@ The University of Oklahoma

Author: Chenghao Wang Page 1 of 3

New paper on urban irrigation published in Nature Communications

Our new paper, “The potential of urban irrigation for counteracting carbon-climate feedback“, is published in Nature Communications (IF: 16.6).

The paper and its supplement can be downloaded at https://www.nature.com/articles/s41467-024-46826-3.

Authors: Peiyuan Li, Zhi-Hua Wang, and Chenghao Wang

Abstract: Global climate changes, especially the rise of global mean temperature due to the increased carbon dioxide (CO2) concentration, can, in turn, result in higher anthropogenic and biogenic greenhouse gas emissions. This potentially leads to a positive loop of climate–carbon feedback in the Earth’s climate system, which calls for sustainable environmental strategies that can mitigate both heat and carbon emissions, such as urban greening. In this study, we investigate the impact of urban irrigation over green spaces on ambient temperatures and CO2 exchange across major cities in the contiguous United States. Our modeling results indicate that the carbon release from urban ecosystem respiration is reduced by evaporative cooling in humid climate, but promoted in arid/semi-arid regions due to increased soil moisture. The irrigation-induced environmental co-benefit in heat and carbon mitigation is, in general, positively correlated with urban greening fraction and has the potential to help counteract climate–carbon feedback in the built environment.

DOI: https://doi.org/10.1038/s41467-024-46826-3

Fig. 2: Governing mechanisms on carbon exchange of urban greenery. a A diagram showing carbon exchange of plants in the built environment with UHI, higher background CO2 concentration, and management (irrigation). b Irrigation-induced change of urban gross primary productivity (dGPPu), led by decrease of air temperature and increase of soil water content. c Irrigation-induced change of urban ecosystem respiration (dRu), led by decrease of soil temperature and increase of soil water content. d Irrigation-induced change of urban net ecosystem exchange (dNEEu), resulting from the combinations of dGPPu and dRu. e Urban ecosystem respiration as a function of soil temperature and soil water content. The light gray lines in b–d show all possible combinations lead to various types of outcomes. The black solid lines indicate pathway to the strong co-benefit effect. The red dashed lines indicate the pathway to the strong tradeoff effect. Circles in (e) indicate the average Ru before (hollow) and after (solid) irrigation. Arrows indicate the direction of change.

New paper on the cooling dynamics of urban vegetation published in Remote Sensing of Environment

Our new paper, “Enhanced observations from an optimized soil-canopy-photosynthesis and energy flux model revealed evapotranspiration-shading cooling dynamics of urban vegetation during extreme heat“, is published in Remote Sensing of Environment (IF: 13.5).

The paper and its supplement can be downloaded at https://www.sciencedirect.com/science/article/pii/S0034425724001093. The Share Link to download a copy is https://authors.elsevier.com/c/1ikad7qzT3Dj5 (valid through Apr 30, 2024).

Authors: Zhaowu Yu, Jiaqi Chen, Jike Chen, Wenfeng Zhan, Chenghao Wang, Wenjuan Ma, Xihan Yao, Siqi Zhou, Kai Zhu, and Ranhao Sun

Abstract: Previous studies on the cooling of urban vegetation mainly focused on its transpiration or shading effect separately, neglecting to explore the combined evapotranspiration-shading cooling. Further, accurate quantification of evapotranspiration-shading cooling remains challenging due to heterogeneity of urban landscapes, which limits understanding of its high-resolution spatiotemporal patterns. Here, we integrate high-precision remote sensing data and the Soil-Canopy-Observations of Photosynthesis and Energy Fluxes (SCOPE) model to propose an optimized quantitative approach. The approach was used to investigate changes in evapotranspiration-shade cooling during extreme heat. Taking Shanghai metropolitan as case, the results show: (1) The cooling capacity of urban vegetation in nighttime (18:00–6:00) is enhanced during extreme heat, which is attributed to accumulated effect of shading and enhanced evapotranspiration due to elevated vapor-pressure deficit. (2) In densely built-up areas with limited vegetation, there is a significant lack of thermal regulation, especially in the early morning (7:00) and late evening (17:00), thus exacerbating thermal stress. (3) At midday (11:00–13:00) there was a slight decrease in evaporative cooling, probably caused by the behaviour of the stomatal closure at high temperatures. Concurrently, high radiation causes the shading effect of vegetation to become more prominent, amplifying the cooling contrast between areas with dense and sparse vegetation cover. Moreover, the study also highlights that grassland with >50% cover can provide cooling effects similar to that of forest land. Overall, our study not only enhances the understanding of urban vegetation’s cooling effects but also underscores the importance of strategic urban vegetation planning in mitigating urban heat, particularly under the escalating frequency and intensity of heat waves.

