Urban population increased progressively in the past century, with merely 13% in 1900 to 29% in 1950. Projections indicated that global urban population would rise to 70% (~6.3 million) by 2050, doubling the number in 20101. Urbanization creates not purely convenience of living and better access to healthcare, it conversely brings about a series of social and environmental issues2. The influences of urbanization on the environment are multifaceted and complex, including air/water pollution, ecosystem, climate, etc., and are felt at various scales3,4,5,6,7. Urban areas produce nearly 80% of carbon emissions and substantial amounts of air pollutants8, contributing significantly to regional/global climate change and posing great threats to public health9,10. Different surface properties make cities warmer than surrounding areas, and such thermal gradients create urban heat island (UHI)11,12 that aggravates heat stress faced by urban residents13,14.

Urbanization is a product of economic growth, and actions are thus needed to mitigate its adverse impacts and achieve sustainable development. Urban warming, as a key player to worsen UHI, is mainly contributed by increased anthropogenic heat that is released from booming urban residents and enlarged use of cement and asphalt15,16. Mitigation measures to lessen the negative impacts of urban warming have been taken around the world17,18,19,20,21. Cool roof and green roof strategies are the most widely evaluated measures and have been officially adopted in a number of megacities over past decades22,23. Cool roofs are designed with high-albedo materials to reflect more sunlight back to space and thus absorb less heat than standard roofs24, while green roofs adopt vegetation evapotranspiration to cool the built environment25. Both cool and green roofs have been demonstrated effectively to reduce near-surface air temperature (by 1–5 °C)26,27,28,29,30 and cut the energy consumption (by 10–50%)31,32,33,34,35,36 of air conditioning use.

Coupled with potently mitigating UHI and reducing carbon emissions, cool and green roof strategies also change ground-level air quality. They are likely to weaken thermal forcing of land surface to the atmosphere to suppress vertical mixing and dispersion of air pollutants or to affect temperature/radiation-dependent chemical processes37. It was reported previously that the applications of cool roofs in Southern California led to a slight rise in PM2.5 concentration38,39. The influence of cool roofs on O3 formation varies with time and space. Some studies reported enhanced O3 concentration by cool roofs due to more reflected solar ultraviolet38,40, while others presented beneficial effects of reduced temperature and thus declined rates of O3 formation30,41,42. In addition to inhibiting turbulent mixing43, green roofs add more green space in the city, which creates conditions that favor dispersion and deposition of particles44,45,46,47,48. A monitoring experiment confirmed that concentrations of PM2.5 above green roof were reduced by up to 14.1% compared with those over bare roof49.

Although the frequency of extreme haze episodes has declined50 after the implementation of the Action Plan for Prevention and Control of Air Pollution in 2013, haze events with relatively lower concentrations of PM2.5 still occur occasionally in recent years51. Aerosol–radiation feedbacks (ARF) cut the amount of downward shortwave radiation (SWD) reaching the ground, reduce the sensible heat flux, and lowers the height of the planet boundary layer (PBLH)27,52, which act to aggravate severity of haze events in China53,54,55,56. The influences of ARF vary with multiple factors, including aerosol concentration57,58, optical properties59,60,61, surface albedo, etc. Adoptions of cool roofs and green roofs alter transmission of radiation and modify micro-environment of dispersion and deposition, complicating the effects on air quality. Insights on this topic are of great significance, as cool and green roof strategies are anticipated to play a growingly important role in mitigating side effects of urbanization.

In this study, we consider roof strategies and associated radiative transfer and urban hydrological processes in a coupled meteorology-chemistry model, with a focus on exploring their effects on wintertime PM2.5 pollution in North China. The study period was selected to cover different stages of a winter haze event and the clean days before the event to represent diverse pollution levels, which offers scenarios that could take place in the near future under air pollution control. We find that the effects of roof strategies are regulated by pollution severity and our results offer useful implications on implementation of roof strategies in China.


