Climate Change Impacts and Adaptation in Saint John, New Brunswick, 2008

AC AP S AINT J O HN

C LIM ATE C HANGE IM PAC TS & AD AP TATIO N IN S AINT J O HN NE W B R U NS W IC K ,20 0 8

Climate Change Impacts & Adaptation Saint John, New Brunswick, Canada

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Atlantic Coastal Action Program Saint John, 2008.

Author: Ian Reeves, MSc, Climate Change Specialist, ACAP Saint John

Advisor: Tim Vickers, MSc, Executive Director, ACAP Saint John

For more information, contact: Atlantic Coastal Action Program Saint John 76 Germain Street PO Box 6878, Station A Saint John, NB E2L 4S3 Canada 506.652.2227 www.acapsj.com

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Acknowledgements This project would not have been possible without the generous financial support provided by a grant from the New Brunswick Environmental Trust Fund.

ACAP Saint John would like to acknowledge the contributions of a number of people who helped contribute to this report through meetings with ACAP staff and providing data. We are grateful for their time and insight into this report. We also thank those who provided data and analysis for the reports.

Stephen King, Environmental Management Services, Halifax Regional Municipality Gary Lines, Climate Change Meteorologist, Environment Canada, Atlantic Region Kyle McKenzie, Climate Change Specialist, Environment Canada, Atlantic Region Wayne Barchard, ACAP Window, Environment Canada, Atlantic Region Lucie Vincent, Climate Researcher, Meteorological Services, Environment Canada Yves Leger, Geographic Information Systems, Planning and Development, City of Saint John

Final editing was provided by Tim Vickers and Gay Wittrien of ACAP Saint John

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Table of Contents 1. Introduction

1

Overview

1

Climate Change

2

Climate Impacts

9

Climate Change and Cities

12

Climate Change and Saint John

14

2. Saint John Climate: Historical trends and projections

15

Introduction

15

Methods

16

Historical Analysis

16

Projected Future Climate Scenarios

17

Results

19

Trends in Historical Temperature Records

19

Trends in Historic Precipitation Record

22

Projected Future Temperature and Precipitation Scenarios

24

Discussion and Conclusions

27

Temperature

27

Precipitation

28

Conclusions

29

3. Sea Level Rise in Saint John

30

Introduction

34

Methods

34

Historic and Projected Changes in Sea Level

34

Storm Surge Modeling

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Results

36

Historic Tide Record

36

Projected Changes in Sea Level

36

Storm Surge

37

Discussion and Conclusions

39

Sea Level Rise

39

Storm Surge

40

Conclusions

41

4. Adaptation

43

Introduction

43

Vulnerability Assessments

46

Adaptation Options

51

Education

52

Coastal/Inland Flooding

52

Water Supply

53

Health

54

Recommendations

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5. Literature Cited

58

6. Appendices

65

Appendix A

65

Appendix B

67

About the Author

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List of Figures Figure 1.1 – Timeline of selected major events in the history of climate change and global warming.

4 Figure 1.2 – Overview of the components of the climate system, including their processes and interactions. (Source: Le Treut et al. 2007)

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Figure 1.3 – Changes in the concentrations and radiative forcing by a) carbon dioxide, b) methane and c) nitrous oxide over the last 20,000 years as reconstructed from ice core and direct atmospheric measurements. Figure d) shows the rate of change for the combined radiative forcing of all the greenhouse gases, with the inset showing a higher resolution detail of a decrease in carbon dioxide reported in the ice records from the 1600’s. (Source: Solomon et al. 2007) 6 Figure 1.4 – Changes in global temperature demonstrated through A) the instrumental temperature record of the last 150 years and B) reconstructed temperature records over the last millennia where the black line represents the instrumental record. (Source: Rhode 2007) 7 Figure 1.5 – Global average sea level rise 1990 to 2100 as developed from seven atmosphere ocean general climate models taking into account thermal expansion and land ice changes and adding the effects of permafrost changes and sediment deposition. Lines indicate the average of all seven climate models for each of the emissions scenarios noted in the legend (see appendix for emissions definitions).

Please note that these projections do not take into account the changes in ice – dynamic changes in the Antarctic and Greenland ice sheets. (Source: Folland et al.

2001) 8 Figure 2.1 – Trends in the mean annual A) maximum and B) minimum temperature from Saint John, NB from 1895 to 2006. Baselines are set at the mean values for the entire record.

20 Figure 2.2 –Trend in the mean of the maximum summer temperature in Saint John, NB from 1895 to 2006. Baseline is set at the mean value for the entire record.

21 Figure 2.3 – Trends in the total annual precipitation (mm) from Saint John, NB from 1895 to 2006 and a five year moving average from 1897-2001. Values calculated from the sum of all daily precipitation values.

22 Figure 2.4 - Projected changes in A) maximum and B) minimum temperature in Saint John, NB for three future tri-decade periods [2020 (2010-2039), 2050 (2040-2069) and 2080 (2070-2099)]. Results are SDSM models using output from the Canadian Climate Model (CGCM2) and the UK Hadley Model (HadCM3) using the B2 scenario as described by the IPCC (2000).

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Figure 2.5 – Projected future % change of total annual precipitation in Saint John, NB for three future tri-decade periods [2020 (2010-2039), 2050 (2040-2069) and 2080 (2070-2099)]. Results are SDSM projections from using output from the Canadian Climate Model (CGCM2) and the UK Hadley Model (HadCM3) using the B2 scenario as described by the IPCC (2000).

25 Figure 2.6 – Comparison of historical precipitation return periods for a 24 hour precipitation event with projections for future return periods. The time periods correspond to the following dates; Historical (1961-1990), 2020s (2010-2039), 2050s (2040-2069) and 2080s (2070-2099) Projections come from SDSM models with data provided by A) the Canadian Climate Model (CGCM2) and B) the UK Hadley model (HadCM3) run using the B2 scenario as described by the IPCC (2000).

26 Figure 3.1 – Areas of the Canadian coast that are currently submerging Source: Shaw et al. 1998.

31 Figure 3.2 – Sensitivity of the Atlantic coasts to sea level rise, with the inset showing a closer view of the region around Saint John and the Bay of Fundy. Red zones indicate high risk, Yellow indicates moderate risk and green indicates low risk. Source: Shaw et al. 1998.

33 Figure 3.3 – Observed sea level change from the historic tide gauge record from Saint John, NB. Baseline is set at the mean for the historical record (4.369 m Datum). 36 Figure 3.4 - Mean sea level changes in Saint John, NB. The solid blue line indicates a reconstruction of the annual mean sea level from the tide gauge record. The dashed blue line indicates projected relative sea level rise (SLR) as a result of crustal subsidence and the solid green line indicates the projected sea level change from the combined values of relative SLR (crustal subsidence), actual SLR (thermal expansion) and tidal amplification. The baseline value is set at the mean for the historical record (4.369 m Datum).

37 Figure 3.5 – Flood risk map for an approximately 1 m storm surge for key areas within the City of Saint John in the year 2100 assuming sea level rise of 0.7 m. Areas within the yellow for Inner Harbour, Saint’s Rest Marsh and Red Head Road are flood lines a 1 m storm surge landing at MHHW taking into account a 0.7 m sea level rise. The Marsh creek flood map is from Drisdelle (2006) based on LiDAR altimetry data showing flood lines for a 4.6 m sea level in the year 2100, which roughly corresponds to 8.8 m (Chart Datum) 38 Figure 3.6 – Comparison of the former extent of the Great Marsh and the resulting flood levels from a storm surge in the year 2100 that results in a 4.6 m water level (orthometric).

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Figure 4.1 – Examples of locations in Saint John that are currently prone to inland flooding during heavy rain events. The top two pictures were from precipitation events in the winter of 2008 and the bottom two pictures were from precipitation events in the summer of 2006.

48 Figure 4.2 – Examples of some of the areas within the city that will become increasingly vulnerable to storm surge as a result of the impacts of sea level rise over the next 100 years.

50 Figure 4.3 – Simple framework outlining the major steps within the adaptation process.

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List of Tables Table 1.1 – Definitions for key terms necessary to understand the climate change and global warming. Definitions adapted from the Pew Centre Glossary (www.pewclimate.org), the US Environmental Protection Agency Glossary of climate change terms (www.epa.gov) and Environment Canada (www.climatechange.gc.ca).

3 Table 1.2 – Examples of the potential impacts of climate change on various sectors in Canada.

10 Table 1.3 – List of major cities that implemented climate change programs involving assessments of climate change impacts and measures to reduce the vulnerability of the city.

13 Table 2.1 – Trends in the annual and seasonal maximum and minimum temperatures in Saint John from 1895-2007. R2 refers to the closeness of fit, E refers to the estimated standard error, and p indicates statistical significance.

19 Table 2.2 – Differences in the mean maximum and minimum temperatures in Saint John, NB before 1950 and after 1950.

21 Table 2.3 – Historic trend data for five year moving averages of total annual and seasonal precipitation for the City of Saint John from 1897 to 2005. R2 refers to the closeness of fit, E refers to the estimated standard error, and p indicates statistical significance.

23 Table 2.4 - Historic annual and seasonal trend data for days with high precipitation, low precipitation and no precipitation in Saint John from 1895 to 2007. R2 refers to the closeness of fit, E refers to the estimated standard error, and p indicates statistical significance.

23 Table 3.1 – Summary of sea level rise projections for the Saint John region, broken down into additive components. MSL – Mean sea level; MHHW – Mean higher high water mark; PSHW – Perigean spring high water mark.

35 Table 4.1 – Summary of different types of adaptation and the method of differentiation.

(Source: Burton 2008) 44 Table 4.2 – Examples of weather related disasters in Canada and estimated cost of the damages.

45 Table 4.3 – Key sectors for climate change impact assessments, as identified from assessments carried out by various other cities during the development of adaptation strategies.

51 Table B2 – Current provincial and territorial strategies, initiatives and best practices for addressing impacts and adaptation to climate change.

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1. INTRODUCTION Overview A recent consensus among the scientific community has strongly suggested that climate change is occurring (Oreskes 2004) and that human activities are influencing the global climate (National Academy of Sciences 2001, IPCC 2007, Kerr 2007). This contention raises concerns as to the potential effects that a changing climate could have on municipalities around the world. Regardless of future changes in anthropogenic greenhouse gas emissions, many cities will face increasing socioeconomic and physical risks resulting from increasing temperatures, changes in precipitation patterns, accelerated sea level rise and the trickle down effects associated with the above.

These effects will have significant implications, both positive and negative, on the built, natural and human systems associated with both urban and rural communities (Medhi et al. 2006). This report presents an assessment of the vulnerability of the City of Saint John, New Brunswick, Canada to the risks associated with climate change, and explores adaptive strategies that could be implemented to reduce the negative impacts of future climate change.

Coastal cities are at particular risk from accelerated sea level rise and even greater risk from severe weather damage (storm surges, hurricanes, etc.). The Geological Survey of Canada has concluded that more than 7000 km of Canadian coastline are at risk from rising sea level, including large portions of the Maritime provinces (Shaw et al. 1998). Many coastal municipalities will become increasingly vulnerable to the socio-economic risks of climate change, including property loss, loss of city infrastructure, and increased flood risks. Although many Canadian municipalities have taken a strong leadership role in promoting greenhouse gas reduction (for more info see the Federation for Canadian Municipalities Partners for Climate Protection Program, www.fcm.ca), it is only recently that municipalities have begun to address the potential impacts of climate change and the challenges of adapting to a changing environment. Global climate change and its various associated issues are the current subject of considerable scientific research; however, there is still much that is not understood. Climate prediction models and historical analyses concentrate heavily on 1

global trends and averages, leaving numerous questions concerning the regional and local impacts of climate change. Predicting local impacts of climate change is complex and difficult, due the inherent variability associated with local weather patterns, but is necessary in order to both evaluate the future risks municipalities are likely to face, and to identify what adaptive strategies could be implemented.

This report presents an overview of the impacts that climate change is likely to have on Saint John over the next century, and how well adapted the City is to deal with these impacts. The first chapter presents an analysis of historic climate and tide records to detect past trends and develop projections of trends during the next century.

The report then utilizes these projected trends (especially as they pertain to sea-level rise and storm surges) to identify high risk (i.e. vulnerable) areas in the City and to predict what City infrastructure is likely to be affected. The vulnerability analysis is then used to evaluate the adaptive capacity of the City, and to subsequently present strategies to help the City prepare and adapt to the potential effects of climate change.

Examples of tools and resources, developed in other municipalities, are also provided.

The overall objective of this report was to compile all of the available information on climate impacts and adaptation and present it in a format that was applicable to the City of Saint John. It was intended that this approach to highlighting sustainable and realistic adaptive strategies could help Saint John face the challenges of climate change.

Climate Change Contrary to popular belief, the idea that humans are contributing to global warming has been around for a long time (Figure 1.1), although it is only in more recent times that climate change is being recognized as an imminent threat to the global community. Global warming and climate change has been the subject of debate for numerous years, but increasing supporting evidence has led to a strong consensus among the scientific community that climate change is real and poses an imminent threat (Oreskes 2004, Arblaster et al. 2007).