DOI: https://doi.org/10.1016/j.rse.2024.114098

Fig. 5. Distribution patterns of urban vegetation evapotranspiration-induced cooling at typical moments of the daily cycle during heat waves in Shanghai.

New paper on urban causal interactions under heat waves published in npj Urban Sustainability

Our new paper, “Megacities are causal pacemakers of extreme heatwaves“, is published in npj Urban Sustainability.

The paper and its supporting information can be downloaded at https://www.nature.com/articles/s42949-024-00148-x.

Authors: Xueli Yang, Zhi-Hua Wang, Chenghao Wang, and Ying-Cheng Lai

Abstract: Global climate change has been shown to cause longer, more intense, and frequent heatwaves, of which anthropogenic stressors concentrated in urban areas are a critical contributor. In this study, we investigate the causal interactions during heatwaves across 520 urban sites in the U.S. combining complex network and causal analysis. The presence of regional mediators is manifest in the constructed causal networks, together with long-range teleconnections. More importantly, megacities, such as New York City and Chicago, are causally connected with most of other cities and mediate the structure of urban networks during heatwaves. We also identified a significantly positive correlation between the causality strength and the total populations in megacities. These findings corroborate the contribution of human activities e.g., anthropogenic emissions of greenhouse gases or waste heat, to urban heatwaves. The emergence of teleconnections and supernodes are informative for the prediction and adaptation to heatwaves under global climate change.

DOI: https://doi.org/10.1038/s42949-024-00148-x

Fig. 6. Comparison of causality (outdegree) with two population metrics for 53 large U.S. cities with a population over 200,000 during the 2020 heatwave event (July 18-22). a, b For population totals, and c, d are for population density. The top panel shows comparison maps of the causal outdegree (triangular markers) and population metrics: population totals in a and population density in c, with sizes represented by gray shaded circles. The bottom panel represents the log-log correlation between the causal outdegree and population metrics: population totals in b and population density in d and causality, with sizes represented by colored circles.

New paper on extreme fire weather published in Scientific Reports

Our new paper, “Extreme fire weather in Chile driven by climate change and El Niño–Southern Oscillation (ENSO)“, is published in Scientific Reports (IF: 4.6).

The paper and its supporting information can be downloaded at https://www.nature.com/articles/s41598-024-52481-x.

Authors: Raúl R. Cordero, Sarah Feron, Alessandro Damiani, Jorge Carrasco, Cyrus Karas, Chenghao Wang, Clarisse T. Kraamwinkel, and Anne Beaulieu

Abstract: A string of fierce fires broke out in Chile in the austral summer 2023, just six years after the record-breaking 2017 fire season. Favored by extreme weather conditions, fire activity has dramatically risen in recent years in this Andean country. A total of 1.7 million ha. burned during the last decade, tripling figures of the prior decade. Six of the seven most destructive fire seasons on record occurred since 2014. Here, we analyze the progression during the last two decades of the weather conditions associated with increased fire risk in Central Chile (30°–39° S). Fire weather conditions (including high temperatures, low humidity, dryness, and strong winds) increase the potential for wildfires, once ignited, to rapidly spread. We show that the concurrence of El Niño and climate-fueled droughts and heatwaves boost the local fire risk and have decisively contributed to the intense fire activity recently seen in Central Chile. Our results also suggest that the tropical eastern Pacific Ocean variability modulates the seasonal fire weather in the country, driving in turn the interannual fire activity. The signature of the warm anomalies in the Niño 1 + 2 region (0°–10° S, 90° W–80° W) is apparent on the burned area records seen in Central Chile in 2017 and 2023.

