Analyze

This book provides a comprehensive overview of the climate hazards facing Vietnam. Chapter 3 in particular details the effects of climate change on the coast of Vietnam, which is relevant to the Vietnam case study and can serve as a reference for coastal climate hazards that intersect with local industrial hazards. The text notes the effects of the region’s topology—mountainous, with a long coastline—on the types of climate hazards experienced in the country in recent decades. The text describes 6 coastal provinces in North Central Vietnam and 15 provinces in the Northern mountainous region (37). Coastal precipitation, storms, flash floods, droughts, coastal erosion, and landslides affect the agriculture, aquaculture, forestry, industry, and tourism sectors, along with the dense local population. Most of the coast is expected (via climate modeling for different RCPs) to see an increase in rainfall this century. Section 2.1.3: Natural Hazards and Section 2.1.4: Climate Change Vulnerability are quoted extensively below.

“Landfalls of storms usually accompanied by high tide and heavy rain result in long periods of rain and floods. The flood season in Central Vietnam lasts from June to October. Along the rivers between Quang Binh and Binh Thuan, the flood season lasts from September to December. The Central region has short and steep rivers with high debits. Dike systems in this region are relatively low or incomplete. 8-meter-high floods not only occur along the main streams but also spread over the floodplains (Le et al. 2012).” (43)

“Storms moved southward in recent years, though it is widely expected that because of the increasing temperature, the North will face more storms in the near future. Also the intensity of the storms is expected to increase, resulting in more wind and more intense precipitation (CCFSC 2001; IPCC 2007). In particular, more intense storms, representing in more threats to people’s lives, livelihoods, infrastructure, and agriculture, are forecasted.” (43)

“In 2009, storm Ketsana affected provinces along the Vietnamese Central coast, killing 163 people and causing over 600 million $USD of damage (CCSFC 2010)...In 2010, storms and other natural hazards killed or caused missing 173 people. 168 others were injured in October 2010 (GSO 2014)...In 2012, the South China Sea faced 12 storms, of which 4 directly affected Central coast…In 2013, Central Vietnam was hit directly by consecutive storms. The Wutip storm in September 2013 damaged over 1000 houses (Vietnam NCHMF 2013). Over 70,000 people in vulnerable areas were moved to shelters along the central coastline (Al Jazeera America, accessed November 22, 2013). In November 2013, the Haiyan storm forced over 800,000 people to evacuate. Storm Nari in November 2013 destroyed about 12,000 houses in 7 central provinces (The Weather Channel, accessed November 22, 2013)...In 2016, six tropical depressions and ten storms affected the Vietnamese Central coast. Six storms and one tropical depression directly impacted the land…In September 2017, Central Vietnam was hit by the Doksuri storm. Over 100,000 people were evacuated, 4 people died, and 10 were injured. The storm Doksuri caused heavy rains and floods all over the provinces in the Vietnamese Northern Central coast. Thousands of houses were damaged or destroyed. More than 50,000 houses in Ha Tinh, Quang Binh, Quang Tri, and Thua Thien Hue provinces were damaged. Quang Binh People’s Committee reported that about 200,000 houses were flooded or submerged, 5000 lost their roofs and 20 collapsed (updated news on Vietnamnet website, accessed on 15 September 2017).” (43-44)

“By 1996, over 2000 square kilometers of the Vietnamese coast was estimated to be at risk for annual floods. Flood damage is expected to worsen if the daily rainfall increases by 12–19%. …Drought intensified as a result of the increased variation in rainfall and evapora- tion (3% along the coast and 8% inland by 2070). The effect is triggered by rising temperatures (MONRE 2016)...Landslides in the Northern Central coast are often triggered by heavy rains and storms, resulting in large amounts of sliding material downhill. Riverbank erosion is widely spread in this region, in particular during the rainy season. The lower part of the rivers is severely affected. Coastal erosion goes up to 10 meters annually, which worsens with the sea level rise of the recent years.” (44)

“The vulnerability of agriculture in the districts depends on extreme climatic events. Most districts in the Ha Tinh, Quang Binh, and Quang Tri provinces have a high exposure because they suffer storms, floods, and drought. Districts with a high exposure index show also a high vulnerability. For example, the Cam Xuyen district (Ha Tinh province) with the highest exposure in the region (0.57) represents the highest vulnerability (0.56). This underlines that the agriculture in the region with traditional methods mainly depends on the weather conditions.” (45)