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Climate change refers to changes in the long-term patterns of weather events, including annual precipitation, mean temperature, and storm frequencies. In order to understand climate change it is important to understand the difference between climate and weather (Table 1.1), as well as understanding the basics of the global climate system. The climate system is complex and comprised of numerous components including the hydrosphere (oceans, rivers and lakes), the atmosphere, the biosphere (both terrestrial and marine) and the land surface (Figure 1.2). How these components interact with each other (e.g. the hydrologic cycle, the carbon cycle and atmospheric circulation) also comprise a large part of the climate system. Since the industrial revolution, humanity’s increasing footprint on the climate system has added new complexity through rapidly increasing emissions of greenhouse gases and the alteration of the land surface and biosphere for forestry, agriculture and urban development.

Table 1.1 – Definitions for key terms necessary to understand climate change and global warming. Definitions are adapted from the Pew Centre Glossary (www.pewclimate.org), the US Environmental Protection Agency Glossary of climate change terms (www.epa.gov), and Environment Canada (www.climatechange.gc.ca).

Term

Definition

Climate

The long-term pattern (decades to millennia) of weather of a region (or global), encompassing weather patterns, storm frequency, temperature patterns.

The ratio of light from the sun that gets reflected by the surface if the earth to light that is absorbed/received by the earth’s surface. Unreflected light is absorbed and converts to heat that warms the planet.

Processes that remove more CO2 from the atmosphere than they emit, such as forests and ocean habitats.

A computer model incorporating the basic dynamics and physics of the global climate system and interactions between the major components (ie; atmosphere, oceans, land surfaces) used to simulate climate variability The natural process that allows radiation from the sun to enter our atmosphere, and prevents the infra-red radiation (heat) to escape from the lower atmosphere and land surfaces to keep the planet warm and hospitable Gas that absorbs infra red radiation in the atmosphere and contributes to heating the planet. Examples include; water vapour, carbon dioxide, methane, nitrous oxide, and chlorofluorocarbons.

The change in balance between the radiation (heat) coming in to the atmosphere and radiation going out of the atmosphere, positive forcing results in warming of the system and negative forcing results in a cooling of the system.

The removal atmospheric CO2 through biological (eg; trees, plants) or geological processes (eg; storage in underground reservoirs) Expansion of a substance as a result of the addition of heat. This is particularly relevant with respect to the expansion of the world’s oceans as global temperature increases Describes the short-term (hourly, daily) state of the atmosphere and can be drastically different over short distances or period of time.

Albedo

Carbon sink General Circulation Model Greenhouse Effect

Greenhouse Gas

Radiative Forcing

Sequestration Thermal expansion Weather

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1859 -Discovery of greenhouse gases (J. Tyndall)

1800

1850

1800 - Beginning of Industrial Revolution

1934 - Analysis of data from weather stations across the USA show warming trend since 1865 (US Weather Bureau) 1957 - Discovery that the ocean 1920-1925 will not readily Opening of Texas absorb surplus and Persian Oil CO2 (R. Revelle) Fields

1900

1896 – First calculation of human influence on global warming as a result of CO2 emissions (S. Arrhenius)

1979 - World Climate Research Programme launched 1971 - Study of Man’s Impact on Climate (SMIC) predicts potential danger of rapid and serious global change caused by human activities

2001 - 3rd IPCC report states that global warming is very likely

1997 - Delegates 1985 - Villach from 160 conference of countries agree climate scientists to the Kyoto recommends Protocol global treaty

1950

1938 - Theory that CO2 greenhouse warming is occuring and could lead to a self sustaining warmer climate (G.S. Callendar)

2000

1960 - Accurate measurement of CO2 in the atmosphere shows a rise of 315 ppm/year (C.D. Keeling)

1976 - CFC’s, methane and ozone are identifed as additional greenhouse gases

1970 - First Earth Day

1992 - Earth Summit in Rio de Janeiro establishes United Nations Framework on Convention on Climate Change

1988 - Establishment of the IPCC and the Toronto conference on the changing atmosphere

2005 - Kyoto treaty goes into effect, signed by all industrial nations except the USA and is the warmest year on record

Figure 1.1 – Timeline of selected major events in the history of climate change and global warming.

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Global climate change occurs when the amount of energy (i.e. heat) within the climate system changes. Warming can occur from an increase in heat introduced into the system or from a decrease in the amount of heat released from the climate system.

Figure 1.2 – Overview of the components of the climate system, including their processes and interactions. (Source: Le Treut et al. 2007) Water vapour is the most abundant greenhouse gas (responsible for roughly 60% of the greenhouse effect), however the greenhouse gases responsible for the other 40% of the greenhouse effect are of greatest concern in terms of climate change as many of these other greenhouse gases are byproducts of our fossil fuel based economy. Concentrations of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) are significantly higher than pre-industrial values found in ice core data (Figure 1.3), with CO2 increasing by ~ 35%, CH4 increasing by over 100%, and N2O increasing by ~ 18% since the late 1700’s (Solomon et al. 2007). Increases in greenhouse gases lead to an increase in the amount of solar energy trapped within the atmosphere and contribute to the increase in global temperatures detected over the last decade.

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Figure 1.3 – Changes in the concentrations and radiative forcing by a) carbon dioxide, b) methane and c) nitrous oxide over the last 20,000 years as reconstructed from ice core and direct atmospheric measurements. Figure d) shows the rate of change for the combined radiative forcing of all the greenhouse gases, with the inset showing a higher resolution detail of a decrease in carbon dioxide reported in the ice records from the 1600’s. (Source: Solomon et al. 2007) A wide range of studies have indicated that the observed changes in climate patterns cannot be explained by natural factors alone and are best explained by anthropogenic influences (Le Treut et al. 2007). The knowledge and understanding of anthropogenic influences on climate has increased substantially in recent years, and scientists have reported that there is over a 95% likelihood that anthropogenic influences on climate have a net warming effect (Solomon et al. 2007), which has contributed to the rise in global temperature detected over the last 1000 years (Figure 1.4).

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A

B

Figure 1.4 – Changes in global temperature demonstrated through A) the instrumental temperature record of the last 150 years and B) reconstructed temperature records over the last millennia where the black line represents the instrumental record. (Source: Rhode 2007) Any change in global climate could have cascading and far-reaching ecological, environmental, social and economic effects, and some of these impacts are already being felt (see Kerr 2007). Slight changes in global temperature can activate feedback loops and stimulate further changes in climate (eg; changes in severe weather patterns and shifts in precipitations and drought patterns) as well as leading to a global rise in 7

sea level as a result of thermal expansion, melting of glaciers and loss of Antarctic ice (Figure 1.5). It must be noted that most models depicting global sea level rise do not take into account changes in the ice dynamics from the Antarctic and Greenland ice sheets. Increased temperature and rising sea level are only the tip of the iceberg with respect to the impacts of global climate change. The recent IPCC report (IPCC 2007) indicates that even if anthropogenic emissions were to cease immediately, we would still experience many of the projected climate impacts. As such, it is necessary to not only mitigate greenhouse gas emissions, but adapt to the pending impacts of climate change.

Range of all emission scenarios including land-ice uncertainty

Range of all 35 emissions scenarios

Range of the averages of all 35 emissions scenarios

Figure 1.5 – Global average sea level rise 1990 to 2100 as developed from seven atmosphere ocean general climate models taking into account thermal expansion and land ice changes and adding the effects of permafrost changes and sediment deposition. Lines indicate the average of all seven climate models for each of the emissions scenarios noted in the legend (see appendix for emissions definitions).

Please note that these projections do not take into account the changes in ice – dynamic changes in the Antarctic and Greenland ice sheets. (Source: Folland et al.

2001) 8

Climate Impacts Evidence is growing that the increases in temperature (observed both globally and regionally) over the past few decades are having significant effects on a diverse set of physical and biological systems. Numerous regional changes in biological and physical processes, such as changes in rainfall intensity, shrinking of glaciers, changes in flowering dates of trees and shifts in lake ice freeze and break-up dates have been linked to climate change and documented in the IPCC’s Third Assessment Report (IPCC Working Group II 2001). It is difficult to identify clear climate impacts, as many impacts have multiple causal factors, but significant associations between regional climate change and observed changes in physical and biological systems have been identified on every continent (White et. al. 2001). More recent analyses are finding more concrete quantitative evidence of climate impacts on biological and physical systems such as, latitudinal and elevational shifts in the range of flora and fauna, shifts in spring peak discharge times, lengthening of growing seasons, earlier fish migration in streams, and warming of surface waters (Parry et al. 2007). In recent years, there has been a greater focus on impacts to the human environment and on identifying how regional climate changes will affect human infrastructure and built systems.

The impacts of climate change vary regionally and will likely have substantial repercussions within Canada (Table 1.2). The sheer magnitude of Canada coupled with its diverse geo-physical makeup, necessitates a greater emphasis be placed on understanding how climate change will affect different regions within the country. All three levels of government (Federal, Provincial and Municipal) have begun to address climate change, however much of the focus has been on mitigating greenhouse gas emissions. Reducing emissions is important and will play a critical role in determining the future climate change; however, even if emissions were stabilized within the next two years, climate change will continue due to the long residence time of greenhouse gases in the atmosphere and the lag between emissions reductions and the stabilization of temperature and ocean levels (Snover et al. 2007).

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Table 1.2 – Examples of the potential impacts of climate change on various sectors in Canada. Modified from: Lemmen and Warren 2004 Climate Change Impacts and Adaptation: A Canadian Perspective.

Water Resources

Agriculture

Forestry

Fisheries

Coastal Zone

Transportation

Human Health

Increased likelihood of severe drought and aridity in prairie regions

Changes in crop yields across the country, increases and decreases in productivity Soil degradation through erosion, chemical depletion, water saturation and solute accumulation Increased weed growth and disease outbreaks

Changes in species diversity

Decreases in Atlantic marine, southern freshwater and southern Pacific marine fisheries Increases in the Arctic marine, northern Pacific marine, and Northern freshwater fisheries

Increased coastal erosion

Changes in length and quality of construction season

Increases in health effects related to air pollution (eg; asthma, cancer, etc.)

More extensive coastal inundation and loss of coastal habitat

Supply problems to northern communities as a result of loss of ice roads and melting permafrost

Increased skin damage and skin cancer from exposure to ultraviolet rays

Increases in the outbreaks of infectious diseases, such as Giardia, west Nile Increased occupational health hazards

Reduced hydroelectric potential

Decrease in the snow cover

Northward shift of ecozones

Local extinctions will occur

Changes in food nutrient supply and predator-prey dynamic

Higher stormsurge flooding and increased coastal erosion

Reduction in mobility as a result of increased landslide and avalanche activity

Increase in forest fire activity and longer season Increased land use conflicts

Reduced growth rates and productivity of shellfish Increase in toxic algal blooms

Higher sea surface temperature

Reduced payload in some of the major shipping routes

Damage to coastal infrastructure and property loss Increased length of shipping season

Increased damage to causeways and bridges

Changes in ice freeze-up and break-up

Longer growing seasons

Increased spring flood risks

Accelerated maturation rates

Saline intrusions into aquifers resulting in loss of potable water Thinner ice cover and an increase in ice-free season and of open water

Decreased herbicide and pesticide efficacy

Changes in forest productivity

Changes in lake clarity and stratification

Possibility of growing new crops

Changes in timber supply and value

Migration of mobile species as water temperatures change

Increasing evaporation rates and decline in water levels

Increased insect damages

Increases in loss of productivity

Increased heat stress periods and associated risks

Loss of cultural resources and values

Increased risk potential from severe storms and tsunamis

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The research generated through the IPCC Working Group II has led to significant advances in climate impacts and adaptation research, with most of the research and work on climate change impacts focusing on individual sectors of the national or global economy, such as agriculture, forestry, transportation, fisheries and water resources.

The Canadian government has focused much of its research efforts on these economic sectors, but has begun assessing climate impacts on human health and well being and the expected impacts on Canada’s coastal zone (Environment Canada 1998, Natural Resources 2004). All areas of the country, as well as all economic sectors will be affected, positively or negatively, by climate change in the future. General consensus is that the majority of climate impacts will be negative and the focus of most research has been on the potential decreases in the food supply or resources at a national scale.

However, recent studies examining the integrated impacts of climate at smaller regional scales indicate that the combined impacts of sea level change, temperature change, and shifting storm patterns on infrastructure and human health may be of greater magnitude than previously thought, particularly because infrastructure and population are concentrated in urban areas (Ruth and Kirshen 2002).

An assessment of the regional impacts of climate change identified the following four key regions that are likely to suffer the most as a result of climate change; 1) coastal regions of the Atlantic Provinces, 2) the poor and agriculture dependent parts of the Prairie Provinces, 3) the Arctic regions, and 4) municipal and urban areas across the country (Chiotti 1998). Municipalities (both large and small) contain a concentration of infrastructure, including built systems (e.g. water and sewage networks), natural systems (e.g. urban watersheds), and human systems (e.g. health care) that are sensitive to changes in climate. It is at the municipal level that more effort can be directed towards integrated approaches to studying climate impacts and beginning to address the need to adapt.