Enhanced wintertime PM2.5 pollution by adoption of cool and green roofs in North China

Model configurations in this study follow Gao et al.54, and extensive model evaluations by using surface observations of meteorological variables and air pollutants, atmospheric sounding products, surface aerosol optical depth (AOD) measurements, and satellite AOD, with respect to temporal, spatial, and vertical distributions of aerosols, indicated reliable representation for the 2010 haze event by WRF-Chem. We evaluate the simulation of surface air pollutants (see Supplementary Fig. 1), and the results are consistent with those in Gao et al.54. Scattering aerosols dominate, particularly in rural and suburban regions. The mean column integrated single scattering albedo (SSA) at 550 nm suggest that SSA values are relatively lower (<0.835) over urban areas, which is associated with high levels of BC from residential sector in the urban. High SSA over northern areas and southeastern coastal areas are associated with dust and sea salt aerosol, respectively. Figure 1 illustrates resulting changes in near-ground PM2.5 concentration and air temperature due to adoptions of cool roofs and green roofs. As the diurnal variations of the influences of roof strategies are significant only during daytime (Supplementary Fig. 3), we present only daytime results here. Higher albedo of cool roofs tends to aggravate PM2.5 pollution during the day in urban areas, with maximum enhancement up to 50 μg m−3 (Fig. 1a). When surface albedo increases, reduced surface shortwave net radiation weakens surface thermal forcing to the atmosphere (Fig. 1c) and inhibits vertical development of convective boundary layer62, leading to an increase in PM2.5 concentration. Consistent findings were reported by refs. 38,39 for widespread adoption of cool roofs in southern California. Although albedo does not change in simulation cases of green roofs from actual cases, we observe still an increase of 10–20 μg m−3 in PM2.5 concentrations in Beijing due to employment of green roofs (see Fig. 1b) because the weak evapotranspiration slightly inhibits the vertical mixing.

Fig. 1: Spatial features of difference in daytime PM2.5 concentration and 2 m air temperature.
figure 1

Difference in daytime (9:00–17:00 LST) a, b near-ground PM2.5 concentration and c, d 2 m air temperature from 14 to 20 January 2010. Green circles represent the locations of urban grids. The impacts of cool roofs are indicated by differences between CR_AF and ACT_AF, while the influences of green roofs are denoted with differences between GR_AF and ACT_AF.

The effects of roof strategies on PM2.5 pollution and the association with pollution severity

Figure 2a suggests that daily variations of changes in PM2.5 induced by employment of cool roofs exhibit a negative relationship with pollution severity. On a clean day (15 January), CR results in largest increase in PM2.5 concentration (~21 μg m−3, 42%). On light pollution days (14 and 16 January), CR results in the moderate increase in PM2.5 (~33 μg m−3, 34% and ~40 μg m−3, 26%). However, a negligible (only ~16 μg m−3, 5%) enhancement is found on severe pollution day (19 January). As PM2.5 pollution worsens in urban regions, CR-induced increases in PM2.5 concentration are likely to be diminished. Compared with the influences of CR, GR-induced changes of PM2.5 concentrations are generally less than 10 μg m−3 and display unremarkable association with pollution levels.

Fig. 2: Trend and variation of PM2.5 concentration and related meteorological variables.
figure 2

Difference in daytime (9:00–17:00 LST) a near-ground PM2.5 concentration and meteorological variables: b 2 m air temperature (T2m), c sensible heat (SH), d latent heat (LH) and e planet boundary layer height (PBLH) between CR_AF and ACT_AF, GR_AF and ACT_AF. The left y axis of Fig. 2a represents solid lines in the figure; the right y axis represents dashed lines.

Cool roofs directly reduce SWD transferred into land surface and thus modify the development of planet boundary layer (PBL) to affect formation and dispersion of PM2.5. Under clear sky conditions, aerosol–radiation interactions affect the amount of SWD reaching land surface56,60. On light pollution days, weaker aerosol–radiation interactions under low aerosol loading produce more SWD at land surface, compared to that on severe pollution day (see Supplementary Fig. 4). Under this circumstance, increased surface albedo due to CR causes larger reductions in SWD transferred into land surface and produces greater changes in surface thermal forcing and PBLH (Fig. 2c, e). The resulting changes in micro-environment and decreases in ventilation can reduce dry deposition of particles39. We notice that the largest decease of dry deposition velocity (Vd) occurs on the light pollution day (2.5 mm s−1, 16 January, Supplementary Fig. 5).

To eliminate the uncertainty raised by cloud/fog on the severe pollution day (Supplementary Fig. 4), cloud/fog-induced and aerosol-induced reductions of SWD were compared, and we consider 16 January as a reference for cloud/fog-free. From 16 to 19 January, SWD reaching the land surface is reduced by 174 W m−2, with combined influences of cloud/fog and aerosol. When aerosol–radiation interaction is not considered, SWD is reduced by 95 W m−2 by cloud/fog, suggesting that aerosol accounts for reductions of 79 W m−2, more than three times of total declines from 16 to 18 January (~23 W m−2). We thus believe that CR induced increase in PM2.5 is suppressed with deterioration of aerosol pollution.