“Provinces of the Vietnamese Northern Central coast have a long coastline, many estuaries, lagoons, and bays (Le et al. 2012). Aquaculture is promoted and gradually became a leading economic sector. Shrimp, crab, seahorse, holothurians, and Gracilaria asiatica are the main products. Aquaculture farmers, including both fish and crustaceans, are water-dependent and influenced the quality of coastal resources. Higher temperatures and more droughts affect the yields. This is ongoing as the yields of the spring crops declined drastically during recent years (GSO 2014). Aquaculture along the Vietnamese Northern Central coast shows high vulnerability to climate change: the vulnerability index ranges between 0.33 and 0.73. The highest value (0.73) is for the Gio Linh (Quang Tri province), while the lowest value (0.33) applies to the Thach Ha district (Ha Tinh province). Aquaculture shows a high vulnerability in majority of the districts (25/28), while only three districts (Sam Son, Cua Lo, and Thach Ha) report a moderate vulnerability. The exposure and sensitivity index of aquaculture are the highest of all sectors considered. The districts in the Quang Tri and Thua Thien Hue provinces show the highest vulnerability because of its high sensitivity (Fig. 2.3).” (46) This is section 2.1.4.2: Vulnerability of Aquaculture

“The majority of economic zones locate near the shoreline. This makes them vulnerable to climate change hazards. However, industry is less affected as compared to agriculture, forestry, and aquaculture. The industrial zones resist the effects of natural disasters easier. This explains that the industry is moderately vulnerable to climate change: this relates to the moderate qualification of exposure, sensitivity, and adaptation capacity of most of the districts. The high vulnerability in seven districts is related with the high exposure. Industrial plants in new areas which do not offer solid constructions and modern equipment are more at risk from natural hazards than other areas.” (48)

“The Vietnamese Northern Central coast shows its uneven distribution of the population, which reflects a difference between the eastern coastal plains and the western hilly and mountainous areas (Le et al. 2012). Most of the population is located along the national road no. 1A and in the eastern coastal plain, which accounts for over 70% of the population and which is more dense than the national average. Hilly and mountainous areas in the West account for 60% of the area, but only 30% of the people live in this region. Consequently, the average density in the western moun- tains of the country is only about 10–50 people per square kilometer (GSO 2014)...Natural hazards damage habitats of locals in hilly and mountainous areas as well as coastal areas, while storms and flash floods impact both uplands and lowlands. These latter are affected by a combination of storm, floods, sea level rise, and coastal erosion. This explains why the region has a moderate to high vulnerability of the population to climatic change.” (49)

“Currently, the government invests in developing marine tourism, ecotourism, speleo-tourism, and heritage tourism along the Vietnamese Northern Central coast. However, climate change affects the cultural monuments. Also the water supply in the region is under stress; biodiversity will decrease, and the hot season is expected lasting longer. All this will have a significant impact on the assets and the revenue from tourism. Tourism experiences the lowest vulnerability as compared to the other sectors in the region due to its low exposure.” (51)