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Climate Change and Cities Climate change will have severe impacts on municipalities across the country and will have a variety of both positive and negative impacts on municipal infrastructure.

Cities have been at the forefront of the climate change movement for a long time, with many cities developing comprehensive greenhouse gas mitigation strategies well in advance of any national or provincial legislation. However, there are few cities that have looked extensively at the impacts climate change will have on their city or taken steps to reduce the vulnerability of their infrastructure and residents. While mitigating greenhouse gases is extremely important, it is evident that cities will experience climate change in the future and it is vital that cities take steps to reduce the vulnerability of residents to the impacts of climate change.

Cities concentrate people, buildings, and transportation infrastructure in small areas, making them vulnerable to the effects of climate change, especially extreme weather events. Cities are built and designed on infrastructure systems and services that are very sensitive to climate, (e.g.; flood control, water supply, wastewater management, energy, and transportation) and many are interrelated (Kirshen et al.

2004). There are numerous features within modern cities that increase the vulnerability and the risks associated with climate change (e.g.; asphalt and other impermeable surfaces, combined sewers, centralized powers sources), resulting in a built environment within cities that is not only at risk from climate change, but in some cases can exacerbate the effects (Ligeti et al. 2007). Cities must account for how climate change could affect the safety, quality of life and development within their community.

Coastal cities, in particular, are at risk from the effects of climate change due to the effects of sea level rise. Sea level rise is one of the most fundamental risks for municipalities and human settlements. Approximately half of the world’s population lives near the coast and population density near the coast is about three times higher than the global average (Nicholls et al. 2007). Many coastal cities are particularly vulnerable to the physical and socio-economic risks associated with sea-level rise and the resulting change in storm surge levels. Much of the current urban infrastructure in coastal cities has been designed according to historic weather patterns and any change in storm 12

surge patterns or climate can place these at risk of damage. For example, many cities design storm water systems by examining precipitation and storm surge return periods.

Changes in climate and sea level can alter these patterns resulting in storm surge levels higher and more frequent than anticipated.

Until recently, most cities have focused on climate change strategies on mitigation, which focuses on reducing greenhouse emissions through energy efficiency, increasing public transportation, reducing urban sprawl and renewable energy programs (Ligeti et al. 2007). While mitigation is still important, it is evident that we will experience climate change effects over the next 100 years even if greenhouse gas emissions were halted today, due to the fact that these gases are already in the atmosphere and can take up to 80 years for them to dissipate in the atmosphere. Recently, a few major cities have begun to develop comprehensive climate change strategies that address the need for adaptation, and have started the process of assessing how vulnerable the cities are and what steps can be taken to reduce the risks (Table 1.3).

Table 1.3 – List of major cities that implemented climate change programs involving assessments of climate change impacts and measures to reduce the vulnerability of the city.

City London, UK

Programmes London Climate Change Partnership (in partnership with the UK Climate Impacts Programme) www.london.gov.uk/climatechangepartnership/

New York, USA

Climate Change Information Resources, New York Metropolitan Region http://ccir.ciesin.columbia.edu/nyc/

Boston, USA

Climate’s Long Term Impacts on Metro Boston (Climb Project) www.tufts.edu/tie/climb/

Halifax, Canada

Climate Sustainable Mitigation and Adaptation Risk Toolkit (Climate SMART) www.halifax.ca/Climate/index.html

Vancouver, Canada Seattle, USA

Cool Vancouver Task Force and the City of Vancouver Sustainability http://vancouver.ca/sustainability/climate_protection.htm Seattle Climate Action NOW and King County Climate Change www.seattlecan.org/ http://dnr.metrokc.gov/dnrp/climate-change/conference-2005.htm

Increasingly, municipalities and the general public are becoming more aware of the concepts and risks associated with climate change. A recent study by Infrastructure 13

Canada highlighted the need for more communication between climate change researchers, policy makers, engineers, architects, operators or asset managers in order to mainstream climate change adaptation into design, maintenance and restoration of infrastructure (Infrastructure Canada, 2006). Climate change science has improved considerably over the last two decades, resulting in more robust predictions and stronger consensus within the scientific community. The greater level of confidence in climate and sea level projections can help city planners, policy makers, governments and developers to integrate climate risks into the decision making process.

Climate Change and Saint John Most areas of the globe are now starting to experience the impacts of climate change and Saint John will be increasingly at risk from these impacts. The coastline in and around Saint John is highly sensitive to sea level rise (Shaw et al. 1998) and much of the city’s infrastructure, such as wastewater treatment, transportation, shipping and commercial activities will become vulnerable to the effects of sea level rise. There are already substantial commercial and residential areas in the city that are subject to regular flooding which may worsen as precipitation patterns shift over the next 100 years. The City of Saint John needs to begin identifying the potential local impacts of climate change and evaluating the adaptive capacity of the city. Taking action in advance of the impacts will result in dramatic reductions in the cost of reacting to climate in the future.

This report examines the potential impacts that climate change will have on the City of Saint John, and identifies some of the most vulnerable areas within the city. This report also presents a simplified vulnerability analysis of Saint John which synthesizes the historical climate and tidal records so as to identify trends, and ultimately develop projections for how climate and sea level are likely to change over the next century.

The report identifies some of the vulnerable areas within the city and explores some of the possible adaptive strategies to deal with the expected impacts. This includes identifying further tools for assessing and increasing adaptive capacity within the city that have been used in other municipalities and exploring sustainable and realistic strategies to help Saint John face the challenges associated with climate impacts.

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2. Saint John Climate: Historical trends and projections Introduction It is now well documented that there has been an increase in the global average surface temperature, with the rate of warming in the last 50 years being roughly double that of the previous 100 years and a substantial increase in the occurrence of heavy precipitation events (Solomon et al. 2007). Although there have been considerable advances in our understanding of past and present climate change and in projecting future changes, much of the research has been focused at the global or continental scale. Observational evidence of the impacts of climate is accumulating and adaptation will be necessary to deal with the unavoidable warming (Parry et al. 2007). Several of the world’s larger cities have started to address this need for adaptation (London, UK; Boston, USA; New York City, USA; Greater Vancouver, CAN; Halifax Regional Municipality, CAN). In general, cities are increasingly becoming aware of the risks and are recognizing that the costs of failing to adapt are much greater than the costs of preparing for climate change.

The City of Saint John is Canada’s oldest incorporated city, established in 1785, and has one of the longest historical climate records in Canada dating back to 1897 (National Climate Data Archive, Environment Canada). The Saint John region is characterized by rocky slopes leading down to tidal and freshwater wetlands. The climate of Saint John is heavily influenced by the Bay of Fundy, acting to moderate the climate, resulting in mild summers and winters.

This section presents an analysis of the historical trends in temperature and precipitation in the Saint John area over the last 100 years. Projections of future climate conditions were developed from existing temperature and precipitation records and using statistical and climate models to help define probable future climate scenarios for the Saint John Region.

15

Methods Historical Analysis This study examines the historical temperature and precipitation records for the City of Saint John, New Brunswick, Canada over the last 110 years. The City is located in the south central area of the province along the north shore of the Bay of Fundy at the mouth of the St. John River. Saint John is the oldest incorporated city in Canada and has one of the longest historical climate records in Canada dating back to 1895.

Data used for analysis comes from the Adjusted Canadian Historical Climate Database (ACHCD, www.cccma.bc.ec.gc.ca/hccd/index.shtml) developed by Vincent and Gullett (1998). The climate database provides homogenized mean, maximum and minimum temperature measurements and adjusted daily precipitation measurements for 210 stations across the country and reported greater than 90% of all records, with 2003 being the only missing year.

The daily mean, maximum and minimum temperature data have been homogenized to account for artificial variations in climate records that are unrelated to actual climate changes, such as instrumentation change, location change site exposure or observing procedures (Vincent et al. 2002). Adjustments were made using regression models to identify inhomogeneities and matrices were used to adjust the records. The Saint John temperature record spans from 1895 to 2006. The daily precipitation amounts were adjusted to remove any inconsistencies as a result of systematic biases due to changes in measurement programs, but do not account for inhomogeneities due to local site changes (Mekis and Hogg 1999). The Saint John precipitation records spans from 1895 to 2006. Data was split into seasons that were defined as follows: winter (December – February), Spring (March – May), Summer (June – August), and Autumn (September – November).

Statistical analyses were done using SYSTAT 10 (Systat Software Inc., Point Richmond, CA). Annual and seasonal averages of temperature were analyzed to detect any trends in the record. Temperature data sets were tested for normal distribution using the Kolmogorov Goodness of Fit test. Temperature trend analyses were done 16

using linear least squares regression and residuals were checked to assure homogeneity of variances. It must be noted that the interdependent nature of temperature data can be sensitive to extreme values and outliers.

Precipitation trend analysis was also carried out using linear least squares regression with the residuals being analyzed to assure homogeneity of variances.

Precipitation data is independent in nature and is considered normally distributed over most parts of Canada (Groisman & Easterling 1994). Analyses of total annual precipitation was as the sum of all daily precipitation values in a given year and was also analyzed using 5 year moving averages, encompassing Âą 2 years of any given year. Precipitation data was also broken into several variables for trend analyses , summing the total number of days with high precipitation (over 2.5mm), low precipitation (between 2.5mm and 0.25mm), and no precipitation (under 0.25mm) in each given year.

Projected Future Climate Scenarios Modeling future climate is primarily done using global climate models (GCM)that break the globe up into large blocks (~ 300km x 400km) that are treated as a single unit and need to be refined or analyzed further to make region specific predictions. All modeling and analysis in this section was conducted by the Climate Change Division of the Meteorological Service of Canada and provided by Gary Lines (Climate Change Meteorologist). Projected GCM output for the Saint John area were taken from the Canadian Climate Centre for Modeling and Analysis (CCCMA), specifically from the Canadian Coupled General Circulation Model 2 (CGCM2), and from the Met Office Hadley Centre for Climate Change, specifically the Hadley Climate Model 3 (HadCM3).

Predictors from models include basic variables, such as mean surface temperature, mean sea level pressure, specific humidity and complex variables, such as geopotential heights and geotrophic winds reconstructed from pressure gradients (Lines et al. 2005).

Predictor sets from both models were generated for three future periods, corresponding to the following tri-decadal periods; 2020s (2010-2039), the 2050s (20402069), and 2080s (2070-2099). Data was provided in the form of daily data from the

17

CGCM2 and HadCM3 experiments, using the B2 scenario as described by IPCC (2000), and normalized with respect to 1961-1990.

Statistical Downscaling Modeling (SDSM) was used to generate local climate scenarios according to the methodology from Lines et al. (2005). The SDSM model is available for public use and can be downloaded from the SDSM UK website, along with a full description in the ‘Users Manual’ (Wilby et al. 2001). A brief description of the model, adapted from Lines et al. (2005), follows here.

The SDSM model is a hybrid of two methods; multiple regression and stochastic downscaling. Climate predictors (eg. mean temperature) were regressed against observed data sets, called predictands (eg. minimum or maximum temperature) to develop regression equations and calibrated to reduce error and increase explained variance. Predictor selection is done by choosing the predictor values that return the highest explained variance and lowest standard error. This set of regression equations is then used to develop future scenarios for the predictand(s) by running data sets from the National Centre for Environmental Prediction (NCEP). The output can also be further validated by comparing downscales projections against actual values from the baseline period. The calibrated output is then run through a stochastic model to generate data sets that could be averaged to provide the downscaled values for the scenarios.

SDSM modeling was used to develop projections of future scenarios of temperature and precipitation. Models were used to predict changes in the mean annual maximum and minimum temperature and total annual precipitation over the tridecadal periods mentioned above. A suite of projected precipitation data is created and examined by Extreme Value Analysis and plotted to the Gumbel distribution to identify precipitation return periods according to the methods outlined in Pancura and Lines (2005). The return period expresses the frequency for which an event is expected to occur in terms of probabilities. The precipitation return values in this report correspond to 24 hour precipitation events and present the 10, 50 and 100 year events and compare historical values to the tri-decadal periods mentioned above.

18

Results Trends in Historical Temperature Records The annual maximum temperatures in Saint John showed a gradual, but consistent increase in temperature over the last 100 years, with a marked increase in the number of warm years in the last 50 years of the record (Figure 2.1). The temperature record showed a mean annual warming trend of 0.09 °C per decade from 1895 to 2007 and similar trends were visible in the annual maximum and minimum temperatures (Table 2.11), but high variability in temperature resulted in a low coefficient of determination. The warming trend was present in each season as well, with the largest trend in the mean maximum summer temperature, warming 0.25 °C per decade with a high coefficient of determination (Figure 2.2).

Table 2.1 – Trends in the annual and seasonal maximum and minimum temperatures in Saint John from 1895-2007. R2 refers to the closeness of fit, E refers to the estimated standard error, and p indicates statistical significance.