DOI: https://doi.org/10.1038/s41598-024-52481-x

Fig. 1. A severe drought worsened by persistent heatwaves fueled fierce fires in February 2023 in Central Chile. (a) Precipitation for February 2023 relative to the 1981–2010 mean. The dry February 2023 came on top of the megadrought that has affected central Chile since 2008. (b) Air temperature for February 2023 relative to the 1981–2010 mean. February 2023 was the warmest on record in Central Chile. (c) Fire Weather Index (FWI) for February 2023 relative to the 1981–2010 mean. Extreme anomalies were registered in the regions severely affected by fires. (d) False-color image acquired on 3 February 2023 by the Operational Land Imager (OLI) on Landsat 8 showing the burn scar of Santa Juana Fire, in the BioBio Region, 100 km southeast of Concepcion, the second most populated city in the country.

Dr. Wang was awarded a single-PI NSF grant

Dr. Wang was recently awarded a single-PI National Science Foundation (NSF) grant. The grant titled “An Integrated Urban Meteorological and Building Stock Modeling Framework to Enhance City-level Building Energy Use Predictions” began on Jan 1, 2024 and is expected to conclude on Dec 31, 2025.

See OU News here: https://www.ou.edu/research-norman/news-events/2024/two-ou-researchers-receive-nsf-epscor-research-fellowships.

New paper on urban waste production published in Nature Cities

Our new paper, “Worldwide scaling of waste generation in urban systems“, is published in Nature Cities.

The paper and its supporting information can be downloaded at https://www.nature.com/articles/s44284-023-00021-5. Data collected and compiled in this study are available in the figshare repository: https://doi.org/10.6084/m9.figshare.19361675.

Authors: Mingzhen Lu, Chuanbin Zhou, Chenghao Wang, Robert B. Jackson, Christopher P. Kempes

Abstract: The production of waste as a consequence of human activities is one of the most fundamental challenges facing our society and global ecological systems. Waste generation is rapidly increasing, with corresponding shifts in the structure of our societies, where almost all nations are moving from rural agrarian societies to urban and technological ones. However, the connections between these societal shifts and waste generation have not yet been described. In this study we applied scaling theory to establish a new understanding of waste in urban systems and identified universal scaling laws of waste generation across diverse urban systems worldwide for three forms of waste: wastewater, municipal solid waste, and greenhouse gases. We found that wastewater generation scales superlinearly, municipal solid waste scales linearly, and greenhouse gas emissions scale sublinearly with city size. In specific cases, production can be understood in terms of city size coupled with financial and natural resources. For example, wastewater generation can be understood in terms of the increased economic activity of larger cities, and the deviations from the scaling relationship, indicating relative efficiency, depend on gross domestic product per person and local rainfall. The temporal evolution of these scaling relationships reveals a loss of economies of scale and a general increase in waste production, where sublinear scaling relationships become linear. Our findings suggest general mechanisms controlling waste generation across diverse cities and global urban systems. Our approach offers a systematic framework to uncover these underlying mechanisms that might be key to reducing waste and pursuing a more sustainable future.

DOI: https://doi.org/10.1038/s44284-023-00021-5

Fig. 1. Scaling law of waste production across cities worldwide. a, Geolocation of the cities included in this study from three distinct data sources. MoHURD, Ministry of Housing and Urban Rural Development (China). The map was generated using R with the ‘ggplot2’ package. b, Wastewater production scales superlinearly with the size of cities (β = 1.15 ± 0.04, n = 675). We highlight two example cities (black circles) that stand out with a large deviation from the scaling law. Dongguan, an industrial city of southern China that features high personal wealth and high annual precipitation, generates disproportionately more wastewater than expected given its size. In contrast, the northwestern city of Tianshui, which features much lower personal wealth and rainfall, generates much less wastewater than expected given its size. c, MSW production scales linearly with city size (β = 1.04 ± 0.05, n = 292). We highlight Seattle (United States) and Lilongwe (Malawi) as two cities that deviate from the general scaling relationship. The much richer Seattle produces eight times more municipal waste than Lilongwe, even though it has a smaller population. d, The emission of GHGs displays sublinear scaling across cities worldwide (β = 0.85 ± 0.1, n = 296). We highlight Rotterdam (the Netherlands) and Bandung (Indonesia) as two cities that deviate from the general scaling relationship, with Rotterdam producing disproportionately more GHGs. The purpose of highlighting certain high- and low-residual cities is to give concrete examples so that readers can relate to the abstract data points presented here (no subjective judgements are made here). The dark gray error bands in bd represent the CIs of each scaling relationship.

