Urban Residential Sector Research Articles

Disparity and driving forces of energy consumption in China's provincial urban residential sector under the carbon neutrality target

China's escalating urbanization contributes significantly to carbon emissions, necessitating an efficient, equitable decarbonization strategy in the urban residential sector. However, an overview of the regional-inequal implications underlying this sector's carbon-neutral pathways is, to our knowledge, still pending. Here, we employ a province-level bottom-up technology optimization model to evaluate energy consumption implications and driving forces, particularly inter-provincial disparities, under various carbon neutrality pathways. We have observed that regional disparities in energy access are largely determined by different carbon cap allocation strategies. Additionally, energy intensity is the key factor influencing changes in energy consumption in scenarios of carbon neutrality compared to scenarios without carbon policies. Furthermore, energy intensity is linked to regional energy consumption disparities across scenarios, with short-term impacts mainly through energy intensity and long-term impacts through energy structure. The study presents a cost-minimizing, equitable carbon neutrality pathway for China's urban residential sector at the provincial level, highlighting that equitable carbon reduction policies promote provincial energy consumption equity compared to cost-efficient strategies. Additionally, the analysis offers guidance for formulating and implementing equitable energy transition policies.

Exploring the dynamic evolutionary trajectories for urban residential building carbon emissions toward 2060: Evidence from the HSCW zone in China

Revealing the long-term development trajectory and peak scenarios of the urban residential building sector is crucial for formulating targeted emission reduction strategies and contributing to achieving the “Dual carbon” target. Given that, significant variables affecting carbon emissions from urban residential buildings (URBCE) at both macro and end-use building levels are identified in this study. Furthermore, an innovative dynamic simulation model is developed by integrating the Monte Carlo simulation model with the Kaya identity model, taking into account the uncertainties of the variables. Subsequently, the long-term evolution trajectories, potential emission peaks, and peak time of the URBCE close to 2060 in China's hot summer and cold winter (HSCW) zone are simulated. Results indicate that URBCE is expected to reach its peak of 272.43 Mt CO2 in 2040 under the baseline scenario. Through the dynamic simulation, the probable peak time of energy consumption in the HSCW zone is 2044 (±1.85), with a peak of 145.42 (±6.91) Mtce, and the possible peak time of carbon emissions is probably 2039 (±1.60), with a peak of 271.93 (±13.40) Mt CO2. According to dynamic sensitivity analysis, carbon emission factor, per capita residential space, and heating energy intensity can promote the peak size and timing. These findings lay a robust foundation for the formulation of regionally specific carbon reduction targets and initiatives.

A GIS-Based Top-Down Approach to Support Energy Retrofitting for Smart Urban Neighborhoods

Energy and environmental challenges are a major concern across the world and the urban residential building sector, being one of the main stakeholders in energy consumption and greenhouse gas emissions, needs to be more energy efficient and reduce carbon emissions. While it is easier to design net zero energy homes, existing home stocks are a major challenge for energy retrofitting. Two key challenges are determining the extent of retrofitting required, and developing knowledge-based effective policies that can be applied en-masse to housing stocks and neighborhoods. To overcome these challenges, it is essential to gather critical data about qualities of existing buildings including their age, geo-location, construction type, as well as electro-mechanical and occupancy parameters of each dwelling. The objective of this study was to develop a GIS-based model embedded with critical data of residential buildings to facilitate evidence-based retrofit programs for urban neighborhoods. A model based on a bottom-up approach was proposed in which information gathered from all stakeholders was inputted into one database that can be used for decision-making. A geo-located case study to validate a proposed GIS-based residential retrofitting model sample size of 74 residential buildings in the city of Riyadh was statistically analyzed and used. The results indicate behavior-based patterns, with a strong positive correlation (r = 0.606) between the number of occupants and number of household appliances, while regression analysis showed high occupancy rates do not necessarily result in high utility costs at the end of the month, and there is no statistical difference in the average monthly cost of gas between partial and fully occupied houses. Furthermore, neither the type of building, height, age, nor occupancy status play a significant role in the average energy consumed. Additionally, the GIS-based model was validated and found to be effective for energy-use mapping and gathering critical data for analyzing energy consumption patterns at neighborhood scale, making it useful for municipalities to develop effective policies aimed at energy efficient and smart neighborhoods, based on a recommended list of most effective energy-saving retrofit measures.