Annual Spring Summer Autumn Winter

Mean Maximum Temperature (°C) R2 SE P °C/Decade 0.08 0.166 0.002 0.01 0.06 0.048 0.003 0.02 0.25 0.532 0.002 <0.01 0.03 0.015 0.002 0.19 0.00 <0.001 0.004 0.97

Mean Minimum Temperature (°C) R2 SE P °C/Decade 0.09 0.144 0.002 <0.01 0.09 0.076 0.003 <0.01 0.06 0.112 0.002 <0.01 0.05 0.042 0.002 0.03 0.15 0.076 0.005 <0.01

The annual minimum temperatures showed a similar trend to the annual maximum temperatures, with an increase in warmer years over the last half of the record, but had poorer goodness of fit than maximum temperatures (Figure 1). The trend in annual minimum temperature from 1895 to 2007 was 0.09 °C per decade, again with a low coefficient of determination. The seasonal minimums displayed warming trends as well, with the largest trend in winter, warming 0.15 °C per decade (Table 2.1).

Summer was the only season to show a coefficient of determination greater than 10%.

The records of mean maximum and minimum temperatures both show an increase in the number of warm years in the latter half of the record, starting around the 1950’s. Analysis of the block means of maximum and minimum temperature show 19

higher temperatures in the latter half of the record, with the annual mean 0.43 °C higher from 1950-2007, and the mean summer temperature 1.48 °C higher from 1950-2007 (Table 2.2).

12.5 12

A

Temperature ° C

11.5 11 10.5 10 9.5 9

Trend + 0.08 °C/Decade

8.5 8 2.5 2.0

B

Temperature ° C

1.5 1.0 0.5 0.0 -0.5 -1.0

Trend + 0.09 °C/Decade

-1.5

Year

Figure 2.1 – Trends in the mean annual A) maximum and B) minimum temperature from Saint John, NB from 1895 to 2006. Baselines are set at the mean values for the entire record.

20

23

Temperature °C

22

21

20

Trend + 0.25 °C/Decade

19

18

Year Figure 2.2 –Trend in the mean of the maximum summer temperature in Saint John, NB from 1895 to 2006. Baseline is set at the mean value for the entire record.

Table 2.2 – Differences in mean maximum and minimum temperatures in Saint John, NB before 1950 and after 1950.

Annual Spring Summer Autumn Winter

Average Minimum Temperature (C°) 1895-1949 1950-2006 0.09 0.63 -1.60 -1.05 10.60 10.94 3.38 3.74 -12.17 -11.11

Average Maximum Temperature (C°) 1895-1949 1950-2006 9.64 10.07 8.02 8.35 19.77 21.25 12.00 12.10 -1.50 -1.47

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Trends in Historic Precipitation Record The total annual precipitation in Saint John was highly variable, showing an increasing trend until peaking around 1980, and showing a decrease in total precipitation of the last 25 years (Figure 2.3). Trend analysis of the five year moving averages for annual and seasonal precipitation show that there was a small but significant increasing trend in annual precipitation of 16.99 mm per decade and the largest trend was in winter precipitation, increasing on average 91.87 mm per decade (Table 2.3).

2100

Total Annual 5 Year Moving average

Precipitation (mm)

1900

1700

1500

1300

1100

1895 1899 1903 1907 1911 1915 1919 1923 1927 1931 1935 1939 1943 1947 1951 1955 1959 1963 1967 1971 1975 1979 1983 1987 1991 1995 1999 2003

900

Year Figure 2.3 â&#x20AC;&#x201C; Trends in the total annual precipitation (mm) from Saint John, NB from 1895 to 2006 and a five year moving average from 1897-2001. Values calculated from the sum of all daily precipitation values.

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Table 2.3 â&#x20AC;&#x201C; Historic trend data for five year moving averages of total annual and seasonal precipitation for the City of Saint John from 1897 to 2005. R2 refers to the closeness of fit, E refers to the estimated standard error, and p indicates statistical significance.

R2 0.132 0.060 0.000 0.075 0.166

mm/Decade 16.99 32.67 -0.24 45.91 91.87

Annual Spring Summer Autumn Winter

E 0.42 0.12 0.16 3.06 0.20

p <0.05 <0.05 0.880 <0.05 <0.05

2

Please note that due to the random nature of precipitation, an R value above 0.1 was considered an acceptable trend.

While there was little significant change in the bulk precipitation records, there were significant changes in the distribution trends of precipitation within the historical record. Annually, the number of days with no precipitation shows a decreasing trend of almost 3 days per decade, whereas the number of days with low precipitation shows an increasing trend of 2 years per decade (Table 2.4). Winter was the only season to have a significant trend in days with high precipitation, showing an increasing trend of half a day per decade.

Table 2.4 - Historic annual and seasonal trend data for days with high precipitation, low precipitation and no precipitation in Saint John from 1895 to 2007. R2 refers to the closeness of fit, E refers to the estimated standard error, and p indicates statistical significance.

Days with High Precipitation (greater than 2.5 mm) Annual Spring Summer Autumn Winter

Days/ Decade 0.51 0.13 -0.16 0.12 0.43

2

Days With Low Precipitation (less than 2.5 mm)

R

E

p

0.014 0.008 0.002 0.006 0.056

0.03 0.02 0.01 0.02 0.02

0.115 0.362 0.264 0.422 <0.05

Days/ Decade 2.14 0.75 0.51 0.36 0.50

R

2

0.235 0.209 0.072 0.044 0.097

Days with no Precipitation (less than 0.25 mm)

E

p

0.04 0.01 0.02 0.02 0.02

<0.05 <0.05 <0.05 <0.01 <0.05

Days/ Decade -2.88 -0.90 -0.33 -0.57 -0.95

2

R

E

p

0.256 0.191 0.017 0.060 0.168

0.05 0.02 0.02 0.02 0.02

<0.05 <0.05 0.091 <0.05 <0.05

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Projected Future Temperature and Precipitation Scenarios SDSM projections from both climate models show that the mean annual maximum and minimum temperature is expected to increase over the next 100 years, increasing by almost a degree each tri-decadal period (Figure 2.4).

3

A

Temperature Change (째C)

2

1

0 2020s 3

2050s

2080s

B

CGCM2 HadCM3

2

1

0 2020s

2050s

2080s

Tri-Decades

Figure 2.4 - Projected changes in A) maximum and B) minimum temperature in Saint John, NB for three future tri-decade periods [2020 (2010-2039), 2050 (2040-2069) and 2080 (2070-2099)]. Results are SDSM models using output from the Canadian Climate Model (CGCM2) and the UK Hadley Model (HadCM3) using the B2 scenario as described by the IPCC (2000).

24

The Canadian model and the Hadley model show opposing predictions for the total annual precipitation (Figure 2.5). The CGCM2 projects an increase of 25% by the 2050s and little change over the next 30 years, whereas the HadCM3 predicts that precipitation will remain fairly constant for the first two tri-decades and decrease by 7% in the final tri-decade period.

30 25 20

% Change

15 10 CGCM2 5

HadCM3

0 -5 -10 2020s

2050s

2080s

Tri-Decade

Figure 2.5 â&#x20AC;&#x201C; Projected future % change of total annual precipitation in Saint John, NB for three future tri-decade periods [2020 (2010-2039), 2050 (2040-2069) and 2080 (2070-2099)]. Results are SDSM projections from using output from the Canadian Climate Model (CGCM2) and the UK Hadley Model (HadCM3) using the B2 scenario as described by the IPCC (2000).

The two models result in different precipitation return scenarios, with the CGCM2 model predicting very little change in return periods, beyond slight increases in precipitation amounts for the 10 year event and the HadCM3 predicting an increase in the amount of precipitation received in 24 events (Figure 2.6). The HadCM3 models show a shift in return periods, whereby the historical 100 year event becomes the 50 year event by the 2050s and we see a large increase the expected precipitation amount in the 100 year event.

25

Precipitation Return Periods (mm)

200 180

A

160 140 120 100 80 60 40 20 10 YEARS

0

Precipitation Return Periods (mm)

200 180

HISTORICAL

2020s

2050s

2080s

B

50 YEARS 100 YEARS

160 140 120 100 80 60 40 20 0 HISTORICAL

2020's

2050's

2080's

Figure 2.6 â&#x20AC;&#x201C; Comparison of historical precipitation return periods for a 24 hour precipitation event with projections for future return periods. The time periods correspond to the following dates; Historical (1961-1990), 2020s (2010-2039), 2050s (2040-2069) and 2080s (2070-2099) Projections come from SDSM models with data provided by A) the Canadian Climate Model (CGCM2) and B) the UK Hadley model (HadCM3) run using the B2 scenario as described by the IPCC (2000).

26

Discussion and Conclusions Historically Saint John has seen slight increases in mean temperature, but projections indicate that temperature will increase more rapidly in the future, resulting in up to 3Ë&#x161;C increase both maximum and minimum annual temperature. The results of these projections fall within the range of larger scale regional models for North America (Christensen et al. 2007) and the Atlantic Region (Hengeveld 2000). There has been no significant predicted change or trend in the total annual amount of precipitation, but there has been a predicted shift in the pattern of distribution, with a significant increase in the number of days with precipitation. Predicting future precipitation scenarios is extremely difficult (i.e. speculative) due to the natural variability of precipitation data, but scenarios indicate that this shift in precipitation patterns is likely to continue and may result in changing precipitation return periods. These changes in temperature and precipitation will have significant impacts on the City of Saint John if they are not addressed.

Temperature Saint John has seen a temperature increase of just under 1 Ë&#x161;C in mean annual temperature over the last 100 years, with a shift in the annual maximum and minimum temperature range, comparable to the average global temperature increase. The most pronounced increase in temperature is predicted for the mean maximum summer temperature ,and to a lesser degree for the minimum winter temperature. Although the historical record shows only small temperature increases, a positive trend is detected (with the exception of autumn maximum temperature) across all seasons in both the mean maximum and minimum temperature suggesting more than simply natural variability. Results of the regional models indicate that the trend of increasing temperature is likely to accelerate in the future, which coincides with the accelerated increase in global temperature predicted by the IPCC (Solomon et al. 2007).

Analysis of the historical temperature trends show that Saint John has experienced slight warming, the most prevalent being increases in the maximum summer temperature. Both the Canadian Climate Model and the Hadley UK climate

27

model project that mean temperature will continue to increase over the next 100 years, warming up to 3 degrees by the mid 2080s. This represents a substantial increase in temperature that could have large impacts on the region. An increase in the mean annual temperature will result in more frequent occurrences of heat waves within the city, exacerbating local air pollution and increasing heat stress to Saint Johnâ&#x20AC;&#x2122;s aging population. An increase in mean temperature can also have biological impacts, including alteration of fish habitat due to watercourse warming or an increase in the number of invasive species within the city. These changes in temperature will also contribute to changes in rates of evapotranspiration and to shifts in the patterns of precipitation.

Precipitation The historical record shows no clear trends in bulk precipitation, but there were significant changes in the distribution patterns. The most prominent change in seasonal distribution pattern was a substantial increase in the amount of winter precipitation, which may be in the form of snow or rain. Saint John has also seen an increase in the number of days with precipitation, again most prominently during the winter. There have not been substantial changes in the bulk precipitation that Saint John receives, but there have been significant shifts in how and when we receive precipitation, which can have an effect on city infrastructure, in particular storm and waste water management.

The projections of future precipitation scenarios are complex and the two models used to determine these projections show significantly different results. The Hadley model predicts a slight decrease in the total annual precipitation, and does match with the pattern of decreasing annual precipitation of seen over the last 25 years. The Canadian model however, predicts that there will be a significant increase in precipitation over the next 100 years. It is uncertain which of these models is correct and further modeling and projections using a variety methods of may be necessary.

The Canadian model may be seen as the worst case scenario in terms of future precipitation scenarios. Projections also indicate that there may be a change in extreme weather events, with a shift in the precipitation return periods. The Hadley model shows a significant shift, where the 100 year storm event shifts to the 50 year event, whereas 28

the Canadian model show only slight increases in the magnitude of the precipitation event. These models may present the range of values that may be expected in the future.

Conclusions The City of Saint John has experienced relatively little change in climate over the last 100 years, but changes are expected to increase in the future. The proximity of the City to the Bay of Fundy has helped buffer the city from the more pronounced changes in temperature seen among other regions in the Atlantic. However, the more accelerated rise in global surface temperature (Solomon et al. 2007) and ocean temperatures (Bindoff et al. 2007) will result in the acceleration of temperature rise in the Saint John region and contribute to changes in precipitation patterns. Saint John will become warmer, most notably with hotter summers and warmer winters and experience a greater range of extreme temperatures. These events may have health implications, including worsening air quality due to synergistic effects with current air pollution problems in Saint John and increasing health risks for Saint Johnâ&#x20AC;&#x2122;s aging population during extreme heat or cold periods.