The effects of green roofs on urban meteorology and PM2.5 pollution are mainly through ambient temperature, constituents of green roof structure and the vegetation properties on the rooftop63. As shown in Fig. 2d, evapotranspiration plays a negligible role due to low air temperature (−10 to 5 ° C) in winter, and maximum decrease of temperature was accordingly only 0.5–1 K (Fig. 2b). We even observe a slight increase in air temperature after sunrise and before sunset due to release of heat storage (Fig. 2b). Under this circumstance, much smaller decreases of PBLH and increases in near-ground PM2.5 concentration are found as the influence of cool roofs. Besides, the treatments of green roofs in our model do not include the changes in deposition processes of particles64,65 due to adoptions of green roofs, which is likely to compete with the effects of evapotranspiration cooling. Our offline calculation of Vd (see Supplementary Fig. 5) reveals different characteristics on clean days and pollution days. On clean days, the positive values of Vd (GR_AF minus ACT_AF) indicate that green roofs increase dry deposition due to the absorption by plants (concluded from differences in red dashed lines between Supplementary Fig. 5a, b) which is probably caused by higher SWD. While on pollution days, the results indicate that green roofs tend to reduce dry deposition of particles as a result of unfavorable ventilation, while absorption of particles by evergreen needleleaf plants in North China compensate the reduction, although negligibly (differences between Supplementary Fig. 5a, b).

Impacts of adoptions of cool and green roofs on ARF

Figure 3 displays ARF-induced changes in near-ground PM2.5 concentration of cool and green roofs, compared with actual conditions. Because the low PM2.5 concentration resulting in rare changes on ARF on first two days (not shown), we only show the conditions on following four days. ARF results in consistent increases in near-ground PM2.5 concentrations for both ACT and CR conditions (see Supplementary Fig. 6a, b). However, the effects of ARF are inhibited in CR, with decreases of 5–20 μg m−3 compared to those for ACT in urban areas. This is because the weaker boundary layer process for the CR suppresses the effects of ARF on PBLH. On the other hand, minimal differences in ARF-induced PM2.5 concentration are found for GR, which is also shown in the temporal variation of ARF-induced changes in PM2.5 (Fig. 3d). It is worth noting that cool roofs reduce ARF-induced enhancements of PM2.5 pollution on heavy (17–18 January) and severe pollution (19 January) days, but increase those on light pollution (16 January) day.

Fig. 3: Spatial and temporal differences in ARF-induced PM2.5 concentration.
figure 3

Difference in daytime (9:00–17:00 LST) mean near-ground PM2.5 concentration a between CR_ARF and ACT_ARF, b between GR_ARF and ACT_ARF; temporal variation of daytime c near-ground PM2.5 concentration and d ARF-induced difference.

On light pollution day (16 January), ARF-induced reductions in SWD inferred from ACT, CR, and GR cases are comparable (24%, Fig. 4a). When grid-average albedo of urban areas increases from 0.18 to 0.5 due to implementation of cool roofs, the reductions of PBLH rise from 26% to 41%, leading to larger increase in near-ground PM2.5 concentration (Fig. 3d). On heavy pollution days (17–18 January), ARF-induced reductions in SWD are still similar for the three cases (29–30%, Fig. 4a), while ARF-induced changes in PBLH are not notably different (42–46%, Fig. 4a). On heavy pollution days (17–18 January), PBLH exhibits lower values (<200 m) for CR, and vertical mixing occurs mainly at a low altitude, compared with the ACT case (Fig. 4). Lower turbulent diffusivity coefficient (Km) for the CR case (Supplementary Fig. 7) suppresses the effects of ARF on Km (Fig. 4c). As a result, 4% greater ARF-induced reductions in PBLH do not cause greater changes in near-ground PM2.5 concentration (Fig. 3d). The situation changes on severe pollution day (19 January), when SWD transferring through the atmosphere is largely reduced by extremely high aerosol loading. The increased aerosol loading also strengthens the re-reflection of the upward shortwave from the land surface. Cool roofs reflect more SWD, resulting in more re-reflected shortwave radiation back to the land surface on severe pollution day. This is the main reason why the SWD reaching the land surface reduces less in CR on 19 January (60%, Fig. 4a). Similar to the conditions on heavy pollution days, PBL exhibits even lower values on severe pollution day (Fig. 4c). Under these influences, the ARF-induced reduction on PBLH is weakened (39%), inhibiting the impacts of ARF on accumulation of near-ground PM2.5 in CR (Fig. 3d). Green roofs exert an impact on ARF only on 19th January when PM2.5 pollution is heaviest. Temperature is the main factor in the influence of green roofs, and ARF causes largest decrease in air temperature when the PM2.5 concentration reaches the peak. As a result, we observe notable influence of green roofs on the severe pollution (Fig. 3d).