The estimation of carbon imbalance and driving factors in China's urban residential building sector

Understanding the imbalance of carbon emissions in the urban residential building (URB) sector is beneficial for equitable and effective emission reduction policies. However, carbon imbalance in URB and its major driving factors remain unclear. Therefore, according to the Kaya identity and Zenga index, this study aims to analyze the imbalance in carbon emissions and carbon emission unit area of URB from 2005 to 2019. The results represent the following: 1) Although the overall carbon emission unit area reached its peak value (36.17 kgCO2/m2) in 2011, the overall carbon emission of URB did not reach the peak value, arriving at 0.86 BtCO2 in 2019; 2) the obvious imbalance of carbon emission and carbon emission unit area was led by the population and energy consumption unit area, respectively; 3) Compared to the difference in economy, the difference in climate had a larger impact on inter-group imbalance of carbon emission unit area without heating. In summary, these results and provided policies facilitate future formulation of fair and effective provincial decarbonization responsibility and emission mitigation implementation policies.

Urban domestic electricity consumption in relation to households’ lifestyles and energy behaviours in Burkina Faso: Findings from a large-scale, city-wide household survey

Information on actual domestic electricity use in Burkina Faso, where the urban zones and residential sector account for 74% and 33% respectively of the total electricity use, remains very challenging to find, as little research currently exists. This study aimed therefore, to provide the first ever insights into the actual urban residential electricity use. A survey with 387 households, the first large-scale, city-wide household electricity study undertaken in Burkina Faso to the authors’ knowledge, was conducted in the city of Ouagadougou. Information on the households' characteristics and behaviours were collected to yield a first comprehensive analysis on the actual city-scale domestic electricity use. Findings demonstrated an average electricity use of 2395 kWh/year by households. Cooling accounts for almost 40% of the total domestic electricity use, followed mainly by cooking and food preserving (23%) and information-communication-entertainment (19%) activities. Three groups of consumers were then formed based on their electricity use level, to investigate interactions between electricity use and households’ lifestyles. The study’s findings lay therefore, the foundations for a better understanding of actual urban domestic electricity use patterns and could help to develop more suitable policies and actions targeting energy conservation in the residential sector.

Spatiotemporal patterns and driving mechanism of carbon emissions in China's urban residential building sector

Revealing the regional differences and drivers of provincial urban residential building sector carbon emissions (URBCE) is critical for regional collaborative emission reduction in achieving the “Dural carbon” targets. This study tries to innovatively construct a framework for the exploration of the spatiotemporal patterns and driving mechanism of Chinese URBCE in 30 provinces during 2000–2019, combining kernel density estimation, spatial autocorrelation analysis and temporal-spatial LMDI model. Results indicate that: (1) A vast majority of regions have undergone a sharp growth in URBCE, with the regional gap of URBCE gradually widening. (2) Besides, the spatial pattern of regional URBCE is basically stable, with High-High distributed in the Northeast and North China, and Low-Low concentrated in the Southwest. (3) Urban residential building floor space per capita, population, and urbanization are promotive driving forces, while carbon intensity and energy intensity are increasingly inhibiting. This study can provide policymakers a better understanding of URBCE and help them develop regionally-specific emission reduction strategies. Additionally, it offers fresh perspective on how to research the spatiotemporal disparities of carbon emissions in other sectors and nations, and could be of international significance.