Open Ph.D. positions at the SURF Lab (2024 Fall admission) – updated

The Sustainable URban Futures (SURF) Lab in the School of Meteorology and the Department of Geography and Environmental Sustainability at the University of Oklahoma in Norman, Oklahoma, USA is seeking multiple doctoral students who are willing to pursue research in one of the following areas. The expected start date is Aug 2024 (Fall admission).

1. Urban Air Pollution Modeling Position

The SURF Lab is seeking a PhD student to develop and apply an integrated high-resolution pollutant dispersion model over complex terrain (including urban environments), which will be evaluated with field observations. The successful candidate will enroll in the Ph.D. program in Meteorology. For prospective Ph.D. students, a master’s degree in atmospheric science, meteorology, engineering, Earth science, or environmental science is preferred. Candidates with the following experience/expertise are especially encouraged to apply: (1) previous research experience in air pollution modeling, (2) proficiency in programming languages (Matlab, Fortran, R, and/or Python), and/or (3) familiar with geographic information systems.

2. Building Energy Modeling Position

The SURF Lab is seeking a PhD student to work on numerical simulations of building energy use and associated carbon emissions in the urban environment. The successful candidate will enroll in the Ph.D. program in Meteorology or Geography and Environmental Sustainability. For prospective Ph.D. students, a master’s degree in engineering, geography, atmospheric science, meteorology, or Earth science is preferred but not required. Candidates with the following experience/expertise are especially encouraged to apply: (1) previous research experience in developing building energy model(s), and (2) proficiency in programming languages (MATLAB, Fortran, R, and/or Python).

3. Urban Climate Modeling and Analytics Position

The SURF Lab is seeking a PhD student to work on multiscale urban climate models and data analytics. The successful candidate will enroll in the Ph.D. program in Meteorology or Geography and Environmental Sustainability. For prospective Ph.D. students, a master’s degree in atmospheric science, meteorology, geography, engineering, Earth science, or environmental science is preferred but not required. Candidates with experience in using programming languages (e.g., Matlab, Python, R, and/or Fortran), reanalysis data, climate projections, and/or remotely sensed data are especially encouraged to apply.

Successful candidates will work with Dr. Chenghao Wang at the University of Oklahoma. With the strong modeling and/or data analysis skills developed during the training, successful candidates will have the opportunity to work in an interdisciplinary research team and study a wide range of urban issues and challenges as well as potential mitigation and adaptation measures on the path toward sustainable and resilient urban environments.

If you are interested, please contact Dr. Chenghao Wang (chenghao.wang@ou.edu) by Nov 25, 2023 (Fall 2024 admission), and attach (1) a copy of your CV, (2) a brief statement that highlights your interest (and skills and previous research experience when applicable) relevant to the position description, and (3) a copy of unofficial academic transcripts and TOEFL/IELTS/PET/DET transcripts (when applicable). Review of applications will begin immediately and continue until the position is filled.

Admission requirements:

About the SURF Lab:

The Sustainable URban Futures Lab at the University of Oklahoma examines the mechanisms of urban environments, their interactions with regional and global climates, and their impacts on building energy use, carbon emissions, and public health using numerical models and data analytics. Through our interdisciplinary research, we aim to advance the understanding of the urban environment and support more sustainable urban development under global environmental changes. Our research has been funded by multiple agencies including the U.S. Department of Energy (DOE), National Science Foundation (NSF), National Oceanic and Atmospheric Administration (NOAA), National Aeronautics and Space Administration (NASA), and the U.S. Environmental Protection Agency (EPA). Our work has been published in several leading journals such as Nature Aging, Nature Communications, Science Advances, Geophysical Research Letters, Remote Sensing of Environment, Earth’s Future, Building and Environment, and Renewable and Sustainable Energy Reviews. More information about ongoing research can be found here: https://sites.create.ou.edu/chenghaowang/.