“The likely effects of climate changes are most tangible in this province [Ky-Anh coast]. They include: 1. The average temperature during the period 2000–2010 increased by 0.6 °C as compared to the period 1970–1980. 2. Extreme weather events: Unusual cold periods (the spring of 2009 was the cold- est of the last 40 years) alternate with heat waves (in July 2010, the province experienced during 10 consecutive days temperatures over 40 °C); storms are frequently accompanied by heavy rains (the 2010 flood lasted for more than 20 days). 3. Changes in the frequency, the timing, and the intensity of the tropical storms are part of the changing weather profile. While traditionally storms occurred during the period September–November, the storm season now extends from August to December. Floods occur from April to December. They become stronger and faster, with more peak events and more devastating impacts (IPONRE 2009)...In short, prolonged periods of high and low temperatures, drought, sea level rise, storms heavy rains, and (sudden) floods are considered the main weather drivers affecting the livelihood of these communities in coastal Ha Tinh. Consequently, Ha Tinh faces four main problems: 1. Changes in water supply: Drinking water supply and irrigation are critical all over the province. In 2010, 27% of the agricultural land was irrigated. The provincial policy goal is irrigating 70% of the fields. Also by 2010, 70% of the population had access to piped water. The daily per capita consumption ranges from 80 to 100 liters on average. The policy goal is supplying 100% of the urban and 80 to 90% of the rural population with safe drinking water (HTG 2013). The increasing pressure on the water supply hampers realizing these goals. 2. Changing land use and urbanization: By 2001, 10% of the land in Ha Tinh was urban area, while the remaining surface was rural. By 2010, the urban land cov- ered 15% of the province, while the rural area decreased to 85% (HTG 2013). The figures illustrate the conversion of agricultural and bare land into urban areas. Consequently, the area is also increasingly affected by the urban heat island effect. 3. Progressing shoreline erosion: Depending on the inclination of the beaches, Ha Tinh loses beaches at a rate of 0.2–15.0 meters per year. 4. Changing livelihoods: Both urbanization and the changing climate affect the way of life in Ha Tinh. Especially farmers, aquaculturists, and fishermen change their habits, adapting to the increasing storms. Urbanization is associated with changes in consumption lifestyles, the size of the families, the ways of commuting, the gender roles, and the time residents spent at home.” (64)

The authors review literature on the datafication of health, which they identify as the way through which health has been quantified on a number of different scales and registers. They focus primarily on the datafication of health in clinical health care and self-care practices, rather than medical research and public health infrastructures. From this literature, they identify three key themes: datafied power (the ways through which data permeates and exerts power over forms of life), living with data (focused on datafication as an intimate form of surveillance, and a technology of the self), and data-human mediations (which emphasizes the nonhuman elements mediating datafication dynamics and experiences—such as algorithms, data infrastructure and data itself).

In examining literature on datafied power, the authors acknowledge a lack of scholarship on understanding data and datafication in terms agency, rather than simply power and domination. For instance, data is sometimes mobilized in “creative and even pioneering ways (Rapp 2016)” (265).

They describe literature on “living with data” as increasingly focus examining the social, narrative, and affective dimensions of data practices and experiences (e.g. work on the “Quantified Self,” a group seeking self-knowledge through numbers – a form of relationality that might be described as datasociality). Some scholars have argued that data can render “‘feelings and problems more tangible and comparable” (Sharon & Zandbergen 2016, p. 11)” (267). Some have also acknowledged as well a “curious resonance between the vision of empowered, resisting individuals that many ethnographers of self-tracking celebrate, and the rhetoric of consumer empowerment found in discourses of digital health (Schull 2017, Sharon 2017)” (267).

The literature on data-human mediations emphasizes the agency, liveliness and/or performativity of nonhuman elements—essentially, how they structure and shape the possibilities for action. For instance: “as social expectations of normality and health become embedded in tracking devices’ target numbers, presentation of scores, and gamified incentives (Depper & Howe 2017, Whitson 2013), a “numerical ontology” comes to suffuse everyday practices and “the ways in which people relate to their own bodies” (Oxlund 2012, p. 53; see also Jethani 2015, p. 40)” (269). Perspectives and action can be enabled or disabled by wide variety of factors: the design and performativity of data technology software (user interface, operational and analytical algorithms), hardware (devices, sensors), data itself (as illustrated in different ways), and data infrastructures (labs, data centers, serve and cloud storage, and networks that organize how data is stored and circulated). An analytically constructive focus in this literature has emerged by applying the concept of “assemblage” as a way of tracing how data moves: “where it flows, where it finds impasses, how algorithms act on it along the way” (270).

Lastly, the authors identify scholarship on “data activism” as an emerging focus on exploring how data technology capacities might be employed to promote social justice, collective action, and political participation, as well as to challenged dominant norms and ideologies: “Individual self-tracking data, for instance, can have social and political potential when it is pooled to identify health inequalities, collective environmental exposure, or disparities in quality of life (Gabrys 2014).” (271)

The common nessesaties that arent given to children in the essex county ultimately handicap the community around them. All the issues directly influence the parents, and the state; because with all of these issues are things the government has a level of control over. By not trying to findd solutions so child poverty the state continues to have to fun child care, enrichment programs that are costly which we current cant afford. The quality of these programs slowly does down until they become another vulnerability themselves