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The assumption that climate mitigation can only be afforded at a particular level of income is implicit in global climate negotiations. This suggests that middle-income countries may reach a tipping point in their development process where low-carbon investment becomes more viable. In order to avoid dangerous levels of climate change, this tipping point needs to be brought forward in time: upper-middle-income countries are already responsible for 37.8% of global CO 2 emissions. We explore the scope for large-scale investment in climate mitigation in Johor Bahru, a fast-growing industrial city in Malaysia. We find that the city could reduce per capita emissions by 10.0% by 2025, relative to 2014 levels, through cost-effective investments. If the returns could be recovered and reinvested in low-carbon measures, Johor Bahru could reduce per capita emissions by 35.2% by 2025, relative to 2014 levels. This result suggests that the tipping point may be a function of political will and institutional capacity as well as income. This has substantial implications for global climate policy discussions, particularly the opportunities and responsibilities of middle-income countries. If comparable savings can be delivered across cities in middle-income countries, this would equate to a reduction in global emissions of 6.3% with the exploitation of cost-effective options and 11.3% with the exploitation of cost-neutral options. Investing in economically attractive low-carbon measures could also provide cities in middle-income countries with an opportunity to build the political momentum and institutional capacities necessary for deeper decarbonization.

Analyzing population and employment sizes at the local finer geographic scale of transit station areas offers valuable insights for cities in terms of developing better decision-making skills to support transit-oriented development. Commonly, the station area population and employment have been derived from census tract or even block data. Unfortunately, such detailed census data are hardly available and difficult to access in cities of developing countries. To address this problem, this paper explores an alternative technique in remote estimation of population and employment by using building floor space derived from an official administrative geographic information system (GIS) dataset. Based on the assumption that building floor space is a proxy to a number of residents and workers, we investigate to what extent they can be used for estimating the station area population and employment. To assess the model, we employ five station areas with heterogeneous environments in Tokyo as our empirical case study. The estimated population and employment are validated with the actual population and employment as reported in the census. The results indicate that building floor space, together with the city level aggregate information of building morphology, the density coefficient, demographic attributes, and real estate statistics, are able to generate a reasonable estimation.

CASBEE-City tool determines the city's Built Environment Efficiency (BEE) by calculating the improvement of Quality of Life (Q) over human activities' Environmental Load (L) within the city's hypothetical boundary. A total of 58 variables (57 Q indicators and one variable for L) are used in the worldwide version of CASBEE-City which were grounded using ISO 37120:2014 Sustainable Development of Communities and 17 Sustainable Development Goals (SDGs) by the United Nations (UN). This paper examines the application of CASBEE-City for Malaysian cities using the case of Johor Bahru City and identifies assessment indicators which are customised based on the data availability, reliability and suitability through focus group discussions (FGDs) which involved 36 respondents (researchers, urban planners and stakeholders). This paper reveals Johor Bahru with moderate score B+ in 2010 and 2025. Consensus were also achieved from the 36 FGD respondents for the practicability and future potential of CASBEE-City and BEE framework in Johor Bahru.