Global climate change will also contribute to regional changes in precipitation patterns and extreme weather events, but these are significantly harder to predict. If the model results are taken as plausible ranges in future precipitation rates, the City may experience small increases in total precipitation, but of greater consequence is the shift in return periods for extreme precipitation events. Changes in the precipitation return periods would have drastic impacts on city infrastructure, such as storm and waste water management. Much of the cityâ&#x20AC;&#x2122;s storm water infrastructure and flood mitigation measures are based on current precipitation return periods and the components of these systems, such as pipes, culverts and surface water courses may break down if more severe or more frequent precipitation events occur. Saint John currently has flooding issues in some key areas of the City, including areas around the Marsh Creek floodplain, and some of the uptown areas around Harbour Station and Market Slip.

Changes in precipitation patterns and return periods could exacerbate current problems and introduce new issues if no action is taken to adapt and prepare for future changes.

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3. Sea Level Rise in Saint John Introduction Sea level has historically fluctuated with changes in global temperatures. For example, during the last glacial period when temperatures where ~ 5 ° C lower than at present much of the ocean’s water was tied up in glaciers and sea level could have been up to 100 meters lower than present sea level (Titus et al. 1991). Sea level has also been up to 6 meters higher than present during interglacial periods (Mercer 1970).

Current increases in global temperature are predicted to have large impacts on global sea level through a combination of thermal expansion and melting glacial ice (Bindoff et al. 2007). The IPCC predictions for global sea level rise in the most recent report states a range of 0.18 – 0.59 m by the year 2100, depending on the emissions scenario (Meehler et al. 2007). The IPCC projections have a high level of confidence, but it must be noted that they do not take into account any acceleration in ice flow from the Greenland and West Antarctic continental ice sheets. There is a high level of uncertainty associated with continental ice sheet movement that makes it difficult to model, but any increase in ice flow from either of these ice sheets would result in greater sea level rise than projected. That is, current sea-level rise predictions can be considered conservative.

The effects of sea level will change from region to region based on local geography, geology and ocean currents. Recent studies have shown that sea level has been rising more quickly in coastal areas than the global average and is rising faster more recently than it has in the past century (Holgate and Woodworth 2004). The Geological Survey of Canada has determined that Atlantic Canada has the longest length of coastlines sensitive to sea-level rise in Canada, with approximately 80% of the Atlantic region’s coast considered moderately to highly sensitive (Shaw et al. 1998).

This high level of sensitivity is due in part to the fact that large portions of the Atlantic coastline are subsiding as a result of crustal movements in response to deglaciation, with this compounding effect resulting in a relatively higher level of sea rise (Figure 3.1).

30

Figure 3.1 â&#x20AC;&#x201C; Areas of the Canadian coast that are currently submerging Source: Shaw et al. 1998.

This predicted rise in sea level has numerous implications for coastal areas, and especially for coastal cities where much of the infrastructure and economy focuses around the water. The Saint John region has been identified as moderate to highly sensitive to sea level rise (Figure 3.2). A previous study by Martec Ltd. (1987) examined the effects that a one metre sea level rise would have on Saint John and the lower reaches of the St. John River, and identified several areas within the city that would be at increased risk from storm surge in the future (Box 3.1). Both Martec Ltd. (1987) and ACAP Saint John (2002) identified storm surge as the biggest risk factor associated with sea level rise. Improvements in modeling technology have led to higher confidence in projections of global sea level rise and more detailed assessment of the regional impacts of sea level rise. Mapping of future sea level rise and storm surge is a valuable tool to help cities to conduct risk assessments and improve adaptive capacity.

31

Box 3.1: Summary: Effects of a 1 metre rise in sea level at Saint John, NB (Martec Ltd. 1987)

Saint John, New Brunswick

E H

H

100 year flood line with 1m sea level rise E Extreme risk area

H

H High risk area

E

Source: Martec, Effects of a one metre sea-level rise at Saint John, NB..., 1987

Saint John Harbour NOTE: FILLED-IN SINCE AIR PHOTOS

Figure 1 â&#x20AC;&#x201C; Flood map of the 1:100 year storm surge on Saint John, NB. Circles indicate areas where city inf rastructure is at risk f rom the ef f ects of the storm surge

Environment Canada, through the Canadian Climate, program funded a study to examine the effects of a 1 metre rise in sea level on the City of St. John and the lower reaches of the Saint John River. The study identified the levels of the1:20 and 1:100 year storm surge and, assuming that a 1 m rise in sea level would correspond with a 1 m rise in the storm surge, mapped the areas that would be affected by these extreme water levels. The results show that the water levels for a 1:100 year event will reach 6.0 m above datum and the 1:20 year event will reach 5.8 m above datum, which is roughly equivalent to the current 1:100 year storm surge.

This change in storm surge levels would have serious implications for the City of Saint John and has the potential to affect large areas of commercial and residential development and transportation infrastructure. Mapping of the 1:100 year flood line identifies several areas that are at risk from storm surge (Figure 1). The two areas most at risk from storm surge are the port facilities on the west side and Marsh Creek flood basin, including the Courtenay Forebay, leading to damage and disruption of marine transportation and infrastructure and rail and road disruptions. Several other areas of the city are at risk from flooding and inundation during storm surge, including sections of the uptown, industrial facilities along the St. John River and sewage and wastewater treatment lagoons (Table 1).

This report highlighted the need to begin long-term planning and retrofitting of existing city infrastructure.

It was recommended that the city start carrying risk-benefit analyses of adaptive strategies to address future rise in sea level. The report suggested that the city develop guidelines to regulate development on lands at risk of inundation or flooding and to identify what data is needed to assess the social and economic costs of sea level rise.

Table 1 â&#x20AC;&#x201C; Potential risks associated with a 1:100 year storm surge in the City of Saint John Harbour and surrounding region. Table represents a summary of risks identif ied in the 1987 study conducted by Martec Ltd.

Citation: Martec Ltd. 1987. Eff ects of a one metre sea-level rise at Saint John, New Brunswick and the lower reaches of the Saint John River. For: Atmospheric Environment Service, Environment Canada.

32

Low Moderate High

Figure 3.2 â&#x20AC;&#x201C; Sensitivity of the Atlantic coasts to sea level rise, with the inset showing a closer view of the region around Saint John and the Bay of Fundy. Red zones indicate high risk, Yellow indicates moderate risk and green indicates low risk. Source: Shaw et al. 1998.

This section examines how sea level rise and the associated changes in storm surge levels will impact Saint John. The first step was an analysis of the historical record of sea level change in the Saint John region and formulation of predictions for future sea level rise incorporating regional effects on sea level rise, such as crustal subsidence and tidal amplification. Simple flood models were constructed to examine the impacts of projected sea level rise and storm surge events using updated elevation data for the Saint John region, including LiDAR (Light Detection and Ranging) surveys of the Marsh Creek floodplain and identify vulnerable areas of the city.

33

Methods Historic and Projected Changes in Sea Level This section focused on the City of Saint John (as described in the previous chapter) and more specifically, the Saint John Harbour and adjacent coastlines including the Saintâ&#x20AC;&#x2122;s Rest Marsh and Red Head Beach. Similar to its climate record, Saint John possesses one of the oldest tidal records in the Atlantic region.

The data for the historical analysis and tide level calculations came from the Marine Environmental Data Services (MEDS) Integrated Science Data Management (http://www.meds-sdmm.dfo-mpo.gc.ca/). This database provides ocean data collected by the Department of Fisheries and Oceans Canada or international programs that are conducted within or near Canadian waters. Tide gauge data was obtained from Station 65 in Saint John (Lat 45.251, Long 66.093), which contains digital records (of almost continuous hourly water levels) from 1896 to the present. The annual mean sea levels were calculated from daily mean tides. The mean sea level for the entire dataset was used to establish the baseline for sea level change and linear regression was used to detect any trends in sea level.

Projected changes in sea level were established by an additive process taking into account global sea level rise projections from the most recent IPCC report A1F1 scenario (Meehl et al. 2007), crustal subsidence inferred from tide gauge data and the effects of tidal amplification (Table 3.1). These changes equate to 0.70 m rise in sea level by the year 2100. Water levels were calculated using hourly tide levels over the last 9 years. MSL (Mean sea level) represents the mean of all hourly water levels over the sample period. MHHW (Mean higher high water) represents the mean of all the higher high water marks each day over the sample period. PSHW (Perigean spring high water mark) represents the mean of the highest monthly high water mark over the sample period.

34

Table 3.1 – Summary of sea level rise projections for the Saint John region, broken down into additive components. MSL – Mean sea level; MHHW – Mean higher high water mark; PSHW – Perigean spring high water mark.

MSL MHHW PSHW 1 2 3

Present Sea-Level 0.24 3.47 4.31

Crustal Subsidence1 0.2 0.2 0.2

Global SeaTidal Level Rise2 Amplification3 0.4 0.1 0.4 0.1 0.4 0.1

2100 Sea Level 0.94 4.17 5.01

Tide Gauge data and Shaw et al. 1998 IPCC Meehl et al. 2007 Webster personal communication, Titus 1990

Storm surge modeling Storm surge models were done using ArcGIS 9.2 (ESRI, Redlands, CA, USA) and gvSIG 1.1 (Conselleria d’Infraestructures I Transport, Valencia, SPN). Elevation data was provided by the City of Saint John GIS Department. Chart datum water levels obtained from MEDS were converted to Canadian Geodetic Vertical Datum of 1928 (CGVD28) according to methodology outlined by Webster et al. (2007). Previous models indicated that the majority of impacts associated with sea level rise stem from storm surges occurring at or near high tide. The present model used the scenario of a 1metre storm surge striking at MHHW under the sea level projections from Table 3.1, which is close to the median for historical storm surges in the Atlantic region with averages ranging from 0.6 – 2 m (Parkes et al 1997). Storm surge maps were constructed for 3 locations in Saint John; the Inner Harbour, Saint’s Rest and the Red Head Road area. Flood risk maps for the Marsh Creek/Glen Falls area were constructed by Drisdelle (2007) for the City of Saint John from LiDAR altimetry.

It should be noted that these flood models are flat earth models and do not take into account wave modeling or shore run-up, and assume that the projected sea-level rise will not alter the morphology of the coastline. Sea level rise would likely result in changes in coastal morphology, such as shifting coastal wetlands and increasing erosion on shorelines with unconsolidated soils. It is difficult to quantify or predict changes in coastal morphology without extensive studies of erosion, sedimentation, and wave action.

35

Results Historic Tide Record Tide gauge records indicate a clear trend of rising sea level over the last 100 years, with Saint John experiencing approximately 2 mm of relative sea level rise per year, resulting in approximately 0.2 m change in mean sea level (Figure 3.3).

0.25 0.20

Trend + 20 mm/decade

Sea Level Change

0.15 0.10 0.05 0.00 -0.05 Observed Sea Level

-0.10

5 yr Moving Average -0.15 -0.20

Year

Figure 3.3 â&#x20AC;&#x201C; Observed sea level change from the historic tide gauge record from Saint John, NB. Baseline is set at the mean for the historical record (4.369 m Datum).

Projected changes in sea level Saint John is projected to see an increase in sea level of 0.80 m by the year 2100, due to a combination of actual sea level rise, relative sea level rise and tidal amplification caused by the morphology of the Bay of Fundy. Sea level rise is expected to increase more rapidly in the future (Figure 3.4), but it is unclear exactly what pattern that sea level rise will follow. Figure 3.4 assumes a logarithmic increase, but any changes in ice sheet behaviour or land based glacier melt could have a severe impact on sea level predictions.

36

1.00

0.80

Sea Level Change (m)

0.60

0.40

0.20

0.00

Relative SLR Combined relative SLR and actual SLR

-0.20

-0.40

Year

Figure 3.4 - Mean sea level changes in Saint John, NB. The solid blue line indicates a reconstruction of the annual mean sea level from the tide gauge record. The dashed blue line indicates projected relative sea level rise (SLR) as a result of crustal subsidence and the solid green line indicates the projected sea level change from the combined values of relative SLR (crustal subsidence), actual SLR (thermal expansion) and tidal amplification. The baseline value is set at the mean for the historical record (4.369 m Datum).

Storm Surge The projected sea level rise increases the flood risks (as a result of storm surge) for several locations in Saint John, including the Inner Harbour (up to the pulp and paper mill on the reversing falls), Saintâ&#x20AC;&#x2122;s Rest Marsh, Red Head Marsh, Red Head Beach, Marsh Creek and its floodplain (Figure 3.5). Storm surge forecasting from Drisdelle (2006) predicts a shift in storm surge return periods with 1:10 year storm at 4.6m, 1:20 year storm at 4.7 m, 1:50 year storm at 4.9 m and the 1:100 year storm 5.2 m, but it must be noted that the sea level rise prediction for the LiDAR model was more conservative than the additive model used for the other maps.