About the University of Oklahoma:

Founded in 1890, the University of Oklahoma is a public research university located in Norman, Oklahoma just 20 minutes south of Oklahoma City, one of the top 50 metropolitan areas in the United States. The university is classified among “R1: Doctoral Universities – Very high research activity”. The School of Meteorology is the largest such program in the nation and is routinely ranked near the top of the nation. More information regarding the University of Oklahoma, the School of Meteorology, the Department of Geography and Environmental Sustainability, and available degree programs can be found here: https://sites.create.ou.edu/chenghaowang/about/.

For further information, please contact Dr. Chenghao Wang (chenghao.wang@ou.edu).

A PDF version of this post in English can be downloaded here:


New paper on N2O emissions from urban wastewater-influenced estuaries published in Communications Earth & Environment

Our new paper, “Wastewater-influenced estuaries are characterized by disproportionately high nitrous oxide emissions but overestimated IPCC emission factor“, is published in Communications Earth & Environment (IF: 7.9).

The paper and its supporting information can be downloaded at https://www.nature.com/articles/s43247-023-01051-6. Data collected and compiled in this study are available in the figshare repository: https://doi.org/10.6084/m9.figshare.24129774.

Authors: Yue Dong, Jia Liu, Xiang Cheng, Fuqiang Fan, Wei Lin, Chunyang Zhou, Shengrui Wang, Shangbin Xiao, Chenghao Wang, Yu Li, and Changlin Li

Abstract: Estuaries play an important role in the global nitrous oxide budget. However, considerable uncertainties exist in estimating their nitrous oxide emissions, largely due to anthropogenic impacts, particularly wastewater discharge. Here we investigate nitrous oxide emission dynamics in the Pearl River Estuary through advanced high-resolution, real-time measurements. Results suggest that Pearl River Estuary is a strong nitrous oxide emission source (1.05 Gg yr−1; range: 0.92–1.23 Gg yr−1) with pronounced spatial heterogeneity. Wastewater discharge substantially impacts emissions by introducing abundant nutrients, altering carbon-to-nitrogen stoichiometry, and stimulating biochemical processes. A meta-analysis further reveals the widespread enhancement of nitrous oxide emission induced by wastewater nitrogen input in global estuaries, with nitrous oxide emission factors considerably lower than that suggested by the IPCC owing to progressive biological saturation. Consequently, refining emission factor estimates through comprehensive bottom-up studies is imperative to improve the understanding of estuarine contributions to the global nitrous oxide budget.

DOI: https://doi.org/10.1038/s43247-023-01051-6

Fig. 2. Spatial distribution of N2O concentrations, saturations, and air–water fluxes in the Pearl River Estuary. a Dissolved N2O concentrations. b N2O saturations. c N2O fluxes. Spatial distributions were interpolated from high-resolution, real-time data using Kriging interpolation. The yellow box in (a) indicates the N2O concentration hotspot to the northwest of Inner Lingding Island.

New paper on urban land surface model intercomparison published in Quarterly Journal of the Royal Meteorological Society

Our new paper, “Evaluation of 30 urban land surface models in the Urban-PLUMBER project: Phase 1 results“, is published in Quarterly Journal of the Royal Meteorological Society (IF: 8.9).

This paper is one of the outcomes of the second international urban land surface model intercomparison project. The paper and its supporting information can be downloaded at https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/qj.4589.

Authors: Lipson, M. J., Grimmond, S., Best, M., Abramowitz, G., Coutts, A., Tapper, N., Baik, J.-J., Beyers, M., Blunn, L., Boussetta, S., Bou-Zeid, E., De Kauwe, M. G., de Munck, C., Demuzere, M., Fatichi, S., Fortuniak, K., Han, B.-S., Hendry, M., Kikegawa, Y., Kondo, H., Lee, D.-I., Lee, S.-H., Lemonsu, A., Machado, T., Manoli, G., Martilli, A., Masson, V., McNorton, J., Meili, N., Meyer, D., Nice, K. A., Oleson, K. W., Park, S.-B., Roth, M., Schoetter, R., Simón-Moral, A., Steeneveld, G.-J., Sun, T., Takane, Y., Thatcher, M., Tsiringakis, A., Varentsov, M., Wang, C., Wang, Z.-H., & Pitman, A.