Estimating long-term and short-term CO2 rebound effects of China’s urban residential sector: evidence from a dynamic econometric approach

This study quantifies China’s urban residential CO2 rebound owing to improvements in energy efficiency. We use a dynamic econometric model (error corrected linear approximated almost ideal demand system, ECM-LA-AIDS) to examine the relationship between energy-efficiency promotion, energy consumption behaviour, and the CO2 rebound effect. An improvement in energy efficiency lowers the energy price, resulting in unbalanced short- and long-term energy consumption behaviours. Inconsistent short- and long-term energy-efficiency policies may lead to greater rebound effects. Therefore, this study estimates the residential energy-related CO2 (ECR-CO2) rebound effects considering both short- and long-term consumption patterns to provide targeted policies for controlling residential ECR-CO2. The results indicate that the short- and long-term urban residential ECR-CO2 effects differ across regions and provinces. Additionally, the direct rebound effect contributes more to the total ECR-CO2 rebound effect than the indirect rebound effect. Finally, at the national level, the urban residential ECR-CO2 rebound effects exhibit a U-shaped divergence, indicating that, among the 31 Chinese provinces considered, the ECR-CO2 rebound effect first converges and then diverges, owing to differences in the levels of technological progress.

Comprehensive analysis on the energy resilience performance of urban residential sector in hot-humid area of China under climate change.

Residential sector is one of the main consumers of the energy market. This study conducts a comprehensive analysis on the future energy resilience performance of urban residential sector in hot-humid area of China in the 21st century. Uncertainties, including future climate, building characteristic and occupancy behavior, are considered in future energy projections. Since the local climate is characterized by hot summer and warm winter, and local building energy is cooling-dominated, this study focuses on the changes in future cooling load. The results indicate that future energy demand of residential sector in hot-humid areas will increase over time except under the Shared Socioeconomic Pathway (SSP) 1-2.6, and the magnitude of the rise could be significant. Under the SSP5-8.5, the most severe scenario for climate change, the average annual energy demand of residential sector in the long-term future is about 90 kWh/m2, which is above twice the energy demand under current typical climate. The annual building energy fluctuates more in a hotter future. Energy demands of dwellings with different building forms and use patterns may vary disproportionately in the changing climate. The framework and findings could give implications on future energy system design in cities.

Electric Vehicle Charging Model in the Urban Residential Sector

Electric vehicles (EVs) have become increasingly popular because they are highly efficient and sustainable. However, EVs have intensive electric loads. Their penetrations into the power system pose significant challenges to the operation and control of the power distribution system, such as a voltage drop or transformer overloading. Therefore, grid operators need to prepare for high-level EV penetration into the power system. This study proposes data-driven, parameterized, individual, and aggregated EV charging models to predict EV charging loads in the urban residential sector. Actual EV charging profiles in Saskatchewan, Canada, were analyzed to understand the characteristics of EV charging. A location-based algorithm was developed to identify residential EV charging from raw data. The residential EV charging data were then used to tune the EV charging model parameters, including battery capacity, charging power level, start charging time, daily EV charging energy, and the initial state of charge (SOC). These parameters were modeled by random variables using statistic methods, such as the Burr distribution, the uniform distribution, and the inverse transformation methods. The Monte Carlo method was used for EV charging aggregation. The simulation results show that the proposed models are valid, accurate, and robust. The EV charging models can predict the EV charging loads in various future scenarios, such as different EV numbers, initial SOC, charging levels, and EV types (e.g., electric trucks). The EV charging models can be embedded into load flow studies to evaluate the impact of EV penetration on the power distribution systems, e.g., sustained under voltage, line loss, and transformer overloading. Although the proposed EV charging models are based on Saskatchewan’s situation, the model parameters can be tuned using other actual data so that the proposed model can be widely applied in different cities or countries.

Socioeconomic Determinants of Household Out-of-Pocket Payments on Healthcare in Sri Lanka

Since its independence, Sri Lanka has had a free health care policy, and out-of-pocket healthcare expense has increased over time. The study's primary goal is to investigate the factors influencing out-of-pocket healthcare spending in Sri Lanka. Secondary data from the Household Income and Expenditure Survey conducted by the Department of Census and Statistics in Sri Lanka in 2016 were used in this study. Data were analyzed using descriptive statistics and the Semi-Log regression model. The results of the Semi-Log regression model show that households with the urban residential sector, post-secondary education, and chronic conditions were significant positive predictors of out-of-pocket healthcare expenditure, while households with primary education were substantial negative predictors. Distance to maternity clinics has a strong beneficial influence on healthcare expenditure on the supply side. As a result, the findings demonstrate a compelling need to mitigate the adverse effects of growing healthcare costs. The government can enact new rules and regulations to protect households' ability to meet their healthcare needs by offering all healthcare facilities and expanding health infrastructure.