37

Inner Harbour

Marsh Creek*

Saint’s Rest Marsh Red Head Road Figure 3.5 – Flood risk map for an approximately 1 m storm surge for key areas within the City of Saint John in the year 2100 assuming sea level rise of 0.7 m. Areas within the yellow for Inner Harbour, Saint’s Rest Marsh and Red Head Road are flood lines a 1 m storm surge landing at MHHW taking into account a 0.7 m sea level rise. The Marsh Creek flood map is from Drisdelle (2006) based on LiDAR altimetry data showing flood lines for a 4.6 m sea level in the year 2100, which roughly corresponds to 8.8 m (Chart Datum) 38

Discussion and Conclusions Saint John has seen a sea level rise of approximately 0.20 m over the last 100 years, predominantly as a result of crustal subsidence (Shaw et al. 1998b; Weddle and Retelle 2001), but sea level is expected rise more rapidly over the next 100 years (Meehl et al. 2007) resulting in a sea level rise of 0.70 m within the Saint John region (Figure 3.4). Saint John will become increasingly vulnerable to impacts from storm surge as sea level rises and some key city, commercial, and industrial infrastructure are at risk (Figure 3.5). The Marsh Creek Floodplain and surrounding areas are most at risk from rising sea level, compounding the pre-existing flood problems that were identified in that area decades ago (Proctor and Redfern 1976, Martec Ltd. 1987).

Sea Level Rise Sea level rise is likely to be one of the most dramatic consequences of climate change, particularly for those living in coastal regions. However, sea level is influenced by a multitude of dynamic and complex processes and historically, large uncertainties and variability have made accurate predictions difficult. However, improvements in the science of modeling, coupled with more accurate measurement of sea level and advances in the understanding of ocean circulation, have led to greater confidence associated with predictions in recent years. Specifically, recent studies have detected enhanced sea level rise over the last decade (Holgate and Wodworth 2004) supporting the projections from the IPCC (Church et al. 2007; Meehl et al. 2007) that sea level rise is beginning to accelerate. The projections for sea level rise in this document are similar to reports from other areas around the Maritimes that have conducted assessments of sea level rise (McCulloch et al. 2002; Forbes et al. 2006). Environment Canada (2006) experimented with different regional models to obtain projections specific to the Atlantic region, but found no models that obtain significantly different results than the global predictions from the IPCC reports.

The sea level rise projections from the most recent IPCC report (Meehl et al.

2007) have much higher confidence levels than previous reports, and clear historic trends in relative sea level change and crustal subsidence (Shaw et al. 1998a; Weddle

39

and Retelle 2001) result in high confidence for the projections presented in this study.

The Canadian models have high confidence that sea level will have risen 0.40 m by the year 2100, but the exact pattern of sea level rise is uncertain and the logarithmic trend shown above (Figure 3.4) may not be an accurate representation. There are some indications that these predictions are too conservative, such as recent sea level rise exceeding earlier model predictions, and that scientists are underestimating sea level rise (Rahmstorf 2007). That potential, combined with the fact that projections in the most recent IPCC reports do not take into account any changes in the land based ice sheets of Greenland and the Western Antarctic, could lead to much higher levels of sea level rise in the future.

The projections in this study indicate that sea level rise will not result in permanent inundation of any portions of Saint John, mostly due to the fact that most of the coastline around Saint John consists of steep rocky shorelines that rise quickly out of the water. There is risk that areas around the Marsh Creek floodplain may be affected during Perigean high tides that may reach over 5 m (orthometric) or 9 m (Chart Datum), which could overtop the causeway at the Courtenay Forebay. The true risk factor behind rising sea level is the resulting changes in storm surge and wave patterns.

Stormwater levels and waves are tied closely to the mean sea level and rising sea level will have important implications for flooding levels and wave run-up (Forbes et al. 2006).

Storm Surge Storm surge has been identified as one of the largest threats to coastal communities in the Atlantic region. Numerous Maritime municipalities are at risk from storm surge as sea level begins to rise, including Charlottetown (McCulloch et al. 2002), Bouctouche and Shediac (Environment Canada 2006), Annapolis Royal (Webster et al.

2007) and Truro (Webster and Forbes 2005). Storm surge, defined as the difference between the observed water level and predicted astronomical tide, has been a risk factor for the Bay of Fundy and the Atlantic region since it was settled. There have been several well documented storm surges that have caused severe damage to communities around the Bay of Fundy, such as the Saxby Gale of 1869 and the Groundhog Day Storm of 1976, where tides rose up to 2.5 m above predicted levels 40

(Desplanque and Mossman 1999). These extreme water levels may become more frequent as sea levels rise, reducing the distance between normal tides and flood conditions. The large tides in the Bay of Fundy reduce the probability of significant storm surges occurring at high tide, as compared to other regions in the Atlantic, but previous events like the Groundhog Day storm indicate that these extreme events are possible and may become more frequent and more severe. This study identifies numerous areas of Saint John that would be at risk from storm surge as the sea level rises.

As stated previously, the Marsh Creek watershed and its associated floodplain are most at risk from storm surge, with the former extent of the Great Marsh flooding soon after the water breaches the causeway (Figure 3.6), and subsequently inundating large sections of residential and commercial property. The Marsh Creek watershed is already prone to inland flooding during heavy precipitation events (Proctor and Redfern 1976) and major storm surges most often occur in conjunction with heavy precipitation events, resulting in the exacerbation of storm surge through inland flooding. The eastern wastewater treatment lagoon near Saints Rest and the wastewater treatment ponds at the pulp and paper mill are at risk from wave run-up associated with storm surge, which could result in contamination of fresh water if breached. The commercial areas near Market Square and the west side docks are also at risk from storm surge.

Conclusions The City of Saint John will become increasingly vulnerable to storm surge and sea level rise over the next century. The flood prone regions on the east side of the city near the Marsh Creek floodplain will become increasingly vulnerable to the effects of combined coastal and inland flooding. The probability of severe storm surges coinciding with MHHW or PGSW are lower than regions such as Southeastern shore of New Brunswick, but they still represent a significant risk to city infrastructure and citizens. More detailed analysis using LiDAR altimetry of the whole city to produce a more accurate DEM, combined with inland flooding analysis will drastically improve the modeling and develop a more complete vulnerability analysis of the City.

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Former extent of Great Marsh

Storm surge resulting in a 4.6 m tide

Figure 3.6 â&#x20AC;&#x201C; Comparison of the former extent of the Great Marsh and the resulting flood levels from a storm surge in the year 2100 that results in a 4.6 m water level (orthometric).

Saint John needs to address the vulnerability of the City and assess its adaptive capacity. Changes in municipal development policy are needed to limit development in some of the high risk areas identified, and to begin addressing options to help the city improve adaptive capacity, such as increasing wetlands and green spaces to help limit flooding, and implementing â&#x20AC;&#x153;no regretsâ&#x20AC;? policies (Medhi et al. 2006; Ligeti et al. 2007).

Many cities have begun to address the mitigation side of climate change, but in order to prepare Saint John for the expected impacts it is important to have an integrated approach addressing both mitigation and adaptation to the changing climate.

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4. Adaptation Introduction It is now well established that a changing global climate is increasing climate variability and exposure to extreme weather events such as floods, droughts and storms (IPCC 2001a, IPCC 2007). This change in climate is the result of a combination of natural factors and human activity; however, recent studies indicate that human activities such as fossil fuel consumption and changes in land-use patterns are playing a dominant role in climate changes observed during the past 100 years (IPCC 2007).

While the need to address climate change has come to the forefront of public awareness, the majority of strategies are focused on the mitigation of greenhouse gas emissions. The reduction of greenhouse gas emissions, termed mitigation, is important in reducing the rate and severity of future climate change. However, climate response to emission reductions will not be seen for at least 50 years due to the slow equilibrating process of global climate. Regardless of any future reduction in emissions, global temperatures and sea level will continue to rise over the next century (Meehl et al.

2007). Therefore, it is important that communities around the globe begin the process of adapting to deal with the short and long-term impacts of climate change.

Adaptation initially referred to future changes in climate, but has increasingly been understood to include adjustments in climate variability and extremes, as well as future climate change. Adaptation, in the context of climate change, refers to any change in activity that reduces the negative impacts of climate change, with the goals of alleviating current impacts, reducing sensitivity and exposure to climate related hazards, and increasing adaptive capacity (Warren and Egginton 2008). There are numerous types of adaptation, including anticipatory; action taken before impacts are observed, and reactive; action taken after impacts are observed (Smit et al. 1999; Table 4.1).

Although the economic costs of adaptation are relatively unknown, the benefits of strong, early action on adaptation and mitigation will far outweigh the costs of adapting after impacts have occurred (Stern 2006). There has been a stronger awareness in recent years of the importance of adapting to climate change and of evaluating the potential impacts of climate change from a variety of perspectives. This newfound 43

perspective also recognizes the different roles for adaptation processes from individuals, communities, the private sector (e.g. industry, business, commerce), and governments at all levels (Burton 2008).

Table 4.1 â&#x20AC;&#x201C; Summary of different types of adaptation and the method of differentiation.

(Source: Burton 2008) Adaptation Type of Adaptation

Based on

Intent In relation to climatic stimulus

Action

Temporal scope Spatial scope

Autonomous

Planned

(e.g. unmanaged natural systems)

(e.g. public agencies)

Reactive

Concurrent

Anticipatory

(post)

(during)

(ante)

(from observed modification)

(prior modification)

Short term

Long term

Adjustments, instantaneous, autonomous

Adaptation, cumulative, policy

Localized

Widespread

Global exposure to climate change associated with extreme weather events is increasing, and (subsequently) the associated economic costs have also been increasing steadily, reaching over US $100 billion in 2004. This trend is expected to continue increasing as the world experiences more frequent and possibly more severe weather events (Burton 2006). Canada is already experiencing the impacts of climate change and can expect to see an increase in climate associated effects (e.g. extreme weather events) in the coming decades and centuries. Economic studies of climate impacts on the US indicate that economic impacts will be seen throughout the country and that the negative impacts will outweigh the benefits in most sectors (Ruth et al.

2007). Climate change has (and will) continue to affect the Canadian economy in numerous ways including; impacts from extreme weather events (Table 4.2), impacts on buildings and infrastructure, costs related to public health and safety, and impacts from 44

changes in water resources (Warren and Egginton 2008). The impacts that climate change will have in Canada vary drastically based on regional geographical, economic and environmental characteristics and are outlined in detail in several federal assessment documents (Koshida and Avis 1998, Lemmen and Warren 2004, Lemmen et al. 2008).

Table 4.2 â&#x20AC;&#x201C; Examples of weather related disasters in Canada and estimated cost of the damages.

Event

Cost

Prairie Drought 2001-2002 Ice Storm 1998 Saguenay Flood 1996 Red River Flood 1997 Calgary hailstorms 1991 Edmonton Tornado 1987 British Colombia Blizzard 1996-1997 Hurricane Juan and White Juan 2003-2004

$ 5 Billion $ 4.2 Billion $ 1.2 Billion $ 400 Million $ 400 Million $ 300 Million $ 200 Million $ 100 Million

Uncertainty regarding the nature of climate change should not be a basis for delaying adaptation strategies, but rather serve to focus on adaptation measures to help address current vulnerabilities through expanding coping ranges and increasing adaptive capacity. Adaptive capacity is defined â&#x20AC;&#x153;as the ability of a system to adjust to climate change (including climate variability and extremes) to moderate potential damages, to take advantage of opportunities, or to cope with the consequencesâ&#x20AC;? (IPCC 2001b). With increased recognition of the need to address climate change impacts, the government of Canada has conducted several studies on the most sensitive sectors and on the adaptive capacity of various regions in Canada (Forbes et al. 1998, Lemmen and Warren 2004, Forbes et al. 2006, Lemmen et al. 2008). Although some adaptation strategies can be implemented at the national or global level, the majority of adaptation efforts will occur at the local level in response to the vulnerabilities of individual communities or municipalities.

Canadian municipalities continue to demonstrate leadership in greenhouse gas mitigation efforts and are poised to lead the way in adaptation to climate change, with

45

several municipalities across the North America implementing adaptation strategies (see The Heinz Center Survey of Climate Change Adaptation Planning 2006). Cities are vulnerable to climate change as they concentrate people and infrastructure into small geographic areas, and because the population is highly dependent on local infrastructure such as water and power distribution, communications systems and sewer and wastewater removal (Penney and Wieditz 2007). The City of Saint John is beginning to see the impacts of climate change, with increases in the number of hot days every year and most markedly with changes in the patterns of extreme weather events. Currently, most of the cities that are developing or have developed adaptation strategies began the process after experiencing a severe weather event that resulted in large economic losses and, in some cases, the loss of human life (e.g. Hurricane Juan and White Juan caused over $100 million in damages to the Halifax Regional Municipality and spawned Climate SMART). Saint John can avoid this mistake by initiating the adaptation process before it becomes impacted by an extreme weather event that results in severe economic costs and risks to human health. This chapter of the report examines the adaptive capacity of Saint John, based on the vulnerabilities identified in the previous two chapters, and presents some possible adaptive strategies.