Fig. 4: Variation of aerosol–radiation–PBLH interaction on different pollution days.
figure 4

a Difference in daytime (9:00–17:00 LST) SW and PBLH in percentage terms ((AF-NAF)/NAF × 100%). Turbulent diffusivity coefficient of b ACT_ARF, c CR_ARF and d GR_ARF. The Black lines in b, c, and d represent PBLH.


With numerical simulations, we assessed how cool and green roof strategies would affect winter PM2.5 pollution in North China and ARF processes. The mechanisms were illuminated with analyses of surface energy balance, structure of PBL, and ARF (see Fig. 5). We find that adoptions of cool roofs tend to aggravate PM2.5 pollution, while the negative effects are likely to be diminished when pollution worsens. In winter, green roofs cause less enhancements of PM2.5 pollution as a result of inhibited evapotranspiration. Besides, cool roofs produce larger effects on ARF in lightly polluted regions, while weaker in heavily polluted regions. We demonstrate that the effects of roof strategies are regulated by pollution severity and our results offer useful implications on implementation of roof strategies in China. Under clean and lightly polluted conditions, green roofs are more beneficial to air quality. For regions suitable for growth of broadleaf plants, absorption of particles by green roofs would further suppress the side effects of green roofs on air quality.

Fig. 5: A conceptual figure of pollution severity-regulated effects of roof strategies on winter PM2.5.
figure 5

The conceptual scheme displays interactions between surface energy balance, structure of PBL, ARF, and aerosol concentrations after the applications of cool roofs and green roofs at different pollution levels at daytime. a Green roof under light pollution. b Actual roof under light pollution. c Cool roof under light pollution. d Green roof under severe pollution. e Actual roof under severe pollution. f Cool roof under severe pollution. Orange arrows represent downward solar radiation and that reflected by the surface. Yellow dashed arrows are the reflected and scattered solar radiation by aerosols. Red wavy arrows show the upward forcing of the surface. White dashed lines are the PBLH. White circled arrows represent the turbulent mixing in the PBL. The various shades of background colors mean the different pollution levels.

Cool roofs and green roofs were officially prescribed to be installed in a number of megacities, including Tokyo in Japan66, Chicago and Los Angeles in the United States22,38 and Toronto in Canada67. China is lagging behind68, and the environmental impacts need more and careful and thoughtful explorations. In cities where aerosol pollution has been successfully controlled69, applications of cool roof and green roof strategies may not cause serious consequence. For example, Epstein, et al.38 found an annual average PM2.5 increase of 0.19 ± 0.007 μg m−3. Zhang et al.39 indicated that cool roofs increased daily average PM2.5 concentration by 0.85 μg m−3 in Southern California in summer. In spite of that, cool roofs’ effects related to ultraviolet reflection by different materials may aggravate O3 pollution38,39,42,43. China’s aerosol pollution has been reduced in recent years, and our examination suggests that daily average increase in PM2.5 concentration due to CR in a haze event can be up to 25 μg m−3. Under light pollution and clean scenario with a relatively lower concentration, the enhancement percentage can be even larger, which is anticipated to occur frequently nowadays. Thus, installing cool roofs might not be a good measure in China, given the current pollution severity level. Green roofs with suppressed evapotranspiration and thus weaker penalty on winter PM2.5 pollution seem to be better choices, especially for regions suitable for growth of broadleaf plants70.

We explore in this study the impacts of adopting roof strategies on air quality and ARF from the perspective of surface energy balance, yet the influences of potential resultant reductions on air conditioning and associated emissions are not included. Besides, GR can serve as urban sources of biogenic volatile organic compounds, which might affect ozone pollution and secondary organic aerosol formation. More efforts are thus needed in the future to include these factors to better understand how roof strategies affect air quality. Further studies focusing on more regions and longer time periods are also valuable for better design of urban heat mitigation measures.