Return on Investment (ROI) Analysis of OFF-Grid Solar Photovoltaic System in Residential Sector of Pakistan

Pakistan being a developing country is observing a rapid rise in electricity demand and currently the big cities such as Karachi, Quetta, Rawalpindi and Lahore are most severely affected by the recent power crises. Therefore, at this time it is important to explore and investigates the alternate and renewable power sources in the country. This study investigates the significance in terms of economic feasibility of off-grid solar photovoltaic systems in the residential sector of Pakistan. Study area comprises the rural and urban residential sector of all four provinces of Pakistan. The return on investment and project payback periods are calculated using the NEPRA defined electricity tariff inclusive of tax so that a concrete conclusion of investing in off-grid solar could be drawn. Results of this study show that most selected areas in Pakistan have sufficient solar radiation potential for electricity generation. Study finds that solar electricity in Pakistan is one of the cost effective and environmental and social friendly forms of electricity. Payback periods of photovoltaic system in Sindh, Baluchistan, Punjab and KPK have been calculated 3.98, 2.33, 3.99 & 6.78 years, respectively. Results of this study may be useful for collective as well as individual consumers while calculating the economic viability of an off grid solar system.
 Keywords: Photovoltaic System, Solar potential, Electricity, Off-Grid Solar System, Return on investment, economic feasibility, Pakistan.

Carbon emissions in China's urban residential building sector through 2060: A dynamic scenario simulation

Carbon-reduction effect of the urban residential building sector is crucial to the carbon neutrality target. This study aims to explore the interaction mechanism among influencing factors and simulate the future evolutionary trajectories of urban residential building carbon emissions (URBCE). An integrated dynamic emission assessment (IDEA) model is innovatively established by coupling the system dynamics (SD) model and a bottom-up end-use decomposition model. Combining with the scenario analysis approach, this IDEA model is applied in China's urban residential building sector from 2000 to 2060. Results show that under the baseline scenario, the URBCE will fail to peak before 2030 but will peak at 1.19 Bt CO2 in 2037. In comparison, it will peak at 0.79 Bt CO2 in 2025 and decline to 0.17 Bt CO2 in 2060 under carbon-neutral scenario, which can be neutralized by negative carbon technologies. Different end-uses and climate zones show marked discrepancies in emission-reduction potential, with the contribution of heating and appliances being over 50%. Sensitivity analyses shows that the low-carbon awareness, electrification rate, proportion of clean energy generation and technological progress contribute positively to the early peak of URBCE. This study provides a deeper understanding of China's potential peaking paths and can assist policy-makers in better evaluating emission paths for other nations and regions.

Urban residential energy switching in China between 1980 and 2014 prevents 2.2 million premature deaths

Urban residential energy switching in China between 1980 and 2014 prevents 2.2 million premature deaths

Dynamic scenario simulations of carbon emission peak in China's city-scale urban residential building sector through 2050

Understanding future trajectory of urban residential building carbon emissions (URBCE) is essential to seeking effective carbon-abatement pathways to combat climate change. However, future evolutionary trajectory, possible emission peaks and peaking times in this sector are still unclear. This study innovatively develops an integrated dynamic simulation model by embedding a bottom-up building end-use energy model into the system dynamics model. Based on this, scenario analysis approach is combined with Monte Carlo simulation method to explore the possible emission peaks and peaking times considering the uncertainties of impact factors. We apply the integrated SD-LEAP model to Chongqing, a typical city in China's hot-summer and cold-winter zone. Results show that URBCE will probably peak at 22.8 (±8.0) Mt CO2 in 2042 (±3.4)—well beyond China's 2030 target. Different building end-uses present substantial disparities. The contribution of combined heating and cooling to URBCE mitigation will be over 60% between business-as-usual and low-carbon scenarios. Dynamic sensitivity analysis reveals that per capita gross domestic product, carbon emission factor, and residential floor space per capita can boost emission peaks and peaking time. This study can not only boost the theory and model development for carbon emission prediction, but also assist governments to set effective carbon-reduction targets and policies.