This report presents steps that Saint John has already taken to address climate impacts and presents ideas and strategies from other municipalities that could help Saint John increase its adaptive capacity. This chapter also provides recommendations on how Saint John can begin the process of addressing climate change and working towards developing a comprehensive adaptation strategy.

Vulnerability Assessments It is important to understand the nature of the current climate and what changes are expected in the future to effectively assess the adaptive capacity of the city. One of the key first steps in developing an appropriate adaptive strategy is the assessment of current and historical climate trends and future projections for the city, as is seen in Chapters 2 and 3 of this report. Saint John has been experiencing subtle changes in climate over the last century, with increases in the number of hot summer days and shifts in patterns of precipitation. However, Saint John is expected to see more 46

pronounced changes in climate over the next 100 years, with an upward shift in temperature and more severe precipitation events. Current climate trends are having negative impacts on the City and will only get worse in the future. The analysis of climate provides the baseline for a vulnerability assessment of the city, helping to identify regions and infrastructure that are at risk from climate impacts.

The Marsh Creek watershed is the most vulnerable area of the city to climate and extreme weather impacts, with inland flooding regularly occurring in residential and commercial areas during heavy precipitation events (Figure 4.1). Hydrological studies carried out by Proctor and Redfern Ltd. (1976) identified significant flood risks during storm events and recommended a number of flood management measures including; an increase in floodway storage along Marsh Creek and Majors Brook, structural and channel improvements, local drainage improvements and strict zoning regulations. This area is still vulnerable and more recent studies, including this one, have highlighted that it is vulnerable both to inland flooding and to storm surges as sea level continues to rise (Martec 1986; Drisdelle 2007). The city has recently hired consultants to develop a new stormwater strategy to address some of these issues, particularly existing problems in the Marsh Creek watershed. The results from this report suggest that Marsh Creek will become more vulnerable to climate impacts in the future as a result of severe precipitation events and rising sea level.

The current and projected patterns in precipitation also present risks for numerous regions and sectors of city infrastructure. Saint John is seeing a shift to more precipitation events in the winter, and an increase in the number of days with precipitation each year. These patterns are projected to continue, resulting in more severe and potentially more frequent extreme precipitation events. Winter rain events often result in more severe flooding, as demonstrated by events in the winter of 2008 (Figure 4.1), as ice cover results in greater impervious surface area within the city and increased overland water velocity. This leads to increased flooding in low lying areas and potential contamination of drinking water sources, as was seen in February 2008 when a 10 day boil water advisory was issuedfor the central and eastern portions of Saint John.

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McAllister Mall

Simpson Drive

Golden Grove Road

McAllister Mall

Figure 4.1 â&#x20AC;&#x201C; Examples of locations in Saint John that are currently prone to inland flooding during heavy rain events. The top two pictures were from precipitation events in the winter of 2008, while the bottom two pictures were from precipitation events in the summer of 2006.

Although Saint John is not expected to see drastic increases in mean temperature, it is projected that Saint will experience more hot summer days. This may contribute to more occurrences of smog days within the city, especially in light of the new industrial developments in the regions, such as the Canaport Liquefied Natural Gas facility and the potential Irving Eider Rock oil refinery. Saint John has seen small improvements in air quality, as indicated by the recent air quality report (DENV 2008), but an increase in industrial development coupled with more frequent hot days could result in worsening air quality in the Saint John region. More detailed analysis of emissions scenarios and atmospheric modeling are needed to determine potential climate associated impacts.

48

Saint John, a coastal city already vulnerable to the effects of storm surge, could see this vulnerability increase as sea level rises over the next 100 years. The exact impacts of sea level rise on coastal cities depends on numerous and complex factors. A complete assessment of potential impacts requires the examination of these factors, such as prevailing wind and storm patterns, existing flood control measures, coastal landform, and building and infrastructure on the coast (Penney and Wiedecki 2007).

The high tides of the Bay of Fundy offer some protection from storm surge events, but storm surge events coinciding with mid to high tide can have drastic consequences as seen from historical events such as the Saxby Gale and the Groundhog Day storm (Desplanque and Mossman 1999). Conservative estimates of sea level rise for the Saint John region predict a 0.70 m rise in sea level by 2100 (see Chapter 3), although any change in the Greenland or Western Antarctic ice sheet could increase this figure by over 1 m, resulting in increasing vulnerability to storm surge for many areas of the Saint John waterfront. The storm surge maps in Chapter 3 identify numerous areas that are vulnerable to storm surge as sea level rises, with some of the key areas, being the Uptown waterfront, the current Irving oil refinery, Saintâ&#x20AC;&#x2122;s Rest Marsh and the Marsh Creek floodplain (Figure 4.2). The Uptown and Marsh Creek areas present high risk areas for residential and commercial losses from inundation of businesses and homes, which could results in hundreds of thousands of dollars in damages. The Lancaster Sewage Treatment Facility is of particular concern, as wave run-up or inland water flow could breach of the existing berm during storm surge events, resulting in contaminated water entering the marsh or leaching into the surrounding soil. Storm surge models indicate the lower sections of the Irving pulp and paper mill, where the wastewater storage tanks area located, are also at risk and could result in contaminated water flow into the Saint John River.

This report provides a preliminary assessment of the climate change impacts on Saint John, and while it should serve as a starting point for identifying what factors or areas are in need of more in-depth investigation, it is by no means a comprehensive vulnerability analysis. Impact assessments from other cities can help identify typical areas of impact and methodology on assessment techniques to address sectors that are in need of further investigation. Penney and Wiedecki (2007) highlight examples 49

from six large cities that have conducted detailed vulnerability assessments and identify some of the key sectors in climate impact assessments (Table 4.3). Saint John needs to identify what sectors need to be examined in greater detail and begin determine how the projected climate changes will impact the sectors being studied. Adaptation to climate change is a highly interdisciplinary field and effective strategies must involve a variety of people including scientists, managers, municipal planners, policy-makers and community members.

Floodplain Uptown

Sewage Lagoon

Saintâ&#x20AC;&#x2122;s Rest Marsh

Refinery

Likelyâ&#x20AC;&#x2122;s Beach & Red Head Marsh

Figure 4.2 â&#x20AC;&#x201C; Examples of some of the areas within the city that will become increasingly vulnerable to storm surge as a result of the impacts of sea level rise over the next 100 years.

50

There are numerous experts and resources available federally and within the Atlantic region to help Saint John begin this process. The Halifax Regional Municipality, Saint John’s partner in the Atlantic Canada Sustainability Initiative, has taken a leadership role in addressing climate change, and the Climate SMART program is recognized as one of the most innovative programs in North America.

Table 4.3 – Key sectors for climate change impact assessments, as identified from assessments carried out by various other cities during the development of adaptation strategies.

Key Sectors Water resources Energy demand & supply Transport Buildings/housing Ecosystems Coastal impacts Public health Social impacts

Components Drinking water, sewer services Changes in energy demand or generation Roads, rail, shipping, air travel Vulnerable structures and zones Wetlands and others Flooding, storm surge Heat, air quality, infectious disease Vulnerable groups (e.g. low income, elderly)

Adaptation Options Adaptation policy cuts across departmental and sectoral boundaries of municipal government and needs to be factored into the decision making process at all levels.

Addressing adaptation may require institutional reform or restructuring, and innovations need to be supported by integrated science and policy (Burton 2006). There are generic adaption options that are effective strategies for almost all cities and serve as a good base to begin the process of identifying options to move forward with (Medhi et al.

2006). The logical first step is to begin adopting ‘no-regret’ policies and infrastructure improvements. No-regrets climate adaptation refers to actions that provide benefit to the community even if the anticipated climate changes do not materialize (Medhi et al.

2006). Adopting no-regrets policies, common sense and long-term planning can make a large difference in avoiding an increase in vulnerability. Hasty decision making or 51

recovery efforts after a disaster can increase vulnerability if climate impacts are not taken into account, resulting in more development in hazard zones and limited improvements in infrastructure design (Burton 2006). Adaptation options can take many forms, including; infrastructure change, simple shifts in development policy, building codes, incentives and land use strategies. Saint John has taken some small steps already to address climate change including; LiDAR survey of the Marsh Creek watershed, Flood Risk by-law for the 1 in 100 year flood plain and the new Eastern Wastewater Treatment facility takes into account a 1 m rise in sea level. Adaptation options fall into several categories, but are highly changeable depending on the situation and needs of individual cities. The following sections present some adaptation options for Saint John to address climate impacts and Appendix A provides a list of detailed technical resources for climate adaptation planning and implementation.

Education •

Educate public about the risks of buying or building homes in areas vulnerable to flooding, erosion or sea level rise.

•

Provide guidance for developers on methods to identify and manage climate associated risks, incorporate climate change into planning decisions, and promote sustainable development. (see Climate SMART Developer’s risk management guide; HRM 2007)

•

Educate communities about climate change and associated risks and provide resources to encourage local action to address climate change. (see Climate SMART Community action guide to climate change and emergency preparedness; HRM 2006)

Coastal/Inland flooding •

Comprehensive stormwater planning that incorporates new technologies and designs that take into account expected changes in sea level and precipitation patterns. Examples include; Incorporation of wetlands into stormwater system, expand capacity of storm sewer systems, increased use of pervious surfaces (e.g. grass parking lots, pervious concrete, green roofs), Low impact 52

development (Department of Environmental Resources 1999), Natural drainage systems (see Case Study www.evergreen.ca/en/cg/pdf/Seattle%20AB.pdf).

•

Protect and preserve existing wetlands within the city and restore wetlands that previously provide flood protection. Significant amount of Saint John wetlands have been lost as a result of commercial, industrial and residential development within the city. Restoration and creation of wetlands in keys areas of the city could provide significant flood protection (e.g. develop wetlands along Marsh Creek to provide additional floodway storage)

•

Installation or refurbishment of control structures (e.g. breakwaters, berms, etc.) in key locations to reduce the vulnerability to storm surge. Raising the berm in between the Lancaster Sewage Treatment facility and Saints Rest Marsh would drastically reduce its vulnerability to storm surge.

•

Converting flood prone areas to green spaces or natural ecosystems to act as buffers to reduce negative impacts associated with flooding and provide more pervious surfaces for absorption of overland water flow.

•

Establishment of effective land use planning strategies to limit development in areas vulnerable to erosion or flooding and to maintain existing. This could include zoning bylaws to prevent development in areas that contain natural systems (e.g. wetlands) that reduce flood risks.

Water Supply •

Reclamation and re-use of grey water and water from wastewater treatment facilities for use in irrigation and industrial uses. Saint John is in the midst of sewage systems upgrades associated with Harbour Clean-up and could incorporate infrastructure to encourage these practices.

•

Assess the risks to water reservoirs associated with increased precipitation events. Implement strategies reduce the threat of overloading treatment facilities

•

Educate the public about conservation and water management, encourage practices that help reduce individual water consumption such as; residential rainwater collection for use on lawns and gardens, alternative gardens (e.g. down spout gardens), regular checks for leaks, and new high efficiency washers.

53

Health •

Development or warning systems and flood protections systems to reduce the dangers associated with extreme weather events. Saint John has an Emergency Management Organization that has implemented some programs to date, but a large percentage of the population is not aware of the system and where to get more information.

•

Air pollution reductions measures to reduce increased air quality issues associated with an increase in hot days. Simple responses include traffic restrictions and improving public or alternate transportation systems.

The above adaptation options are by no means a comprehensive list of possible adaptation strategies, but they provide examples of some of the strategies that could help Saint John increase its adaptive capacity and begin to address the impacts of climate change. Adaptation is a complex process and there are numerous challenges to the developing adaption policy, with these three key errors defined by Wilkins (2007); i) under-adaptation – climate impacts are underestimated, ii) over-adaptation – climate change is not a significant factor in the decision resulting in overspending, and iii) maladaptation – climate change is taken into consideration, but the wrong response was chosen. Lessons from cities that have already begun that adaptation process indicate that that researchers and private sector consultants can help drive the adaptation agenda forward, but ultimately local government need create and fund institutional mechanisms for the integration of climate change adaptation into the decision making process to create a successful strategy (Penney and Wiedecki 2007).

Saint John is in the midst of numerous changes and it is well positioned to reduce the economic and social risks associated with climate change further advance itself as a leader in sustainable development.

54

Box 4.1: Examples of Climate Adaptation from other Municipalities (information taken from comprehensive adaptation reports from each city, see Appendix a) King County, US: Land use strategies for global warming preparedness: King County Departments employ coordinated strategies of land use to mitigate and adapt to global warming focusing on the preservation of open space, forests and protection of existing watershed areas.

Floodwater Hazard Management Program: Policy focuses on the protection of watersheds, rivers and coastal areas vulnerable to variable climate, including buying out homes in flood zones and elevating some to minimize risk.

Brightwater Wastewater Treatment Plant: uses reclaimed water for irrigation and industrial uses Boston, US: Relocation of water treatment plant in Boston Harbour to account for sea level rise.

New York, US: Creation of the Office of Long-term Planning and Sustainability tasked with integrating sustainable development and environmental issues into city plan.