WRF-Chem model configuration

The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.6.1 was employed to simulate dynamic evolution of air pollutants and their interactions with weather71. Three domains were configured with two-way nesting, and grid resolutions of 81 km, 27 km and 9 km were selected, respectively. The innermost domain covers the entire areas of Beijing and Tianjin, and most regions of Hebei province (see Supplementary Fig. 8). We introduced the Moderate Resolution Imaging Spectroradiometer land cover data in 2010 into simulations to better capture the spatial distribution of different land use types (Supplementary Fig. 8). The 6-h National Centers of Environmental Prediction Final Analysis was used as meteorological initial and boundary conditions. We used the monthly 2010 Multi-resolution Emission Inventory for China (MEIC 2010) offered at 0.25° × 0.25° grids as anthropogenic emissions72, and online calculated biogenic emissions by the Model of Emissions of Gases and Aerosols from Nature73. As biomass burning was not significant in North China during study period54, we did not include emissions of open biomass burning.

Gas phase and aerosol chemistry were modeled with the Carbon-Bond Mechanism version Z74 and the 8-bin version of Model for Simulating Aerosol Interactions and Chemistry75 that includes aqueous chemistry and volatility basis set secondary organic aerosol. Lin cloud microphysics76 and Grell 3D Ensemble Scheme77 were employed to simulate aerosol-cloud interactions and precipitation. RRTM78 and Goddard79 schemes were used to calculate sub-grid long-wave and short-wave radiation, respectively. Yonsei University planetary boundary layer parameterization80 was used to simulate boundary layer processes, and we made modifications to output turbulent diffusion coefficient (Km). Land-atmosphere exchange was simulated using Noah land surface model81. Specifically, land-atmosphere exchange in urban grids were calculated by the Urban Canopy Model (UCM)82, which considers the three-dimensional structure of city and calculates energy balance on the surface of roof, wall and street. The UCM model is a single layer model which has a simplified urban geometry. In UCM, an urban grid will be partitioned into two parts: an impervious fraction and a vegetated fraction, and surface temperature and heat flux of an urban grid cell is an area-averaged temperature and heat flux based on their fractions. The impervious part is further partitioned into two artificial facets in horizontal direction: roof and street, and each has its individual parameters including albedo, emissivity, heat capacity, etc. This enables changing related parameters of the roof to design scenarios for cool roof simulations83. We also coupled the module of urban hydrological processes that treats the effects of green roofs to the WRF-Chem model version 3.6.1 as it was officially added after the version of 3.765. It was only employed to calculate the hydrological processes in urban grids of green roofs in the simulation of green roof cases. The evapotranspiration in the model is affected by solar radiation, vapor pressure deficit, air temperature, and soil moisture84. To address the issue of underpredicting sulfate, we added also heterogeneous reactions, following Gao et al.85. Besides, a photosynthesis-transpiration scheme (GEM) was employed offline to estimate dry deposition velocity (Vd) of air pollutants86. The dry deposition velocity algorithm comprises aerodynamic resistance, laminar boundary-layer resistance and canopy resistance70,87,88.

Experimental design

We designed three sets of simulations, namely ACT, CR, and GR, to explore the impacts cool and green roofs on ARF and formation of air pollution. The simulation period was from 11 to 20 January 2010 with first three days set up as spin-up time. The first day of the studying period is a light pollution day (14 January), followed by one clean day but with relatively high concentrations (15 January), one light pollution day (16 January), two heavy pollution days (17 and 18 January) and one severe pollution day (19 January). The studying period covered all stages that evolved from clean to severe condition of haze pollution in winter. ACT cases were performed with actual albedo, while CR/GR cases represent the situations with cool/green roofs installed extensively in urban regions. For each set of simulation, aerosol-radiation feedbacks were turned on (AF) and off (NAF). Detailed descriptions of these simulations are shown in Table 1. In ACT and GR cases, the roof albedos were set as default value of 0.2 in UCM. While in CR cases, we set albedo to 0.9 to maximize the impacts of cool roofs on climate and subsequent response in the air pollutants, following Zhang et al.89. The albedo of the innermost domain can be seen in Supplementary Fig. 9. The GR cases assumed that the roofs cover 50% of each urban grid and 80% of the roofs in urban areas are vegetation-covered roofs, following Yang et al.65 and He et al.90.

Table 1 Descriptions of model simulations.