Urban Residential Energy Demand and Rebound Effect in China: A Stochastic Energy Demand Frontier Approach

The energy rebound effect is a potential threat to energy-saving targets based on energy efficiency improvements. This paper employs a stochastic energy demand frontier model to analyze the energy demand and rebound effect in China’s urban residential sector. Using a panel data set of 30 Chinese provincial-level regions over the period 2001-2014, for the first time, we investigate the degrees and determinants of China’s urban residential energy demand and energy rebound effect.The results show that residents’ income level, energy price, temperature deviation, population scale, household size, and district heating system are significant influencing factors of residential energy consumption. Regarding the energy rebound effect, we find that energy price is negatively correlated with the rebound effect, and an inverted U-shaped relationship between residents’ income level and rebound-effect size exists. The magnitude of the rebound effect varies across regions, with an average of 65.4%. The main policy implication generated by this study is that it should be in urgent need of energy pricing reform to mitigate the rebound effect in China.

Deep decarbonization pathways in the building sector: China’s NDC and the Paris agreement

China’s economic growth has been largely relying on the consumption of coal. The country has realized that its economic development has to be free from dependence on fossil fuels. On 30 June 2015, China submitted its ‘Nationally Determined Contribution (NDC)’ in preparation for the Conference of Parties 21 (COP21). One of the important actions in China’s NDC is to lower carbon dioxide (CO2) emissions per unit of GDP by 60% to 65% from 2005 levels by 2030. This study examines the efforts from China’s building sector (i.e. urban residential, rural residential and service) in achieving the CO2 reduction target stated in China’s NDC. Furthermore, this study also explores the post-NDC era and looks into the opportunities towards deep decarbonization in the building sector by mid-century for contributing to the Paris agreement. The study covers 31 provincial regions of mainland China anddisparities of climate and socioeconomic indicators across regions are fully considered. We use a bottom-up cost optimization model called AIM/Enduse to evaluate the CO2 reduction potential brought by efficient technologies in China’s building sector. Five scenarios are designed to illustrate the emission pathways through 2050. The results show that, when energy constraint and emission target is introduced in mitigation scenarios, new generation biomass contribute a lot to emission reduction. Reduction potential in the nearly zero emission scenario is mainly from the urban residential sector, and to achieve deep decarbonization by 2050, it is important to bring a significant reduction of per-capita energy consumption in addition to ci improvement both in urban and rural households. Co-benefit analysis suggests that air pollutants can also be significantly reduced by deep decarbonization policies.

Nonlinear influence of urbanization on China's urban residential building carbon emissions: New evidence from panel threshold model

Carbon mitigation in the urban residential building sector is critical for China to achieve its carbon peak and carbon neutral commitment. However, how urbanization affects urban residential building carbon emissions is still unclear. This study adopts the panel threshold regression model to explore the dynamic influence mechanism of the urbanization on urban residential building CO2 emissions based on the evidence from China's 30 provincial regions during 2000–2015. Results indicate that urbanization contributes positively to the increase of urban residential building CO2 emissions, while such degree of influence varies across different stages of income and energy structure. As for per capita income, the promoting effect of the urbanization on urban residential building CO2 emissions is enhanced with the growth of per capita income. And the degree of such increasing effect becomes greater when per capita income exceeds its threshold value. Regarding the energy mix, the driving effect of urbanization on urban residential building CO2 emissions is also strengthened when the energy mix crosses its threshold value, showing a “stepwise growth” feature. This study reveals the nonlinear influence mechanism of urbanization on urban building CO2 emissions, and this is helpful in boosting the related theoretical and practical exploration on the impact of urbanization on the environment. Based on our findings, an environmentally-friendly consumption pattern should be promoted and more penetration of cleaner energies should be improved in urban households, which will be effective to alleviate the increase of residential carbon emissions.

