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Think globally, act locally: adoption of climate action plans in California

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Abstract

California has been a global leader in reducing greenhouse gas (GHG) emissions. The state has set an ambitious goal of reducing GHG to 1990 levels by 2020 and 80% below 1990 levels by 2050. The statewide goal cannot be accomplished without the support of local stakeholders. We analyzed over 150 city climate action plans (CAPs) in California and examined their reduction goals. We hypothesized five sets of factors that can explain whether a jurisdiction adopts a plan or not, and what kind of target it sets. We find that size of the city, political ideology, and institutional capacity are related to a higher chance of adopting a climate action plan, while political ideology and air quality explain the extent of aspiration of targets. We also find evidence of policy diffusion where neighbors are more likely to adopt plans. Our findings identify gaps in the CAPs within the state and address what lessons can be learned from the Californian experience of local climate policy adoption and goal-setting.

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Notes

  1. See the 2030 Agenda for Sustainable Development (https://sustainabledevelopment.un.org/post2015/transformingourworld) and the COP21 Paris Agreement (https://unfccc.int/sites/default/files/english_paris_agreement.pdf)

  2. See Center for Climate and Energy Solutions: https://www.c2es.org/document/climate-action-plans/

  3. See California Institute for Local Government: http://www.ca-ilg.org/climate-action-plans

  4. See Center for Climate and Energy Solutions: https://www.c2es.org/document/climate-action-plans/

  5. See California Institute for Local Government: http://www.ca-ilg.org/climate-action-plans

  6. Toolkit can be found here: https://www.arb.ca.gov/cc/localaction/localgovstrat.htm

  7. It is important to highlight that CAPs are just one type of official target dealing with GHG emissions. There are other planning documents, local ordinances that jurisdictions have adopted to address GHG emissions. See, for example, http://opr.ca.gov/docs/California_Jurisdictions_Addressing_Climate_Change_PDF.pdf

  8. See League of California Cities, as at 1 July 2011: http://www.cacities.org/Resources/Learn-About-Cities

  9. See California Governor’s Office of Planning and Research: http://opr.ca.gov/docs/California_Jurisdictions_Addressing_Climate_Change_PDF.pdf

  10. Ibid.

  11. See C40 Unlocking Climate Action in Megacities: https://www.c40.org/researches/unlocking-climate-action-in-megacities

  12. https://igs.berkeley.edu/library/california-local-government-documents (accessed September 30, 2017)

  13. https://data2.nhgis.org/main (accessed September 30, 2017)

  14. https://bythenumbers.sco.ca.gov/City-Other-Data/City-Consolidated-Statement/e4s3-uwib/data (accessed May 30, 2018)

  15. https://www.sos.ca.gov/elections/report-registration/ (accessed September 30, 2017)

  16. https://oehha.ca.gov/calenviroscreen/report/calenviroscreen-30 (accessed May 30, 2018)

  17. There is a concern that perhaps these variables are highly correlated and multicolinearity may explain why none of the air quality coefficients are statistically significant at 0.05 level. We have experimented with various specification of the model and inclusion of variables and yet arrived at the same conclusion. We also tried re-specifying our models without the variable, EnviroScreen 3.0 score and only retained the air pollution indicators (ozone, PM 2.5, diesel PM) in our models. We arrived at the same conclusion: the EnviroScreen score was not statistically significant at 0.05 level.

  18. In addition, based on the recommendation of our journal reviewer, we located a dataset from CAL FIRE which lists the cities for which CAL FIRE has made recommendations on very high fire hazard severity zones. (http://www.fire.ca.gov/fire_prevention/fire_prevention_wildland_zones_maps_citylist). We added this variable to our models but it is not statistically significant at 0.05 level. That is, there is no linkage between potential fire hazard and adoption of CAP. The result is shown in Online Appendix Table A1.

  19. We created our neighbor adjacency matrix with k-nearest neighbors, where k was set to 4.

  20. See California Air Resources Board 2018 Greenhouse Gas Emissions

    Inventory: https://www.arb.ca.gov/cc/inventory/data/data.htm

  21. For example, coastal jurisdictions are encouraged to develop separate plans to address the rising sea level problems. http://www.opc.ca.gov/planning-for-sea-level-rise-database/

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Correspondence to Iris Hui.

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Hui, I., Smith, G. & Kimmel, C. Think globally, act locally: adoption of climate action plans in California. Climatic Change 155, 489–509 (2019). https://doi.org/10.1007/s10584-019-02505-7

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