Greening the Bronx initiative to reduce the impacts of urban heat island effect.

London, UK: Use of Sustainable drainage systems (SUDS) in new business parks and commercial developments, including the use of permeable pavements, swales and detention ponds.

Full time Officer to develop adaptation strategy that through and integrated process involving city staff and outside agencies.

Vancouver, CAN: Integrated Stormwater Management Plan that will result in no net loss to the environmental quality, by addressing erosion, drainage issues and protect communities from localized flooding.

Recommendations It is now well established that climate change is occurring (IPCC 2001a, IPCC 2007) and this report outlines impacts that Saint John is already experiencing and assesses what the likely impacts will be in the future. Over 80% of the Atlantic coastline has been identified as sensitive to sea level rise and Saint John is located in a moderate to high risk area (Shaw et al. 1998) making it vulnerable to the impacts of sea level rise.

Historical records indicate that Saint John has been experiencing subtle changes in climate, but these trends are expected to increase in the future resulting in significant changes precipitation patterns and more frequent occurrences of high temperatures.

The impacts of climate change, more frequent occurrence of extreme weather events in particular, pose a significant risk to the City of Saint John. Although the initial costs of 55

the adaptation process can seem high, economic studies are indicating that the cost of not preparing will be significantly higher and could lead to millions of dollars in damages (Ruth et al. 2007). Adaptation responses and action plans can seem difficult to implement with the timeframes of impacts seeming distant, often looking at 100 year time scales and beyond, but cities worldwide are recognizing the importance of addressing climate change and beginning the process of adaptation and integrating climate change considerations within to the decision- and policy-making process. Longterm thinking (50-100 years) and common sense in city planning will go a long way to prevent cases of maladaptation and reduce the cityâ&#x20AC;&#x2122;s vulnerability to the impacts of climate change.

This report presents an initial assessment of how vulnerable Saint John is to the impacts of climate change and presents some ideas to increase our adaptive capacity.

This report provides a starting point for a more detailed vulnerability assessment of the city and the development of a comprehensive adaptation strategy. The following presents a simple framework for the adaptation process (Figure 4.3) and some key recommendations for Saint John to begin addressing climate change.

Build Awareness

Engage Stakeholders & City Staff

Assess Climate Trends Vulnerability Assessment Current & Future

Adaptation Options Identification of options and analysis of existing policies

Evaluate and Prioritize

Implement Adaptation Strategy

Monitor and Evaluate

Figure 4.3 â&#x20AC;&#x201C; Simple framework outlining the major steps within the adaptation process.

56

1. Carry out a detailed vulnerability assessment of the City of Saint John. This would involve; i) a thorough assessment of current and future climate trends, some available in this report and more detailed analysis available from Climate Change Division of Environment Canada, Atlantic region, ii) High resolution topographical mapping of the city (e.g. LiDAR) to help conduct detailed flood models and hydrological modeling, iii) Identification of vulnerable areas within the city (as seen in the previous section) and inventory of vulnerable infrastructure, iv) Impact assessment of the key sectors within the city (water resources, flood risks, energy use, health and security, building/development and transport). This involves engaging affected stakeholders, including city officials, city staff, public and private-sector companies, and community members.

2. Integrated policy that combines mitigation and adaptation is the best method to address climate change, where strategies will help reduce risk from climate impacts and reduce greenhouse gas emissions.

3. Climate change concerns must be integrated into the decision making process at all levels and across all departments of the municipal government. Adaptation is a policy agenda that cuts across departmental and sectoral boundaries (Burton 2006) and must be imbedded into the municipal planning process and policy development process.

4. Begin the process now, before a major event. Kirshen et al. (2004) states anticipatory action results in significantly less total adaptation costs than taking no action. The majority of cities that began the adaptation process did so in the wake of an extreme weather event that resulted in serious economic losses.

Saint John has seen an increase in precipitation events resulting in flooding, property damage and increased erosion, but has not had a major event. Saint would save millions of dollars by investing in the adaptation process now and preventing the economic losses seen in other cities (e.g. Halifax, New Orleans, Toronto).

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5. Literature Cited Bigio, Anthony G (2003), “Cities and climate change”, in Alcira Kreimer, Margaret Arnold and Anne Carlin (editors), Building Safer Cities: The Future of Disaster Risk, World Bank, Washington DC, pp. 91–99.

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6. Appendix APPENDIX A Guides and Manuals for Adaptation to Climate Change BEST (Better Environmentally Sound Transportation). Offering innovative programs to reduce greenhouse gas emissions and encourage cycling, walking, public transportation and carpooling. www.best.bc.ca.

Birch Hill Geosolutions. 2007. Climate Change Adaptations for Land use Planners.

Project A1209. http://adaptation.nrcan.gc.ca/projdb/178_e.php. pp. 159.

Burnham, C. 2006. A guide to climate change for small- to medium- sized enterprises.

Canadian Chamber of Commerce and Pollution Probe. pp. 56. www.pollutionprobe.org.

CIRIA (Construction Industry Research and Information Association). SUDS. Sustainable drainage systems: promoting good practice. www.ciria.org/suds/index.html.

Feenstra, J.F., I. Burton, J.B. Smith, and R.S.J. Tol (eds). 1998. Handbook on methods for climate change impacts assessment and adaptation strategies. United Nations Environment Programme. Amsterdam, The Netherlands. 464 pp.

Greater London Authority. 2005. Adapting to climate change: a checklist for development, Guidance on designing developments in a changing climate. Three Regions Climate Change Group. London, UK. 72 pp.

Halifax Regional Municipality. 2007. Climate Change: Developerâ&#x20AC;&#x2122;s risk management guide. Climate SMART. Halifax, NS. 26 pp.

Halifax Regional Municipality. 2006. Community action guide to climate change and emergency preparedness. Climate SMART. Halifax, NS. 23 pp.

MOE (Ontario Ministry of the Environment). 2003. Stormwater Management Planning and Design Manual. www.ene.gov.on.ca/envision/gp/4329eindex.htm.

Perkins, B., D. Ojima, and R. Corell. 2007. A survey of climate change adaptation planning. The Heinz Center. Washington, D.C. 52 pp.

Stewart, P., R. Rutherford, H. Levy, and J. Jackson. 2003. A guide to land use planning in coastal areas of the Maritime provinces. Oceans and Environment Branch. Canadian Technical Report of Fisheries and Aquatic Sciences No. 2443. 177 pp.

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Wulkan, B, S Tilley, and T Droscher. 2003. Natural Approaches to stormwater management: low impact development in Puget Sound. Puget Sound Action Team: Office of the Governor. Olympia, WA. 55 pp.

Coastal and/or Climate Change Policy Examples Coastal Resources Management Council. 1996. The State of Rhode Island Coastal Resources Management Program – As Amended. 270 pp. www.crmc.ri.gov/regulations/programs/redbook.pdf Maine State Planning Office. 2001. Maine Coastal Plan: Assessment and Strategy under Section 309 of the Coastal Zone Management Act. 93 pp. www.maine.gov.spo/mcp/downloads/309_reports/final_309A&S.pdf New Zealand Climate Change Office. 2004. Coastal hazards and climate change; A guidance for local government in New Zealand. Ministry for the Environment.

Wellington, New Zealand. 145 pp.

Nova Scotia Department of Energy. 2007. Climate Change in Nova Scotia; A background paper to guide Nova Scotia’s Climate Action Plan. www.gov.ns.ca/energy/energystrategy/ Health Robichaud, A.G. 2007. Operation White Tide: Evaluating the capacity of the Atlantic coastal communities to adapt to extreme events related to climate change. Natural Resources Canada. http://adaptation.nrcan.gc.ca/projdb/158_e.php Adaptation Resources on the Web ADAM Project (Adaptation and Mitigation Strategies: supporting European climate policy) www.adamproject.eu/ Adaptation Network www.adaptationnetwork.org/ AIACC (Assessments of impacts and adaptations to climate change in multiple regions and sectors) www.aiaccproject.org/ Environmental Protection Agency – Adaptations www.epa.gov/climatechange/effects/adaptation.html Natural Resource Canada – Climate Change Impacts and Adaptation Program http://adaptation.nrcan.gc.ca/index_e.php UK Climate Impacts Programme www.ukcip.org.uk/

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APPENDIX B Table B2 – Current provincial and territorial strategies, initiatives and best practices for addressing impacts and adaptation to climate change.

Alberta

British Columbia

Manitoba

New Brunswick

Newfoundland

Alberta Climate Change Adaptation Team Incorporation of mitigation and adaptation strategies into departmental management plans Research to improve adaptive capacity Provincial vulnerability assessment project (environmental, economic and social) Climate scenarios for the 2020’s, 2050’s and 2080’s (Prairie Adaptation Research Collaborative) Built Green Program Green Cities Initiative Pacific Climate Impacts Consortium Future Forests Ecosystem Initiative (Adapting to climate impacts on forestry) Incorporation of climate risks into park management plans Storm surge modeling and forecasting Report: Indicators of climate for British Columbia Conferences on climate impact and adaptation Government to carbon neutral by 2010 Conferences and workshops on climate change impacts and adaptation Green building policy: all new buildings and major renovation projects by government or other organizations receiving provincial funding must be at least 33% better than the Model National Energy Code for Buildings and be certified LEED Silver or better Green Building Policy Sustainable planning based on climate change adaptation and impacts on the boreal forest and First Nations communities on the east side of Lake Winnipeg Integrated watershed planning/evaluation of best management practices project Expansion of flood management infrastructure to include floodway around capital New Brunswick Climate Change Secretariat and other relevant NB departments Environmental procurement guidelines; sustainable building practices such as LEED; retrofitting of public buildings Promotion of climate change activities by community groups and universities through the Environmental Trust Fund Sea-level rise project Integration of climate change considerations into decision-making processes involving economic, social and environmental considerations High environmental standards for infrastructure projects receiving public funds Incorporation of climate change and sustainable development issues into high school science curriculum 67

Northwest Territories

Nova Scotia

Nunavut Ontario

Prince Edward Island

Quebec

Saskatchewan

Yukon

Development of a land use policy Participation in development of national and local strategies to address long-term impacts of climate change and identify appropriate adaptation initiatives Impact and adaptation plan for the NT City of Yellowknife Adaptation Plan Good Building Practice for Northern Facilities Incorporation of climate change into the primary and secondary curricula Steps to protect infrastructure from increased permafrost problems encountered throughout the NT Canadian Climate Impacts and Adaptation Research Network Adapting to changing climate in Nova Scotia (2004) Study of climate change impacts on the Halifax Harbour ClimAdapt Halifax Climate Sustainable Mitigation and Adaptation Risk Toolkit Canadian Climate Impacts and Adaptation Research Network Nunavut Climate Change Adaptation Plan Climate change projections for Ontario: practical information for policymakers and planners (2007) Climate change and Ontarioâ&#x20AC;&#x2122;s provincial parks: towards an adaptation strategy (2007) Coastal zone management under a changing climate in the Great Lakes Greening government initiative: government-wide use of processes, materials and energy minimize creation of pollutants and waste, and reduce overall risk to human health and the environment Canadian Climate Impacts and Adaptation Research Network Exploration of opportunities to improve capacity for adaptation planning (e.g. hazard mapping) Best practices guide for urban management Ouranos Consortium Interministerial Committee on Climate Change Operating agreement between the Consortium on regional climatology and adaptation to climate change (Ouranos) and its partners Framework for natural hazard prevention Climate Change Saskatchewan Prairie Adaptation Research Collaborative Expansion of provincial watershed planning process to better protect water supplies Northern Climate ExChange Yukon climate change action plan Work with all levels of government on comprehensive adaptive strategies

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About the Author Ian Reeves Ian started his education in Forest Engineering at UNB in Fredericton, NB, but quickly discovered that the only part he liked about Forest Engineering and was the forest. After two years, he transferred to Trent University in Peterborough, ON to pursue a degree in biology with a focus on plant ecology and conservation. Ian graduated in 2003 with a B.Sc Hons. in Biology, following which he took a year off to teach rock climbing, mountain navigation and outdoor education in the Swiss and Austrian Alps before returning to Trent to pursue a Masters in biology in the Watershed Ecosystems Graduate program. He spent the next 2 ½ years hanging from wires 20 metres off the ground studying the regulation of gas exchange in the canopy of a mature Sugar Maple forest. After completing his masters, Ian spent 7 months in South America learning to speak Spanish and working for Global Vision International as an Expedition Scientist and base camp manager, where he spent 4 months living in Lanin National Park, Argentina and working with local ecologists and biologists helping study the impacts of invasive species on Auracaria and Southern Beech forests. Ian spent the last year working for ACAP Saint John as a climate change specialist, researching climate impacts and adaptation, learning about wetland management and community environment work. When not in the office he is likely to be found on the nearest field playing Ultimate or the nearest cliff climbing and he is looking forward to exploring the ocean, mountains and ecology of a new place as he prepares to move to Christchurch, NZ with his wife as she pursues her PhD in Ecology.

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