Abstract: Accurately predicting weather and climate in cities is critical for safeguarding human health and strengthening urban resilience. Multimodel evaluations can lead to model improvements; however, there have been no major intercomparisons of urban-focussed land surface models in over a decade. Here, in Phase 1 of the Urban-PLUMBER project, we evaluate the ability of 30 land surface models to simulate surface energy fluxes critical to atmospheric meteorological and air quality simulations. We establish minimum and upper performance expectations for participating models using simple information-limited models as benchmarks. Compared with the last major model intercomparison at the same site, we find broad improvement in the current cohort’s predictions of short-wave radiation, sensible and latent heat fluxes, but little or no improvement in long-wave radiation and momentum fluxes. Models with a simple urban representation (e.g., ‘slab’ schemes) generally perform well, particularly when combined with sophisticated hydrological/vegetation models. Some mid-complexity models (e.g., ‘canyon’ schemes) also perform well, indicating efforts to integrate vegetation and hydrology processes have paid dividends. The most complex models that resolve three-dimensional interactions between buildings in general did not perform as well as other categories. However, these models also tended to have the simplest representations of hydrology and vegetation. Models without any urban representation (i.e., vegetation-only land surface models) performed poorly for latent heat fluxes, and reasonably for other energy fluxes at this suburban site. Our analysis identified widespread human errors in initial submissions that substantially affected model performances. Although significant efforts are applied to correct these errors, we conclude that human factors are likely to influence results in this (or any) model intercomparison, particularly where participating scientists have varying experience and first languages. These initial results are for one suburban site, and future phases of Urban-PLUMBER will evaluate models across 20 sites in different urban and regional climate zones.

DOI: https://doi.org/10.1002/qj.4589

Fig. 1. Model schematics of the main built, hydrological and behavioural attributes for participating models. Here models are categorised into five cohorts (left column) based on the geometric representation of buildings, with built, hydrological and behavioural attributes used to refine a ‘total complexity’ (Figure 2). Block array, statistical distribution and building-resolved models are grouped together into a ‘complex’ cohort in later analysis.

New paper on urban building energy use published in Nature Communications

Our new paper, “Impacts of climate change, population growth, and power sector decarbonization on urban building energy use“, is published in Nature Communications (IF: 16.6).

The paper and its supplement can be downloaded at https://www.nature.com/articles/s41467-023-41458-5.

Authors: Chenghao Wang, Jiyun Song, Dachuan Shi, Janet L. Reyna, Henry Horsey, Sarah Feron, Yuyu Zhou, Zutao Ouyang, Ying Li, and Robert B. Jackson

Abstract: Climate, technologies, and socio-economic changes will influence future building energy use in cities. However, current low-resolution regional and state-level analyses are insufficient to reliably assist city-level decision-making. Here we estimate mid-century hourly building energy consumption in 277 U.S. urban areas using a bottom-up approach. The projected future climate change results in heterogeneous changes in energy use intensity (EUI) among urban areas, particularly under higher warming scenarios, with on average 10.1–37.7% increases in the frequency of peak building electricity EUI but over 110% increases in some cities. For each 1 °C of warming, the mean city-scale space-conditioning EUI experiences an average increase/decrease of ~14%/ ~ 10% for space cooling/heating. Heterogeneous city-scale building source energy use changes are primarily driven by population and power sector changes, on average ranging from –9% to 40% with consistent south–north gradients under different scenarios. Across the scenarios considered here, the changes in city-scale building source energy use, when averaged over all urban areas, are as follows: –2.5% to –2.0% due to climate change, 7.3% to 52.2% due to population growth, and –17.1% to –8.9% due to power sector decarbonization. Our findings underscore the necessity of considering intercity heterogeneity when developing sustainable and resilient urban energy systems.

DOI: https://doi.org/10.1038/s41467-023-41458-5

Fig. 1. a SSP1-2.6 scenario. b SSP2-4.5 scenario. c SSP3-7.0 scenario. d SSP5-8.5 scenario. Each point represents the relative change (%) based on the ensemble mean of the simulations driven by 10 CMIP6 models under each SSPX-Y scenario.

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