Will the urbanization process influence the peak of carbon emissions in the building sector? A dynamic scenario simulation

The accelerating urbanization has posed great challenges to China’s carbon-mitigation efforts and global climate change response. However, how does the urbanization process impact the peak of future carbon emissions from buildings is still unclear. This study first establishes a comprehensive urbanization framework from three dimensions. Then, a dynamic scenario simulation model is innovatively constructed by combining the extended Kaya identity and Monte Carlo simulation approach to explore future dynamic evolution trajectory, possible peaks and peaking time of China’s building carbon emissions from 2000 to 2050, considering the uncertainties of factors. Finally, dynamic sensitivity analysis is performed to investigate the contributions of different dimensions of the urbanization. Results show that under the business-as-usual scenario, the rural residential building sector will be the first to reach its energy peak in 2027. Dynamic scenario simulation shows that the building sector will peak at 3.09 (±0.36) Bt CO2 in 2037 (±4). Specifically, the urban residential building sector will peak at 1.27 (±0.18) Bt CO2 in 2040 (±4), while the rural residential building sector will peak at 0.51 (±0.03) Bt CO2 in 2021 (±4) and the commercial building sector will peak in 2038 (±4) at 1.41 (±0.30) Bt CO2. Dynamic sensitivity analysis indicates that rural–urban migration will exert promoting effect on the peaking time and emission peaks of building carbon emissions through the concomitant effects of the urbanization process, i.e., the economic urbanization and space urbanization. Overall, this study can provide a better insight into the impact of urbanization on carbon emission peak and can support governments and decision-makers to formulate effective carbon-mitigation strategies.

Modeling the willingness to pay for energy efficient residence in urban residential sector in China

Abstract: Whether and how to share the incremental cost of energy efficient residence compared with common buildings between housing developers and buyers is an urgent problem to be solved in promoting energy efficient residence. This study estimates urban residents' willingness to pay (WTP) for energy efficient residence in Beijing and Changchun in China to provide important reference for this issue. The revised norm-motivated consumer choice model is used to identify the key factors in the two decision-making stages of determining WTP. Based on survey data and using probit and interval regression models, it shows that energy-saving revenue and incremental cost are the key factors affecting whether or not to buy energy efficient residence, and the preference for positive personal image only has a significant positive effect in Beijing. The mean and median WTP of Beijing residents are about 340 Yuan and 405 Yuan per square meter, respectively, whereas those of Changchun residents are about 350 Yuan per square meter. Policies targeting the energy saving and incremental cost of energy efficient residence and tailored to local residents' preferences can stimulate the promotion of energy efficient residence effectively.

Evaluation of energy-related household carbon footprints in metropolitan areas of Japan

In the Post-Paris Era, urban emissions have received worldwide attention as cities are considered to be responsible for most of the world’s environmental footprint. A better understanding of urban CO2 emissions and their related carbon footprints offers benefits to policymakers interested in promoting effective and efficient low-carbon solutions. In particular, a clear determination of direct and indirect emissions inventories (that is, identification of emissions related to specific sources) can provide a valuable baseline for the planning, assessing, implementing, and monitoring of urban mitigation actions. Focusing on the Japanese urban residential sector, this paper uses an established urban database and emission database based on global-related input-output analysis to systematically analyze household carbon footprints related to energy demand, targeting both direct and indirect energy-related CO2 emissions in Japan’s megacities. The results reveal the city-specific emissions status of Japan’s three major metropolitan areas, showing, for example, that Tokyo is a source of high direct emissions, while Utsunomiya is a significant source of indirect emissions. The study also tentatively concludes that the depopulation of cities can result in higher per capital emissions, both direct and indirect, as they relate to energy demand. Improved sector and spatially explicit information for better mitigation policymaking and environmental education at the urban level is presented. Valuable insights are offered through an in-depth investigation of the relationship between CO2 emissions and urban socioeconomic activities, benefitting future low-carbon city research and practice.