sink capacity of these tree plantations. The calculation method of carbon sinks refers to subsection 4 in chapter 4 of the IPCC guidelines (IPCC. 2006). Those will reduce GHG emission by 10,476.44 ton CO2e annually. The calculation process is described as follows.

Firstly, annual increase in biomass carbon (C) stocks due to biomass growth CG is calculated by the following equation:

CG = A ∙ GW ∙ (1 + R) ∙ CF where: CG=annual increase in biomass carbon stocks due to biomass growth A=area of revegetation, here unit is ha.

GW=average annual above-ground biomass growth, here GW=5.0 ton d. m. ha-1 yr-1

R=ratio of below-ground biomass to above-ground biomass, here R=0.39 ton d. m. (tonne d. m.)-1 CF=carbon faction of dry matter (d.m.), CF=0.47 ton C (ton d. m.)-1

Here, GW, R and CF use the values of Asian temperature mountain system of forest plantations in Tables 4.3, 4.4 and 4.10 of (IPCC, 2006).

Secondly, annual increase in carbon stock is converted to units of CO2 emission by multiplying the carbon change by -44/12. According to the above progress, the

conversion factor is estimated to 11.978 tons CO2e per ha. It can be estimated trees and

plants subprojects will achieve 10,476.44 tons CO2e of carbon sink per year.

Table 10: Estimates of GHG Emission by the Trees and Plants Subprojects Annual Average Conversion GHG Emission a Area (ha) Factor (ton CO2e yr) Elaeagnus 871.96 -11.978 -10,444.34 mollis diels factory tree 2.68 -11.978 -32.10 planting Total -10,476.44 a Refer to Baidu Wenku , in which the conversion factors are based on IPCC (2006) and Chinese caloric value of various energy sources.

97. In summary, this project will generate an annual net GHG emission of 46,536.77 ton CO2e per year, which is less than ADB threshold of 100,000 tCO2e per year. Based on our calculations, we conclude that the proposed project is a complete low-carbon project. Table 11: Estimates of GHG Emission and Carbon Sequestration by the Project GHG Reference for Conversion Emission Conversion Total Factor (tCO2e) Factor a Coal use (ton/yr) 1,718.17 2.46 4,226.70 IPCC, 2006 b natural gas use(‘000m3/yr) 1,736.76 2.09a 3,629.83 IPCC, 2006 c Fuel oil use (ton/yr) 14.98 2.39 35.80 IPCC, 2006 d Diesel use (ton/yr) 305.51 3.69 1,127.33 IPCC, 2006 e Net of Electricity use (‘000 kWh/yr) 29,879.42 1.246 37,229.76 GPGGI, 2011 f Livestock 10,763.79 GPGGI, 2011 Total annual emissions before sequestration 57,013.21 g Revegetation (ha/yr) 874.64 -11.978 -10,476.44 IPCC, 2006 Total annual emission after sequestration 46,536.77 a Refer to Baidu Wenku , in which the conversion factors are based on IPCC (2006) and Chinese caloric value of various energy sources.

G. ACCOUNTING CLIMATE FINANCE 98. The total climate finance of this project is estimated to cost $12.8 million and $5.9 million for adaptation and mitigation, respectively to which $8.0 million and $3.9 million are from the ADB fund (Table 12). Table 12: Climate Finance Accounting for All Subprojects Number of Adaptation Mitigation Adaptation Mitigation Subprojects subprojects Total ($M) Total ($M) ADB ($M) ADB ($M) Livestock and poultry 6 2.65 1.57 Orchard 2 5.89 5.89 3.91 3.91 Mushroom and Vegs 4 1.88 1.16 Food processing 5 1.98 1.00

Number of Adaptation Mitigation Adaptation Mitigation Subprojects subprojects Total ($M) Total ($M) ADB ($M) ADB ($M) Market whole sale 2 0.43 0.33 Total 19 12.83 5.87 7.96 3.91

99. In accounting climate finance, it is ideally based on the cost for each recommended adaptation and mitigation measures. However, the current FSRs are not costing to such level of details yet. Based on their experiences in similar projects,1 the DI advised that it is estimated that 5% of construction and equipment costs are attributed to adaptation measures for animal and poultry production projects. Adaptation measures include temperature reduction, water saving measures adopted in construction works, relevant equipment and other adaptation measures. Mitigation measures include upgraded insulation and adopting energy saving equipment as well as manure processing systems including biogas and manure fermentation. The total investment to those enterprises is estimated at $2.65 million for adaptation, in which $1.57 million is from the ADB fund for adaptation and mitigation respectively. 100. The tree planting related activities of orchard subprojects are considered as dual benefit climate finance investment. The total climate finance investment for those revegetation activities is estimated at $11.77 million of climate finance, in which ADB investment is $7.82 million, each 50% of the ADB investment is accounted for adaptation and mitigation respectively. 101. For mushroom and vegetable production subprojects, major construction works are building plastic green houses, which are much simpler structures than those animal houses. Based on their experience in similar project, 2 the DI estimated the cost of recommended adaptation measures is slightly lower than those animal production projects, whilst similar costs for the recommended mitigation measures. Therefore, it is estimated that 4% of the construction and equipment investment are attributed to adaptation measures. The total investment to those enterprises is estimated at $1.88 million for adaptation, in which $1.16 million are from the ADB fund. 102. For the climate finance of food processing it is estimated at 5% of construction and equipment costs are attributed to adaptation and mitigation respectively. However, only 2% of the investments to cold storages of those projects are accounted as adaptation investment. The total investment to those enterprises is accounted for $1.98 million for adaptation, in which $1 million are from the ADB fund. 103. For the climate finance of agro-product wholesale markets is accounted that 5% of construction and equipment costs are attributed to adaptation and mitigation respectively. Similar to food processing, only 2% of the investments to cold storages of those projects are accounted as adaptation investment. The total investment to those enterprises is accounted for $1.98 million for adaptation, in which $1 million are from the ADB fund.

1 Reference projects included the DI designed 1) Livestock Reproduction and production project for the Fengxu Agriculture and livestock Ltd Co of Datong City; 2) Beef production industry development project for Heshun County; and 3) Yuxian beef cattle production project. 2 Commercialised Mushroom Production Project of Jiaocheng Hongji Mushroom Production Ltd Co.

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